Winter Storm Uri, one of the coldest in decades, brought snow and ice to Texas along with record subfreezing temperatures for 5 days February 13-17, 2021, and was followed by Winter Storm Viola, which brought more of the same February 18-19, 2021. Millions of Texans lost electricity and clean, running water for several days, which some suggest was due in part to a state-regulated energy market. Many Texas schools shut down for the entire week, as the death toll rose from these storms due to hypothermia and exposure, carbon monoxide poisoning, fire, drowning, and poor road conditions. Not only were COVID-19 vaccinations halted due to impassable roads but also Texas hospitals struggled to provide electricity and water pressure needed to perform life-saving medical treatments for their patients. The purpose of this article is to provide an overview of the historic winter storm event, identify vulnerable populations and key public health policies, and highlight the potential environmental public health risks associated with the storms.
The purpose of this Consensus Statement is to provide a global, collaborative, representative and inclusive vision for educating an interprofessional healthcare workforce that can deliver sustainable healthcare and promote planetary health. It is intended to inform national and global accreditation standards, planning and action at the institutional level as well as highlight the role of individuals in transforming health professions education. Many countries have agreed to ‘rapid, far-reaching and unprecedented changes’ to reduce greenhouse gas emissions by 45% within 10 years and achieve carbon neutrality by 2050, including in healthcare. Currently, however, health professions graduates are not prepared for their roles in achieving these changes. Thus, to reduce emissions and meet the 2030 Sustainable Development Goals (SDGs), health professions education must equip undergraduates, and those already qualified, with the knowledge, skills, values, competence and confidence they need to sustainably promote the health, human rights and well-being of current and future generations, while protecting the health of the planet.The current imperative for action on environmental issues such as climate change requires health professionals to mobilize politically as they have before, becoming strong advocates for major environmental, social and economic change. A truly ethical relationship with people and the planet that we inhabit so precariously, and to guarantee a future for the generations which follow, demands nothing less of all health professionals.This Consensus Statement outlines the changes required in health professions education, approaches to achieve these changes and a timeline for action linked to the internationally agreed SDGs. It represents the collective vision of health professionals, educators and students from various health professions, geographic locations and cultures. ‘Consensus’ implies broad agreement amongst all individuals engaged in discussion on a specific issue, which in this instance, is agreement by all signatories of this Statement developed under the auspices of the Association for Medical Education in Europe (AMEE).To ensure a shared understanding and to accurately convey information, we outline key terms in a glossary which accompanies this Consensus Statement (Supplementary Appendix 1). We acknowledge, however, that terms evolve and that different terms resonate variably depending on factors such as setting and audience. We define education for sustainable healthcare as the process of equipping current and future health professionals with the knowledge, values, confidence and capacity to provide environmentally sustainable services through health professions education. We define a health professional as a person who has gained a professional qualification for work in the health system, whether in healthcare delivery, public health or a management or supporting role and education as ‘the system comprising structures, curricula, faculty and activities contributing to a learning process’. This Statement is relevant to the full continuum of training – from undergraduate to postgraduate and continuing professional development.
BACKGROUND: Hurricanes are the immediate ways that people experience climate impacts in the Caribbean. These events affect socio-ecological systems and lead to major disruptions in the healthcare system, having effects on health outcomes. In September 2017, Puerto Rico (PR) and the United States Virgin Islands (USVI) experienced one of the most catastrophic hurricane seasons in recent history (Hurricane Irma was a Category 5 and Hurricane Mar?¡a was a Category 4 when they hit PR). OBJECTIVE: This study examines environmental stressors experienced by women with gynecologic (GYN) cancers from PR and USVI who received oncologic cancer care in PR, in the aftermath of the hurricanes. METHODS: A descriptive qualitative study design was used to obtain rich information for understanding the context, barriers, knowledge, perspectives, risks, vulnerabilities, and attitudes associated to these hurricanes. We performed focus groups among GYN cancer patients (n = 24) and key-informant interviews (n = 21) among health-care providers and administrators. Interviews were conducted from December 2018-April 2019. RESULTS: Environmental health stressors such as lack of water, heat and uncomfortable temperatures, air pollution (air quality), noise pollution, mosquitos, and rats ranked in the top concerns among cancer patients and key-informants. CONCLUSIONS: These findings are relevant to cancer patients, decision-makers, and health providers facing extreme events and disasters in the Caribbean. Identifying environmental secondary stressors and the most relevant cascading effects is useful for decision-makers so that they may address and mitigate the effects of hurricanes on public health and cancer care.
OBJECTIVE: Community characteristics, such as collective efficacy, a measure of community strength, can affect behavioral responses following disasters. We measured collective efficacy 1 month before multiple hurricanes in 2005, and assessed its association to preparedness 9 months following the hurricane season. METHODS: Participants were 631 Florida Department of Health workers who responded to multiple hurricanes in 2004 and 2005. They completed questionnaires that were distributed electronically approximately 1 month before (6.2005-T1) and 9 months after (6.2006-T2) several storms over the 2005 hurricane season. Collective efficacy, preparedness behaviors, and socio-demographics were assessed at T1, and preparedness behaviors and hurricane-related characteristics (injury, community-related damage) were assessed at T2. Participant ages ranged from 21-72 (M(SD) = 48.50 (10.15)), and the majority were female (78%). RESULTS: In linear regression models, univariate analyses indicated that being older (B = 0.01, SE = 0.003, P < 0.001), White (B = 0.22, SE = 0.08, P < 0.01), and married (B = 0.05, SE = 0.02, p < 0.001) was associated with preparedness following the 2005 hurricanes. Multivariate analyses, adjusting for socio-demographics, preparedness (T1), and hurricane-related characteristics (T2), found that higher collective efficacy (T1) was associated with preparedness after the hurricanes (B = 0.10, SE = 0.03, P < 0.01; and B = 0.47, SE = 0.04, P < 0.001 respectively). CONCLUSION: Programs enhancing collective efficacy may be a significant part of prevention practices and promote preparedness efforts before disasters.
BACKGROUND: It is widely believed that during the Great Depression (1929-1933) there was a rise in suicidal rates which was causally related to the increase in unemployment. There are no studies on the effect the Great Depression had on homicidal rates METHODS: The data concerning suicide, homicide, economic and climatic variables for the years 1900-1940 for the whole of the US were gathered from the US Center for Disease Control, the Maddison Project, the National Bureau of Economic Research and the National Climatic Data Center. Time Series Analysis was performed. RESULTS: The results are inconclusive on the role of economic factors but preclude any role of climate on suicidal rates during the years 1900-1940 in the US. Suicidal rates might have a 24-years periodicity, however much longer time series are needed to confirm this. On the contrary they strongly suggest an effect of higher temperatures on homicidal rates after 1922. CONCLUSIONS: The results of the current study suggest a direct and clear effect of climate (higher temperatures) on the increasing homicidal rates in the US after 1922 but failed to establish a causal relationship between suicide rates and economic or climate variables. These should be considered together with increasing concerns on the possible effect of climate change on mental health.
With accelerating climate change, US coastal communities are experiencing increased flood risk intensity, resulting from accelerated sea level rise and stronger storms. These conditions place pressure on municipalities and local residents to consider a range of new disaster risk reduction programs, climate resilience initiatives, and in some cases transformative adaptation strategies (e.g., managed retreat and relocation from highly vulnerable, low-elevation locations). Researchers have increasingly understood that these climate risks and adaptation actions have significant impacts on the quality of life, well-being, and mental health of urban coastal residents. We explore these relationships and define conditions under which adaptation practices will affect communities and residents. Specifically, we assess climate and environmental stressors, community change, and well-being by utilizing the growing climate change literature and the parallel social science literature on risk and hazards, environmental psychology, and urban geography work, heretofore not widely integrated into work on climate adaptation.
Age differences in posttraumatic stress disorder (PTSD) are widely researched, but findings remain inconclusive. The mixed findings may in part result from sampling participants exposed to different trauma types at different times. Here, we controlled for this issue by sampling participants exposed to the same devastating hurricane. A total of 1.5 months after Hurricane Florence (T1), we asked 174 adults living in two severely affected states to describe their hurricane experience and fill in measures of PTSD and event centrality. Then, 7 months after the hurricane (T2), participants were reinvited to the survey, and 98 filled in the same questionnaire. The hurricane descriptions were coded for level of exposure severity. When controlling for trauma characteristics, including level of severity, younger age significantly predicted PTSD at T1 but not T2. When also controlling for event centrality, younger age predicted PTSD at both measurement times. Moreover, from T1 to T2, young adults significantly increased how severely they described their hurricane experience to be, whereas such amplification was absent in the older age groups. Overall, the findings provide some evidence that younger age increase vulnerability for PTSD and increase the perception of trauma severity over time.
Construction workers are at a high risk of exposure to excessive heat generated by several factors such as intensive physical activities, personal protective clothing, and frequent heat events at construction sites. Previous studies attempted to evaluate the occupational risk of heat stress by concentrating on environmental variables or the self-assessment measures of perceived heat. Despite their potentials, most of these approaches were intrusive, inaccurate, and intermittent. More importantly, they mainly overlooked the disparities in workers’ physical and physiological characteristics. To address these limitations, this study proposes a heat-stress risk-assessment process to evaluate workers’ bodily responses to heat – heat strain – based on the continuous measurement of their physiological signals. To this end, workers’ physiological signals were captured using a wristband-type biosensor. Subsequently, their physiological signals were decontaminated from noises, resampled into an array of informative features, and finally interpreted into distinct states of individuals’ heat strain by employing several supervised learning algorithms. To examine the performance of the proposed process, physiological signals were collected from 18 subjects while performing specific construction tasks under three predetermined environmental conditions with a different probability of exposure to heat stress. The analysis results revealed the proposed process could predict the risk of heat strain with more than 92% accuracy, illuminating the potentials of wearable biosensors to continuously assess workers’ heat strain. The long-term implications of this study can be capitalized as guidelines to improve systematic evaluation of heat strain and promote workers’ occupational safety and well-being through early detection of heat strain at construction sites.
Heat stress illnesses represent a rising public health threat; however, associations between environmental heat and observed adverse health outcomes across populations and geographies remain insufficiently elucidated to evaluate risk and develop prevention strategies. In particular, military-relevant large-scale studies of daily heat stress morbidity responses among physically active, working-age adults to various indices of heat have been limited. We evaluated daily means, maximums, minimums, and early morning measures of temperature, heat index, and wet bulb globe temperature (WBGT) indices, assessing their association with 31,642 case-definition heat stroke and heat exhaustion encounters among active duty servicemembers diagnosed at 24 continental US installations from 1998 to 2019. We utilized anonymized encounter data consisting of hospitalizations, ambulatory (out-patient) visits, and reportable events to define heat stress illness cases and select the 24 installations with the highest case counts. We derived daily indices of heat from hourly-scale gridded climate data and applied a case-crossover study design incorporating distributed-lag, nonlinear models with 5 days of lag to estimate odds ratios at one-degree increments for each index of heat. All indices exhibited nonlinear odds ratios with short-term lag effects throughout observed temperature ranges. Responses were positive, monotonic, and exponential in nature, except for maximum daily WBGT, minimum daily temperature, temperature at 0600 h (local), and WBGT at 0600 h (local), which, while generally increasing, showed decreasing risk for the highest heat category days. The risk for a heat stress illness on a day with a maximum WBGT of 32.2 °C (90.0 °F) was 1.93 (95% CI, 1.82 – 2.05) times greater than on a day with a maximum WBGT of 28.6 °C (83.4 °F). The risk was 2.53 (2.36-2.71) times greater on days with a maximum heat index of 40.6 °C (105 °F) compared to 32.8 °C (91.0 °F). Our findings suggest that prevention efforts may benefit from including prior-day heat levels in risk assessments, from monitoring temperature and heat index in addition to WBGT, and by promoting control measures and awareness across all heat categories.
BACKGROUND: Maternal exposure to weather-related extreme heat events (EHEs) has been associated with congenital heart defects (CHDs) in offspring. Certain medications may affect an individual’s physiologic responses to EHEs. We evaluated whether thermoregulation-related medications modified associations between maternal EHE exposure and CHDs. METHODS: We linked geocoded residence data from the U.S. National Birth Defects Prevention Study, a population-based case-control study, to summertime EHE exposures. An EHE was defined using the 90(th) percentile of daily maximum temperature (EHE90) for each of six climate regions during postconceptional weeks 3-8. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for associations between EHE90 and the risk of CHDs were estimated by strata of maternal thermoregulation-related medication use and climate region. Interaction effects were evaluated on multiplicative and additive scales. RESULTS: Over 45% of participants reported thermoregulation-related medication use during the critical period of cardiogenesis. Overall, these medications did not significantly modify the association between EHEs and CHDs. Still, medications that alter central thermoregulation increased aORs (95% CI) of EHE90 from 0.73 (0.41, 1.30) among non-users to 5.09 (1.20, 21.67) among users in the Southwest region, U.S. This effect modification was statistically significant on the multiplicative (P = 0.03) and additive scales, with an interaction contrast ratio (95% CI) of 1.64 (0.26, 3.02). CONCLUSION: No significant interaction was found for the maternal use of thermoregulation-related medications with EHEs on CHDs in general, while medications altering central thermoregulation significantly modified the association between EHEs and CHDs in Southwest U.S. This finding deserves further research.
BACKGROUND: Elevated temperature is well-recognized as a health hazard, and may be particularly harmful to pregnant women, including increasing risk of stillbirth. We conducted a study in Northern and Central Florida, an area prone to periodic extreme heat but with significant seasonal variation, focusing on the most socioeconomically vulnerable populations least able to mitigate the impact of heat. METHODS: We obtained electronic health records data from the OneFlorida Data Trust for the period 2012-2017, with 1876 stillbirths included in the analysis. We used a case-crossover design to examine the risk of stillbirth associated with acute exposures to elevated heat prior to the outcome, contrasting the case period (the week preceding the stillbirth) with a control period (the week prior to the case period and the week after the stillbirth). Average heat index and maximum warning level during the case and control periods of each woman were assigned by ZIP code. Conditional logistic regression models were used to assess the association between stillbirth and heat exposure, controlling for PM(2.5) and O(3). RESULTS: The adjusted odds ratio showed no overall association with stillbirth except for a weak association for exposure above the 90th percentile which was larger among the most socioeconomically deprived and non-Hispanic Black women. In the hot months, there was a clear association for all indices of heat exposure, but largest again for the most socioeconomically deprived population (aOR = 2.4, 95% CI: 1.2-5.2 in the 4th vs. 1st quartile) and among non-Hispanic Black women (aOR = 1.8, 95% CI: 1.0-3.2 in the 4th vs. 1st quartile). CONCLUSIONS: Our results provide further evidence that elevated ambient heat is related to stillbirth and encourage a focus on the most susceptible individuals and possible clinical pathways.
Safety zones (SZs) are critical tools that can be used by wildland firefighters to avoid injury or fatality when engaging a fire. Effective SZs provide safe separation distance (SSD) from surrounding flames, ensuring that a fire’s heat cannot cause burn injury to firefighters within the SZ. Evaluating SSD on the ground can be challenging, and underestimating SSD can be fatal. We introduce a new online tool for mapping SSD based on vegetation height, terrain slope, wind speed, and burning condition: the Safe Separation Distance Evaluator (SSDE). It allows users to draw a potential SZ polygon and estimate SSD and the extent to which that SZ polygon may be suitable, given the local landscape, weather, and fire conditions. We begin by describing the algorithm that underlies SSDE. Given the importance of vegetation height for assessing SSD, we then describe an analysis that compares LANDFIRE Existing Vegetation Height and a recent Global Ecosystem Dynamics Investigation (GEDI) and Landsat 8 Operational Land Imager (OLI) satellite image-driven forest height dataset to vegetation heights derived from airborne lidar data in three areas of the Western US. This analysis revealed that both LANDFIRE and GEDI/Landsat tended to underestimate vegetation heights, which translates into an underestimation of SSD. To rectify this underestimation, we performed a bias-correction procedure that adjusted vegetation heights to more closely resemble those of the lidar data. SSDE is a tool that can provide valuable safety information to wildland fire personnel who are charged with the critical responsibility of protecting the public and landscapes from increasingly intense and frequent fires in a changing climate. However, as it is based on data that possess inherent uncertainty, it is essential that all SZ polygons evaluated using SSDE are validated on the ground prior to use.
Extreme heat is an increasing climate risk due to climate change and the urban heat island (UHI) effect and can jeopardize points of dispensing (PODs) for COVID-19 vaccination distribution and broader public health emergency preparedness (PHEP) response operations. These PODs were often located on large parking lot sites with high heat severity and did not take heat mitigation or management strategies into account for unacclimated workers and volunteers. To investigate the personal heat exposure of workers, volunteers, and clients at three PODs in Tucson, Arizona, we collected ambient air temperatures, wet bulb globe temperatures (WBGT), surface temperatures, and thermal images. We also made qualitative observations and compared data against daily meteorological records. Ambient air temperatures at all three PODs exceeded the meteorological recorded high. WBGT on average were 8°F (4.4 °C) higher in full sun locations than shaded locations such as tents. Evaporative cooling decreased ambient air temperatures by 2°F (1.2 °C) when placed one per tent, but decreased ambient air temperatures by 7°F (3.9 °C) when placed en masse in a larger tent. Vehicle surface temperatures exceeded recommended safe limits of 140°F (60 °C) at all three sites, with a maximum temperature recorded at 170.9°F (77.2 °C). Public health professionals should consider heat resilience, including heat mitigation and management measures, in POD and PHEP response operations to reduce exposure. This includes considering the UHI effect in the siting of PODs, applying heat mitigation strategies in the design of PODs such as the adaptive use of solar panels for shading, and improving heat safety guidance for workers and volunteers.
We provide the first estimates of the impacts of prenatal exposure to extreme temperatures on infant health at birth using the latest national birth data from 2009 to 2018 from all U.S. states. We consistently find that an additional day with mean temperature greater than 80°F or less than 10°F increases preterm births and low birthweight. Strikingly, the adverse effects are borne disproportionately by Black and Hispanic mothers, suggesting that the projected increase in extreme temperatures may further exacerbate the existing birth health disparities across different race/ethnicity groups. We also contribute by investigating the impact of deviations from the normal weather pattern, to identify the extreme weather events after accounting for the adaptation response. We find that prenatal exposure to extreme heat two standard deviations above county’s historic average induces preterm births and NICU admissions, particularly for mothers whose pregnancies overlap with summer months. These results are timely and policy relevant, considering the recent weather trends with rising temperatures and frequent extreme weather events.
The effects of climate change on infectious diseases are a topic of considerable interest and discussion. We studied West Nile virus (WNV) in New York (NY) and Connecticut (CT) using a Weather Research and Forecasting (WRF) model climate change scenario, which allows us to examine the effects of climate change and variability on WNV risk at county level. We chose WNV because it is well studied, has caused over 50,000 reported human cases, and over 2200 deaths in the United States. The ecological impacts have been substantial (e.g., millions of avian deaths), and economic impacts include livestock deaths, morbidity, and healthcare-related expenses. We trained two Random Forest models with observational climate data and human cases to predict future levels of WNV based on future weather conditions. The Regional Model used present-day data from NY and CT, whereas the Analog Model was fit for states most closely matching the predicted future conditions in the region. Separately, we predicted changes to mosquito-based WNV risk using a trait-based thermal biology approach (Mosquito Model). The WRF model produced control simulations (present day) and pseudo-global warming simulations (future). The Regional and Analog Models predicted an overall increase in human cases of WNV under future warming. However, the Analog Model did not predict as strong of an increase in the number of human cases as the Regional Model, and predicted a decrease in cases in some counties that currently experience high numbers of WNV cases. The Mosquito Model also predicted a decrease in risk in current high-risk areas, with an overall reduction in the population-weighted relative risk (but an increase in area-weighted risk). The Mosquito Model supports the Analog Model as making more realistic predictions than the Regional Model. All three models predicted a geographic increase in WNV cases across NY and CT.
Some communities recover more quickly after a disaster than others. Some differentials in recovery are explained by variation in the level of disaster-related community damage and differences in pre-disaster community characteristics, e.g., the quality of housing stock. But distinct communities that are similar on the above characteristics may experience different recovery trajectories, and, if so, these different trajectories must be due to more subtle differences among them. Our principal objective is to assess short-term and long-term post-disaster mental health for Vietnamese and African Americans living in two adjacent communities in eastern New Orleans that were similarly flooded by Hurricane Katrina. We employ data from two population-based cohort studies that include a sample of African American adults (the Gulf Coast Child and Family Health [GCAFH study]) and a sample of Vietnamese American adults (Katrina Impacts on Vietnamese Americans [KATIVA NOLA study]) living in adjacent neighborhoods in eastern New Orleans who were assessed near the second and thirteenth anniversaries of the disaster. Using the 12-Item Short Form Survey (SF-12) as the basis of our outcome measure, we find in multivariate analysis a significant advantage in post-disaster mental health for Vietnamese Americans over their African American counterparts at the two-year mark, but that this advantage had disappeared by the thirteenth anniversary of the Katrina disaster.
Smoke from wildfires is a growing health risk across the US. Understanding the spatial and temporal patterns of such exposure and its population health impacts requires separating smoke-driven pollutants from non-smoke pollutants and a long time series to quantify patterns and measure health impacts. We develop a parsimonious and accurate machine learning model of daily wildfire-driven PM(2.5) concentrations using a combination of ground, satellite, and reanalysis data sources that are easy to update. We apply our model across the contiguous US from 2006 to 2020, generating daily estimates of smoke PM(2.5) over a 10 km-by-10 km grid and use these data to characterize levels and trends in smoke PM(2.5). Smoke contributions to daily PM(2.5) concentrations have increased by up to 5 μg/m(3) in the Western US over the last decade, reversing decades of policy-driven improvements in overall air quality, with concentrations growing fastest for higher income populations and predominantly Hispanic populations. The number of people in locations with at least 1 day of smoke PM(2.5) above 100 μg/m(3) per year has increased 27-fold over the last decade, including nearly 25 million people in 2020 alone. Our data set can bolster efforts to comprehensively understand the drivers and societal impacts of trends and extremes in wildfire smoke.
Amid worsening climate change, the recurrent wildfires have substantially worsened air quality in the Western United States (U.S.). Understanding the knowledge, attitudes, perception, and practices (KAPP) over time in response to natural disasters such as wildfires is crucial for public health interventions and disaster preparedness. This is the first study to investigate the change in air quality KAPP over time in response to natural disasters. Previous studies have only assessed KAPP at a fixed time point. Using a two-wave panel survey (during and post-wildfires), we assessed the association between KAPP and respiratory health indicators as well as the changes over time in 212 participants in the U.S. Between the two waves, we found a significant 8% increase in knowledge, which was mainly driven by participants in areas unaffected by the wildfires. In addition, we found differential associations between KAPP and respiratory health indicators between areas affected and unaffected by the wildfires. These findings suggest that experiencing wildfires may affect KAPP and more longitudinal studies are warranted, particularly during periodic air quality crises.
The FY2021 edition of USGCRP’s annual report to Congress, Our Changing Planet, responds to the Global Change Research Act mandate to provide an overview of the Program’s progress in delivering on its strategic goals as well as a summary of agency expenditures under USGCRP’s budget crosscut.
This special issue presents the findings of an international collaborative research project conducted between 2019 and 2021. This study is a follow-up of a previous study conducted between 2016 and 2019. In both studies, we examined the livelihoods of future climate migrants, who may relocate from Pacific atoll countries to developed countries. The Maldives was also included in this study, as it developed a unique strategy to cope with anticipated sea-level rise. They have developed a new city on reclaimed land and elevated it, intending to move the majority of its population there. In our first research project, we learned of the challenges faced by Pacific Islanders when transitioning to their new lives in a foreign country. This included inter alia unemployment or lack of opportunities for upward mobility, limited access to healthcare and legal services, and discrimination. We thus developed a formal policy and legal framework for the concept of “Migration with Dignity,” built upon the phrase first coined by then-Kiribati President Anote Tong. Our framework represents the opportunity for migrants to live a life equal to or better than the one they left behind. We then applied our concept of the Migration with Dignity framework to the challenges faced by climate migrants in the real world. The global outbreak of COVID-19 occurred during the implementation of our new research project. This made field research almost impossible in both atoll and developed countries and led us to modify our survey methods to include tele-interviews and remote surveys through the Internet. The pandemic also revealed the exacerbated vulnerabilities of the people who migrated to developed countries, such as discrimination, poor or no translation of medical documents, and challenging healthcare processes. We decided to address these issues within the framework of our research. We leave it to the readers of this special issue to decide how far we were able to maintain the quality of our research despite the difficulties we faced due to the sudden pandemic. As we felt at the end of our last collaboration, we now know what we need to do in our next endeavor.
This report was developed for the National Climate Task Force by the White House Office of Science and Technology Policy, NOAA, and FEMA, with input from a number of federal agencies, in response to President Biden’s Executive Order 14008, to identify opportunities for expanding and improving climate information to better enable the public to prepare for climate change. This report outlines a vision for advancing the development, communication, and accessibility of climate services through a whole-of-government approach, including close collaboration between science providers and science users.
Natural and anthropogenic disasters may be associated with redistribution of chemical contaminants in the environment; however, current methods for assessing hazards and risks of complex mixtures are not suitable for disaster response. This study investigated the suitability of in vitro toxicity testing methods as a rapid means of identifying areas of potential human health concern. We used sediment samples (n = 46) from Galveston Bay and the Houston Ship Channel (GB/HSC) areas after hurricane Harvey, a disaster event that led to broad redistribution of chemically-contaminated sediments, including deposition of the sediment on shore due to flooding. Samples were extracted with cyclohexane and dimethyl sulfoxide and screened in a compendium of human primary or induced pluripotent stem cell (iPSC)-derived cell lines from different tissues (hepatocytes, neuronal, cardiomyocytes, and endothelial) to test for concentration-dependent effects on various functional and cytotoxicity phenotypes (n = 34). Bioactivity data were used to map areas of potential concern and the results compared to the data on concentrations of polycyclic aromatic hydrocarbons (PAHs) in the same samples. We found that setting remediation goals based on reducing bioactivity is protective of both known risks associated with PAHs and unknown risks associated with bioactivity, but the converse was not true for remediation based on PAH risks alone. Overall, we found that in vitro bioactivity can be used as a comprehensive indicator of potential hazards and is an example of a new approach method (NAM) to inform risk management decisions on site cleanup.
Population growth and climate variability highlight the need to enhance freshwater security and diversify water supplies. Subsurface storage of water in depleted aquifers is increasingly used globally to alleviate disparities in water supply and demand often caused by climate extremes including floods and droughts. Managed aquifer recharge (MAR) stores excess water supplies during wet periods via infiltration into shallow underlying aquifers or direct injection into deep aquifers for recovery during dry seasons. Additionally, MAR can be designed to improve recharge water quality, particularly in the case of soil aquifer treatment and riverbank filtration. While there are many potential benefits to MAR, introduction of recharge water can alter the native geochemical and hydrological conditions in the receiving aquifer, potentially mobilizing toxic, naturally occurring (geogenic) contaminants from sediments into groundwater where they pose a much larger threat to human and ecosystem health. On the basis of the present literature, arsenic poses the most widespread challenge at MAR sites due to its ubiquity in subsurface sediments and toxicity at trace concentrations. Other geogenic contaminants of concern include fluoride, molybdenum, manganese, and iron. Water quality degradation threatens the viability of some MAR projects with several sites abandoning operations due to arsenic or other contaminant mobilization. Here, we provide a critical review of studies that have uncovered the geochemical and hydrological mechanisms controlling mobilization of arsenic and other geogenic contaminants at MAR sites worldwide, including both infiltration and injection sites. These mechanisms were evaluated based on site-specific characteristics, including hydrological setting, native aquifer geochemistry, and operational site parameters (e.g., source of recharge water and recharge/recovery cycling). Observed mechanisms of geogenic contaminant mobilization during MAR via injection include shifting redox conditions and, to a lesser extent, pH-promoted desorption, mineral solubility, and competitive ligand exchange. The relative importance of these mechanisms depends on various site-specific, operational parameters, including pretreatment of injection water and duration of injection, storage, and recovery phases. This critical review synthesizes findings across case studies in various geochemical, hydrological, and operational settings to better understand controls on arsenic and other geogenic contaminant mobilization and inform the planning and design of future MAR projects to protect groundwater quality. This critical review concludes with an evaluation of proposed management strategies for geogenic contaminants and identification of knowledge gaps regarding fate and transport of geogenic contaminants during MAR.
The extent to which climate change and other factors will influence building energy use and population exposures to indoor pollutants is not well understood. Here, we develop and apply nationally representative residential energy and indoor pollutant model sets to estimate energy use, indoor pollutant concentrations, and associated chronic health outcomes across the U.S. residential building stock in the mid-21st century. The models incorporate expected changes in meteorological and ambient air quality conditions associated with IPCC RCP 8.5 and assumptions for changes in housing characteristics and population movements while keeping other less predictable factors constant. Site and source energy consumption for residential space-conditioning are predicted to decrease by ∼37-43 and ∼20-31%, respectively, in the 2050s compared to those in a 2010s reference scenario. Population-average indoor concentrations of pollutants of ambient origin are expected to decrease, except for O(3). Holding indoor emission factors constant, indoor concentrations of pollutants with intermittent indoor sources are expected to decrease by <5% (PM(2.5)) to >30% (NO(2)); indoor concentrations of pollutants with persistent indoor sources (e.g., volatile organic compounds (VOCs)) are predicted to increase by ∼15-45%. We estimate negligible changes in disability-adjusted life-years (DALYs) lost associated with residential indoor pollutant exposures, well within uncertainty, although the attribution among pollutants is predicted to vary.
Climate change poses a significant and increasing threat to global health. While veterinarians play integral roles in public and environmental health, the profession has been less engaged in the topic of climate change relative to their human medical counterparts. The objective of this study was to synthesize veterinary students’ perceptions and knowledge about the relationship between veterinary medicine and climate change to identify educational gaps and opportunities. An online questionnaire was disseminated to American Veterinary Medical Association (AVMA)-accredited veterinary colleges through the Student American Veterinary Medical Association newsletter. Respondents were overwhelmingly confident that climate change is happening, is due to human activities, and is impacting both human and animal health. Veterinary students also expressed the belief that veterinarians should take a leadership role on the issue of climate change, especially through promoting environmental sustainability in clinical practice. Despite this enthusiasm, most students reported a lack of educational opportunities within their veterinary programs. The results of this survey highlight opportunities for the development of educational resources on the topic, many of which could complement existing material such as that devoted to practice management, economics, and client communication. Veterinarians have the potential to meaningfully contribute to both mitigation and adaptation efforts around climate change; however, they must be equipped with the tools to do so.
From August 31 – September 2, 2020, the U S Environmental Protection Agency’s Ofce of Research and Development (EPA-ORD) held a virtual workshop with public health, health care, and health care system practitioners to discuss environmental health priorities within their felds and with their organizational members and to build relationships for future dialogue and collaboration on specifc topics Using a mind mapping exercise, workshop participants identifed six environmental areas of concern: built environment; climate change; environmental justice and equity; natural environment; occupational environment; and research, data, and implementation Conversations during the workshop around the mind mapping results led to a greater understanding of how environmental health concerns are intensifed during public health crises (such as the COVID-19 pandemic) and existing cross-cutting environmental health issues that impact each area of concern [which include lead (Pb), environmental justice and equity, children’s health, mental health, and community design]. Opportunities were also identifed for cross-sector and crossdisciplinary communication, engagement, and collaboration (such as establishing partnerships in non-emergency times to help weather public health crises, training and workforce development, information sharing, and communication and risk communication). The information from this workshop can help EPA-ORD and its partners better understand mutual areas of interest and identify opportunities for more targeted cross-disciplinary discussions around the specifc environmental health topics of mutual concern.
The Trump administration has severely curtailed the work of the United States Environmental Protection Agency (EPA). The EPA has rolled back environmental protections, lost ground on addressing climate change and environmental justice, and shed large numbers of experienced staff. All of this has accelerated a longer-term decline in EPA resources, expertise, and authority. Here, we present perspectives of EPA employees and retirees on reconfiguring and strengthening the agency to address current and future environmental health problems, based on qualitative data obtained through 100 semi-structured interviews with 76 current and former EPA employees. Interviewees emphasized a number of internal and external issues, including a hyper-partisan context in which the agency operates, lack of public understanding of the extent of domestic and global environmental problems, budget shortfalls, staffing and leadership challenges, reduced scientific capacity and use of science in decision-making, insufficient attention to environmental justice, and lagging technology. We argue that reforms cannot only be expert-driven but must also come from the public, incorporating community driven solutions and focusing on remedying environmental injustice.
BACKGROUND: Ambient ultraviolet (UV) radiation has been increasing due to climate change. While this may result in adverse health consequences such as an increased incidence of skin cancer, UV radiation is also a source of vitamin D, which has been hypothesized to be protective for breast cancer risk. METHODS: Using a spatiotemporal kriging model, we estimated residential UV exposure levels for the enrollment addresses (2003-2009) of breast cancer-free women aged 35-74 years participating in the Sister Study and living in the contiguous United States (N = 48,450). Cox proportional hazards models were used to estimate adjusted hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the risk associated with UV exposure levels (mW/m^(2)) categorized in quintiles. We examined the association for breast cancer overall (invasive and ductal carcinoma in situ) and by estrogen receptor (ER) status of the tumor. We considered effect modification by regular (≥4 times/week) vitamin D supplement use. RESULTS: Over a median of 10.5 years of follow up, 3,510 incident breast cancer diagnoses were reported. We found no evidence of an association between living in areas with higher levels of UV radiation and overall breast cancer risk (HR(Q5 vs. Q1) = 1.00, 95% CI: 0.90, 1.11). Higher UV levels were inversely associated with the risk of ER- breast cancer (HR(Q5 vs. Q1) = 0.73, 95% CI: 0.55-0.99), but not ER+ (HR (Q5 vs. Q1) = 1.04, 95% CI: 0.92-1.18). For ER- breast cancer, the inverse association was only evident in women who did not regularly take vitamin D supplements (HR(Q5 vs. Q1) = 0.52, 95% CI: 0.33-0.81) compared with those who did regularly take vitamin D supplements (HR(Q5 vs. Q1) = 1.02, 95% CI: 0.68-1.54; p-for-heterogeneity = 0.12). CONCLUSIONS: The findings from this study support a role for UV exposure and vitamin D in the etiology of ER- breast cancer.
Physical/cognitive limitations associated with the aging process place older adults at disproportionate risk of negative consequences during disasters. Guided by the profession’s commitment to supporting vulnerable populations, gerontological social workers have long been on the frontlines supporting older adults during disasters. Yet, disaster social work practice remains an undeveloped and under-researched area. Thus, we asked “what is the current role of gerontological social workers in disaster preparedness with older adults in the United States, and potential areas for improvement?” This paper systematically reviews the literature discussing social work and disaster preparedness/response with older adults in the U.S., to identify needs and inform future directions. PRISMA guidelines were followed to conduct a systematic search across relevant databases for peer-reviewed-publications between January 1, 2009-June 12, 2020. Eleven articles met inclusion criteria. This body of literature is small and covers two broad areas: (1) charging the social work profession to engage in this work, and (2) describing current efforts and unique challenges of older adults during disasters. Only three empirical studies were identified. Future educational efforts should formalize training to prepare social workers for this practice area. Research should detail the roles of social workers in disaster preparedness/response, and factors that predict involvement.
Losses from natural hazards are escalating dramatically, with more properties and critical infrastructure affected each year. Although the magnitude, intensity, and/or frequency of certain hazards has increased, development contributes to this unsustainable trend, as disasters emerge when natural disturbances meet vulnerable assets and populations. To diagnose development patterns leading to increased exposure in the conterminous United States (CONUS), we identified earthquake, flood, hurricane, tornado, and wildfire hazard hotspots, and overlaid them with land use information from the Historical Settlement Data Compilation data set. Our results show that 57% of structures (homes, schools, hospitals, office buildings, etc.) are located in hazard hotspots, which represent only a third of CONUS area, and ∼1.5 million buildings lie in hotspots for two or more hazards. These critical levels of exposure are the legacy of decades of sustained growth and point to our inability, lack of knowledge, or unwillingness to limit development in hazardous zones. Development in these areas is still growing more rapidly than the baseline rates for the nation, portending larger future losses even if the effects of climate change are not considered.
INTRODUCTION: In the United States, fall-related emergency department (ED) visits among older adults (age 65 and older) have increased over the past decade. Studies document seasonal variation in fall injuries in other countries, while research in the United States is inconclusive. The objectives of this study were to examine seasonal variation in older adult fall-related ED visits and explore if seasonal variation differs by the location of the fall (indoors vs. outdoors), age group, and sex of the faller. METHODS: Fall-related ED visit data from the National Electronic Injury Surveillance System-All Injury Program were analyzed by season of the ED visit, location of the fall, and demographics for adults aged 65 years and older. RESULTS: Total fall-related ED visits were higher during winter compared with other seasons. This seasonal variation was found only for falls occurring outdoors. Among outdoor falls, the variation was found among males and adults aged 65 to 74 years. The percentages of visits for weather-related outdoor falls were also higher among males and the 65-74 year age group. CONCLUSIONS: In 2015, there was a seasonal variation in fall-related ED visits in the United States. Weather-related slips and trips in winter may partially account for the seasonal variation. PRACTICAL IMPLICATIONS: These results can inform healthcare providers about the importance of screening all older adults for fall risk and help to identify specific patients at increased risk during winter. They may encourage community-based organizations serving older adults to increase fall prevention messaging during winter.
The Earth’s climate is changing. Multiple lines of evidence show changes in our weather, oceans, ecosystems, and seasonal events. This technical report summarizes the current state of the science on observed changes related to seasonality in the United States and discusses how climate change affects the timing and nature of seasonal events. The report uses several key indicators sensitive to and related to seasonality as a framework for understanding the implications of a changing climate over time. The indicators are based on long-term observations and reveal the many dimensions of seasonal events, including critical connections between physical changes and biological responses. The report provides examples of how changes in seasonality affect ecological and human systems, as well as our everyday lives.
In September 2021, the Office of Air and Radiation (OAR) offered the opportunity for national, state, local, and Tribal air, public health, and radiation associations to provide early input to inform the development of the OAR National Program Guidance (NPG) for FY 2023-2024 via letters of invitation. OAR received four sets of comments and shared that input with its offices and other national program offices, where relevant.
Societal benefits from climate change mitigation accrue via multiple pathways. We examine the US impacts of emission changes on several factors that are affected by both climate and air quality responses. Nationwide benefits through midcentury stem primarily from air quality improvements, which are realized rapidly, and include human health, labor productivity, and crop yield benefits. Benefits from reduced heat exposure become large around 2060, thereafter often dominating over those from improved air quality. Monetized benefits are in the tens of trillions of dollars for avoided deaths and tens of billions for labor productivity and crop yield increases and reduced hospital expenditures. Total monetized benefits this century are dominated by health and are much larger than in previous analyses due to improved understanding of the human health impacts of exposure to both heat and air pollution. Benefit-cost ratios are therefore much larger than in prior studies, especially those that neglected clean air benefits. Specifically, benefits from clean air exceed costs in the first decade, whereas benefits from climate alone exceed costs in the latter half of the century. Furthermore, monetized US benefits largely stem from US emissions reductions. Increased emphasis on the localized, near-term air quality-related impacts would better align policies with societal benefits and, by reducing the mismatch between perception of climate as a risk distant in space and time and the need for rapid action to mitigate long-term climate change, might help increase acceptance of mitigation policies.
OBJECTIVES: The adverse effects that racial and ethnic minority groups experience before, during, and after disaster events are of public health concern. The objective of this study was to examine disparities in the epidemiologic and geographic patterns of natural disaster and extreme weather mortality by race and ethnicity. METHODS: We used mortality data from the Centers for Disease Control and Prevention from January 1, 1999, through December 31, 2018. We defined natural disaster and extreme weather mortality based on International Classification of Diseases, 10th Revision codes X30-X39. We calculated age-adjusted mortality rates by race, ethnicity, and hazard type, and we calculated age-adjusted mortality rate ratios by race, ethnicity, and state. We used geographic mapping to examine age-adjusted mortality rate ratios by race, ethnicity, and state. RESULTS: Natural disasters and extreme weather caused 27 335 deaths in the United States during 1999-2018. Although non-Hispanic White people represented 68% of total natural disaster and extreme weather mortality, the mortality rate per 100 000 population among non-Hispanic Black people was 1.87 times higher (0.71) and among non-Hispanic American Indian/Alaska Native people was 7.34 times higher (2.79) than among non-Hispanic White people (0.38). For all racial and ethnic groups, exposure to extreme heat and cold were the 2 greatest causes of natural disaster and extreme weather mortality. Racial and ethnic disparities in natural disaster and extreme weather mortality were highest in the South, Southwest, Mountain West, and Upper Midwest. CONCLUSIONS: Racial and ethnic minority populations have a greater likelihood of mortality from natural disaster or extreme weather events than non-Hispanic White people. Our study strengthens the current knowledge base on these disparities and may inform and improve disaster preparedness and response efforts.
Outcomes of acute heart failure hospitalizations are worse during the winter than the rest of the year. Seasonality data are more limited for outcomes in chronic heart failure and the effect of environmental variables is unknown. In this population-level study, we merged 20-year data for 555,324 patients with heart failure from the national Veterans Administration database with data on climate from the National Oceanic and Atmospheric Administration and air pollutants by the Environmental Protection Agency. The outcome was the all-cause mortality rate, stratified by geographical location and each month. The impact of environmental factors was assessed through Pearson’s correlation and multiple regression with a family-wise α = 0.05. The monthly all-cause mortality was 13.9% higher in the winter than the summer, regardless of gender, age group, and heart failure etiology. Winter season, lower temperatures, and higher concentrations of nitrogen dioxide were associated with a higher mortality rate in multivariate analysis of the overall population. Different environmental factors were associated in regions with similar patterns of temperature and precipitation. The only environmental factor associated with the mortality rate of patients dwelling in large urban centers was the air quality index. In conclusion, the mortality in chronic heart failure exhibits a seasonal pattern, regardless of latitude or climate. In this group of patients, particularly those of male gender, a higher mortality was associated with environmental factors and incorporating these factors in treatment plans and recommendations could have a favorable cost-benefit ratio.
CONTEXT: Colorado is experiencing dramatic changes related to population growth, climate change, and expanded industrial activity. Local and state public health professionals are trying to address a growing array of unique public health issues with stagnant or limited resources. OBJECTIVES: To understand, through perspectives from local and state public health professionals, the alignment of contemporary environmental and community health issues with state and local capacity and state environmental public health-tracking priorities. DESIGN: During 2014-2015, we conducted semistructured interviews which informed the development of a statewide survey of Colorado’s professionals from public health, emergency management, forestry, and transportation. SETTING: This work took place in Colorado. PARTICIPANTS: Fifteen professionals from public (n = 9), academic (n = 4), and private (n = 2) sectors were interviewed. Forty-seven professionals, representing 34 counties and 40 public agencies, completed the 25-minute online survey. MAIN OUTCOME MEASURES: Environmental and community health concerns; contributing factors to environmental concerns; strengths and limitations of capacity to respond to issues; and frequency of community engagement activities. RESULTS: Top environmental health concerns were indoor air pollution (eg, radon), outdoor air pollution, and waste management. Transportation, extreme weather (eg, wildfires), and oil and gas development were most frequently reported as major contributing factors to concerns. Obesity, physical inactivity, and mental illness were the top community health concerns. To remain prepared for emerging challenges, professionals cited a need for more spatiotemporal-refined data related to their top concerns in the environmental public health-tracking database, and support from local, state, and federal agencies, in addition to personnel and funding. To address concerns, participants reported frequently working with government officials, advisory committees, and media outlets. CONCLUSIONS: This project illuminates opportunities to strengthen connections between the state’s environmental public health-tracking priorities and local-level capacity related to professionals’ top concerns. It also suggests reinforcing and broadening partnerships to improve data infrastructure and inform environmental public health priorities.
Many areas of the United States have air pollution levels typically below Environmental Protection Agency (EPA) regulatory limits. Most health effects studies of air pollution use meteorological (e.g., warm/cool) or astronomical (e.g., solstice/equinox) definitions of seasons despite evidence suggesting temporally-misaligned intra-annual periods of relative asthma burden (i.e., asthma seasons). We introduce asthma seasons to elucidate whether air pollutants are associated with seasonal differences in asthma emergency department (ED) visits in a low air pollution environment. Within a Bayesian time-stratified case-crossover framework, we quantify seasonal associations between highly resolved estimates of six criteria air pollutants, two weather variables, and asthma ED visits among 66,092 children ages 5-19 living in South Carolina (SC) census tracts from 2005 to 2014. Results show that coarse particulates (particulate matter <10 μm and >2.5 μm: PM10-2.5) and nitrogen oxides (NOx) may contribute to asthma ED visits across years, but are particularly implicated in the highest-burden fall asthma season. Fine particulate matter (<2.5 μm: PM2.5) is only associated in the lowest-burden summer asthma season. Relatively cool and dry conditions in the summer asthma season and increased temperatures in the spring and fall asthma seasons are associated with increased ED visit odds. Few significant associations in the medium-burden winter and medium-high-burden spring asthma seasons suggest other ED visit drivers (e.g., viral infections) for each, respectively. Across rural and urban areas characterized by generally low air pollution levels, there are acute health effects associated with particulate matter, but only in the summer and fall asthma seasons and differing by PM size.
This is a one-page summary of findings from EPA’s report Climate Change and Social Vulnerability in the United States: A Focus on Six Impacts related to disproportionate risks of climate change to Black and African American individuals.
This is a one-page summary of findings from EPA’s report Climate Change and Social Vulnerability in the United States: A Focus on Six Impacts related to disproportionate risks of climate change to low income individuals.
BACKGROUND: Short-term exposure to high or low temperatures is associated with increased mortality and morbidity. Less is known about effects of long-term exposure to high or low temperatures. Prolonged exposure to high or low temperatures might contribute to pathophysiological mechanisms, thereby influencing the development of diseases. Our aim was to evaluate associations of long-term temperature exposure with cardiovascular disease (CVD) hospitalizations. METHODS: We constructed an open cohort consisting of all fee-for-service Medicare beneficiaries, aged ≥65, living in the contiguous US from 2000 through 2016 (∼61.6 million individuals). We used data from the 4 km Gridded Surface Meteorological dataset to assess the summer (June-August) and winter (December-February) average daily maximum temperature for each year for each zip code. Cox-equivalent Poisson models were used to estimate associations with first CVD hospitalization, after adjustment for potential confounders. We performed stratified analyses to assess potential effect modification by sex, age, race, Medicaid eligibility and relative humidity. RESULTS: Higher summer average and lower winter average temperatures were associated with an increased risk of CVD hospitalization. We found a HR of 1.068 (95% CI: 1.063, 1.074) per IQR increase (5.2 °C) for summer average temperature and a HR of 1.022 (95% CI: 1.017, 1.028) per IQR decrease (11.7 °C) for winter average temperature. Positive associations of higher summer average temperatures were strongest for individuals aged <75 years, Medicaid eligible, and White individuals. Positive associations of lower winter average temperatures were strongest for individuals aged <75 years and Black individuals, and individuals living in low relative humidity areas. CONCLUSIONS: Living in areas with high summer average temperatures or low winter average temperatures could increase the risk of CVD hospitalizations. The magnitude of the associations of summer and winter average temperatures differs by demographics and relative humidity levels.
We present an exploratory cross-sectional analysis of the effect of season and weather on Freesurfer-derived brain volumes from a sample of 3,279 healthy individuals collected on two MRI scanners in Hartford, CT, USA over a 15 year period. Weather and seasonal effects were analyzed using a single linear regression model with age, sex, motion, scan sequence, time-of-day, month of the year, and the deviation from average barometric pressure, air temperature, and humidity, as covariates. FDR correction for multiple comparisons was applied to groups of non-overlapping ROIs. Significant negative relationships were found between the left- and right- cerebellum cortex and pressure (t = -2.25, p = 0.049; t = -2.771, p = 0.017). Significant positive relationships were found between left- and right- cerebellum cortex and white matter between the comparisons of January/June and January/September. Significant negative relationships were found between several subcortical ROIs for the summer months compared to January. An opposing effect was observed between the supra- and infra-tentorium, with opposite effect directions in winter and summer. Cohen’s d effect sizes from monthly comparisons were similar to those reported in recent psychiatric big-data publications, raising the possibility that seasonal changes and weather may be confounds in large cohort studies. Additionally, changes in brain volume due to natural environmental variation have not been reported before and may have implications for weather-related and seasonal ailments.
OBJECTIVE: We review the existing research on environmentally sustainable surgical practices to enable SAO to advocate for improved environmental sustainability in operating rooms across the country. SUMMARY OF BACKGROUND DATA: Climate change refers to the impact of greenhouse gases emitted as a byproduct of human activities, trapped within our atmosphere and resulting in hotter and more variable climate patterns.1 As of 2013, the US healthcare industry was responsible for 9.8% of the country’s emissions2; if it were itself a nation, US healthcare would rank 13th globally in emissions.3 As one of the most energy-intensive and wasteful areas of the hospital, ORs drive this trend. ORs are 3 to 6 times more energy intensive than clinical wards.4 Further, ORs and labor/delivery suites produce 50%-70% of waste across the hospital.5,6 Due to the adverse health impacts of climate change, the Lancet Climate Change Commission (2009) declared climate change “the biggest global health threat of the 21st century” and predicted it would exacerbate existing health disparities for minority groups, children and low socioeconomic patients.7. METHODS/RESULTS: We provide a comprehensive narrative review of published efforts to improve environmental sustainability in the OR while simultaneously achieving cost-savings, and highlight resources for clinicians interested in pursuing this work. CONCLUSION: Climate change adversely impacts patient health, and disproportionately impacts the most vulnerable patients. SAO contribute to the problem through their resource-intensive work in the OR and are uniquely positioned to lead efforts to improve the environmental sustainability of the OR.
Approximately 75% of farmworkers in the United States are Latino migrants, and about 50% of hired farmworkers do not have authorization to work in the United States. Farmworkers face numerous chemical, physical, and biological threats to their health. The adverse effects of these hazards may be amplified among Latino migrant farmworkers, who are concurrently exposed to various psychosocial stressors. Factors such as documentation status, potential lack of authorization to work in the United States, and language and cultural barriers may also prevent Latino migrants from accessing federal aid, legal assistance, and health programs. These environmental, occupational, and social hazards may further exacerbate existing health disparities among US Latinos. This population is also likely to be disproportionately impacted by emerging threats, including climate change and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Latino migrant farmworkers are essential to agriculture in the United States, and actions are needed to protect this vulnerable population.
Acute flaccid myelitis (AFM) recently emerged in the United States as a rare but serious neurological condition since 2012. Enterovirus D68 (EV-D68) is thought to be a main causative agent, but limited surveillance of EV-D68 in the United States has hampered the ability to assess their causal relationship. Using surveillance data from the BioFire Syndromic Trends epidemiology network in the United States from January 2014 to September 2019, we characterized the epidemiological dynamics of EV-D68 and found latitudinal gradient in the mean timing of EV-D68 cases, which are likely climate driven. We also demonstrated a strong spatiotemporal association of EV-D68 with AFM. Mathematical modeling suggested that the recent dominant biennial cycles of EV-D68 dynamics may not be stable. Nonetheless, we predicted that a major EV-D68 outbreak, and hence an AFM outbreak, would have still been possible in 2020 under normal epidemiological conditions. Nonpharmaceutical intervention efforts due to the ongoing COVID-19 pandemic are likely to have reduced the sizes of EV-D68 and AFM outbreaks in 2020, illustrating the broader epidemiological impact of the pandemic.
This study explores the role of access to essential facilities and emergency services during hazard weather events in shaping individuals’ risk perceptions. We develop a framework in which resi-dents’ views of required actions facing extreme weather are influenced by their level of access to essential facilities to obtain medical and emergency services. The effect of access is comple-mented by perceptions about the status of local infrastructure conditions as enabling access. Us -ing a sample of Texas residents collected during April 2021, we demonstrate the role of restricted access and views of local infrastructure conditions as important predictors of increased concerns during natural disasters. The results demonstrate the effects of factors such as access and status of local infrastructure on the risk assessments of individuals in vulnerable communities who face in-creased risks from extreme weather. Accordingly, the findings advance our understanding of the unexplored relationship between access of essential facilities and risk perceptions, and could in-form disaster managers and public officials regarding the importance of evaluating access as an element of public risk perceptions facing extreme weather events.
Mitigating future climate change and managing future air quality are inter-related fields that have the potential to benefit from coordinated strategies that leverage the efforts in one area to achieve positive outcomes in the other area. California plans to reduce greenhouse gas (GHG) emission by 80% (relative to year 1990) by the year 2050. The changes required to meet this target also have the potential to improve air quality. Previous work developed an energy-economic model CA-TIMES and an emission inventory model CA-REMARQUE to study the possible pathways of meeting the GHG mitigation target and the air pollutant emissions associated with those pathways. Here we update the CA-TIMES and CA-REMARQUE model framework and analyze six different sce-narios: (i) BAU -a business-as-usual future reference scenario, (ii) CAP30 -a loose GHG reduction scenario that meets current policy references but only achieves a 40% GHG reduction (relative to 1990 levels) by the year 2030, (iii) GHGAi -a climate-friendly 80% GHG reduction scenario featuring broad adoption of advanced technologies and renewable energies, (iv) CCS -a scenario that achieves 80% net GHG reductions but allows for more fossil energy combustion by focusing on adoption of carbon capture and sequestration technology, (v) NGB- a variation on the GHGAi scenario that allows for more natural gas combustion for residential and commercial buildings, and (vi) NGT – a variation of the GHGAi scenario that allows for more natural gas combustion for electricity generation. Results show that the GHGAi deep GHG mitigation scenario significantly reduces emissions (-41% PM0.1,-8% PM2.5, and-26% NOX) and improves air quality (-1 mu g m(-3) PM2.5) yielding public health benefits (+USD 20B yr(-1)) relative to the BAU scenario. The CCS scenario achieves the same GHG reductions but increases emissions in some areas (+2.5% PM2.5) resulting in only one third of the public health benefits compared to the GHGAi scenario. The NGB and NGT scenarios show that an 18% increase in natural gas utilization in buildings or a 15% increase in natural gas power generation offsets 32% and 46% of the ultrafine particle emission reduction achieved in the GHGAi scenario but has little impact on PM2.5 concentrations, producing approximately 90% of the public health benefits of the GHGAi scenario. These public health benefits should be considered when making decisions about future GHG mitigation strategies.
Mycotoxin contamination of corn results in significant agroeconomic losses and poses serious health issues worldwide. This paper presents the first report utilizing machine learning and historical aflatoxin and fumonisin contamination levels in-order-to develop models that can confidently predict mycotoxin contamination of corn in Illinois, a major corn producing state in the USA. Historical monthly meteorological data from a 14-year period combined with corresponding aflatoxin and fumonisin contamination data from the State of Illinois were used to engineer input features that link weather, fungal growth, and aflatoxin production in combination with gradient boosting (GBM) and bayesian network (BN) modeling. The GBM and BN models developed can predict mycotoxin contamination with overall 94% accuracy. Analyses for aflatoxin and fumonisin with GBM showed that meteorological and satellite-acquired vegetative index data during March significantly influenced grain contamination at the end of the corn growing season. Prediction of high aflatoxin contamination levels was linked to high aflatoxin risk index in March/June/July, high vegetative index in March and low vegetative index in July. Correspondingly, high levels of fumonisin contamination were linked to high precipitation levels in February/March/September and high vegetative index in March. During corn flowering time in June, higher temperatures range increased prediction of high levels of fumonisin contamination, while high aflatoxin contamination levels were linked to high aflatoxin risk index. Meteorological events prior to corn planting in the field have high influence on predicting aflatoxin and fumonisin contamination levels at the end of the year. These early-year events detected by the models can directly assist farmers and stakeholders to make informed decisions to prevent mycotoxin contamination of Illinois grown corn.
Environmental racism has long plagued the United States and continues to do so as the effects of climate change worsen and grow. These effects have a broad impact on every aspect of life from physical and mental health to financial stability and access to opportunities. In order to more fully understand the consequences of climate change on people, it is helpful to develop an understanding of the historical, economic, and political dimensions of climate change. This paper aims to assist in understanding as well as provide sources of engagement for social workers.
All aspects of society are affected by our changing climate. Individuals and communities experience the health impacts associated with climate change most every day, whether or not they realize it. Increasing both the knowledge and capacity to respond to the health impacts of climate change will be imperative for future public health leaders. This manuscript will highlight three case studies in how problem-based learning was used by California State University, East Bay’s Department of Public Health undergraduate students to address climate change issues for local community and government organizations. The results from problem-based learning collaborations between undergraduate students and community and government organizations have been mutually beneficial and increased the knowledge and workforce capacity of climate and health in the San Francisco Bay Area. The authors believe the use of problem-based learning is an effective model to achieve these goals. Both the students and the community benefit from these experiences and results of projects that enhance an organization’s ability to prepare for and respond to climate change in their communities.
The burden of temperature-associated mortality and hospital visits is significant, but temperature’s effects on non-emergency health outcomes is less clear. This burden is potentially greater in low-income households unable to afford efficient heating and cooling. We examined short-term associations between indoor temperatures and cognitive function and daytime sleepiness in low-income residents of Detroit, Michigan. Apparent temperature (AT, based on temperature and humidity) was recorded hourly in 34 participant homes between July 2019-March 2020. Between July-October 2019, 18 participants were administered word list immediate (WLL) and delayed (WLD) recall tests (10-point scales) and the Epworth Sleepiness Scale (24-point scale) 2-4 times. We applied longitudinal models with nonlinear distributed lags of temperature up to 7 days prior to testing. Indoor temperatures ranged 8-34°C overall and 15-34°C on survey days. We observed a 0.4 (95% CI: 0.0, 0.7) point increase in WLL and 0.4 (95% CI: 0.0, 0.9) point increase in WLD scores per 2°C increase in AT. Results suggested decreasing sleepiness scores with decreasing nighttime AT below 22??C. Low-income Detroit residents experience uncomfortably high and low indoor temperatures. Indoor temperature may influence cognitive function and sleepiness, although we did not observe deleterious effects of higher temperatures.
Our society is currently facing an unprecedented number of environmental and societal challenges. Stakeholder and community engagement can help identify priority issues and needs at local levels. One approach to engage stakeholders and communities in the contexts of environmental, health, and societal challenges is to leverage outreach and extension programs. Within this context, and to help identify priority issues to focus subsequent research and extension programs in North Carolina (NC), a survey was conducted with extension agents to identify priority issues as they relate to environmental health and risks and related needs. Based on responses from 66 study participants that represented half of the 100 NC counties, we found that Water pollution, Flooding, Natural resources management, and Engaging stakeholders were top priority issues across all environmental health and risk topics. Participants also identified that practices of Engaging stakeholders as well as Assessing, Managing, and Communicating risks were increasingly important. Participants indicated they needed a moderate-to-significant amount of guidance across a range of areas related to assessing, managing, communicating, and making decisions regarding environmental health and risk topics, as well as engaging with local communities. Outcomes from this work can not only help inform subsequent research and outreach efforts at local scales, but this work demonstrates a simple, low-cost approach to elicit perspectives and priorities can be leveraged in other states and regions with established stakeholder and community outreach programs more broadly. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10669-022-09864-0.
Climate change has been labeled one of the most significant threats to patient health. Advanced practice registered nurses must acquire adequate preparatory education to care for patients during climate change. They would benefit from implementing climate change concepts to provide safe and quality care for patients. This article aims to discuss integrating climate change concepts into advanced practice nurses curricula by applying the National Organization of Nurse Practitioner Faculties’ competencies.
OBJECTIVE: To assess knowledge, attitudes, and practices (KAP) related to antimicrobial resistance (AMR) among college students. PARTICIPANTS: Undergraduate students at a large public university in the United States. METHODS: Anonymous online questionnaire completed in early 2020. RESULTS: While 82% of participants knew that resistant pathogens can spread between people, 38% believed that antibiotics weaken the immune system and 32% believed that AMR is only a problem for people who take antibiotics often. Many undergraduates have or would stop taking antibiotics before completing a full course because of side effects (44%) or feeling better (38%), and some would take (23%) or share (13%) antibiotics that had not been prescribed to the recipient. Only 57% are worried about AMR, compared to 88% who are worried about global climate change. CONCLUSIONS: Health education about antimicrobial stewardship and other global health issues must improve knowledge, perceptions, health behaviors, self-efficacy, and social norms.
The potential environmental and human health impacts associated with constructing and operating terminal buildings is explored for commercial airports in the United States. Research objectives are to quantify: (1) baseline and mitigated greenhouse gas (GHG) and criteria air pollutant (CAP) emissions; (2) operational costs; and (3) climate change damages from terminal building construction and materials, operational energy consumption, water consumption and wastewater generation, and solid waste generation. An Excel-based decision-support tool, Airport Terminal Environmental Support Tool (ATEST), has been created to allow stakeholders to conduct preliminary assessments of current baseline and potential mitigated impacts. Emissions are quantified using a life-cycle approach that accounts for cradle-to-grave effects. Climate change and human health indicators are characterized using EPA’s Tool for Reduction and Assessment of Chemical Impact (TRACI) factors. ATEST is applied to multiple case study airports- Reno/Tahoe International (RNO), Pittsburgh International (PIT), Newark Liberty International (EWR), Seattle-Tacoma International (SEA), San Francisco International (SFO), and Hartsfield-Jackson Atlanta International (ATL)-to demonstrate its scalability and capability to assess varying spatial factors. Across all airports, electricity mix and construction are significant in determining GHG and CAP emissions, respectively. A sensitivity analysis of GHG emissions for the SFO case study reveals that the electricity mix, amount of electricity consumed within the terminal, terminal gross area, and amount of compostables in the solid waste stream have the most impact on increasing annual GHG emissions. ATEST represents a crucial first step in helping stakeholders to make decisions that will lead to healthier, more sustainable airport terminals.
Oil and natural gas are the largest primary global energy sources, and upstream gas emissions from these fuels can impact global climate change and local public health. This paper employs a public health-oriented perspective that reviews grey and academic literature, industry data, technical reports, and policy trends to highlight issues of emissions monitoring. We identify gaps in the existing landscape of emissions reduction strategies and highlight options for addressing them. Policy recommendations include the use of new digital monitoring technologies to better understand causes of emission events, to create data-driven oil and gas regulations, and to begin accurately measuring the volumes of gases released during oil and gas production. Areas for future research relating to emissions and public health impacts are outlined to further enable oil and gas policy discussions.
The present study examines the temperature variability in physical activity (PA), sedentary behavior (SB), and sleep in a free-living population. A representative sample of 1235 adults (ages 21-70) from Iowa, U.S.A., wore a SenseWear Mini Armband (SWA) for a randomly assigned day. Koppen’s weather climate classification was used to precisely classify the temperature: cold (-13 to 32 °F), cool (32 to 50 °F), mild (50 to 64 °F), warm (64 to 73 °F), and hot (73 to 95 °F). The main effect of three-way ANOVA (age × gender × temperature) had differences for SB and sleep, with older adults having higher levels than younger adults (p < 0.05). However, moderate to vigorous PA (MVPA) did not vary systematically by age or gender, and contrary to expectations, the main effect of the weather was not significant for MVPA (p > 0.05). Participants spent more time participating in PA at cold than at hot temperatures. The results clarify the impact of temperature on shaping PA and SB patterns in adults. The variable impacts and differential patterns by age suggest that weather should be considered when interpreting differences in PA patterns in research or surveillance applications.
BACKGROUND: Studies of thunderstorm asthma to understand risk factors using high-resolution climate data and asthma outcomes on a large scale are scarce. Moreover, thunderstorm asthma is not well studied in the United States. OBJECTIVES: We examined whether climate parameters involved in thunderstorms are associated with emergency department (ED) visits for acute asthma attacks in the United States. METHODS: We analyzed 63,789 asthma-related, daily ED visits for all age groups, and thunderstorm-associated climate data in Louisiana during 2010 through 2012. We performed time-series analyses using quasi-Poisson regression models with natural cubic splines of date, parish, holiday, day of week, season, daily maximum concentrations of ozone (O3) and fine particulate matter [PM ≤ 2.5 μm in aerodynamic diameter (PM2.5)], and daily mean pressure, precipitation, and temperature. Because of a significant interaction effect between temperature and lightning days on asthma-related visits, we performed stratified analyses by days with/without lightning or thunderstorm (defined by any lightning and precipitation). RESULTS: On thunderstorm days, higher asthma-related ED visits were associated with higher daily mean precipitation [relative risk (RR) = 1.145 per 1 g/m2/s (95% CI: 1.009, 1.300)] and lower daily mean temperature [RR = 1.011 per 1°C change (1.000-1.021)] without carry-over effect to the next non-thunderstorm day. These higher risks were found mainly among children and adults < 65 years of age. We observed similar results on lightning days. However, we did not find similar associations for non-thunderstorm or non-lightning days. Daily maximum O3 and PM2.5 levels were not significantly associated with asthma ED visits on thunderstorm days. DISCUSSION: Higher precipitation and lower temperature on thunderstorm days appear to contribute to asthma attacks among people with asthma, suggesting they should consider taking precautions during thunderstorms. EDs should consider preparing for a potential increase of asthma-related visits and ensuring sufficient stock of emergency medication and supplies for forecasted severe thunderstorm days. https://doi.org/10.1289/EHP10440.
BACKGROUND: While evidence suggests that daily ambient temperature exposure influences stroke risk, little is known about the potential triggering role of ultra short-term temperature. METHODS: We examined the association between hourly temperature and ischemic and hemorrhagic stroke, separately, and identified any relevant lags of exposure among adult New York State residents from 2000 to 2015. Cases were identified via ICD-9 codes from the New York Department of Health Statewide Planning and Reearch Cooperative System. We estimated ambient temperature up to 36 h prior to estimated stroke onset based on patient residential ZIP Code. We applied a time-stratified case-crossover study design; control periods were matched to case periods by year, month, day of week, and hour of day. Additionally, we assessed effect modification by leading stroke risk factors hypertension and atrial fibrillation. RESULTS: We observed 578,181 ischemic and 164,755 hemorrhagic strokes. Among ischemic and hemorrhagic strokes respectively, the mean (standard deviation; SD) patient age was 71.8 (14.6) and 66.8 (17.4) years, with 55% and 49% female. Temperature ranged from -29.5 °C to 39.2 °C, with mean (SD) 10.9 °C (10.3 °C). We found linear relationships for both stroke types. Higher temperature was associated with ischemic stroke over the 7 h following exposure; a 10 °C increase over 7 h was associated with 5.1% (95% Confidence Interval [CI]: 3.8, 6.4%) increase in hourly stroke rate. In contrast, temperature was negatively associated with hemorrhagic stroke over 5 h, with a 5-h cumulative association of -6.2% (95% CI: 8.6, -3.7%). We observed suggestive evidence of a larger association with hemorrhagic stroke among patients with hypertension and a smaller association with ischemic stroke among those with atrial fibrillation. CONCLUSION: Hourly temperature was positively associated with ischemic stroke and negatively associated with hemorrhagic stroke. Our results suggest that ultra short-term weather influences stroke risk and hypertension may confer vulnerability.
Context: A 10-week elective course, designed by students and supported by faculty, was developed to raise awareness about climate change and health among graduate health professional students. This article aims to characterise the course design, implementation, and student feedback gathered over three years. Description of Course: Course topics aligned with United Nations General Assembly Sustainable Development Goals and were sequenced to first introduce students to basic climate change concepts, followed by examples of human activities with environmental and health consequences. Speakers held diverse roles in health care, research, public health organisations, and advocacy groups. Students evaluated both individual speakers and the course. Evaluation: 152 health professional students enrolled in the course over 3 years. The course was well-received with favourable speaker ratings and course evaluations across all years. Students commented on the importance and relevance of the course topics taught by a diverse group of speakers. Students also requested examples of ways to address climate health issues. Future plans: A 10-week elective course on climate change and health, designed by students and supported by faculty, resulted in favourable evaluations among health professions students. The authors plan to conduct an assessment of student knowledge gained from the course and delayed assessments of students’ attitudes and behaviours to evaluate changes over time and achievement of course goals.
INTRODUCTION: As medical schools continue to improve and refine their undergraduate curricula, they are also redefining the roadmap for preparing future generations of physicians. Climate change is a critical topic to integrate into medical education. This period of change for undergraduate medical education coincides with a surge in interest and design efforts for climate and health curricula in health professional education, but this nascent field has yet to be solidly institutionalized. To continue to grow the number of medical students who achieve competency in the effects of climate change on individual health and the health of the planet during their training, we must examine what has worked to date and continue to shift our approach as curricular changes are implemented for feasibility and relevancy. OBJECTIVE AND METHODS: In the present study, we assessed the “climate and health” content at one northeastern U.S. medical school that is undergoing an overhaul of their entire curriculum to explore strategies to deliver more robust climate health education in the context of the educational redesign. We conducted 1) a retrospective review of the now four-year-old initiative to investigate the sustainability of the original content, and 2) semi-structured interviews with lecturers, course directors, and medical education coordinators involved in implementation, and with faculty tasked with developing the upcoming curricular redesign. RESULTS AND DISCUSSION: Of the original implementation plan, the content was still present in nine of the 14 lectures. Themes determined from our conversations with involved faculty included the need for 1) a shared vision throughout the content arc, 2) further professional development for faculty, and 3) involvement of summative assessment for students and the content itself to ensure longevity. The interviews also highlighted the importance of developing climate-specific resources that fit within the school’s new curricular priorities. This critical review can serve as a case study in curriculum to inform other schools undergoing similar changes.
OBJECTIVE: To characterize US State and Territorial Health Agencies’ (S/THA) climate change adaptation activities and priorities to facilitate appropriate investments, skills development, and support that will strengthen health sector capacity in response to a changing climate. DESIGN: In 2021, we conducted an online survey of S/THA staff requesting information on current activities related to climate change and health, the state of climate and health programming, and anticipated needs and priorities for assistance. We analyzed survey results using descriptive statistics. SETTING: US State and Territorial Health Agencies. PARTICIPANTS: We received responses from 41 of 59 S/THAs (69.5%). MAIN OUTCOME MEASURES: Implementation of S/THA climate and health programs (CHPs); engagement in climate and health activities; maintenance of hazard early warning systems and action plans; employment of climate and health communications strategies; capability to assess risks and adaptation needs related to various climate-sensitive conditions; priorities and plans for climate change adaptation in relation to climate-sensitive health risks; climate change adaptation-related partnerships and collaborations; requests of the Association of State and Territorial Health Officials (ASTHO) for advancing climate change adaptation activities; and the impacts of the COVID-19 pandemic on climate change work. RESULTS: Nineteen S/THAs reported having CHPs, the majority of which are federally funded. On average, S/THAs without CHPs reported engagement in fewer climate and health activities and more early warning activities. The S/THAs reported the highest levels of concerns regarding non-vector-borne infectious disease (66%), vector-borne infectious diseases (61%), and extreme heat (61%) hazards. CONCLUSIONS: As S/THAs with CHPs report substantially greater climate and health capacity than those without, additional federal and state investments (eg, Building Resilience Against Climate Effects [BRACE]) are urgently needed to catalyze climate and health capacity.
BACKGROUND: There has been increasing interest in climate change among healthcare professionals, but it is unclear to what extent resources on this topic are available to students and clinicians in New England. METHODS: Structured review of publicly available information regarding climate change and health activity at schools of medicine, public health, and physician assistant studies and in state medical and physician assistant societies in New England. RESULTS: Of 39 programs reviewed, 18 (46%) had at least one climate-related initiative. Six universities accounted for 87% of climate change and health initiatives in the region. Three out of 12 state professional associations had committees or position statements addressing climate change. CONCLUSION: There is substantial activity related to climate change and health in New England, but it is concentrated in a small number of locations. Opportunities exist to improve access to education on this topic and increase involvement of health professional associations.
In response to growing recognition for the mental health impacts of climate change, understanding the full range of children’s psychological experiences in climate change education (CCE) contexts is critical to developing approaches that support children’s constructive engagement and overall well-being. Through surveys and focus groups conducted with fifty-five children (ages 10-12), this mixed-methods study examined the affective and attitudinal impacts of a multi-site CCE program that encouraged children’s learning, reflection, and action. Findings suggest that, through the program, children acquired stronger pro-environmental attitudes, a deeper respect for nature, and a greater sense of urgency towards the need for climate action. Importantly, children’s negative emotions (e.g. fear, worry, anger, sadness) were mitigated by positive emotions grounded in youth-led climate action in family and community contexts. Findings are interpreted through theories of cognitive and affective transformation, which shed light on the beneficial micro- and macrolevel outcomes of children’s perspective shifts.
Climate change is considered one of the top health threats in the United States. This research sought to (1) to understand the perceptions of occupational health and safety (OHS) professionals regarding the impacts of climate-related hazards on OHS in Region X, and (2) to explore the ideas of these OHS professionals regarding the content of future training programs that would better prepare OHS professionals to identify and mitigate climate-related hazards in Region X. Key informant (KI) interviews with 17 OHS professionals familiar with the climate-related hazards and impacts to OHS in Region X were coded and thematically analyzed. Climate hazards, social and economic impacts from climate-related hazards, and sector-specific worker and workplace impacts from climate-related hazards were described as having interacting relationships that influenced worker health and safety impacts. KIs further described how workplace controls could be used to mitigate OHS impacts of climate-related hazards, and how training of the OHS workforce could influence the ability to successfully implement such controls. Our findings suggest that OHS impacts are sector-specific, influenced by social and economic factors, and can be mitigated through workplace controls designed and implemented by a trained OHS workforce. The findings from this work should inform future educational and training programming and additional research and translation activities in the region, while our approach can inform other regions as they develop regionally specific OHS climate change training and programming.
Natural hazards are the underlying cause of between 1 and 7 percent of federally reported hazmat releases in the US every year. During the period from 1990 through 2019 the fraction of releases caused by natural hazards has increased, in large part due to increased releases from hurricanes as well as floods, storms and wind. Many of these events are minor, but some have resulted in large and expensive releases as well as deaths, injuries, and evacuations. Inter annual variability of these releases is correlated with occurrence of extreme weather and associated climate indices. Given observed and future predicted increases in extreme weather events, it is likely many of these types of releases will continue to increase. Greater attention to management of natural hazard risk to industry, and in particularly to bulk storage facilities, is required to prevent further increase in the frequency and severity of these events.
BACKGROUND: Combined sewer overflows (CSOs) discharge untreated sewage into surface and recreational water, often following heavy precipitation. Given projected increases in frequency and intensity of precipitation due to climate change, it is important to understand the health impacts of CSOs and mediating effects of sewerage systems. OBJECTIVES: In this study we estimate associations of CSO events and emergency department (ED) visits for gastrointestinal (GI) illness among City of Atlanta, Georgia, residents and explore how these associations vary with sewerage improvements. METHODS: We estimate associations using Poisson generalized linear models, controlling for time trends. We categorized CSOs by overflow volume and assessed effects of CSO events prior to ED visits with 1-, 2- and 3-wk lags. Similarly, we evaluated effects of weekly cumulative precipitation greater than the 90th percentile at the same lags. We also evaluated effect modification by ZIP Code Tabulation Area (ZCTA)-level poverty and infrastructure improvement period using interaction terms. RESULTS: Occurrence of a large volume CSO in the previous week was associated with a 9% increase in daily ED visits for GI illness. We identified significant interaction by ZCTA-level poverty, with stronger CSO-GI illness associations in low than high poverty areas. Among areas with low poverty, we observed associations at 1-wk and longer lags, following both large and lower volume CSO events. We did not observe significant interaction by infrastructure improvement period for CSO- nor precipitation-GI illness associations; however, the number of CSO events decreased from 2.31 per week before improvements to 0.49 after improvements. DISCUSSION: Our findings suggest that CSOs contribute to acute GI illness burden in Atlanta and that the magnitude of this risk may be higher among populations living in areas of low poverty. We did not find a protective effect of sewerage system improvements. Nonetheless, observed reductions in CSO frequency may lower the absolute burden of GI illness attributable to these events. https://doi.org/10.1289/EHP10399.
As the effects of climate change become more widespread and significant, communities least able to respond are bearing the largest burden. In the United States, communities disadvantaged by a legacy of racial segregation and environmental injustice struggle with disparate health outcomes, are vulnerable to the effects of climate change (e.g., severe flooding in low-lying areas and extreme heat in urban neighborhoods), and lack sufficient resources to recover from and rebuild for resilience against future events. On October 12 and 14, 2021, the 2-day virtual workshop “Communities, Climate Change, and Health Equity – A New Vision” brought together environmental health experts, resilience practitioners, climate scientists, and people with lived experience to discuss the disproportionate impact of climate change on communities experiencing health disparities and environmental injustice. During the workshop, the first in a four-part series, 41 speakers shared their perspectives on the topic and suggested specific actions that decision-makers can take to address the intersecting crises of climate change and health inequity. This publication summarizes the presentation and discussion of the workshop.
Places around the world already experience significant damage from climate change–related weather events, economic disruption, and health impacts, exacerbated by poverty, segregation, and inequitable infrastructure. Unfortunately, Texas provides a perfect illustration of these forces, with impacts made even more severe by a lack of climate planning. How can planners minimize harm and reduce risk, given the state leadership’s unwillingness to undertake climate planning? One place to start is to investigate residents’ climate change beliefs to understand whether they share the state’s climate antagonism and then use this information to shape a planning response. In this study, I analyzed a survey (n = 1,053) to ask: What are Texans’ perceptions of climate change, and how can planners use this knowledge to create strategies to catalyze climate planning? Respondents expressed strong agreement about negative effects of climate change and increased frequency of extreme weather. They believed that climate change is due at least in part to human activity, and they expressed robust support for climate-related planning activities. These responses sharply differ from the state’s approach. However, despite agreement about climate issues, respondents did not identify climate change as a major concern about the future. This contrast suggests an opportunity for new climate-related communication frames to bridge the gap between climate perceptions and planning action.
Knowledge of the health impacts of environmental exposures (such as pollution disasters, poor air quality, water contamination, climate change) on children’s health has dramatically increased in the past 40 years. The World Health Organization (WHO) estimated that 23% of all deaths worldwide were attributable to the environment, and 26% of deaths in children less than 5 years old could be prevented with removal of environmental risks factors. Yet, little has permeated medical education, leaving pediatric providers ill equipped to address these issues. To address this gap, members from the Pediatric Environmental Health Specialty Units, a United States nationwide network of academically affiliated experts who have created numerous environmental health educational materials and programs, have identified fifteen core environmental health (EH) competencies needed by health care providers to enable them to effectively address environmental health concerns. These competencies can serve as the foundation for the development and implementation of relevant educational programs. The core EH competencies are based upon these foundational elements: 1) Definition of “children’s environmental health” that describes how environmental exposures (positive and negative) in early life influence the health and development in childhood and across the entire human life span 2) Children are not “little adults” and so have unique vulnerabilities to environmental hazards; 3) Environmental health inequities exist, causing some children to have a disproportionate amount of unhealthy exposures and consequently a greater risk of adverse effects; 4) Climate change will translate to numerous adverse health effects that will particularly affect children worldwide. In this article, the authors describe the core environmental health competencies and provide resources, online tools, strategies, and examples targeted to all levels of training and practice to better enable leaders and educators to bring this important content to the forefront.
A new dynamical core, known as the Finite-Volume Cubed-Sphere (FV3) and developed at both NASA and NOAA, is used in NOAA’s Global Forecast System (GFS) and in limited-area models for regional weather and air quality applications. NOAA has also upgraded the operational FV3GFS to version 16 (GFSv16), which includes a number of significant developmental advances to the model configuration, data assimilation, and underlying model physics, particularly for atmospheric composition to weather feedback. Concurrent with the GFSv16 upgrade, we couple the GFSv16 with the Community Multiscale Air Quality (CMAQ) model to form an advanced version of the National Air Quality Forecasting Capability (NAQFC) that will continue to protect human and ecosystem health in the US. Here we describe the development of the FV3GFSv16 coupling with a “state-of-the-science” CMAQ model version 5.3.1. The GFS-CMAQ coupling is made possible by the seminal version of the NOAA-EPA Atmosphere-Chemistry Coupler (NACC), which became a major piece of the next operational NAQFC system (i.e., NACC-CMAQ) on 20 July 2021. NACC-CMAQ has a number of scientific advancements that include satellite-based data acquisition technology to improve land cover and soil characteristics and inline wildfire smoke and dust predictions that are vital to predictions of fine particulate matter (PM(2.5)) concentrations during hazardous events affecting society, ecosystems, and human health. The GFS-driven NACC-CMAQ model has significantly different meteorological and chemical predictions compared to the previous operational NAQFC, where evaluation of NACC-CMAQ shows generally improved near-surface ozone and PM(2.5) predictions and diurnal patterns, both of which are extended to a 72 h (3 d) forecast with this system.
Analyses of the relationships between climate, air substances and health usually concentrate on urban environments because of increased urban temperatures, high levels of air pollution and the exposure of a large number of people compared to rural environments. Ongoing urbanization, demographic ageing and climate change lead to an increased vulnerability with respect to climate-related extremes and air pollution. However, systematic analyses of the specific local-scale characteristics of health-relevant atmospheric conditions and compositions in urban environments are still scarce because of the lack of high-resolution monitoring networks. In recent years, low-cost sensors (LCS) became available, which potentially provide the opportunity to monitor atmospheric conditions with a high spatial resolution and which allow monitoring directly at vulnerable people. In this study, we present the atmospheric exposure low-cost monitoring (AELCM) system for several air substances like ozone, nitrogen dioxide, carbon monoxide and particulate matter, as well as meteorological variables developed by our research group. The measurement equipment is calibrated using multiple linear regression and extensively tested based on a field evaluation approach at an urban background site using the high-quality measurement unit, the atmospheric exposure monitoring station (AEMS) for meteorology and air substances, of our research group. The field evaluation took place over a time span of 4 to 8 months. The electrochemical ozone sensors (SPEC DGS-O3: R(2): 0.71-0.95, RMSE: 3.31-7.79 ppb) and particulate matter sensors (SPS30 PM1/PM2.5: R(2): 0.96-0.97/0.90-0.94, RMSE: 0.77-1.07 µg/m(3)/1.27-1.96 µg/m(3)) showed the best performances at the urban background site, while the other sensors underperformed tremendously (SPEC DGS-NO2, SPEC DGS-CO, MQ131, MiCS-2714 and MiCS-4514). The results of our study show that meaningful local-scale measurements are possible with the former sensors deployed in an AELCM unit.
INTRODUCTION: Climate change is a global public health emergency causing extensive morbidity and mortality worldwide. Although most large medical organizations endorse the need to train health care professionals in climate change, such trainings are not readily available. METHODS: This article describes the results of an 8-week, 75-min per week, Climate Change and Human Health ECHO (CCHH ECHO) synchronous telementoring course for post-licensure health professionals. The primary goals were: to increase knowledge, self-efficacy, and communication skills. Participants were eligible to receive up to 10 h of no-cost continuing education credits and a certificate for completing the program. RESULTS: The 8-week course included 625 unique participants from 25 countries. An interprofessional group of clinicians, health professionals, and educators included: 130/28% PhD, 92/20% MD/DO, 52/12% RN/NP/PA, 50/11% MPH. The prospective survey demonstrated a significant improvement in knowledge, confidence, attitudes (P < .001) and communication skills (P = .029) at 3 months post course. CONCLUSIONS: The climate crisis is a public health emergency, and health professionals worldwide are considered the most trusted source of health information. Training current and future health professionals regarding the health-related effects of global warming is vital. The CCHH ECHO may be a successful model to facilitate knowledge transfer and promote communication skills between subject matter experts and course participants.
Introduction Sickle cell disease (SCD) is characterized by acute vaso-occlusive crisis (VOC) often manifested as painful episodes. Environmental factors are known to play a role in the frequency and severity of VOC. Methods The aim of this study is to analyze the relationship between weather changes and VOC in children with SCD. Data on daily temperature, humidity, and wind speed in Brooklyn, New York was collected over one year. Daily census data of children < 20 years of age with SCD presenting with VOC during the study period was retrieved from the Health Information Systems database. Data was analyzed to determine correlations of daily temperature, humidity, and wind speed with the number of VOCs using Pearson correlation co-efficient and time-series statistics. Results The total number of episodes of VOC was 344, with 218 outpatients and 126 inpatients. Total episodes of VOC peaked during January (n=44), while they were lowest in July (n=16). We observed a negative correlation of VOC with temperature (r= -0.05, p=0.04) and no correlation with humidity (r=0.01, p=0.85) was noted. Analysis of wind speed showed a negative correlation with VOC which is not significant. Conclusion No significant correlation was found between changes in humidity or wind speed and VOC. As this study was performed in an urban environment with extreme weather changes, results may be different in other geographic areas.
The disaster cycle involves four phases: preparation, response, recovery, and mitigation. The cycle illustrates the steps that emergency managers take when planning for and responding to a disaster. Preparation is the phase where response plans are constructed. The response is the phase where there is immediate action to limit the hazards created by the disaster. Recovery is the effort to return a community to pre-disaster levels of functioning. Mitigation is the phase where new measures are undertaken to prevent or minimize the effects of future disasters. Some sources refer to the mitigation phase as “prevention.” To meaningfully discuss disaster response, it is essential also to discuss disaster and disaster management. Though there exists no consensus definition of disaster, the various definitions published by organizations and agencies at the forefront of disaster management have overlapping concepts. A disaster is a state in which the usual, normal day-to-day human activities within a determined geographic area cease indefinitely. It is defined by a severe disruption in the basic structure and function of a society. This abnormal state is triggered by some extraordinary circumstance, either occurring naturally or as the result of human activity. A disaster is the consequence of a sudden event or series of events of grand magnitude, which results in injury, disease, illness, loss of life, destruction of property, and/or damage to critical infrastructure and essential services. The precipitating event may be natural, i.e., natural disasters (e.g., tornado, hurricane, drought, famine, earthquake, landslides, infectious disease outbreaks, etc.) or man-made. Man-made events may be unintentional (fires, building collapses, nuclear reactor meltdowns) or intentional (terrorism, sabotage, cyber-attacks, conflict-based). In recent times, both man-made and natural disasters have occurred at an increasing frequency. Due to its scale and dimension, a disaster exceeds the emergency management capacity of local organizations and agencies, thus necessitating external assistance. That assistance may come from the state, national, and/or international levels. The rapid, immediate, and short-term actions circumjacent to a disaster are known as disaster response. Disaster response is one of the core activities of disaster management. It involves the execution of a disaster plan in the event of a disaster.
OBJECTIVE: The healthcare system accounts for 8%-10% of all greenhouse gas emissions in the United States and hospital buildings are significant contributors. Operating rooms account for 20%-33% of all hospital waste. This may contribute to significant climate change and negatively affect public health. Physicians and surgeons must act to reduce our collective carbon footprint to improve the health of our patients. The traditional graduate medical education curriculum does not routinely train future generations of physicians in healthcare sustainability. We describes a fellowship program designed to change this. DESIGN AND SETTING: The Cleveland Clinic surgical residency has implemented a unique educational program. Here we describe the 5-year results of our novel fellowship program in health care sustainability, primarily focused on greening the operating room. PARTICIPANTS: Selected General Surgery residents interested in healthcare sustainability and greening the operating room. RESULTS: We have successfully implemented a novel resident focused fellowship program in healthcare sustainability. Fellowship projects have led to significant reductions in our hospitals’ collective carbon footprint. CONCLUSIONS: Surgeons have a unique responsibility to reduce the carbon footprint of the Operating Room. Implementing a dedicated fellowship program or similar intensive educational experience in healthcare sustainability within the framework of a graduate medical education curriculum will help to ensure future generations of surgeons are thoughtful leaders in environmental stewardship.
We estimate how the mortality effects of temperature vary across U.S. climate regions to assess local and national damages from projected climate change. Using 22 years of Medicare data, we find that both cold and hot days increase mortality. However, hot days are less deadly in warm places while cold days are less deadly in cool places. Incorporating this heterogeneity into end-of-century climate change assessments reverses the conventional wisdom on climate damage incidence: cold places bear more, not less, of the mortality burden. Allowing places to adapt to their future climate substantially reduces the estimated mortality effects of climate change.University of Illinois and NBER.
BACKGROUND: There is overwhelming evidence the impacts of climate change present a probable threat to personal health and safety. However, traditional risk management approaches have not been applied to ameliorate the crises. The purpose of this study was to assess the impact on personal motivation for action of a communication intervention that framed climate change as a safety issue that can be mitigated through a safety and health risk management framework. Participants’ perception of climate change in terms of its anthropogenicity, context and importance, perception as a personal threat, belief in the efficacy of human action, motivating drivers for action, knowledge of climate change impacts, perceived personal barriers to climate action, and short- and long-term preferences for mitigating actions were evaluated. In addition, this study assessed the role of personal worldview on motivation for climate action. METHODS: Through an online survey instrument embedded with a communication/education intervention, data were collected from N = 273 participants. Pre and post-intervention responses were assessed using Wilcoxon signed-rank tests and descriptive statistics. A path analysis assessed the influence of anthropogenicity, personal impact, and human efficacy beliefs on participant motivation for action. Multi-regression analyses and descriptive statics were used to evaluate the role of worldview on participant motivation for climate action. RESULTS: Personal motivation for action significantly increased post-intervention. Anthropogenicity, personal impact, and human efficacy beliefs were predictive of personal motivation. Those who prioritized climate change as a safety issue and those driven by a desire to protect current and future generations had higher levels of personal motivation, post-intervention. Knowledge of climate change increased, psychosocial factors as barriers to climate action decreased, and preferences for personal mitigating actions shifted towards more impactful choices post-intervention. Holding Egalitarian worldviews significantly predicted climate action motivation. CONCLUSION: Presenting climate change and climate action strategies via a traditional health and safety risk management context was effective in increasing personal motivation for climate action. This study contributes to the literature on climate change communication and climate action motivation.
The Environmental Justice Small Grants (EJSG) Program provides funding directly to community-based organizations and tribes for projects that help residents of underserved communities understand and address local environmental and public health issues. The term “underserved community” refers to a community with environmental justice concerns and/or vulnerable populations, including people of color, low income, rural, tribal, indigenous, and homeless populations. The long-term goals of the program are to support underserved communities in their efforts to build their overall capacity and create self-sustaining, community-based partnerships that will improve local environments in the future. In 2021, 99 organizations nationwide were selected to receive awards totaling approximately $7.4 million in grant funding. Individual grants are for up to $75,000 each for one-year projects. These grants will benefit communities in 37 different states, as well as Washington DC and Puerto Rico.
The resilience of communities has emerged as a major goal in policy and practice. Cities, states, and counties within the United States and around the world are passing laws requiring the incorporation of climate-related hazard vulnerability assessments within their master plan updates for resilience planning and design. The resilience of communities under present and future scenarios is thus becoming a cornerstone of decision making and actions. Decisions that would enhance resilience, however, span multiple sectors and involve various stakeholders. Quantifying community resilience is a key step in order to describe the preparedness level of communities, and subsequently locating non-resilient areas to further enhance their capacity to endure disasters. Two main approaches are currently being pursued to evaluate resilience. The first approach is the “community resilience” developed mainly by social scientists and planners, and it captures social resilience using numerous pre-disaster attributes to describe the functioning of a community. This approach subsumes that pre-disaster attributes can predict the community resilience to a disaster. The second approach is adopted for infrastructure resilience, mostly used by engineers, and it focuses on robustness, redundancy, resourcefulness, and rapidity. This approach is appropriate for systems that are operated by highly skilled personnel and where the actions are of engineering type. In this paper, we provide an overview of the two approaches, and we leverage their limitations to propose a hybrid approach that combines community and infrastructure capitals into an Area Resilience metric, called ARez. ARez captures the role/impact of both infrastructure and community and combines five sectors: energy, public health, natural ecosystem, socio-economic, and transportation. We present a proof-of-concept for the ARez metric, showing its practicality and applicability as a direct measure for resilience, over various time scales.
Approximately 2000 official and potential Superfund sites are located within 25 miles of the East or Gulf coasts, many of which will be at risk of flooding as sea levels rise. More than 60 million people across the United States live within 3 miles of a Superfund site. Disentangling multifaceted environmental health problems compounded by climate change requires a multidisciplinary systems approach to inform better strategies to prevent or reduce exposures and protect human health. The purpose of this minireview is to present the National Institute of Environmental Health Sciences Superfund Research Program (SRP) as a useful model of how this systems approach can help overcome the challenges of climate change while providing flexibility to pivot to additional needs as they arise. It also highlights broad-ranging SRP-funded research and tools that can be used to promote health and resilience to climate change in diverse contexts.
The rapid emergence of the COVID-19 pandemic and the insidiously evolving climate crisis represent two of the most pressing public health threats to Indigenous Peoples in the United States. Understanding the ways in which these syndemics uniquely impact Indigenous Peoples, given the existing health disparities for such communities, is essential if we are to address modifiable root causes of health vulnerability and devise effective and equitable strategies to protect and improve health in the evolving climate landscape. We explore the compounding burden of the COVID-19 pandemic and climate change on Indigenous Peoples’ health, and present several case studies which outline novel Indigenous approaches and perspectives that address climate change, COVID-19 and future health threats.
This memorandum recommends approaches for U.S. Environmental Protection Agency (EPA or Agency) regions to consider when evaluating climate resilience throughout the remedy selection and implementation process for sites proposed or currently listed on the National Priorities List (NPL) in accordance with the Comprehensive Environmental Response, Compensation, and Liability Act of 1980, as amended (CERCLA). Consideration of climate resilience in the Superfund cleanup process should be carried out in a manner consistent with CERCLA as well as the National Oil and Hazardous Substances Pollution Contingency Plan (NCP) and EPA policy and guidance documents. This memorandum supplements the Agency’s existing policy statements addressing climate
resilience activities, tools, considerations and technical information found in fact sheets; however, it does not amend or modify the NCP in any way. Consideration of climate resilience should not be treated as a new criterion under 40 CFR §300.430(e)(9)(iii)).
Communities in the United States are increasingly dependent upon aging infrastructure systems and challenged by more frequent and intense extreme weather events due in part to climate change. However, prioritizing resilience-related investments in these systems is hindered by the lack of performance metrics that objectively quantify the societal outcomes of infrastructure disruptions, such as power or water outages. This article outlines the process of developing an equity-focused resilience metric that captures the social consequences of infrastructure service disruptions on households. Theoretically grounded in the Capabilities Approach (CA) theory of human development, this metric focuses on estimating the burden of post-event adaptations taken by households to maintain their basic capabilities (e.g., ability to access food and water) and fulfill important household functionings (e.g., maintaining health and well-being). A travel cost method (TCM) that considers travel-related expenses, direct out-of-pocket expenses, and opportunity costs is presented as a way to measure the value of locations (e.g., grocery stores, emergency shelters, etc.) that provide services that enable households to maintain capabilities. A gravity-weighted model of accessibility is also discussed as a way to capture the value of having multiple potential service locations from which to choose and offers a way to capture important factors impacting a household’s ability to access important goods and services during outages. The proposed social burden metric equation incorporates the valuation principles of the TCM into the framework of the gravity model, resulting in a novel metric with strong methodological heritage. The article concludes by discussing the types of data needed to populate the proposed metric and future applications of this work that could inform the resilient infrastructure investments and planning necessary to mitigate the social burdens of power outages on vulnerable populations.
This report provides a vital snapshot of the overall progress that governments have made in the field of health and climate change to date, as well as insight into what work remains in order to protect their populations from the most devastating health impacts of climate change. The health and climate change country survey is conducted every three years and in addition to tracking global progress, the national data are presented in the health and climate change country profiles. 95 countries participated in the 2021 survey. The survey is sent to the national health authorities, who in collaboration with other relevant ministries and stakeholders, provide updated information on key areas including: leadership and governance, national vulnerability and adaptation assessments, emergency preparedness, disease surveillance, adaptation and resilience measures, climate and health finance, and mitigation in the health sector. Regular updates on key health and climate change indicators provide insight into the implementation of policies and plans, the status of assessments of health vulnerability and capacity to respond to climate change and better understand the barriers to achieving health adaptation and mitigation priorities. The 2021 global survey report provides an update to the 2017/2018 survey, and was published at the COP26 UN climate conference in November 2021.
BACKGROUND: Left unabated, rising temperatures pose an escalating threat to human health. The potential effects of hot temperatures on fetal health have been under-explored. Here, we examined the association between prenatal ambient temperature exposure and fetal growth measures in a Massachusetts-based pregnancy cohort. METHODS: We used ultrasound measurements of biparietal diameter (BPD), head circumference (HC), femur length and abdominal circumference (AC), in addition to birthweight (BW), from 9446 births at Beth Israel Deaconess Medical Center from 2011 to 2016. Ultrasound scans were classified into three distinct gestational periods: 16-23 weeks, 24-31 weeks, 32+ weeks; and z-scores were created for each fetal growth measure using the INTERGROWTH-21st standards. We fitted distributed lag models to estimate the time-varying association between weekly temperature and fetal growth, adjusting for sociodemographic characteristics, seasonal and long-term trends, humidity and particulate matter (PM2.5). RESULTS: Higher ambient temperature was associated with smaller fetal growth measures. The critical window of exposure appeared to be Weeks 1-20 for ultrasound parameters, and high temperatures throughout pregnancy were important for BW. Associations were strongest for head parameters (BPD and HC) in early to mid-pregnancy, AC late in pregnancy and BW. For example, a 5ºC higher cumulative temperature exposure was associated with a lower mean AC z-score of -0.26 (95% CI: -0.48, -0.04) among 24-31-Week scans, and a lower mean BW z-score of -0.32 (95% CI: -0.51, -0.12). CONCLUSION: Higher temperatures were associated with impaired fetal growth. This has major health implications given that extreme temperatures are more common and escalating.
A Code Red has been declared for the planet and human health. Climate change (e.g., increasing temperatures, adverse weather events, rising sea levels) threatens the planet’s already declining ecosystems. Without urgent action, all of Earth’s inhabitants face an existential threat. Health professions education should therefore prepare learners to not only practice in a changing world, but authentic educational activities should also develop competencies for global and planetary citizenship. Planetary health has been integrated across the five-year Bond University (Australia) medical curriculum. It begins in the second week of Year 1 and ends with a session on Environmentally Sustainable Healthcare in the General Practice rotation in the final year. The purpose of this article is to describe the outcomes of the first 5 years (2018-2022) of a learner-centered planetary health assignment, underpinned by the 2030 United Nations (UN) Sustainable Development Goals (SDGs), in the second year of a five-year medical program. Using systems and/or design thinking with a focus on SDG13 (Climate Action) plus a second SDG of choice, self-selected teams of 4-6 students submit a protocol (with feedback) to develop a deliverable “product” for an intended audience. Data analysis of the first 5 years of implementation found that the most frequently selected SDGs in addition to SDG13 were: SDG12 Sustainable Production and Consumption (41% of teams), mostly relating to healthcare emissions and waste; SDG3 Health and Well-being (22%), generally involving the impact of air pollution; and SDG6 Clean Water and Sanitation (15%). A survey at the concluding conference garnered student feedback across various criteria. The planetary health assignment is authentic in that teams provide solutions to address climate change. Where appropriate, final “products” are sent to local or federal ministers for consideration (e.g., policy proposals) or integrated into the curriculum (e.g., learning modules). We believe that the competencies, attitudes, and values fostered through engagement with planetary health. Throughout the medical program, as evidenced by their evaluations, stands students in good stead to be change agents, not only in clinical practice but in society. An awareness has been created about the need for planetary citizenship in addition to global citizenship.
Big data analytics, an emerging and most useful technology in the field of data analysis dealing with huge quantity of data, is used in this paper for exploring the domain and the repercussions of climate change with its adverse effects on health. Humans have failed until now to prevent the generation of greenhouse gases in the stratosphere which does not allow us to prevent health impacts that climate change is likely to direct upon humans and cause of global warming. Mining of climate, temperature, global health and death dataset, helps in visualization of data and the clear analysis of the problem. Technologies, related to the Big Data field, have been applied for analyzing and drawing correlations among radical features which are causing climate change. The first is the use of pollution datasets in different cities of the United States. The second technology used is Global temperature analysis with the help of datasets of different chronological timelines and the third is NCHS Leading causes of deaths in the United states using demographic and medical characteristics, Decision tree modeling using ML LIB is one of the key features in proper analysis.
Contaminated groundwater is a priority issue on the environmental agendas of developed countries. Therefore, there is an obvious need to develop instruments and decision-making mechanisms that allow the estimation of the risk to human health due to the presence of contaminants in soils and groundwater, in a fast and reliable manner. Thus, this study aims to assess whether the spilling of hydraulic fracturing fluids prior to injection has a potential risk to groundwater quality in the Kern County Sub-basin, California, by identifying the hydrological factors and solute transport characteristics that control these risks while taking into consideration the temperature rises due to climate change. The approach uses the concept of the groundwater pollution risk based on comparing the concentration of pollutants within the water table by using a predetermined permissible level. The current average annual temperature and that by the end of the 21st century was used to estimate the diffusion of benzene through three types of soil by using HYDRUS-1D software. The software was used to predict the contaminant concentration profile of benzene in the water table with special reference to the impact of surface temperatures. The results showed that an expected rise of the surface temperature by 4.3 °C led to an increase in the concentration of benzene by 2.3 μg/l in sandy loam soil, 6.8 μg/l in silt loam soil, and finally, 2.6 μg/l in loam soil. The results show that climate change can substantially affect soil properties and their chemical constituents, which then play a major role in absorbing pollutants.
Our endocrine system is not only complex, but is also enormously sensitive to the imbalances caused by the environmental stressors, extreme weather situation, and other geographical factors. The endocrine disruptions are associated with the bone diseases. Osteoporosis is a bone disorder that occurs when bone mineral density and bone mass decrease. It affects women and men of all races and ethnic groups, causing bone weakness and the risk of fractures. Environmental stresses are referred to physical, chemical, and biological factors that can impact species productivity. This research aims to examine the impact of environmental stresses on bone diseases like osteoporosis and low bone mass (LBM) in the United States (US). For this purpose, we use an artificial neural network model to evaluate the correlation between the data. A multilayer neural network model is constructed using the Levenberg-Marquardt training algorithm, and its performance is evaluated by mean absolute error and coefficient of correlation. The data of osteoporosis and LBM cases in the US are divided into three groups, including gender group, age group, and race/ethnicity group. Each group shows a positive correlation with environmental stresses and thus the endocrinology.
IMPORTANCE Acute appendicitis is a common cause of abdominal pain and the most common reason for emergency surgery in several countries. Increased cases during summer months have been reported. OBJECTIVE To investigate the incidence of acute appendicitis by considering local temperature patterns in geographic regions with different climate over several years. DESIGN, SETTING, AND PARTICIPANTS This cohort study used insurance claims data from the MarketScan Commercial Claims and Encounters Database and the Medicare Supplemental and Coordination of Benefits Database from January 1, 2001, to December 31, 2017. The cohort included individuals at risk for appendicitis who were enrolled in US insurance plans that contribute data to the MarketScan databases. Cases of appendicitis in the inpatient, outpatient, and emergency department settings were identified using International Classification of Diseases, Ninth Revision, Clinical Modification or International Statistical Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes. Local weather data were obtained for individuals living in a metropolitan statistical area (MSA) from the Integrated Surface Database. Associations were characterized using a fixed-effects generalized linear model based on a negative binomial distribution. The model was adjusted forage, sex, and day of week and included fixed effects for year and MSA. The generalized linear model was fit with a piecewise linear model by searching each 0.56 degrees C in temperature for change points. To further isolate the role of temperature, observed temperature was replaced with the expected temperature and the deviation of the observed temperature from the expected temperature for a given city on a given day of year. Data were analyzed from October 1, 2021, to July 31, 2022. MAIN OUTCOMES AND MEASURES The primary outcome was the daily number of appendicitis cases in a given city stratified by age and sex, with mean temperature in the MSA over the previous 7 days as the independent variable. RESULTS A total of 450 723 744 person-years at risk and 689 917 patients with appendicitis (mean [SD] age, 35 [18] years; 347 473 male [50.4%] individuals) were included. Every 5.56 degrees C increase in temperature was associated with a 1.3% increase in the incidence of appendicitis (incidence rate ratio [IRR]. 1.01; 95% CI, 1.01-1.02) when temperatures were 10.56 degrees C or lower and a 2.9% increase in incidence (IRR, 1.03; 95% CI, 1.03-1.03) for temperatures higher than 10.56 degrees C. In terms of temperature deviations, a higher-than-expected temperature increase greater than 5.56 degrees C was associated with a 3.3% (95% CI, 1.0%-5.7%) increase in the incidence of appendicitis compared with days with near-0 deviations. CONCLUSIONS AND RELEVANCE Results of this cohort study observed seasonality in the incidence of appendicitis and found an association between increased incidence and warmer weather. These results could help elucidate the mechanism of appendicitis.
Climate change is increasingly recognized for its impacts on human health, including how biotic and abiotic factors are driving shifts in infectious disease. Changes in ecological conditions and processes due to temperature and precipitation fluctuations and intensified disturbance regimes are affecting infectious pathogen transmission, habitat, hosts, and the characteristics of pathogens themselves. Understanding the relationships between climate change and infectious diseases can help clinicians broaden the scope of differential diagnoses when interviewing, diagnosing, and treating patients presenting with infections lacking obvious agents or transmission pathways. Here, we highlight key examples of how the mechanisms of climate change affect infectious diseases associated with water, fire, land, insects, and human transmission pathways in the hope of expanding the analytical framework for infectious disease diagnoses. Increased awareness of these relationships can help prepare both clinical physicians and epidemiologists for continued impacts of climate change on infectious disease in the future.
BACKGROUND: Climate change is a defining issue and grand challenge for the health sector in North America. Synthesizing evidence on climate change impacts, climate-health adaptation, and climate-health mitigation is crucial for health practitioners and decision-makers to effectively understand, prepare for, and respond to climate change impacts on human health. This protocol paper outlines our process to systematically conduct a literature review to investigate the climate-health evidence base in North America. METHODS: A search string will be used to search CINAHL®, Web of Science™, Scopus®, Embase® via Ovid, and MEDLINE® via Ovid aggregator databases. Articles will be screened using inclusion/exclusion criteria by two independent reviewers. First, the inclusion/exclusion criteria will be applied to article titles and abstracts, and then to the full articles. Included articles will be analyzed using quantitative and qualitative methods. DISCUSSION: This protocol describes review methods that will be used to systematically and transparently create a database of articles published in academic journals that examine climate-health in North America.
The Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (2014) assessed the state of climate change and health knowledge, globally through the Human Health: Impacts, Adaptation, and Co-Benefits Chapter and regionally through chapters, such as the North America Chapter. With IPCC’s 6th Assessment Report scheduled to be released in 2021-22, we asked: how has climate change and health research in North America advanced since the IPCC’s 5th Assessment Report in 2014? Specifically, we systematically identified and examined trends in the extent, range, and nature of climate-health research conducted in North America. We used a scoping review methodology to systematically identify literature and map publication trends. A search string was used to search five academic databases. Two independent reviewers first screened titles and abstracts, and then the full texts of articles for relevance. Research articles and reviews using systematic methods published since 2013 were eligible for inclusion, and no language restrictions were applied. To be included, articles had to measure and link climatic variables or hazards to health outcomes in North America. Relevant articles were analysed using descriptive statistics to explore publication trends. The number of climate-health articles has significantly increased since the last IPCC Assessment Report. Published research about climate change impacts, heat-related mortality and morbidity, and respiratory illness taking place in urban centres and in the USA continue to dominate the North American climate-health literature, reflected by the high proportion of articles published. Important research gaps on previously neglected climate-sensitive health outcomes, however, are beginning to be filled, including climate change impacts on mental health, nutrition, and foodborne disease. We also observed progress in research that included future projections of climate-health risks; however, projection research is still relatively nascent and under-studied for many climate-sensitive health outcomes in North America, and would benefit from considering social and demographic variables in models. Important research disparities in geographical coverage were noted, including research gaps in Canada and Mexico, and in rural and remote regions. Overall, these publication trends suggest an improved understanding of exposure-response relationships and future projections of climate-health risks for many climate-sensitive health outcomes in North America, which is promising and provides an evidence-base to inform the IPCC 6th Assessment Report. Despite these advancements and considering the urgent policy and practice implications, more research is needed to deepen our understanding of climate-sensitive health outcomes, as well as examine new arising issues that have limited evidence-bases. In particular, transdisciplinary and cross-sector research, that includes the social sciences, examining current and future climate-health adaptation, mitigation, and the adaptation-mitigation nexus should become a top priority for research, given the urgent need for this evidence to inform climate change policies, actions, and interventions.
Rural populations experience underinvestment in communication and technology infrastructure that may contribute to an information gap about climate change and the relationship to health impacts in rural communities. This report describes how a student and nursing faculty member provided community edu-cation to 3 rural communities about how climate change impacts the health of rural communities through the local community newspaper serving the 3 communities. Climate and health-related topics in a weekly newspaper column in this project included extreme heat events, Lyme disease, air pollution, water quality, soil health, environmental justice, and the role of the nurse in planetary health.(c) 2021 Elsevier Inc. All rights reserved.
The current study uses pooled National Crime Victimization Survey data (1992-2015) to examine if the relationship between climate change and victimization risk is modified by victim and incident characteristics. Panel analysis yields interesting findings. First, results mirror those found in prior studies utilizing Uniform Crime Report data, providing another indication that the link between a warming climate and crime may be quite robust. Second, the results indicate that climatic effects may play out differently in different contexts. For example, outdoor victimizations, especially those near a person’s residence, appear increasingly elastic during anomalously warm temperatures. In addition, subpopulations (males and African Americans) are also at increased risk of victimization. Our results effectively suggest that at-risk populations are more vulnerable to climatic variability.
Out of hospital cardiac arrest (OHCA) remains a leading cause of mortality among adults in the United States. Environmental impact on incidence and outcomes of OHCA has not been fully investigated in recent years. Previous studies showed a possible increase in incidence and mortality in winter season and during seasons with temperature extremes. This study examines seasonal variation in incidence and outcomes of OHCA in the United States.Retrospective study of adult OHCA using the Nationwide Emergency Department Sample was carried out. Monthly incidence rate per 100,000 ED presentations was calculated. Survival rates for each month of admission were examined by hospital region. Multivariate analyses were conducted to determine the effect of the season and month of admission on survival.A total of 122,870 adult OHCA cases presented to emergency departments (EDs) in 2014 and were included. Average incidence of OHCA cases was 147 per 100,000 ED presentations. Overall survival rate in the study population was 5.6% (95% confidence intervals [CI] = 5.4%-5.9%). Patients had an average age of 65.5 (95% CI: 65.3-65.7) years and were mainly men (61.8%). Rates of OHCA presentations were highest during December and January (9.9% and 10.0%) while survival rates were lowest during December (4.6%) and highest in June (6.9%). Regional variation in OHCA outcomes was also noted with highest average survival rate in West (7.8%) and lowest in South (4.3%). After adjusting for confounders including region of hospital, Summer season (Ref: all other seasons), and more specifically month of June (Ref: all other months) were found to be positively associated with survival (OR 1.27, 95% CI [1.07-1.52], P-value = .008) and (OR 1.43, 95% CI [1.08-1.89], P-value = .012 respectively).Incidence and outcomes of out of hospital cardiac arrest presentations to the emergency departments in the United States have seasonal variation. Both incidence and mortality of OHCA increase during colder months, and survival is significantly higher in summer season or in June. Exploring how to use this variation to improve outcomes through refresher training of medical providers or through other mitigation plans is needed.
BACKGROUND: Short-term temperature variability has been consistently associated with mortality, with limited evidence for cardiovascular outcomes. Previous studies have used multiple metrics to measure temperature variability; however, those metrics do not capture hour-to-hour changes in temperature. OBJECTIVES: We assessed the correlation between sub-daily temperature-change-over-time metrics and previously-used metrics, and estimated associations with myocardial infarction (MI) hospitalizations. METHODS: Hour-to-hour change-over-time was measured via three metrics: 24-hr mean absolute hourly first difference, 24-hr maximum absolute hourly first difference, and 24-hr mean hourly first difference. We first assessed the Spearman correlations between these metrics and four previously-used metrics (24-hr standard deviation of hourly temperature, 24-hr diurnal temperature range, 48-hr standard deviation of daily minimal and maximal temperatures, and 48-hr difference of daily mean temperature), using hourly data from the North America Land Data Assimilation System-2 Model. Subsequently, we estimated the association between these metrics and primary MI hospitalization in adult residents of New York State for 2000-2015 using a time-stratified case-crossover design. RESULTS: The hour-to-hour change-over-time metrics were correlated, but not synonymous, with previously-used metrics. We observed 809,259 MI, 45% of which were among females and the mean (standard deviation) age was 70 (15). An increase from mean to 90th percentile in mean absolute first difference of temperature was associated with a 2.04% (95% Confidence Interval [CI]: 1.30-2.78%) increase in MI rate. An increase from mean to 90th percentile in mean first difference also yielded a positive association (1.86%; 95%CI: 1.09-2.64%). We observed smaller- or similar-in-magnitude positive associations for previously-used metrics. DISCUSSION: First, short-term hour-to-hour temperature change was positively associated with MI risk. Second, all other variability metrics yielded positive associations with MI, with varying magnitude. In future research on temperature variability, researchers should define their research question, including which aspects of variability they intend to measure, and apply the appropriate metric. ALTERNATIVE: All metrics of temperature variability, including short-term hour-to-hour temperature changes, were positively associated with MI risk, though the magnitude of effect estimates varied by metric.
Many diseases have been linked with birth seasonality, and these fall into four main categories: mental, cardiovascular, respiratory and women’s reproductive health conditions. Informatics methods are needed to uncover seasonally varying infectious diseases that may be responsible for the increased birth month-dependent disease risk observed. We have developed a method to link seasonal infectious disease data from the USA to birth month dependent disease data from humans and canines. We also include seasonal air pollution and climate data to determine the seasonal factors most likely involved in the response. We test our method with osteosarcoma, a rare bone cancer. We found the Lyme disease incidence was the most strongly correlated significant factor in explaining the birth month-osteosarcoma disease pattern (R=0.418, p=2.80X10-23), and this was true across all populations observed: canines, pediatric, and adult populations.
Climate change is unarguably a critical existential threat to humanity in the 21st century. As the most abundant organisms on Earth, microorganisms make considerable contributions to and are greatly affected by a changing climate. Microbes are major drivers of elemental cycles (such are carbon, nitrogen, and phosphorus), important producers and consumers of greenhouse gases, and pertinent pathogens of humans, animals, and plants. While the threat of climate change looms large, conversations about the relationship between it and microorganisms are still rare outside of the microbial sciences community. To understand fully how our climate may change in the future, it is important to learn how a changing climate will impact microbes and their relationships with humans and their environment, as well as incorporate microbial processes into climate models. This report is based on the deliberations of experts who participated in a colloquium on 5 November 2021 organized by the American Academy of Microbiology, the honorific leadership group and think tank within the American Society for Microbiology. These experts came from diverse disciplines and sectors and provided multifaceted perspectives and insights. Over the course of the discussion, the group made several major recommendations for academic, policy, and market partners to promote innovation for microbe-driven climate change solutions that support human well-being.
Surgical site infections (SSI) are one of the most common and costly hospital-acquired infections in the United States. Meteorological variables such as temperature, humidity, and precipitation may represent a neglected group of risk factors for SSI. Using a national private insurance database, we collected admission and follow-up records for National Healthcare Safety Network-monitored surgical procedures and associated climate conditions from 2007 to 2014. We found that every 10 cm increase of maximum daily precipitation resulted in a 1.09 odds increase in SSI after discharge, while every g/kg unit increase in specific humidity resulted in a 1.03 odds increase in SSI risk after discharge. We identified the Southeast region of the United States at highest risk of climate change-related SSI, with an estimated 3% increase in SSI by 2060 under high emission assumptions. Our results describe the effect of climate on SSI and the potential burden of climate-change related SSI in the United States.
PURPOSE OF REVIEW: We review and analyze recent literature in public health, urban planning, and disaster management to better understand the relationships between climate change, natural disasters, and root causes of health disparities in the USA. RECENT FINDINGS: Existing scholarship establishes clear linkages between climate change and increasing occurrences and severity of natural disasters across the USA. The frequency and types of disasters vary by region and impact both short and long-term health outcomes. Current research highlights health inequities affecting lower income and minoritized communities disproportionately, but data-driven studies critically examining the role of structural inequalities in climate-induced health disparities are sparse. Adding to the body of knowledge, our conceptual framework maps how long-standing structural inequalities in policy, practice, and funding shape vulnerability of lower-income, racially and ethnically marginalized individuals. Vulnerability follows three common pathways: disparities in “exposure”, “sensitivity”, and “resiliency” before, during, and after a climate disaster. We recommend that future research, policy, and practice shift towards solutions that unearth and address the structural biases that cause environmental disaster and health inequities.
Pediatric populations are expected to bear most of the climate change impacts, with racial minorities and children living in poorer countries being particularly vulnerable. Given their relevance to cutaneous disease, dermatologists should be aware of these climate-sensitive health impacts and the ways in which they intersect with social factors. Strategies including targeted risk communication, motivational interviewing, and storytelling can help facilitate climate discussions during the patient encounter. In this article the authors summarize common dermatologic health impacts related to environmental exposures and provide sample scripts for climate messaging.
BACKGROUND: Emergency medical services (EMS) response volume has been linked to weather and temporal factors in a regional EMS system. We aimed to identify if models of EMS utilization incorporating these data are generalizable through geographically disparate areas in the United States. METHODS: We performed a retrospective analysis of EMS dispatch data from four regions: New York City, San Francisco, Cincinnati, and Marin County for years 2016-2019. For each model, we used local weather data summarized from the prior 6 h into hourly bins. Our outcome for each model was EMS dispatches as count data. We fit and optimized a negative binomial regression model for each region, to estimate incidence rate ratios. We compared findings to a prior study performed in Western Pennsylvania. RESULTS: We included 5,940,637 EMS dispatches from New York City, 809,405 from San Francisco, 260,412 from Cincinnati, and 77,461 from Marin County. Models demonstrated consistency with the Western Pennsylvania model with respect to temperature, season, wind speed, dew point, and time of day; both in terms of direction and effect size when expressed as incidence rate ratios. Precipitation was associated with increasing dispatches in the New York City, Cincinnati, and Marin County models, but not the San Francisco model. CONCLUSION: With minor differences, regional models demonstrated consistent associations between dispatches and time and weather variables. Findings demonstrate the generalizability of associations between these variables with respect to EMS use. Weather and temporal factors should be considered in predictive modeling to optimize EMS staffing and resource allocation.
An extensive review of new resources to support the provision of evidence-based care for women and infants. The current column includes a discussion of men’s experiences of pregnancy loss and commentaries on reviews focused on the effects of perineal massage on perineal trauma and air pollution and heat exposure on birth outcomes.
Previous research on health effects of extreme weather has emphasized heat events even though cold-attributable mortality exceeds heat-attributable mortality worldwide. Little is known about the mental health effects of cold weather events, which often cascade to produce secondary impacts like power outages, leaving a knowledge gap in context of a changing climate. We address that gap by taking a novel “cascading disaster health inequities” approach to examine winter storm-associated post-traumatic stress (PTS) using survey data (n = 790) collected in eight Texas metro areas following Winter Storm Uri in 2021, which occurred against the backdrop of COVID-19. The incidence of storm-related PTS was 18%. Being Black (odds ratio [OR]: 6.6), Hispanic (OR: 3.5), or of another non-White race (OR: 4.2) was associated with greater odds of PTS compared to being White, which indicates substantial racial/ethnic inequities in mental health impacts (all p < 0.05). Having a disability also increased odds of PTS (OR: 4.4) (p < 0.05). Having piped water outages (OR: 1.9) and being highly impacted by COVID-19 (OR: 3.3) increased odds of PTS (both p < 0.05). When modelling how COVID-19 and outages cascaded, we compared householders to those with no outages and low COVID-19 impacts. PTS was more likely (p < 0.05) if householders had a water or power outage and high COVID-19 impacts (OR: 4.4) and if they had water and power outages and high COVID-19 impacts (OR: 7.7). Findings provide novel evidence of racial/ethnic inequities and cascading effects with regard to extreme cold events amid the COVID-19 pandemic.
Eco-concern, the distress experienced relating to climate change, is associated with mental health, yet no study has examined disordered eating related to eco-concern. This study developed and validated a 10-item scale assessing Eating-Related Eco-Concern (EREC). Participants (n = 224) completed the EREC, Climate Change Worry Scale (CCWS), and Eating Disorder Examination-Questionnaire (EDE-Q). Construct validity, convergent validity, and internal consistency were evaluated. Sex differences in EREC were evaluated using t-tests. Associations among the EREC, CCWS, and EDE-Q were evaluated using linear regression models. Sensitivity analyses were conducted in individuals below EDE-Q global score clinical cut-offs. Factor analysis suggested that all items loaded adequately onto one factor. Pearson’s correlation and Bland-Altman analyses suggested strong correlation and acceptable agreement between the EREC and CCWS (r = 0.57), but weak correlation and low agreement with the EDE-Q global score (r = 0.14). The EREC had acceptable internal consistency (α = 0.88). No sex difference was observed in the EREC in the full sample; females had a significantly higher mean score than males in sensitivity analysis. The EREC was significantly positively associated with the CCWS and EDE-Q global and shape concern scores, but not in sensitivity analysis. The EREC is a brief, validated scale that can be useful to screen for eating-related eco-concern.
BACKGROUND: Suicide is among the top 10 leading causes of premature morality in the United States and its rates continue to increase. Thus, its prevention has become a salient public health responsibility. Risk factors of suicide transcend the individual and societal level as risk can increase based on climatic variables. The purpose of the present study is to evaluate the association between average temperature and suicide rates in the five most populous counties in California using mortality data from 1999 to 2019. METHODS: Monthly counts of death by suicide for the five counties of interest were obtained from CDC WONDER. Monthly average, maximum, and minimum temperature were obtained from nCLIMDIV for the same time period. We modelled the association of each temperature variable with suicide rate using negative binomial generalized additive models accounting for the county-specific annual trend and monthly seasonality. RESULTS: There were over 38,000 deaths by suicide in California’s five most populous counties between 1999 and 2019. An increase in average temperature of 1 °C corresponded to a 0.82% increase in suicide rate (IRR = 1.0082 per °C; 95% CI = 1.0025-1.0140). Estimated coefficients for maximum temperature (IRR = 1.0069 per °C; 95% CI = 1.0021-1.0117) and minimum temperature (IRR = 1.0088 per °C; 95% CI = 1.0023-1.0153) were similar. CONCLUSION: This study adds to a growing body of evidence supporting a causal effect of elevated temperature on suicide. Further investigation into environmental causes of suicide, as well as the biological and societal contexts mediating these relationships, is critical for the development and implementation of new public health interventions to reduce the incidence of suicide, particularly in the face increasing temperatures due to climate change.
This study used a trait-level approach to understanding pro-environmental behavior in the context of climate change. We asked 194 adult participants to report their belief in climate change and their risk perception and then tested the correlation between self-reported Big Five traits, trait-level anxiety, and empathy. Our analysis revealed that Openness, Perspective Taking, sex, and age correlate with climate change attitudes. These results increase our understanding of environmental challenges to the general public and offer implications for future research on how to execute pro-environmental strategies.
The increase in weather and climate disasters in recent years has prompted an interest in analyzing their consequences and the mitigation and adaptation measures that can help minimize their potentially large impacts on individuals’ welfare. We match thirtyone billion-dollar disasters with individual survey data from the Behavioral Risk Factor Surveillance System to estimate the effect of extreme weather events on the subjective well-being of U.S. residents. Our results indicate that natural disasters have a negative and robust impact on subjective well-being in the affected communities, and that, on average, this impact peaks 6 months after the event, and then decays over time. We then investigate the attenuating impact of health care access, flood insurance, and governmental assistance programs and find a partial compensating role for risk-transfer and relief measures. We also find that stronger emotional and social support mitigates the negative impact of natural disasters.
The Seasonal Beliefs Questionnaire (SBQ) is a 26-item self-report measure of a winter seasonal affective disorder (SAD)-specific cognitive vulnerability consisting of maladaptive thoughts about the seasons, light availability, and weather conditions. In a known groups comparison, currently depressed adults with SAD had significantly higher SBQ scores than currently depressed adults with nonseasonal major depressive disorder (MDD) and healthy controls, and the MDD group had significantly higher SBQ scores than controls. Using that database, this study explored the predictive validity of using an SBQ cutoff score to differentiate SAD from MDD. Receiver operator characteristic curve analyses used SBQ total score to predict SAD versus MDD, SAD versus control, and MDD versus control status. The SBQ subscale combined score, derived from multivariable logistic regression with SBQ subscales, was examined as an alternative predictor. SBQ total score with a cutpoint of 132 had good predictive ability for distinguishing SAD from MDD (C-statistic = .792, sensitivity = .798, specificity = .794). The SBQ subscale combination score slightly improved predictive ability for the SAD/MDD distinction (C-statistic = .813), with better sensitivity (.930) but worse specificity (.571). In contrast, the score on a generic measure of depressogenic cognitive vulnerability, the Dysfunctional Attitudes Scale, was poor for differentiating SAD from MDD. SBQ total score was excellent in discriminating SAD cases from controls with a cutpoint of 121 (C-statistic = .962, sensitivity = .939, specificity .873), but had poor sensitivity for discriminating MDD cases from controls. Results support using the SBQ to screen for probable SAD in practice settings. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
A growing body of research has documented the phenomenon of climate change anxiety (CCA), defined broadly as negative cognitive, emotional, and behavioral responses associated with concerns about climate change. A recently validated scale of CCA indicated two subscales: cognitive emotional impairment and functional impairment (Clayton & Karazsia, 2020). However, there are few empirical studies on CCA to date and little evidence regarding whether CCA is associated with psychiatric symptoms, including symptoms of Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD), and whether engaging in individual and collective action to address climate change could buffer such relationships. This mixed methods study draws on data collected from a sample of emerging adult students (ages 18-35) in the United States (N = 284) to address these gaps. Results indicated that both CCA subscales were significantly associated with GAD symptoms, while only the Functional Impairment subscale was associated with higher MDD symptoms. Moreover, engaging in collective action, but not individual action, significantly attenuated the association between CCA cognitive emotional impairment and MDD symptoms. Responses to open-ended questions asking about participants’ worries and actions related to climate change indicated the severity of their worries and, for some, a perception of the insignificance of their actions relative to the enormity of climate change. These results further the field’s understanding of CCA, both in general and specifically among emerging adults, and suggest the importance of creating opportunities for collective action to build sense of agency in addressing climate change.
BACKGROUND: Little is known about the associations between ambient environmental exposures and the risk of acute episodes of psychiatric disorders. We aimed to estimate the link between short-term exposure to atmospheric pollutants, temperature, and acute psychiatric hospital admissions in adults aged 65 years and older in the USA. METHODS: For this study, we included all people (aged ≥65 years) enrolled in the Medicare programme in the USA who had an emergency or urgent hospital admission for a psychiatric disorder recorded between Jan 31, 2000, and Dec 31, 2016. We applied a case-crossover design to study the associations between short-term exposure to air pollution (fine particulate matter [PM(2·5)], ozone, and nitrogen dioxide [NO(2)]), ambient temperature, and the risk of acute hospital admissions for depression, schizophrenia, and bipolar disorder in this population. The percentage change in the risk of hospital admission and annual absolute risk differences were estimated. FINDINGS: For each 5°C increase in short-term exposure to cold season temperature, the relative risk of acute hospital admission increased by 3·66% (95% CI 3·06-4·26) for depression, by 3·03% (2·04-4·02) for schizophrenia, and by 3·52% (2·38-4·68) for bipolar disorder in the US Medicare population. Increased short-term exposure to PM(2·5) and NO(2) was also associated with a significant increase in the risk of acute hospital admissions for psychiatric disorders. Each 5 μg/m(3) increase in PM(2·5) was associated with an increase in hospital admission rates of 0·62% (95% CI 0·23-1·02) for depression, 0·77% (0·11-1·44) for schizophrenia, and 1·19% (0·49-1·90) for bipolar disorder; each 5 parts per billion (ppb) increase in NO(2), meanwhile, was linked to an increase in hospital admission rates of 0·35% (95% CI 0·03-0·66) for depression and 0·64% (0·20-1·08) for schizophrenia. No such associations were found with warm season temperature. INTERPRETATION: In the US Medicare population, short-term exposure to elevated concentrations of PM(2·5) and NO(2) and cold season ambient temperature were significantly associated with an increased risk of hospital admissions for psychiatric disorders. Considering the increasing burden of psychiatric disorders in the US population, these findings suggest that intervening on air pollution and ambient temperature levels through stricter environmental regulations or climate mitigation could help ease the psychiatric health-care burden. FUNDING: US National Institute of Environmental Health Sciences, US Environmental Protection Agency, and US National Institute on Aging.
Profound environmental changes will affect vast human populations, if not pose an existential threat to humanity, raising the question how individuals will adapt psychologically to address these changes and how they manage stress and anxiety in the face of chronic threats such as climate change. We propose that ecological coping (efforts to manage adaptational demands of a degrading environment) is an important construct. Our purpose is to use a person-centered approach to identify profiles of ecological coping and to determine how these profiles differ on mental health outcomes and pro-environmental behaviors in an online survey (N=334 U.S. adults). Using Latent Profile Analysis (LPA), we also investigate whether these profiles are explained based on general (demographics) or environment-specific (e.g., eco-stressors) factors. Results showed: (1) The identification of two profiles: Adaptive Approach Coping (P1; 69.46%) and Maladaptive Avoidance Coping (P2; 30.54%); (2) Environment-related factors (vs. health) are associated with the profiles; (3) All 6 environment-specific characteristics predicted profile membership. Future research and policy can use these profiles to develop interventions to increase pro-environmental engagement to address climate change.
BACKGROUND: The physical environmental risk factors for psychotic disorders are poorly understood. This study aimed to examine the associations between exposure to ambient air pollution, climate measures and risk of hospitalization for psychotic disorders and uncover potential disparities by demographic, community factors. METHODS: Using Health Cost and Utilization Project (HCUP) State Inpatient Databases (SIDs), we applied zero-inflated negative binomial regression to obtain relative risks of hospitalization due to psychotic disorders associated with increases in residential exposure to ambient air pollution (fine particulate matter, PM(2.5); nitrogen dioxide, NO(2)), temperature and cumulative precipitation. The analysis covered all-age residents in eight U.S. states over the period of 2002-2016. We additionally investigated modification by age, sex and area-level poverty, percent of blacks and Hispanics. RESULTS: Over the study period and among the covered areas, we identified 1,211,100 admissions due to psychotic disorders. For each interquartile (IQR) increase in exposure to PM(2.5) and NO(2), we observed a relative risk (RR) of 1.11 (95% confidence interval (CI) = 1.09, 1.13) and 1.27 (95% CI = 1.24, 1.31), respectively. For each 1 °C increase of temperature, the RR was 1.03 (95% CI = 1.03, 1.04). Males were more affected by NO(2). Older age residents (≥30 yrs) were more sensitive to PM(2.5) and temperature. Population living in economically disadvantaged areas were more affected by air pollution. CONCLUSIONS: The study suggests that living in areas with higher levels of air pollutants and ambient temperature could contribute to additional risk of inpatient care for individuals with psychotic disorders.
Lessons learned from recent pandemics, such as SARS-CoV-2 have illustrated that education and training in a One Health approach, which recognizes the interdependency of the health of people, animals and the environment, are essential in improving preparations for and responses to disease outbreaks. For this reason and others, there is a critical need to provide One Health (OH) training to medical professionals early in their careers. 133 U.S. medical schools were surveyed for the incorporation of OH learning activities. Results showed that 56% of surveyed programs included OH-related subject matter, primarily in the context of preclinical classroom learning. This supports previous findings that OH education efforts in medical schools lag behind veterinary schools, with many veterinary schools already including OH as a central part of their curricula. A two week OH elective course for third year medical students was developed and implemented at Georgetown University School of Medicine. Topics such as emerging infectious diseases, zoonoses, vector-borne diseases, epidemiology, emergency preparedness, the human-animal bond, and effects of climate change on public health were discussed. The 21 participants were surveyed before and after the course regarding their knowledge and understanding of OH. Participation in the course enhanced the students’ knowledge of OH and furthermore, the students’ perception of the importance of incorporating OH within the curriculum and in their future careers changed significantly. This study provides clear evidence that successful integration of OH material is achievable at low cost through interdepartmental and interdisciplinary collaboration. A more holistic approach to health care that takes into consideration environmental, wildlife, and domestic animal factors, and introduction of concepts such as OH into the medical school curriculum, can help close the educational gaps identified in the surveys.
We examined the extent to which cities’ climate change adaptation plans, in U.S. cities broadly and in shrinking cities, discuss health equity/justice, including injustices related to green spaces. Using content analysis of 88 cities’ climate change adaptation plans, we coded for health, equity/justice, parks/green space, and joint usage of these terms. We made comparisons of keyword usage between shrinking and non-shrinking cities to examine how shrinking cities-with overlapping vulnerabilities and industrial legacies-differ from stronger market cities. Although health (97%) and equity/justice (81%) were common, only half of the cities discussed health and equity/justice concurrently, with overrepresentation from shrinking cities. Parks/green space were discussed alongside these themes in 28% of cities. Health equity emerged more in shrinking cities and recent plans (e.g., since 2018), suggesting recent shifts toward equity. Many cities vaguely described health equity solutions, necessitating clearer solutions for injustices, including parks/green space as climate adaptation and health infrastructure.
Climate change is reshaping the geostrategic, operational, and tactical environments with significant implications for U.S. national security and defense. Increasing temperatures; changing precipitation patterns; and more frequent, intense, and unpredictable extreme weather conditions caused by climate change are exacerbating existing risks and creating new security challenges for U.S. interests. The risks of climate change to Department of Defense (DoD) strategies, plans, capabilities, missions, and equipment, as well as those of U.S. allies and partners, are growing. Global efforts to address climate change – including actions to address the causes as well as the effects – will influence DoD strategic interests, relationships, competition, and priorities. To train, fight, and win in this increasingly complex environment, DoD will consider the effects of climate change at every level of the DoD enterprise. The DoD Climate Risk Analysis (DCRA) responds to requirements specified in Executive Order (EO) 14008, “Tackling the Climate Crisis at Home and Abroad.” The DCRA is organized as follows:
– Section I introduces key security implications of climate change to DoD, including DoD’s role supporting whole-of-government and international efforts in concert with allies and partners.
– Section II reviews DoD climate policy and responsibilities, highlighting key documents.
– Section III presents a review of climate hazards, risks, and security implications. Sections on specific regions have been identified as Controlled Unclassified Information (CUI) and not releasable to the public. These sections were removed to allow this to be a publicly-releasable document.
– Section IV outlines how DoD will incorporate consideration of climate into relevant strategy, planning, and processes.
– Section V describes interagency scientific and intelligence products and experts, which could support future analyses of climate risk, as well as expected funding for exercises, wargames, analyses, and studies related to climate change.
– Section VI concludes the DCRA.
The DCRA is an important step towards integration of climate change considerations at DoD. To understand specific climate effects on plans, resourcing, operations, and missions, DoD Components will include climate considerations in relevant risk analyses, leveraging high-quality data, scenarios, and analytical tools tailored to DoD needs. Working within the whole-of-government, and in coordination with allies and partners, DoD will strive to prevent, mitigate, account for, and respond to defense and security risks associated with climate change.
Climate change education in advanced practice registered nursing curricula prepares nurse practitioners to respond to the health effects of climate change. Knowledge of the relationship between human and environmental health is essential for nurse practitioners to identify, teach, and respond to the health effects of climate change in clinical and community settings. This article describes a webinar hosted by the Sarah P. Duke Gardens in partnership with the Duke University School of Nursing. Our webinar provided an opportunity for attendees to understand how gardening can mitigate climate change, the important relationship between human and environmental health, and nurses’ role in climate crisis.(c) 2021 Elsevier Inc. All rights reserved.
The Urban Climate and Resiliency-Science Working Group (i.e., The WG) was convened in the summer of 2018 to explore the scientific grand challenges related to climate resiliency of cities. The WG leveraged the presentations at the 10th International Conference on Urban Climate (ICUC10) held in New York City (NYC) on 6–10 August 2018 as input forum. ICUC10 was a collaboration between the International Association of Urban Climate, American Meteorological Society, and World Meteorological Organization. It attracted more than 600 participants from more than 50 countries, resulting in close to 700 oral and poster presentations under the common theme of “Sustainable & Resilient Urban Environments”. ICUC10 covered topics related to urban climate and weather processes with far-reaching implications to weather forecasting, climate change adaptation, air quality, health, energy, urban planning, and governance. This article provides a synthesis of the analysis of the current state of the art and of the recommendations of the WG for future research along each of the four Grand Challenges in the context of urban climate and weather resiliency; Modeling, Observations, Cyber-Informatics, and Knowledge Transfer & Applications.
How do older people’s living environments influence their vulnerabilities to climate change? Much has been written about the physiological consequences of climate change for older individuals, particularly the dangers of increased incidence of severe heat. Less is known about how older people’s residential settings moderate their exposure to climate stressors, their particular sensitivities to the effects of climate change, or their capacities to respond to extreme events or adapt to long-term environmental changes. Drawing on literature in English, with a focus on work relevant to the United States, we examine how the housing, neighborhood, and urban or rural contexts in which older people live shape their experiences of climate change, moderating their exposure to risks related to climate change, sensitivity to those events and trends, and their capacities to adapt and recover. Older people face multiple life changes, making prioritizing climate readiness more challenging. They are also diverse, with different vulnerabilities and perceptions of risks and the ability to manage them. This paper lays out an agenda where additional research can inform policy and planning efforts aimed at reducing older individuals’ risk and building the capacity to adapt to climate change. The agenda includes understanding specific vulnerabilities and how older people and their housing providers are already responding.
The concept of biophilic urban planning has inspired neighborhood greening projects in many older urban communities in the USA and beyond. The strengths (e.g., environmental management, biodiversity, heat island mitigation) and challenges (e.g., greenwashing, green gentrification) of such projects are well-documented. Additional research on the relationship between these projects and various social factors (e.g., public perceptions, feelings, and mental health and well-being) is necessary to better understand how people adapt to said projects while struggling to navigate other more pressing socioeconomic issues, especially in communities facing environmental injustice and health inequity. In this article, we focus on one aspect of biophilic urban planning-green stormwater infrastructure (GSI) (e.g., rain gardens, bio-swales, pervious pavements, and wildflower meadows)-in Waterfront South, a post-industrial neighborhood in Camden, NJ, USA, where residents have faced environmental injustices for decades. Our qualitative analysis of in-depth semi-structured interviews of sixteen residents offered a thorough insight into their perceptions and emotions regarding different types of urban GSI projects. Residents acknowledge the many benefits that GSI offers to combat the neighborhood’s social and environmental injustices, but they are cautious about the possibility of some projects prompting new issues and concerns within the community. Our findings reveal potential implications in GSI planning, research, and practice in this neighborhood and similar urban places elsewhere that have yet to undergo gentrification.
Climate change is disproportionally impacting the Circumpolar North, with particular impacts among Indigenous populations. Environmental changes are felt in many aspects of daily life of Northern communities, including both physical and mental health. Thus, health institutions from around the Arctic must meet emerging needs, while the phenomenon remains marginal to their southern counterparts. In this systematic review, we aimed to review current scientific knowledge on the mental health impacts of climate change in Indigenous Peoples across the Circumpolar North. Seven databases were searched. Original peer-reviewed research articles were included if they addressed links between climate change and mental health in Arctic or Subarctic Indigenous Populations. After extraction, data were synthesized using thematic analysis. Of the 26 articles that met inclusion criteria, 16 focused on Canadian Inuit communities and 21 were exclusively qualitative. Being on the land was identified as a central determinant of wellbeing. Immediate impacts of climate change on mental health were felt through restricted mobility and disrupted livelihoods. Effects on mental health were further felt through changes in culture and identity, food insecurity, interpersonal stress and conflicts, and housing problems. Various ways in how communities and individuals are coping with these effects were reported. Understanding climate-related pathways of mental health risks in the Arctic is crucial to better identify vulnerable groups and to foster resilience. Clinicians can play a role in recognizing and providing support for patients affected by these disruptions. Policies sensitive to the climate-mental health relationship must be advocated for.
Political, economic, and climatic upheaval can result in mass human migration across extreme terrain in search of more humane living conditions, exposing migrants to environments that challenge human tolerance. An empirical understanding of the biological stresses associated with these migrations will play a key role in the development of social, political, and medical strategies for alleviating adverse effects and risk of death. We model physiological stress associated with undocumented migration across a commonly traversed section of the southern border of the United States and find that locations of migrant death are disproportionately clustered within regions of greatest predicted physiological stress (evaporative water loss). Minimum values of estimated evaporative water loss were sufficient to cause severe dehydration and associated proximate causes of mortality. Integration of future climate predictions into models increased predicted physiological costs of migration by up to 34.1% over the next 30 years.
OBJECTIVES: To ascertain common experiences and needs of a diverse group of caregivers challenged by hurricanes/floods and COVID-19. METHODS: In-depth interviews with unpaid caregivers in U.S. Southeast/Gulf Coast states who had experienced caregiving during a natural disaster and during COVID-19. RESULTS: Caregivers report challenges including daily living disruption, altered social supports, complicated health management, additional disaster planning, and emotional/financial impacts. Caregivers suggested helpful resources, policy options, and preparatory tools at individual, local, and health system levels to mediate discontinuity. CONCLUSIONS: Our data describe combined caregiver experiences of hurricanes/floods and the pandemic. Caregivers experience unique burdens related to care recipient diagnosis, location, and veteran status. Access to community supports varies as they manage the tasks required for care recipients’ health and safety. Our findings indicate the need for public health reinforcement of caregiving though caregiver pre-planning and targeted support. Bolstering understanding of communities’ caregiving capacity though first responder trainings and caregiver registries may enhance health and safety.
Natural and anthropogenic hazards are increasingly becoming commonplace due to climate change and population pressures. The state of Texas is particularly vulnerable to these hazards and is ranked first in the USA due to the immense variety and frequency of large-scale events. While much research has looked at the immediate impacts these incidents have on mental health, little research has addressed the effects of compounding and repeated exposure to hazards. This cross-sectional study (N = 1224) collected survey data from a representative sample within the Houston Metropolitan Statistical Area. Utilizing the 12 item Short Form Health Survey version 2, a general composite score assessing mental health was compared against the type and frequency of hazard exposures. Findings revealed an observed reduction in mental health scores as participants had repeated exposures to major disasters. Further, the only significant result (p < 0.001) in dictating a reduced mental health scores was repeat exposure to hazards even after adjusting for demographic data and socioeconomic variables. This research reveals the long-term mental impact hazard exposures can have and underscores the need for target public health interventions and engaged community efforts.
The increase in worldwide population is putting much pressure on the existent urban management plans. In this context, strategies and policies should be updated to conserve natural resources, but more importantly, to improve inhabitants’ well-being. Studies focusing on pervious areas have many potentials, particularly regarding the assessment of potential green infrastructures within the vicinities of cities. This study highlights the pervious area change between 2001 and 2016 within every county in the CONtiguous United States (CONUS) based on the National Land Cover Database (NLCD). The study found that 43 different counties can be considered dense. A statistical analysis is followed, highlighting the air temperature, wind speed, precipitation, solar radiation, and Normalized Difference Vegetation Index (NDVI) trends in five characteristic counties. These datasets were retrieved from diverse remote sensing and satellite platforms between 1980 and 2019. The main results also found that air temperature was significantly (at alpha = 0.95) increasing for the same period. The other climatic variables depict fluctuating and usually insignificant trends. Such information would benefit decisionand policy makers to focus their initiatives towards the most vulnerable counties while projecting different scenarios based on their current and historical conditions. Furthermore, this approach can be portable to other countries.
This paper takes the United States as a case study on the gendered implications of hyper-incarceration in the age of climate emergency. Prisons here are often located on toxic sites and constitute sources of contamination; climate change and global warming exacerbate these conditions. Incarcerated women and their communities are particularly affected. The female incarceration rate has skyrocketed, and women come to the carceral complex with unique histories of abuse, and higher rates of physical and mental illness. Researchers and policymakers need to address, analyse, and include incarcerated women’s experiences of climate stress in global policy mechanisms such as the UN Commission on the Status of Women (CSW) and the United Nations Rules for the Treatment of Women Prisoners and Non-custodial Measures for Women Offenders (“Bangkok Rules”). Abolition feminism and the voices of incarcerated women should meaningfully help connect the dots in the larger framework of the Sustainable Development Goals (SDGs).
The COVID-19 pandemic has created new workforce considerations for emergency management community in addressing cumulative and cascading disasters. This research identifies how emergency management planning for both the changing dynamics of COVID-19 and the upcoming hurricane season may change under a compound threat. Many jurisdictions have faced challenges in providing adequate staffing of shelters before the pandemic. Now, fatigue among staff further exacerbates these challenges as resources are stretched thin. Six workshops, involving 265 national, state, and local leaders, staff, experts, and advocates from 22 states, and a range of disciplines (disaster planning, public health, social services, academia, and healthcare), were convened to identify concerns and potential strategies to address staffing, training, logistics, and support. Strategies proposed to increase the number and skill set of staff available involve increased reliance upon volunteers and nonprofit organizations. Mental health resources, personal protective equipment, sanitation supplies, and defining roles within emergency shelters were recommended to reduce fatigue and redistribute responsibilities. Findings illuminate additional research avenues regarding assessing the underlying stressors contributing to the planning process and effective means of implementing these interventions to bolster emergency management shelter operations during a prolonged pandemic and in the future.
IMPORTANCE: Tropical cyclones have a devastating effect on society, but a comprehensive assessment of their association with cause-specific mortality over multiple years of study is lacking. OBJECTIVE: To comprehensively evaluate the association of county-level tropical cyclone exposure and death rates from various causes in the US. DESIGN, SETTING, AND PARTICIPANTS: A retrospective observational study using a Bayesian conditional quasi-Poisson model to examine how tropical cyclones were associated with monthly death rates. Data from 33.6 million deaths in the US were collected from the National Center for Health Statistics over 31 years (1988-2018), including residents of the 1206 counties in the US that experienced at least 1 tropical cyclone during the study period. EXPOSURES: Tropical cyclone days per county-month, defined as number of days in a month with a sustained maximal wind speed 34 knots or greater. MAIN OUTCOMES AND MEASURES: Monthly cause-specific county-level death rates by 6 underlying causes of death: cancers, cardiovascular diseases, infectious and parasitic diseases, injuries, neuropsychiatric conditions, and respiratory diseases. The model yielded information about the association between each additional cyclone day per month and monthly county-level mortality compared with the same county-month in different years, up to 6 months after tropical cyclones, and how these estimated associations varied by age, sex, and social vulnerability. The unit of analysis was county-month. RESULTS: There were 33 619 393 deaths in total (16 691 681 females and 16 927 712 males; 8 587 033 aged 0-64 years and 25 032 360 aged 65 years or older) from the 6 causes recorded in 1206 US counties. There was a median of 2 tropical cyclone days experienced in total in included US counties. Each additional cyclone day was associated with increased death rates in the month following the cyclone for injuries (3.7% [95% credible interval {CrI}, 2.5%-4.9%]; 2.0 [95% CrI, 1.3-2.7] additional deaths per 1 000 000 for 2018 monthly age-standardized median rate [DPM]; 54.3 to 56.3 DPM), infectious and parasitic diseases (1.8% [95% CrI, 0.1%-3.6%]; 0.2 [95% CrI, 0.0-0.4] additional DPM; 11.7 to 11.9 DPM), respiratory diseases (1.3% [95% CrI, 0.2%-2.4%]; 0.6 [95% CrI, 0.1-1.1] additional DPM; 44.9 to 45.5 DPM), cardiovascular diseases (1.2% [95% CrI, 0.6%-1.7%]; 1.5 [95% CrI, 0.8-2.2] additional DPM; 129.6 to 131.1 DPM), neuropsychiatric conditions (1.2% [95% CrI, 0.1%-2.4%]; 0.6 [95% CrI, 0.1-1.2] additional DPM; 52.1 to 52.7 DPM), with no change for cancers (-0.3% [95% CrI, -0.9% to 0.3%]; -0.3 [95% CrI, -0.9 to 0.3] additional DPM; 100.4 to 100.1 DPM). CONCLUSIONS AND RELEVANCE: Among US counties that experienced at least 1 tropical cyclone from 1988-2018, each additional cyclone day per month was associated with modestly higher death rates in the months following the cyclone for several causes of death, including injuries, infectious and parasitic diseases, cardiovascular diseases, neuropsychiatric conditions, and respiratory diseases.
OBJECTIVE: This study aimed to characterize ophthalmology consultations ordered after Hurricane Harvey compared to consultations ordered during the same time period of the prior year. METHODS: A retrospective chart review was performed at an urban, level 1 trauma center of a county hospital. All patients were included who received an electronic health record, documented ophthalmology consultation order between September 2017 and October 2017 (the time period immediately following Hurricane Harvey) or September 2016 and October 2016. Patient demographic risk factors were collected. Patient ICD10 clinical diagnoses were categorized as extraocular, intraocular, infectious, physiological, or other, and then subcategorized as trauma or non-trauma-related. A geographical heat map was generated to compare the changes in diagnosis volume by zip code to the magnitude of rainfall in the county. RESULTS: Following Hurricane Harvey, ophthalmology consultation volume decreased, number of infectious ophthalmology diagnoses increased (P < 0.001), percentage of patients on immunosuppression increased (P < 0.001), and the number of private insurance payers increased while the number of county-funded insurance payers decreased (P = 0.003). CONCLUSIONS: The risk of infectious eye diagnosis was double the risk of traumatic eye diagnosis from Hurricane Harvey flooding. During public disaster planning, different ophthalmological medical resources and responses should be considered for flooding versus high-wind events.
IMPORTANCE: As public health emergencies become more prevalent, it is crucial to identify adverse physical and mental health conditions that may be triggered by natural disasters. There is a lack of data on whether Hurricane Maria in 2017 influenced the disease burden of adults in Puerto Rico. OBJECTIVE: To estimate the prevalence of chronic diseases and their associated risk factors among adults living in Puerto Rico before and after Hurricane Maria in 2017. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used data from 2 previous cross-sectional studies, including the pre-Hurricane Maria Puerto Rico Assessment on Diet, Lifestyles and Disease (PRADLAD) study, conducted in 2015, and the post-Hurricane Maria Puerto Rico Observational Study of Psychosocial, Environmental, and Chronic Disease Trends (PROSPECT), conducted in 2019. Participants included adults aged 30 to 75 years residing in Puerto Rico. Data were analyzed from April to October 2020. EXPOSURES: Self-reported data were obtained on sociodemographic, lifestyle, and psychosocial factors and medically diagnosed conditions using validated questionnaires. Anthropometrics were measured in triplicate. MAIN OUTCOMES AND MEASURES: Data were obtained using similar protocols in both studies. Characteristics were contrasted for all participants across studies and for 87 PRADLAD participants who returned to PROSPECT. RESULTS: A total of 825 participants from both cohorts were included, with 380 PRADLAD participants and 532 PROSPECT participants. In the 2019 PROSPECT study, the mean (SD) age was 53.7 (10.8) years, and 363 participants (68.2%) were assigned female at birth and 169 participants (31.8%) were assigned male at birth. In the 2019 cohort, 360 participants (67.7%) had college education or higher, 205 participants (38.5%) reported annual income greater than $20 001, and 263 participants (49.5%) were employed. Most sociodemographic variables were similar between studies, except for higher income and employment after the hurricane. In the main analysis, participants in 2019, compared with participants in 2015, had higher abdominal obesity (389 participants [73.2%] vs 233 participants [61.3%]), sedentarism (236 participants [44.4%] vs 136 participants [35.8%]), binge drinking (95 participants [17.9%] vs 46 participants [12.1%]), and social support (mean [SD] score, 26.9 [7.2] vs 24.7 [7.1]) but lower depressive symptoms (169 participants [31.7%] vs 200 participants [52.6%]) and perceived stress (mean [SD] score, 19.3 [9.5] vs 21.7 [7.7]). In 2019, compared with 2015, there were higher rates of hypertension (252 participants [47.3%] vs 149 participants [39.2%]), arthritis (172 participants [32.3%] vs 97 participants [25.6%]), high cholesterol (194 participants [36.4%] vs 90 participants [23.8%]), high triglycerides (123 participants [23.1%] vs 56 participants [14.7%]), eye disease (94 participants [17.6%] vs 48 participants [12.7%]), fatty liver disease (68 participants [12.8%] vs 29 participants [7.5%]), and osteoporosis (74 participants [13.9%] vs 20 participants [5.2%]). Secondary analysis for the 87 returning participants showed similar results. CONCLUSIONS AND RELEVANCE: In this cross-sectional study, a higher prevalence of unhealthy behaviors and chronic conditions was noted among adults in Puerto Rico after Hurricane Maria, warranting long-term studies. Psychosocial factors were better, but still need attention. As natural disasters intensify, efforts should focus on continuous surveillance of health outcomes and promoting healthy behaviors, positive emotional health, and disease control, particularly in populations with higher risk for poor health.
COVID-19 is not the first, nor the last, public health challenge the US political system has faced. Understanding drivers of governmental responses to public health emergencies is important for policy decision-making, planning, health and social outcomes, and advocacy. We use federal political disaster-aid debates to examine political factors related to variations in outcomes for Puerto Rico, Texas, and Florida after the 2017 hurricane season. Despite the comparable need and unprecedented mortality, Puerto Rico received delayed and substantially less aid. We find bipartisan participation in floor debates over aid to Texas and Florida, but primarily Democrat participation for Puerto Rican aid. Yet, deliberation and participation in the debates were strongly influenced by whether a state or district was at risk of natural disasters. Nearly one-third of all states did not participate in any aid debate. States’ local disaster risk levels and political parties’ attachments to different racial and ethnic groups may help explain Congressional public health disaster response failures. These lessons are of increasing importance in the face of growing collective action problems around the climate crisis and subsequent emergent threats from natural disasters.
In September 2017, Hurricane Maria devastated Puerto Rico, causing extensive infrastructure damage and a significant number of deaths. In the months and years since, recovery from Maria has been slow, hampered by delayed delivery of fiscal aid, corruption, economic hardships, and Puerto Rico’s colonial status. Simultaneously, Puerto Rico’s population is rapidly aging and hundreds of thousands of mostly younger Puerto Ricans are migrating out of Puerto Rico for more opportunities. Many Puerto Ricans who are older or disabled and need long-term care receive this care in home-based environments, as Puerto Rico has minimal institutionalized long-term care infrastructure and limited funding to expand it. The Department of Veterans Affairs (VA) offers several home-based long-term care options for Veterans in Puerto Rico. In this qualitative case study, veterans, VA staff, veterans’ caregivers, caregivers’ family members, and veterans’ family members receiving or involved with providing this care were interviewed regarding their experiences during and after Hurricane Maria. Specifically, this study highlights how social determinants of health of those residing in or involved with VA home-based long-term care programs influenced recovery from Hurricane Maria, and how findings can inform disaster recovery and provision of home-based long-term care going forward.
OBJECTIVE: The aim of this study was to examine birth outcomes in areas affected by Hurricane Michael. METHODS: Vital statistics data of 2017-2019 were obtained from the state of Florida. Births occurring in the year before and after the date of Hurricane Michael (October 7, 2018) were used. Florida counties were divided into 3 categories reflecting extent of impact from Hurricane Michael. Birth outcomes including incidence of preterm birth (PTB), low birth weight (LBW), and small for gestational age (SGA) were also compared before and after Hurricane Michael. Spontaneous and indicated PTBs were distinguished based on previously published algorithms. Multiple regression was used to control for potential confounders. RESULTS: Both LBW (aRR 1.19, 95% CI: 1.07, 1.32) and SGA (aRR 1.11, 95% CI: 1.01, 1.21) were higher in the year after Michael than the year before in the most-affected area; a similar effect was not seen in other areas. A stronger effect was seen for exposure in the first trimester or in the 2 months after Michael than in the second or third trimester. CONCLUSION: Consistent with many previous studies, this study of Hurricane Michael found an effect on fetal growth.
BACKGROUND: Hurricanes are severe weather events that can disrupt power, water, and transportation systems. These disruptions may be deadly for patients requiring maintenance dialysis. We hypothesized that the mortality risk among patients requiring maintenance dialysis would be increased in the 30 days after a hurricane. METHODS: Patients registered as requiring maintenance dialysis in the United States Renal Data System who initiated treatment between January 1, 1997 and December 31, 2017 in one of 108 hurricane-afflicted counties were followed from dialysis initiation until transplantation, dialysis discontinuation, a move to a nonafflicted county, or death. Hurricane exposure was determined as a tropical cyclone event with peak local wind speeds ≥64 knots in the county of a patient’s residence. The risk of death after the hurricane was estimated using time-varying Cox proportional hazards models. RESULTS: The median age of the 187,388 patients was 65 years (IQR, 53-75) and 43.7% were female. There were 27 hurricanes and 105,398 deaths in 529,339 person-years of follow-up on dialysis. In total, 29,849 patients were exposed to at least one hurricane. Hurricane exposure was associated with a significantly higher mortality after adjusting for demographic and socioeconomic covariates (hazard ratio, 1.13; 95% confidence interval, 1.05 to 1.22). The association persisted when adjusting for seasonality. CONCLUSIONS: Patients requiring maintenance dialysis have a higher mortality risk in the 30 days after a hurricane.
OBJECTIVE: The devastation of pharmaceutical production facilities from Hurricane Maria caused a national shortage of parenteral amino acids in October 2017. Our institution decreased trophamine in very low birth weight (VLBW) infants and initiated human milk fortification at a lower feeding volume to increase enteral protein intake more quickly. The objective of this study was to assess how protein management during the shortage period affected the incidence of malnutrition. METHODS: This was a retrospective cohort study of infants admitted to 2 neonatal intensive care units from June 1, 2017 to May 31, 2018. Infants between 23 and 32 weeks’ gestation were included in this study. The primary outcome was the incidence of malnutrition at 14 days, defined as a z score decline of ≥0.8 SDs, in the pre-shortage period compared with the shortage period. Clinical data regarding adverse effects associated with early fortification and pharmacy costs were recorded. RESULTS: There were 68 infants prior to and 65 during the shortage who met inclusion criteria. There was no difference in malnutrition between the pre-shortage and shortage groups; however, a significant increase in malnutrition was observed in infants who did not receive early fortification during the shortage. No difference in time to full enteral feeds or necrotizing enterocolitis was observed with early fortification. CONCLUSIONS: Early fortification in VLBW infants receiving less trophamine during the shortage was not associated with an increase in malnutrition. Restricting trophamine in neonates during the shortage allowed for distribution to other critically ill patients.
BACKGROUND: Prior to the introduction of intravenous (IV) drip infusion, most IV drugs were delivered in a syringe bolus push. However, intravenous drip infusions subsequently became the standard of care. Puerto Rico is the largest supplier of IV fluid bags and in the aftermath of Hurricane Maria, there was a nationwide fluid bag shortage. This shortage required stewardship measures to maintain the operation of the self-administered outpatient parenteral antimicrobial therapy (OPAT) program at Parkland Health. METHODS: Parkland pharmacists evaluated all self-administered antimicrobials for viability of administration as an IV syringe bolus push (IVP) instead of an IV-drip infusion. Medications deemed appropriate were transitioned to IVP. The hospital EMR was used to identify patients discharged to the OPAT clinic using all methods of parenteral drug delivery. Data was collected for patient demographics, patient satisfaction, and clinical outcomes. Finally cost of care was calculated for IVP and IV drip administration. RESULTS: One-hundred and thirteen self-administered IVP and 102 self-administered IV drip treatment courses were identified during the study period. Individuals using IVP had a statistically significant decrease in hospital length of stay. Patient satisfaction was greater with IVP and IVP saved 504 liters of normal saline resulting in a savings of $43,652 over 6 months. The 30-day readmission rate and mortality were similar. CONCLUSION: The abrupt IV fluid shortage following a natural disaster led to implementation of a high value care model that improved efficiency, reduced costs, and did not affect safety or efficacy.
BACKGROUND: Large-scale power outages (PO) are increasing in the context of climate change. Although some research has been conducted into the adverse health impacts of POs, significant gaps remain regarding whether POs would affect the health of pregnant women. We investigated the association between ED visits due to pregnancy complications and the occurence, intensity, and duration of large-scale POs in eight Sandy-affected counties in New York State (NYS). METHODS: In this cross-sectional study, daily ED visits for pregnancy complications and large-scale PO data in eight counties in NYS from October to December in 2005-2014 were collected. Using time-series analysis, we estimated the relative increase in ED visits for pregnancy complications during POs compared with non-PO periods at lag 0-7 days. Short-term health impacts of PO intensity and PO duration were investigated. Estimations were also stratified by sociodemographic characteristics and disease subtypes including threatened or spontaneous abortion, threatened or early labor, hypertension complications, infections of genitourinary tract, renal diseases, gestational diabetes mellitus, mental illnesses, and cardiovascular diseases during pregnancy. RESULTS: From October to December in 2005-2014, there were 307,739 ED visits for pregnancy complications in the eight counties. We found significant increases in ED visits for overall pregnancy complications (16.6%, 95% confidence interval [CI]: 10.3%, 23.2%) during the Hurricane-PO period at lag 0-7 days. The ED visits increased by 8.8% per level increase in PO intensity and 1.4% per day increase in PO duration. Specifically, threatened/early delivery and gestational diabetes mellitus during the PO period increased by 26.7% (95% CI: 8.2%, 48.4%) and 111.8% (95% CI: 16.7%, 284.4%), respectively. Young adult, Black, Hispanic, and uninsured individuals were at higher risk of complications. CONCLUSIONS: POs may adversely impact pregnancy, especially for certain pregnancy complications and among low sociodemographic women.
The U.S. 2020 hurricane season was extraordinary because of a record number of named storms coinciding with the COVID-19 pandemic. This study draws lessons on how individual hurricane preparedness is influenced by the additional risk stemming from a pandemic, which turns out to be a combination of perceptions of flood and pandemic risks that have opposite effects on preparedness behavior. We conducted a survey in early June 2020 of 600 respondents in flood-prone areas in Florida to obtain insights into households’ risk perceptions and preparedness for the upcoming hurricane season under COVID-19. The results show that concerns over COVID-19 dominated flood risk perceptions and negatively impacted people’s evacuation intentions. Whereas hotel costs were the main obstacle to evacuating during Hurricane Dorian in 2019 in the same geographic study area, the main evacuation obstacle identified in the 2020 hurricane season is COVID-19. Our statistical analyses investigating the factors influencing evacuation intentions show that older individuals are less likely to evacuate under a voluntary order, because they are more concerned about the consequences of becoming infected by COVID-19. We observe similar findings based on a real-time survey we conducted in Florida with another group of respondents under the threat of Hurricane Eta at the end of the hurricane season in November 2020. We discuss the implications of our findings for risk communication and emergency management policies that aim to improve hurricane preparedness when dealing with additional health risks such as a pandemic, a situation that may be exacerbated under the future climate. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11069-021-05064-2.
RATIONALE: In the weeks and months following a disaster, acute illness and injuries requiring hospital admission increase. It is not known whether disaster exposure is associated with increased risk for hospitalization in the years after a disaster. OBJECTIVE: We examined the extent to which disaster exposure is associated with hospitalization two years after Hurricane Sandy. The analyses fill a clinical gap in our understanding of long-term physical health consequences of disaster exposure by identifying older adults at greatest risk for hospitalization two years after disaster exposure. METHOD: Survey data from a longitudinal panel study collectedbefore and after Hurricane Sandy were linked with Medicare inpatient files in order to assess the impact of Hurricane Sandy on hospital admissions two years following the hurricane. RESULTS: We found that people who reported experiencing a lot of fear and distress in the midst of Hurricane Sandy were at an increased risk of being hospitalized two years after the hurricane [Hazard Ratio = 1.75; 95% CI (1.12-2.73)]. Findings held after controlling for pre-disaster demographics, social risks, chronic conditions, hospitalizations during the year before the hurricane, and decline in physical functioning. CONCLUSIONS: These findings are the first to show that disaster exposure increases the risk for hospital admissions two years after a disaster. Controlling for known risk factors for hospitalization, older adults who experience high levels of fear and distress during a disaster are more likely to be hospitalized two years following the disaster than older adults who do not have this experience.
The 2020 hurricane season threatened millions of Americans concurrently grappling with COVID-19. Processes guiding individual-level mitigation for these conceptually distinct threats, one novel and chronic (COVID-19), the other familiar and episodic (hurricanes), are unknown. Theories of health protective behaviors suggest that inputs from external stimuli (e.g., traditional and social media) lead to threat processing, including perceived efficacy (self- and response) and perceived threat (susceptibility and severity), guiding mitigation behavior. We surveyed a representative sample of Florida and Texas residents (N = 1846) between April 14, 2020 and April 27, 2020; many had previous hurricane exposure; all were previously assessed between September 8, 2017 and September 11, 2017. Using preregistered analyses, two generalized structural equation models tested direct and indirect effects of media exposure (traditional media, social media) on self-reported (1) COVID-19 mitigation (handwashing, mask-wearing, social distancing) and (2) hurricane mitigation (preparation behaviors), as mediated through perceived efficacy (self- and response) and perceived threat (susceptibility and severity). Self-efficacy and response efficacy were associated with social distancing (p = .002), handwashing, mask-wearing, and hurricane preparation (ps < 0.001). Perceived susceptibility was positively associated with social distancing (p = 0.017) and hurricane preparation (p < 0.001). Perceived severity was positively associated with social distancing (p < 0.001). Traditional media exhibited indirect effects on COVID-19 mitigation through increased response efficacy (ps < 0.05), and to a lesser extent self-efficacy (p < 0.05), and on hurricane preparation through increased self-efficacy and response efficacy and perceived susceptibility (ps < 0.05). Social media did not exhibit indirect effects on COVID-19 or hurricane mitigation. Communications targeting efficacy and susceptibility may encourage mitigation behavior; research should explore how social media campaigns can more effectively target threat processing, guiding protective actions.
Background: Nursing home (NH) residents are vulnerable to increased mortality after a natural disaster such as hurricanes but the specific vulnerability of NH residents on hospice and the impact on admission to hospice are unknown. Objectives: Exposure to Hurricane Irma (2017) was used to evaluate increased mortality among Florida NH residents by hospice status compared with the same time period in a nonhurricane year. Difference in hospice utilization rates poststorm for short- and long-stay NH residents was also examined. Setting/Subjects: Subject were all Florida NH residents of age 65 years and older utilizing fee-for-service Medicare claims data exposed to Hurricane Irma in 2017 compared with a control group of residents residing at the same NHs in 2015. Analysis: Mortality rates were calculated by hospice status, rates of hospice enrollment, and the corresponding odds ratios (ORs). Results: Hurricane exposure was associated with an increase in mortality 30 days poststorm (OR = 1.12, 95% confidence interval [CI]: 1.00-1.26) but not 90 days poststorm (OR = 1.02, 95% CI: 0.95-1.10) for residents on hospice. For the rate of hospice enrollment poststorm among residents previously not on hospice, there was an increase in odds of enrollment among long-stay residents in 30 days (OR = 1.15, 95% CI: 1.02-1.23) and 90 days (OR = 1.12, 95% CI: 1.05-1.20) but not short-stay residents within 30 (OR = 1.02, 95% CI: 0.91-1.15) and 90 days (OR = 1.07, 95% CI: 0.99-1.15). Conclusion: Mortality in NH residents on hospice care increased in the aftermath of Hurricane Irma. In addition, NH residents not on hospice were more likely to be referred to hospice in the 30 days after the storm.
OBJECTIVES: To determine death occurrences of Puerto Ricans on the mainland USA following the arrival of Hurricane Maria in Puerto Rico in September 2017. DESIGN: Cross-sectional study. PARTICIPANTS: Persons of Puerto Rican origin on the mainland USA. EXPOSURES: Hurricane Maria. MAIN OUTCOME: We use an interrupted time series design to analyse all-cause mortality of Puerto Ricans in the USA following the hurricane. Hispanic origin data from the National Vital Statistics System and from the Public Use Microdata Sample of the American Community Survey are used to estimate monthly origin-specific mortality rates for the period 2012-2018. We estimated log-linear regressions of monthly deaths of persons of Puerto Rican origin by age group, gender, and educational attainment. RESULTS: We found an increase in mortality for persons of Puerto Rican origin during the 6-month period following the hurricane (October 2017 through March 2018), suggesting that deaths among these persons were 3.7% (95% CI 0.025 to 0.049) higher than would have otherwise been expected. In absolute terms, we estimated 514 excess deaths (95% CI 346 to 681) of persons of Puerto Rican origin that occurred on the mainland USA, concentrated in those aged 65 years or older. CONCLUSIONS: Our findings suggest an undercounting of previous deaths as a result of the hurricane due to the systematic effects on the displaced and resident populations in the mainland USA. Displaced populations are frequently overlooked in disaster relief and subsequent research. Ignoring these populations provides an incomplete understanding of the damages and loss of life.
BACKGROUND: Little is known about the impact of the ecosystem disruption and its contribution on the non-tuberculosis mycobacteria (NTM) diseases (cases) rate in Florida (FL), a state with a high prevalence of NTM in the United States. We aimed to evaluate the epidemiological distribution of NTM in FL and identify its association with extreme weather events. METHODS: We used OneFlorida Clinical Research Consortium dataset and extracted data on NTM cases using ICD codes 9- CM 031.0 and ICD-10 A31 during 2012-2018. The number of hurricanes during the study period which affected FL were extracted data from the National Hurricane Center (NHC) and the National Oceanic and Atmospheric Administration (NOAA). RESULTS: Prevalence of NTM gradually increased during the study period. The rate was 2012: 14.3/100,000, 2015; 20.1/100,000 and 2018; 22.6/100,00 except in 2014 where there was an 8% decrease. The incidences were 2012; 6.5/100,00, 2015; 4.9/100,000 and in 2015; 5.4/100,000. Geographical analysis demonstrated a gradual expansion of the NTM cases in Alachua, and Marion Counties throughout the study period. Notably, the 2018 heat map showed higher prevalence of NTM in the northwestern, panhandle region of FL which had been absent in the heat maps for years 2012-2018. High number of the hurricanes was associated with the higher number of the new cases of NTM infection for years 2012, 2016-2018, while the lower number of the hurricanes was associated with the lower number of the new cases of NTM infection for years 2014-2015. CONCLUSION: The current study found the prevalence rates of NTM disease in FL rose from 2012 to 2018. A higher prevalence was seen following the hurricanes..
Excess phosphorus loading to waterbodies has led to increasing frequency and severity of harmful algal blooms, negatively impacting economic activity and human health. While interventions to improve water quality can create large societal benefits, these investments are costly and the value of benefits is often unknown. Understanding the social and economic impacts of reduced phosphorus loading is critical for developing effective land use policies and for generating public and political support for these initiatives. Here, we quantify the social benefits and costs of improving water quality in Lake Champlain under a range of phosphorus reduction and climate change scenarios between 2016 and 2050. We use statistical models to link water quality outputs from an established integrated assessment model with three categories of benefits: tourism expenditures, property sales, and avoided human health impacts. We estimate the costs of reducing phosphorus loading using data reported by the State of Vermont. We find that under the most aggressive phosphorus reduction scenario, the total benefits of improved water quality are $55 to $60 million between 2016 and 2050. Over this 35 year time horizon, the combined benefits do not outweigh the costs under any scenario. If the time horizon is extended to 2100 or beyond, however, the benefits may exceed the costs if the applied discount rate is less than 3%. Importantly, we almost certainly underestimate the value of clean water, due to the omission of other types of benefits. Despite this uncertainty, our study provides a tractable framework for disentangling the complex relationships between water quality and human well-being, and illuminates the value of reductions in phosphorus loading to society.
Climate change-induced disasters are increasing in intensity and frequency in the United States. Infant feeding in the aftermath of an extreme event is particularly challenging, especially given large variations in community vulnerability and resilience. The aim of this study was to identify the physical, social, and spatial vulnerabilities of communities along the Gulf Coast and highlight locations where high (or low) breastfeeding initiation rates have the potential to offset (or exacerbate) infant feeding challenges in the wake of a disaster. We structured this study as a retrospective, spatial data analysis of breastfeeding initiation, the risk for extreme events, social vulnerability, and community resilience to uncover locations that may need post-disaster intervention. The results suggested that significant gaps in the geographic distribution of community risk, vulnerability, resilience, and breastfeeding initiation existed. While many metropolitan areas benefitted from high breastfeeding initiation rates, they were also the most “at risk” for disasters. Conversely, many rural communities faced less risk for extreme events but exhibited more social vulnerability and less resilience should a disaster strike. Prioritizing emergency response resources to support infant feeding after a disaster is critically important, but urban and rural communities have divergent profiles that will require variable strategies to ensure recovery. Our results highlight this variability and provide prescriptive guidance regarding where to potentially allocate emergency resources.
Strategic preparedness reduces the adverse health impacts of hurricanes and tropical storms, referred to collectively as tropical cyclones (TCs), but its protective impact could be enhanced by a more comprehensive and rigorous characterization of TC epidemiology. To generate the insights and tools necessary for high-precision TC preparedness, we introduce a machine learning approach that standardizes estimation of historic TC health impacts, discovers common patterns and sources of heterogeneity in those health impacts, and enables identification of communities at highest health risk for future TCs. The model integrates (i) a causal inference component to quantify the immediate health impacts of recent historic TCs at high spatial resolution and (ii) a predictive component that captures how TC meteorological features and socioeconomic/demographic characteristics of impacted communities are associated with health impacts. We apply it to a rich data platform containing detailed historic TC exposure information and records of all-cause mortality and cardiovascular- and respiratory-related hospitalization among Medicare recipients. We report a high degree of heterogeneity in the acute health impacts of historic TCs, both within and across TCs, and, on average, substantial TC-attributable increases in respiratory hospitalizations. TC-sustained windspeeds are found to be the primary driver of mortality and respiratory risks.
In September of 2017, Hurricane Maria made landfall in Puerto Rico, bringing widespread damage to public systems across the island, which included particularly devastating impacts to local hospitals and medical facilities. Health care organisations operating on the ground played an essential role in hurricane response efforts as they attempted to address the medical needs of vulnerable populations. However, minimal research has discussed how the provision of post-disaster healthcare rested on the knowledge and participation of local communities. This study aims to fill these gaps by exploring the ways in which health care workers relied on their relationships with informal community networks to navigate the post-disaster landscape and provide adequate health services. This study uses post-disaster response data collected in Puerto Rico, which includes interviews with private, non-profit, and university-affiliated health organisations, as well as community health centers and emergent health outreach groups. Findings from this study highlight the critical role informal networks, community outreach, and relationship building play in response work as organisations attempt to overcome the specific complexities and challenges of operating in the post-disaster context. Furthermore, our research illustrates how deficient government support and systematic failings shift the burden of resilience building onto community members and organisations.
BACKGROUND: On September 20, 2017, Hurricane Maria, a devastating Category 5 storm struck the Caribbean Island of Puerto Rico and officially took the lives of 2 975 people although the Harvard University survey in 2018 placed that number much higher at 4 645 [12]. The island’s infrastructure was devastated. Eight months later in May 2020, many vital services including telecommunications, utilities, and health care systems had not yet been repaired. OBJECTIVES: To (1) review the immediate public health problems and the longer-term repercussions of Hurricane Maria; (2) identify pre-existing infrastructural deficiencies, health disparities, and problems in governance that may have increased vulnerability and delayed recovery; and (3) offer proposals for preventive measures to increase resiliency and adequately prepare Puerto Rico for future disasters. METHODS: Data from the CDC and the Puerto Rico’s Health Department were collected and analyzed. Government publications, news articles, scholarly journal entries and previous research were examined. Interviews were conducted with local citizens and public health professionals. The author’s personal experience is referenced. FINDINGS: The Puerto Rican Electric Power Authority (PREPA) and the Puerto Rico Aqueduct and Sewer Authority (PRASA) both had severely weakened infrastructures before the hurricane as a result of a massive financial crisis that had begun in 2006. These pre-existing weaknesses increased vulnerability and made reconstruction more challenging. Approximately 95% of the cell towers in Puerto Rico sustained significant damage during the hurricane and resulted in almost total loss of cell phone communication [3]. Subpar management of relief efforts by both federal agencies and the local government further hindered recovery, resulting in mass emigration of Puerto Ricans. The public health problems of Hurricane Maria continue to plague Puerto Rico’s citizens and will have long-term consequences. CONCLUSION: Lack of resilience in Puerto Rico’s infrastructure and government agencies rendered the island highly vulnerable to the detrimental effects of Hurricane María. Improvements to infrastructures and a transition towards a more sustainable way of life could improve Puerto Rico’s preparation and response to future disasters – natural and human-made.
BACKGROUND: Hurricane Maria, which hit Puerto Rico in 2017, catastrophically impacted infrastructure and severely disrupted medical services. The US Department of Veterans Affairs Caribbean Healthcare System (VA CHCS), which serves approximately 67,000 patients and has most of its facilities on the island of Puerto Rico, was able to successfully maintain operations after the hurricane. As a part of the larger VA system, VA CHCS also has a mission to support “national, state, and local emergency management, public health, safety and homeland security efforts.” The objective of this study is to better understand the ways VA and its facilities meet this mission by exploring how VA CHCS acted as a community resource following Hurricane Maria. METHODS: This study investigated experiences of five employees in critical emergency response positions for VA CHCS, Veterans Integrated Service Networks (VISN) 8, and the Office of Emergency Management. All respondents were interviewed from March to July 2019. Data were collected via semistructured interviews exploring participants’ experiences and knowledge about VA’s activities provided to the community of Puerto Rico following Hurricane Maria. Data were analyzed using thematic and in vivo coding methods. RESULTS: All respondents underscored VA’s primary mission after a disaster was to maintain continuity of care to Veterans, while concomitantly describing the role of VA in supporting community recovery. Three major themes emerged: continuity of operations for the San Juan VA Medical Center (VAMC) and its affiliated outpatient clinics, provision of services as a federal partner, and services provided directly to the Puerto Rican community. DISCUSSION: Recent disasters have revealed that coordinated efforts between multidisciplinary agencies can strengthen communities’ capacity to respond. This case example demonstrates how a VA hospital not only continued serving its patients but, with the support from the greater VA system, also filled a wide variety of requests and resource gaps in the community. Building relationships with local VAMCs can help determine how VA could be incorporated into emergency management strategies. In considering the strengths community partners can bring to bear, a coordinated regional response would benefit from involving VA as a partner during planning.
IMPORTANCE: On September 20, 2017, one of the most destructive hurricanes in US history made landfall in Puerto Rico. Anecdotal reports suggest that many persons with kidney failure left Puerto Rico after Hurricane Maria; however, empirical estimates of migration and health outcomes for this population are scarce. OBJECTIVE: To assess the changes in migration and mortality among patients with kidney failure in need of dialysis treatment in Puerto Rico after Hurricane Maria. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used an interrupted time-series design of 6-month mortality rates and migration of 11 652 patients who received hemodialysis or peritoneal dialysis care in Puerto Rico before Hurricane Maria (before October 1, 2017) and/or during and after Hurricane Maria (on/after October 1, 2017). Data analyses were performed from February 12, 2019, to June 16, 2022.. MAIN OUTCOMES AND MEASURES: Number of unique persons dialyzed in Puerto Rico per quarter; receipt of dialysis treatment outside Puerto Rico per quarter; and 6-month mortality rate per person-quarter for all persons undergoing dialysis. EXPOSURES: Hurricane Maria. RESULTS: The entire study sample comprised 11 652 unique persons (mean [SD] age, 59 [14.7] years; 7157 [61.6%] men and 4465 [38.4%] women; 10 675 [91.9%] Hispanic individuals). There were 9022 patients with kidney failure and dialysis treatment before and 5397 patients after Hurricane Maria. Before the hurricane, the mean quarterly number of unique persons dialyzed in Puerto Rico was 2834 per quarter (95% CI, 2771-2897); afterwards it dropped to 261 (95% CI, -348 to -175; relative change, 9.2%). The percentage of persons who had 1 or more dialysis sessions outside of Puerto Rico in the next quarter following a previous dialysis in Puerto Rico was 7.1% before Hurricane Maria (95% CI, 4.8 to 9.3). There was a significant increase of 5.8 percentage points immediately after the hurricane (95% CI, 2.7 to 9.0). The 6-month mortality rate per person-quarter was 0.08 (95% CI, 0.08 to 0.09), and there was a nonsignificant increase in level of mortality rates and a nonsignificant decreasing trend in mortality rates. CONCLUSIONS AND RELEVANCE: The findings of this cross-sectional study suggest there was a significant increase in the number of people receiving dialysis outside of Puerto Rico after Hurricane Maria. However, no significant differences in mortality rates before and after the hurricane were found, which may reflect disaster emergency preparedness among dialysis facilities and the population with kidney failure, as well as efforts from other stakeholders.
While conceptual definitions provide a foundation for the study of disasters and their impacts, the challenge for researchers and practitioners alike has been to develop objective and rigorous measures of resilience that are generalizable and scalable, taking into account spatiotemporal dynamics in the response and recovery of localized communities. In this paper, we analyze mobility patterns of more than 800,000 anonymized mobile devices in Houston, Texas, representing approximately 35% of the local population, in response to Hurricane Harvey in 2017. Using changes in mobility behavior before, during, and after the disaster, we empirically define community resilience capacity as a function of the magnitude of impact and time-to-recovery. Overall, we find clear socioeconomic and racial disparities in resilience capacity and evacuation patterns. Our work provides new insight into the behavioral response to disasters and provides the basis for data-driven public sector decisions that prioritize the equitable allocation of resources to vulnerable neighborhoods. Understanding how cities respond to extreme weather is critical; as such events are becoming more frequent. Using anonymized mobile phone data for Houston, Texas during Hurricane Harvey in 2017, the authors find that mobility behavior exposes neighborhood disparities in resilience capacity and recovery.
OBJECTIVES: Patients with end stage kidney disease (ESKD) are at higher risk for increased mortality and morbidity due to disaster-related disruptions to care. We examine effects of Hurricanes Irma and Maria on access to dialysis care for US Department of Veterans Affairs (VA) ESKD patients in Puerto Rico. METHODS: A retrospective, longitudinal cohort study was conducted among VA patients with at least 1 dialysis-related encounter between September 6, 2016, and September 5, 2018. The annual number of dialysis encounters, visits to an emergency department (ED), and the number of deaths pre- and post-hurricanes were compared. A random effects logistic regression model for correlated binary outcomes was fitted for predictors of mortality. Chi-square tests were for differences between pre- and post-hurricane visits. RESULTS: The number of ED visits increased in post-hurricane period (1172 [5.7%] to 1195 [6.6%]; P < 0.001). ESKD-related ED visits increased from 200 (0.9%) to 227 (1.3%) (P < 0.05). Increase in mortality was associated with age (OR = 1.66; CI: 1.23-2.17), heart failure (OR = 2.07; CI: 1.26-3.40), chronic pulmonary disease (OR = 3.26; CI: 1.28-8.28), and sepsis (OR = 3.16; CI: 1.89-5.29). CONCLUSIONS: There was an increase in dialysis services at the San Juan VA Medical Center post-Irma/Maria, and access to dialysis care at the non-VA clinics was limited. The role of VA dialysis centers in providing care during disasters warrants further investigation.
OBJECTIVES: In recent years, catastrophic hurricanes have devastated numerous areas, prompting a need to build resilience particularly in at-risk populations that rely on health care and social services. The Maternal and Child Health (MCH) workforce covers a wide breadth of services to pregnant women, families, and children with special health care needs. Research has noted the need to strengthen this workforce with training and skills to help their patients and clients prepare, respond, and recover from disasters. METHODS: Focus groups and interviews with 35 Florida parents and professionals impacted by Hurricanes Irma, Maria, and Michael were conducted to evaluate the stressors placed on systems of care serving mothers and infants in Florida. Journey mapping was used to explore opportunities for improving MCH training and services. RESULTS: Results highlight the importance of increased communication and collaboration between families and providers, coordination among health care and social services providers, effective public messaging, tailored preparedness materials and processes, and the need for post-disaster mental health services and employment resources. CONCLUSION: Ultimately, hurricane preparation and mitigation are key for improving community resilience and these efforts should be tailored to MCH populations as well as delivered by the providers who know their needs best.
BACKGROUND: In September 2017, hurricanes Irma and Maria affected Puerto Rico (PR) and the US Virgin Islands (USVI), causing major disruptions in basic services and health care. This study documented the stressors and experiences of patients with gynecologic cancer receiving oncology care in PR following these hurricanes. METHODS: We conducted 4 focus groups (December 2018-April 2019) among women aged ≥21 years from PR who were diagnosed with gynecological cancer between September 2016 and September 2018 (n = 24). Using the same eligibility criteria, we also interviewed patients from the USVI (n = 2) who were treated in PR. We also conducted key-informant interviews with oncology care providers and administrators (n = 23) serving gynecologic cancer patients in PR. Discussions were audio-recorded, transcribed verbatim, and coded to identify emergent themes using a constant comparison method. RESULTS: Analyses of focus group discussions and interviews allowed us to identify the following emergent themes: 1) disruptions in oncology care were common; 2) communication between oncology providers and patients was challenging before and after the hurricanes hit; 3) patient resilience was key to resume care; and 4) local communities provided much-needed social support and resources. CONCLUSIONS: This study provides firsthand information about the disruptions in oncology care experienced by and the resiliency of women with gynecologic cancer following hurricanes Irma and Maria. Our findings underscore the need to incorporate oncology care in the preparedness and response plans of communities, health systems, and government agencies to maintain adequate care for cancer patients during and after disasters such as hurricanes.
BACKGROUND: After its landfall in Puerto Rico in 2017, Hurricane Maria caused the longest blackout in United States history, producing cascading effects on a health care system that had already been weakened by decades of public sector austerity and neoliberal health reforms. This article addresses how health care professionals and administrators experienced the health care system’s collapse and the strategies used by them to meet their communities’ health needs. METHODS: Data were collected between September 2018 and February 2020. Ethnographic observations in health care facilities and semi-structured qualitative interviews with representatives of the health care system were conducted. This paper focuses on data from interviews with health care providers (n?Çë=?Çë10) and administrators (n?Çë=?Çë10), and an ethnographic visit to a pop-up community clinic. The analysis consisted of systematic thematic coding of the interview transcripts and ethnographic field notes. RESULTS: Results provide insight on how participants, who witnessed first-hand the collapse of Puerto Rico’s health care system, responded to the crisis after Maria. The prolonged power outage and lack of a disaster management plan were partly responsible for the death of 3,052 individuals who experienced extended interruptions in access to medical care. Participants reported a sense of abandonment by the government and feelings of mistrust. They also described the health sector as chaotic and lacking clear guidelines on how to provide services or cope with personal crises while working under extreme conditions. In such circumstances, they developed resilient responses to meet communities’ health needs (e.g., itinerant acupuncture services, re-locating physicians to local pharmacies). CONCLUSIONS: Participants’ narratives emphasize that the management of Hurricane Maria was fraught with political and economic constraints affecting Puerto Rico. Ineffective planning and post-Maria responses of the local and federal governments were determinants of the disaster’s impact. The findings contribute to a growing scientific literature indicating that Hurricane Maria revealed ‘the collapse before the collapse,’ alluding to the structural deficiencies that presaged the catastrophic event. In the context of governmental abandonment, the authors argue for the importance of developing alternative strategies in post-disaster health care provision among health professionals and administrators who work at the front lines of recovery.
OBJECTIVE: The aim of this study was to compare primary care appointment disruptions around Hurricanes Ike (2008) and Harvey (2017) and identify patterns that indicate differing continuity of primary care or care systems across events. METHODS: Primary care appointment records covering 5 wk before and after each storm were identified for Veterans Health Affairs (VA) facilities in the greater Houston and surrounding areas and a comparison group of VA facilities located elsewhere. Appointment disposition percentages were compared within and across storm events to assess care disruptions. RESULTS: For Hurricane Harvey, 14% of primary care appointments were completed during the week of landfall (vs 33% for Hurricane Ike and 69% in comparison clinics), and 49% were completed the following week (vs 58% for Hurricane Ike and 71% for comparison clinics). By the second week after Hurricane Ike and third week after Harvey, the scheduled appointment completion percentage returned to prestorm levels of approximately 60%. CONCLUSIONS: There were greater and more persistent care disruptions for Hurricane Harvey relative to Hurricane Ike. As catastrophic emergencies including major natural disasters and infectious disease pandemics become a more recognized threat to primary and preventive care delivery, health-care systems should consider implementing strategies to monitor and ensure primary care appointment continuity.
BACKGROUND/PURPOSE: Extreme events such as hurricanes adversely impact healthcare systems and the communities they serve. The degree to which hurricanes affect healthcare use among high need groups such as older adults with chronic conditions has not been well examined, nor has the impact of hurricane severity on health outcomes. We characterized hospitalizations among older adults by chronic condition after eight large-scale hurricanes in the United States. METHODS: Using a combination of administrative healthcare data and the Federal Emergency Management Agency’s Disaster Declaration database we conducted a self-controlled case series analysis. We identified Medicare beneficiaries who were exposed to one of eight hurricanes and compared hospitalizations in the 30-days after a hurricane to hospitalizations in the rest of the calendar year of the hurricane. We examined hospitalizations (1) in total, (2) separately for diabetes, congestive heart failure (CHF) and chronic obstructive pulmonary disease (COPD) admissions, and (3) by hurricane damage category. RESULTS: Among all older adults exposed, hospitalizations in the 30-day period after each disaster increased for all three chronic conditions; diabetes (incidence rate ratio [IRR] = 1.06, 95% confidence interval [CI] 1.03, 1.10), COPD (IRR = 1.06, 95% CI 1.04, 1.08), and CHF (IRR = 1.19, 95% CI 1.17, 1.21. In the 30-to-60-day period hospitalizations also increased for each chronic condition; diabetes (IRR = 1.06, 95% CI 1.03, 1.10), COPD (IRR = 1.12, 95% CI 1.10, 1.15), and CHF (IRR = 1.32, 95% CI 1.30, 1.34). Substantial differences in hospitalizations were observed according to individual hurricane and by the chronic disease examined. CONCLUSION: Exposure to hurricanes is associated with an increase in hospitalizations for chronic conditions across all hurricane damage categories. As disasters are expected to increase in strength and frequency, our results underscore the need for response strategies and health policy planning for healthcare systems designed to address the health needs of older Americans with chronic conditions.
Following hurricanes, there can be increases in exacerbations of chronic diseases, such as asthma. Asthma is common among children, and many asthma exacerbations can be prevented. This systematic literature review assessed literature describing the impact of hurricanes on children with asthma in the United States. Medline, Embase, Global Health, PubMed, and Scopus databases were searched for peer-reviewed, English-language articles published January 1990 to June 2019 that described the effect of a hurricane on children with asthma. This search identified 212 articles; 8 met inclusion criteria. All 8 were related to Hurricane Katrina, but research questions and study design varied. Articles included information on asthma after hurricanes from cross-sectional surveys, retrospective chart review, and objective clinical testing. Four articles described discontinuity in health insurance, asthma-related health care, or asthma medication use; and 3 articles examined the relationship between mold exposure and asthma symptoms and reported varying results. The eighth study quantified the burden of asthma among people visiting mobile medical units but did not describe factors associated with asthma symptoms. These results highlight opportunities for future research (eg, on more recent hurricanes) and disaster preparedness planning (eg, strategies to prevent health-care discontinuity among children with asthma).
The COVID-19 pandemic drastically altered the lives of global populations. As many struggled to adapt to the challenges of a pandemic, 2020 brought the most active Atlantic hurricane season on record. Government officials and other emergency management sources were faced with the challenge of crafting communications that took into account these dual crises and the challenges people navigated when making storm preparation decisions in light of health risks posed by COVID-19. Past research has shown that social media act as valuable sources of information during emergencies and natural disasters, therefore a mixed methods approach was used to analyze tweets about preparation for Hurricane Laura, which struck America’s Gulf Coast during August 2020. The Crisis and Emergency Risk Communication Model (CERC) was used to examine how the simultaneous occurrence of threats in the pre-crisis and maintenance stages impacted the public’s concerns as well as how official messaging matched with or diverged from audience needs. Findings indicate the continuing utility of CERC, while at the same time suggesting needed revisions for when dual crises strike, situations that are likely to continue in an age of accelerating climate change. We couch conclusions with implications for scholars, practitioners and public officials.
Climate change will create more intense and frequent disasters, resulting in the increased exposure of the most vulnerable populations. It is debatable whether the vulnerability research that follows major disasters, like Hurricane Katrina, has resulted in increased resiliency of those who were the most vulnerable during that disaster. It may even be plausible to suggest that research that exposes countless vulnerabilities within a population is guilty of helping none. Through support from a focused review of the related literature, research findings include the following: (1) post-disaster research analysis tends not to present an actionable hierarchy for public agencies and community organizations to prioritize efforts, (2) the most common thread that runs through societal vulnerability in daily life, and opposite the force multiplying effects of climate change, is poverty; and (3) climate change is likely to facilitate more post-disaster windows of opportunity characterized by increased public consonance that can galvanize transformative change at a local level.
The objective of this study is to empirically and systematically assess the combination of inherent susceptibility factors, protective actions, and factors of hazard exposure that influence a house-hold’s level of hardship experienced due to disruptions in critical infrastructure services during disasters. Classification and regression tree (CART) decision tree models and survey data from three major hurricane events were used to: (1) identify the pathways leading to impact(s) due to service disruptions and explore the differences in pathways across vulnerable population groups; and (2) identify the points of intervention to mitigate well-being impacts in households due to disruptions in water, energy, food, and road transportation services. The results reveal how the associative pathways between these factors change between socioeconomic and demographic groups in the impacted community and for different infrastructure service system types. The findings suggest that not all vulnerable households experienced high hardship outcomes despite prolonged outages. Finally, the hardship pathways suggest recommendations for improving resilience in infrastructure systems in a more equitable manner. The findings can be used by emergency and infrastructure managers and operators to better prioritize resource allocation for hazard mitigation investments and restorations. Accordingly, this study contributes to the theory of human-centric infrastructure resilience.
Quantifying the impact of natural disasters or epidemics is critical for guiding policy decisions and interventions. When the effects of an event are long-lasting and difficult to detect in the short term, the accumulated effects can be devastating. Mortality is one of the most reliably measured health outcomes, partly due to its unambiguous definition. As a result, excess mortality estimates are an increasingly effective approach for quantifying the effect of an event. However, the fact that indirect effects are often characterized by small, but enduring, increases in mortality rates present a statistical challenge. This is compounded by sources of variability introduced by demographic changes, secular trends, seasonal and day of the week effects, and natural variation. Here, we present a model that accounts for these sources of variability and characterizes concerning increases in mortality rates with smooth functions of time that provide statistical power. The model permits discontinuities in the smooth functions to model sudden increases due to direct effects. We implement a flexible estimation approach that permits both surveillance of concerning increases in mortality rates and careful characterization of the effect of a past event. We demonstrate our tools’ utility by estimating excess mortality after hurricanes in the United States and Puerto Rico. We use Hurricane Maria as a case study to show appealing properties that are unique to our method compared with current approaches. Finally, we show the flexibility of our approach by detecting and quantifying the 2014 Chikungunya outbreak in Puerto Rico and the COVID-19 pandemic in the United States. We make our tools available through the excessmort R package available from https://cran.r-project.org/web/packages/excessmort/.
Nursing homes (NHs) are responsible for caring for frail, older adults, who are highly vulnerable to natural disasters, such as hurricanes. Due to the influence of highly uncertain environmental conditions and varied NH characteristics (e.g., geo-location, staffing, residents’ health conditions), the NH evacuation response, namely evacuating or sheltering-in-place, is highly uncertain. Accurate prediction of NH evacuation response is important for emergency management agencies to accurately anticipate the NH evacuation demand surge with healthcare resources proactively planned. Existing hurricane evacuation research mainly focuses on the general population. For NH evacuation, existing studies mainly focus on conceptual studies and/or qualitative analysis using a single source of data, such as surveys or resident health data. There is a lack of research to develop analytics-based method by fusing rich environmental data with NH data to improve the prediction accuracy. In this paper, we propose a Geographic Information System (GIS) data enhanced predictive analytics approach for forecasting NH evacuation response by fusing multi-source data related to storm conditions, geographical information, NH organizational characteristics as well as staffing and residents characteristics of each NH. In particular, multiple GIS features, such as distance to storm trajectory, projected wind speed, potential storm surge and NH elevation, are extracted from rich GIS information and incorporated to improve the prediction performance. A real-world case study of NH evacuation during Hurricane Irma in 2017 is examined to demonstrate superior prediction performance of the proposed work over a large number of predictive analytics methods without GIS information.
After Hurricane Laura struck the southeast coast of Louisiana in August 2020, the National Disaster Medical System (NDMS), a component of the US Department of Health and Human Services, Office of the Assistant Secretary for Preparedness and Response, deployed several 35-person disaster medical assistance teams in response to requests for medical support at 3 hospital locations that had been severely damaged in the storm. This was the first natural disaster medical deployment for NDMS during the coronavirus disease (COVID-19) pandemic. This article describes the modifications to the standard operating procedures that were made at 1 site to reduce the risk of infection to our patients and NDMS responders, including changes to the physical layout of the tenting, and alterations to the triage and treatment process.
INTRODUCTION AND PURPOSE: The geographic location of the Gulf South leaves communities in continuous threat, response, and recovery disaster cycles. Hurricane Katrina in 2005 provided an opportunity to study disaster mental health. Less than 5 years after the storm, many Hurricane Katrina survivors were impacted again by the Deepwater Horizon Gulf oil spill. Despite adversities impacting Gulf communities, over 90% of participants reported they were resilient. The purpose of this study was to improve the understanding of the mechanisms that contribute to strengths following adversity in communities affected by repeated disasters. Specifically, we focused on survivor perceptions of personal, spiritual, or community changes in efforts to describe community resilience and posttraumatic growth (PTG). METHODS: Participants were recruited through a quantitative survey and community flyers. Participants represented southeastern Louisiana, in areas impacted by hurricanes and the oil spill-for a total of five focus groups and 41 participants. Focus groups began by asking each participant to provide a brief overview of their disaster survival story and three additional guiding strengths-based questions. Data were transcribed using Dragon Speech Recognition software. A total of 963 unique responses were analyzed and coded. RESULTS: The following themes were identified: connectedness (n = 259), coping (n = 94), spirituality (n = 60), adaptability (n = 47), and self-reliance (n = 23). Participants noted a growth mindset from the disasters and also acknowledged coinciding negative experiences (n = 154) associated with community change and loss, where subthemes included change in connectedness (n = 97), crime (n = 26), and feeling like an outsider (n = 31). DISCUSSION AND IMPLICATIONS: These findings help scholars and mental health practitioners better understand the lived experiences of PTG in a community of survivors impacted by recurring traumatic experiences. In keeping with previous literature, PTG and negative experiences associated with trauma are not mutually exclusive, but occur simultaneously. Our results offer a holistic picture of coping with cumulative or repeated traumas and suggest that connectedness, coping, and spirituality provide important buffers to negative psychosocial outcomes.
While much research investigates how social capital relates to mental health after disasters, less work employs a multi-scalar, multi-dimensional social capital framework. This study applies such a construct to an analysis of novel survey data of approximately 1,000 rural and urban Texans after Hurricane Harvey struck the United States in August 2017. On the individual level, it finds that greater social support is linked to fewer mental health impacts, but that greater civic and organisational engagement is connected to greater mental health impacts. At the community level, it finds that neither a density of bridging social capital organisations nor of bonding social capital organisations is associated with poorer mental health, although a greater number of bonding organisations is related to negative mental health impacts on rural residents. The paper concludes by focusing on how individual and community social capital relationships with mental health are contingent on measurement, scale, and rural or urban location.
Using data from the 2017-18 Health of Houston Survey, this study estimates the effect of Hurricane Harvey, the second costliest storm in the history of the United States, on the physical and mental health of adults living in Houston, Texas. The survey was fielded to a population-based probability sample whose data collection activities were interrupted and delayed by Hurricane Harvey. This interruption in data collection created a natural experiment that allowed for a comparison of community health before and after the storm. Following the storm, adults in Houston on average experienced an increase of 1.12 days a month of poor physical health and an increase of 1.31 days a month of poor mental health. These effects were most pronounced in parts of the city where structural damage from the storm was most severe.
BACKGROUND: Expressive writing requires journaling stressor-related thoughts and feelings over four daily sessions of 15 min. Thirty years of research have popularized expressive writing as a brief intervention for fostering trauma-related resilience; however, its ability to surpass placebo remains unclear. This study aimed to determine the efficacy of expressive writing for improving post-traumatic stress symptoms in perinatal women who were living in the Houston area during major flooding caused by Hurricane Harvey. METHODS: A total of 1090 women were randomly allocated (1:1:1) to expressive writing, neutral writing or no writing. Interventions were internet-based. Online questionnaires were completed before randomization and at 2 months post-intervention. The primary outcome was post-traumatic stress symptoms, measured with the Impact of Event Scale-Revised; secondary outcomes were affective symptoms, measured with the 40-item Inventory of Depression and Anxiety Scales. Feelings throughout the intervention were reported daily using tailored questionnaires. RESULTS: In intention-to-treat analyses, no post-treatment between-group differences were found on the primary and secondary outcomes. Per-protocol analyses yielded similar results. A number of putative moderators were tested, but none interacted with expressive writing. Expressive writing produced greater feelings of anxiety and sadness during the intervention compared to neutral writing; further, overall experiences from the intervention mediated associations between expressive writing and greater post-traumatic stress at 2 months post-intervention. CONCLUSIONS: Among disaster-stricken perinatal women, expressive writing was ineffective in reducing levels of post-traumatic stress, and may have exacerbated these symptoms in some.
IMPORTANCE: During the past century, more than 100 catastrophic hurricanes have impacted the Florida coast; climate change will likely be associated with increases in the intensity of future storms. Despite these annual threats to residents, to our knowledge, no longitudinal studies of representative samples at risk of hurricane exposure have examined psychological outcomes associated with repeated exposure. OBJECTIVE: To assess psychosocial and mental health outcomes and functional impairment associated with repeated hurricane exposure. DESIGN, SETTING, AND PARTICIPANTS: In this survey study, a demographically representative sample of Florida residents was assessed in the 60 hours prior to Hurricane Irma (wave 1: September 8-11, 2017). A second survey was administered 1 month after Hurricane Irma (wave 2: October 12-29, 2017), and a third survey was administered after Hurricane Michael (wave 3: October 22 to November 6, 2018). Data were analyzed from July 19 to 23, 2021. EXPOSURE: Hurricanes Irma and Michael. MAIN OUTCOMES AND MEASURES: The main outcomes were posttraumatic stress symptoms (PTSS), global distress, worry about future events (generalized worries), and functional impairment. Path models were used to assess associations of individual-level factors (prior mental health, recent adversity), prior storm exposures (loss and/or injury, evacuation), and direct, indirect, and media-based exposures to hurricanes Irma and Michael with those outcomes. Poststratification weights were applied to facilitate population-based inferences. RESULTS: Of 2873 individuals administered the survey in wave 1, 1637 responded (57.0% completion rate) (894 [54.6%, weighted] women; mean [SD] age, 51.31 [17.50] years); 1478 in wave 2 (90.3% retention from wave 1) and 1113 in wave 3 (75.3% retention from wave 2) responded. Prior mental health ailments (b, 0.18; 95% CI, 0.07-0.28), prior hurricane-related loss and/or injury (b, 0.09; 95% CI, 0.02-0.17), hours of Hurricane Irma-related media exposure (b, 0.03; 95% CI, 0.02-0.04), being in an evacuation zone during Hurricane Irma and not evacuating (b, 0.14; 95% CI, 0.02-0.27), and loss and/or injury in Hurricane Irma (b, 0.35; 95% CI, 0.25-0.44) were positively associated with PTSS after Hurricane Irma; most associations persisted and were associated with responses to Hurricane Michael. Prior mental health ailments (b, 0.10; 95% CI, 0.03-0.17), hours of Hurricane Michael-related media exposure (b, 0.01; 95% CI, 0.003-0.02), hurricane Irma-related PTSS (b, 0.42; 95% CI, 0.34-0.50), recent individual-level adversity (b, 0.03; 95% CI, 0.005-0.05), being in an evacuation zone during Hurricane Irma and evacuating (b, 0.10; 95% CI, 0.002-0.19), and direct (b, 0.36; 95% CI, 0.16-0.55) and indirect (b, 0.12; 95% CI, 0.05-0.18) Hurricane Michael-related exposures were directly associated with Hurricane Michael-related PTSS. After Hurricane Michael, prior mental health ailments (b, 0.17; 95% CI, 0.06-0.28), and PTSS related to hurricanes Irma (b, 0.11; 95% CI, 0.001-0.22) and Michael (b, 0.58; 95% CI, 0.47-0.69) were associated with respondents’ functional impairment. Analogous analyses using global distress and generalized worries as mediators of functional impairment yielded a similar pattern of results. CONCLUSIONS AND RELEVANCE: In this survey study, repeated direct, indirect, and media-based exposures to hurricanes were associated with increased mental health symptoms among Florida residents who experienced hurricanes Irma and Michael, suggesting that people were sensitized to respond with more psychological symptoms over time. These results may inform targeted public health intervention efforts for natural disasters.
Natural disasters have increased exponentially in recent decades, imposing existential threats to humans. Yet, surprisingly little research has explored the role of religion and spirituality (R/S) and transcendence-related character strengths in post-disaster depression. Using data (N = 491) from victims of Category 5 Hurricane Michael, this study examined whether R/S factors and character strengths helped to buffer against post-disaster depressive symptoms. A hierarchical regression model revealed an inverse association of perceived spiritual support with depression, after adjusting for demographic and event-related factors; strength of faith and the use of prayer for coping were not significantly related with depression. Upon inclusion of character strengths into the model, those relationships changed dramatically. Hope and optimism negatively predicted depression, whereas strength of faith and prayer for coping did so positively. Follow-up moderation analyses found that victims reporting particularly high levels of R/S factors and particularly low levels of character strength experienced the most depressive symptoms. The findings suggest that the potential protection of R/S factors in disasters may actually be due to transcendence-related character strength factors.
Prior research has found that the prevalence and severity of intimate partner violence (IPV) increase in communities experiencing a disaster. Less studied are the associations between IPV, disaster exposure, and mental health outcomes following disaster events. In the current study, authors examined the prevalence of IPV before and after Hurricane Harvey and the direct and indirect effects of risk (i.e., disaster exposure, IPV) and resilience on mental health outcomes using structural equation modeling with 382 adults. Results indicate that exposure to Hurricane Harvey was significantly associated with risk for IPV, posttraumatic stress (PTS) symptoms, and depression symptoms. In addition, IPV mediated the relationships between disaster exposure and PTS and depression symptoms. These findings support the need to incorporate IPV services and resources into disaster mental health services.
OBJECTIVE: Natural disasters, such as hurricanes, can contribute to the development of posttraumatic stress symptoms (PTSS), anxiety, and depression. Furthermore, mothers and children are especially vulnerable postdisasters. Despite the rise in the frequency of climate-related disasters and also the threat of disasters (e.g., storms that threaten but do not make landfall), little is known about how predisaster experiences are associated with mothers’ and children’s postdisaster psychological functioning. This study examined evacuation-related stressors as predictors of mothers’ and youths’ psychological functioning 3 months after Hurricane Irma. METHOD: Mothers (N = 535; 33% ethnic/racial minorities) from South Florida counties most affected by Hurricane Irma completed an online survey that assessed evacuation-related stressors (both pre- and posthurricane), hurricane exposure (i.e., life threat, loss/disruption), and posthurricane social support and mental health symptomatology (i.e., PTSS, anxiety, depression). Mothers of children aged 7-17 years (n = 226) also reported on their child’s psychological functioning. RESULTS: Using a risk and resilience model, evacuation stressors significantly predicted mothers’ and youths’ PTSS and symptoms of anxiety and depression, even after accounting for demographic factors, hurricane exposure, and availability of social support. Mothers of older children also reported significantly higher levels of PTSS, anxiety, and depression than mothers who only had young children (aged 6 or younger) at home. CONCLUSIONS: Evacuation experiences represent significant stressors that may put mothers and children at risk for PTSS and psychological distress. Resilience-building efforts should include efforts to better prepare families for prestorm evacuations, thereby reducing risk in mothers and youth and ultimately contributing to better psychosocial functioning. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
OBJECTIVE: Extreme weather events pose major risks to human health and have a greater psychological impact on women and parents, but little is known about how they affect health risk behaviors. This study evaluated how disaster-related experiences before, during, and after Hurricane Irma were associated with mothers’ health-risk behaviors, and the extent to which posttraumatic stress symptoms (PTSS) and depressive symptoms potentially mediated these relationships. METHOD: Mothers (N = 534; 33% underrepresented minorities) residing in Southern Florida completed an online survey about their evacuation experiences before and hurricane experiences during and after Irma. Mothers also completed measures of PTSS, depressive symptoms, and health risk behaviors (i.e., substance use, sedentary behaviors, and difficulty falling or staying asleep). Confirmatory factor analysis assessed the fit of the health-risk behavior indicators on a latent factor. Structural equation modeling evaluated relationships between variables. RESULTS: A one-factor model for health risk behaviors fit the data well. After controlling for income, loss and disruption after the storm and depressive symptoms were directly associated with mothers’ health risk behaviors. Before-the-storm evacuation stressors, actual life-threatening events during the storm, and loss and disruption after the storm were related to mothers’ PTSS and depressive symptoms and also associated with health risk behaviors indirectly via depressive symptoms. CONCLUSIONS: Stressful experiences before, during, and after hurricanes are associated with mothers’ health-risk behaviors via postevent emotional distress. Health interventions should include strategies that help parents cope with the impact of extreme weather events, both before and after such events occur. Mothers’ distress potentially could affect child health. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Weather-related disasters are increasing in both frequency and severity, which in turn increases the likelihood for the development of adverse mental health outcomes (Augustinavicius et al., 2021; CRED & UNDRR, 2015; NOAA National Centers for Environmental Information, 2020). Religion and spirituality are an accessible form of coping that many people turn to during and after weather-related disasters and may be especially valuable to survivors who face barriers to accessing mental health treatment or may not feel served by formal mental health institutions (Abu-Raiya & Pargament, 2015; Bryant-Davis & Wong, 2013). Researchers have drawn distinctions between positive religious coping (PRC) and negative religious coping (NRC), both conceptually and in their relation to mental health outcomes (Pargament et al., 2011). This study utilized data from the Resilience in Survivors of Katrina project, an ongoing longitudinal study of low-income, female, primarily Black Hurricane Katrina survivors, and drew on four waves of data from before the hurricane in 2005 through 2018 to explore the longitudinal relationship between religious coping and mental health outcomes. Multiple linear regression analyses revealed that NRC was a significant predictor of posttraumatic stress, b = .14, p < .05, whereas PRC was a significant predictor of posttraumatic growth, b = .22, p < .01. Future research should further examine associations between religious coping styles and later well-being as well as strategies for beneficial outcomes.
This study examined the extent to which Christian religious affiliation promoted greater forgiveness and search for meaning and consequently may have mitigated posttraumatic stress disorder (PTSD) symptoms in the wake of the devastation and loss following two hurricanes in Puerto Rico in 2017. Participants included 511 surviving Puerto Ricans. Most were assigned “female” at birth, educated, Christian, and middle-aged. Participants completed measures of PTSD symptoms, search for meaning, forgiveness, and demographics. Path modeling showed that Christian religious affiliation was negatively associated with PTSD symptoms and was positively associated with forgiveness but not search for meaning. Forgiveness was negatively and search for meaning was positively associated with PTSD symptoms. Christian religious affiliation may stimulate forgiveness, which may be a crucial factor for coping with PTSD symptoms in a natural disaster context such as Hurricanes Irma and Maria in Puerto Rico.
Prior research suggests that meaning-making and forgiveness are associated with lower post traumatic stress symptoms (PTSS) following exposure to trauma. Few studies have examined these factors in the aftermath of natural disasters. This study therefore aimed to investigate the relationship between meaning-making and forgiveness, and their association with PTSS after the 2017 Hurricane Maria in Puerto Rico. Bivariate correlations and hierarchical regression analyses indicated that meaning-making and forgiveness were negatively correlated with PTSS. Higher levels of “presence of meaning,” “self-forgiveness,” “forgiveness of others,” and “feeling forgiven by God” were significantly associated with lower levels of PTSS. Conversely, “search for meaning” was positively associated with PTSS. The results suggest the importance of meaning-making and forgiveness education for building and promoting well-being in the face of extreme stressors.
Several studies showed an association between lower respiratory tract symptoms (LRS) and exposure to the 9/11 terrorist attack. However, few studies have examined the long-term impact of natural disasters on those with prior respiratory distress. The present study aims to assess the impact of Hurricane Sandy on persistent LRS among people exposed to the World Trade Center (WTC) terrorist attack. The analytic sample consisted of WTC Health Registry enrollees who completed survey waves 1, 3, and 4 and the Hurricane Sandy Survey and did not report LRS before the WTC terrorist attack. The log binomial was used to assess the association between the impact of Hurricane Sandy and persistent LRS. Of 3277 enrollees, 1111 (33.9%) reported persistent LRS post-Sandy. Participants of older age, males, lower household income, current smokers, and those with previous asthma were more likely to report persistent LRS. In separate adjusted models, multiple Sandy-related inhalation exposures (relative risk (RR): 1.2, 95% CI: 1.06-1.37), Sandy-related PTSD (RR: 1.27, 95% CI: 1.15-1.4), and Sandy LRS (RR: 1.64, 95% CI: 1.48-1.81) were associated with persistent LRS post-Sandy. Our findings suggest that respiratory protection is important for everyone performing reconstruction and clean-up work after a natural disaster, particularly among those with previous respiratory exposures.
Natural disasters represent major stressors, resulting in psychological distress and physiological responses such as increased cortisol. During pregnancy, this impacts not only maternal well-being, but also fetal development. In 2018, Hurricane Florence caused extensive damage across the eastern United States. Studies indicated that compared to married pregnant women, unmarried pregnant women had higher risk of distress. Here we assess hair cortisol among a subsample of participants, and variations based on marital status. METHODS: We analyzed multiple stress measures among 37 participants who were pregnant during Hurricane Florence. We used questionnaires modeled on previous studies to assess hardship associated with the hurricane, psychological distress, sociodemographic characteristics, social support, and food security. We analyzed cortisol concentrations in proximal and distal hair sections, representing stress around the time of the disaster (distal) and 3-4 months following the disaster (proximal). We used linear regression to test relationships between hair cortisol and self-report stress measures, and variations based on marital status. RESULTS: Self-report measures of distress and hardship were similar among married and unmarried participants. Mean cortisol levels in distal and proximal sections were higher among unmarried participants. Controlling for confounding variables, hardship was not associated with hair cortisol. Distress predicted cortisol in distal sections (β = .482, p = .018), with a trend for proximal sections (β = .368, p = .055). Marital status was a significant predictor of distal (β = .388, p = .027) and proximal (β = .333, p = .047) hair cortisol, explaining 8.6%-11.7% of unique variance. CONCLUSIONS: Preexisting and intersecting risk factors likely place unmarried pregnant individuals at risk of stress during and following a disaster.
In theoretical research on disaster vulnerability, access to resources is critical for optimal outcomes. Studying the impact of a hurricane on maternal stress can expand theories of disaster vulnerability. This is a cross-sectional mixed-methods prospective study of maternal stress during Hurricane Florence in the United States. Results from chi-squares compared the proportion of respondents who reported having support for a financial emergency were significant, specifically that higher income respondents indicated the ability to rely on someone in case of an emergency. A regression analysis indicated that social support was significant and negatively related to stress as a dependent variable, while evacuation status and pregnancy status were not significant predictors of stress. Five themes emerged from the overall qualitative data: concerns about infant feeding, evacuation logistics, general stress, family roles, and ‘other’ issues.
Exposure to natural disasters predisposes individuals to significant physical and mental health consequences. Research identifies a number of stressors important to determining what might exacerbate this exposure risk, as well as what types of social/psychological resources might help mitigate these negative outcomes. Using a targeted quota sample of adults (n = 316) interviewed two months after Hurricane Harvey made landfall on the Gulf Coast of Texas in August 2017, the present study examines the intersection of vulnerabilities, stressors, and resources and their relationship with post-traumatic stress symptomatology. Stress is high among this sampled group with over one-quarter of respondents reporting high enough symptoms to meet the clinical caseness criteria for PTSD. Results show significant variation across categorical groupings of post-traumatic stress symptoms; younger persons, nonwhites, and those displaced from their home during the storm were more likely to be found in the highest symptom count category. Regression results confirm the bivariate results and as hypothesized, stressors were associated with higher symptom reporting among respondents, and social and psychological resources were associated with lower symptom reporting. With one of the only studies to report these relationships between vulnerability, stressors, and resources in the post-disaster Harvey setting, our work underscores the importance of identifying who is at risk, what factors can potentially mitigate that risk, and just how severe the consequences can be for survivors requiring mental health services after a disaster. Clearly, more work is needed, particularly on the identification of resources acting as protection against the overwhelming circumstances of exposure to devastation and destruction caused by natural disasters.
BACKGROUND: Although injuries experienced during hurricanes and other tropical cyclones have been relatively well-characterized through traditional surveillance, less is known about tropical cyclones’ impacts on noninjury morbidity, which can be triggered through pathways that include psychosocial stress or interruption in medical treatment. METHODS: We investigated daily emergency Medicare hospitalizations (1999-2010) in 180 US counties, drawing on an existing cohort of high-population counties. We classified counties as exposed to tropical cyclones when storm-associated peak sustained winds were ≥21 m/s at the county center; secondary analyses considered other wind thresholds and hazards. We matched storm-exposed days to unexposed days by county and seasonality. We estimated change in tropical cyclone-associated hospitalizations over a storm period from 2 days before to 7 days after the storm’s closest approach, compared to unexposed days, using generalized linear mixed-effect models. RESULTS: For 1999-2010, 175 study counties had at least one tropical cyclone exposure. Cardiovascular hospitalizations decreased on the storm day, then increased following the storm, while respiratory hospitalizations were elevated throughout the storm period. Over the 10-day storm period, cardiovascular hospitalizations increased 3% (95% confidence interval = 2%, 5%) and respiratory hospitalizations increased 16% (95% confidence interval = 13%, 20%) compared to matched unexposed periods. Relative risks varied across tropical cyclone exposures, with strongest association for the most restrictive wind-based exposure metric. CONCLUSIONS: In this study, tropical cyclone exposures were associated with a short-term increase in cardiorespiratory hospitalization risk among the elderly, based on a multi-year/multi-site investigation of US Medicare beneficiaries ≥65 years.
Hurricane or typhoon evacuations in the United States are typically managed by state, territorial, or tribal emergency management officials with federal, state, and local agency operational support. The evacuation process may involve issuing mandatory or “voluntary” evacuation orders to alert the community and mitigate loss of life and injury. We conducted an analysis of state and local hurricane evacuation policies identified through a literature review (January 1990 to June 2019) and key informant interviews with state public health and emergency management officials in Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, and Texas in October and November 2019. Findings from the literature review show that most gaps in hurricane evacuation preparedness-based on 44 policy-related publications identified in the review-could be categorized into 4 themes: shelters, evacuation decisionmaking, at-risk populations, and transportation. Findings from key informant interviews for 7 states revealed that coastal states have been able to address most of these gaps since Hurricane Katrina in 2005. However, an important remaining gap in preparedness is providing timely warnings to at-risk populations during hurricane evacuations.
This case study presents an evaluation framework to assess the facilitating and constraining factors that influenced the emergency response, operation, and management of a Special Needs Shelter Program in Monroe County, Florida during Hurricane Irma in 2017. A qualitative analysis of key documents and discussions with agencies directly involved in the Monroe County Special Needs Shelter Program was used to assess four major emergency response processes: notifications and communications, evacuation and transportation, sheltering, and interagency coordination. A critical cross-cutting theme emerged, which was a lack of a common definition for populations with “special needs” across different agencies resulting in uncertainties about who should be admitted to the Special Needs Shelter and have access to their services. We generate public health and emergency management lessons to inform future adaptation, preparedness, and response plans to extreme weather events for populations with access and functional needs in Monroe County and Florida’s coastal communities more broadly.
As climate change progresses, it is crucial that researchers and policymakers understand the ways in which climate-mental health risks arise through interactions between climate hazards, human exposure and social vulnerabilities across time and location. This scoping review systematically examined the nature, range and extent of published research in North America that investigates climate-mental health interactions. Five electronic databases were searched and two independent reviewers applied pre-determined criteria to assess the eligibility of articles identified in the search. Eighty-nine articles were determined to be relevant and underwent data extraction and analysis. The published literature reported on numerous exposure pathways through which acute and chronic climate hazards interacted with social vulnerabilities to increase mental health risks, including wellbeing, trauma, anxiety, depression, suicide and substance use. This review also highlights important gaps within the North American climate-mental health evidence base, including minimal research conducted in Mexico, as well as a lack of studies investigating climate-mental health adaptation strategies and projected future mental health risks. Further research should support effective preparation for and adaptation to the current and future mental health impacts of climate change. Such strategies could reduce health risks and the long-term mental health impacts that individuals and communities experience in a changing climate.
Hurricane Maria is regarded as one of the worst natural disasters in United States history as it devasted Puerto Rico (PR) in September 2017. This study compared population-based key health indicators among PR residents pre-and post-Hurricane Maria. We examined Behavioral Risk Factor Surveillance System (BRFSS) PR data from five survey years, including pre-and post-Hurricane Maria: 2015 (N = 4556), 2016 (N = 5765), 2017 (N = 4462), 2018 (N = 4814), and 2019 (N = 4958). The sample consisted of non-institutionalized adults aged ≥ 18 years with access to a landline or a cellular telephone. Using logistic regression we compared health care utilization, health behaviors, and outcomes pre-and post-Hurricane Maria. Models adjusted for age, sex, race, education, employment, income, and marital status (2017 = referent). Compared to 2017, post-hurricane participants were more likely to have a college degree or higher, be currently employed, and not married/partnered. Post-hurricane, participants were less likely to have health insurance coverage (2018 AOR, 95% CI: 0.75, 0.58-0.97) and had lower rates of diabetes (2018 AOR: 0.82, 0.70-0.96). The odds of being overweight/obese were lower pre-hurricane compared to 2017 (2015 AOR, 95% CI: 0.88, 0.79-0.97). There was no statistically significant difference in health behaviors across survey years. Results may suggest that PR residents with lower socioeconomic status and/or chronic illness were more likely to emigrate, resulting in a compositional change in the population post-hurricane. This analysis highlights the need for long-term follow-up of PR residents to better determine the impact of Hurricane Maria, and adequately design public health programs to address healthcare needs, access, and outcomes.
OBJECTIVE: To assess changes in the availability of mental health crisis services in Puerto Rico relative to US states before and after Hurricanes Maria and Irma. DATA SOURCES/STUDY SETTING: National Mental Health Services Surveys conducted in 2016 and 2020. STUDY DESIGN: Repeated cross-sectional design. The independent variable was mental health facility location in Puerto Rico or a US state. Dependent variables were the availability of three mental health crisis services (psychiatric emergency walk-in services, suicide prevention services, and crisis intervention team services). DATA COLLECTION/EXTRACTION METHODS: The proportion and per 100,000 population rate of facilities offering crisis services were calculated. PRINCIPAL FINDINGS: The availability of crisis services at mental health facilities in Puerto Rico remained stable between 2016 and 2020. These services were offered less at indigent care facilities in Puerto Rico than US states (e.g., 38.2% vs. 49.5% for suicide prevention, p = 0.06) and the magnitude of difference increased following Hurricane Maria. CONCLUSIONS: There are disparities between Puerto Rico and US states in the availability of mental health crisis services for indigent patients.
Disaster research concerning the behavior of international students at U.S. institutions of higher education is very limited. The main objective of our study is to develop new knowledge about international student’s behavior at U.S. institutions of higher education in relation to hurricanes in order to enhance the overall campus crisis management. A mix of quantitative and qualitative methods was used to collect data from University of Florida (UF) main campus in Gainesville, Florida; UF administrative leaders committed to international students’ safety in emergencies were interviewed. In addition, 120 international students at UF were surveyed. The data analysis sought to provide insights into one main research question: In a disaster-context, what challenges do international students face that contribute to their vulnerability at UF main campus? Three main groups of challenges were found; Institutional challenges, Students’ well-being and daily challenges, and Disaster preparedness challenges. Moreover, considerable variations in students’ behavior were found among some demographics, including gender, ethnicity, housing, degree level, and previous hurricane experience. The research findings shed a light on a research area that has been under-investigated, and contribute to an increased understanding of international students’ vulnerabilities at U.S. institutions of higher education.
OBJECTIVE: Research indicates that greater exposure to Hurricane Sandy is associated with increased mental health difficulties. This study examined whether Project Restoration, a program that linked adults into mental health care (L2C), was effective in reducing post-Sandy mental health difficulties as compared to a cohort of adults matched on mental health difficulties that were not linked into post-Sandy mental health care. METHODS: Project Restoration participants (n = 52) with elevated self-reported mental health difficulties had the option to enroll into L2C. Project LIGHT (n = 63) used similar methodologies but did not have a L2C component and served as the matched control group. RESULTS: Multivariable modeling showed significant decreases in all mental health difficulties except for depression in the Project Restoration group, whereas there were no significant decreases in LIGHT. The decrease in anxiety from baseline to follow-up was significantly greater for Project Restoration as compared to LIGHT. CONCLUSION: Findings confirm the powerful impact community outreach and treatment have on reducing mental health difficulties after a disaster.
OBJECTIVES: To examine whether hurricane exposure, lack of access to medical care (LAMC), and displacement during Hurricane Sandy were associated with PTSD and other mental health (MH) symptoms among older adult New York residents. METHODS: Participants (N = 411) were ≥60 years old at the time of survey data collection (1-4 years post-Sandy). Outcomes included PTSD, depression, and anxiety symptoms and stress. Hurricane exposure, displacement, and LAMC were primary predictors. RESULTS: Older adults with greater hurricane exposure had increased PTSD, anxiety, and stress symptoms. LAMC had a strong association (ORadj = 4.11) with PTSD symptoms but was not associated with other MH symptoms. Displacement was not associated with MH outcomes. DISCUSSION: This is the first study to examine exposure, displacement, and LAMC together and to examine their varying impacts on different MH outcomes among older adults post-hurricane. Findings support the importance of disaster preparedness interventions tailored to the MH needs of community-dwelling older adults.
Early forecasts give people in a storm’s path time to prepare. Less is known about the cost to society when forecasts are incorrect. In this observational study, we examine over 700,000 births in the path of Hurricane Irene and find exposure was associated with impaired birth outcomes. Additional warning time was associated with decreased preterm birth rates for women who experienced intense storm exposures documenting a benefit of avoiding a type II forecasting error. A larger share of this at-risk population experienced a type I forecasting error where severe physical storm impacts were anticipated but not experienced. Disaster anticipation disrupted healthcare services by delaying and canceling prenatal care, which may contribute to storm-impacted birth outcomes. Recognizing storm damages depend on human responses to predicted storm paths is critical to supporting the next generation’s developmental potential with judicious forecasts that ensure public warning systems mitigate rather than exacerbate climate damages.
INTRODUCTION: Hurricanes Irma and Maria made landfall in the US Virgin Islands (USVI) in 2017. To date, there is no published literature available on the experiences of pregnant women in the USVI exposed to these hurricanes. Understanding how hurricanes affect pregnant women is key to developing and executing targeted hurricane preparedness and response policies. The purpose of this study was to explore the experiences of pregnancy and birth among women in the USVI exposed to Hurricanes Irma and Maria. METHODS: We employed a qualitative descriptive methodology to guide sampling, data collection, and analysis. Semi-structured interviews of 30-60 min in length were conducted with a purposive sample of women (N = 18) in the USVI who were pregnant during or became pregnant within two months after the hurricanes. Interviews were transcribed verbatim and data managed in MAXQDA. Team members developed a codebook, applied codes for content, and reconciled discrepancies. We thematically categorized text according to a socioecological conceptual framework of risk and resilience for maternal-neonatal health following hurricane exposure. RESULTS: Women’s experiences were organized into two main categories (risk and resilience). We identified the following themes related to risk at 3 socioecological levels including: (1) individual: changes in food access (We had to go without) and stress (I was supposed to be relaxing); (2) household/community: diminished psychosocial support (Everyone was dealing with their own things) and the presence of physical/environmental hazards (I was really scared); and (3) maternity system: compromised care capacity (The hospital was condemned). The themes related to resilience included: (1) individual: personal coping strategies (Being calm); (2) household/community: mutual psychosocial and tangible support (We shared our resources); and (3) the maternity system: continuity of high-quality care (On top of their game). CONCLUSIONS: A socioecological approach provides a useful framework to understand how risk and resilience influence the experience of maternal hurricane exposure. As the frequency of the most intense hurricanes is expected to increase, clinicians, governments, and health systems should work collaboratively to implement hurricane preparedness and response plans that address pregnant women’s unique needs and promote optimal maternal-infant health.
OBJECTIVE: The aim of this study was to use a mixed-method analysis to investigate the associations between qualitative themes found in written responses and quantitative reported level of stress after Hurricane Sandy. METHODS: A survey was conducted among World Trade Center Health Registry enrollees 5-12 mo after Hurricane Sandy. This study included 1202 participants who completed the free-response section and answered the question on how stressful their experiences were with Hurricane Sandy and its aftermath. Content analysis was used to generate qualitative data. Mixed-methods analysis was performed using a 1-way analysis of variance test for bivariate comparisons of qualitative thematic codes and the quantitative outcome of mean Sandy stress scores. RESULTS: Seven themes emerged from the qualitative analysis. The themes of lack of information, negative emotional response, and financial stress had higher quantitative mean Sandy stress scores compared with other themes. The theme of patriotism/gratitude had an overall lower quantitative Sandy stress scores than other themes. CONCLUSIONS: Qualitative and mixed-methods research on mental health outcomes after a disaster add new depth and findings to the existing literature. Using such methodologies to identify modifiable factors, such as improving communication during a disaster, may confer better mental health outcomes after a disaster.
PURPOSE: In September 2017, Hurricane Maria devastated Puerto Rico. Houses were destroyed, millions of people lost power and access to clean water, and many roads were flooded and blocked. In the years following the storm, hundreds of thousands of people have left Puerto Rico and settled on the U.S. mainland. The purpose of this study is to examine the impact of disaster trauma among Puerto Rican adults who moved to the U.S. mainland after Hurricane Maria. METHOD: Participants were 319 adult Puerto Rican Hurricane Maria survivors on the U.S. mainland. Women comprised 71.2% of the sample. Data were collected between August 2020 and October 2021. Participants completed Spanish-language measures of hurricane-related trauma, perceived ethnic discrimination and negative context of reception on the U.S. mainland, language stress, depressive symptoms, anxiety, optimism, life satisfaction, and problem drinking. RESULTS: We estimated a structural equation model where hurricane trauma predicted cultural stress, which in turn predicted internalizing symptoms, optimism, and life satisfaction. Internalizing symptoms, optimism, and life satisfaction were specified as predictors of problem drinking. Results indicated that hurricane trauma predicted cultural stress. Cultural stress predicted internalizing symptoms, optimism, and life satisfaction. Internalizing symptoms predicted problem drinking. Hurricane trauma indirectly predicted internalizing symptoms through cultural stress and indirectly predicted problem drinking through cultural stress and internalizing symptoms. CONCLUSIONS: Traumatic experiences from the storm may predispose Puerto Rican Hurricane Maria survivors to perceive cultural stress on the U.S. mainland. In turn, cultural stressors may be associated with internalizing symptoms and alcohol problems. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Formulating disaster responses that mitigate social inequalities is crucial because disasters disproportionately harm marginalized communities. This study seeks to inform more equitable post-disaster policies by examining how post-disaster residential outcomes relate to subsequent income and health outcomes among a sample of Hurricane Katrina survivors. Analyzing pre-hurricane survey data, three waves of survey data over 12-15 years post-disaster for 385 low-income women, as well as qualitative data from a subset of participants, we show that durable residence in counties previously shown to promote greater intergenerational socioeconomic advancement predicts higher income, but not better mental or self-rated health. Statistical control for prospectively collected, pre-disaster confounders, coupled with qualitative insights, suggest causal relationships between county-level opportunity and income. We further find that persis-tence in high opportunity counties was driven by family obligations, relationship changes, or access to job opportunities, not differences in individual priorities. Disaster policy should better support displaced survivors’ ability to access high opportunity areas.
BACKGROUND: Few studies have evaluated the long-term effects of disasters on older adults. We examined if older individuals experienced increased mental health (MH) effects immediately and long-term after Hurricane Sandy and if these effects varied by socioeconomic status (SES), disease subtypes, number of comorbidities, and length of stay. METHODS: We identified older patients (≥64 years) with hospital admissions and Emergency Department (ED) visits (2001-2015) with primary diagnosis of MH diseases using the New York State discharged data. We quantified both short-term (immediately post-Sandy) and long-term effects (3-month, 1-year, 2-year, and 3-year) following Hurricane Sandy, and used the pre-Sandy period in the affected counties as the control period. Poisson regression was used to compare daily counts of MH cases overall and by multiple strata pre-/post Sandy. FINDINGS: Older individuals had significantly increased risk of MH ED visits immediately (32%), and 3-months, 1, 2, and 3-years after Sandy (2%, 9%, 15%, and 10%, respectively). MH hospital admissions did not increase immediately, but significantly increased by 8% a year later. Males and those with low SES had delayed, but increased risks of MH 1-3 years after Sandy (RRs range: 1.14-1.71). The top MH subtypes after Sandy were psychosis, mood disorders, substance abuse, suicide, and anxiety (RRs range: 1.12-2.62). After Sandy, patients with ≥8 comorbidities increased from 15% to >25%, along with their length of hospital stay. CONCLUSION: We found long-term adverse effects of MH after Sandy, especially among vulnerable populations, which may help plan future disaster preparedness and recovery efforts.
OBJECTIVES: To evaluate the association between adverse experiences during Hurricane María and mental and emotional distress in Puerto Rico. METHODS: This cross-sectional study used baseline data from adult (30-75 years) participants of the Puerto Rico Observational Study of Psychosocial, Environmental, and Chronic Disease Trends (PROSPECT). Enrolled individuals prior to COVID-19 who completed a 33-item questionnaire on Hurricane María-related experiences (sub-categorized as personal, service, or property losses), depression symptomatology, post-traumatic stress disorder (PTSD), and anxiety were included for analysis (n = 456). RESULTS: Most participants experienced fear for their family’s safety, damage to their home and personal items, communication outages, and water shortages. Each additional stressor was significantly associated with higher odds of depression symptoms, PTSD, and anxiety. Personal losses were significantly associated with higher likelihood of all outcomes, while services losses were associated with depression symptoms and anxiety; property loss was not significantly associated with any outcome. CONCLUSIONS: Adverse experiences during a major natural disaster are associated with mental and emotional distress. Strategies to minimize hardships during natural disasters, especially personal and service losses, are essential to preserve mental health. Post-disaster psychological support to individuals is crucial.
OBJECTIVE: To examine the levels of burnout and self-perceived stress in workers at the Puerto Rico Electric Power Authority, who experienced major disasters: Hurricanes Irma and Maria. METHODS: A quantitative descriptive cross-sectional study with a non-probabilistic convenience sample was conducted in workers at the Puerto Rico Electric Power Authority. A structured questionnaire was administered to a sample of 163 eligible participants, aged 21 years and older, who participated voluntarily. Using employees of the electric company, the study examined the relationships between burnout and several characteristics (years of employment, existing health conditions, and coping strategies) both before and after Hurricanes Irma and Maria. Burnout was assessed with Gil-Monte’s Spanish Burnout Inventory, and self-perceived stress was assessed with the 14-item Perceived Stress Scale. RESULTS: Before the hurricanes, 16.6% of the workers reported high levels of burnout syndrome, while, after the hurricanes, the proportion increased to one-fifth (20.9%). Prior to the 2 hurricanes, more than one-fourth (23.4%) of the sample reported being extremely stressed; after the hurricanes, that proportion increased to 55%. Factors such as years of employment, counseling, and self-perceived stress showed significant statistical associations (P < .05) with burnout. CONCLUSION: From a public health standpoint, priority should be given to this population, thereby preventing burnout and any other negative effects of the aftermath (i.e., the lengthy response, recovery, and reconstruction) of these kinds of major disaster.
Based on data from 103 surveys of Puerto Rican migrants living in Florida and 54 in-depth interviews with a subgroup of them, we examine how Puerto Ricans who left the archipelago after Hurricane Maria have navigated settlement in their new homes. In this article, we observed and classified our participants’ descriptions of how they managed opportunities and challenges regarding education, employment, and social relations, the traditional benchmarks for the assessment of societal integration. We also observed how our participants described Covid-19’s interaction with these benchmarks. We found that our participants have experienced a series of cascading disasters since 2017-namely, Hurricane Maria, the earthquakes that affected Puerto Rico starting in late 2019, the humanitarian crises that followed both disasters, and now the global pandemic. These disasters, compounded with migration, have resulted in a process of adaptation to Florida in which social and labor-market integration and the ability to nurture social ties have been significantly diminished.
Media use can be beneficial in many ways, but little is known about how it might improve wellbeing outcomes following a traumatic natural disaster. Survivors (n = 491) of deadly Hurricane Michael, which struck the Florida (USA) coastline in 2018, completed an online survey, reporting indicators of post-traumatic growth (PTG) and stress (PTSS). A serial mediation model explored how hurricane-related stressors were related to both outcomes, as mediated by approach, avoidant, and support-seeking coping strategies and post-hurricane hedonic, eudaimonic, and self-transcendent media use as coping tools. Factors contributing to each type of post-hurricane media use were also explored. Results indicate that hurricane-related stressors were associated with PTG, serially mediated through approach coping strategies and self-transcendent media use, thus providing some of the first empirical evidence of the longer-term, beneficial wellbeing effects of media use on survivors of trauma. Additionally, hurricane-related stressors were associated with avoidant coping strategies, which were associated with increased eudaimonic media use. However, hedonic and eudaimonic media use were not associated with PTSS or PTG. Finally, factors known to be associated with media use were not predictive of post-hurricane media use, perhaps suggesting that media play a different role in survivors’ lives in the months following a traumatic event.
Disasters adversely affect individuals’ mental health; yet, research is scant on the mental health needs of frontline workers during and immediately after disasters. Our study explored this gap through the perspectives of home-based care providers (HBCP) who provided care during and after Hurricanes Irma and Harvey. In this qualitative study, five in-person focus groups were held between January and November 2019 with 25 HBCP drawn from home health care agencies in southern Florida and the Greater Houston Area. Four themes were identified using an abductive analytic approach: HBCPs’ disaster-related mental health needs; HBCP resilience in the context of disaster; psychological tensions associated with simultaneously caring for self, family, and patients; and supporting patients’ mental health needs during and after disaster. Our data suggest that HBCP may benefit from formal training and interventions to support their own mental health as well as that of their patients in the context of disasters.
BACKGROUND: Natural disasters are associated with increased mental health disorders and suicidal ideation; however, associations with suicide deaths are not well understood. We explored how Hurricane Florence, which made landfall in September 2018, may have impacted suicide deaths in North Carolina (NC). METHODS: We used publicly available NC death records data to estimate associations between Hurricane Florence and monthly suicide death rates using a controlled, interrupted time series analysis. Hurricane exposure was determined by using county-level support designations from the Federal Emergency Management Agency. We examined effect modification by sex, age group, and race/ethnicity. RESULTS: 8363 suicide deaths occurred between January 2014 and December 2019. The overall suicide death rate in NC between 2014 and 2019 was 15.53 per 100 000 person-years (95% CI 15.20 to 15.87). Post-Hurricane, there was a small, immediate increase in the suicide death rate among exposed counties (0.89/100 000 PY; 95% CI -2.69 to 4.48). Comparing exposed and unexposed counties, there was no sustained post-Hurricane Florence change in suicide death rate trends (0.02/100 000 PY per month; 95% CI -0.33 to 0.38). Relative to 2018, NC experienced a statewide decline in suicides in 2019. An immediate increase in suicide deaths in Hurricane-affected counties versus Hurricane-unaffected counties was observed among women, people under age 65 and non-Hispanic black individuals, but there was no sustained change in the months after Hurricane Florence. CONCLUSIONS: Although results did not indicate a strong post-Hurricane Florence impact on suicide rates, subgroup analysis suggests differential impacts of Hurricane Florence on several groups, warranting future follow-up.
Situations faced in the advent of powerful hurricanes can be stressful for individuals due to the uncertainty they bring along. The consequences of these phenomena can leave individuals’ recovery in their own hands until order is re-established, and support can reach out to them. This work aims to develop a tool to guide individuals through their decision-making during a hurricane disaster and recovery, using the experience of Hurricane María. The tool is a classic inventory model adapted to monitor individual’s wellness through 48 hours after a hurricane arrival. This article presents the three stages followed in the development in this work: the assessment of individuals’ sentiments toward Hurricane María via an online questionnaire, the development of the mathematical model, and the creation of a prototype in the form of a mobile application. Each phase presents an important contribution: a summary of first-hand knowledge obtained from the reactions of individuals who survived Hurricane María, a novel modeling approach to the problem, and a convenient framework that synthesizes both previous components.
OBJECTIVES: Natural disasters can have devastating, long-lasting effects on the mental health of older adults. However, few studies have examined associations among disaster exposure and positive and negative affect, and no longitudinal studies have investigated the extent to which predisaster perceived social support affects these associations. These analyses examine the associations among predisaster perceived social support, disaster exposure, and positive and negative affect experienced by community-dwelling older adults 4 years after Hurricane Sandy, controlling for predisaster affect. METHODS: Self-reported data collected before and after Hurricane Sandy from participants (aged 50-74 years) in the ORANJ BOWL panel (N = 2,442) were analyzed using linear regression models. RESULTS: Higher levels of peritraumatic stress experienced during Hurricane Sandy and greater hardship experienced after the storm were associated with more negative affect 4 years following the disaster. Higher perceived social support at baseline was related to more positive affect and less negative affect both before and after the hurricane. Social support did not moderate the effect of hurricane exposure on either positive or negative affect. DISCUSSION: Findings suggest that psychological effects may persist years after natural disasters and that more effective interventions may be needed during and after a disaster. While social support is critical to positive and negative affect in general, its buffering effects when disaster strikes may be limited.
Hurricane Harvey was associated with flood-related damage to chemical plants and oil refineries, and the flooding of hazardous waste sites, including 13 Superfund sites. As clean-up efforts began, concerns were raised regarding the human health impact of possible increased chemical exposure resulting from the hurricane and subsequent flooding. Personal sampling devices in the form of silicone wristbands were deployed to a longitudinal panel of individuals (n = 99) within 45 days of the hurricane and again one year later in the Houston metropolitan area. Using gas chromatography−mass spectroscopy, each wristband was screened for 1500 chemicals and analyzed for 63 polycyclic aromatic hydrocarbons (PAHs). Chemical exposure levels found on the wristbands were generally higher post-Hurricane Harvey. In the 1500 screen, 188 chemicals were detected, 29 were detected in at least 30% of the study population, and of those, 79% (n = 23) were found in significantly higher concentrations (p < 0.05) post-Hurricane Harvey. Similarly, in PAH analysis, 51 chemicals were detected, 31 were detected in at least 30% of the study population, and 39% (n = 12) were found at statistically higher concentrations (p < 0.05) post-Hurricane Harvey. This study indicates that there were increased levels of chemical exposure after Hurricane Harvey in the Houston metropolitan area.
Disparities exist in post-disaster flooding exposure and vulnerable populations bear a disproportionate impact of this exposure. We describe the unequal burden of flooding in a cohort of New York residents following Hurricane Sandy and assess whether the likelihood of flooding was distributed equally according to socioeconomic demographics, and whether this likelihood differed when analyzing self-reported or FEMA flood exposure measures. Residents of New York City and Long Island completed a self-administered survey 1.5-4.0 years after the storm. Multivariable logistic regressions were performed to determine the relationship between sociodemographic characteristics and flood exposure. Participants (n = 1231) residing in areas of the lowest two quartiles of median household income experienced flooding the most often (FEMA/self-reported: <$40,298: 65.3%/42.0%, $40,298-$67,188: 43.3%/32.1%), and these areas contained the highest proportions of non-White participants (<$40,298: 39.1%, $40,298-$67,188: 36.6%) and those with ≤high school education (<$40,298: 35.5%, $40,298-$67,188: 33.6%). Both self-report (p < 0.05) and FEMA (p < 0.05) flood measures indicated that older participants were more likely to live in a household exposed to flooding, while those living in higher-income areas had decreased likelihood of flooding (p < 0.0001). Socioeconomic and age disparities were present in exposure to flooding during Hurricane Sandy. Future disaster preparedness responses must understand flooding from an environmental justice perspective to create effective strategies that minimize disproportionate exposure and its adverse outcomes.
OBJECTIVES: To assess the economic and mental health impacts of COVID-19 in the presence of previous exposure to flooding events. METHODS: Starting in April 2018, the Texas Flood Registry (TFR) invited residents to complete an online survey regarding their experiences with Hurricane Harvey and subsequent flooding events. Starting in April 2020, participants nationwide were invited to complete a brief online survey on their experiences during the pandemic. This study includes participants in the TFR (N = 20,754) and the COVID-19 Registry (N = 8568) through October 2020 (joint N = 2929). Logistic regression and generalized estimating equations were used to examine the relationship between exposure to flooding events and the economic and mental health impacts of COVID-19. RESULTS: Among COVID-19 registrants, 21% experienced moderate to severe anxiety during the pandemic, and 7% and 12% of households had difficulty paying rent and bills, respectively. Approximately 17% of Black and 15% of Hispanic households had difficulty paying rent, compared to 5% of non-Hispanic white households. The odds of COVID-19 income loss are 1.20 (1.02, 1.40) times higher for those who previously had storm-related home damage compared to those who did not and 3.84 (3.25-4.55) times higher for those who experienced Harvey income loss compared to those who did not. For registrants for whom Harvey was a severe impact event, the odds of having more severe anxiety during the pandemic are 5.14 (4.02, 6.58) times higher than among registrants for whom Harvey was a no meaningful impact event. CONCLUSIONS: Multiple crises can jointly and cumulatively shape health and wellbeing outcomes. This knowledge can help craft emergency preparation and intervention programs.
Flood risk assessment requires a quantitative understanding of hazards and vulnerability. In the coastal built environment, the human’s vulnerability to combined hazards due to the floodwater and winds is an integral component of flood risks. The present study aims to reveal the human vulnerability to storm-induced coastal flooding, focusing on New York City during Hurricane Sandy. We develop a physics-based model to quantify individuals’ physical vulnerability, both adults and children, to compound hazards of floodwater and winds. The model accounts for the failure of individuals caused by physical instability due to slipping and toppling. The governing equations consider the balance between the driving and resisting forces and moments applied to an individual concurrently exposed to floodwater and winds. We first calibrate the model using existing measurements in the literature and then implement it to study the vulnerability of New York residents in Manhattan to coastal flooding during Hurricane Sandy. Model results indicate that when combined floodwater and wind hazards were at their highest-level during Sandy, the majority of flooded areas were mainly a hazardous zone for adults and either a failure or drowning zone for children. About 5.4% and 47.4% of the total flooded area became a failure zone, and 19.9% and 42.4% became a drowning zone for adults and children, respectively. We conclude that winds can have a significant impact on the physical instability of individuals. For example, model results for children show that neglecting winds results in a reduction of 97.7% in the area of the failure zone.
Coastal and riverine communities in the United States are largely unprepared for the projected effects of the climate crisis, including more intense storm surges, sea level rise, and increased precipitation. Flooding poses its own hazards, but in recent years, chemical releases triggered by extreme weather, such as hurricanes, have become more frequent, exposing nearby communities to toxic chemicals in the midst of natural disaster. This article reviews the public health implications of chemical releases triggered by extreme weather and provides commentary on possible policy solutions. The Gulf Coast, where there is an abundance of chemical facilities, is particularly vulnerable to these events, one of the latest examples being the August 2020 BioLab chlorine factory fire in Lake Charles, Louisiana, during Hurricane Laura. Low-wealth, Black, and Hispanic communities are disproportionately located near high-risk chemical facilities. The cumulative burden of flooding, toxic chemical releases, and other social stressors borne of systemic racism harms these communities, highlighting a critical environmental injustice. The federal and state governments have failed to develop regulatory safeguards that would prevent chemical releases triggered by extreme storms. State regulators should make facility reporting data available to the public and establish a regulatory regime for aboveground storage tanks. State regulators should also complete an analysis of flood risks to high-risk chemical facilities and impacts on historically disenfranchised communities, require permitted facilities to implement climate-responsive spill preventions practices, and establish a task force that can investigate strategies to prevent climate-driven chemical disaster and engage key stakeholders.
Natural disasters such as floods and hurricanes impact urbanized estuarine environments. Some impacts pose potential environmental and public health risks because of legacy or emerging chemical contamination. However, characterizing the baseline spatial and temporal distribution of environmental chemical contamination before disasters remains a challenge. To address this gap, we propose using systematic evidence mapping (SEM) in order to comprehensively integrate available data from diverse sources. We demonstrate this approach is useful for tracking and clarifying legacy chemical contamination reporting in an urban estuary system. We conducted a systematic search of peer-reviewed articles, government monitoring data, and grey literature. Inclusion/exclusion criteria are used as defined by a Condition, Context, Population (CoCoPop) statement for literature from 1990 to 2019. Most of the peer-reviewed articles reported dioxins/furans or mercury within the Houston Ship Channel (HSC); there was limited reporting of other organics and metals. In contrast, monitoring data from two agencies included 89-280 individual chemicals on a near-annual basis. Regionally, peer-reviewed articles tended to record metals in Lower Galveston Bay (GB) but organics in the HSC, while the agency databases spanned a wider spatial range in GB/HSC. This SEM has shown that chemical data from peer-reviewed and grey literature articles are sparse and inconsistent. Even with inclusion of government monitoring data, full spatial and temporal distributions of baseline levels of legacy chemicals are difficult to determine. There is thus a need to expand the chemical, spatial, and temporal coverage of sampling and environmental data reporting in GB/HSC.
OBJECTIVES: Extensive floodwater damage following hurricane Harvey raised concerns of increase in invasive mould infections (IMIs), especially in immunocompromised patients. To more comprehensively characterize the IMI landscape pre- and post-Harvey, we used a modified, less restrictive clinical IMI (mcIMI) definition by incorporating therapeutic-intent antifungal drug prescriptions combined with an expanded list of host and clinical features. METHODS: We reviewed 103 patients at MD Anderson Cancer Center (Houston, Texas), who lived in Harvey-affected counties and had mould-positive cultures within 12 months pre-/post-Harvey (36 and 67 patients, respectively). Cases were classified as proven or probable IMI (EORTC/MSG criteria), mcIMI, or colonization/contamination. We also compared in-hospital mortality and 42- day survival outcomes of patients with mcIMI pre-/post-Harvey. RESULTS: The number of patients with mould- positive cultures from Harvey-affected counties almost doubled from 36 pre- Harvey to 67 post- Harvey (p < 0.01). In contrast, no significant changes in (mc)IMI incidence post-Harvey nor changes in the aetiological mould genera were noted. However, patients with mcIMIs from flood affected areas had significantly higher in-hospital mortality (p = 0.01). CONCLUSIONS: We observed increased colonization but no excess cases of (mc)IMIs in immunosuppressed cancer patients from affected areas following a large flooding event such as hurricane Harvey.
OBJECTIVES: When Hurricane Harvey struck the coastline of Texas in 2017, it caused 88 fatalities and over US $125 billion in damage, along with increased emergency department visits in Houston and in cities receiving hurricane evacuees, such as the Dallas-Fort Worth metroplex (DFW).This study explored demographic indicators of vulnerability for patients from the Hurricane Harvey impact area who sought medical care in Houston and in DFW. The objectives were to characterize the vulnerability of affected populations presenting locally, as well as those presenting away from home, and to determine whether more vulnerable communities were more likely to seek medical care locally or elsewhere. METHODS: We used syndromic surveillance data alongside the Centers for Disease Control and Prevention Social Vulnerability Index to calculate the percentage of patients seeking care locally by zip code tabulation area. We used this variable to fit a spatial lag regression model, controlling for population density and flood extent. RESULTS: Communities with more patients presenting for medical care locally were significantly clustered and tended to have greater socioeconomic vulnerability, lower household composition vulnerability, and more extensive flooding. CONCLUSIONS: These findings suggest that populations remaining in place during a natural disaster event may have needs related to income, education, and employment, while evacuees may have more needs related to age, disability, and single-parent household status.
INTRODUCTION: Natural disasters are increasingly common and devastating. It is essential to understand children’s health needs during disasters as they are a particularly vulnerable population. The objective of this study was to evaluate pediatric disease burden after Hurricane Harvey compared to the preceding month and the same period in the previous year to inform pediatric disaster preparedness. METHODS: This was a retrospective cross-sectional study of patients seen at pediatric emergency departments (ED) and urgent care centers (UCC) 30 days before (late summer) and after (early fall) the hurricane and from the same time period in 2016. We collected demographic information and the first five discharge diagnoses from a network of EDs and UCCs affiliated with a quaternary care children’s hospital in Houston, Texas. We calculated the odds of disease outcomes during various timeframes using binary logistic regression modeling. RESULTS: There were 20,571 (median age: 3.5 years, 48.1% female) and 18,943 (median age: 3.5 years, 47.3% female) patients in 2016 and 2017, respectively. Inpatient admission rates from the ED a month after Harvey were 20.5%, compared to 25.3% in the same period in 2016 (P<0.001). In both years, asthma and other respiratory illnesses increased from late summer to early fall. After controlling for these seasonal trends, the following diseases were more commonly seen after the hurricane: toxicological emergencies (adjusted odds ratio [aOR]: 2.61, 95% [confidence interval] CI, 1.35-5.05); trauma (aOR: 1.42, 95% CI, 1.32-1.53); and dermatological complaints (aOR: 1.34, 95% CI, 1.23-1.46). CONCLUSION: We observed increases in rashes, trauma, and toxicological diagnoses in children after a major flood. These findings highlight the need for more medication resources and public health and education measures focused on pediatric disaster preparedness and management.
BACKGROUND: Flooding following heavy rains precipitated by hurricanes has been shown to impact the health of people. Earth observations can be used to identify inundation extents for subsequent analysis of health risks associated with flooding at a fine spatio-temporal scale. OBJECTIVE: To evaluate emergency department (ED) visits before, during, and following flooding caused by Hurricane Harvey in 2017 in Texas. METHODS: A controlled before and after design was employed using 2016-2018 ED visits from flooded and non-flooded census tracts. ED visits between landfall of the hurricane and receding of flood waters were considered within the flood period and post-flood periods extending up to 4 months were also evaluated. Modified Poisson regression models were used to estimate adjusted rate ratios for total and cause specific ED visits. RESULTS: Flooding was associated with increased ED visits for carbon monoxide poisoning, insect bite, dehydration, hypothermia, intestinal infectious diseases, and pregnancy complications. During the month following the flood period, the risk for pregnancy complications and insect bite was still elevated in the flooded tracts. SIGNIFICANCE: Earth observations coupled with ED visits increase our understanding of the short-term health risks during and following flooding, which can be used to inform preparedness measures to mitigate adverse health outcomes and identify localities with increased health risks during and following flooding events.
BACKGROUND: Hurricane Florence made landfall in North Carolina in September 2018 causing extensive flooding. Several potential point sources of hazardous substances and Superfund sites sustained water damage and contaminants may have been released into the environment. OBJECTIVE: This study conducted temporal analysis of contaminant distribution and potential human health risks from Hurricane Florence-associated flooding. METHODS: Soil samples were collected from 12 sites across four counties in North Carolina in September 2018, January and May 2019. Chemical analyses were performed for organics by gas chromatography-mass spectrometry. Metals were analyzed using inductively coupled plasma mass spectrometry. Hazard index and cancer risk were calculated using EPA Regional Screening Level Soil Screening Levels for residential soils. RESULTS: PAH and metals detected downstream from the coal ash storage pond that leaked were detected and were indicative of a pyrogenic source of contamination. PAH at these sites were of human health concern because cancer risk values exceeded 1 × 10(-6) threshold. Other contaminants measured across sampling sites, or corresponding hazard index and cancer risk, did not exhibit spatial or temporal differences or were of concern. SIGNIFICANCE: This work shows the importance of rapid exposure assessment following natural disasters. It also establishes baseline levels of contaminants for future comparisons.
IMPORTANCE: Hurricanes and flooding can interrupt health care utilization. Understanding the magnitude and duration of interruptions, as well as how they vary according to hazard exposure, race, and income, are important for identifying populations in need of greater retention in care. OBJECTIVE: To determine how the differential exposure to Hurricane Harvey in August 2017 is associated with changes in utilization of Veterans Health Administration health care. DESIGN, SETTING, AND PARTICIPANTS: This is a retrospective cohort analysis of primary care practitioner (PCP) visits, emergency department visits, and inpatient admissions in the Veterans Health Administration among Texas veterans residing in counties impacted by Hurricane Harvey from 2016 to 2018. Data analysis was performed from September 2020 to May 2021. EXPOSURES: Residential flooding after Hurricane Harvey. MAIN OUTCOMES AND MEASURES: Interrupted time series analysis measured changes in health care utilization over time, stratified by residential flood exposure, race, and income. RESULTS: Of the 99858 patients in the cohort, 89931 (90.06%) were male, and their median (range) age was 58 (21 to 102) years. Compared with veterans in nonflooded areas, veterans living in flooded areas were more likely to be Black (24?ǻ715 veterans [33.80%] vs 4237 veterans [15.85%]) and low-income (14895 veterans [20.37%] vs 4853 veterans [18.15%]). Rates of PCP visits decreased by 49.78% (95% CI, -64.52% to -35.15%) for veterans in flooded areas and by 45.89% (95% CI, -61.93% to -29.91%) for veterans in nonflooded areas and did not rebound until more than 8 weeks after the hurricane. Rates of PCP visits in flooded areas remained lower than expected for 11 weeks among White veterans (-6.99%; 95% CI, -14.36% to 0.81%) and for 13 weeks among racial minority veterans (-7.22%; 95% CI, -14.11% to 0.30%). Low-income veterans, regardless of flood status, experienced greater suppression of PCP visits in the 8 weeks following the hurricane (-13.72%; 95% CI, -20.51% to -6.68%) compared with their wealthier counterparts (-9.63%; 95% CI, -16.74% to -2.26%). CONCLUSIONS AND RELEVANCE: These findings suggest that flood disasters such as Hurricane Harvey may be associated with declines in health care utilization that differ according to flood status, race, and income strata. Patients most exposed to the disaster also had the greatest delay or nonreceipt of care.
In August 2017, after Hurricane Harvey made landfall, almost 52 inches of rain fell during a three-day period along the Gulf Coast Region of Texas, including Harris County, where Houston is located. Harris County was heavily impacted with over 177,000 homes and buildings (approximately 12 percent of all buildings in the county) experiencing flooding. The objective of this study was to measure 13 heavy metals in soil in residential areas and to assess cancer and non-cancer risk for children and adults after floodwaters receded. Between September and November 2017, we collected 174 surface soil samples in 10 communities, which were classified as “High Environmental Impact” or “Low Environmental Impact” communities, based on a composite metric of six environmental parameters. A second campaign was conducted between May 2019 and July 2019 when additional 204 soil samples were collected. Concentrations of metals at both sampling campaigns were higher in High Environmental Impact communities than in Low Environmental Impact communities and there was little change in metal levels between the two sampling periods. The Pollution Indices of lead (Pb), zinc, copper, nickel, and manganese in High Environmental Impact communities were significantly higher than those in Low Environmental Impact communities. Further, cancer risk estimates in three communities for arsenic through soil ingestion were greater than 1 in 1,000,000. Although average soil Pb was lower than the benchmark of the United States Environmental Protection Agency, the hazard indices for non-cancer outcomes in three communities, mostly attributed to Pb, were greater than 1. Health risk estimates for children living in these communities were greater than those for adults.
BACKGROUND: Social inequities affecting minority populations after Hurricane Katrina led to an expansion of environmental justice literature. In August 2017, Hurricane Harvey rainfall was estimated as a 3000- to 20,000-year flood event, further affecting minority populations with disproportionate stroke prevalence. The Stomp Out Stroke initiative leveraged multimedia engagement, creating a patient-centered cerebrovascular health intervention. OBJECTIVE: This study aims to address social inequities in cerebrovascular health through the identification of race- or ethnicity-specific health needs and the provision of in-person stroke prevention screening during two community events (May 2018 and May 2019). METHODS: Stomp Out Stroke recruitment took place through internet-based channels (websites and social networking). Exclusively through web registration, Stomp Out Stroke participants (aged >18 years) detailed sociodemographic characteristics, family history of stroke, and stroke survivorship. Participant health interests were compared by race or ethnicity using Kruskal-Wallis or chi-square test at an α=.05. A Bonferroni-corrected P value of .0083 was used for multiple comparisons. RESULTS: Stomp Out Stroke registrants (N=1401) were 70% (973/1390) female (median age 45 years) and largely self-identified as members of minority groups: 32.05% (449/1401) Hispanic, 25.62% (359/1401) African American, 13.63% (191/1401) Asian compared with 23.63% (331/1401) non-Hispanic White. Stroke survivors comprised 11.55% (155/1401) of our population. A total of 124 stroke caregivers participated. Approximately 36.81% (493/1339) of participants had a family history of stroke. African American participants were most likely to have Medicare or Medicaid insurance (84/341, 24.6%), whereas Hispanic participants were most likely to be uninsured (127/435, 29.2%). Hispanic participants were more likely than non-Hispanic White participants to obtain health screenings (282/449, 62.8% vs 175/331, 52.9%; P=.03). Asian (105/191, 54.9%) and African American (201/359, 55.9%) participants were more likely to request stroke education than non-Hispanic White (138/331, 41.6%) or Hispanic participants (193/449, 42.9%). African American participants were more likely to seek overall health education than non-Hispanic White participants (166/359, 46.2% vs 108/331, 32.6%; P=.002). Non-Hispanic White participants (48/331, 14.5%) were less likely to speak to health care providers than African American (91/359, 25.3%) or Asian participants (54/191, 28.3%). During the 2018 and 2019 events, 2774 health screenings were completed across 12 hours, averaging four health screenings per minute. These included blood pressure (1031/2774, 37.16%), stroke risk assessment (496/2774, 17.88%), bone density (426/2774, 15.35%), carotid ultrasound (380/2774, 13.69%), BMI (182/2774, 6.56%), serum lipids (157/2774, 5.65%), and hemoglobin A(1c) (102/2774, 3.67%). Twenty multimedia placements using the Stomp Out Stroke webpage, social media, #stompoutstroke, television, iQ radio, and web-based news reached approximately 849,731 people in the Houston area. CONCLUSIONS: Using a combination of internet-based recruitment, registration, and in-person assessments, Stomp Out Stroke identified race- or ethnicity-specific health care needs and provided appropriate screenings to minority populations at increased risk of urban flooding and stroke. This protocol can be replicated in Southern US Stroke Belt cities with similar flood risks.
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is the third-leading cause of death worldwide with continuous rise. Limited studies indicate that COPD was associated with major storms and related power outages (PO). However, significant gaps remain in understanding what PO’s role is on the pathway of major storms-COPD. This study aimed to examine how PO mediates the major storms-COPD associations. METHODS: In this time-series study, we extracted all hospital admissions with COPD as the principal diagnosis in New York, 2001-2013. Using distributed lag nonlinear models, the hospitalization rate during major storms and PO was compared to non-major storms and non-PO periods to determine the risk ratios (RRs) for COPD at each of 0-6 lag days respectively after controlling for time-varying confounders and concentration of fine particulate matter (PM(2.5)). We then used Granger mediation analysis for time series to assess the mediation effect of PO on the major storms-COPD associations. RESULTS: The RRs of COPD hospitalization following major storms, which mainly included flooding, thunder, hurricane, snow, ice, and wind, were 1.23 to 1.49 across lag 0-6 days. The risk was strongest at lag3 and lasted significantly for 4 days. Compared with non-outage periods, the PO period was associated with 1.23 to 1.61 higher risk of COPD admissions across lag 0-6 days. The risk lasted significantly for 2 days and was strongest at lag2. Snow, hurricane and wind were the top three contributors of PO among the major storms. PO mediated as much as 49.6 to 65.0% of the major storms-COPD associations. CONCLUSIONS: Both major storms and PO were associated with increased hospital admission of COPD. PO mediated almost half of the major storms-COPD hospitalization associations. Preparation of surrogate electric system before major storms is essential to reduce major storms-COPD hospitalization.
BACKGROUND: Making landfall in Rockport, Texas in August 2017, Hurricane Harvey resulted in unprecedented flooding, displacing tens of thousands of people, and creating environmental hazards and exposures for many more. OBJECTIVE: We describe a collaborative project to establish the Texas Flood Registry to track the health and housing impacts of major flooding events. METHODS: Those who enroll in the registry answer retrospective questions regarding the impact of storms on their health and housing status. We recruit both those who did and did not flood during storm events to enable key comparisons. We leverage partnerships with multiple local health departments, community groups, and media outlets to recruit broadly. We performed a preliminary analysis using multivariable logistic regression and a binomial Bayesian conditional autoregressive (CAR) spatial model. RESULTS: We find that those whose homes flooded, or who came into direct skin contact with flood water, are more likely to experience a series of self-reported health effects. Median household income is inversely related to adverse health effects, and spatial analysis provides important insights within the modeling approach. SIGNIFICANCE: Global climate change is likely to increase the number and intensity of rainfall events, resulting in additional health burdens. Population-level data on the health and housing impacts of major flooding events is imperative in preparing for our planet’s future.
Harmful Algal Blooms (HABs) pose unique risks to the citizens, stakeholders, visitors, environment and economy of the state of Florida. Florida has been historically subjected to reoccurring blooms of the toxic marine dinoflagellate Karenia brevis (C. C. Davis) G. Hansen & Moestrup since at least first contact with explorers in the 1500’s. However, ongoing immigration of more than 100,000 people year–1 into the state, elevated population densities in coastal areas with attendant rapid, often unregulated development, coastal eutrophication, and climate change impacts (e.g., increasing hurricane severity, increases in water temperature, ocean acidification and sea level rise) has likely increased the occurrence of other HABs, both freshwater and marine, within the state as well as the number of people impacted by these blooms. Currently, over 75 freshwater, estuarine, coastal and marine HAB species are routinely monitored by state agencies. While only blooms of K. brevis, the dinoflagellate Pyrodinium bahamense (Böhm) Steidinger, Tester, and Taylor and the diatom Pseudo-nitzschia spp. have resulted in closure of commercial shellfish beds, other HAB species, including freshwater and marine cyanobacteria, pose either imminent or unknown risks to human, environmental and economic health. HAB related human health risks can be classified into those related to consumption of contaminated shellfish and finfish, consumption of or contact with bloom or toxin contaminated water or exposure to aerosolized HAB toxins. While acute human illnesses resulting from consumption of brevetoxin-, saxitoxin-, and domoic acid-contaminated commercial shellfish have been minimized by effective monitoring and regulation, illnesses due to unregulated toxin exposures, e.g., ciguatoxins and cyanotoxins, are not well documented or understood. Aerosolized HAB toxins potentially impact the largest number of people within Florida. While short-term (days to weeks) impacts of aerosolized brevetoxin exposure are well documented (e.g., decreased respiratory function for at-risk subgroups such as asthmatics), little is known of longer term (>1 month) impacts of exposure or the risks posed by aerosolized cyanotoxin [e.g., microcystin, β-N-methylamino-L-alanine (BMAA)] exposure. Environmental risks of K. brevis blooms are the best studied of Florida HABs and include acute exposure impacts such as significant dies-offs of fish, marine mammals, seabirds and turtles, as well as negative impacts on larval and juvenile stages of many biota. When K. brevis blooms are present, brevetoxins can be found throughout the water column and are widespread in both pelagic and benthic biota. The presence of brevetoxins in living tissue of both fish and marine mammals suggests that food web transfer of these toxins is occurring, resulting in toxin transport beyond the spatial and temporal range of the bloom such that impacts of these toxins may occur in areas not regularly subjected to blooms. Climate change impacts, including temperature effects on cell metabolism, shifting ocean circulation patterns and changes in HAB species range and bloom duration, may exacerbate these dynamics. Secondary HAB related environmental impacts are also possible due to hypoxia and anoxia resulting from elevated bloom biomass and/or the decomposition of HAB related mortalities. Economic risks related to HABs in Florida are diverse and impact multiple stakeholder groups. Direct costs related to human health impacts (e.g., increased hospital visits) as well as recreational and commercial fisheries can be significant, especially with wide-spread sustained HABs. Recreational and tourism-based industries which sustain a significant portion of Florida’s economy are especially vulnerable to both direct (e.g., declines in coastal hotel occupancy rates and restaurant and recreational users) and indirect (e.g., negative publicity impacts, associated job losses) impacts from HABs. While risks related to K. brevis blooms are established, Florida also remains susceptible to future HABs due to large scale freshwater management practices, degrading water quality, potential transport of HABs between freshwater and marine systems and the state’s vulnerability to climate change impacts.
In the past ten years wildfires have burned an average of 6.8 million acres per year and this is expected to increase with climate change. Wildfire burn patient outcomes have not been previously well characterized. Wildfire burn patients from the Tubbs or Camp wildfires and non-wildfire burn matched controls were identified from the burn center database and outcomes were compared. The primary outcome was mortality. Secondary outcomes included length of stay (LOS), intensive care unit (ICU) LOS, readmission and development of wound infections. Time of presentation and operating room use after wildfires was evaluated. Sixteen wildfire burn patients were identified and matched with 32 controls. Wildfire burn patients trended towards higher mortality (19% wildfire vs. 9% non-wildfire, p=0.386), longer LOS (18 days wildfire vs. 15 days non-wildfire, p=0.406), longer ICU LOS (17 days wildfire vs. 11 days non-wildfire, p=0.991), increased readmission (19% wildfire vs. 3% non-wildfire, p=0.080) and higher rates of wound infection (31% wildfire vs. 19% non-wildfire, p=0.468). The majority of wildfire patients (88%) presented within 24 hours of the wildfire reaching a residential area. Operating room time within the first week was 13 hours 44 minutes for the Tubbs Fire and 19 hours 1 minute for the Camp Fire. Patients who sustain burns in wildfires are potentially at increased risk of mortality, prolonged LOS, wound infection and readmission.
The health benefits of green space are well known, but the health effects of green infrastructure less so. Green infrastructure goes well beyond the presence of green space and refers more to a strategically planned network of natural and seminatural areas, with other environmental features designed and managed to deliver a wide range of ecosystem services and possibly to improve human health. In this narrative review, we found that small green infrastructure, such as green roofs and walls, has the potential to mitigate urban flooding, attenuate indoor temperatures and heat islands, improve air quality, and muffle noise, among other benefits, but these effects have not been linked directly to health. Larger green infrastructure has been associated with reduced temperatures, air pollution, and crimes and violence, but less so with health, although some evidence suggests that it may be beneficial for health (e.g., good health, decreased mortality). Finally, parks and street trees show many health benefits, but it is not clear if they can always be considered green infrastructure.
Few empirical studies have examined environmental equity (EE) within the context of flooding in the United States (US). This paper explores whether lower-income, minority, and vulnerable communities in cities are disproportionately impacted by flooding, as evidenced by Federal Emergency Management Agency (FEMA) designated flood zones. Tampa and Houston, both coastal cities in the US, were investigated to understand flood risk and related equity issues using Geographical Information System (GIS) and statistical analyses. Both approaches allowed us to extract and integrate information from flood hazard maps with census block group-level sociodemographic data. Dasymetric mapping (i.e., binary mapping approach) was performed to calculate population density. Both correlations and logistic regression were used to examine the relationships between sociodemographic characteristics of population and flood risk associated with FEMA flood zones. Our research findings do not suggest any racial and ethnic disparities; however, a measurable inequity is observed in exposure to flood risk across age groups, education level, and income status. Since these vulnerable groups are often unrecognized in hazard-related policy discourses (i.e., preparedness, response, and recovery), the ramifications of these research findings may have significant impacts on EE research relating to flood hazards and related policy formulations.
OBJECTIVES: The aim of this study was to examine social network characteristics and social support (emotional and instrumental support) and to determine how those factors differed between relocating older adults and nonrelocating older adults who were affected by the 2015 flood in South Carolina. METHODS: Twenty-five community-dwelling elderly (CDE) were interviewed between December 2015 and May 2016 to learn about their experiences in the immediate aftermath of the flood. Ego-centric network data were collected with a focus on social network members and the types of flood-related support that these network members provided. RESULTS: Ten of 25 CDE relocated because of the flood. All CDE were more likely to receive social support from female network members and family members than from other acquaintances. Relocating CDE received significantly less emotional support in comparison to nonrelocating CDE. The odds of receiving instrumental support were higher, but nonsignificant, among relocating CDE in comparison to nonrelocating CDE. CONCLUSIONS: The findings around the support provision are concerning particularly because of the additional psychological burden that relocation can place on flood-affected, older adults. Recommendations for public health preparedness strategies are provided in addition to future research directions for examining the well-being of flood-affected, older adults.
We examined the inoculation and stress sensitization explanations concerning mental health outcomes in 223 predominately middle-aged and older adults after a flood (M age = 49.6 years, SD = 17.7 years, range: 18-88 years). In multiple linear regression models, having flood damage was associated with higher levels of posttraumatic stress disorder (PTSD) and depressive symptoms, while social support was associated with fewer symptoms. Greater lifetime trauma and flood-related stress were associated with more symptoms of depression and PTSD, respectively. Older age was associated with more religious coping and fewer depressive and worry symptoms. Future directions for research on postdisaster vulnerabilities and resilience are discussed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Associations of disaster mental health sequelae between children and their parents have been demonstrated, but not using full diagnostic assessment. This study examined children and their parents after a series of disasters in 1982 to investigate associations of their psychiatric outcomes. Members of 169 families exposed to floods and/or dioxin or no disaster were assessed in 1986-1987 with structured diagnostic interviews. This vintage dataset collected several decades ago provides new information to this field because of the methodological rigor that is unparalleled in this literature. Disaster-related PTSD and incident postdisaster disorders in children were associated, respectively with disaster-related PTSD and incident postdisaster disorders in the chief caregiver and mother. More flood-only than dioxin-only exposed parents reported great harm by the disaster, but neither children nor parents in these two groups differed in incident psychiatric disorders. Although this study did not determine the direction of causal influences, its findings suggest that clinicians working with disaster-exposed families should work with children and adult members together, as their mental health outcomes may be intertwined.
Climate change is intensifying coastal floods and increasing the risks of traffic disruption in lowlying, coastal communities. Efforts to understand the differential impacts of traffic disruption on communities have led to the concept of traffic resilience which captures the degree to which a traffic system can recover from disruption. Existing proxies of traffic resilience are focused on quantifying travel time delays but lack the important dimension of road safety. In this study, we quantify traffic resilience in terms of the change in non-highway car and pedestrian accident rates during the 5-10 am period as a result of coastal flooding in the San Francisco Bay Area for the 2020-2040 period. We use a regional traffic model to simulate traffic patterns under a range of coastal flood water levels. We use regressions that relate traffic volumes to historical accident rates to estimate accidents rates in the presence of flooding. Our results show that the flooding of highways forces commuters onto local roads passing through residential communities, causing a spike in accident rates. Unlike delays which increase sharply at the higher water levels considered in this study, we project that region-wide peak-hour accident rates may increase substantially at lower water levels.
There is a consensus that future sea-level rise (SLR) will increase the exposure of population and assets to coastal flooding. However, the extent to which SLR affects flood hazards and human vulnerability to flooding in the built environment is not well understood. This study investigates the effects of future SLR on coastal flood hazards and human vulnerability to flooding in New York City’s built environment. With a focus on a hurricane-induced flood event, we utilize a building-scale hydrodynamic model to simulate flood hazards under different 21st-century SLR scenarios. We further implement a human vulnerability model to reveal how the physical vulnerability of individuals to flooding would respond to the effects of SLR on flood hazards. We find that SLR would result in a substantial increase in not only the floodwater depth but also the floodwater velocity in the study area. For example, under a 1.04 m SLR scenario, the increase in the max floodwater speed exceeds 2.7 m/s (1271%) in 5% of the area that was flooded under the no-SLR scenario (control run). Model results show that, due to nonlinear interactions, the floodwater depth simulated by the hydrodynamic model for a SLR scenario could substantially differ from the depth estimated based on a linear addition of the SLR to the control-run floodwater depth. We find that the effects of SLR on flood hazards would, in turn, substantially affect the extent, intensity, and duration of human physical vulnerability to flooding, which could potentially increase the number of injuries and mortalities.
With increasing population growth and urban sprawl, many coastal lowlands are unprecedentedly vulnerable to climate change and its impacts, such as rising sea levels, increasing extreme storm events, and coastal flooding. Quantifying coastal flood vulnerability serves as a tool to identify a system’s weakness, monitor its change, and support making targeted climate adaptation policies. The assessment framework proposed in this research uses principal component analysis (PCA) and a weighting method to build a composite indicator of flood vulnerability index and evaluate the vulnerability for 256 coastal census tracts and 24 municipalities along the coast of Connecticut, USA. The research uses Keiser-Meyer-Olkin (KMO) test and Bartlett’s test of sphericity to test sample adequacy and performs data standardization for all indicators. Through PCA, 30 coastal vulnerability-related indicators were grouped into four major dimensions: hazard exposure, socio-economic, physical/land use and land cover, and natural. The findings highlight the variations of flood vulnerability across highly ur-banized areas, suburban areas, and rural areas; and the gradient from coastal low-elevation region to high-elevation inland area. This variance is unevenly caused by different dimensions although they may trade-off with each other when aggregated, the dominant dimensions play a significant or decisive role in the vulnera-bility assessment. This research built an automatic and objective assessment framework that is flexible enough to be applied at a smaller scale so as to obtain detailed analysis and it can be used as a decision-making support system.
This paper examines communities’ accessibility to critical facilities such as hospitals, emergency medical services, and emergency shelters when facing flooding. We use travel speed reduction to account for flood-induced partial road failure. A modified betweenness centrality metric is also introduced to calculate the criticality of roads for connecting communities to critical facilities. The proposed model and metric are applied to the Delaware road network under 100-year floods. This model highlights the severe critical facility access loss risk due to flood isolation of facilities. The mapped post-flooding accessibility suggests a significant travel time increase to critical facilities and reveals disparities among communities, especially for vulnerable groups such as long-term care facility residents. We also identified critical roads that are vital for post-flooding access to critical facilities. The results of this research can help inform targeted infrastructure investment decisions and hazard mitigation strategies that contribute to equitable community resilience enhancement.
Understanding availability and accessibility of critical infrastructure systems during the pre-disaster phase and evaluating the impact of their possible disruption during the disaster phase are crucial for measuring the vulnerability and resiliency of communities. This study proposes a new quantitative framework for flood risk assessment that helps understand the existing disaster risk and proactively mitigate the impact of infrastructure disruption on communities by systematically analyzing: (1) reliability of a transportation network and (2) vulnerability of residents and critical facilities. The methodology addresses the following infrastructure systems categorized as: (1) distribution-based and (2) facility-based systems. This study has modeled the dependency of the facility-based category on the transportation network and developed a general framework that measures the deficiency in pre-disaster phase and possible disruptions during the disaster response phase. For a cast study, this framework was applied to evaluate the vulnerability and resiliency of emergency facilities in the East Baton Rouge. It was concluded that a detailed analysis of both preexisting conditions and during disaster conditions along with social vulnerability provide a more realistic insight and more accurate benchmark of vulnerability and resiliency of communities pertaining to infrastructure systems. This framework is expected to improve hazard mitigation and decision-making processes in investments and prioritization of infrastructure improvement projects.
BACKGROUND: Satellite observations following flooding coupled with electronic health data collected through syndromic surveillance systems (SyS) may be useful in efficiently characterizing and responding to health risks associated with flooding. RESULTS: There was a 10% (95% Confidence Interval (CI): 1%-19%) increase in asthma related ED visits and 22% (95% CI: 5%-41%) increase in insect bite related ED visits in the flooded ZCTAs compared to non-flooded ZCTAs during the flood period. One month following the floods, diarrhea related ED visits were increased by 15% (95% CI: 4%-27%) for flooded ZCTAs and children and adolescents from flooded ZCTAs had elevated risk for dehydration related ED visits. During the protracted period (2-3 months after the flood period), the risk for asthma, insect bite, and diarrhea related ED visits were elevated among the flooded ZCTAs. Effect modification by reported age, ethnicity and race was observed. CONCLUSION: Combining satellite observations with SyS data can be helpful in characterizing the location and timing of environmentally mediated adverse health outcomes, which may be useful for refining disaster resilience measures to mitigate health outcomes following flooding.
The Centers for Disease Control and Prevention (CDC)/Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index (SVI) is a census-based metric that includes 15 socioeconomic and demographic factors split into four themes relevant to disaster planning, response, and recovery. Using CDC/ATSDR SVI, health outcomes, and remote sensing data, we sought to understand the differences in the occurrence of overall and cause-specific emergency department (ED) visits before and after a 2017 flood event in Texas following Hurricane Harvey, modified by different levels of social vulnerability. We used a controlled before-after study design to estimate the association between flooding and overall and cause-specific ED visits after adjusting for the baseline period, seasonal trends, and individual-level characteristics. We estimated rate ratios stratified by CDC/ATSDR SVI quartiles (overall and 4 themes separately) and tested for the presence of effect modification. Positive effect modification was found such that total ED visits from flooded census tracts with moderate, high, and very high levels of social vulnerability were less reduced compared to tracts with the least vulnerability during flooding and the month following the flood event. The CDC/ATSDR SVI socioeconomic status theme, household composition and disability theme, and housing and transportation type theme explained this result. We found predominantly negative effect modification with higher ED visits among tracts with the least vulnerability for ED visits related to insect bites, dehydration, and intestinal infectious diseases.
This paper presents a research study that is a valuable first project in setting the stage for bringing a foresight perspective to the impacts of severe flooding on health, poverty, and equity in Houston, out to the year 2050. Drawing on qualitative and quantitative research gathered from methodologies such as the Delphi and Cross-Impact Analysis combined with insights gained from interviews with subject-matter experts, it explores four alternative, plausible scenarios for Houston’s long-term future. Exploring scenarios that feature the continuation of present-day trends, a system collapse, a system balanced by a new equilibrium, and a system transformation provides an opportunity for stakeholders and policymakers to work together to create a more inclusive future for all city residents.
Impact Statement In October of 2017, Sonoma County, California, experienced devastating and historic wildfires and subsequent community trauma. This manuscript details the development, dissemination, and evaluation of a public mobile mental health app for wildfire survivors. Lessons learned are offered to contribute to the science and practice of using digital tools to conduct disaster mental health outreach and research. In October 2017, Northern California experienced devastating and historic wildfires leaving the community in need of support to foster emotional resilience during the recovery process. Adolescents represent a particularly vulnerable population in the wake of disaster, and digital mental health interventions may hold promise for reaching teens at scale. The present study examined the feasibility and efficacy of a mobile mental health app for disaster, Sonoma Rises. A multiple-baseline single-case experimental design (SCED) utilizing a research-enabled version of the app was employed with seven adolescents who experienced significant damage to their homes and schools in the wildfires. Participants completed daily mood ratings, weekly measures of posttraumatic stress symptoms, internalizing and externalizing symptoms, psychosocial functioning, and then pre-post-measures of anxiety, depression, wellbeing, sleep, academic engagement, and perceived social support as well as quantitative and qualitative measures of intervention satisfaction and feasibility. Sonoma Rises was found to be feasible in terms of engagement, satisfaction, and likelihood of recommending to a friend. During the study, another wildfire occurred and all participants underwent a prolonged mandated evacuation and were subject to a series of extended power outages. Uptake of the publicly available version of the Sonoma Rises app among the general population was modest but engagement among users was sustained. Lessons learned are offered to contribute to the science and practice of building, disseminating, and implementing digital tools to conduct more equitable disaster mental health outreach and research.
Purpose This paper describes the educational experiences of children and youth (aged 3-20) with disabilities during school closures resulting from the 2017 Northern California wildfires. Students with disabilities are particularly vulnerable to the adverse impacts of disaster, yet the effects of school closures on these children remains understudied. This study identifies considerations for students with disabilities and their families post-disaster. Design/methodology/approach An inductive, qualitative approach was used for the study design, methodology and analysis. In-depth interviews were conducted with parents of 14 students with disabilities about their experiences during and following school closures. All of these children had missed between a week and over a month of school as a result of the wildfires. Thematic analysis was used to code data and identify four themes present across the data. Findings Our findings indicate that children and youth with disabilities experienced disruptions in school-based services; lost previously acquired skills; exhibited negative health and behavioral issues; had difficulties adapting to new, unfamiliar routines and were saddened by lost social connections. Additionally, findings pinpoint the importance of social connections while schools were closed, the benefits of resuming school which included access to responsive school staff, as well as challenges faced by children with disabilities and their families once schools reopened. Originality/value Families of children with disabilities, as illustrated in this study, often must transverse a different post-disaster landscape. Schools should assist them in navigating that landscape so students with disabilities can experience a more equitable return to education post-disaster.
In October of 2017 and 2019, Sonoma County California endured historic wildfires and subsequent community trauma. The Sonoma Wildfire Mental Health Collaborative was created to (a) democratize access to evidence-based mental health resources and services for personal recovery and long-term community resilience building, and to (b) measure the reach and efficacy of the strategies employed in order to create a knowledge base to inform disaster response in other communities. Offerings included a mind-body yoga program and training in Skills for Psychological Recovery (SPR) for counselors who wished to provide services to individuals impacted by the wildfires. An evaluation of the mental health strategies employed revealed that (a) the mind-body program was well-received, with a high degree of satisfaction and self-reported benefit among individuals who attended trauma-informed yoga classes and (b) counselors found SPR to be a practical, flexible short-term intervention for individuals in the aftermath of the wildfires and expressed moderate to high levels of intent to use it in practice. Importantly, the evaluation of the 2017 wildfire mental health response was compromised by the Kincade Fire in 2019, in which prolonged mandatory evacuations and power outages impacted response rates. The origin story is shared for how a community collaborative was built. Lessons learned are discussed and recommendations summarized so as to contribute to the science and practice of disaster mental health outreach. Impact Statement In October of 2017 and 2019, Sonoma County, California experienced devastating and historic wildfires and subsequent community trauma. This manuscript describes the origin story of the Wildfire Mental Health Collaborative and preliminary findings from two mental health interventions employed with wildfire survivors (trauma-informed yoga, Skills for Psychological Recovery). Lessons learned and recommendations are offered to guide future work in the science and practice of disaster mental health.
Background Wildfires in California have become more deadly and destructive in recent years, and four of the ten most destructive fires occurred in 2017 and 2018. Through interviews with service providers, this article explores how these recent wildfires have impacted surrounding communities and the role various recovery resources have played in responding to the short- and long-term health and social needs of survivors. Methods Using a purposive sampling methodology, we interviewed 21 health and social service personnel who assisted in wildfire recovery efforts in California in 2017 and 2018. The study participants worked or volunteered in medical facilities, social services agencies and philanthropy/nonprofit organizations located in communities affected by wildfires. Participants were asked about three common, overarching themes that fire-impacted communities navigate post-disaster: health issues, social issues, and response and recovery resources. Inductive coding was used to identify common subthemes. Results The two most frequently discussed social issues during interviews were housing and employment access. Mental and emotional well-being and access to health resources were identified as being the most challenging health concerns that survivors face post-disaster. Participants also identified the following private and public recovery resources that survivors use to attempt to restabilize following the fire: community support, county agencies, the Federal Emergency Management Agency (FEMA,) insurance companies and philanthropic organizations. However, participants noted that the cumulative impacts of these efforts still leave many of their patients and clients without the resources needed to restabilize emotionally, financially and physically. Finally, participants spoke about the community-wide, downstream impacts of wildfires, noting that “survivors” are not only those whose health is immediately compromised by the disaster. Conclusion Given the worsening wildfire seasons in California, we must increase our understanding of both the scope of the health and social issues that survivors navigate following a disaster, as well as the effectiveness and sustainability of recovery resources available to survivors. We must also understand the “ripple effect” that wildfires have on surrounding communalities, impacting housing access, social services, and health care access. More research and support, especially during the current COVID-19 pandemic, is urgently needed to improve our ability to support the health and social needs of wildfire survivors in the future.
Objectives: This case study examined multi-level social-ecological supports in promoting well-being through college students impacted by one of the deadliest wildfires in U.S. history.Participants: College students attending a large public university were surveyed (N = 354, M(age =) 22.7, 76.2% female, 61% white).Methods: Measures included demographics, individual factors (mindfulness, sleep problems), social support (emotional support, family support, and friendship), and sense of community. Multiple linear regression models on well-being were constructed.Results: Findings indicated that mindfulness, sleep disturbances, emotional support, family support, number of close friends, and sense of community were significant predictors of well-being.Conclusion: Findings highlight the importance of universities in proactively bolstering critical social-ecological needs of college students living in communities vulnerable to climate-change accelerated environmental disasters.
Little research has examined the mental health risks of concurrent disasters. For example, disasters like wildfires have been shown to have a strong association with psychological symptoms-the 2020 U.S. Western wildfire season was the worst on record and occurred while the country was still navigating the COVID-19 pandemic. We implemented two quasi-experimental analyses, an interrupted time series analysis, and a difference-in-difference analysis to evaluate the impacts of wildfires and COVID-19 on mental health crisis help-seeking patterns. Both methods showed no statistical association between exposure to wildfires and the seeking of mental health support during the COVID-19 pandemic. Results highlighted that 2020 wildfires were not associated with an acute increase in crisis texts for youth in the two months after the events, likely due to an already elevated text volume in response to the COVID-19 pandemic from March 2020 throughout the fall wildfire season (Aug to Oct 2020). Future research is needed outside of the context of the pandemic to understand the effects of extreme and concurrent climatic events on adolescent mental health, and targeted interventions are required to ensure youth and adolescents are receiving adequate support during these types of crisis events.
The psychological effects of disasters on children with disabilities are understudied, despite evidence towards increased risk for complications after other types of trauma exposure. This study investigated the experience of children and youth with disabilities exposed to the 2017 Northern California wildfires, with a particular focus on psychological reactions. In-depth interviews were conducted with parents of 14 children and youth with disabilities one year post-disaster. Thematic analysis was used to analyze the interviews. Parents described the wildfires as traumatic events for both themselves and their children. Children and youth exhibited stress, grief, and other emotional and behavioral reactions during evacuation, in the immediate aftermath, and one year post-disaster. Navigating disability-related needs, such as accessible housing, contributed to parent stress post-disaster. School and community-based mental health efforts are described, along with a call for increased attention to disaster-related reactions in children with developmental disabilities. Suggestions for improving preparedness and response efforts that better support children with disabilities and their families post-disaster are given.
Young adulthood is a critical developmental life stage and a period of enhanced vulnerability to stress. In 2020, young adults in Northern California were faced with a series of unforeseen, collective stressors: the COVID-19 pandemic, extreme wildfires, social tension associated with the murder of George Floyd, and a contentious election that culminated in an attack on the nation’s capital. In a natural experiment, we compared the psychosocial development of 415 young adults across 8 monthly assessment waves during 2020 to a control cohort (n = 465) who completed the same assessment protocol in 2019, prior to the onset of stressors. Results of latent growth curve models indicated that the 2020 cohort had less adaptive trajectories of affective well-being and lower levels and less adaptive trajectories of social functioning, suggesting detrimental effects of cumulative, collective stressors on the socio-emotional development of young adults.
Wildfires are an essential part of a healthy ecosystem, yet the expansion of the wildland-urban interface, combined with climatic changes and other anthropogenic activities, have led to the rise of wildfire hazards in the past few decades. Managing future wildfires and their multi-dimensional impacts requires moving from traditional reactive response to deploying proactive policies, strategies, and interventional programs to reduce wildfire risk to wildland-urban interface communities. Existing risk assessment frameworks lack a unified analytical method that properly captures uncertainties and the impact of decisions across social, ecological, and technical systems, hindering effective decision-making related to risk reduction investments. In this paper, a conceptual probabilistic wildfire risk assessment framework that propagates modeling uncertainties is presented. The framework characterizes the dynamic risk through spatial probability density functions of loss, where loss can include different decision variables, such as physical, social, economic, environmental, and health impacts, depending on the stakeholder needs and jurisdiction. The proposed approach consists of a computational framework to propagate and integrate uncertainties in the fire scenarios, propagation of fire in the wildland and urban areas, damage, and loss analyses. Elements of this framework that require further research are identified, and the complexity in characterizing wildfire losses and the need for an analytical-deliberative process to include the perspectives of the spectrum of stakeholders are discussed.
There is limited population-scale evidence on the burden of exposure to wildfire smoke during pregnancy and its impacts on birth outcomes. In order to investigate this relationship, data on every singleton birth in California 2006-2012 were combined with satellite-based estimates of wildfire smoke plume boundaries and high-resolution gridded estimates of surface PM2.5 concentrations and a regression model was used to estimate associations with preterm birth risk. Results suggest that each additional day of exposure to any wildfire smoke during pregnancy was associated with an 0.49 % (95 % CI: 0.41-0.59 %) increase in risk of preterm birth ( 37 weeks). At sample median smoke exposure (7 days) this translated to a 3.4 % increase in risk, relative to an unexposed mother. Estimates by trimester suggest stronger associations with exposure later in pregnancy and estimates by smoke intensity indicate that observed associations were driven by higher intensity smoke-days. Exposure to low intensity smoke-days had no association with preterm birth while an additional medium (smoke PM2.5 5-10 mu g/m(3)) or high (smoke PM2.5 10 mu g/m(3)) intensity smoke-day was associated with an 0.95 % (95 % CI: 0.47-1.42 %) and 0.82 % (95 % CI: 0.41-1.24 %) increase in preterm risk, respectively. In contrast to previous findings for other pollution types, neither exposure to smoke nor the relative impact of smoke on preterm birth differed by race/ethnicity or income in our sample. However, impacts differed greatly by baseline smoke exposure, with mothers in regions with infrequent smoke exposure experiencing substantially larger impacts from an additional smoke-day than mothers in regions where smoke is more common. We estimate 6,974 (95 % CI: 5,513-8,437) excess preterm births attributable to wildfire smoke exposure 2007-2012, accounting for 3.7 % of observed preterm births during this period. Our findings have important implications for understanding the costs of growing wildfire smoke exposure, and for understanding the benefits of smoke mitigation measures.
In recent years, wildfires have ravaged the landscape in many Western American states, especially California. But will these horrific wildfire experiences increase public support for wildfire adaptation measures? We conducted an individual-level survey in California in 2019. Combining survey data with geocoded information about a respondent’s proximity to wildfire events and exposure to wildfire smoke, we assess whether respondents’ experiences increased support for several wildfire adaptation policies. We also control for party affiliation. We find that Californians generally oppose restrictive resilience policies and view the decision to take adaptive steps as a matter of personal choice. Republicans are generally more opposed than Democrats to spending public funds to incentivize resilience measures, but proximity to wildfires lessens their opposition to using public funds to encourage homeowners to upgrade their properties for increased protection from wildfires and encourage relocation to safer places. Although exposure to wildfire smoke is extensive and harmful to health, we found that its main impact on policy preferences was statistically insignificant.
OBJECTIVE: Determine serum lipid and general health/fitness alterations following a 5-month wildfire suppression season. METHODS: We recruited 100 wildland firefighters (WLFFs) to a 5-month pre- to post-season observational study. Nude body mass, blood pressure (BP), grip strength, and steptest heart rate (HR) were recorded. Blood samples were collected for lipid panel analysis (total cholesterol, high density lipoproteins (HDL)-cholesterol, low density lipoproteins-cholesterol, very low density lipoproteinscholesterol, triglycerides, triglyceride:HDL-cholesterol ratio). Two-tailed dependent t tests determined statistical significance (P < 0.05). RESULTS: There were pre- to post-season changes in nude body mass (+2 ± 4%, P = 0.001), systolic BP (-2 ± 10%, P = 0.01), step-test HR (-5 ± 10%, P < 0.001), and all serum lipids (total cholesterol: +5 ± 14%, P = 0.02, HDL-cholesterol: = 1 ± 17%, P = 0.04, low density lipoproteins-cholesterol: +8 ± 22%, P = 0.02, very low density lipoproteins-cholesterol: +31 ± 49%, P < 0.001, triglycerides: +30 ± 49%, P < 0.001, triglyceride:HDL-cholesterol ratio: +37 ± 58%, P < 0.001). Pre- to post-season diastolic BP (P = 0.12) and grip strength (P = 0.60) remained stable. CONCLUSIONS: WLFFs demonstrate maladaptive serum lipids and body mass alterations despite subtle aerobic fitness improvements.
Historically, firefighting has been a hazardous profession and in response, many departments and national organizations have adopted rehabilitation protocols to minimize excess risk. Fire rehab is a coordinated plan to ensure firefighters, who encounter extremes of temperature, exposure, and exertion, do not develop significant illnesses related to exertion or exposure. Fire rehab can vary from simple temperature management and oral rehydration to aggressive medical treatments and transport to a higher level of care. Fire rehab is continually evolving as our understanding of physiologic responses to exertion and exposure change, technologies evolve, and risk tolerance adjusts. Fire rehab services have a varying structure, depending on the service and the region. Small, rural fire services may have few responders with medical training and coordinate with local EMS agencies to assist or oversee rehab. Some fire services have a sufficient number of trained EMS providers and coordinate their own rehab, including transport to health care facilities. Large services may have highly scalable rehab plans that include multiple rehabilitation units operating under a coordinating officer. Over the years, a group of central resources has been created that provides education and guidance on fire rehab. In 1987, the National Fire Protection Association (NFPA) released its Standard on Fire Department Occupational Safety and Health Program, which comprehensively addressed common dangers and protective measures for firefighters. In 1992, the U.S. Fire Administration (USFA) published the short report FA-114, Emergency Incident Rehabilitation, which included a sample standard operating procedure (SOP) for fire rehab. A textbook bearing the same title was released in 1997, providing further details of the science and reasoning for the fire rehab protocols. USFA published an updated SOP, and much more comprehensive, report on Emergency Incident Rehabilitation in 2008. NFPA 1584, Recommended Practice on the Rehabilitation of Members Operating at Incident Scene Operations and Training Exercises was issued in 2003, establishing guidelines for fire services. These recommendations were upgraded to standards in a 2008 update and again updated in 2015, with carbon monoxide monitoring added to recommended practices. It is important to delineate that fire rehabilitation, when discussed in the context of wildfires, relates to the ecological recovery of an affected area, not the physiological recovery of humans working to contain fires. The subject of the ecological recovery after a wildfire is addressed in other literature and will not be covered in this article.
Over the past four decades, the average area annually burned in wildfires in the United States has roughly quadrupled. Larger, more powerful wildfires increasingly threaten inhabited areas as well as vital infrastructure, including many installations of the United States Armed Forces. This article first introduces readers to what wildfire is and the unique challenges it creates to the environment, health and, specifically, to the Department of Defense (DOD). Next, it discusses the dominant approaches to addressing the wildfire threat, prescribed fire, and mechanical treatment. It then summarizes the primary laws, policies and partners involved in wildfire policy in the United States as applied to the DOD. Finally, it proposes a statutory solution, the Building Up Resilience Now for Defense (BURND) Act, that would improve the wildfire resilience of the DOD and communities hosting DOD installations in important ways, thus enhancing our national defense.
Wildfires are now a common feature of the western US, increasing in both intensity and number of acres burned over the last three decades. The effects of this changing wildfire and smoke landscape are a critical public and occupational health issue. While respiratory morbidity due to smoke exposure is a priority, evaluating the molecular underpinnings that explain recent extrapulmonary observations is necessary. Here, we use an Apoe(-/-) mouse model to investigate the epigenetic impact of paternal exposure to simulated wildfire smoke. We demonstrate that 40 days of exposure to smoke from Douglas fir needles induces sperm DNA methylation changes in adult mice. DNA methylation was measured by reduced representation bisulfite sequencing and varied significantly in 3353 differentially methylated regions, which were subsequently annotated to 2117 genes. The differentially methylated regions were broadly distributed across the mouse genome, but the vast majority (nearly 80%) were hypermethylated. Pathway analyses, using gene-derived and differentially methylated region-derived gene ontology terms, point to a number of developmental processes that may warrant future investigation. Overall, this study of simulated wildfire smoke exposure suggests paternal reproductive risks are possible with prolonged exposure.
Alabama currently experiences an above-average threat from extreme heat events compared to the remaining states in the USA. More than 160,000 people living in the state (infants, elderly age groups, or poverty-ridden populations) remain vulnerable to heat events. The risk of heat-related mortalities and morbidities disproportionately impacts the growing Alabama cities due to increasing hot-weather episodes and several underlying social vulnerability factors. The exposure threat in 2050 is projected to increase by more than 90 average heat days a year and the number of heat-wave days is predicted to increase from 15 to more than 70 days a year. Although the state’s hazard mitigation plan covers extreme heat issues and heat emergency plans, Alabama lacks heat adaptation plans and is conducting heat vulnerability assessments from time to time. This study focused on determining the social drivers of heat vulnerability and identifying regions within the state that experienced intense heat island effects over the course of five years (2015-2019). 15 sociodemographic factors data from the 2018 American Community Survey (ACS), and 6 health outcome variables (asthma, obesity, stroke, high blood pressure, diabetes) were analyzed to assess cumulative social vulnerability using principal component analysis (PCA). Using Spatial Autoregression (SAR) model, exposure risk was measured as a function of environmental parameters including proportional vegetation, normalized difference water index (NDWI), digital elevation model (DEM), and percent imperviousness of land surface. A heat risk index calculated as a product of social vulnerability and exposure risk was analyzed for Alabama’s eight largest and growing cities (Birmingham, Huntsville, Hoover, Montgomery, Mobile, Tuscaloosa, Auburn, and Dothan) at the block-group census resolution. Spatial data depicting the physical landscape characteristics across the cities revealed differing levels of and factors in exposure to urban heat effects across the city.
BACKGROUND: In the United States (US), urinary tract infections (UTI) lead to more than 10 million office visits each year. Temperature and season are potentially important risk factors for UTI, particularly in the context of climate change. METHODS: We examined the relationship between ambient temperature and outpatient UTI diagnoses among patients followed from 2015 to 2017 in two California healthcare systems: Kaiser Permanente Southern California (KPSC) and Sutter Health in Northern California. We identified UTI diagnoses in adult patients using diagnostic codes and laboratory records from electronic health records. We abstracted patient age, sex, season of diagnosis, and linked community-level Index of Concentration at the Extremes (ICE-I, a measure of wealth and poverty concentration) based on residential address. Daily county-level average ambient temperature was assembled from the Parameter-elevation Regressions on Independent Slopes Model (PRISM). We implemented distributed lag nonlinear models (DLNM) to assess the association between UTI and lagged daily temperatures. Main analyses were confined to women. In secondary analyses, we stratified by season, healthcare system, and community-level ICE-I. RESULTS: We observed 787,186 UTI cases (89% among women). We observed a threshold association between ambient temperature and UTI among women: an increase in daily temperature from the 5th percentile (6.0 ˚C) to the mean (16.2 ˚C) was associated with a 3.2% (95% CI: 2.4, 3.9%) increase in same-day UTI diagnosis rate, whereas an increase from the mean to 95th percentile was associated with no change in UTI risk (0.0%, 95% CI: -0.7, 0.6%). In secondary analyses, we observed the clearest monotonic increase in the rate of UTI diagnosis with higher temperatures in the fall. Associations did not differ meaningfully by healthcare system or community-level ICE-I. Results were robust to alternate model specifications. DISCUSSION: Increasing temperature was related to higher rate of outpatient UTI, particularly in the shoulder seasons (spring, autumn).
Exertional heat illness (EHI) presents significant risks for National Guard (NG) disaster response teams, especially when they are performing operations in impermeable personal protective equipment (PPE). Impermeable PPE does not allow passage of air or fluids either from the outside or inside of the equipment. While EHI prevention and management strategies are well documented, these strategies do not account for the additional heat-related risks NG teams confront when responding to disasters requiring PPE that protects against any hazards. NG personnel who wear the full gamut of impermeable PPE (including Trek coveralls and respirators) experience core body temperature increase as a result of builtup body heat or accumulated perspiration. We conducted a qualitative descriptive study using thematic analysis with three focus groups to identify EHI-related factors during disaster response operations that require PPE. We organized focus group data into phases of disaster response operation: pre-event, event, and post-event to reflect four conceptual groups: human (host), agent (energy transfer), environmental, and workplace/social conditions. Participants identified 12 themes covering the 3 phases and situated in the 4 conceptual groups. Results of this study serve as an evidence-based foundation for enhancing pre-event, event, and post-event assessments administered by NG medical personnel and can be applied to other professionals who are required to wear PPE.
Background: There remains a dearth of cross-city comparisons on the impact of climate change through extreme temperature and precipitation events on road safety. We examined trends in traffic fatalities, injuries and property damage associated with high temperatures and heavy rains in Boston (USA) and Santo Domingo (Dominican Republic). Methods: Official publicly available data on daily traffic outcomes and weather conditions during the warm season (May to September) were used for Boston (2002-2015) and Santo Domingo (2013-2017). Daily maximum temperatures and mean precipitations for each city were considered for classifying hot days, warm days, and warm nights, and wet, very wet, and extremely wet days. Time-series analyses were used to assess the relationship between temperature and precipitation and daily traffic outcomes, using a quasi-Poisson regression. Results: In Santo Domingo, the presence of a warm night increased traffic fatalities with a rate ratio (RR) of 1.31 (95% CI [confidence interval]: 1.00,1.71). In Boston, precipitation factors (particularly, extremely wet days) were associated with increments in traffic injuries (RR 1.25, 95% CI: 1.18, 1.32) and property damages (RR 1.42, 95% CI: 1.33, 1.51). Conclusion: During the warm season, mixed associations between weather conditions and traffic outcomes were found across Santo Domingo and Boston. In Boston, increases in heavy precipitation events were associated with higher traffic injuries and property damage. As climate change-related heavy precipitation events are projected to increase in the USA, the associations found in this study should be of interest for road safety planning in a rapidly changing environment.
BACKGROUND: Studies have shown that prenatal heat exposure may impact fetal growth, but few studies have examined the critical windows of susceptibility. As extreme heat events and within season temperature variability is expected to increase in frequency, it is important to understand how this may impact gestational growth. OBJECTIVES: We investigated associations between various measures of weekly prenatal heat exposure (mean and standard deviation (SD) of temperature and heat index (HI), derived using temperature in °C and dew point) and term birthweight or odds of being born small for gestational age (SGA) to identify critical windows of susceptibility. METHODS: We analyzed data from mother-child dyads (n = 4442) in the Boston-based Children’s HealthWatch cohort. Birthweights were collected from survey data and electronic health records. Daily temperature and HI values were obtained from 800 m gridded spatial climate datasets aggregated by the PRISM Climate Group. Distributed lag-nonlinear models were used to assess the effect of the four weekly heat metrics on measures of gestational growth (birthweight, SGA, and birthweight z-scores). Analyses were stratified by child sex and maternal homelessness status during pregnancy. RESULTS: HI variability was significantly associated with decreased term birthweight during gestational weeks 10-29 and with SGA for weeks 9-26. Cumulative effects for these time periods were -287.4 g (95% CI: -474.1 g, -100.8 g for birthweight and 4.7 (95% CI: 1.6, 14.1) for SGA. Temperature variability was also significantly associated with decreased birthweight between weeks 15 and 26. The effects for mean heat measures on term birthweight and SGA were not significant for any gestational week. Stratification by sex revealed a significant effect on term birthweight in females between weeks 23-28 and in males between weeks 9-26. Strongest effects of HI variability on term birthweight were found in children of mothers who experienced homelessness during pregnancy. Weekly HI variability was the heat metric most strongly associated with measures of gestational growth. The effects observed were largest in males and those who experienced homelessness during pregnancy. DISCUSSION: Given the impact of heat variability on birthweight and risk of SGA, it is important for future heat warnings to incorporate measure of heat index and temperature variability.
Trend assessments suggest that poverty and health will worsen in the United States in the coming decades and that climate change will exacerbate these trends. An aging society, lack of affordable housing, and automation threaten the economic sustainability of millions of households. Despair, drug abuse, and unhealthy lifestyles have led to the first decline in life spans in the U.S. during a non-war period. Extreme weather events caused by climate change can be anticipated to disrupt economic activities and destroy homes and infrastructure, pushing millions of more Americans into poverty. A warming climate threatens vulnerable individuals, such as elders, with heat stress, increasing levels of air pollution, and increasing risks from new tropical diseases entering the country. It is anticipated that climate change will force tens of millions of Americans from their homes, creating The Great Migration (TGM) scenario. The welfare of the migrants will depend on what types of human settlements they migrate to. Seven different types of settlements are depicted within the TGM scenario, such as Willow Pond settlements that represent radical redesigns of suburbs to make them sustainable and resilient to climate change. Numerous recommendations are provided to foster positive outcomes with respect to TGM, including having the U. S. formally designate that the right to safe and adequate housing is a human right.
The troubling trend of rising heat-associated mortalities in an urban desert region (Maricopa County, AZ, USA) has motivated us to explore the extent to which environmental factors may contribute to increased heat-health risks. Summertime data from 2010 to 2019 were used to construct a suite of models for daily heat-associated mortalities. The best-performing full model included the following predictors, ordered from strongest to weakest influence: daily average air temperature, average of previous 5 days daily average air temperature, year, day of year, average of previous 5 days daily average dew point temperature, average of previous 5 days daily average PM(2.5), and daily average PM(10). This full model exhibited a 5.39% reduction in mean absolute error in daily heat-associated mortalities as compared to the best-performing model that included only air temperature as an environmental predictor. The extent to which issued and modeled excessive heat warnings (from both the temperature only and full models) corresponded with heat-associated mortalities was also examined. Model hindcasts for 2020 and 2021 showed that the models were able to capture the high number of heat-associated mortalities in 2020, but greatly undercounted the highest yet observed number of heat-associated mortalities in 2021. Results from this study lend insights into environmental factors corresponding to an increased number of heat-associated mortalities and can be used for informing strategies towards reducing heat-health risks. However, as the best-performing model was unable to fully capture the observed number of heat-associated mortalities, continued scrutiny of both environmental and non-environmental factors affecting these observations is needed.
Concerns over regional climate change include its impact on air quality. A major contributor to unhealthy air quality is surface-based temperature inversions. Poor air quality is a serious public health concern that is often addressed by public health agencies. To assist with understanding the climatology and trend of temperature inversions for a large public health department, innovative pragmatic criteria were developed and used to determine morning and evening surface-based temperature inversions from datasets derived from Pittsburgh National Weather Service (NWS) radiosonde measurements made from 1 January 1991 through 31 December 2020. During this 30-year period, the strength of the morning (7 a.m. EST; 12 UTC) inversions was 3.9 °C on average. The depth of the inversion layer measured an average height of 246 m above the ground. The inversions tended to dissipate by 10 a.m. EST. The frequency of occurrence of morning inversions averaged 47%. The mean strength of the evening (7 p.m. EST; 00 UTC) inversions was 1.1 °C with a mean depth of 101 m above the ground. The frequency of evening inversion occurrence averaged 20% during this period. The 30-year climatology revealed generally declining frequency of inversions in the Pittsburgh area. Morning surface-based inversion strengths usually declined while morning depths and break times were steady. Evening inversion strengths and depths increased overall during the 30-year period. Monthly means showed a morning-evening overlap of some months that record the most frequent substantial inversions during the fall time of the year, coinciding with the time when the worst air pollution events occur.
The smart helmet is designed for a wildland firefighter to send vital data to their supervisor while they are working to extinguish an active fire. The smart helmet collects temperature, heart rate, and acceleration data from each firefighter via sensors inside and around the helmet. The data is used to alert the supervisor of potential health or emergency issues, such as heat-related illness, dehydration, potential falls or abnormal heart rates. A mobile app that the supervisor connects to their smart helmet device collects data in real time from the firefighters, without the need of any cellular coverage or WiFi.
Extreme temperature events are linked to increased emergency department visits, hospitalizations, and mortality for individuals with behavioral health disorders (BHD). This study aims to characterize risk factors for concurrent temperature-related illness among BHD hospitalizations in New York State. Using data from the NYS Statewide and Planning Research and Cooperative System between 2005-2019, multivariate log binomial regression models were used in a population of BHD hospitalizations to estimate risk ratios (RR) for a concurrent heat-related (HRI) or cold-related illness (CRI). Dementia (RR 1.65; 95% CI:1.49, 1.83) and schizophrenia (RR 1.38; 95% CI:1.19, 1.60) were associated with an increased risk for HRI among BHD hospitalizations, while alcohol dependence (RR 2.10; 95% CI:1.99, 2.22), dementia (RR 1.52; 95% CI:1.44, 1.60), schizophrenia (RR 1.41; 95% CI:1.31, 1.52), and non-dependent drug/alcohol use (RR 1.20; 95% CI:1.15, 1.26) were associated with an increased risk of CRI among BHD hospitalizations. Risk factors for concurrent HRI among BHD hospitalizations include increasing age, male gender, non-Hispanic Black race, and medium hospital size. Risk factors for concurrent CRI among BHD hospitalizations include increasing age, male gender, non-Hispanic Black race, insurance payor, the presence of respiratory disease, and rural hospital location. This study adds to the literature by identifying dementia, schizophrenia, substance-use disorders, including alcohol dependence and non-dependent substance-use, and other sociodemographic factors as risk factors for a concurrent CRI in BHD hospitalizations.
INTRODUCTION: The purpose of this study was to evaluate heat stress occurring in wildfire management activities with variable environmental conditions. METHODS: Direct observation and real-time wireless physiological monitoring allowed for weather and physiological metrics, including heart rate, core temperature (T(c)), skin temperature, and physiological strain index (PSI), of male (n=193) and female (n=28) wildland firefighters (WLFFs) to be recorded during wildfire management activities. Accelerometry data were used to categorize intensity level of activity. RESULTS: Ambient temperature and relative humidity values were used to compute the heat index (HI; n=3891 h) and divided into quartiles (Q1: 13.3-25.1°C; Q2: 25.2-26.4°C; Q3: 26.5-28.9°C; Q4: 29.0-49.1°C). Activity levels remained relatively constant across all HI quartiles. The percentage of time spent performing moderate/vigorous activities was lowest during the hotter Q4 (Q1: 3%; Q2: 2%; Q3: 2%; Q4: 1%). Heart rate, T(c), PSI, and skin temperature associations with HI varied by resource type. Sixty-one percent of WLFFs (n=134) experienced a T(c) ≥38.0°C, and 50% of WLFFs (n=111) experienced a PSI ≥6.0. CONCLUSIONS: Heat stress was prevalent as WLFFs performed job tasks of varying intensities in all ambient conditions. Spontaneous bouts of arduous labor, duration of work shifts, and other occupation characteristics present the possibility for substantial durations of hyperthermia, although no heat-related injuries occurred in this study. Despite chronic exposure to rugged sloped terrain, load carriage, and environmental conditions, self-regulation and individual attention to managing work:rest appears to be the primary management strategy in mitigating excessive accumulation of body heat in this occupation.
Uncompensable heat from wildland firefighter personal protective equipment decreases the physiological tolerance while exercising in the heat. Our previous work demonstrated that the standard wildland firefighter helmet significantly increases both perceived and actual head heat. This study compared heat accumulation under simulated working conditions while wearing a standard non-vented helmet versus a vented helmet. Ten male subjects randomly completed two trials separated by a 2-week washout. Subjects walked 180 min (5.6 km h−1, 5% grade) in a heat chamber (35°C, 30% relative humidity) broken into three segments of 50 min of exercise and 10 min rest, followed by a work capacity test to exhaustion. Each trial measured the physiological strain index, perceived head heat, helmet temperature and relative humidity, rating of perceived exertion and heart rate. At the end of the 3-h trial heart rate, physiological strain, perceived exertion, helmet temperature and humidity showed the main effects of time (P < 0.05) but were not different between trials. Work capacity was significantly greater in the vented trial (P = 0.001). End-trial strain and heart rate were significantly related to work performed (r = –0.8, P < 0.001). Elevated work, trends for changes in perceived exertion, helmet microenvironment and perceived head heat suggest greater heat dissipation and comfort with the vented helmet.
High ambient temperatures and strenuous physical activity put workers at risk for a variety of heat-related illnesses and injuries. Through primary prevention, secondary prevention, and treatment, OEM health providers can protect workers from the adverse effects of heat. This statement by the American College of Occupational and Environmental Medicine provides guidance for OEM providers who serve workers and employers in industries where heat exposure occurs.
OBJECTIVE: Climate and social vulnerability contribute to morbidity and health care utilization. We examined associations between the neighborhood Social Vulnerability Index (SVI) and the Heat Vulnerability Index (HVI) and recurrent hospitalizations among individuals with rheumatic conditions. METHODS: Using a Massachusetts multihospital centralized clinical data repository, we identified individuals ≥18 years of age with a rheumatic condition who received rheumatology care within 3 years of April 2021. We defined the index date as 2 years before the last encounter and the baseline period as 1 year pre-index date. Addresses were geocoded and linked by census tract to the SVI and the HVI. We used multilevel, multinomial logistic regression to examine the odds of 1-3 and ≥4 hospitalizations (reference = 0) over 2 years post index date by vulnerability index, adjusting for age, gender, race/ethnicity, insurance, and comorbidities. RESULTS: Among 14,401 individuals with rheumatic conditions, the mean ± age was 61.9 ± 15.7 years, 70% were female, 79% White, 7% Black, and 2% Hispanic. There were 8,251 hospitalizations; 11,649 individuals (81%) had 0 hospitalizations, 2,063 (14%) had 1-3, and 689 (5%) had ≥4. Adjusting for individual-level factors, individuals living in the highest versus lowest SVI areas had 1.84 times higher odds (95% confidence interval [95% CI] 1.43-2.36) of ≥4 hospitalizations. Individuals living in the highest versus lowest HVI areas had 1.64 times greater odds (95% CI 1.17-2.31) of ≥4 hospitalizations. CONCLUSION: Individuals with rheumatic conditions living in areas with high versus low social and heat vulnerability had significantly greater odds of recurrent hospitalizations. Studies are needed to determine modifiable factors to mitigate risks.
The prevention of snake envenomations in North America often focuses on avoiding interactions between humans and snakes. Previous strategies have focused on the influence of geography, type of habitat, and time of year, though a detailed analysis of weather patterns on snakebite envenomation behavior is lacking. We present a case-crossover study of non-pregnant adults (n = 489) who reported snake envenomations to a single state’s poison control center from 2014 to 2018. Age and gender of the individual, as well as the date, time, zip code associated with the envenomation, and snake descriptions were collected. Information regarding barometric pressure, actual temperature, high and low daily temperature, and weather condition (fair, cloudy, or rain/precipitation) was collected and compared to the same zip code, date, and time exactly one week and one year prior to the envenomation using historical data from the Weather Underground database. Paired t-tests and Stuart-Maxwell tests were used to determine differences in weather conditions during the study period. This study was IRB-approved. At the time of envenomation, the weather was most often fair (52.2%), followed by cloudy (44%), and least frequently demonstrated rain/precipitation (3.9%). Snake envenomations increased significantly (p < 0.0001) on days with an elevated daily high temperature. There were statistical differences in the distribution of weather conditions (fair, cloudy, or rain/precipitation) on the day of envenomation compared to one week prior (p < 0.0001) and one year prior (p < 0.0008). Comparisons based on both control groups indicated that envenomations were significantly less likely to occur during rain/precipitation and cloudy weather than during fair weather. Limitations include its retrospective nature and low total number of envenomations. In our single-center study, snake envenomation behavior as it relates to readily reportable weather measurements, appears to be associated with the warmer days, the overall high temperature on the day of envenomation, and fair weather conditions. Actual temperature at the time of envenomation, low temperature, barometric pressure, and precipitation at the time of envenomation do not appear to be associated with an increased risk of envenomation. Additional studies to determine the cause of these associations would be beneficial in further delineating the findings of this study.
OBJECTIVES: High ambient temperatures may contribute to acute asthma exacerbation, a leading cause of morbidity in children. We quantified associations between hot-season ambient temperatures and asthma exacerbation in children ages 0-18 years in Philadelphia, PA. METHODS: We created a time series of daily counts of clinical encounters for asthma exacerbation at the Children’s Hospital of Philadelphia linked with daily meteorological data, June-August of 2011-2016. We estimated associations between mean daily temperature (up to a 5-day lag) and asthma exacerbation using generalised quasi-Poisson distributed models, adjusted for seasonal and long-term trends, day of the week, mean relative humidity,and US holiday. In secondary analyses, we ran models with adjustment for aeroallergens, air pollutants and respiratory virus counts. We quantified overall associations, and estimates stratified by encounter location (outpatient, emergency department, inpatient), sociodemographics and comorbidities. RESULTS: The analysis included 7637 asthma exacerbation events. High mean daily temperatures that occurred 5 days before the index date were associated with higher rates of exacerbation (rate ratio (RR) comparing 33°C-13.1°C days: 1.37, 95% CI 1.04 to 1.82). Associations were most substantial for children ages 2 to <5 years and for Hispanic and non-Hispanic black children. Adjustment for air pollutants, aeroallergens and respiratory virus counts did not substantially change RR estimates. CONCLUSIONS: This research contributes to evidence that ambient heat is associated with higher rates of asthma exacerbation in children. Further work is needed to explore the mechanisms underlying these associations.
Adaptation across systems’ in agriculture is essential for sustainability under ongoing climate change. Farmers and agricultural employers implement changes in their work (e.g., mechanization, changing crops, managing workspaces) in ways that may directly impact worker health. In this study, semi-structured interviews were conducted with farmers and farm labor contractors in three agriculturally productive regions of California. We investigated (1) how farmers view changing climate in terms of worker safety and health; (2) how they are currently adapting to long-term weather patterns; (3) how their choices of management practices might impact their workers; (4) how they view their responsibility for their workers; and (5) what their overall observations are concerning environmental changes. Many employers made a clear distinction between weather and climate but not all agreed on whether they were experiencing climate change. Heat was notably the biggest climate hazard farmers identified. Most of the employers interviewed were proud of their longevity and ability to adapt to changing conditions in the field; however, they did not have established emergency procedures. Despite regulations that put the onus on employers, most participants believed that workers needed to take individual responsibility to keep themselves safe in the workplace. This research is one step in an ongoing research process designed to address the impacts of health and safety for agricultural workers in the context of climate change.
OBJECTIVES: To characterise heat-related acute kidney injury (HR-AKI) among US workers in a range of industries. METHODS: Two data sources were analysed: archived case files of the Occupational Safety and Health Administration’s (OSHA) Office of Occupational Medicine and Nursing from 2010 through 2020; and a Severe Injury Reports (SIR) database of work-related hospitalisations that employers reported to federal OSHA from 2015 to 2020. Confirmed, probable and possible cases of HR-AKI were ascertained by serum creatinine measurements and narrative incident descriptions. Industry-specific incidence rates of HR-AKI were computed. A capture-recapture analysis assessed under-reporting in SIR. RESULTS: There were 608 HR-AKI cases, including 22 confirmed cases and 586 probable or possible cases. HR-AKI occurred in indoor and outdoor industries including manufacturing, construction, mail and package delivery, and solid waste collection. Among confirmed cases, 95.2% were male, 50.0% had hypertension and 40.9% were newly hired workers. Incidence rates of AKI hospitalisations from 1.0 to 2.5 hours per 100000 workers per year were observed in high-risk industries. Analysis of overlap between the data sources found that employers reported only 70.6% of eligible HR-AKI hospitalisations to OSHA, and only 41.2% of reports contained a consistent diagnosis. CONCLUSIONS: Workers were hospitalised with HR-AKI in diverse industries, including indoor facilities. Because of under-reporting and underascertainment, national surveillance databases underestimate the true burden of occupational HR-AKI. Clinicians should consider kidney risk from recurrent heat stress. Employers should provide interventions, such as comprehensive heat stress prevention programmes, that include acclimatisation protocols for new workers, to prevent HR-AKI.
Multiple sclerosis (MS) is a neurological disorder that progressively distorts the myelination of axons within the central nervous system (CNS). Increased core body temperature or metabolism as a result of exercise are common causes of short-term exacerbations of neurological symptoms in MS. About 60-80% of patients with MS experience a worsening of their symptoms when exposed to heat. In comparison, less data are available on the relationship between ambient meteorological conditions (e.g., temperature and relative humidity (RH)) and fluctuations in such variables in relation to MS symptoms. Thus, this study examined associations between time-lagged exposure to meteorological conditions and risk of a clinic visit due to MS among US veterans between 2010 and 2013. This study leveraged data from the Veterans Affairs (VA) and National Climactic Data Center (NCDC) for the continental US, partitioned into eight climate zones. We used a case crossover design to assess the risk of a MS clinic visit with respect to several meteorological conditions. Location-specific time-lagged daily (ambient) exposure to temperature, RH, and temperature variations (standard deviation (SD) of temperature) were computed (up to 30 days) for each case (i.e., day of MS visit) and control (a randomly assigned date ± 90-270 days prior to visit). Statistical analyses were conducted to examine independent associations between the selected meteorological conditions and risk of MS visits at the national and regional levels. A total of 533,066 patient visits received a MS diagnosis (International Classifications of Diseases (ICD)-9 code = 340). The Northeast (NE) and Upper Midwest (UMW) regions reported the highest frequency of clinic visits due to MS. Clinic visits were 9% more likely to occur in the spring, summer, and fall months (March-October) than in the winter (OR = 1.089; 95% CI = 1.076-1.103; p < 0.01). In the univariate analyses, the SD of temperature, temperature, and temperature-RH interaction were positively associated with an elevated risk of a MS clinic visit, while the RH was negatively associated with the risk for a clinic visit. In multivariate analyses, the strongest association of a MS clinic visit was observed with the SD of the temperature (OR = 1.012; 95% CI 1.008-1.017; p < 0.01). These associations between MS clinic visits and meteorological conditions varied across climate regions, with the strongest associations being observed in the LMW, UMW, DSW, and NE zones. The SD of the temperature was again the strongest associated predictor when examined regionally. Temperature variations and temperature-RH interactions (a proxy of the heat index) showed significant associations with MS clinic visits. These associations varied across climate regions when examined geographically. Our findings have implications for the management of MS in severe or recurrent cases, especially considering the impending changes in the daily temperature variations and intensity of the heatwaves expected with the intensification of global warming.
BACKGROUND: Increasing temperatures negatively impact health and increases demands on healthcare systems. However, this has been poorly studied in Rhode Island (RI). Here we characterize the impact of heat on emergency medical services (EMS) utilization in RI. METHODS: The Rhode Island National Emergency Services Information System V3 dataset was merged with data from the National Center for Environmental Information of the National Oceanic and Atmospheric Administration from the summers of 2018 and 2019. The outcome of daily mean EMS runs were compared against the exposure increasing daily temperatures, measured as daily maximum, minimum and daily average °F, using Poisson regressions. Patient characteristics were included across temperature models. RESULTS: Increasing daily temperatures were associated with increasing EMS encounters. The adjusted incident rate ratio (IRR) for mean daily EMS encounters by increasing maximum daily temperature was 1.006 (95% CI 1.004-1.007, Table 3). This resulted in a projected 17.2% increase in EMS runs on days with a maximum temperature of 65°F compared to days with a maximum temperature of 95°F. The adjusted IRR for mean daily EMS encounters by the daily minimum temperature was 1.004 (1.003-1.006) and the adjusted IRR for the mean daily EMS encounters by the daily average temperature was 1.006 (1.005-1.008). CONCLUSIONS: Increasing minimum, maximum, and average daily temperatures were associated with increasing EMS utilization across Rhode Island in the summers of 2018 and 2019. Further research into these trends may help with planning and resource allocation as summer temperatures continue to rise.
Acute heat exposure protects against endothelial ischemia-reperfusion (I/R) injury in humans. However, the mechanism/s mediating this protective effect remain unclear. We tested the hypothesis that inhibiting the increase in shear stress induced by acute heat exposure would attenuate the protection of endothelial function following I/R injury. Nine (3 women) young healthy participants were studied under three experimental conditions: 1) thermoneutral control; 2) whole body heat exposure to increase body core temperature by 1.2°C; and 3) heat exposure + brachial artery compression to inhibit the temperature-dependent increase in shear stress. Endothelial function was assessed via brachial artery flow-mediated dilatation before (pre-I/R) and after (post-I/R) 20 min of arm ischemia followed by 20 min of reperfusion. Brachial artery shear rate was increased during heat exposure (681 ± 359 s^(−1)), but not for thermoneutral control (140 ± 63 s−1; P < 0.01 vs. heat exposure) nor for heat + brachial artery compression (139 ± 60 s−1; P < 0.01 vs. heat exposure). Ischemia-reperfusion injury reduced flow-mediated dilatation following thermoneutral control (pre-I/R, 5.5 ± 2.9% vs. post-I/R, 3.8 ± 2.9%; P = 0.06), but was protected following heat exposure (pre-I/R, 5.8 ± 2.9% vs. post-I/R, 6.1 ± 2.9%; P = 0.5) and heat + arterial compression (pre-I/R, 4.4 ± 2.8% vs. post-I/R, 5.8 ± 2.8%; P = 0.1). Contrary to our hypothesis, our findings demonstrate that shear stress induced by acute heat exposure is not obligatory to protect against endothelial I/R injury in humans.NEW & NOTEWORTHY Acute heat exposure protects against endothelial ischemia-reperfusion injury in humans. However, the mechanism/s mediating this protective effect remain unclear. We utilized arterial compression to inhibit the temperature-dependent increase in brachial artery blood velocity that occurs during acute heat exposure to isolate the contribution of shear stress to the protection of endothelial function following ischemia-reperfusion injury. Our findings demonstrate that shear stress induced by acute heat exposure is not obligatory to protect against endothelial I/R injury.
Upward trends in ground-level warming are expected to intensify, affecting the health of human populations. Specific to the United States, the Northeast (NE) region is one of the most vulnerable to these warming trends. Previous research has found social disparities in the distribution of heat, while recent studies have examined associations between metropolitan racial/ethnic segregation and heat exposures. We advance upon previous research by including a novel measure of neighborhood-level racial/ethnic diversity in our examination of social inequalities in heat for NE neighborhoods (census tracts). We paired data derived from the United States Geological Survey on mean land surface temperature (LST) for the summer months of 2013-2017 with sociodemographic data from the American Community Survey (5-year estimates, 2013-2017). We use multivariable generalized estimating equations (GEEs) that adjust for geographic clustering. Findings reveal heat exposure disparities across NE neighborhoods. Neighborhoods with higher proportions of racial/ethnic minorities, people of lower socioeconomic status, households without access to an automobile, and greater diversity experience higher temperatures. Diversity was more strongly related to increased heat in neighborhoods with lower Latinx and lower Black composition suggesting that neighborhood homogeneity confers a differentially greater cooling effect based on higher White composition. The social groups that carry the unequal thermal burdens are also those who are most vulnerable. Interventions to reduce heat risks in the NE should therefore prioritize reducing the burden on historically disadvantaged communities.
In recent years, demographic growth has caused cities to expand their urban areas, increasing the risk of overheating, creating insurmountable microclimatic conditions within the urban area, which is why studies have been carried out on the urban heat island effect (UHI) and its mitigation. Therefore, this research aims to evaluate the cooling potential in the application of strategies based on biomimicry for the microclimate in a historical heritage city of Panama. For this, three case studies (base case, case 1, and case 2) of outdoor thermal comfort were evaluated, in which the Envi-met software was used to emulate and evaluate the thermal performance of these strategies during March (highest temperature month) and October (rainier month). The strategies used were extracted from the contrast of zebra skin, human skin, evaporative cooling, and ant skin. The results showed a reduction of 2.8 °C in the air temperature at 11:00, the radiant temperature decreased by 2.2 °C, and the PET index managed to reduce the thermal comfort indicator among its categories. The importance of thinking based on biomimicry in sustainable strategies is concluded; although significant changes were obtained, high risks of discomfort persist due to the layout and proximity of the building.
Emerging research suggests that internet search patterns may provide timely, actionable insights into adverse health impacts from, and behavioral responses to, days of extreme heat, but few studies have evaluated this hypothesis, and none have done so across the United States. We used two-stage distributed lag nonlinear models to quantify the interrelationships between daily maximum ambient temperature, internet search activity as measured by Google Trends, and heat-related emergency department (ED) visits among adults with commercial health insurance in 30 US metropolitan areas during the warm seasons (May to September) from 2016 to 2019. Maximum daily temperature was positively associated with internet searches relevant to heat, and searches were in turn positively associated with heat-related ED visits. Moreover, models combining internet search activity and temperature had better predictive ability for heat-related ED visits compared to models with temperature alone. These results suggest that internet search patterns may be useful as a leading indicator of heat-related illness or stress.
Place-based structural inequalities can have critical implications for the health of vulnerable populations. Historical urban policies, such as redlining, have contributed to current inequalities in exposure to intra-urban heat. However, it is unknown whether these spatial inequalities are associated with disparities in heat-related health outcomes. The aim of this study is to determine the relationships between historical redlining, intra-urban heat conditions, and heat-related emergency department visits using data from 11 Texas cities. At the zip code level, the proportion of historical redlining was determined, and heat exposure was measured using daytime and nighttime land surface temperature (LST). Heat-related inpatient and outpatient rates were calculated based on emergency department visit data that included ten categories of heat-related diseases between 2016 and 2019. Regression or spatial error/lag models revealed significant associations between higher proportions of redlined areas in the neighborhood and higher LST (Coef. = 0.0122, 95% CI = 0.0039-0.0205). After adjusting for indicators of social vulnerability, neighborhoods with higher proportions of redlining showed significantly elevated heat-related outpatient visit rate (Coef. = 0.0036, 95% CI = 0.0007-0.0066) and inpatient admission rate (Coef. = 0.0018, 95% CI = 0.0001-0.0035). These results highlight the role of historical discriminatory policies on the disparities of heat-related illness and suggest a need for equity-based urban heat planning and management strategies.
Much research has shown a general decrease in the negative health response to extreme heat events in recent decades. With a society that is growing older, and a climate that is warming, whether this trend can continue is an open question. Using eight additional years of mortality data, we extend our previous research to explore trends in heat-related mortality across the United States. For the period 1975-2018, we examined the mortality associated with extreme-heat-event days across the 107 largest metropolitan areas. Mortality response was assessed over a cumulative 10-day lag period following events that were defined using thresholds of the excess heat factor, using a distributed-lag nonlinear model. We analyzed total mortality and subsets of age and sex. Our results show that in the past decade there is heterogeneity in the trends of heat-related human mortality. The decrease in heat vulnerability continues among those 65 and older across most of the country, which may be associated with improved messaging and increased awareness. These decreases are offset in many locations by an increase in mortality among men 45-64 (+1.3 deaths per year), particularly across parts of the southern and southwestern United States. As heat-warning messaging broadly identifies the elderly as the most vulnerable group, the results here suggest that differences in risk perception may play a role. Further, an increase in the number of heat events over the past decade across the United States may have contributed to the end of a decades-long downward trend in the estimated number of heat-related fatalities.
Construction workers often expose to heat stress hazards as temperature and humidity increase. Heat-related illnesses include heat stroke, heat exhaustion, heat cramps, and heat rash conditions. Without immediate and correct treatments, patients may suffer from brain damage or other organ failures, and even death. Heat exposure can also cause fatigue and then lead to other construction accidents. It is crucial to raise awareness of heat-related illnesses and equip people with the means and methods to prevent them from happening. This study aims to assess the current status of people’s knowledge of heat-related illnesses using an online survey questionnaire. The results suggest that further heat-related training should put more focus on the training topics of heat-related illnesses prevention strategies, first-aid, and symptom identifications. The participants whose work is directly related to safety have a better understanding of heat-related illness symptoms than the rest. The results also indicate that the participants’ knowledge of heat-related illness prevention is related to their age and whether they had participated in heat-related training. The findings of this research can help with the development of future heat-related illnesses training and facilitate construction companies to improve their current safety culture and practices.
OBJECTIVE: To quantify the association between ambient heat and visits to the emergency department (ED) for any cause and for cause specific conditions in the conterminous United States among adults with health insurance. DESIGN: Time stratified case crossover analyses with distributed lag non-linear models. SETTING: US nationwide administrative healthcare claims database. PARTICIPANTS: All commercial and Medicare Advantage beneficiaries (74.2 million) aged 18 years and older between May and September 2010 to 2019. MAIN OUTCOME MEASURES: Daily rates of ED visits for any cause, heat related illness, renal disease, cardiovascular disease, respiratory disease, and mental disorders based on discharge diagnosis codes. RESULTS: 21 996 670 ED visits were recorded among adults with health insurance living in 2939 US counties. Days of extreme heat-defined as the 95th centile of the local warm season (May through September) temperature distribution (at 34.4°C v 14.9°C national average level)-were associated with a 7.8% (95% confidence interval 7.3% to 8.2%) excess relative risk of ED visits for any cause, 66.3% (60.2% to 72.7%) for heat related illness, 30.4% (23.4% to 37.8%) for renal disease, and 7.9% (5.2% to 10.7%) for mental disorders. Days of extreme heat were associated with an excess absolute risk of ED visits for heat related illness of 24.3 (95% confidence interval 22.9 to 25.7) per 100?Çë000 people at risk per day. Heat was not associated with a higher risk of ED visits for cardiovascular or respiratory diseases. Associations were more pronounced among men and in counties in the north east of the US or with a continental climate. CONCLUSIONS: Among both younger and older adults, days of extreme heat are associated with a higher risk of ED visits for any cause, heat related illness, renal disease, and mental disorders. These results suggest that the adverse health effects of extreme heat are not limited to older adults and carry important implications for the health of adults across the age spectrum.
Extreme temperature significantly affects workforce health during the summer in locations with sustained high temperatures. The exposure of workers to excessive heat has increased in the last decades, and it is correlated with reduced productivity and work efficiency. The effects of extreme heat on the health of outdoor workers in the southwestern USA were assessed using the heat index (HI) calculated using temperature and humidity information from National Oceanic and Atmospheric Administration and data on occupational injuries/illnesses from the US Bureau of Labor Statistics. The analysis of the data was performed using the Spearman’s rho nonparametric analysis. A statistically significant increase in the heat index was found in two of the three locations selected for this study. At the Phoenix Sky Harbor Airport (Phoenix, AZ) and Harry Reid International Airport (Las Vegas, NV) stations, seasonal maximum HI values exceeded the extreme danger threshold and seasonal average HI ranges were found within the dangerous range. The number of nonfatal occupational heat-related injuries/illnesses in Arizona, California, and Nevada were also analyzed and were found to be steadily increasing in all three states over the study period (2011-2018). The overall number of nonfatal occupational injuries/illnesses were also analyzed as a function of the length of service with the employer, which showed an increase in the number of events with an increase in the length of service. The time of the day and number of hours worked were also found to significantly affect the overall number of nonfatal occupational injuries/illnesses in the three locations studied. In addition, the number of days away from work after the occurrence of a heat-related, nonfatal occupational injury/illness event was significantly higher for events during which the worker remained away from work for more than 30 days. Results from this study suggest that extreme heat poses a real threat for outdoor workers and decision-making devoted to addressing this risk is required to prevent undesirable effects.
Occupational heat exposure is linked to the development of kidney injury and disease in individuals who frequently perform physically demanding work in the heat. For instance, in Central America, an epidemic of chronic kidney disease of nontraditional origin (CKDnt) is occurring among manual laborers, whereas potentially related epidemics have emerged in India and Sri Lanka. There is growing concern that workers in the United States suffer with CKDnt, but reports are limited. One of the leading hypotheses is that repetitive kidney injury caused by physical work in the heat can progress to CKDnt. Whether heat stress is the primary causal agent or accelerates existing underlying pathology remains contested. However, the current evidence supports that heat stress induces tubular kidney injury, which is worsened by higher core temperatures, dehydration, longer work durations, muscle damaging exercise, and consumption of beverages containing high levels of fructose. The purpose of this narrative review is to identify occupations that may place US workers at greater risk of kidney injury and CKDnt. Specifically, we reviewed the scientific literature to characterize the demographics, environmental conditions, physiological strain (i.e., core temperature increase, dehydration, heart rate), and work durations in sectors typically experiencing occupational heat exposure, including farming, wildland firefighting, landscaping, and utilities. Overall, the surprisingly limited available evidence characterizing occupational heat exposure in US workers supports the need for future investigations to understand this risk of CKDnt.
BACKGROUND: Some socioeconomically vulnerable groups may experience disproportionately higher risk of extreme heat illness than other groups, but no study has utilized the presence/absence of a social security number (SSN) as a proxy for vulnerable sub-populations. METHODS: This study focused on the warm season from 2008 to 2012 in Florida, U.S. With a total number of 8,256,171 individual level health outcomes, we devised separate case-crossover models for five heat-sensitive health outcomes (cardiovascular disease, dehydration, heat-related illness, renal disease, and respiratory disease), type of health care visit (emergency department (ED) and hospitalization), and patients reporting/not reporting an SSN. Each stratified model also considered potential effect modification by sex, age, or race/ethnicity. RESULTS: Mean temperature raised the odds of five heat-sensitive health outcomes with the highest odds ratios (ORs) for heat-related illness. Sex significantly modified heat exposure effects for dehydration ED visits (Males: 1.145, 95 % CI: 1.137-1.153; Females: 1.110, 95 % CI: 1.103-1.117) and hospitalization (Males: 1.116, 95 % CI: 1.110-1.121; Females: 1.100, 95 % CI: 1.095-1.105). Patients not reporting an SSN between 25 and 44 years (1.264, 95 % CI: 1.192-1.340) exhibited significantly higher dehydration ED ORs than those reporting an SSN (1.146, 95 % CI: 1.136-1.157). We also observed significantly higher ORs for cardiovascular disease hospitalization from the no SSN group (SSN: 1.089, 95 % CI: 1.088-1.090; no SSN: 1.100, 95 % CI: 1.091-1.110). CONCLUSIONS: This paper partially supports the idea that individuals without an SSN could experience higher risks of dehydration (for those 25-45 years), renal disease, and cardiovascular disease than those with an SSN.
IMPORTANCE: Firearm violence is a leading public health crisis in the US. Understanding whether and how ambient temperature is associated with firearm violence may identify new avenues for prevention and intervention. OBJECTIVE: To estimate the overall and regional association between hotter temperatures and higher risk of firearm violence in the US. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used distributed lag nonlinear models, controlling for seasonality and long-term time trends by city and pooled results overall and by climate region. The most populous cities in the US with the highest number of assault-related firearm incidence (ie, shootings) from 2015 to 2020 were analyzed. Data analysis was performed from October 2021 to June 2022. EXPOSURES: Maximum daily temperature by city. MAIN OUTCOMES AND MEASURES: The primary outcome was the number of assault-related firearm shootings by city. RESULTS: A total of 116 511 shootings in 100 cities were included in this analysis. The pooled analysis estimated that 6.85% (95% CI, 6.09%-7.46%) of all shootings were attributable to days hotter than city-specific median temperatures. This equates to 7973 total shootings (95% CI, 7092-8688 total shootings) across the 100 cities over the 6-year study period, although the number of total persons injured or killed would be higher. Estimated risk of firearm incidents increased almost monotonically with higher temperatures, with a local peak at the 84th percentile of the temperature range corresponding to a relative risk of 1.17 (95% CI, 1.12-1.21) compared with the median temperature. However, even moderately hot temperatures were associated with higher risk of shootings. Although significant, there was low heterogeneity between cities (I2 = 11.7%; Cochran Q test, P = .02), indicating regional or climate-specific variation in the daily temperature and incident shootings relationship. CONCLUSIONS AND RELEVANCE: These findings underscore the importance of heat adaptation strategies broadly throughout the year to reduce shootings, rather than focusing on only the hottest days.
Here we use remotely sensed land surface temperature measurements to explore the distribution of the United States’ urban heating burden, both at high resolution (within cities or counties) and at scale (across the whole contiguous United States). While a rich literature has documented neighborhood-level disparities in urban heat exposures in individual cities, data constraints have precluded comparisons across locations. Here, drawing on urban temperature anomalies during extreme summer surface temperature events from all 1,056 US counties with more than 10 developed census tracts, we find that the poorest tracts (and those with lowest average education levels) within a county are significantly hotter than the richest (and more educated) neighborhoods for 76% of these counties (54% for education); we also find that neighborhoods with higher Black, Hispanic, and Asian population shares are hotter than the more White, non-Hispanic areas in each county. This holds in counties with both large and small spreads in these population shares, and for 71% of all counties the significant racial urban heat disparities persist even when adjusting for income. Although individual locations have different histories that have contributed to race- and class-based geographies, we find that the physical features of the urban environments driving these surface heat exposure gradients are fairly uniform across the country. Systematically, the disproportionate heat surface exposures faced by minority communities are due to more built-up neighborhoods, less vegetation, and—to a lesser extent—higher population density.
BACKGROUND: Emerging literature has documented heat-related impacts on child health, yet few studies have evaluated the effects of heat among children of different age groups and comparing emergency department (ED) and hospitalisation risks. OBJECTIVES: To examine the differing associations between high ambient temperatures and risk of ED visits and hospitalisations among children by age group in New York City (NYC). METHODS: We used New York Statewide Planning and Research Cooperative System (SPARCS) data on children aged 0-18 years admitted to NYC EDs (n = 2 252 550) and hospitals (n = 228 006) during the warm months (May-September) between 2005 and 2011. Using a time-stratified, case-crossover design, we estimated the risk of ED visits and hospitalisations associated with daily maximum temperature (Tmax) for children of all ages and by age group. RESULTS: The average Tmax over the study period was 80.3°F (range 50°, 104°F). Tmax conferred the greatest risk of ED visits for children aged 0-4, with a 6-day cumulative excess risk of 2.4% (95% confidence interval [CI] 1.7, 3.0) per 13°F (ie interquartile range) increase in temperature. Children and adolescents 5-12 years (0.8%, 95% CI 0.1, 1.6) and 13-18 years (1.4%, 95% CI 0.6, 2.3) are also sensitive to heat. For hospitalisations, only adolescents 13-18 years had increased heat-related risk, with a cumulative excess risk of 7.9% (95% CI 2.0, 14.2) per 13°F increase in Tmax over 85°F. CONCLUSIONS: This urban study in NYC reinforces that young children are particularly vulnerable to effects of heat, but also demonstrates the sensitivity of older children and adolescents as well. These findings underscore the importance of focussing on children and adolescents in targeting heat illness prevention and emergency response activities, especially as global temperatures continue to rise.
Climate change is expected to exacerbate the urban heat island (UHI) effect in cities worldwide, increasing the risk of heat-related morbidity and mortality. Solar reflective ‘cool pavement’ is one of several mitigation strategies that may counteract the negative effects of the UHI effect. An increase in pavement albedo results in less heat absorption, which results in reduced surface temperatures (T (surface)). Near surface air temperatures (T (air)) could also be reduced if cool pavements are deployed at sufficiently large spatial scales, though this has never been confirmed by field measurements. This field study is the first to conduct controlled measurements of the impacts of neighborhood-scale cool pavement installations. We measured the impacts of cool pavement on albedo, T (surface), and T (air). In addition, pavement albedo was monitored after installation to assess its degradation over time. The field site (similar to 0.64 km(2)) was located in Covina, California; similar to 30 km east of Downtown Los Angeles. We found that an average pavement albedo increase of 0.18 (from 0.08 to 0.26) corresponded to maximum neighborhood averaged T (surface) and T (air) reductions of 5 degrees C and 0.2 degrees C, respectively. Maximum T (surface) reductions were observed in the afternoon, while minimum reductions of 0.9 degrees C were observed in the morning. T (air) reductions were detected at 12:00 local standard time (LST), and from 20:00 LST to 22:59 LST, suggesting that cool pavement decreases T (air) during the daytime as well as in the evening. An average albedo reduction of 30% corresponded to a similar to 1 degrees C reduction in the T (surface) cooling efficacy. Although we present here the first measured T (air) reductions due to cool pavement, we emphasize that the tradeoffs between T (air) reductions and reflected shortwave radiation increases are still unclear and warrant further investigation in order to holistically assess the efficacy of cool pavements, especially with regards to pedestrian thermal comfort.
Extreme heat events pose a threat to human health. Forecasting and warning strategies have been developed to mitigate heat-health hazards. Yet, studies have found that the public lacks knowledge about their heat-health risks and preventive actions to take to reduce risks. Local governmental websites are an important means to communicate preparedness to the public. The purpose of this study is to examine information provided to the public on municipal government web pages of the 10 most populous U.S. cities. A two-level document and content analyses were conducted. A direct content analysis was conducted using federal government websites and documents to create the Extreme Heat Event Public Response Rubric. The rubric contains two broad categories of populations and actions that are further specified. The rubric was then used to examine local government extreme heat event websites for the 10 most populous cities in the United States. The examination of the local government sites found that information included on the websites failed to identify the breadth of populations at greater risk for adverse heat-health outcomes and omitted some recommended actions designed to prevent adverse heat-health events. Local governments often communicated concrete and simple content to the public but more complex information was not included on their websites. SIGNIFICANCE STATEMENT: Extreme heat is the leading weather-related cause of mortality in the United States annually. Public response to extreme heat events requires that the public understand their risk and know the actions to take to mitigate that risk. The public seeks information from local government websites. Our results found that many local government websites did not provide the information to the public on the array of conditions and factors that put people at a greater risk for an adverse heat-health event, nor did the websites include information on the variety of actions that the public should take in response to an extreme heat event in order to reduce their risks. Addressing the omission of the information on these websites may improve public response to extreme heat events.
The occurrence of extreme weather and climate events has increased in recent decades. This increasing frequency has adversely impacted economic and health outcomes, leading to an increasingly urgent need to study climate extremes. The National Centers for Environmental Information (NCEI) created the Climate Extremes Index (CEI) in 1996 to quantify climate extremes. In this article, we explore the potential for enhancing the CEI via the use of the Z-score statistic to calculate the CEI on a numerical scale, to increase usability at smaller spatial scales, and to allow the creation of a new climate Extremes Vulnerability Index (EVI). The EVI combines the results from the revised CEI with values from the Social Vulnerability Index from the Centers for Disease Control and Prevention (CDC). The EVI can be used by policy-makers, planners, and the public to understand a subregion’s vulnerability to climate extremes. This information from the EVI could then be used to implement policies and changes in infrastructure that mitigate risk in vulnerable climate divisions. In a trial application, it is found that the southeastern and portions of the central United States had the highest levels of vulnerability for the abnormal month of December 2015.
BACKGROUND: Heatwaves are becoming more frequent and may acutely increase the risk of stillbirth, a rare and severe pregnancy outcome. OBJECTIVES: Examine the association between multiple heatwave metrics and stillbirth in six U.S. states. METHODS: Data were collected from fetal death and birth records in California (1996-2017), Florida (1991-2017), Georgia (1994-2017), Kansas (1991-2017), New Jersey (1991-2015), and Oregon (1991-2017). Cases were matched to controls 1:4 based on maternal race/ethnicity, maternal education, and county, and exposure windows were aligned (gestational week prior to stillbirth). County-level temperature data were obtained from Daymet and linked to cases and controls by residential county and the exposure window. Five heatwave metrics (1 categorical, 3 dichotomous, 1 continuous) were created using different combinations of the duration and intensity of hot days (mean daily temperature exceeding the county-specific 97.5(th) percentile) during the exposure window, as well as a continuous measure of mean temperature during the exposure window modeled using natural splines to allow for nonlinear associations. State-specific odds ratios (ORs) and 95% confidence intervals (CI) were estimated using conditional logistic regression models. State-specific results were pooled using a fixed-effects meta-analysis. RESULTS: In our data set of 140,428 stillbirths (553,928 live birth controls), three of the five heatwave metrics examined were not associated with stillbirth. However, four consecutive hot days during the previous week was associated with a 3% increase in stillbirth risk (CI: 1.01, 1.06), and a 1 °C average increase over the threshold was associated with a 10% increase in stillbirth risk (CI: 1.04, 1.17). In continuous temperature analyses, there was a slight increased risk of stillbirth associated with extremely hot temperatures (≥ 35 °C). DISCUSSION: Most heat wave definitions examined were not associated with acute changes in stillbirth risk; however, the most extreme heatwave durations and temperatures were associated with a modest increase in stillbirth risk.
BACKGROUND: Extreme-heat events are increasing as a result of climate change. Prior studies, typically limited to urban settings, suggest an association between extreme heat and cardiovascular mortality. However, the extent of the burden of cardiovascular deaths associated with extreme heat across the United States and in different age, sex, or race and ethnicity subgroups is unclear. METHODS: County-level daily maximum heat index levels for all counties in the contiguous United States in summer months (May-September) and monthly cardiovascular mortality rates for adults ≥20 years of age were obtained. For each county, an extreme-heat day was identified if the maximum heat index was ≥90 °F (32.2 °C) and in the 99th percentile of the maximum heat index in the baseline period (1979-2007) for that day. Spatial empirical Bayes smoothed monthly cardiovascular mortality rates from 2008 to 2017 were the primary outcome. A Poisson fixed-effects regression model was estimated with the monthly number of extreme-heat days as the independent variable of interest. The model included time-fixed effects and time-varying environmental, economic, demographic, and health care-related variables. RESULTS: Across 3108 counties, from 2008 to 2017, each additional extreme-heat day was associated with a 0.12% (95% CI, 0.04%-0.21%; P=0.004) higher monthly cardiovascular mortality rate. Extreme heat was associated with an estimated 5958 (95% CI, 1847-10 069) additional deaths resulting from cardiovascular disease over the study period. In subgroup analyses, extreme heat was associated with a greater relative increase in mortality rates among men compared with women (0.20% [95% CI, 0.07%-0.33%]) and non-Hispanic Black compared with non-Hispanic White adults (0.19% [95% CI, 0.01%-0.37%]). There was a greater absolute increase among elderly adults compared with nonelderly adults (16.6 [95% CI, 14.6-31.8] additional deaths per 10 million individuals per month). CONCLUSIONS: Extreme-heat days were associated with higher adult cardiovascular mortality rates in the contiguous United States between 2008 and 2017. This association was heterogeneous among age, sex, race, and ethnicity subgroups. As extreme-heat events increase, the burden of cardiovascular mortality may continue to increase, and the disparities between demographic subgroups may widen.
IMPORTANCE: The number of extreme heat events is increasing because of climate change. Previous studies showing an association between extreme heat and higher mortality rates generally have been limited to urban areas, and whether there is heterogeneity across different populations is not well studied; understanding whether this association varies across different communities, particularly minoritized racial and ethnic groups, may allow for more targeted mitigation efforts. OBJECTIVE: To the assess the association between extreme heat and all-cause mortality rates in the US. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study involved a longitudinal analysis of the association between the number of extreme heat days in summer months from 2008 to 2017 (obtained from the Centers for Disease Control and Prevention’s Environmental Public Health Tracking Program) and county-level all-cause mortality rates (obtained from the National Center for Health Statistics), using a linear fixed-effects model across all counties in the contiguous US among adults aged 20 years and older. Data analysis was performed from September 2021 to March 2022. EXPOSURES: The number of extreme heat days per month. Extreme heat was identified if the maximum heat index was greater than or equal to 90 °F (32.2 °C) and in the 99th percentile of the maximum heat index in the baseline period (1979 to 2007). MAIN OUTCOMES AND MEASURES: County-level, age-adjusted, all-cause mortality rates. RESULTS: There were 219 495 240 adults aged 20 years and older residing in the contiguous US in 2008, of whom 113 294 043 (51.6%) were female and 38 542 838 (17.6%) were older than 65 years. From 2008 to 2017, the median (IQR) number of extreme heat days during summer months in all 3108 counties in the contiguous US was 89 (61-122) days. After accounting for time-invariant confounding, secular time trends, and time-varying environmental and economic measures, each additional extreme heat day in a month was associated with 0.07 additional death per 100 000 adults (95% CI, 0.03-0.10 death per 100 000 adults; P = .001). In subgroup analyses, greater increases in mortality rates were found for older vs younger adults (0.19 death per 100 000 individuals; 95% CI, 0.04-0.34 death per 100 000 individuals), male vs female adults (0.12 death per 100 000 individuals; 95% CI, 0.05-0.18 death per 100 000 individuals), and non-Hispanic Black vs non-Hispanic White adults (0.11 death per 100 000 individuals; 95% CI, 0.02-0.20 death per 100 000 individuals). CONCLUSIONS AND RELEVANCE: These findings suggest that from 2008 to 2017, extreme heat was associated with higher all-cause mortality in the contiguous US, with a greater increase noted among older adults, men, and non-Hispanic Black individuals. Without mitigation, the projected increase in extreme heat due to climate change may widen health disparities between groups.
RATIONALE & OBJECTIVE: Extreme heat exposure is associated with multiple diseases. However, our current understanding of the specific impact of extreme heat exposure on kidney disease is limited. STUDY DESIGN: Case-crossover study. SETTING & PARTICIPANTS: 1,114,322 emergency department (ED) visits with a principal diagnosis of kidney disease were identified in New York state, 2005-2013. EXPOSURE: Extreme heat exposure was defined as when the daily temperature exceeded the 90th percentile temperature of that month during the study period in the county. OUTCOME: ED visits with a principal diagnosis of kidney disease and its subtypes (ICD-9 [International Classification of Diseases, Ninth Revision] codes 580-599, 788). ANALYTICAL APPROACH: Extreme heat exposure on the ED visit days was compared with extreme heat exposure on control days using a conditional logistic regression model, controlling for humidity, air pollutants, and holidays. The excess risk of kidney disease was calculated for a week (lag days 0-6) after extreme heat exposure during the warm season (May through September). We also stratified our estimates by sociodemographic characteristics. RESULTS: Extreme heat exposure was associated with a 1.7% (lag day 0) to 3.1% (lag day 2) higher risk of ED visits related to kidney disease; this association was stronger with a greater number of extreme heat exposure days in the previous week. The association with extreme heat exposure lasted for an entire week and was stronger in the transitional months (ie, May and September; excess rates ranged from 1.8% to 5.1%) rather than the summer months (June through August; excess rates ranged from 1.5% to 2.7%). The strength of association was greater among those with ED visits related to acute kidney injury, kidney stones, and urinary tract infections. Age and sex may modify the association between extreme heat exposure and ED visits. LIMITATIONS: Individual exposure to heat-how long people were outside or whether they had access to air conditioning-was unknown. CONCLUSIONS: Extreme heat exposure was significantly associated with a dose-dependent greater risk of ED visits for kidney disease.
BACKGROUND: Climate change is increasing the frequency and intensity of heatwaves. Prior studies associate high temperature with preterm birth. OBJECTIVES: We tested the hypotheses that acute exposure to extreme heat was associated with higher risk of live spontaneous preterm birth (≥20 and <37 completed weeks), and that risks were higher among people of colour and neighbourhoods with heat-trapping landcover or concentrated racialised economic disadvantage. METHODS: We conducted a retrospective cohort study of people giving birth between 2007 and 2011 in Harris County, Texas (Houston metropolitan area) (n = 198,013). Exposures were daily ambient apparent temperature (AT(max) in 5°C increments) and dry-bulb temperatures (T(max) and T(min) >historical [1971-2000] summertime 99(th) percentile) up to a week prior for each day of pregnancy. Survival analysis controlled for individual-level risk factors, secular and seasonal trends. We considered race/ethnicity, heat-trapping neighbourhood landcover and Index of Concentration at the Extremes as effect modifiers. RESULTS: The frequency of preterm birth was 10.3%. A quarter (26.8%) of people were exposed to AT(max) ≥40°C, and 22.8% were exposed to T(max) and T(min) >99(th) percentile while at risk. The preterm birth rate among the exposed was 8.9%. In multivariable models, the risk of preterm birth was 15% higher following extremely hot days (hazard ratio [HR] 1.15 (95% confidence interval [CI] 1.01, 1.30) for AT(max) ≥40°C vs. <20°C; HR 1.15 (95% CI 1.02, 1.28) for T(max) and T(min) >99(th) percentile). Censoring at earlier gestational ages suggested stronger associations earlier in pregnancy. The risk difference associated with extreme heat was higher in neighbourhoods of concentrated racialised economic disadvantage. CONCLUSIONS: Ambient heat was associated with spontaneous preterm birth, with stronger associations earlier in pregnancy and in racially and economically disadvantaged neighbourhoods, suggesting climate change may worsen existing social inequities in preterm birth rates.
BACKGROUND: Previous extreme heat and human health studies have investigated associations either over time (e.g. case-crossover or time series analysis) or across geographic areas (e.g. spatial models), which may limit the study scope and regional variation. Our study combines a case-crossover design and spatial analysis to identify: 1) the most vulnerable counties to extreme heat; and 2) demographic and socioeconomic variables that are most strongly and consistently related to heat-sensitive health outcomes (cardiovascular disease, dehydration, heat-related illness, acute renal disease, and respiratory disease) across 67 counties in the state of Florida, U. S over 2008-2012. METHODS: We first used a case-crossover design to examine the effects of air temperature on daily counts of health outcomes. We employed a time-stratified design with a 28-day comparison window. Referent periods were extracted from ±7, ±14, or ± 21 days to address seasonality. The results are expressed as odds ratios, or the change in the likelihood of each health outcome for a unit change in heat exposure. We then spatially examined the case-crossover extreme heat and health odds ratios and county level demographic and socioeconomic variables with multiple linear regression or spatial lag models. RESULTS: Results indicated that southwest Florida has the highest risks of cardiovascular disease, dehydration, acute renal disease, and respiratory disease. Results also suggested demographic and socioeconomic variables were significantly associated with the magnitude of heat-related health risk. The counties with larger populations working in farming, fishing, mining, forestry, construction, and extraction tended to have higher risks of dehydration and acute renal disease, whereas counties with larger populations working in installation, maintenance, and repair workers tended to have lower risks of cardiovascular, dehydration, acute renal disease, and respiratory disease. Finally, our results showed that high income counties consistently have lower health risks of dehydration, heat-related illness, acute renal disease, and respiratory disease. CONCLUSIONS: Our study identified different relationships with demographic/socioeconomic variables for each heat-sensitive health outcome. Results should be incorporated into vulnerability or risk indices for each health outcome.
The effects of heat waves on traffic collisions require investigation to improve traffic safety during extreme heat events. A time-stratified case-crossover design was used to examine associations between heat waves and traffic collisions in Alabama between May and September from 2009 to 2018. We derived a heat wave index, defined as the daily mean temperature greater than the 95th percentile for two or more consecutive days, by meteorological data from Phase 2 of the North American Land Data Assimilation System. We obtained traffic collision records from the Alabama Department of Transportation. A nonsignificant and negative association between traffic collisions and heat waves was noted, with a 1.4 percent decrease (95 percent confidence interval [CI] [-3.1 percent, 0.4 percent]) in traffic collisions on heat wave days compared to non-heat wave days. Similar results were found when the analysis was stratified by driver-related factors (i.e., gender, age, race, employment status, and driver residence distances), vehicle-related factors (i.e., vehicle usage), and collision-related factors (i.e., rural or urban roads, speed limits, and intersections). A significant and positive association was observed on heat wave days without precipitation, however (23.5 percent increase; 95 percent CI [7.3 percent, 42.3 percent]). In conclusion, traffic collisions were not associated with heat waves in many collision-related conditions in Alabama.
Extreme heat is one of the most important pathways illustrating the connection between climate and human health, and climate change is expected to exacerbate this public health issue. This study first used a case-crossover analysis to characterize the historical (1980-2018) association between summertime heat and non-traumatic mortality in Washington State. A separate analysis was conducted for each of the state’s ten climate divisions to produce distinct exposure-response curves expressing odds of mortality as a function of humidex. Stratified analyses were used to assess the impact of age, sex, race/ethnicity, and select causes of death, and the reported results are pooled across all divisions using meta-analysis. The historical heat-mortality relationship was combined with climate projections to estimate the impact of climate change on heat-related deaths in 2030, 2050, and 2080 under two warming scenarios. The odds ratio (OR) and 95% confidence intervals of mortality at the 99th percentile of humidex compared to the 50th percentile did not include the null value in four climate divisions (E Olympic Cascade Foothills, NE Olympic San Juan, Northeastern, and Puget Sound Lowlands). The statewide odds of mortality are 8% higher (6%, 10%) on 99th percentile days compared to 50th percentile days, driven primarily by an OR of 1.09 (1.06, 1.11) in the Puget Sound Lowlands. Risk is higher for women than men and for Blacks than Whites. Risk increases with age and for diabetic, circulatory, cardiovascular, ischemic, cerebrovascular, and respiratory deaths. The 95% confidence intervals of projected heat-attributable mortality did not overlap with zero in three climate divisions (E Olympic Cascade Foothills, NE Olympic San Juan, and Puget Sound Lowlands). In these three divisions, the average percent increase in heat-attributable mortality across both warming scenarios is 35%, 35%, and 603% in 2030, 2050, and 2080, respectively. This research is the most extensive study of heat-related mortality in Washington to date and can help inform public health initiatives aiming to improve present and future health outcomes in the state.
The earth is rapidly warming, driven by increasing atmospheric carbon dioxide and other gases that result primarily from fossil fuel combustion. In addition to causing arctic ice melting and extreme weather events, climatologic factors are linked strongly to the transmission of many infectious diseases. Changes in the prevalence of infectious diseases not only reflect the impacts of temperature, humidity, and other weather-related phenomena on pathogens, vectors, and animal hosts but are also part of a complex of social and environmental factors that will be affected by climate change, including land use, migration, and vector control. Vector- and waterborne diseases and coccidioidomycosis are all likely to be affected by a warming planet; there is also potential for climate-driven impacts on emerging infectious diseases and antimicrobial resistance. Additional resources for surveillance and public health activities are urgently needed, as well as systematic education of clinicians on the health impacts of climate change.
BACKGROUND: Heat warnings are issued in advance of forecast extreme heat events, yet little evidence is available regarding their effectiveness in reducing heat-related illness and death. We estimated the association of heat warnings and advisories (collectively, “alerts”) issued by the United States National Weather Service with all-cause mortality and cause-specific hospitalizations among Medicare beneficiaries aged 65 years and older in 2,817 counties, 2006-2016. METHODS: In each county, we compared days with heat alerts to days without heat alerts, matched on daily maximum heat index and month. We used conditional Poisson regression models stratified on county, adjusting for year, day of week, federal holidays, and lagged daily maximum heat index. RESULTS: We identified a matched non-heat alert day for 92,029 heat alert days in 2,817 counties, or 54.6% of all heat alert days during the study period. Contrary to expectations, heat alerts were not associated with lower risk of mortality (RR: 1.005 [95% CI: 0.997, 1.013]). However, heat alerts were associated with higher risk of hospitalization for fluid and electrolyte disorders (RR: 1.040 [95% CI: 1.015, 1.065]) and heat stroke (RR: 1.094 [95% CI: 1.038, 1.152]). Results were similar in sensitivity analyses additionally adjusting for same-day heat index, ozone, and PM(2.5). CONCLUSIONS: Our results suggest that heat alerts are not associated with lower risk of mortality but may be associated with higher rates of hospitalization for fluid and electrolyte disorders and heat stroke, potentially suggesting that heat alerts lead more individuals to seek or access care.
BACKGROUND: Typical thermoregulatory responses to elevated temperatures among healthy individuals include reduced blood pressure and perspiration. Individuals with end-stage kidney disease (ESKD) are susceptible to systemic fluctuations caused by ambient temperature changes that may increase morbidity and mortality. We investigated whether pre-dialysis systolic blood pressure (preSBP) and interdialytic weight gain (IDWG) can independently mediate the association between ambient temperature, all-cause hospital admissions (ACHA), and all-cause mortality (ACM). METHODS: The study population consisted of ESKD patients receiving hemodialysis treatments at Fresenius Medical Care facilities in Philadelphia County, PA, from 2011 to 2019 (n = 1981). Within a time-to-event framework, we estimated the association between daily maximum dry-bulb temperature (TMAX) and, as separate models, ACHA and ACM during warmer calendar months. Clinically measured preSBP and IDWG responses to temperature increases were estimated using linear mixed effect models. We employed the difference (c-c’) method to decompose total effect models for ACHA and ACM using preSBP and IDWG as time-dependent mediators. Covariate adjustments for exposure-mediator and total and direct effect models include age, race, ethnicity, blood pressure medication use, treatment location, preSBP, and IDWG. We considered lags up to two days for exposure and 1-day lag for mediator variables (Lag 2-Lag 1) to assure temporality between exposure-outcome models. Sensitivity analyses for 2-day (Lag 2-only) and 1-day (Lag 1-only) lag structures were also conducted. RESULTS: Based on Lag 2- Lag 1 temporal ordering, 1 °C increase in daily TMAX was associated with increased hazard of ACHA by 1.4% (adjusted hazard ratio (HR), 1.014; 95% confidence interval, 1.007-1.021) and ACM 7.5% (adjusted HR, 1.075, 1.050-1.100). Short-term lag exposures to 1 °C increase in temperature predicted mean reductions in IDWG and preSBP by 0.013-0.015% and 0.168-0.229 mmHg, respectively. Mediation analysis for ACHA identified significant indirect effects for all three studied pathways (preSBP, IDWG, and preSBP + IDWG) and significant indirect effects for IDWG and conjoined preSBP + IDWG pathways for ACM. Of note, only 1.03% of the association between temperature and ACM was mediated through preSBP. The mechanistic path for IDWG, independent of preSBP, demonstrated inconsistent mediation and, consequently, potential suppression effects in ACHA (-15.5%) and ACM (-6.3%) based on combined pathway models. Proportion mediated estimates from preSBP + IDWG pathways achieved 2.2% and 0.3% in combined pathway analysis for ACHA and ACM outcomes, respectively. Lag 2 discrete-time ACM mediation models exhibited consistent mediation for all three pathways suggesting that 2-day lag in IDWG and preSBP responses can explain 2.11% and 4.41% of total effect association between temperature and mortality, respectively. CONCLUSION: We corroborated the previously reported association between ambient temperature, ACHA and ACM. Our results foster the understanding of potential physiological linkages that may explain or suppress temperature-driven hospital admissions and mortality risks. Of note, concomitant changes in preSBP and IDWG may have little intermediary effect when analyzed in combined pathway models. These findings advance our assessment of candidate interventions to reduce the impact of outdoor temperature change on ESKD patients.
Background: Higher temperatures have been associated with increased stone formation and subsequent utilization of hospital resources, including inpatient admission. However, these observations have been derived from the adult population. We sought to examine if this purported association extends to the pediatric population. Methods: We used the 2016 Kids’ Inpatient Database to identify nationwide pediatric inpatient admissions related to nephrolithiasis. Temperature data from the National Oceanic and Atmospheric Administration was linked to each admission. Comparative statistics analyzed patient and admission characteristics. Multivariable logistic regression analyzed associations between stone-related admissions and temperature. As a frame of reference, this analysis was replicated using the National Inpatient Sample from 2016 to evaluate associations in the adult population. Results: Of the 2,496,257 pediatric admissions, 8453 (0.33%) were related to nephrolithiasis. Temperatures at the time of stone admission were higher than those during nonstone admission (55.9°F vs 54.8°F, p < 0.001). The stone admission group had a higher proportion of females than the nonstone admission group (64.8% vs 55.4%, p < 0.001). Stone admission was significantly associated with temperature (odds ratio [OR] 1.025 per 10°F, confidence interval [95% CI] 1.003-1.049, p = 0.03) and female gender (OR 1.097, 95% CI 1.027-1.171, p = 0.006). In the adult population, 380,520 out of 30,000,941 patients (1.3%) were admitted with a stone. The effect of temperature on stone admissions was similar to that in the pediatric population (OR 1.020, 95% CI 1.014-1.026, p < 0.001), but women were >20% less likely to be admitted for stones than men (OR 0.770, 95% CI 0.757-0.784, p < 0.001). Conclusions: Increased temperatures were associated with an increased risk of stone-related admission in both the pediatric and adult populations. Females were at increased risk for stone-related admissions during childhood, but this trend reverses in adulthood.
Heat stroke is the most severe manifestation of heat-related illnesses. Classic heat stroke (CHS), also known as passive heat stroke, occurs at rest, whereas exertional heat stroke (EHS) occurs during physical activity. EHS differs from CHS in etiology, clinical presentation, and sequelae of multi-organ dysfunction. Until recently, only models of CHS have been well established. This protocol aims to provide guidelines for a refined preclinical mouse model of EHS that is free from major limiting factors such as the use of anesthesia, restraint, rectal probes, or electric shock. Male and female C57Bl/6 mice, instrumented with core temperature (Tc) telemetric probes were utilized in this model. For familiarization with the running mode, mice undergo 3 weeks of training using both voluntary and forced running wheels. Thereafter, mice run on a forced wheel inside a climatic chamber set at 37.5 °C and 40%-50% relative humidity (RH) until displaying symptom limitation (e.g., loss of consciousness) at Tc of 42.1-42.5 °C, although suitable results can be obtained at chamber temperatures between 34.5-39.5 °C and humidity between 30%-90%. Depending on the desired severity, mice are removed from the chamber immediately for recovery in ambient temperature or remain in the heated chamber for a longer duration, inducing a more severe exposure and a higher incidence of mortality. Results are compared with sham-matched exercise controls (EXC) and/or naïve controls (NC). The model mirrors many of the pathophysiological outcomes observed in human EHS, including loss of consciousness, severe hyperthermia, multi-organ damage as well as inflammatory cytokine release, and acute phase responses of the immune system. This model is ideal for hypothesis-driven research to test preventative and therapeutic strategies that may delay the onset of EHS or reduce the multi-organ damage that characterizes this manifestation.
Workers in the electric power industry commonly perform physically demanding jobs in hot environments, which combined with the protective clothing worn, places them at risk of disease and health problems related to occupational heat stress. With climate change fueling an increase in the occurrence of hot weather, a targeted approach to heat stress management within the industry is needed. To better understand current heat management practices and identify opportunities for refinement, we conducted an exploratory survey among 33 electric utility companies operating in the United States (n = 32) and Canada (n = 1). Forty-six employees responsible for health and safety of company workers completed 26 questions assessing heat stress as a workplace hazard and heat management practices within five categories: (1) use and administration of heat stress management program; (2) surveillance of heat stress and heat strain; (3) job evaluation and heat-mitigation guidance; (4) education and training programs; and (5) treatment of heat-related illness. While a majority of the respondents (87.0%) indicated heat stress is a workplace hazard and their organization has a heat stress management program (78.3%), less than half reported performing real-time monitoring of heat stress in the workplace (47.8%) or tracking worker heat strain (19.6%) (i.e., physiological response to heat stress). However, most organizations indicated they conducted pre-job evaluations for heat stress (71.7%) and implemented an employee training program on managing heat stress (73.9%). The latter included instruction on various short- and long-term heat-mitigation guidance for workers (e.g., use of work exposure limits, hydration protocols) and the prevention (52.2%) and treatment (63.1%) of heat-related illnesses. Altogether, our survey demonstrates that although many companies employ some form of a heat management program, the basic components defining the programs vary and are lacking for some companies. To maximize worker health and safety during work in hot environments, a consensus-based approach, which considers the five basic components of a heat management program, should be employed to formulate effective practices and methodologies for creating an industry-specific heat management strategy.
OBJECTIVE: Determine compliance with and effectiveness of California regulations in reducing farmworkers’ heat-related illness (HRI) risk and identify main factors contributing to HRI. METHODS: In a cross-sectional study of Latino farmworkers, core body temperature (CBT), work rate, and environmental temperature (WBGT) were monitored over a work shift by individual ingestible thermistors, accelerometers, and weather stations, respectively. Multiple logistic modeling was used to identify risk factors for elevated CBT. RESULTS: Although farms complied with Cal/OSHA regulations, worker training of HRI prevention and hydration replacement rates were insufficient. In modeling (AOR [95% CI]) male sex (3.74 [1.22 – 11.54]), WBGT (1.22 [1.08 – 1.38]), work rate (1.004 [1.002 – 1.006]), and increased BMI (1.11 [1.10 – 1.29]) were all independently associated with elevated CBT. CONCLUSION: Risk of HRI was exacerbated by work rate and environmental temperature despite farms following Cal/OSHA regulations.
With global warming, much attention has been paid to the upper limits of human adaptability. However, the time to reach a generally accepted core temperature criterion (40.2°C) associated with heat-related illness above (uncompensable heat stress) and just below (compensable heat stress) the upper limits for heat balance remains unclear. Forty-eight (22 men/26 women; 23 ± 4 yr) subjects were exposed to progressive heat stress in an environmental chamber during minimal activity (MinAct, 159 ± 34 W) and light ambulation (LightAmb, 260 ± 55 W) in warm-humid (WH; ∼35°C, >60% RH) and hot-dry (HD; 43°C-48°C, <25% RH) environments until heat stress became uncompensable. For each condition, we compared heat storage (S) and the change in gastrointestinal temperature (ΔT(gi)) over time during compensable and uncompensable heat stress. In addition, we examined whether individual characteristics or seasonality were associated with the rate of increase in T(gi). During compensable heat stress, S was higher in HD than in WH environments (P < 0.05) resulting in a greater but more variable ΔT(gi) (P ≥ 0.06) for both metabolic rates. There were no differences among conditions during uncompensable heat stress (all P > 0.05). There was no influence of sex, aerobic fitness, or seasonality, but a larger body size was associated with a greater ΔT(gi) during LightAmb in WH (P = 0.003). The slopes of the T(gi) response during compensable (WH: MinAct, 0.06, LightAmb, 0.09; HD: MinAct, 0.12, LightAmb, 0.15°C/h) and uncompensable (WH: MinAct, 0.74, LightAmb, 0.87; HD: MinAct, 0.71, LightAmb, 0.93°C/h) heat stress can be used to estimate the time to reach a target core temperature from any given starting value.NEW & NOTEWORTHY This study is the first to examine heat storage and the rate of change in core temperature above (uncompensable heat stress) and just below (compensable heat stress) critical environmental limits to human heat balance. Furthermore, we examine the influence of individual subject characteristics and seasonality on the change in core temperature in warm-humid versus hot-dry environments. We provide the rate of change in core temperature, enabling projections to be made to and from any hypothetical core temperature.
In the United States, there is a growing interest in understanding heat stress in lower-income and racially isolated neighborhoods. This study spatially identifies heat-vulnerable neighborhoods, evaluates the relationship between race/ethnicity and temperature exposure, and emphasizes differences among Hispanics by origin to capture environmental injustices in Santa Clara County (SCC), CA. The current methodology uses Landsat 8 via Google Earth Engine to measure the Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) to assess the physical environment. The human environment is evaluated using the Modified Darden-Kamel Composite Socioeconomic Index to determine the spatial variability of socioeconomic status (SES) and the Index of Dissimilarity to determine the level of segregation between Hispanics and non-Hispanic Whites and among Hispanics/Latinos. The combination of these assessments comprises a comprehensive human-environment approach for health exposure evaluation by which to define environmental injustice. Results reveal socioeconomic inequalities and an uneven residential distribution between Hispanics and non-Hispanic Whites. Low NDVI and high LST values were found in Mexican neighborhoods, implying possible environmental racism. Almost half the Mexican population lives in highly segregated neighborhoods with low and very low SES, mainly located in East San Jose, where, historically, they have been ghettoized. Mexicans, in general, could be at a higher risk of heat stress and heat mortality during heat waves. Future work should examine additional variables (e.g., housing characteristics, crime, social cohesion, and collective behaviors) to comprehensively evaluate the at-risk Mexican population.
An urban atmospheric modeling study was undertaken with the goal of informing the development of a heat-mitigation plan for the greater Sacramento Valley, California. Realistic levels of mitigation measures were characterized and ranked in terms of their effectiveness in producing urban cooling under current conditions and future climate and land use. An urban heat-island index was computed for current and future climates based on each location’s time-varying upwind temperature reference points and its hourly temperatures per coincident wind direction. For instance, the UHII for the period 16-31 July 2015, for all-hours averaged temperature equivalent (i.e., degrees C center dot h hr(-1)), ranged from 1.5 to 4.7 degrees C across the urban areas in the region. The changes in local microclimates corresponding to future conditions were then quantified by applying a modified high-resolution urban meteorology model in dynamically downscaling a climate model along with future urbanization and land use change projections for each area. It was found that the effects of urbanization were of the same magnitude as that of the local climate change. Considering the urban areas in the region and the selected emissions scenarios, the all-hours temperature equivalent of the UHII (degrees C center dot h hr(-1)) increased by between 0.24 and 0.80 degrees C, representing an increase of between 17% and 13% of their respective values in the current climate. Locally, instantaneous (e.g., hourly) temperatures could increase by up to similar to 3 degrees C because of climate effects and up to similar to 5 degrees C because of both climate and urbanization changes. The efficacies of urban heat mitigation measures were ranked both at the county level and at local project scales. It was found that urban cooling measures could help decrease or offset exceedances in the National Weather Service heat index (NWS HI) above several warning thresholds and reduce the number of heatwave or excessive heat event days. For example, measures that combine increased albedo and urban forests can reduce the exceedances above NWS HI Danger level by between 50% and 100% and the exceedances above Extreme Caution level by between 18% and 36%. UHII offsets from each mitigation measure were quantified for two situations: (1) a scenario where a community implements cooling measures and no other nearby communities take any action and (2) a scenario where both the community and its upwind neighbors implement cooling measures. In this second situation, the community benefits from cooler air transported from upwind areas in addition to the local cooling resulting from implementation of its own heat mitigation strategies. The modeling of future climates showed that except for a number of instances, the ranking of measures in each respective urban area remains unchanged into the future.
Little is known about the separate and combined influences of humidity conditions, sex, and aerobic fitness on heat tolerance in unacclimatized males and females. The purpose of the current study was to describe heat tolerance, in terms of critical WBGT (WBGT(crit)), in unacclimatized young males and females in hot-dry (HD) and warm-humid (WH) environments. Eighteen subjects (9 M/9F; 21 ± 2 yr) were tested during exercise at 30% V̇O(2max) in a controlled environmental chamber. Progressive heat stress exposures were performed with either (1) constant dry-bulb temperature (T(db)) of 34 and 36 °C and increasing ambient water vapor pressure (P(a)) (P(crit) trials; WH); or (2) constant P(a) of 12 and 16 mmHg and increasing T(db) (T(crit) trials; HD). Chamber T(db) and P(a), and subject esophageal temperature (T(es)), were continuously monitored throughout each trial. After a 30-min equilibration period, progressive heat stress continued until subject heat balance could no longer be maintained and a clear rise in T(es) was observed. Absolute WBGT(crit) and WBGT(crit) adjusted to a metabolic rate of 300 W (WBGT(300)), and the difference between WBGT(crit) and occupational exposure limits (OEL; ΔOEL) was assessed. WBGT(crit), WBGT(300), and ΔOEL were higher in WH compared to HD (p < 0.0001) for females but were the same between environments for males (p ≥ 0.21). WBGT(crit) was higher in females compared to males in WH (p < 0.0001) but was similar between sexes in HD (p = 0.44). When controlling for metabolic rate, WBGT(300) and ΔOEL were higher in males compared to females in WH and HD (both p < 0.0001). When controlling for sex, V̇O(2max) was not associated with WBGT(300) or ΔOEL for either sex (r ≤ 0.12, p ≥ 0.49). These findings suggest that WBGT(crit) is higher in females compared to males in WH, but not HD, conditions. Additionally, the WBGT(crit) is lower in females, but not males, in HD compared to WH conditions.
Wearable sensors have been used to collect information on individual exposure to excessive heat and humidity. To date, no consistent diurnal classification method has been established, potentially resulting in missed opportunities to understand personal diurnal patterns in heat exposure. Using individually experienced temperatures (IET) and heat indices (IEHI) collected in the southeastern United States, this work aims to determine whether current methods of classifying IETs and IEHIs accurately characterize “day,” which is typically the warmest conditions, and “night,” which is typically the coolest conditions. IET and IEHI data from four locations were compared with the closest hourly weather station. Different day/night classifications were compared to determine efficacy. Results indicate that diurnal IET and IEHI ranges are higher than fixed-site ranges. Maximum IETs and IEHIs are warmer and occur later in the day than ambient conditions. Minimum IETs are lower and occur earlier in the day than at weather stations, which conflicts with previous assumptions that minimum temperatures occur at night. When compared to commonly used classification methods, a method of classifying day and night based on sunrise and sunset times best captured the occurrence of maximum IETs and IEHIs. Maximum IETs and IEHIs are often identified later in the evening, while minimum IETs and IEHIs occur throughout the day. These findings support future research focusing on nighttime heat exposure, which can exacerbate heat-related health issues, and diurnal patterns of personal exposure throughout the entire day as individual patterns do not necessarily follow the diurnal pattern seen in ambient conditions.
This study characterized associations between annually scaled thermal indices and annual heat stress illness (HSI) morbidity outcomes, including heat stroke and heat exhaustion, among active-duty soldiers at ten Continental U.S. (CONUS) Army installations from 1991 to 2018. We fit negative binomial models for 3 types of HSI morbidity outcomes and annual indices for temperature, heat index, and wet-bulb globe temperature (WBGT), adjusting for installation-level effects and long-term trends in the negative binomial regression models using block-bootstrap resampling. Ambulatory (out-patient) and reportable event HSI outcomes displayed predominately positive association patterns with the assessed annual indices of heat, whereas hospitalization associations were mostly null. For example, a one-degree Fahrenheit (°F) (or 0.55°C) increase in mean temperature between May and September was associated with a 1.16 (95% confidence interval [CI]: 1.11, 1.29) times greater rate of ambulatory encounters. The annual-scaled rate ratios and their uncertainties may be applied to climate projections for a wide range of thermal indices to estimate future military and civilian HSI burdens and impacts to medical resources.
OBJECTIVE: The aim of this study was to model the effect of body armor coverage on body core temperature elevation and wet-bulb globe temperature (WBGT) offset. BACKGROUND: Heat stress is a critical factor influencing the health and safety of military populations. Work duration limits can be imposed to mitigate the risk of exertional heat illness and are derived based on the environmental conditions (WBGT). Traditionally a 3°C offset to WBGT is recommended when wearing body armor; however, modern body armor systems provide a range of coverage options, which may influence thermal strain imposed on the wearer. METHOD: The biophysical properties of four military clothing ensembles of increasing ballistic protection coverage were measured on a heated sweating manikin in accordance with standard international criteria. Body core temperature elevation during light, moderate, and heavy work was modeled in environmental conditions from 16°C to 34°C WBGT using the heat strain decision aid. RESULTS: Increasing ballistic protection resulted in shorter work durations to reach a critical core temperature limit of 38.5°C. Environmental conditions, armor coverage, and work intensity had a significant influence on WBGT offset. CONCLUSION: Contrary to the traditional recommendation, the required WBGT offset was >3°C in temperate conditions (<27°C WBGT), particularly for moderate and heavy work. In contrast, a lower WBGT offset could be applied during light work and moderate work in low levels of coverage. APPLICATION: Correct WBGT offsets are important for enabling adequate risk management strategies for mitigating risks of exertional heat illness.
PURPOSE: To mitigate rises in core temperature >1°C, the American Conference of Governmental Industrial Hygienists (ACGIH) recommends upper limits for heat stress (action limit values [ALV]), defined by wet-bulb globe temperature (WBGT) and a worker’s metabolic rate. However, these limits are based on data from young men and are assumed to be suitable for all workers, irrespective of age or health status. We therefore explored the effect of aging, type 2 diabetes (T2D), and hypertension (HTN) on tolerance to prolonged, moderate-intensity work above and below these limits. METHODS: Core temperature and heart rate were assessed in healthy, heat unacclimatized young (18-30 yr, n = 13) and older (50-70 yr) men (n = 14) and heat unacclimatized older men with T2D (n = 10) or HTN (n = 13) during moderate-intensity (metabolic rate: 200 W·m-2) walking for 180 min (or until termination) in environments above (28°C and 32°C WBGT) and below (16°C and 24°C WBGT) the ALV for continuous work at this intensity (25°C WBGT). RESULTS: Work tolerance in the 32°C WBGT was shorter in men with T2D (median [IQR]; 109 [91-173] min; P = 0.041) and HTN (120 [65-170] min; P = 0.010) compared with healthy older men (180 [133-180] min). However, aging, T2D, and HTN did not significantly influence (i) core temperature or heart rate reserve, irrespective of WBGT; (ii) the probability that core temperature exceeded recommended limits (>1°C) under the ALV; and (iii) work duration before core temperature exceeded recommended limits (>1°C) above the ALV. CONCLUSION: These findings demonstrate that T2D and HTN attenuate tolerance to uncompensable heat stress (32°C WBGT); however, these chronic diseases do not significantly impact thermal and cardiovascular strain, or the validity of ACIGH recommendations during moderate-intensity work.
Heat waves are the deadliest weather-related hazard in the United States while also increasing in frequency, intensity, and duration. Population growth is also occurring in places most exposed to extreme heat. Current US National Weather Service (NWS) guidelines to issue heat alerts vary geographically and may not facilitate optimal heat risk communication. This study focuses on professionals’ decision making and communication in the context of extreme heat risk in Utah, a state with historically low but increasing heat risk due to climate change, a growing population, and rising outdoor recreation visitation. We analyze the mental models of decision-makers responsible for forecasting, communicating, and managing heat risk in Utah using interviews with 32 weather forecasters, media broadcasters, and public officials including park managers. Results demonstrate that institutional norms have influenced how forecasters characterize extreme heat in the western region of the US. NWS heat alerts and tools are new and unfamiliar to many decision-makers, especially in areas of the state where previous criteria did not warrant alerts. Only 44% of participants from these areas were familiar with NWS heat alerts compared to 100% of participants from areas with a history of heat events. While experience with NWS heat alerts and tools varied widely among participants, 100% were familiar with heat protective behaviors. 94% stated they had personally experienced extreme heat and 66% stated that this experience influenced their decisions. Personal experience may be an effective means to communicate heat risk and promote adaptive practices. These insights may be generalizable to other settings where risk is changing and communication strategies are underdeveloped.
Extreme heat puts tremendous stress on human health and limits people’s ability to work, travel, and socialize outdoors. To mitigate heat in public spaces, thermal conditions must be assessed in the context of human exposure and space use. Mean Radiant Temperature (MRT) is an integrated radiation metric that quantifies the total heat load on the human body and is a driving parameter in many thermal comfort indices. Current sensor systems to measure MRT are expensive and bulky (6-directional setup) or slow and inaccurate (globe thermometers) and do not sense space use. This engineering systems paper introduces the hardware and software setup of a novel, low-cost thermal and visual sensing device (MaRTiny). The system collects meteorological data, concurrently counts the number of people in the shade and sun, and streams the results to an Amazon Web Services (AWS) server. MaRTiny integrates various micro-controllers to collect weather data relevant to human thermal exposure: air temperature, humidity, wind speed, globe temperature, and UV radiation. To detect people in the shade and Sun, we implemented state of the art object detection and shade detection models on an NVIDIA Jetson Nano. The system was tested in the field, showing that meteorological observations compared reasonably well to MaRTy observations (high-end human-biometeorological station) when both sensor systems were fully sun-exposed. To overcome potential sensing errors due to different exposure levels, we estimated MRT from MaRTiny weather observations using machine learning (SVM), which improved RMSE. This paper focuses on the development of the MaRTiny system and lays the foundation for fundamental research in urban climate science to investigate how people use public spaces under extreme heat to inform active shade management and urban design in cities.
PURPOSE: This study examines risk factors for heat-related mortality due to hyperthermia in emergency department patients, a vulnerable population. METHODS: This matched case-control study used statewide, longitudinally linked emergency department (ED) data and death records from California. Cases comprised California residents (≥18 years) who presented to a state-licensed ED and died of hyperthermia during the study period (2009-2012). For each case, up to five ED patients were randomly selected as live controls and matched on sex and age. Patients’ demographic characteristics and history of ED utilization for alcohol use, drug use, psychiatric disorders, heart-related conditions, chronic respiratory disease, neurodegenerative disorders, and cerebrovascular disease were assessed in relationship to hyperthermia mortality. RESULTS: Using multivariate conditional logistic regression models, hyperthermia mortality cases had higher odds of prior ED utilization for alcohol use (OR = 11.16, 95% CI = 3.87, 32.17) compared to controls. Cases were also more likely than controls to have Medicare insurance (OR = 5.80, 95% CI = 1.70, 15.15) or self-pay (OR = 5.39, 95% CI = 1.73, 16.79), at their most recent ED visit. CONCLUSIONS: ED patients presenting with alcohol problems may face increased risk of hyperthermia mortality. To help reduce heat-related mortality, EDs should consider interventions that target patients vulnerable to heat exposure.
BACKGROUND: The effect of heatwaves on adverse birth outcomes is not well understood and may vary by how heatwaves are defined. The study aims to examine acute associations between various heatwave definitions and preterm and early-term birth. METHODS: Using national vital records from 50 metropolitan statistical areas (MSAs) between 1982 and 1988, singleton preterm (< 37 weeks) and early-term births (37-38 weeks) were matched (1:1) to controls who completed at least 37 weeks or 39 weeks of gestation, respectively. Matching variables were MSA, maternal race, and maternal education. Sixty heatwave definitions including binary indicators for exposure to sustained heat, number of high heat days, and measures of heat intensity (the average degrees over the threshold in the past 7 days) based on the 97.5(th) percentile of MSA-specific temperature metrics, or the 85(th) percentile of positive excessive heat factor (EHF) were created. Odds ratios (OR) for heatwave exposures in the week preceding birth (or corresponding gestational week for controls) were estimated using conditional logistic regression adjusting for maternal age, marital status, and seasonality. Effect modification by maternal education, age, race/ethnicity, child sex, and region was assessed. RESULTS: There were 615,329 preterm and 1,005,576 early-term case-control pairs in the analyses. For most definitions, exposure to heatwaves in the week before delivery was consistently associated with increased odds of early-term birth. Exposure to more high heat days and more degrees above the threshold yielded higher magnitude ORs. For exposure to 3 or more days over the 97.5(th) percentile of mean temperature in the past week compared to zero days, the OR was 1.027 for early-term birth (95%CI: 1.014, 1.039). Although we generally found null associations when assessing various heatwave definitions and preterm birth, ORs for both preterm and early-term birth were greater in magnitude among Hispanic and non-Hispanic black mothers. CONCLUSION: Although associations varied across metrics and heatwave definitions, heatwaves were more consistently associated with early-term birth than with preterm birth. This study's findings may have implications for prevention programs targeting vulnerable subgroups as climate change progresses.
OBJECTIVE: Schools with aging infrastructure may expose students to extreme temperatures. Extreme outdoor temperatures have previously been linked to more asthma-related health care utilization. Explore the relationship between classroom temperatures and school-based health care visits for asthma in an urban school building with an outdated heating and cooling system. METHODS: Participants were students in grades K-8 who received health care from a school-based health center (SBHC) (n = 647) or school nurse (n = 1244) in 2 co-located urban public schools between 2016 and 2018. The probability of an asthma visit to the SBHC or school nurse was modeled as a function of indoor temperature exposure using generalized estimating equations with covariates accounting for grade, sex, outdoor temperature, days at risk of asthma visit, nonasthma visits, month, and year fixed effects. RESULTS: Classroom temperatures ranged from 48.0 °F to 100.6 °F. Higher mean grade-level indoor temperatures from a baseline of approximately 70 °F to 76 °F were associated with increased rates of asthma-related visits to the SBHC or school nurse on same day of exposure. Model-generated estimates suggest that an increase of 10 degrees F in indoor temperature relative to a baseline of 75 °F was associated with a 53% increase in the rate of asthma-related SBHC visits. CONCLUSIONS: Elevated classroom temperatures may be associated with more school-based health care utilization for asthma. Low-income and students from racial and ethnic minority groups have disproportionately higher rates of asthma and are also more likely to attend schools with poor infrastructure. The potential benefits of school infrastructure investments for student health, health care costs, and health equity merit further investigation.
Objectives. To determine the effect of heat waves on emergency department (ED) visits for individuals experiencing homelessness and explore vulnerability factors. Methods. We used a unique highly detailed data set on sociodemographics of ED visits in San Diego, California, 2012 to 2019. We applied a time-stratified case-crossover design to study the association between various heat wave definitions and ED visits. We compared associations with a similar population not experiencing homelessness using coarsened exact matching. Results. Of the 24 688 individuals identified as experiencing homelessness who visited an ED, most were younger than 65 years (94%) and of non-Hispanic ethnicity (84%), and 14% indicated the need for a psychiatric consultation. Results indicated a positive association, with the strongest risk of ED visits during daytime (e.g., 99th percentile, 2 days) heat waves (odds ratio = 1.29; 95% confidence interval = 1.02, 1.64). Patients experiencing homelessness who were younger or elderly and who required a psychiatric consultation were particularly vulnerable to heat waves. Odds of ED visits were higher for individuals experiencing homelessness after matching to nonhomeless individuals based on age, gender, and race/ethnicity. Conclusions. It is important to prioritize individuals experiencing homelessness in heat action plans and consider vulnerability factors to reduce their burden. (Am J Public Health. 2022;112(1):98-106. https://doi.org/10.2105/AJPH.2021.306557).
Elevated air temperatures in urban neighborhoods due to the Urban Heat Island effect is a form of heat pollution that causes thermal discomfort, higher energy consumption, and deteriorating public health. Mitigation measures can be expensive, with the need to maximize benefits from limited resources. Here we show that significant mitigation can be achieved through a limited application of reflective surfaces. We use a Computational Fluid Dynamics model to resolve the air temperature within a prototypical neighborhood for different wind directions, building configurations, and partial application of reflective surfaces. While reflective surfaces mitigate heat pollution, their effectiveness relative to cost varies with spatial distribution. Although downstream parts experience the highest heat pollution, applying reflective surfaces to the upstream part has a disproportionately higher benefit relative to cost than applying them downstream.
Heat-related illness is a spectrum of conditions progressing from heat exhaustion, heat injury, to life-threatening heat stroke. Heat stroke is a clinical constellation of symptoms that include a severe elevation in body temperature which typically, but not always, is greater than 40°C. Also, there must be clinical signs of central nervous system dysfunction that may include ataxia, delirium, or seizures, in the setting of exposure to hot weather or strenuous physical exertion. Risk factors include environmental variables, medications, drug use, and other medical comorbidities.
The potential for critical infrastructure failures during extreme weather events is rising. Major electrical grid failure or “blackout” events in the United States, those with a duration of at least 1 h and impacting 50,000 or more utility customers, increased by more than 60% over the most recent 5 year reporting period. When such blackout events coincide in time with heat wave conditions, population exposures to extreme heat both outside and within buildings can reach dangerously high levels as mechanical air conditioning systems become inoperable. Here, we combine the Weather Research and Forecasting regional climate model with an advanced building energy model to simulate building-interior temperatures in response to concurrent heat wave and blackout conditions for more than 2.8 million residents across Atlanta, Georgia; Detroit, Michigan; and Phoenix, Arizona. Study results find simulated compound heat wave and grid failure events of recent intensity and duration to expose between 68 and 100% of the urban population to an elevated risk of heat exhaustion and/or heat stroke.
Extreme heat is a major threat to human health worldwide. The COVID-19 pandemic, with its complexity and global reach, created unprecedented challenges for public health and highlighted societal vulnerability to hazardous hot weather. In this study, we used data from a three-wave nationally representative survey of 3036 American adults to examine how the COVID-19 pandemic affected extreme heat vulnerability during the summer of 2020. We used mixed effects models to examine the roles of socio-demographic characteristics and pandemic-related factors in the distribution of negative heat effects and experiences across the United States. The survey findings show that over a quarter of the US population experienced heat-related symptoms during the summer of 2020. Mixed effects models demonstrate that among all socio-economic groups, those who were most vulnerable were women, those in low-income households, unemployed or on furlough, and people who identify as Hispanic or Latino or as other non-white census categories (including Asian, American Indian or Alaska Native, Native Hawaiian or other Pacific Islander, and multi-racial US residents). The study findings indicate that millions of people in the US had difficulty coping with or responding to extreme heat because of the direct and indirect effects of the COVID-19 pandemic. Limited access to cooling as well as COVID-19 related social isolation played a major role in adverse heat health effects. Geographically, the South and the West of the US stood out in terms of self-reported negative heat effects. Overall, the study suggests that the intersection of two health hazards-extreme heat and coronavirus SARS-CoV2-amplified existing systemic vulnerabilities and expanded the demographic range of people vulnerable to heat stress.
Exposure to high temperatures is detrimental to human health. As climate change is expected to increase the frequency of extreme heat events, and raise ambient temperatures, an investigation into the trend of heat-related emergency department (ED) visits over the past decade is necessary to assess the human health impact of this growing public health crisis. ED visits were examined using the Nationwide Emergency Department Sample. Visits were included if the diagnostic field contained an ICD-9-CM or ICD-10-CM code specific to heat-related emergency conditions. Weighted counts were generated using the study design and weighting variables, to estimate the national burden of heat-related ED visits. A total of 1,078,432 weighted visits were included in this study. The annual incidence rate per 100,000 population increased by an average of 2.85% per year, ranging from 18.21 in 2009, to 32.34 in 2018. The total visit burden was greatest in the South (51.55%), with visits increasing to the greatest degree in the Midwest (8.52%). ED visit volume was greatest in July (29.79%), with visits increasing to the greatest degree in July (15.59%) and March (13.18%). An overall increase in heat-related ED visits for heat-related emergency conditions was found during the past decade across the United States, affecting patients in all regions and during all seasons.
Efforts to understand the complex, multidimensional nature of environmental vulnerability can generate new knowledge by deploying a convergence research framework within a community-engaged approach. We explore the benefits and shortcomings of what we call engaged convergence research (ECR) by narrating a case study that uncovered a pattern of indoor heat-related deaths that was previously unexplained: Although only 5 percent of Maricopa County, Arizona, residents live in mobile homes, residents of mobile homes account for 29 percent of indoor heat-related deaths. Exploring the multiplicative threats of economic precarity, population sensitivity to environmental exposure, site, and shelter type, we recharacterize the reality faced by mobile home dwellers to find them falling between the cracks of available heat resilience options. Beyond contributing to scholarship on indoor heat-related deaths, we demonstrate the potential for novel and actionable insights emerging from ECR. We also elucidate some of the challenges faced when enlisting community actors as coproducers of knowledge in geographic research.
Climate change is known to increase the frequency and intensity of hot days (daily maximum temperature ≥30°C), both globally and locally. Exposure to extreme heat is associated with numerous adverse human health outcomes. This study estimated the burden of heat-related illness (HRI) attributable to anthropogenic climate change in North Carolina physiographic divisions (Coastal and Piedmont) during the summer months from 2011 to 2016. Additionally, assuming intermediate and high greenhouse gas emission scenarios, future HRI morbidity burden attributable to climate change was estimated. The association between daily maximum temperature and the rate of HRI was evaluated using the Generalized Additive Model. The rate of HRI assuming natural simulations (i.e., absence of greenhouse gas emissions) and future greenhouse gas emission scenarios were predicted to estimate the HRI attributable to climate change. Over 4 years (2011, 2012, 2014, and 2015), we observed a significant decrease in the rate of HRI assuming natural simulations compared to the observed. About 3 out of 20 HRI visits are attributable to anthropogenic climate change in Coastal (13.40% [IQR: -34.90,95.52]) and Piedmont (16.39% [IQR: -35.18,148.26]) regions. During the future periods, the median rate of HRI was significantly higher (78.65%: Coastal and 65.85%: Piedmont), assuming a higher emission scenario than the intermediate emission scenario. We observed significant associations between anthropogenic climate change and adverse human health outcomes. Our findings indicate the need for evidence-based public health interventions to protect human health from climate-related exposures, like extreme heat, while minimizing greenhouse gas emissions.
Exposure to extreme heat is a known risk factor that is associated with increased heat-related illness (HRI) outcomes. The relevance of heat wave definitions (HWDs) could change across health conditions and geographies due to the heterogenous climate profile. This study compared the sensitivity of 28 HWDs associated with HRI emergency department visits over five summer seasons (2011−2016), stratified by two physiographic regions (Coastal and Piedmont) in North Carolina. The HRI rate ratios associated with heat waves were estimated using the generalized linear regression framework assuming a negative binomial distribution. We compared the Akaike Information Criterion (AIC) values across the HWDs to identify an optimal HWD. In the Coastal region, HWDs based on daily maximum temperature with a threshold > 90th percentile for two or more consecutive days had the optimal model fit. In the Piedmont region, HWD based on the daily minimum temperature with a threshold value > 90th percentile for two or more consecutive days was optimal. The HWDs with optimal model performance included in this study captured moderate and frequent heat episodes compared to the National Weather Service (NWS) heat products. This study compared the HRI morbidity risk associated with epidemiologic-based HWDs and with NWS heat products. Our findings could be used for public health education and suggest recalibrating NWS heat products.
The Army Heat Center at Fort Benning, GA was established to identify and disseminate best practices for the prevention, field care, evacuation, hospital care, and return to duty of exertional heat casualties. During the 2017-2021 surveillance period, there were 1,911 heat casualties treated at Ft. Benning’s Martin Army Community Hospital. Most patients were junior enlisted and officer personnel who were engaged in initial entry training. Heat exhaustion, heat injury, heat stroke, and hyponatremia accounted for 52.6%, 18.4%, 18.2%, and 2.0% of total heat illnesses, respectively. The annual proportion of heat casualties that were due to heat exhaustion rose steadily during the surveillance period, reaching 77.7% in 2021, while the incidence of heat injury and heat stroke did not increase during this period. Data are presented on the occurrence of clusters of heat illness, the association of cases of heat stroke with arduous physical activities, and the seasonal variation in incidence of heat illnesses. It is important that unit leaders and trainers understand the risk factors for heat illness among those being trained and that early first aid measures be employed in the field (especially rapid cooling).
OBJECTIVES: To understand how health departments implemented the response to the dual hazards of Heat Related Illness (HRI) and COVID-19 in Summer 2020. METHODS: We interviewed five health jurisdictions with a Building Resilience Against Climate Effects (BRACE) Framework HRI project to understand impacts to organizational roles and preparedness activities, capacity to respond to the heat season, challenges experienced with resources and personnel, and how partners influenced their capacity to respond to dual hazards. RESULTS: Health jurisdictions working in both heat preparedness and on the COVID-19 response highlighted three components as integral to maintaining public health capacity throughout the pandemic: 1) adapting to changing roles and responsibilities, 2) building and strengthening inter-organizational partnerships, and 3) maintaining flexibility through cross-training as themes to maintain the public health capacity throughout the pandemic. CONCLUSIONS: With impacts of the changing climate, including resultant extreme events with subsequent public health impacts, simultaneous responses are likely to arise again in the future. Developing cross-training programs, fostering flexibility and adaptability within the workforce, and building and sustaining external partnerships can support health departments anticipating the need to respond to simultaneous public health hazards in the future.
BACKGROUND: Agricultural workers are disproportionately at risk for heat-related morbidity and mortality. The purpose of this study was to explore how sociocultural and occupational factors, and environmental heat stress influenced fluid intake and hydration status among Latino farmworkers working in eastern North Carolina. METHODS: A community-informed, mixed methods research study was conducted in partnership with staff at a federally qualified health center. In summer 2020, we recruited Latino farmworkers at migrant camps. Twenty-eight male, migrant farmworkers participated in focus group discussions and 30 completed surveys and provided urine specimens. Wet bulb globe temperatures were measured in fields where workers labored. Content analysis and parametric analyses were performed. Data integration was completed using a meta-matrix. RESULTS: Prior to work, 46.7% of farmworkers’ urine specific gravity measurements indicated dehydration, which increased to 100% after work. The farmworkers spent between 2 and 7.5 hours of their day working in conditions above the recommended limits for workplace heat exposure. Farmworkers described exposure to extreme heat and inconsistent occupational policy compliance. Farmworkers expressed the opportunity to drink water but accessibility and poor water quality limited hydration. The integrated data supported congruent findings of extreme heat, few work breaks, and substandard housing. CONCLUSION/APPLICATION TO PRACTICE: Farmworkers are dehydrated at work, placing them at higher risk for heat-related illness (HRI). By engaging with agricultural stakeholders, occupational health nurses can combine efforts and advocate for effective health and safety work policies to reduce HRIs and deaths among farmworkers. Legislation stipulating cooling and hydration practices would support safer work environments.
In the wake of growing concern for climate change, heat waves and their potential health effects (McGeehin and Mirabelli, 2001) [37] have become a recurring phenomenon (Beniston, 2004; Fouillet et al., 2006) [8,21]. Extreme heat events in the USA are responsible for more deaths as compared to other weather events such as hurricanes, lightning, tornadoes and floods (Luber and McGeehin, 2008) [33]. Heat exposure in buildings has risen due to global warming in conjunction with other factors like urban-ization and associated heat island effects (Kolokotroni et al., 2012) [25], lack of thermal mass (Lomas and Porritt, 2017a) [31], exposure to solar insolation on higher stories, absence of window shading, over-crowding and envelope properties exacerbate the overheating inside the dwellings (Vellei et al., 2017). [45]. Stone et al. specialIntscript [43] provides a macro view of the indoor environments in buildings due to the concurrent event of power outage during heat wave in face of climate change. This paper builds on the previous publication and provides a detailed view of modeling methodology, building physics that explains the sources/sinks of heat and entails a detailed evaluation of the current building stock for the low to moderate income residences in the city of Phoenix, Arizona in terms of their thermal performance. Finite Element models of building stock were simulated using MATLAB for microclimate weather files of Phoenix generated by Weather Research and Forecasting (WRF) simulation. Significant differences in temperature were noted in same building archetypes in different pockets of the city indicating the role of urbanization in aggravating the impact of heat wave. Dwellings with high thermal mass are found to be much more resilient to high ambient temperatures as compared to code compliant residences with base-ments being the coolest zones in all prototypes. (C) 2021 Elsevier B.V. All rights reserved.
The disorders of hyperthermia, also known as heat-related injury or illness, exist on a continuum, which is marked by dysregulation of the body’s thermoregulatory capacity. This condition can vary both in presentation and in severity, from benign conditions, including heat cramps and heat edema, to life-threatening hyperthermia, also known as heatstroke. This article will discuss non-life-threatening heat-related illnesses. It is essential to be able to identify and manage these conditions appropriately as moderate hyperthermia can progress to life-threatening heatstroke. As such, including these injuries in medical decision-making, prompt identification, and appropriate treatment is important. This article will also review the epidemiology, including at-risk populations, red-flag features of patient presentations, treatment options and strategies, and preventative techniques, which all play a significant role in decreasing the morbidity, mortality, and healthcare costs associated with these injuries.
Globally, there is increasing recognition that agricultural workers are at risk for chronic kidney disease of unknown etiology (CKDu). Recurrent heat exposure, physical exertion, dehydration, muscle damage, and inflammation are hypothesized to contribute to the development of CKDu, but the relative importance of these processes and the interactions among them remain unclear. Moreover, there is a need to identify biomarkers that could distinguish individuals who are at greatest risk for kidney damage to target preventative interventions for CKDu. In this study, we evaluated dehydration and markers of inflammation, muscle damage, and renal function in agricultural workers at a non-workday baseline assessment. Urine specific gravity and kidney function were measured before and after work shifts on three subsequent days, and heat index, core body temperature, and heart rate were monitored during the work shifts. A combination of direct comparisons and machine learning algorithms revealed that reduced levels of uromodulin and sodium in urine and increased levels of interleukin-6 and C-reactive protein in serum were indicative of dehydration at baseline, and that dehydration, high body mass index, reduced urine uromodulin, and increased serum interleukin-6, C-reactive protein, and lipopolysaccharide-binding protein at baseline were predictive of acute kidney injury on subsequent workdays. Our findings suggest a method for identifying agricultural workers at greatest risk for kidney injury and reveal potential mechanisms responsible for this process, including pathways overlapping in dehydration and kidney injury. These results will guide future studies confirming these mechanisms and introducing interventions to protect kidney health in this vulnerable population.
Wet bulb temperatures (T(wet)) during extreme heat events are commonly 31°C. Recent predictions indicate that T(wet) will approach or exceed 34°C. Epidemiological data indicate that exposure to extreme heat events increases kidney injury risk. We tested the hypothesis that kidney injury risk is elevated to a greater extent during prolonged exposure to T(wet) = 34°C compared with T(wet) = 31°C. Fifteen healthy men rested for 8 h in T(wet) = 31 (0)°C and T(wet) = 34 (0)°C. Insulin-like growth factor-binding protein 7 (IGFBP7), tissue inhibitor of metalloproteinase 2 (TIMP-2), and thioredoxin 1 (TRX-1) were measured from urine samples. The primary outcome was the product of IGFBP7 and TIMP-2 ([IGFBP7·TIMP-2]), which provided an index of kidney injury risk. Plasma interleukin-17a (IL-17a) was also measured. Data are presented at preexposure and after 8 h of exposure and as mean (SD) change from preexposure. The increase in [IGFBP7·TIMP-2] was markedly greater at 8 h in the 34°C [+26.9 (27.1) (ng/mL)(2)/1,000) compared with the 31°C [+6.2 (6.5) (ng/mL)(2)/1,000] trial (P < 0.01). Urine TRX-1, a marker of renal oxidative stress, was higher at 8 h in the 34°C [+77.6 (47.5) ng/min] compared with the 31°C [+16.2 (25.1) ng/min] trial (P < 0.01). Plasma IL-17a, an inflammatory marker, was elevated at 8 h in the 34°C [+199.3 (90.0) fg/dL; P < 0.01] compared with the 31°C [+9.0 (95.7) fg/dL] trial. Kidney injury risk is exacerbated during prolonged resting exposures to T(wet) experienced during future extreme heat events (34°C) compared with that experienced currently (31°C), likely because of oxidative stress and inflammatory processes.NEW AND NOTEWORTHY We have demonstrated that kidney injury risk is increased when men are exposed over an 8-h period to a wet bulb temperature of 31°C and exacerbated at a wet bulb temperature of 34°C. Importantly, these heat stress conditions parallel those that are encountered during current (31°C) and future (34°C) extreme heat events. The kidney injury biomarker analyses indicate both the proximal and distal tubules as the locations of potential renal injury and that the injury is likely due to oxidative stress and inflammation.
Exposure to excessive heat is associated with a higher risk of death. Although the relative risk of death on extreme-heat days has decreased over the past several decades in the United States, the drivers of this decline have not been fully characterized. In particular, while extreme heat earlier in the warm season has been shown to confer greater risk of mortality than exposure later in the season, it is unknown whether this within-season variability in susceptibility has changed over time and whether it is modified by region, climatic changes, or social vulnerability. METHODS: We used distributed-lag nonlinear models and meta-regression to estimate the association between ambient maximum daily temperature during the early, late, and overall warm seasons and the relative risk of mortality for two decades, 1973-1982 and 1997-2006, in 186 metropolitan areas in the United States. We assessed changes in relative risk nationally, regionally, and between places with differential changes in early-season relative extreme heat and indicators of social vulnerability. RESULTS: Most of the reduction in heat-related mortality nationally between the two decades is driven by decreases in late-season mortality, while substantial early-season risk remains. This difference is most apparent in the Northeast, in cities with greater increases in early-season relative extreme heat, and in places that have become more socially vulnerable. CONCLUSIONS: Early-season heat mortality risks have persisted despite overall adaptations, particularly in places with greater warming and increasing social vulnerability. Interventions to reduce heat mortality may need to consider greater applicability to the early warm season.
BACKGROUND: There is a compelling need to identify agricultural workers at risk for heat related illness (HRI). METHODS: Data from Florida agricultural workers (N = 221) were collected over 3 summer workdays (2015 to 2017) to examine risk factors for exceeding NIOSH-recommended core temperature (Tc) thresholds (38 °C [Tc38] and 38.5 °C [Tc38.5]) using generalized linear mixed models. RESULTS: On an average workday, 49% of participants exceeded Tc38 and 10% exceeded Tc38.5. On average, participants first exceeded both thresholds early in the day; the Tc38 threshold mid-morning (10:38 AM), and Tc38.5 about a half hour later (11:10 AM). Risk factors associated with exceeding Tc38 included years working in US agriculture, body mass index, time performing moderate-to-vigorous physical activity, increasing heat index, and field crop work. CONCLUSIONS: The high prevalence of core temperatures exceeding recommended limits emphasizes the serious need for mandated HRI prevention programs for outdoor workers.
Among persons with high spinal cord injury (Hi-SCI: > T5), changes in core body temperature (Tcore) and cognitive performance during heat exposure appear related to degree of sympathetic interruption. Twenty men with Hi-SCI (C4-T4, American Spinal Injury Association Impairment Scale [AIS] A-B) and 19 matched, able-bodied controls were acclimated to 27°C baseline (BL) before exposure to 35°C heat challenge (HC). Two groups, differentiated by increase in Tcore during HC, were identified: high responders (HR-SCI: ΔTcore ≥0.5°C; n = 13, C4-T2) and low responders (LR-SCI: ΔTcore <0.5°C; n = 7, C4-T4). Tcore, distal skin temperatures (Tsk(avg)), and distal microvascular perfusion (LDF(both feet)) were measured, as were indices of sympathetic integrity, mean arterial pressure (MAP), and extremity sweat rate (SR(avg)). Cognitive performance was assessed at BL and post-HC, using the Stroop Color and Word and Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) Digit Span tests. At BL, Tcore of the HR-SCI group (36.6 ± 0.4°C) was lower than that for the LR-SCI (37.1 ± 0.3°C; p = 0.011) and control groups (37.3 ± 0.3°C; p < 0.001). After HC, Tcore was not different among groups. MAP of the HR-SCI group (70.9 ± 9.8 mm Hg) was lower than that of the LR-SCI (81.8 ± 7.0 mm Hg; p = 0.048) and control groups (89.9 ± 9.9 mm Hg; p < 0.001). SR(avg) increased more in the control group (77.0 ± 52.5 nL/cm(2)/min) than in the HR-SCI group (15.5 ± 22.0 nL/cm(2)/min; p = 0.001). Only the HR-SCI group had significant increases in T-Scores of Stroop Word (7.5 ± 4.4; p < 0.001), WAIS-IV Digit Span Sequence (1.9 ± 1.8; p = 0.002), and WAIS-IV Digit Span Total (1.4 ± 1.6; p = 0.008). Persons with SCI who responded to HC with a greater change in Tcore demonstrated evidence of greater sympathetic interruption and had an associated improvement in cognitive performance.
The purpose of this consensus document was to develop feasible, evidence-based occupational heat safety recommendations to protect the US workers that experience heat stress. Heat safety recommendations were created to protect worker health and to avoid productivity losses associated with occupational heat stress. Recommendations were tailored to be utilized by safety managers, industrial hygienists, and the employers who bear responsibility for implementing heat safety plans. An interdisciplinary roundtable comprised of 51 experts was assembled to create a narrative review summarizing current data and gaps in knowledge within eight heat safety topics: (a) heat hygiene, (b) hydration, (c) heat acclimatization, (d) environmental monitoring, (e) physiological monitoring, (f) body cooling, (g) textiles and personal protective gear, and (h) emergency action plan implementation. The consensus-based recommendations for each topic were created using the Delphi method and evaluated based on scientific evidence, feasibility, and clarity. The current document presents 40 occupational heat safety recommendations across all eight topics. Establishing these recommendations will help organizations and employers create effective heat safety plans for their workplaces, address factors that limit the implementation of heat safety best-practices and protect worker health and productivity.
Background: Outdoor workers are exposed to hot work environments and are at risk of heat-related morbidity and mortality. The purpose of this study was to evaluate the knowledge of migrant farmworkers about first aid for heat-related illness (HRI) symptoms. Methods: The authors recruited 60 migrant farmworkers out of 66 who were approached from vegetable farms in Georgia. They were workers who participated in the 2018 Farmworker Family Health Program (FWFHP). The authors surveyed the workers to assess demographics, prevalence of HRI symptoms, hydration practices, and knowledge of HRI first aid. Descriptive statistics for worker demographics, HRI symptoms, and hydration data were calculated, as were the percentages of correctly answered pilot questions. Findings: Of the 60 workers who chose to participate in this study, more than 50% incorrectly answered pilot questions related to their knowledge of HRI first aid. The two most common HRI symptoms reported were heavy sweating and muscle cramps. More than two thirds reported experiencing at least one HRI symptom during the workday. Mean liquid consumption within this sample was 72.95 oz per day, which is much less than the recommended 32 oz per hour. Conclusion/Application to Practice: Until larger structural change can occur to protect farmworkers, farm owners can prevent morbidity and mortality from inadequate hydration practices and working in high-heat conditions by providing migrant farmworkers with training in heat-related first aid. Appropriate heat-illness interventions should focus on first aid measures to reduce morbidity and mortality related to heat illness in farmworkers.
BACKGROUND: The burden of adverse health effects from heat exposure is substantial, and outdoor workers who perform heavy physical work are at high risk. Though heat prevention interventions have been developed, studies have not yet systematically evaluated the effectiveness of approaches that address risk factors at multiple levels. OBJECTIVE: We sought to test the effectiveness of a multi-level heat prevention approach (heat education and awareness tools [HEAT]), which includes participatory training for outdoor agricultural workers that addresses individual and community factors and a heat awareness mobile application for agricultural supervisors that supports decisions about workplace heat prevention, in the Northwest United States. DESIGN: We designed the HEAT study as a parallel, comparison, randomized group intervention study that recruited workers and supervisors from agricultural workplaces. In intervention arm crews, workers received HEAT training, and supervisors received the HEAT awareness application. In comparison arm crews, workers were offered non-HEAT training. Primary outcomes were worker physiological heat strain and heat-related illness (HRI) symptoms. In both worker groups, we assessed HRI symptoms approximately weekly, and heat strain physiological monitoring was conducted at worksites approximately monthly, from June through August. DISCUSSION: To our knowledge, this is the first study to evaluate the effectiveness of a multi-level heat prevention intervention on physiological heat strain and HRI symptoms for outdoor agricultural workers. TRIAL REGISTRATION: ClinicalTrials.gov Registration Number: NCT04234802.
Practitioners and researchers use vulnerability indices to understand the conditions that influence hazard risk. However, there has been little research on how well such indices depict household-scale vulnerability to specific hazards. We examined relationships between an all-hazard index and a hazard-specific index with householdlevel adaptive resources, adaptive behaviors, proximate sensitivities, and self-reported health outcomes related to extreme heat. Household measures were drawn from a stratified random sample survey conducted in Phoenix, Arizona, USA (n = 163). The results point to different experiences between households in more and less heat vulnerable areas. The largest differences between households stratified by the hazard-specific index (Heat Vulnerability Index) primarily involved adaptive resources and behaviors, whereas indicators of proximate sensitivity were more strongly differentiated by the all-hazard index (Social Vulnerability Index). Differences in health outcomes between more and less vulnerable neighborhoods were more evident using HVI than SoVI, although effect sizes using either index were small and confidence intervals were wide. The relationship between vulnerability indices and several survey measures varied across four study sites. The specific ways in which more and less vulnerable communities differ from one another varies based on the adaptation, sensitivity, or outcome measure of interest, location within the city, and choice of vulnerability index.
There is a pressing need for strategies to prevent the heat-health impacts of climate change. Cooling urban areas through adding trees and vegetation and increasing solar reflectance of roofs and pavements with higher albedo surface materials are recommended strategies for mitigating the urban heat island. We quantified how various tree cover and albedo scenarios would impact heat-related mortality, temperature, humidity, and oppressive air masses in Los Angeles, California, and quantified the number of years that climate change-induced warming could be delayed in Los Angeles if interventions were implemented. Using synoptic climatology, we used meteorological data for historical summer heat waves, classifying days into discrete air mass types. We analyzed those data against historical mortality data to determine excess heat-related mortality. We then used the Weather Research and Forecasting model to explore the effects that tree cover and albedo scenarios would have, correlating the resultant meteorological data with standardized mortality data algorithms to quantify potential reductions in mortality. We found that roughly one in four lives currently lost during heat waves could be saved. We also found that climate change-induced warming could be delayed approximately 40-70 years under business-as-usual and moderate mitigation scenarios, respectively.
Urban tree cover contributes to human well-being through a variety of ecosystem services. In this study, we focus on the role that trees can play in reducing temperature during warm seasons and associated impacts on human health and well-being. We introduce a method for quantifying and valuing changes in premature mortality from extreme heat due to the changes in urban tree cover and apply this method to Baltimore City, Maryland. The model i-Tree Cool Air uses a water and energy balance to estimate hourly changes in air temperature due to alternative scenarios of tree cover applied across 653 Census Block Groups. The changes in temperature are applied to existing temperature?mortality models to estimate changes in health outcomes and associated values. Existing tree cover in Baltimore is estimated to reduce annual mortality by 543 deaths as compared to a 0% tree cover scenario. Increasing the area of current tree cover by 10% of each Census Block Group reduced baseline annual mortality by 83 to 247 deaths (valued at $0.68 ?2.0 billion applying Value of Statistical Life estimates). Over half of the reduced mortality is from the over 65 year age group, who are among the most vulnerable to extreme heat. Reductions in air temperature due to increased tree cover were greatest in downtown Baltimore where tree cover is relatively low and impervious cover is relatively high. However, the greatest reductions in mortality occurred in the outskirts of Baltimore where a greater number of people who are over 65 years in age reside. Quantifying and valuing the health benefits of changes in air temperatures due to increased tree cover can inform climate adaptation and mitigation plans by decision makers. Developing adaptation strategies to effectively address these issues will become increasingly important in the future under changing climates and an aging population.
BACKGROUND: Short-term associations between extreme heat events and adverse health outcomes are well-established in epidemiologic studies. However, the use of different exposure definitions across studies has limited our understanding of extreme heat characteristics that are most important for specific health outcomes or subpopulations. METHODS: Logic regression is a statistical learning method for constructing decision trees based on Boolean combinations of binary predictors. We describe how logic regression can be utilized as a data-driven approach to identify extreme heat exposure definitions using health outcome data. We evaluated the performance of the proposed algorithm in a simulation study, as well as in a 20-year time-series analysis of extreme heat and emergency department visits for 12 outcomes in the Atlanta metropolitan area. RESULTS: For the Atlanta case study, our novel application of logic regression identified extreme heat exposure definitions that were associated with several heat-sensitive disease outcomes (e.g., fluid and electrolyte imbalance, renal diseases, ischemic stroke, and hypertension). Exposures were often characterized by extreme apparent minimum temperature or maximum temperature over multiple days. The simulation study also demonstrated that logic regression can successfully identify exposures of different lags and duration structures when statistical power is sufficient. CONCLUSION: Logic regression is a useful tool for identifying important characteristics of extreme heat exposures for adverse health outcomes, which may help improve future heat warning systems and response plans.
Urban heat stress poses a major risk to public health. Case studies of individual cities suggest that heat exposure, like other environmental stressors, may be unequally distributed across income groups. There is little evidence, however, as to whether such disparities are pervasive. We combine surface urban heat island (SUHI) data, a proxy for isolating the urban contribution to additional heat exposure in built environments, with census tract-level demographic data to answer these questions for summer days, when heat exposure is likely to be at a maximum. We find that the average person of color lives in a census tract with higher SUHI intensity than non-Hispanic whites in all but 6 of the 175 largest urbanized areas in the continental United States. A similar pattern emerges for people living in households below the poverty line relative to those at more than two times the poverty line.
Cities inadvertently create warmer and drier urban climate conditions than their surrounding areas through urbanization that replaces natural surfaces with impervious materials. These changes cause heat-related health problems and many studies suggest microclimatic urban design (MUD) as an approach to address these problems. In MUD-related research, although terrestrial radiation plays an important role in human thermal comfort and previous studies use thermal comfort models to identify human heat stress, few studies have addressed the effect of terrestrial radiation. This study develops the ground ratio factor (GRF) model to estimate the different terrestrial radiation according to different ground conditions. Three types of ground materials (asphalt, concrete, and grass) were considered in the model, and field studies were conducted in humid subtropical climate (Cfa) zone during the hot season (13 July to 19 September 2020). The model was validated by comparing the predicated terrestrial radiation (PTR) from the model with the actual terrestrial radiation (ATR). The results showed that there is a statistically significant strong correlation between PTR and ATR. The model can contribute to MUD strategies by updating existing human energy budget models, which can lead to the measurement of more accurate human thermal comfort for mitigating thermal environments.
Background: Extreme heat is a leading cause of morbidity and mortality during summer months in the United States. Risk of heat exposure and associated health outcomes are disproportionately experienced by people with lower incomes, people of color, and/or immigrant populations.Methods: As qualitative research on the experiences of residents in heat islands is limited, this community-based study examined barriers and coping strategies for keeping cool among residents of Chelsea and East Boston, Massachusetts-environmental justice (EJ) areas that experience the urban heat island effect-through semistructured interviews and qualitative content analysis.Results: Results indicate that all participants (n = 12) had air conditioning, but high energy bills contributed to low use. Eight participants were self-described heat-sensitive, with five experiencing poor health in heat. In addition, nine reported insufficient hydration due to work schedules, distaste of water, or perceptions of it being unsafe.Discussion: This research highlights the importance of understanding perceptions of residents in EJ communities to contextualize vulnerability and identify multipronged heat coping strategies and targeted interventions.
Beliefs in climate change are influenced by personal experiences and sociodemographic charac-teristics; yet justice considerations are often overlooked. We unveil the influence of these factors? on climate change beliefs in a large American city facing substantial climate change impacts, Phoenix, Arizona. Using the Phoenix Area Social Survey that includes data collected from (n = 806) households across fourteen cities in the Phoenix metropolitan area, we investigate what factors influence a belief that ?global warming and climate change are already occurring.? Engaging adaptive capacity and justice literatures with climate belief models, we find that belief in climate change and global warming is positively associated with race specifically other than non-Hispanic Whites, high levels of education, personal experience with heat-related illnesses, and liberal beliefs. Widespread agreement about climate change is found within the scientific community, but general populations, especially in the USA, lag behind in accepting climate change. Critically, there are important justice dimensions absent in the existing literature relevant to understanding belief in and the impacts of climate change. Unpacking these factors could help inform policy makers and civil society organizations in their efforts to design more ?just adaptation? strategies.
Recent studies have characterized individually experienced temperatures or individually experienced heat indices, including new exposure metrics that capture dimensions of exposure intensity, frequency, and duration. Yet, few studies have examined the personal thermal exposure in underrepresented groups, like outdoor workers, and even fewer have assessed corresponding changes in physiologic heat strain. The objective of this paper is to examine a cohort of occupationally exposed grounds and public safety workers (n = 25) to characterize their heat exposure and resulting heat strain. In addition, a secondary aim of this work is to compare individually heat index exposure (IHIE) across exposure metrics, fixed-site in situ weather stations, and raster-derived urban heat island (UHI) measurements in Charleston, SC, a humid coastal climate in the Southeastern USA. A Bland-Altman (BA) analysis was used to assess the level of agreement between the personal IHIE measurements and weather-station heat index (HI) and Urban Heat Island (UHI) measurements. Linear mixed-effect models were used to determine the association between individual risk factors and in situ weather station measurements significantly associated with IHIE measurements. Multivariable stepwise Cox proportional hazard modeling was used to identify the individual and workplace factors associated with time to heat strain in workers. We also examined the non-linear association between heat strain and exposure metrics using generalized additive models. We found significant heterogeneity in IHIE measurements across participants. We observed that time to heat strain was positively associated with a higher IHIE, older age, being male, and among Caucasian workers. Important nonlinear associations between heat strain occurrence and the intensity, frequency, and duration of personal heat metrics were observed. Lastly, our analysis found that IHIE measures were significantly similar for weather station HI, although differences were more pronounced for temperature and relative humidity measurements. Conversely, our IHIE findings were much lower than raster-derived UHI measurements. Real-time monitoring can offer important insights about unfolding temperature-health trends and emerging behaviors during thermal extreme events, which have significant potential to provide situational awareness.
The growing frequency, intensity, and duration of extreme heat events necessitates interventions to reduce heat exposures. Local opportunities for heat adaptation may be optimally identified through collection of both quantitative exposure metrics and qualitative data on perceptions of heat. In this study, we used mixed methods to characterize heat exposure among urban residents in the area of Boston, Massachusetts, US, in summer 2020. Repeated interviews of N = 24 study participants ascertained heat vulnerability and adaptation strategies. Participants also used low-cost sensors to collect temperature, location, sleep, and physical activity data. We saw significant differences across temperature metrics: median personal temperature exposures were 3.9 °C higher than median ambient weather station temperatures. Existing air conditioning (AC) units did not adequately control indoor temperatures to desired thermostat levels: even with AC use, indoor maximum temperatures increased by 0.24 °C per °C of maximum outdoor temperature. Sleep duration was not associated with indoor or outdoor temperature. On warmer days, we observed a range of changes in time-at-home, expected given our small study size. Interview results further indicated opportunities for heat adaptation interventions including AC upgrades, hydration education campaigns, and amelioration of energy costs during high heat periods. Our mixed methods design informs heat adaptation interventions tailored to the challenges faced by residents in the study area. The strength of our community-academic partnership was a large part of the success of the mixed methods approach.
Temperature profiles of the lower atmosphere (<3 km) over complex urban areas are related to health risks, including heat stress and respiratory illness. This complexity leads to uncertainty in numerical simulations, and many studies call for more observations of the lower atmosphere over cities. Using 20 years of observations from the Aircraft Meteorological Data Relay (AMDAR) program over Dallas-Fort Worth, Texas, average profiles every 0.5 h are created from the 1.5 million individual soundings. Dallas-Fort Worth is ideal because it is a large urban area in the central Great Plains, has no major topographic or coastal influences, and has two major airports near the center of the urban heat island. With frequent and high-quality measurements over the city, we investigate the evolution of the lower atmosphere around sunrise to quantify the stability, boundary layer height, and duration of the morning transition when there are southerly winds, few clouds, and no precipitation so as to eliminate transient synoptic events. Characteristics of the lower atmosphere are separated by season and maximum wind speed because the the Great Plains low-level jet contributes to day-to-day variability. In all seasons, stronger wind over the city leads to a weaker nocturnal temperature inversion at sunrise and a shorter morning transition period, with the greatest difference during autumn and the smallest difference during summer. During summer, the boundary layer height at sunrise is higher on average, deepens the most as wind strengthens, and has the fewest days exhibiting a surface temperature inversion over the city. Significance StatementCities impact health by creating an urban heat island caused by more heating at the surface, less evaporative cooling, and increased anthropogenic waste heat, and they can have high pollution. Cooling overnight stabilizes the lower atmosphere and traps pollutants near the surface until surface heating after sunrise mixes them away. Inadequate pollution observations make it difficult to study these issues. The greatest mixing occurs about 2 h after sunrise but can be modulated by wind speed. Observations from 1.5 million aircraft landing and taking off over Dallas-Fort Worth, Texas, reveal that strong low-level wind leads to morning transitions ending 0.84 h earlier on average than with light wind. Details from this vast dataset contribute to improved understanding of the lower atmosphere over cities and provide a baseline for simulations.
Extreme heat is a recognized threat to human health. This study examines projected future trends of multiple measures of extreme heat across Texas throughout the next century, and evaluates the expected climate changes alongside Texas athletic staff (coach and athletic trainer) attitudes toward heat and climate change. Numerical climate simulations from the recently published Community Earth System Model version 2 and the Climate Model Intercomparison Project were used to predict changes in summer temperatures, heat indices, and wet bulb temperatures across Texas and also within specific metropolitan areas. A survey examining attitudes toward the effects of climate change on athletic programs and student athlete health was also distributed to high-school and university athletic staff. Heat indices are projected to increase beyond what is considered healthy/safe limits for outdoor sports activity by the mid-to-late 21st century. Survey results reveal a general understanding and acceptance of climate change and a need for adjustments in accordance with more dangerous heat-related events. However, a portion of athletic staff still do not acknowledge the changing climate and its implications for student athlete health and their athletic programs. Enhancing climate change and health communication across the state may initiate important changes to athletic programs (e.g., timing, duration, intensity, and location of practices), which should be made in accordance with increasingly dangerous temperatures and weather conditions. This work employs a novel interdisciplinary approach to evaluate future heat projections alongside attitudes from athletic communities toward climate change.
Background: Little is known about menopausal symptoms in underserved women. Aim: To better understand self-reported menopausal symptoms in underserved and homeless women living in extreme heat during different seasons. Methods: A cross-sectional study, including the Greene Climacteric Scale (GCS), climate-related questions, and demographics was administered June to August of 2017 and December to February 2018 to women 40-65 years of age. Results: In 104 predominantly Hispanic (56%), uninsured (53%), menopausal (56%), and mid-aged (50 ± 9.5) women, 57% reported any bother, while 20% of these women reported “quite a bit” or “extreme” bother from hot flushes. The total GCS score was a mean of 41 ± 15.0; out of 63 indicating significant symptoms, the psychological and somatic clusters were highest. Women did not think temperature outside influenced their menopausal symptoms at either time point (69% in winter vs. 57% in summer, p = 0.23). In multivariable analyses after adjusting for race, body mass index, and living situation neither season nor temperature was associated with self-reported hot flush bother. While one-third of women reported becoming ill from the heat, 90% of women reported not seeking care from a doctor for their illness. Conclusion: Menopausal, underserved, homeless women living in Arizona reported few vasomotor symptoms regardless of season, and endorsed psychological and somatic complaints. Socioeconomic factors may influence types of bothersome menopausal symptoms in this population of women.
Extreme heat exposure increases the risk for heat-related illnesses (HRIs) and deaths, and comprehensive strategies to prevent HRIs are increasingly important in a warming climate (1). An estimated 702 HRI-associated deaths and 67,512 HRI-associated emergency department visits occur in the United States each year (2,3). In 2020, Phoenix and Yuma, Arizona, experienced a record 145 and 148 days, respectively, of temperatures >100°F (37.8°C), and a record 522 heat-related deaths occurred in the state. HRIs are preventable through individual and community-based strategies*(,)(†); cooling centers,(§) typically air-conditioned or cooled buildings designated as sites to provide respite and safety during extreme heat, have been established in Maricopa and Yuma counties to reduce HRIs among at-risk populations, such as older adults. This analysis examined trends in HRIs by age during 2010-2020 for Maricopa and Yuma counties and data from a survey of older adults related to cooling center availability and use in Yuma County during 2018-2019. Data from CDC’s Social Vulnerability Index (SVI) were also used to overlay cooling center locations with SVI scores. During 2010-2020, heat days, defined as days with an excessive heat warning issued by the National Weather Service Phoenix Office,(¶) for any part of Maricopa and Yuma counties (4), increased in both Maricopa County (1.18 days per year) and Yuma County (1.71 days per year) on average. Adults aged ≥65 years had higher rates of HRI hospitalization compared with those aged <65 years. In a survey of 39 adults aged ≥65 years in Yuma County, 44% reported recent HRI symptoms, and 18% reported electricity cost always or sometimes constrained their use of air conditioning. Barriers to cooling center access among older adults include awareness of location and transportation. Collaboration among diverse community sectors and health profession education programs is important to better prepare for rising heat exposure and HRIs. States and communities can implement adaptation and evaluation strategies to mitigate and assess heat risk, such as the use of cooling centers to protect communities disproportionately affected by HRI during periods of high temperatures.
It is predicted that heat waves will increase as climate changes. Related public health interventions have expanded over the past decades but are primarily targeted at health outcomes occurring during heat waves. However, heat adaptation is dynamic and adverse outcomes related to heat injuries occur with moderate increases in temperature throughout the summertime. We analyzed outpatient and inpatient heat related injuries from 2013 to 2019. National Weather Service event summaries were used to characterize reported heat wave days and weather data was linked to individual cases. Despite the higher rate of heat injury on heat wave days, only 12.7% of the 17,662 heat-related injuries diagnosed from 2013 to 2019 occurred during reported heat waves. In addition, the National Weather Service surveillance system monitoring heat related injuries only captured 2.1% of all heat related injuries and 30.6% of heat related deaths. As climate changes and warmer conditions become more common, public health response to moderate increases in temperature during summertime needs to be strengthened as do the surveillance systems used to monitor adverse heat related health events. Improved surveillance systems, long-term interventions and strategies addressing climate change may help mitigate adverse health outcomes attributable to heat related injuries over the summertime.
As climate change increases the frequency and intensity of devastating and unpredictable extreme heat events, developments to the built environment should consider instigating practices that minimize the likelihood of indoor overheating during hot weather. Heatwaves are the leading cause of death among weather-related causes worldwide, including in developed and developing countries. In this empirical study, a four-step approach was used to collect, extract and analyze data from twenty-seven states in the United States. Three housing characteristic categories (i.e., general housing conditions, living conditions, and housing thermal inertia) and eight variables were extracted from the American Housing Survey database, ResStock database and CDC’s National Environmental Public Health Tracking Network. Multivariable regression models were used to understand the influential variables, a multicollinearity test was used to determine the dependence of those variables, and then a logistic model was used to verify the results. Three variables-housing age (HA), housing crowding ratio (HCR), and roof condition (RC)-were found to be correlated with the risk of heat-related illness (HRI) indexes. Then, a logistic regression model was generated using the three variables to predict the risk of heat-related emergency department visits (EDV) and heat-related mortality (MORD) on a state level. The results indicate that the proposed logistic regression model correctly predicted 100% of the high-risk states for MORD for the eight states tested. Overall, this analysis provides additional evidence about the housing character variables that influence HRI. The outcomes also reinforce the concept of the built environment determined health and demonstrate that the built environment, especially housing, should be considered in techniques for mitigating climate change-exacerbated health conditions.
Although extreme heat exposure (EHE) was reported to be associated with increased risks of multiple diseases, little is known about the effects of EHE on pregnancy complications. We examined the EHE-pregnancy complications associations by lag days, subtypes, sociodemographic characteristics, and areas in New York State (NYS). We conducted a case-crossover analysis to assess the EHE-pregnancy complications associations in summer (June-August) and transitional months (May and September). All emergency department (ED) visits and hospital admissions due to pregnancy complications (ICD 9 codes: 630-649) from 2005 to 2013 in NYS were included. Daily mean temperature > 90th percentile of the monthly mean temperature in each county was defined as an EHE. We used conditional logistic regression while controlling for other weather factors, air pollutants and holidays to assess the EHE-pregnancy complications associations. EHE was significantly associated with increased ED visits for pregnancy complications in summer (ORs ranged: 1.01-1.04 from lag days 0-5). There was also a significant and stronger association in transitional months (ORs ranged: 1.02-1.06, Lag 0). Furthermore, we found EHE affected multiple subtypes of pregnancy complications, including threatened/spontaneous abortion, renal diseases, infectious diseases, diabetes, and hypertension (ORs range: 1.13-1.90) during transitional months. A significant concentration response effect between the number of consecutive days of EHE and ED visits in summer (P for trend <0.001), ED visits in September (P for trend =0.03), and hospital admission in May (P for trend<0.001) due to pregnancy complications was observed, respectively. African Americans and residents in lower socioeconomic position (SEP) counties were more susceptible to the effects of EHE. In conclusion, we found an immediate and prolonged effect of EHE on pregnancy complications in summer and a stronger, immediate effect in transitional months. These effects were stronger in African Americans and counties with lower SEP. Earlier warnings regarding extreme heat are recommended to decrease pregnancy complications.
Extreme heat events are the deadliest weather-related event in the United States. Cities throughout the United States have worked to develop heat adaptation strategies to limit the impact of extreme heat on vulnerable populations. However, the COVID-19 pandemic presented unprecedented challenges to local governments. This paper provides a preliminary review of strategies and interventions used to manage compound COVID-19-extreme heat events in the 25 most populous cities of the United States. Heat adaptation strategies employed prior to the COVID-19 pandemic were not adequate to meet during the co-occurring compound hazard of COVID-19-EHE. Long-term climate-adaptation strategies will require leveraging physical, financial, and community resources across multiple city departments to meet the needs of compound hazards, such as COVID-19 and extreme heat.
Globally, heat stress (HS) is nearly certain to increase rapidly over the coming decades, characterized by increased frequency, severity, and spatiotemporal extent of extreme temperature and humidity. While these characteristics have been investigated independently, a holistic analysis integrating them is potentially more informative. Using observations, climate projections from the CMIP5 model ensemble, and historical and future population estimates, we apply the IPCC risk framework to examine present and projected future potential impact (PI) of summer heat stress for the contiguous United States (CONUS) as a function of non-stationary HS characteristics and population exposure. We find that the PI of short-to-medium duration (1-7 days) HS events is likely to increase more than three-fold across densely populated regions of the U.S. including the Northeast, Southeast Piedmont, Midwest, and parts of the Desert Southwest by late this century (2060-2099) under the highest emissions scenario. The contribution from climate change alone more than doubles the impact in the coastal Pacific Northwest, central California, and the Great Lakes region, implying a substantial increase in HS risk without aggressive mitigation efforts.
Previous field studies monitoring small groups of participants showed that heat stress in the electrical utilities industry may be detrimental to worker health and safety. Our aim in this study was to characterize heat stress and strain in electrical utilities workers across North America. A total of 428 workers in the power generation, transmission and distribution industry across 16 US states and three Canadian Provinces completed a two-part on-line questionnaire anonymously. The first part comprised 13 general questions on the employee’s workplace location, role in the organization, years of experience, general duties, average work shift duration, and other job-related information. It also included two questions on self-reported heat stress. The second part consisted of the “Heat Strain Score Index” (HSSI), a validated questionnaire which evaluates heat stress at the workplace as “safe level” (score ≤13.5: worker experiences no/low heat strain), “caution level” (score 13.6 to 18.0: moderate risk for heat strain), and “danger level” (score >18.0: high risk for heat strain). In addition to the survey, we obtained meteorological data from weather stations in proximity (12.3 ± 12.2 km) to the work locations. Based on the HSSI, 32.9%, 22.3%, 44.4% of the responders’ workplaces were diagnosed as “safe level”, “caution level”, and “danger level”, respectively. The HSSI varied significantly depending on the occupation from 4.9 ± 3.2 in contact center workforce to 19.1 ± 5.4 in mechanics (p < 0.001), and demonstrated moderate linear relationships with summertime (June, July, August) midday air temperature (r = 0.317, p < 0.001) and outdoor midday Wet-Bulb Globe Temperature (r = 0.322, p < 0.001). The highest HSSI was observed in mechanics, machine operators in line installations, line workers, electricians, and meter-readers. We conclude that electrical utilities workers experience instances of severe environmental heat stress resulting in elevated levels of heat strain, particularly when performing physically demanding tasks (e.g., manually climbing utility poles, installing lines).
This article describes results from a survey of firefighters designed to identify conditions that contribute to heat strain in structural firefighting. Based on responses from about 3000 firefighters across the USA and Canada, the article provides invaluable information about how firefighters associate environmental conditions, work tasks and other factors with heat strain. One-half of firefighters surveyed have experienced heat stress during their service. They can wear fully deployed turnout gear for 2 h or more at the fire scene, reinforcing the importance of turnout suit breathability as a factor in heat strain. Survey results are useful in weighing the comparative value of total heat loss (THL) and evaporative heat resistance (Ref) for predicting turnout-related heat strain. Survey findings support the inclusion of a performance criterion in the National Fire Protection Association 1971 standard for firefighter personal protective equipment based on limiting Ref of turnout materials along with current THL requirement.
The spectrum of historical features and clinical presentations of heat illness and heatstroke in the pediatric population has received limited focus in the emergency medicine literature. The majority of published cases involve children trapped in closed spaces and adolescent athletes undergoing high-intensity training regimens in geographical regions with moderately high ambient temperatures and high humidity. There has been less research on the potential impact of extreme temperatures and radiant heat that are the hallmarks of the US southwest region. We performed a retrospective review of pediatric heat illness at our facility located in a North American desert climate.
Heatwave warning systems rely on forecasts made for fixed-point weather stations (WS), which do not reflect variation in temperature and humidity experienced by individuals moving through indoor and outdoor locations. We examined whether neighborhood measurement improved the prediction of individually experienced heat index in addition to nearest WS in an urban and rural location. Participants (residents of Birmingham, Alabama [N = 89] and Wilcox County, Alabama [N = 88]) wore thermometers clipped to their shoe for 7 days. Shielded thermometers/hygrometers were placed outdoors within participant’s neighborhoods (N = 43). Nearest WS and neighborhood thermometers were matched to participant’s home address. Heat index (HI) was estimated from participant thermometer temperature and WS humidity per person-hour (HI[individual]), or WS temperature and humidity, or neighborhood temperature and humidity. We found that neighborhood HI improved the prediction of individually experienced HI in addition to WS HI in the rural location, and neighborhood heat index alone served as a better predictor in the urban location, after accounting for individual-level factors. Overall, a 1 °C increase in HI[neighborhood] was associated with 0.20 °C [95% CI (0.19, 0.21)] increase in HI[individual]. After adjusting for ambient condition differences, we found higher HI[individual] in the rural location, and increased HI[individual] during non-rest time (5 a.m. to midnight) and on weekdays.
It is important to quantify human heat exposure in order to evaluate and mitigate the negative impacts of heat on human well-being in the context of global warming. This study proposed a human-centric framework to examine human personal heat exposure based on anonymous GPS trajectories data mining and urban microclimate modeling. The mean radiant temperature (T-mrt) that represents human body’s energy balance was used to indicate human heat exposure. The meteorological data and high-resolution 3D urban model generated from multispectral remotely sensed images and LiDAR data were used as inputs in urban microclimate modeling to map the spatio-temporal distribution of the T-mrt, in the Boston metropolitan area. The anonymous human GPS trajectory data collected from fitness Apps was used to map the spatio-temporal distribution of human outdoor activities. By overlaying the anonymous GPS trajectories on the generated spatio-temporal maps of T-mrt, this study further examined the heat exposure of runners in different age-gender groups in the Boston area. Results show that there is no significant difference in terms of heat exposure for female and male runners. The female runners in the age of 45-54 are exposed to more heat than female runners of 18-24 and 25-34, while there is no significant difference among male runners. This study proposed a novel method to estimate human heat exposure, which would shed new light on mitigating the negative impacts of heat on human health.
Extreme heat in the United States is a leading cause of weather-related deaths, disproportionately affecting low-income communities of color who tend to live in substandard housing with limited indoor cooling and fewer trees. Trees in cities have been documented to improve public health in many ways and provide climate regulating ecosystem services via shading, absorbing, and transpiring heat, measurably reducing heat-related illnesses and deaths. Advancing “urban forest equity” by planting trees in marginalized neighborhoods is acknowledged as a climate health equity strategy. But information is lacking about the efficacy of tree planting programs in advancing urban forest equity and public wellbeing. There is a need for frameworks to address the mismatch between policy goals, governance, resources, and community desires on how to green marginalized neighborhoods for public health improvement-especially in water-scarce environments. Prior studies have used environmental management-based approaches to evaluate planting programs, but few have focused on equity and health outcomes. We adapted a theory-based, multi-dimensional socio-ecological systems (SES) framework regularly used in the public health field to evaluate the Tree Ambassador, or Promotor Forestal, program in Los Angeles, US. The program is modeled after the community health worker model-where frontline health workers are trusted community members. It aims to address urban forest equity and wellbeing by training, supporting, and compensating residents to organize their communities. We use focus groups, surveys, and ethnographic methods to develop our SES model of community-based tree stewardship. The model elucidates how interacting dimensions-from individual to society level-drive urban forest equity and related public health outcomes. We then present an alternative framework, adding temporal and spatial factors to these dimensions. Evaluation results and our SES model highlight drivers aiding or hindering program trainees in organizing communities, including access to properties, perceptions about irrigation responsibilities, and lack of trust in local government. We also find that as trainee experience increases, measures including self- and collective efficacy and trust in their neighbors increase. Findings can inform urban forestry policy, planning, and management actions at the government and non-profit levels that aim to increase tree cover and reduce heat exposure in marginalized communities.
Extreme heat events induced by climate change present a growing risk to transit passenger comfort and health. To reduce exposure, agencies may consider changes to schedules that reduce headways on heavily trafficked bus routes serving vulnerable populations. This paper develops a schedule optimization model to minimize heat exposure and applies it to local bus services in Phoenix, Arizona, using agent-based simulation to inform travel demand and rider characteristics. Rerouting as little as 10% of a fleet is found to reduce network-wide exposure by as much as 35% when operating at maximum fleet capacity. Outcome improvements are notably characterized by diminishing returns, owing to skewed ridership and the inverse relationship between fleet size and passenger wait time. Access to spare vehicles can also ensure significant reductions in exposure, especially under the most extreme temperatures. Rerouting, therefore, presents a low-cost, adaptable resilience strategy to protect riders from extreme heat exposure.
BACKGROUND: This article describes the first Community Assessment for Public Health Emergency Response (CASPER) rapid needs assessment project to be conducted in Wisconsin. The project focused on extreme heat preparedness. METHODS: Fifteen teams conducted household surveys in 30 census blocks in the city of Milwaukee, Wisconsin. RESULTS: Survey results indicated that the majority of households were unaware of the location of a nearby cooling center. Although the vast majority of households reported some form of air conditioning in their house, over half felt too hot inside their home sometimes, most of the time, or always. DISCUSSION: The community partnerships ensured that this project was conducted with local partner input and that the data could be used to inform extreme heat response.
Problem, research strategy, and findings Extreme heat is the deadliest climate hazard in the United States. Climate change and the urban heat island effect are increasing the number of dangerously hot days in cities worldwide and the need for communities to plan for extreme heat. Existing literature on heat planning focuses on heat island mapping and modeling, whereas few studies delve into heat planning and governance processes. We surveyed planning professionals from diverse cities across the United States to establish critical baseline information for a growing area of planning practice and scholarship that future research can build on. Survey results show that planners are concerned with extreme heat risks, particularly environmental and public health impacts from climate change. Planners already report impacts from extreme heat, particularly to energy and water use, vegetation and wildlife, public health, and quality of life. Especially in affected communities, planners claim they address heat in plans and implement heat mitigation and management strategies such as urban forestry, emergency response, and weatherization, but perceive many barriers related to human and financial resources and political will. Takeaway for practice Planners are concerned about extreme heat, especially in the face of climate change. They are beginning to address heat through different strategies and plan types, but we see opportunities to better connect planners to existing heat information sources and leverage existing planning tools, including vegetation, land use regulations, and building codes, to mitigate risks. Although barriers to heat planning persist, including human and capital resources, planners are uniquely qualified to coordinate communities’ efforts to address the rising threat of extreme heat.
Long-term community resilience, which privileges a long view look at chronic issues influencing communities, has begun to draw more attention from city planners, researchers and policymakers. In Phoenix, resilience to heat is both a necessity and a way of life. In this paper, we attempt to understand how residents living in Phoenix experience and behave in an extreme heat environment. To achieve this goal, we introduced a smartphone application (ActivityLog) to study spatio-temporal dynamics of human interaction with urban environments. Compared with traditional paper activity log results we have in this study, the smartphone-based activity log has higher data quality in terms of total number of logs, response rates, accuracy, and connection with GPS and temperature sensors. The research results show that low-income residents in Phoenix mostly stay home during the summer but experience a relatively high indoor temperature due to the lack/low efficiency of air-conditioning (AC) equipment or lack of funds to run AC frequently. Middle-class residents have a better living experience in Phoenix with better mobility with automobiles and good quality of AC. The research results help us better understand user behaviors for daily log activities and how human activities interact with the urban thermal environment, informing further planning policy development. The ActivityLog smartphone application is also presented as an open-source prototype to design a similar urban climate citizen science program in the future.
Extreme heat does not affect all urban residents equally. While vulnerability is often defined as a combination of exposure, sensitivity, and adaptive capacity, many scholars have argued that the quantitative representation of adaptive capacity is particularly difficult. How people who live in vulnerable situations change their behavior to cope with and manage extreme urban temperatures, and the resources necessary to prevent adverse health effects, highlight different adaptive capacity within a city. Our understanding and depiction of how and why the impacts of urban heat vary between individuals and groups is constrained by contemporary approaches to quantify vulnerability using aggregate-scale data drawn from censuses, surveys, and administrative records. Thus, adaptive capacity is likely poorly represented in modern heat vulnerability analyses and their applications. This article explores how different city residents understand and adapt to increasing extreme urban heat, the tradeoffs different populations must make between generic and specific adaptive capacity, and the coping strategies that influence heat adaptive capacity at various scales. Using metropolitan Phoenix as a test site, open-ended interviews were conducted in which residents told their stories about past and present extreme heat adaptive capacity and adaptive behaviors. Three narratives emerged: heat is an inconvenience, heat is a manageable problem, and heat is a catastrophe. Framing heat vulnerability using these differing narratives can help evaluate if standard recommendations for coping with heat adequately represent solutions for the lived experiences of different vulnerable groups. Learning how and under what circumstances vulnerable people are motivated to make necessary changes to increase thermal comfort and safeguard public health will ensure that targeted heat mitigation and adaptation policies are widely adopted. Heat adaptation and mitigation policy makers need to be cognizant of the gap in heat risk perception across different segments of the population and reflect on whether those decisions reflect their experience (of likely belonging to the inconvenience group) or incorporate differing scales of heat adaptive capacity.
Current bioclimate and air quality indices provide insufficient information about the combined effect on human physiology in outdoor spaces. This work examined, large scale gridded meteorological observations, including air temperature, wind speed, solar radiation, and relative humidity, to derive Universal Thermal Climate Index (UTCI) at hourly intervals along with the air quality index (AQI) derived from Environmental Protection Agency (EPA) observation stations. UTCI and AQI were combined into a single framework using geospatial analytics and a newly developed lookup table approach. High risk areas for heat stress and poor air quality were identified using Moran’s I and Getis-Ord GI* statistics. Moderate to strong heat stress was observed during the summer months of 2015-2019, with UTCI ranging from 26 degrees C to 38 degrees C. Coastal regions consistently experienced higher UTCI during noon due to higher humidity but the effect subsided with cooler air circulation from the ocean, especially in the morning and evening. Results also indicated the vulnerability of this region due to the combined impact of heat stress and poor air quality based on 95th percentile values. The final products from this analysis can provide valuable insights for urban planning and preventative measures to ensure improved public health in outdoor environments.
Exposure to heat is a growing public health concern as climate change accelerates worldwide. Different socioeconomic and racial groups often face unequal exposure to heat as well as increased heat-related sickness, mortality, and energy costs. We provide new insight into thermal inequities by analyzing 20 Southwestern U.S. metropolitan regions at the census block group scale for three temperature scenarios (average summer heat, extreme summer heat, and average summer nighttime heat). We first compared average temperatures for top and bottom decile block groups according to demographic variables. Then we used spatial regression models to investigate the extent to which exposure to heat (measured by land surface temperature) varies according to income and race. Large thermal inequities exist within all the regions studied. On average, the poorest 10% of neighborhoods in an urban region were 2.2 °C (4 °F) hotter than the wealthiest 10% on both extreme heat days and average summer days. The difference was as high as 3.3-3.7 °C (6-7 °F) in California metro areas such as Palm Springs and the Inland Empire. A similar pattern held for Latinx neighborhoods. Temperature disparities at night were much smaller (usually ~1 °F). Disparities for Black neighborhoods were also lower, perhaps because Black populations are small in most of these cities. California urban regions show stronger thermal disparities than those in other Southwestern states, perhaps because inexpensive water has led to more extensive vegetation in affluent neighborhoods. Our findings provide new details about urban thermal inequities and reinforce the need for programs to reduce the disproportionate heat experienced by disadvantaged communities.
Extreme heat exposure and sensitivity have been a growing concern in urban regions as the effects of extreme heat pose a threat to public health, the water supply, and the infrastructure. Heat-related illnesses demand an immediate Emergency Medical Service (EMS) response since they might result in death or serious disability if not treated quickly. Despite increased concerns about urban heat waves and relevant health issues, a limited amount of research has investigated the effects of heat vulnerability on heat-related illnesses. This study explores the geographical distribution of heat vulnerability in the city of Austin and Travis County areas of Texas and identifies neighborhoods with a high degree of heat vulnerability and restricted EMS accessibility. We conducted negative binomial regressions to investigate the effects of heat vulnerability on heat-related EMS incidents. Heat-related EMS calls have increased in neighborhoods with more impervious surfaces, Hispanics, those receiving social benefits, people living alone, and the elderly. Higher urban capacity, including efficient road networks, water areas, and green spaces, is likely to reduce heat-related EMS incidents. This study provides data-driven evidence to help planners prioritize vulnerable locations and concentrate local efforts on addressing heat-related health concerns.
The U-shaped association between health outcomes and ambient temperatures has been extensively investigated. However, such analyses cannot fully estimate the mortality burden of climate change because the features of the association (e.g., minimum mortality temperature) vary with human adaptation; thus, they are not generalizable to different locations. In this study, we assumed that humans could adapt to regular temperature variations; and thus examined the all-cause mortality attributable to temperature anomaly (TA), an indicator widely utilized in climate science to measure irregular temperature fluctuations, across 115 cities in the United States (US). We first used quasi-Poisson regressions to obtain the city-specific TA-mortality associations, then used meta-regression to pool these city-specific estimates. Finally, we calculated the number of TA-related deaths using the uniform pooled association, then compared it to the estimates from city-specific associations, which had been controlled for adaptation. Meta-regression showed a U-shaped TA-mortality association, centered at a TA near 0. According to the pooled association, 0.579 % (95 % confidence interval [CI]: 0.465-0.681 %), 0.394 % (95 % CI: 0.332-0.451 %), and 0.185 % (95 % CI: 0.107-0.254 %) of all-cause deaths were attributable to all anomalous temperatures (TA ≠ 0), anomalous heat (TA > 0), and anomalous cold (TA < 0), respectively. At the city level, heat-related deaths estimated from the pooled association were in good agreement with heat-related deaths estimated from the city-specific associations (R(2) = 0.84). However, the cold-related deaths estimated from the two methods showed a weaker correlation (R(2) = 0.07). Our findings suggest that TA constitutes a generalizable indicator that can uniformly evaluate deaths attributable to anomalous heat in distinct geographical locations.
We use temperature variation within narrowly defined geographic and demographic cells to show that exposure to extreme temperature increases the risk of maternal hospitalization during pregnancy. This effect is driven by emergency hospitalizations for various pregnancy complications, suggesting that it represents a deterioration in underlying maternal health rather than a change in women’s ability to access health care. The effect is larger for black women than for women of other races, suggesting that without significant adaptation, projected increases in extreme temperatures over the next century may further exacerbate racial disparities in maternal health.
Extreme heat events are becoming more frequent and more severe in the Pacific Northwest and in comparable dry-summer climates worldwide, increasing the occurrence of heat-related illness and death. Much of this risk is attributed to overheating in multifamily dwellings, particularly in neighborhoods with abundant asphalt, few trees, and limited financial resources. Air-conditioning expansion is problematic, however, because it creates vulnerability to operational costs and power outages, while expelled hot air intensifies urban heat island effects. In contrast, passive cooling strategies that deflect solar radiation and recruit the cool night air typical of Mediterranean, semi-arid, and arid climates are quite promising, but their abilities to improve residential survivability during extreme heat have not yet been explored. To understand this potential, here we investigate the extent to which well-controlled shading and natural ventilation, in some cases with fan assistance, could have diminished the hours in which indoor heat index levels exceeded ‘caution’, ‘extreme caution’, ‘danger’, and ‘extreme danger’ thresholds during the June 2021 heat wave in the Pacific Northwest; building thermal performance was simulated in EnergyPlus under conditions experienced by Vancouver BC, Seattle WA, Spokane WA, Portland OR, and Eugene OR. Strikingly, we find that in Portland, where the highest temperatures occurred, integrated shading and natural ventilation eliminated all hours above the danger threshold during the 3-day event, lowering peak indoor air temperatures by approximately 14 degrees C (25 degrees F); without cooling, all 72h exceeded this threshold. During the encompassing 10-day period, these passive measures provided 130-150h of thermal relief; baseline conditions without cooling provided none. Additionally, passive cooling reduced active cooling loads by up to 80%. Together, these results show the immediate, substantial value of requiring effective operable shading and secure operable windows in apartments in mild dry-summer climates with rising heatwave intensity, as well as public health messaging to support the productive operation of these elements.
Rising global temperatures and the urban heat island effect can amplify heat-related health risks to urban res-idents. Cities are considering various heat adaptation actions to improve public health, enhance social equity, and cope with future conditions beyond past experience. We present the City-Heat Equity Adaptation Tool (City -HEAT), which suggests optimal investments for mitigating urban heat and reducing health impacts through modifications of built (cool roofs/pavements) and natural (urban afforestation) environments and reductions of people’s heat exposure (cooling centers). The optimization considers multiple public health and social objectives under a wide range of future scenarios. An application to Baltimore, MD (USA) demonstrates how City-HEAT can generate Pareto-efficient multi-year heat adaptation plans. We quantify effectiveness-efficiency-equity tradeoffs among alternative plans and show the advantages of flexible decision-making. City-HEAT can be adapted to the natural, built, and social environments of other cities to support their urban heat adaptation planning, recog-nizing local objectives and uncertainty.
Although research indicates health and well-being benefits of greenspace, little is known regarding how greenspace may influence adaptation to health risks from heat, particularly how these risks change over time. Using daily hospitalization rates of Medicare beneficiaries ≥65 years for 2000-2016 in 40 U.S. Northeastern urban counties, we assessed how temperature-related hospitalizations from cardiovascular causes (CVD) and heat stroke (HS) changed over time. We analyzed effect modification of those temporal changes by Enhanced Vegetation Index (EVI), approximating greenspace. We used a two-stage analysis including a generalized additive model and meta-analysis. Results showed that relative risk (RR) (per 1 °C increase in lag0-3 temperature) for temperature-HS hospitalization was higher in counties with the lowest quartile EVI (RR = 2.7, 95% CI: 2.0, 3.4) compared to counties with the highest quartile EVI (RR = 0.40, 95% CI: 0.14, 1.13) in the early part of the study period (2000-2004). RR of HS decreased to 0.88 (95% CI: 0.31, 2.53) in 2013-2016 in counties with the lowest quartile EVI. RR for HS changed over time in counties in the highest quartile EVI, with RRs of 0.4 (95% CI: -0.7, 1.4) in 2000-2004 and 2.4 (95% CI: 1.6, 3.2) in 2013-2016. Findings suggest that adaptation to heat-health associations vary by greenness. Greenspace may help lower risks from heat but such health risks warrant continuous local efforts such as heat-health plans.
Cooling centers have played a significant role in reducing the risks of adverse health impacts of extreme heat exposure. However, there have been no comparative studies investigating cooling center preparedness in terms of population coverage, location efficiency, and population coverage disparities among different subpopulation groups. Using a catchment area method with a 0.8 km walking distance, we compared three aspects of cooling center preparedness across twenty-five cities in the U.S. We first calculated the percentage of the population covered by a single cooling center for each city. Then, the extracted values were separately compared to the city’s heat indexes, latitudes, and spatial patterns of cooling centers. Finally, we investigated population coverage disparities among multiple demographics (age, race/ethnicity) and socioeconomic (insurance, poverty) subpopulation groups by comparing the percentage of population coverage between selected subpopulation groups and reference subpopulation groups. Our results showed that cooler cities, higher latitude cities, and cities with dispersed cooling centers tend to be more prepared than warmer cities, lower latitude cities, and cities with clustered cooling centers across the U.S. Moreover, older people (≥65) had 9% lower population coverage than younger people (≤64). Our results suggest that the placement of future cooling centers should consider both the location of other nearby cooling centers and the spatial distribution of subpopulations to maximize population coverage and reduce access disparities among several subpopulations.
A wet-bulb temperature of 35°C has been theorized to be the limit to human adaptability to extreme heat, a growing concern in the face of continued and predicted accelerated climate change. Although this theorized threshold is based in physiological principles, it has not been tested using empirical data. This study examined the critical wet-bulb temperature (T(wb,crit)) at which heat stress becomes uncompensable in young, healthy adults performing tasks at modest metabolic rates mimicking basic activities of daily life. Across six experimentally determined environmental limits, no subject’s T(wb,crit) reached the 35°C limit and all means were significantly lower than the theoretical 35°C threshold. Mean T(wb,crit) values were relatively constant across 36°C -40°C humid environments and averaged 30.55 ± 0.98°C but progressively decreased (higher deviation from 35°C) in hotter, dry ambient environments. T(wb,crit) was significantly associated with mean skin temperature (and a faster warming rate of the skin) due to larger increases in dry heat gain in the hot-dry environments. As sweat rates did not significantly differ among experimental environments, evaporative cooling was outpaced by dry heat gain in hot-dry conditions, causing larger deviations from the theoretical 35°C adaptability threshold. In summary, a wet-bulb temperature threshold cannot be applied to human adaptability across all climatic conditions and where appropriate (high humidity), that threshold is well below 35°C.NEW & NOTEWORTHY This study is the first to use empirical physiological observations to examine the well-publicized theoretical 35°C wet-bulb temperature limit for human to extreme environments. We find that uncompensable heat stress in humid environments occurs in young, healthy adults at wet-bulb temperatures significantly lower than 35°C. In addition, uncompensable heat stress occurs at widely different wet-bulb temperatures as a function of ambient vapor pressure.
In this study, we examine how climatic heat stress can be mediated by green infrastructure outcomes and how energy justice effort contributes to health adaptation within the U.S. Great Lakes regions and their primary metropolitan areas over a recent 10-year period (2005–2015). Through the lens of policy innovation and the vulnerability-readiness nexus, we explore how climate policy intervention contributes to the mitigation of heat stress by using a quantitative approach. Empirical results suggest that green infrastructure outcomes and energy justice efforts have the potential to mitigate heat stress and enhance health adaptation. Additional results reflect that climate policy innovation and readiness efforts were viable factors in health adaptation to heat events.
OBJECTIVES: To derive an empirical model for the impact of aerobic fitness (maximal oxygen consumption; V̇O(2max) in mL∙kg(-1)∙min(-1)) on physical work capacity (PWC) in the heat. DESIGN: Prospective, repeated measures. METHODS: Total work completed during 1 h of treadmill walking at a fixed heart rate of 130 b∙min(-1) was assessed in 19 young adult males across a variety of warm and hot climate types, characterised by wet-bulb globe temperatures (WBGT) ranging from 12 to 40 °C. For data presentation and obtaining initial parameter estimates for modelling, participants were grouped into low (n = 6, 74 trials), moderate (n = 8, 76 trials), and high (n = 5, 29 trials) fitness, with group mean V̇O(2max) 42, 52, and 64 mL∙kg(-1)∙min(-1)(,) respectively. For the heated conditions (WBGT 18 to 40 °C), we calculated PWC% by expressing total energy expenditure (kJ above resting) in each trial relative to that achieved in a cool reference condition (WBGT = 12 °C = 100% PWC). RESULTS: The relative reduction in energy expenditure (PWC%) caused by heat was significantly smaller by up to 16% for the fit participants compared to those with lower aerobic capacity. V̇O(2max) also modulated the relationship between sweat rate and body temperature changes to increasing WBGT. Including individual V̇O(2max) data in the PWC prediction model increased the predicting power by 4%. CONCLUSIONS: Incorporating individual V̇O(2max) improved the predictive power of the heat stress index WBGT for Physical Work Capacity in the heat. The largest impact of V̇O(2max) on PWC was observed at a WBGT between 25 and 35 °C.
BACKGROUND: Latinx children in the United States are at high risk for nature-deficit disorder, heat-related illness, and physical inactivity. We developed the Green Schoolyards Project to investigate how green features-trees, gardens, and nature trails-in school parks impact heat index (i.e., air temperature and relative humidity) within parks, and physical activity levels and socioemotional well-being of these children. Herein, we present novel methods for a) observing children’s interaction with green features and b) measuring heat index and children’s behaviors in a natural setting, and a selection of baseline results. METHODS: During two September weeks (high temperature) and one November week (moderate temperature) in 2019, we examined three joint-use elementary school parks in Central Texas, United States, serving predominantly low-income Latinx families. To develop thermal profiles for each park, we installed 10 air temperature/relative humidity sensors per park, selecting sites based on land cover, land use, and even spatial coverage. We measured green features within a geographic information system. In a cross-sectional study, we used an adapted version of System for Observing Play and Recreation in Communities (SOPARC) to assess children’s physical activity levels and interactions with green features. In a cohort study, we equipped 30 3rd and 30 4th grade students per school during recess with accelerometers and Global Positioning System devices, and surveyed these students regarding their connection to nature. Baseline analyses included inverse distance weighting for thermal profiles and summing observed counts of children interacting with trees. RESULTS: In September 2019, average daily heat index ranged 2.0 °F among park sites, and maximum daily heat index ranged from 103.4 °F (air temperature = 33.8 °C; relative humidity = 55.2%) under tree canopy to 114.1 °F (air temperature = 37.9 °C; relative humidity = 45.2%) on an unshaded playground. 10.8% more girls and 25.4% more boys interacted with trees in September than in November. CONCLUSIONS: We found extreme heat conditions at select sites within parks, and children positioning themselves under trees during periods of high heat index. These methods can be used by public health researchers and practitioners to inform the redesign of greenspaces in the face of climate change and health inequities.
Concurrent with a rapid rise in temperatures within US cities, the frequency of regional electric grid system failures is also rising in recent decades, resulting in a growing number of blackouts during periods of extreme heat. As mechanical air conditioning is a primary adaptive technology for managing rising temperatures in cities, we examine in this paper the impact of a prolonged blackout on heat exposure in residential structures during heat wave conditions, when air conditioning is most critical to human health. Our approach combines a regional climate modeling system with a building energy model to simulate how a concurrent heat wave and grid failure event impacts residential building-interior temperatures across Phoenix. Our results find a substantial increase in heat exposure across residential buildings in response to the loss of electrical power and mechanical cooling systems, with such an event potentially exposing more than one million residents to hazardous levels of heat. We further find the installation of cool roofing to measurably lower the risk of extreme heat exposure for residents of single-story structures.
The urban heat island (UHI) effect is caused by intensive development practices in cities and the diminished presence of green space that results. The evolution of these phenomena has occurred over many decades. In many cities, historic zoning and redlining practices barred Black and minority groups from moving into predominately white areas and obtaining financial resources, a practice that still affects cities today, and has forced these already disadvantaged groups to live in some of the hottest areas. In this study, we used a new dataset on the spatial distribution of temperature during a heat wave in Richmond, Virginia to investigate potential associations between extreme heat and current and historical demographic, socioeconomic, and land use factors. We assessed these data at the census block level to determine if blocks with large differences in temperature also had significant variation in these covariates. The amount of canopy cover, percent impervious surface, and poverty level were all shown to be strong correlates of UHI when analyzed in conjunction with afternoon temperatures. We also found strong associations of historical policies and planning decisions with temperature using data from the University of Richmond’s Digital Scholarship Lab’s “Mapping Inequality” project. Finally, the Church Hill area of the city provided an interesting case study due to recent data suggesting the area’s gentrification. Differences in demographics, socioeconomic factors, and UHI were observed between north and (more gentrified) south Church Hill. Both in Church Hill and in Richmond overall, our research found that areas occupied by people of low socioeconomic status or minority groups disproportionately experienced extreme heat and corresponding impacts on health and quality of life.
Climate change-related natural disasters, including wildfires and extreme weather events, such as intense storms, floods, and heatwaves, are increasing in frequency and intensity. These events are already profoundly affecting human health in the United States and globally, challenging the ability of communities to prepare, respond, and recover. The purpose of this research was to examine the peer-reviewed literature on community resilience initiatives in one of the most densely populated and economically important regions, the Northeastern United States, and to identify evidence-based interventions and metrics that had been field-tested and evaluated. This paper addresses two critical gaps in the literature: (1) what strategies or interventions have been implemented to build or enhance community resilience against climate change-related natural disasters; and (2) what metrics were used to measure community resilience as an outcome of those strategies or interventions? This review provides a succinct list of effective interventions with specific health outcomes. Community or state-level health officials can use the results to prioritize public health interventions. This review used existing database search tools to discover 205 studies related to community resilience and health outcomes. Methods set criteria to assess if interventions were able to measure and change levels of community resilience to the health impacts associated with a changing climate. Criteria included: (a) alignment with the United States’ National Preparedness Goal for reducing risks to human health and for recovering quickly from disasters; (b) derived from publicly available data sources; (c) developed for use by communities at a local scale; and (d) accessible to modestly resourced municipalities and county health agencies. Five (5) peer-reviewed, evidence-based studies met all of the selection criteria. Three of these articles described intervention frameworks and two reported on the use of standardized tools. Health-related outcomes included mental health impacts (PTSD/depression), mental stress, emergency preparedness knowledge, social capital skills, and emergency planning skills. The paper recommends the COAST project, COPEWELL Rubric for self-assessment, and Ready CDC intervention as examples of strategies that could be adapted by any community engaged in building community resilience.
This study aims to estimate the impacts of climate variation on suicide rates in the USA by using county-level data on temperature, and mental health-related suicides between 2011 and 2020. In addition to climate factors, several socio-economic factors such as uninsured population rate, access to mental health providers, and unemployment rate are included to estimate their impacts on suicides. The estimation is separately performed for female, male and overall groups. The results indicate that while there is limited evidence of the impact of precipitation on suicidal behaviours, the average daily minimum air temperature is an important determinant of the suicides in the US counties.
IMPORTANCE: The implications of extreme heat for physical health outcomes have been well documented. However, the association between elevated ambient temperature and specific mental health conditions remains poorly understood. OBJECTIVE: To investigate the association between ambient heat and mental health-related emergency department (ED) visits in the contiguous US among adults overall and among potentially sensitive subgroups. DESIGN, SETTING, AND PARTICIPANTS: This case-crossover study used medical claims data obtained from OptumLabs Data Warehouse (OLDW) to identify claims for ED visits with a primary or secondary discharge psychiatric diagnosis during warm-season months (May to September) from 2010 through 2019. Claims for adults aged 18 years or older with commercial or Medicare Advantage health insurance who were living in 2775 US counties were included in the analysis. Emergency department visits were excluded if the Clinical Classifications Software code indicated that the visits were for screening for mental health outcomes and impulse control disorders. EXPOSURES: County-specific daily maximum ambient temperature on a continuous scale was estimated using the Parameter-Elevation Relationships on Independent Slopes model. Extreme heat was defined as the 95th percentile of the county-specific warm-season temperature distribution. MAIN OUTCOMES AND MEASURES: The daily incidence rate of cause-specific mental health diagnoses and a composite end point of any mental health diagnosis were assessed by identifying ED visit claims using primary and secondary discharge diagnosis International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes. Conditional logistic regression models were used to estimate the incidence rate ratio (IRR) and 95% CIs for the association between daily temperature and incidence rates of ED visits. RESULTS: Data from 3 496 762 ED visits among 2 243 395 unique individuals were identified (56.8% [1 274 456] women; mean [SD] age, 51.0 [18.8] years); of these individuals, 14.3% were aged 18 to 26 years, 25.6% were aged 27 to 44 years, 33.3% were aged 45 to 64 years, and 26.8% were aged 65 years or older. Days of extreme heat were associated with an IRR of 1.08 (95% CI, 1.07-1.09) for ED visits for any mental health condition. Associations between extreme heat and ED visits were found for specific mental health conditions, including substance use disorders (IRR, 1.08; 95% CI, 1.07-1.10); anxiety, stress-related, and somatoform disorders (IRR, 1.07; 95% CI, 1.05-1.09); mood disorders (IRR, 1.07; 95% CI, 1.05-1.09); schizophrenia, schizotypal, and delusional disorders (IRR, 1.05; 95% CI, 1.03-1.07); self-harm (IRR, 1.06; 95% CI, 1.01-1.12); and childhood-onset behavioral disorders (IRR, 1.11; 95% CI, 1.05-1.18). In addition, associations were higher among men (IRR, 1.10; 95% CI, 1.08-1.12) and in the US Northeast (IRR, 1.10; 95% CI, 1.07-1.13), Midwest (IRR, 1.11; 95% CI, 1.09-1.13), and Northwest (IRR, 1.12; 95% CI, 1.03-1.21) regions. CONCLUSIONS AND RELEVANCE: In this case-crossover study of a large population of US adults with health insurance, days of extreme heat were associated with higher rates of mental health-related ED visits. This finding may be informative for clinicians providing mental health services during periods of extreme heat to prepare for increases in health service needs when times of extreme heat are anticipated.
Maria made a landfall in Puerto Rico on September 20, 2017 as a category 4 hurricane, causing severe flooding, widespread electricity outages, damage to infrastructure, and interruptions in water and wastewater treatment. Small rural community water systems face unique challenges in providing drinking water, which intensify after natural disasters. The purpose of this study was to evaluate the functionality of six very small rural public water systems and one large regulated system in Puerto Rico six months after Maria and survey a broad sweep of fecal, zoonotic, and opportunistic pathogens from the source to tap. Samples were collected from surface and groundwater sources, after water treatment and after distribution to households. Genes indicative of pathogenic Leptospira spp. were detected by polymerase chain reaction (PCR) in all systems reliant on surface water sources. Salmonella spp. was detected in surface and groundwater sources and some distribution system water both by culture and PCR. Legionella spp. and Mycobacteria spp. gene numbers measured by quantitative PCR were similar to nonoutbreak conditions in the continental U.S. Amplicon sequencing provided a nontarget screen for other potential pathogens of concern. This study aids in improving future preparedness, assessment, and recovery operations for small rural water systems after natural disasters.
Hurricanes often flood homes and industries, spreading pathogens. Contact with pathogen-contaminated water can result in diarrhea, vomiting, and/or nausea, known collectively as acute gastrointestinal illness (AGI). Hurricanes Matthew and Florence caused record-breaking flooding in North Carolina (NC) in October 2016 and September 2018, respectively. To examine the relationship between hurricane flooding and AGI in NC, we first calculated the percent of each ZIP code flooded after Hurricanes Matthew and Florence. Rates of all-cause AGI emergency department (ED) visits were calculated from NC’s ED surveillance system data. Using controlled interrupted time series, we compared AGI ED visit rates during the three weeks after each hurricane in ZIP codes with a third or more of their area flooded to the predicted rates had these hurricanes not occurred, based on AGI 2016-2019 ED trends, and controlling for AGI ED visit rates in unflooded areas. We examined alternative case definitions (bacterial AGI) and effect measure modification by race and age. We observed an 11% increase (rate ratio (RR): 1.11, 95% CI: 1.00, 1.23) in AGI ED visit rates after Hurricanes Matthew and Florence. This effect was particularly strong among American Indian patients and patients aged 65 years and older after Florence and elevated among Black patients for both hurricanes. Florence’s effect was more consistent than Matthew’s effect, possibly because little rain preceded Florence and heavy rain preceded Matthew. When restricted to bacterial AGI, we found an 85% (RR: 1.85, 95% CI: 1.37, 2.34) increase in AGI ED visit rate after Florence, but no increase after Matthew. Hurricane flooding is associated with an increase in AGI ED visit rate, although the strength of effect may depend on total storm rainfall or antecedent rainfall. American Indians and Black people-historically pushed to less desirable, flood-prone land-may be at higher risk for AGI after storms.
BACKGROUND: While most prior research has focused on extreme heat, few assessed the immediate health effects of winter storms and associated power outages (PO), although severe storms have become more frequent. This study evaluates the joint and independent health effects of winter storms and PO, snow versus ice-storm, effects by time window (peak timing, winter/transitional months) and the impacts on critical care indicators including numbers of comorbidity, procedure, length of stay and cost. METHODS: We use distributed lag nonlinear models to assess the impacts of winter storm/PO on hospitalizations due to cardiovascular, lower respiratory diseases (LRD), respiratory infections, food/water-borne diseases (FWBD) and injuries in New York State on 0-6 lag days following storm/PO compared with non-storm/non-PO periods (references), while controlling for time-varying factors and PM(2.5). The storm-related hospitalizations are described by time window. We also calculate changes in critical care indicators between the storm/PO and control periods. RESULTS: We found the joint effects of storm/PO are the strongest (risk ratios (RR) range: 1.01-1.90), followed by that of storm alone (1.02-1.39), but not during PO alone. Ice storms have stronger impacts (RRs: 1.04-3.15) than snowstorms (RRs: 1.03-2.21). The storm/PO-health associations, which occur immediately, and some last a whole week, are stronger in FWBD, October/November, and peak between 3:00-8:00 p.m. Comorbidity and medical costs significantly increase after storm/PO. CONCLUSION: Winter storms increase multiple diseases, comorbidity and medical costs, especially when accompanied by PO or ice storms. Early warnings and prevention may be critical in the transitional months and afternoon rush hours.
BACKGROUND: Drought represents a globally relevant natural disaster linked to adverse health. Evidence has shown agricultural communities to be particularly susceptible to drought, but there is a limited understanding of how drought may impact occupational stress in farmers. METHODS: We used repeated measures data collected in the Musculoskeletal Symptoms among Agricultural Workers Cohort study, including 498 Midwestern U.S. farmers surveyed with a Job Content Questionnaire (JCQ) at six-month intervals in 312 counties from 2012 through 2015. A longitudinal linear mixed effects model was used to estimate the change in job strain ratio, a continuous metric of occupational psychosocial stress, during drought conditions measured with a 12-month standardized precipitation index. We further evaluated associations between drought and psychological job demand and job decision latitude, the job strain components, and applied a stratified analysis to evaluate differences by participant sex, age, and geography. RESULTS: During the growing season, the job strain ratio increased by 0.031 (95% CI: 0.012, 0.05) during drought conditions, an amount equivalent to a one-half standard deviation change (Cohen’s D = 0.5), compared to non-drought conditions. The association between drought and the job strain ratio was driven mostly by increases in the psychological job demand (2.09; 95% CI: 0.94, 3.24). No risk differences were observed by sex, age group, or geographic region. CONCLUSIONS: Our results suggest a previously unidentified association between drought and increased occupational psychosocial stress among farmers. With North American climate anticipated to become hotter and drier, these findings could provide important health effects data for federal drought early warning systems and mitigation plans.
This study assesses the potential impact of drought on arsenic exposure from private domestic wells by using a previously developed statistical model that predicts the probability of elevated arsenic concentrations (>10 μg per liter) in water from domestic wells located in the conterminous United States (CONUS). The application of the model to simulate drought conditions used systematically reduced precipitation and recharge values. The drought conditions resulted in higher probabilities of elevated arsenic throughout most of the CONUS. While the increase in the probability of elevated arsenic was generally less than 10% at any one location, when considered over the entire CONUS, the increase has considerable public health implications. The population exposed to elevated arsenic from domestic wells was estimated to increase from approximately 2.7 million to 4.1 million people during drought. The model was also run using total annual precipitation and groundwater recharge values from the year 2012 when drought existed over a large extent of the CONUS. This simulation provided a method for comparing the duration of drought to changes in the predicted probability of high arsenic in domestic wells. These results suggest that the probability of exposure to arsenic concentrations greater than 10 μg per liter increases with increasing duration of drought. These findings indicate that drought has a potentially adverse impact on the arsenic hazard from domestic wells throughout the CONUS.
As is the case for many semi-arid regions globally, drought in the Intermountain West of the United States is a recurrent, costly phenomenon that leaves few aspects of human and natural systems untouched. Here, we focus on drought impact data and evaluation challenges across four non-agricultural sectors: water utilities, forest resources, public health, and recreation and tourism. There are marked commonalities in the way drought indicators-that is, hydrometeorological conditions-are tracked, but considerable differences in how impacts are measured, evaluated, and disseminated. For drought indicator data, researchers and practitioners have a veritable smorgasbord of data at their fingertips. Such data are often spatially and temporally continuous, available at a wide variety of scales, and readily accessible through government-funded online portals. This is in stark contrast to drought impact data, which are typically collected opportunistically, if at all. These data are thus often limited in spatiotemporal scope and difficult to access relative to drought indicators. Concerningly, even within a given sector, the definition of drought impacts, quantitative or otherwise, can vary considerably, making it difficult to evaluate the true cost of drought. Far from being specific to the Intermountain West, these problems are found in most regions experiencing drought. We suggest such challenges are surmountable through the development of a common drought impact framework based around economic damages and purposeful, continuous, government-funded drought impact data collection. These tractable changes will allow for a better quantification of drought’s true impacts under both present conditions and climate change scenarios in the Intermountain West and beyond. This article is categorized under: Human Water > Value of Water Science of Water > Water Extremes Water and Life > Stresses and Pressures on Ecosystems
BACKGROUND: Climate change will increase drought duration and severity in many regions around the world, including the Central Plains of North America. However, studies on drought-related health impacts are still sparse. This study aims to explore the potential associations between drought and all-cause mortality in Nebraska from 1980 to 2014. METHODS: The Evaporative Demand Drought Index (EDDI) were used to define short-, medium- and long-term drought exposures, respectively. We used a Bayesian zero-inflated censored negative binomial (ZICNB) regression model to estimate the overall association between drought and annual mortality first in the total population and second in stratified sub-populations based on age, race, sex, and the urbanicity class of the counties. RESULTS: The main findings indicate that there is a slightly negative association between all-cause mortality and all types of droughts in the total population, though the effect is statistically null. The joint-stratified analysis renders significant results for a few sub-groups. White population aged 25-34 and 45-64 in metro counties and 45-54 in non-metro counties were the population more at risk in Nebraska. No positive associations were observed in any race besides white. Black males aged 20-24 and white females older than 85 showed protective effect against drought mainly in metro counties. We also found that more sub-populations had higher rates of mortality with longer-term droughts compared to shorter-term droughts (12-month vs 1- or 6-month timescales), in both metro and non-metro counties, collectively. CONCLUSION: Our results suggest that mortality in middle aged white population in Nebraska shows a greater association with drought. Moreover, women aged 45-54 were more affected than men in non-metro counties. With a projected increase in the frequency and severity of drought due to climate change, understanding these relationships between drought and human health will better inform drought mitigation planning to reduce potential impacts.
The outcomes of drought can be difficult to assess due to the complexity of its effects. While most risk assessments of drought are developed for agriculture or water resources, the associations with human health are not well studied due to unclear and complex pathways. This study is the first to assess potential changes in health risk from droughts during the last decade in the contiguous United States. To assess the risk, we spatially superimposed vulnerability variables associated with drought on historical drought exposure over the last decade. Different variations in Local Moran’s I statistics were used to assess the spatial distribution of health vulnerability, risk of drought, and changes in the two five-year study periods (2010-2014 and 2015-2019). Our results show large clusters of the western United States had a significant increase in risk during the latter part of the study period due to increases in vulnerability and hazard. In addition, southern areas of the United States were consistently above the national average in drought risk. Since our vulnerability variables include agriculture, drinking water, and sociodemographic indicators, the results of this study can help various experts interested in drought preparedness efforts associated with human health.
As global warming impacts the climate, severe cases of droughts, abnormalities in precipitations, unusual patterns of hurricanes, and excessive heat are becoming more frequent. Excessive heat and droughts in US have made dehydration a problem on construction job sites. Despite the studies about the efficient use of water in buildings post occupancy, little has been explored about water consumption during the construction phase. Given this lack of focus, this study investigates drinking water consumption by construction personnel during construction of a new academic building located in Fort Myers, Florida. Daily potable water consumption data on a jobsite have been recorded during construction through daily interviews with site personnel. Regression analysis is used to examine the existence of correlations between daily humidity, temperature and precipitation data, and daily drinking water consumption by each construction worker. An artificial neural network model is also deployed to examine the existence of such a link.
The impacts of climate change on agricultural production are a global concern and have already begun to occur (Kawasaki 2018 Am. J. Agric. Econ. 101 172-92; Ortiz-Bobea et al 2021 Nat. Clim. Change 11 306-12), with major drivers including warmer temperatures and the occurrence of extreme weather events (Lobell and Field 2007 Environ. Res. Lett. 2 014002; Challinor et al 2014 Nat. Clim. Change 4 287; Rosenzweig et al 2001 Glob. Change Hum. Health 2 90-104; Schlenker and Roberts 2009 Proc. Natl Acad. Sci. USA 106 15594-8; Lobell et al 2014 Science 344 516-9; Ortiz-Bobea et al 2019 Environ. Res. Lett. 14 064003). An important dimension of the climate change-crop yield relationship that has often been overlooked in the empirical literature is the influence that warming temperatures can have on plant damage arriving through biotic channels, such as pest infestation or fungal infection (Rosenzweig et al 2001 Glob. Change Hum. Health 2 90-104). Aflatoxins are carcinogenic chemicals produced by the fungi Aspergillus flavus and A. parasiticus, which commonly infect food crops. Currently, in the United States, aflatoxin is a perennial contaminant in corn grown in the South, but rare in the Corn Belt and northern states. Climate change may expand aflatoxin’s geographical prevalence, however; because hot, dry summers promote aflatoxin accumulation. Here we model aflatoxin risk as a function of corn plant growth stages and weather to predict US regions with high aflatoxin risk in 2031-2040, based on 16 climate change models. Our results suggest that over 89.5% of corn-growing counties in 15 states, including the Corn Belt, will experience increased aflatoxin contamination in 2031-2040 compared to 2011-2020. Interestingly, the results are spatially heterogeneous and include several southern counties expected to have lower aflatoxin risk, because the causative fungi become inactivated at very high temperatures.
Global climate change has increased the risks of extreme weather-related disasters, leading to severe public health burdens. In February 2021, Winter Storm Uri brought severe cold to southern United States and caused unprecedented health and safety concerns. Residents in subsidized rental housing were among the most vulnerable to cold stress during such a cold storm. However, existing research on the assessment and mitigation of cold stress in underserved neighborhoods in warmer climate zones is limited, which results in the negligence of cold event preparedness and mitigation policies. Therefore, this study aims to assess the micrometeorological conditions and human cold stress in subsidized housing neighborhoods during the 2021 Winter Storm and determine the extent to which cold mitigation windbreak designs are effective in reducing cold stress. Field measurements, ENVI-met simulations, and biometeorological calculations were conducted to reconstruct the microclimate conditions and cold stress during the storm, and three cold-mitigation windbreak designs with varying foliage densities were evaluated. Results showed that the conditions were categorized as extreme cold stress for the majority of the day, but especially during nighttime. Areas close to the buildings were generally warmer, and the wind-blocking effects of a building decreased as the distance to the building increased. A moderately dense-foliage windbreak was the most effective in reducing wind speed and improving thermal comfort. Intentional environmental modifications to alter wind velocity and disaster relief programs that provide emergency clothing supplies during power outage may be beneficial to these underserved communities.
BACKGROUND: Acute coronary syndrome (ACS) is affected by several weather conditions. Studies from different geographical locations have yielded mixed results regarding the outcomes of patients presenting with ACS during snowy days, and we aim to report the Cleveland Clinic experience. METHODS: Patients who presented with an ACS and underwent percutaneous coronary intervention (PCI) from July 1, 2009 to September 30, 2017 were divided into ST-segment elevation myocardial infarction (STEMI), and non-ST segment elevation ACS (NSTE-ACS). According to snowy day arrival, we compared in-hospital mortality, culprit lesion anatomy, and door-to-balloon (DTB) time (in STEMI patients). Findings were confirmed in propensity-score matched cohorts. RESULTS: A total of 6878 patients were included: 1608 patients with STEMI (139 snowy-day vs 1469 non-snowy day PCIs) and 5270 NSTE-ACS (419 snowy-day vs 4851 non-snowy day PCIs). Right coronary artery territories accounted for most of the stented culprit lesions in all STEMI and NSTE-ACS snowy-day PCIs. While left anterior descending artery lesions were predominant in NSTE-ACS non-snowy day PCIs. There was no difference in in-hospital mortality between the snowy-day vs non-snowy day groups (4.3% vs 4.5% in the STEMI group [P=.92] and 1.2% vs 1.7% in the NSTE-ACS group [P=41]). In STEMI patients, mean DTB times were similar (43 ± 55.1 minutes vs 46.7 ± 59.6 minutes; P=.61), which remained true after hours, during weekends and holidays. Outcomes were similar in propensity-score matched cohorts. CONCLUSION: At our institution, snowy days do not seem to affect in-patient mortality. In STEMI patients, DTB times were similar in those who underwent PCI regardless of the snowfall.
Health researchers have examined the physiological impacts of extreme air temperature on the human body. Yet, the mental health impacts of temperature have been understudied. Research has shown that the environment can create circumstances that exacerbate mental health issues. This may be particularly challenging for some of the fastest growing cities, located in hot, dry climates. Given the theoretical relationship between air temperature and mental health, we seek to measure the association between temperature and schizophrenia hospital admissions in an arid urban climate and quantify the associated public health burden. We collected 86,672 hospitalization records for schizophrenia from 2006 to 2014 in Maricopa County, Arizona, USA. Using a distributed lag non-linear model (DLNM), we tested for a statistical association between temperature and schizophrenia hospital admissions after controlling for year, season, weekends, and holidays. We calculated the cumulative attributable risk of nighttime temperature on schizophrenia for the entire dataset as well as among demographic subgroups. The relative risk of schizophrenia hospital admissions increased with both high and low temperatures. Statistical models using daily minimum temperature were more strongly associated with hospitalization than those using mean or maximum. Schizophrenia hospital admissions increased on days with minimum temperatures above 30 °C and below 3 °C, with some subgroups experiencing higher rates of hospitalization. The total fraction of schizophrenia hospital admissions attributable to non-optimal minimum temperature is 3.45 % (CI: -4.91-10.80 %) and high minimum temperature is 0.28 % (CI: -1.18-1.78 %). We found that non-whites and males appear to be at a slightly increased risk than the general population, although there did not appear to be a statistically significant difference. A conservative estimate of healthcare costs annually from non-optimal temperature attributed schizophrenia hospitalization is $1.95 million USD. Therefore, nighttime cooling strategies and efforts could increase the accessibility of shelters to reduce overnight exposure to extreme air temperature.
BACKGROUND: Health disparities exist between urban and rural populations, yet research on rural-urban disparities in temperature-mortality relationships is limited. As inequality in the United States increases, understanding urban-rural and regional differences in the temperature-mortality association is crucial. OBJECTIVE: We examined regional and urban-rural differences of the temperature-mortality association in North Carolina (NC), USA, and investigated potential effect modifiers. METHODS: We applied time-series models allowing nonlinear temperature-mortality associations for 17 years (2000-2016) to generate heat and cold county-specific estimates. We used second-stage analysis to quantify the overall effects. We also explored potential effect modifiers (e.g. social associations, greenness) using stratified analysis. The analysis considered relative effects (comparing risks at 99th to 90th temperature percentiles based on county-specific temperature distributions for heat, and 1st to 10th percentiles for cold) and absolute effects (comparing risks at specific temperatures). RESULTS: We found null effects for heat-related mortality (relative effect: 1.001 (95% CI: 0.995-1.007)). Overall cold-mortality risk for relative effects was 1.019 (1.015-1.023). All three regions had statistically significant cold-related mortality risks for relative and absolute effects (relative effect: 1.019 (1.010-1.027) for Coastal Plains, 1.021 (1.015-1.027) for Piedmont, 1.014 (1.006-1.023) for Mountains). The heat mortality risk was not statistically significant, whereas the cold mortality risk was statistically significant, showing higher cold-mortality risks in urban areas than rural areas (relative effect for heat: 1.006 (0.997-1.016) for urban, 1.002 (0.988-1.017) for rural areas; relative effect for cold: 1.023 (1.017-1.030) for urban, 1.012 (1.001-1.023) for rural areas). Findings are suggestive of higher relative cold risks in counties with the less social association, higher population density, less green-space, higher PM(2.5,) lower education level, higher residential segregation, higher income inequality, and higher income (e.g., Ratio of Relative Risks 1.72 (0.68, 4.35) comparing low to high education). CONCLUSION: Results indicate cold-mortality risks in NC, with potential differences by regional, urban-rural areas, and community characteristics.
BACKGROUND: Accurate and precise estimates of ambient air temperatures that can capture fine-scale within-day variability are necessary for studies of air temperature and health. METHOD: We developed statistical models to predict temperature at each hour in each cell of a 927-m square grid across the Northeast and Mid-Atlantic United States from 2003 to 2019, across ~4000 meteorological stations from the Integrated Mesonet, using inputs such as elevation, an inverse-distance-weighted interpolation of temperature, and satellite-based vegetation and land surface temperature. We used a rigorous spatial cross-validation scheme and spatially weighted the errors to estimate how well model predictions would generalize to new cell-days. We assess the within-county association of temperature and social vulnerability in a heat wave as an example application. RESULTS: We found that a model based on the XGBoost machine-learning algorithm was fast and accurate, obtaining weighted root mean square errors (RMSEs) around 1.6 K, compared to standard deviations around 11.0 K. We found similar accuracy when validating our model on an external dataset from Weather Underground. Assessing predictions from the North American Land Data Assimilation System-2 (NLDAS-2), another hourly model, in the same way, we found it was much less accurate, with RMSEs around 2.5 K. This is likely due to the NLDAS-2 model’s coarser spatial resolution, and the dynamic variability of temperature within its grid cells. Finally, we demonstrated the health relevance of our model by showing that our temperature estimates were associated with social vulnerability across the region during a heat wave, whereas the NLDAS-2 showed a much weaker association. CONCLUSION: Our high spatiotemporal resolution air temperature model provides a strong contribution for future health studies in this region.
BACKGROUND: Older adults are particularly vulnerable to the adverse health effects of extreme temperature-related events. A growing body of literature highlights the importance of the natural environment, including air pollution and sunlight, on cognitive health. However, the relationship between exposure to outdoor temperatures and cognitive functioning, and whether there exists any differences across climate region, remains largely unexplored. We address this gap by examining the temperature-cognition association, and whether there exists any variation across climate regions in a national cohort of aging adults. METHODS: In this cross-sectional study, we obtained data on temperature exposure based on geocoded residential location of participants in the REasons for Geographic And Racial Differences in Stroke (REGARDS) study. For each participant, this information was linked to their cognitive scores from Word List Learning and Recall tests to assess cognitive functioning. We used distributed lag non-linear models (dlnm) to model temperature effects over 2 days. Multivariable linear regression was used to compute temperature-cognitive functioning associations, adjusted for important covariates. Region-specific (“Dry”, “Mediterranean/oceanic”, “Tropical” and “Continental”) associations were examined by including an interaction term between climate region and temperature. RESULTS: Amongst 20,687 individuals (mean age = 67.8; standard deviation = 9.2), exposure to region-specific extreme cold temperatures in the “dry” region (e.g., Arizona) over 2 days was associated with lower cognitive scores (Mean Difference [MD]: -0.76, 95% Confidence Interval [CI]: - 1.45, - 0.07). Associations remained significant for cumulative effects of temperature over 2 days. Extremely cold exposure in the “Mediterranean/oceanic” region (e.g., California) over 2 days was also associated with significantly lower cognitive performance (MD: -0.25, 95% CI: - 0.47, - 0.04). No significant associations were observed for exposure to hot temperatures. Cognitive performance was slightly higher in late summer and fall compared to early summer. CONCLUSION: We noted adverse cognitive associations with cold temperatures in traditionally warmer regions of the country and improved cognition in summer and early fall seasons. While we did not observe very large significant associations, this study deepens understanding of the impact of climate change on the cognitive health of aging adults and can inform clinical care and public health preparedness plans.
BACKGROUND: Extreme heat exposure can lead to premature death. Climate change is expected to increase the frequency, intensity, and duration of extreme heat events, resulting in many additional heat-related deaths globally, as well as changing the nature of extreme cold events. At the same time, vulnerability to extreme heat has decreased over time, probably due to a combination of physiological, behavioural, infrastructural, and technological adaptations. We aimed to account for these changes in vulnerability and avoid overstated projections for temperature-related mortality. We used the historical observed decrease in vulnerability to improve future mortality estimates. METHODS: We used historical mortality and temperature data from 208 US cities to quantify how observed changes in vulnerability from 1973 to 2013 affected projections of temperature-related mortality under various climate scenarios. We used geographically structured meta-regression to characterise the relationship between temperature and mortality for these urban populations over the specified time period. We then used the fitted relationships to project mortality under future climate conditions. FINDINGS: Between Oct 26, 2018, and March 9, 2020, we established that differences in vulnerability to temperature were geographically structured. Vulnerability decreased over time in most areas. US mortalities projected from a 2°C increase in mean temperature decreased by more than 97% when using 2003-13 data compared with 1973-82 data. However, these benefits declined with increasing temperatures, with a 6°C increase showing only an 84% decline in projected mortality based on 2003-13 data. INTERPRETATION: Even after accounting for adaptation, the projected effects of climate change on premature mortality constitute a substantial public health risk. Our work suggests large increases in temperature will require additional mitigation to avoid excess mortality from heat events, even in areas with high air conditioning coverage in place. FUNDING: The US Environmental Protection Agency and Abt Associates.
Aedes aegypti mosquitoes are the main vector of dengue viruses globally and are present throughout much of the state of Florida (FL) in the United States of America. However, local transmission of dengue viruses in FL has mainly occurred in the southernmost counties; specifically Monroe and Miami-Dade counties. To get a better understanding of the ecologic risk factors for dengue fever incidence throughout FL, we collected and analyzed numerous environmental factors that have previously been connected to local dengue cases in disease-endemic regions. We analyzed these factors for each county-year in FL, between 2009-2019, using negative binomial regression. Monthly minimum temperature of 17.5-20.8 °C, an average temperature of 26.1-26.7 °C, a maximum temperature of 33.6-34.7 °C, rainfall between 11.4-12.7 cm, and increasing numbers of imported dengue cases were associated with the highest risk of dengue incidence per county-year. To our knowledge, we have developed the first predictive model for dengue fever incidence in FL counties and our findings provide critical information about weather conditions that could increase the risk for dengue outbreaks as well as the important contribution of imported dengue cases to local establishment of the virus in Ae. aegypti populations.
Rodents can transmit infectious diseases directly to humans and other animals via bites and exposure to infectious salivary aerosols and excreta. Arthropods infected while blood-feeding on rodents can also transmit rodent-borne pathogens indirectly to humans and animals. Environmental events, such as wet winters, cooler summers, heavy rains, and flooding, have precipitated regional rodent-borne infectious disease outbreaks; these outbreaks are now increasing with climate change. The objectives of this review are to inform wilderness medicine providers about the environmental conditions that can precipitate rodent-borne infectious disease outbreaks; to describe the regional geographic distributions of rodent-borne infectious diseases in North America; and to recommend prophylactic treatments and effective prevention and control strategies for rodent-borne infectious diseases. To meet these objectives, Internet search engines were queried with keywords to identify scientific articles on outbreaks of the most common regional rodent-borne infectious diseases in North America. Wilderness medicine providers should maintain high levels of suspicion for regional rodent-borne diseases in patients who develop febrile illnesses after exposure to contaminated freshwater after heavy rains or floods and after swimming, rafting, or paddling in endemic areas. Public health education strategies should encourage limiting human contact with rodents; avoiding contact with or safely disposing of rodent excreta; avoiding contact with contaminated floodwaters, especially contact with open wounds; securely containing outdoor food stores; and modifying wilderness cabins and campsites to deter rodent colonization.
Amblyomma maculatum (Gulf Coast tick), and Dermacentor andersoni (Rocky Mountain wood tick) are two North American ticks that transmit spotted fevers associated Rickettsia. Amblyomma maculatum transmits Rickettsia parkeri and Francisella tularensis, while D. andersoni transmits R. rickettsii, Anaplasma marginale, Coltivirus (Colorado tick fever virus), and F. tularensis. Increases in temperature causes mild winters and more extreme dry periods during summers, which will affect tick populations in unknown ways. Here, we used ecological niche modeling (ENM) to assess the potential geographic distributions of these two medically important vector species in North America under current condition and then transfer those models to the future under different future climate scenarios with special interest in highlighting new potential expansion areas. Current model predictions for A. maculatum showed suitable areas across the southern and Midwest United States, and east coast, western and southern Mexico. For D. andersoni, our models showed broad suitable areas across northwestern United States. New potential for range expansions was anticipated for both tick species northward in response to climate change, extending across the Midwest and New England for A. maculatum, and still farther north into Canada for D. andersoni.
Aedes aegypti and Aedes albopictus are important pathogen-carrying vectors that broadly exhibit similar habitat suitability, but that differ at fine spatial scales in terms of competitive advantage and tolerance to urban driven environmental parameters. This study evaluated how spatial and temporal patterns drive the assemblages of these competing species in cemeteries of New Orleans, LA, applying indicators of climatic variability, vegetation, and heat that may drive habitat selection at multiple scales. We found that Ae. aegypti was well predicted by urban heat islands (UHI) at the cemetery scale and by canopy cover directly above the cemetery vase. As predicted, UHI positively correlate to Ae. aegypti, but contrary to predictions, Ae. aegypti, was more often found under the canopy of trees in high heat cemeteries. Ae. albopictus was most often found in low heat cemeteries, but this relationship was not statistically significant, and their overall abundances in the city were lower than Ae. aegypti. Culex quinquefasciatus, another important disease vector, was also an abundant mosquito species during the sampling year, but we found that it was temporally segregated from Aedes species, showing a negative association to the climatic variables of maximum and minimum temperature, and these factors positively correlated to its more direct competitor Ae. albopictus. These findings help us understand the mechanism by which these three important vectors segregate both spatially and temporally across the city. Our study found that UHI at the cemetery scale was highly predictive of Ae. aegypti and strongly correlated to income level, with low-income cemeteries having higher UHI levels. Therefore, the effect of excessive heat, and the proliferation of the highly competent mosquito vector, Ae. aegypti, may represent an unequal disease burden for low-income neighborhoods of New Orleans that should be explored further. Our study highlights the importance of considering socioeconomic aspects as indirectly shaping spatial segregation dynamics of urban mosquito species.
Ixodes cookei Packard, the groundhog tick or woodchuck tick, is the main known vector of Powassan virus (POWV) disease in North America and an ectoparasite that infests diverse small- and mid-size mammals for blood meals to complete its life stages. Since I. cookei spends much of its life cycle off the host and needs hosts for a blood meal in order to pass to the next life stage, it is susceptible to changes in environmental conditions. We used a maximum-entropy approach to ecological niche modeling that incorporates detailed model-selection routes to link occurrence data to climatic variables to assess the potential geographic distribution of I. cookei under current and likely future climate conditions. Our models identified suitable areas in the eastern United States, from Tennessee and North Carolina north to southern Canada, including Nova Scotia, New Brunswick, eastern Newfoundland and Labrador, southern Quebec, and Ontario; suitable areas were also in western states, including Washington and Oregon and restricted areas of northern Idaho, northwestern Montana, and adjacent British Columbia, in Canada. This study produces the first maps of the potential geographic distribution of I. cookei. Documented POWV cases overlapped with suitable areas in the northeastern states; however, the presence of this disease in areas classified by our models as not suitable by our models but with POWV cases (Minnesota and North Dakota) requires more study.
How weather affects tick development and behavior and human Lyme disease remains poorly understood. We evaluated relations of temperature and humidity during critical periods for the tick lifecycle with human Lyme disease. We used electronic health records from 479,344 primary care patients in 38 Pennsylvania counties in 2006-2014. Lyme disease cases (n = 9657) were frequency-matched (5:1) by year, age, and sex. Using daily weather data at ~4 km(2) resolution, we created cumulative metrics hypothesized to promote (warm and humid) or inhibit (hot and dry) tick development or host-seeking during nymph development (March 1-May 31), nymph activity (May 1-July 30), and prior year larva activity (Aug 1-Sept 30). We estimated odds ratios (ORs) of Lyme disease by quartiles of each weather variable, adjusting for demographic, clinical, and other weather variables. Exposure-response patterns were observed for higher cumulative same-year temperature, humidity, and hot and dry days (nymph-relevant), and prior year hot and dry days (larva-relevant), with same-year hot and dry days showing the strongest association (4th vs. 1st quartile OR = 0.40; 95% confidence interval [CI] = 0.36, 0.43). Changing temperature and humidity could increase or decrease human Lyme disease risk.
Climate change is already impacting the North American Great Lakes ecosystem and understanding the relationship between climate events and public health, such as waterborne acute gastrointestinal illnesses (AGIs), can help inform needed adaptive capacity for drinking water systems (DWSs). In this study, we assessed a harmonized binational dataset for the effects of extreme precipitation events (≥90th percentile) and preceding dry periods, source water turbidity, total coliforms, and protozoan AGIs – cryptosporidiosis and giardiasis – in the populations served by four DWSs that source surface water from Lake Ontario (Hamilton and Toronto, Ontario, Canada) and Lake Michigan (Green Bay and Milwaukee, Wisconsin, USA) from January 2009 through August 2014. We used distributed lag non-linear Poisson regression models adjusted for seasonality and found extreme precipitation weeks preceded by dry periods increased the relative risk of protozoan AGI after 1 and 3-5 weeks in three of the four cities, although only statistically significant in two. Our results suggest that the risk of protozoan AGI increases with extreme precipitation preceded by a dry period. As extreme precipitation patterns become more frequent with climate change, the ability to detect changes in water quality and effectively treat source water of varying quality is increasingly important for adaptive capacity and protection of public health.
With a focus on five sites in an impaired, densely populated area in the New Orleans area, we investigated the temporal and spatial variability of standard FIB and a marker of human-associated pollution (Bacteroides HF183). With all sites combined, only a weak positive correlation (r = 0.345; p = 0.001) was observed between E. coli and HF183. Also, specific conductivity (r = - 0.374; p < 0.0001) and dissolved oxygen (r = - 0.390; p < 0.0001) were observed to show a weak moderate correlation with E. coli. These correlations increased to moderately negative when HF183 was correlated with specific conductivity (r = - 0.448; p < 0.0001) and dissolved oxygen (r = - 0.455; p < 0.0001). E. coli contamination was generally highest at the sites in the canal that are situated in the most densely populated part of the watershed while HF183 was frequently detected across all sites. E. coli concentrations were significantly higher (p < 0.05) when HF183 was present. HF183 was detected at significantly higher concentrations in samples that exceeded the EPA water quality standard (WQS) than those that did not (p < 0.05). Dissolved oxygen and specific conductivity were significantly lower when E. coli WQS was exceeded or when HF183 was present (p < 0.05). Rainfall impacted E. coli concentrations and HF183 differently at the study sites. While HF183 and E. coli concentrations levels were significantly higher (p < 0.05) if the days prior to sampling had been wet, the frequency of detection of HF183 was unimpacted, as comparable detection rates were recorded during wet and dry weather conditions. Without testing for HF183, it would have been assumed, based on testing for E. coli alone, that human fecal pollution was only associated with densely populated areas and rainfall events. E. coli alone may not be an effective indicator of sewage pollution at the study sites across all weather conditions and may need to be complemented with HF183 enumeration to optimize human fecal pollution identification and management at the watershed level.
Despite the widely acknowledged public health impacts of surface water fecal contamination, there is limited understanding of seasonal effects on (i) fate and transport processes and (ii) the mechanisms by which they contribute to water quality impairment. Quantifying relationships between land use, chemical parameters, and fecal bacterial concentrations in watersheds can help guide the monitoring and control of microbial water quality and explain seasonal differences. The goals of this study were to (i) identify seasonal differences in Escherichia coli and Bacteroides thetaiotaomicron concentrations, (ii) evaluate environmental drivers influencing microbial contamination during baseflow, snowmelt, and summer rain seasons, and (iii) relate seasonal changes in B. thetaiotaomicron to anticipated gastrointestinal infection risks. Water chemistry data collected during three hydroclimatic seasons from 64 Michigan watersheds were analyzed using seasonal linear regression models with candidate variables including crop and land use proportions, prior precipitation, chemical parameters, and variables related to both wastewater treatment and septic usage. Adaptive least absolute shrinkage and selection operator (LASSO) linear regression with bootstrapping was used to select explanatory variables and estimate coefficients. Regardless of season, wastewater treatment plant and septic system usage were consistently selected in all primary models for B. thetaiotaomicron and E. coli. Chemistry and precipitation-related variable selection depended upon season and organism. These results suggest a link between human pollution (e.g., septic systems) and microbial water quality that is dependent on flow regime. IMPORTANCE In this study, a data set of 64 Michigan watersheds was utilized to gain insights into fecal contamination sources, drivers, and chemical correlates across seasons for general E. coli and human-specific fecal indicators. Results reaffirmed a link between human-specific sources (e.g., septic systems) and microbial water quality. While the importance of human sources of fecal contamination and fate and transport variables (e.g., precipitation) remain important across seasons, this study provides evidence that fate and transport mechanisms vary with seasonal hydrologic condition and microorganism source. This study contributes to a body of research that informs prioritization of fecal contamination source control and surveillance strategy development to reduce the public health burden of surface water fecal contamination.
Vibrio vulnificus is an opportunistic pathogen indigenous to estuarine and marine environments and associated with aquatic organisms. Vibrio vulnificus is of utmost importance because it causes 95% of the seafood-related deaths in the United States due to rapid progression of septicemia. Changes in environmental parameters associated with climate change and coastal population expansion are altering geographical constraints, resulting in increased Vibrio spread, exposure, and rates of infection. In addition, coastal population expansion is resulting in increased input of treated municipal sewage into areas that are also experiencing increased Vibrio proliferation. This study aimed to better understand the influence of treated sewage effluent on effluent-receiving microbial communities using Vibrio as a model of an opportunistic pathogen. Integrated transcriptomic approaches were used to analyze the changes in overall gene expression of V. vulnificus NBRC 15645 exposed to wastewater treatment plant (WWTP) effluent for a period of 6h using a modified seawater yeast extract media that contained 0, 50, and 100% filtered WWTP effluent. RNA-seq reads were mapped, annotated, and analyzed to identify differentially expressed genes using the Pathosystems Resource Integration Center analysis tool. The study revealed that V. vulnificus responds to wastewater effluent exposure by activating cyclic-di-GMP-influenced biofilm development. Also, genes involved in crucial functions, such as nitrogen metabolism and bacterial attachment, were upregulated depending on the presence of treated municipal sewage. This altered gene expression increased V. vulnificus growth and proliferation and enhanced genes and pathways involved in bacterial survival during the early stages of infection in a host. These factors represent a potential public health risk due to exposure to environmental reservoirs of potentially Vibrio strains with enhanced virulence profiles in coastal areas.
Low elevation coastal zones (LECZ) are extensive throughout the southeastern United States. LECZ communities are threatened by inundation from sea level rise, storm surge, wetland degradation, land subsidence, and hydrological flooding. Communication among scientists, stakeholders, policy makers and minority and poor residents must improve. We must predict processes spanning the ecological, physical, social, and health sciences. Communities need to address linkages of (1) human and socioeconomic vulnerabilities; (2) public health and safety; (3) economic concerns; (4) land loss; (5) wetland threats; and (6) coastal inundation. Essential capabilities must include a network to assemble and distribute data and model code to assess risk and its causes, support adaptive management, and improve the resiliency of communities. Better communication of information and understanding among residents and officials is essential. Here we review recent background literature on these matters and offer recommendations for integrating natural and social sciences. We advocate for a cyber-network of scientists, modelers, engineers, educators, and stakeholders from academia, federal state and local agencies, non-governmental organizations, residents, and the private sector. Our vision is to enhance future resilience of LECZ communities by offering approaches to mitigate hazards to human health, safety and welfare and reduce impacts to coastal residents and industries.
Sea level rise has increased the frequency of tidal flooding even without accompanying precipitation in many coastal areas worldwide. As the tide rises, inundates the landscape, and then recedes, it can transport organic and inorganic matter between terrestrial systems and adjacent aquatic environments. However, the chemical and biological effects of tidal flooding on urban estuarine systems remain poorly constrained. Here, we provide the first extensive quantification of floodwater nutrient concentrations during a tidal flooding event and estimate the nitrogen (N) loading to the Lafayette River, an urban tidal sub-tributary of the lower Chesapeake Bay (USA). To enable the scale of synoptic sampling necessary to accomplish this, we trained citizen-scientist volunteers to collect 190 flood water samples during a perigean spring tide to measure total dissolved N (TDN), dissolved inorganic N (DIN) and phosphate concentrations, and Enterococcus abundance from the retreating ebb tide while using a phone application to measure the extent of tidal inundation. Almost 95% of Enterococcus results had concentrations that exceeded the standard established for recreational waters (104 MPN 100 mL(-1)). Floodwater dissolved nutrient concentrations were higher than concentrations measured in natural estuarine waters, suggesting floodwater as a source of dissolved nutrients to the estuary. However, only DIN concentrations were statistically higher in floodwater samples than in the estuary. Using a hydrodynamic model to calculate the volume of water inundating the landscape, and the differences between the median DIN concentrations in floodwaters and the estuary, we estimate that 1,145 kg of DIN entered the Lafayette River during this single, blue sky, tidal flooding event. This amount exceeds the annual N load allocation for overland flow established by federal regulations for this segment of the Chesapeake Bay by 30%. Because tidal flooding is projected to increase in the future as sea levels continue to rise, it is crucial we quantify nutrient loading from tidal flooding in order to set realistic water quality restoration targets for tidally influenced water bodies.
Urban floodwater could lead to significant risk for public and environmental health from mobilization of microbial pathogens and overflow of wastewater treatment systems. Here, we attempted to assess this risk by obtaining metagenomic profiles of antibiotic resistance genes (ARGs), virulence factors (VFs) and pathogens present in floodwater samples collected in urban Atlanta, GA that were categorized in two distinct groups: floods that occurred after periods of drought and those after regular (seasonal) rain events. Even though no major (known) pathogens were present at the limit of detection of our sequencing effort (~3 Gbp/sample), we observed that floodwaters after drought showed a 2.5-fold higher abundance of both ARGs and VFs compared to floodwater after rainy days. These differences were mainly derived by several novel species of the Pseudomonas genus, which were more dominant in the former versus the latter samples and carried several genes to cope with osmotic stress in addition to ARGs and VFs. These results revealed that there are previously undescribed species that become mobilized after flooding events in the Southeast US urban settings and could represent an increased public health risk, especially after periods of drought, which warrants further attention.
Wastewater treatment plants (WWTPs) are among the most important infrastructures, especially in coastal cities with a risk of flooding. During intense floods, runoff volume may exceed the capacity of a WWTP causing plant failures. This paper investigates the impacts of flooding on combined sewer overflows (CSOs) in a WWTP in New York City. The impacts of CSOs after flooding are classified into four terms of health, economic, social, and environmental factors. Different factors are defined to evaluate impacts of CSOs using multi-criteria decision-making of Preference Ranking Organization Method For Enrichment Evaluation and fuzzy technique for order performance by similarity to ideal solution. Since volume and depth were found the most significant factors for the CSO impact assessment, the Gridded Surface Subsurface Hydrologic Analysis model was run to compute flood depth and CSO volume under three treatment plant failure scenarios considering the hurricane Sandy information. Sensitivity analysis revealed that the TSS, BOD, and dissolved oxygen have the highest impacts on CSO. Uncertainty analysis was applied to investigate CSO impact variation. Results show that evaluating the impacts of CSOs in different aspects can give a good idea for flood planning and management with higher efficiency during storms.
Hurricanes and associated stormwater runoff events are expected to greatly impact coastal marine water quality, yet little is known about their immediate effects on microbiological quality of near-shore water. This study sampled Hilo Bay immediately after the impact of Hurricane Lane to understand the spatial and temporal variations of the abundance and diversity of fecal indicator enterococci, common fecal pathogens, and antibiotic resistance genes (ARGs). Water samples from seven sampling sites over 7 days were collected and analyzed, which showed that the overall microbiological water quality parameters [enterococci geometric mean (GM): 6-22 cfu/100 mL] fell within water quality standards and that the temporal dynamics indicated continuing water quality recovery. However, considerable spatial variation was observed, with the most contaminated site exhibiting impaired water quality (GM = 144 cfu/100 mL). The Enterococcus population also showed distinct genotypic composition at the most contaminated site. Although marker genes for typical fecal pathogens (invA for Salmonella, hipO for Campylobacter, mip for Legionella pneumophila, and eaeA for enteropathogenic Escherichia coli) were not detected, various ARGs (ermB, qurS, tetM, blaTEM, and sul1) and integron-associated integrase intI1 were detected at high levels. Understanding the temporal and spatial variation of microbiological water quality at fine granularity is important for balancing economic and recreational uses of coastal water and the protection of public health post the impact of major hurricane events.
Densely populated, low-lying coastal areas are most at-risk for negative impacts from increasing intensity of storm-induced flooding. Due to the effects of global warming and subsequent climate change, coastal temperatures and the magnitude of storm-induced flooding are projected to increase, creating a hospitable environment for the aquatic Vibrio spp. bacteria. A relative risk model analysis was used to determine which census block groups in coastal South Carolina have the highest risk of Vibrio spp. exposure using storm surge flooding as a proxy. Coastal block groups with dense vulnerable sub-populations exposed to storm surge have the highest relative risk, while inland block groups away from riverine-mediated storm surge have the lowest relative risk. As Vibriosis infections may be extremely severe or even deadly, the best methods of infection control will be regular standardized coastal and estuarine water monitoring for Vibrio spp. to enable more informed and timely public health advisories and help prevent future exposure.
Everglades virus (EVEV) is a subtype (II) of Venezuelan equine encephalitis virus (VEEV), endemic in southern Florida, USA. EVEV has caused clinical encephalitis in humans, and antibodies have been found in a variety of wild and domesticated mammals. Over 29,000 Culex cedecei females, the main vector of EVEV, were collected in 2017 from Big Cypress and Fakahatchee Strand Preserves in Florida and pool-screened for the presence of EVEV using reverse transcription real-time polymerase chain reaction. The entire 1 E1 protein gene was successfully sequenced from fifteen positive pools. Phylogenetic analysis showed that isolates clustered, based on the location of sampling, into two monophyletic clades that diverged in 2009. Structural analyses revealed two mutations of interest, A116V and H441R, which were shared among all isolates obtained after its first isolation of EVEV in 1963, possibly reflecting adaptation to a new host. Alterations of the Everglades ecosystem may have contributed to the evolution of EVEV and its geographic compartmentalization. This is the first report that shows in detail the evolution of EVEV in South Florida. This zoonotic pathogen warrants inclusion into routine surveillance given the high natural infection rate in the vectors. Invasive species, increasing urbanization, the Everglades restoration, and modifications to the ecosystem due to climate change and habitat fragmentation in South Florida may increase rates of EVEV spillover to the human population.
Temperature plays a significant role in the vector competence, extrinsic incubation period, and intensity of infection of arboviruses within mosquito vectors. Most laboratory infection studies use static incubation temperatures that may not accurately reflect daily temperature ranges (DTR) to which mosquitoes are exposed. This could potentially compromise the application of results to real world scenarios. We evaluated the effect of fluctuating DTR versus static temperature treatments on the infection, dissemination, and transmission rates and viral titers of Culex tarsalis and Culex quinquefasciatus mosquitoes for West Nile virus. Two DTR regimens were tested including an 11 and 15 °C range, both fluctuating around an average temperature of 28 ??C. Overall, no significant differences were found between DTR and static treatments for infection, dissemination, or transmission rates for either species. However, significant treatment differences were identified for both Cx. tarsalis and Cx. quinquefasciatus viral titers. These effects were species-specific and most prominent later in the infection. These results indicate that future studies on WNV infections in Culex mosquitoes should consider employing realistic DTRs to reflect interactions most accurately between the virus, vector, and environment.
Leishmaniasis, a chronic and persistent intracellular protozoal infection caused by many different species within the genus Leishmania, is an unfamiliar disease to most North American providers. Clinical presentations may include asymptomatic and symptomatic visceral leishmaniasis (so-called Kala-azar), as well as cutaneous or mucosal disease. Although cutaneous leishmaniasis (caused by Leishmania mexicana in the United States) is endemic in some southwest states, other causes for concern include reactivation of imported visceral leishmaniasis remotely in time from the initial infection, and the possible long-term complications of chronic inflammation from asymptomatic infection. Climate change, the identification of competent vectors and reservoirs, a highly mobile populace, significant population groups with proven exposure history, HIV, and widespread use of immunosuppressive medications and organ transplant all create the potential for increased frequency of leishmaniasis in the U.S. Together, these factors could contribute to leishmaniasis emerging as a health threat in the U.S., including the possibility of sustained autochthonous spread of newly introduced visceral disease. We summarize recent data examining the epidemiology and major risk factors for acquisition of cutaneous and visceral leishmaniasis, with a special focus on implications for the United States, as well as discuss key emerging issues affecting the management of visceral leishmaniasis.
Seasonal variations in environmental conditions lead to changing infectious disease epidemic risks at different times of year. The probability that early cases initiate a major epidemic depends on the season in which the pathogen enters the population. The instantaneous epidemic risk (IER) can be tracked. This quantity is straightforward to calculate, and corresponds to the probability of a major epidemic starting from a single case introduced at time t=t(0), assuming that environmental conditions remain identical from that time onwards (i.e. for all t≥t(0)). However, the threat when a pathogen enters the population in fact depends on changes in environmental conditions occurring within the timescale of the initial phase of the outbreak. For that reason, we compare the IER with a different metric: the case epidemic risk (CER). The CER corresponds to the probability of a major epidemic starting from a single case entering the population at time t=t(0), accounting for changes in environmental conditions after that time. We show how the IER and CER can be calculated using different epidemiological models (the stochastic Susceptible-Infectious-Removed model and a stochastic host-vector model that is parameterised using temperature data for Miami) in which transmission parameter values vary temporally. While the IER is always easy to calculate numerically, the adaptable method we provide for calculating the CER for the host-vector model can also be applied easily and solved using widely available software tools. In line with previous research, we demonstrate that, if a pathogen is likely to either invade the population or fade out on a fast timescale compared to changes in environmental conditions, the IER closely matches the CER. However, if this is not the case, the IER and the CER can be significantly different, and so the CER should be used. This demonstrates the need to consider future changes in environmental conditions carefully when assessing the risk posed by emerging pathogens.
This case study examined current trends in the prevalence of vector-borne diseases and the impact of climate change on disease distribution. Our findings indicate that the dynamics of the Anopheles mosquito population in particular has changed dramatically in the past decade and now poses an increasing threat to human populations previously at low risk for malaria transmission. Given their geographic location and propensity for sustaining vector-borne disease outbreaks, southeastern states are particularly vulnerable to climate-induced changes in vector populations. We demonstrate the need to strengthen our hospital and laboratory infrastructure prior to further increases in the incidence of vector-borne diseases by discussing a case of uncomplicated malaria in a patient who arrived in one of our hospitals in Louisiana. This case exemplifies a delay in diagnosis and obtaining appropriate treatment in a timely manner, which suggests that our current health care infrastructure, especially in areas heavily affected by climate change, may not be adequately prepared to protect patients from vector-borne diseases. We conclude our discussion by examining current laboratory protocols in place with suggestions for future actions to combat this increasing threat to public health in the United States.
The Greater Everglades Region of South Florida is one of the largest natural wetlands and the only subtropical ecosystem found in the continental United States. Mosquitoes are seasonally abundant in the Everglades where several potentially pathogenic mosquito-borne arboviruses are maintained in natural transmission cycles involving vector-competent mosquitoes and reservoir-competent vertebrate hosts. The fragile nature of this ecosystem is vulnerable to many sources of environmental change, including a wetlands restoration project, climate change, invasive species and residential development. In this study, we obtained baseline data on the distribution and abundance of both mosquitos and arboviruses occurring in the southern Everglades region during the summer months of 2013, when water levels were high, and in 2014, when water levels were low. A total of 367,060 mosquitoes were collected with CO2-baited CDC light traps at 105 collection sites stratified among the major landscape features found in Everglades National Park, Big Cypress National Preserve, Fakahatchee State Park Preserve and Picayune State Forest, an area already undergoing restoration. A total of 2,010 pools of taxonomically identified mosquitoes were cultured for arbovirus isolation and identification. Seven vertebrate arboviruses were isolated: Everglades virus, Tensaw virus, Shark River virus, Gumbo Limbo virus, Mahogany Hammock virus, Keystone virus, and St. Louis encephalitis virus. Except for Tensaw virus, which was absent in 2013, the remaining viruses were found to be most prevalent in hardwood hammocks and in Fakahatchee, less prevalent in mangroves and pinelands, and absent in cypress and sawgrass. In contrast, in the summer of 2014 when water levels were lower, these arboviruses were far less prevalent and only found in hardwood hammocks, but Tensaw virus was present in cypress, sawgrass, pinelands, and a recently burned site. Major environmental changes are anticipated in the Everglades, many of which will result in increased water levels. How these might lead to the emergence of arboviruses potentially pathogenic to both humans and wildlife is discussed.
From 2016 to 2018, Hidalgo County observed the emergence of Zika virus (ZIKV) infections along with sporadic cases of Dengue virus (DENV) and West Nile virus (WNV). Due to the emergence of ZIKV and the historical presence of other mosquito-borne illnesses, Hidalgo County obtained funding to enhance mosquito surveillance and educate residents on arboviruses and travel risks. During this time period, Hidalgo County mosquito surveillance efforts increased by 1.275%. This increase resulted in >8000 mosquitoes collected, and 28 mosquito species identified. Aedes aegypti, Ae albopictus and Culex quinquefasciatus made up approximately two-thirds of the mosquitoes collected in 2018 (4122/6171). Spatiotemporal shifts in vector species composition were observed as the collection period progressed. Significantly, temperature variations (p < 0.05) accounted for associated variations in vector abundance, whereas all other climate variables were not significant.
BACKGROUND: West Nile virus (WNV), a global arbovirus, is the most prevalent mosquito-transmitted infection in the United States. Forecasts of WNV risk during the upcoming transmission season could provide the basis for targeted mosquito control and disease prevention efforts. We developed the Arbovirus Mapping and Prediction (ArboMAP) WNV forecasting system and used it in South Dakota from 2016 to 2019. This study reports a post hoc forecast validation and model comparison. OBJECTIVES: Our objective was to validate historical predictions of WNV cases with independent data that were not used for model calibration. We tested the hypothesis that predictive models based on mosquito surveillance data combined with meteorological variables were more accurate than models based on mosquito or meteorological data alone. METHODS: The ArboMAP system incorporated models that predicted the weekly probability of observing one or more human WNV cases in each county. We compared alternative models with different predictors including a) a baseline model based only on historical WNV cases, b) mosquito models based on seasonal patterns of infection rates, c) environmental models based on lagged meteorological variables, including temperature and vapor pressure deficit, d) combined models with mosquito infection rates and lagged meteorological variables, and e) ensembles of two or more combined models. During the WNV season, models were calibrated using data from previous years and weekly predictions were made using data from the current year. Forecasts were compared with observed cases to calculate the area under the receiver operating characteristic curve (AUC) and other metrics of spatial and temporal prediction error. RESULTS: Mosquito and environmental models outperformed the baseline model that included county-level averages and seasonal trends of WNV cases. Combined models were more accurate than models based only on meteorological or mosquito infection variables. The most accurate model was a simple ensemble mean of the two best combined models. Forecast accuracy increased rapidly from early June through early July and was stable thereafter, with a maximum AUC of 0.85. The model predictions captured the seasonal pattern of WNV as well as year-to-year variation in case numbers and the geographic pattern of cases. DISCUSSION: The predictions reached maximum accuracy early enough in the WNV season to allow public health responses before the peak of human cases in August. This early warning is necessary because other indicators of WNV risk, including early reports of human cases and mosquito abundance, are poor predictors of case numbers later in the season. https://doi.org/10.1289/EHP10287.
Eastern equine encephalitis (EEE) is a rare but lethal mosquito-borne zoonotic disease. Recent years have seen incursion into new areas of the USA, and in 2019 the highest number of human cases in decades. Due to the low detection rate of EEE, previous studies were unable to quantify large-scale and recent EEE ecological dynamics. We used Bayesian spatial generalized-linear mixed model to quantify the spatiotemporal dynamics of human EEE incidence in the northeastern USA. In addition, we assessed whether equine EEE incidence has predictive power for human cases, independently from other environmental variables. The predictors of the model were selected based on variable importance. Human incidence increased with temperature seasonality, but decreased with summer temperature, summer, fall, and winter precipitation. We also found EEE transmission in equines strongly associated with human infection (OR: 1.57; 95% CI: 1.52-1.60) and latitudes above 41.9 °N after 2018. The study designed for sparse dataset described new and known relationships between human and animal EEE and environmental factors, including geographical directionality. Future models must include equine cases as a risk factor when predicting human EEE risks. Future work is still necessary to ascertain the establishment of EEE in northern latitudes and the robustness of the available data.
Human granulocytic anaplasmosis (HGA) and human babesiosis are tick-borne diseases spread by the blacklegged tick (Ixodes scapularis Say, Acari: Ixodidae) and are the result of infection with Anaplasma phagocytophilum and Babesia microti, respectively. In New York State (NYS), incidence rates of these diseases increased concordantly until around 2013, when rates of HGA began to increase more rapidly than human babesiosis, and the spatial extent of the diseases diverged. Surveillance data of tick-borne pathogens (2007 to 2018) and reported human cases of HGA (n = 4,297) and human babesiosis (n = 2,986) (2013-2018) from the New York State Department of Health (NYSDOH) showed a positive association between the presence/temporal emergence of each pathogen and rates of disease in surrounding areas. Incidence rates of HGA were higher than human babesiosis among White and non-Hispanic/non-Latino individuals, as well as all age and sex groups. Human babesiosis exhibited higher rates among non-White individuals. Climate, weather, and landscape data were used to build a spatially weighted zero-inflated negative binomial (ZINB) model to examine and compare associations between the environment and rates of HGA and human babesiosis. HGA and human babesiosis ZINB models indicated similar associations with forest cover, forest land cover change, and winter minimum temperature; and differing associations with elevation, urban land cover change, and winter precipitation. These results indicate that tick-borne disease ecology varies between pathogens spread by I. scapularis.
Odocoileus virginianus (white-tailed deer) is the primary host of adult Ixodes scapularis (deer tick). Most of the research into I. scapularis has been geographically restricted to the northeastern United States, with limited interest in Oklahoma until recently as the I. scapularis populations spread due to climate change. Ticks serve as a vector for pathogenic bacteria, protozoans, and viruses that pose a significant human health risk. To date, there has been limited research to determine what potential tick-borne pathogens are present in I. scapularis in central Oklahoma. Using a one-step multiplex real-time reverse transcription-PCR, I. scapularis collected from white-tailed deer was screened for Anaplasma phagocytophilum, Borrelia burgdorferi, Borrelia miyamotoi, Babesia microti, and deer tick virus (DTV). Ticks (n = 394) were pooled by gender and life stage into 117 samples. Three pooled samples were positive for B. miyamotoi and five pooled samples were positive for DTV. This represents a minimum infection rate of 0.8% and 1.2%, respectively. A. phagocytophilum, B. burgdorferi, and B. microti were not detected in any samples. This is the first report of B. miyamotoi and DTV detection in Oklahoma I. scapularis ticks. This demonstrates that I. scapularis pathogens are present in Oklahoma and that further surveillance of I. scapularis is warranted.
Rhipicephalus sanguineus is a species complex of ticks that vector disease worldwide. Feeding primarily on dogs, members of the complex also feed incidentally on humans, potentially transmitting disease agents such as Rickettsia rickettsii, R. conorii, and Ehrlichia species. There are two genetic Rh. sanguineus lineages in North America, designated as the temperate and tropical lineages, which had occurred in discrete locations, although there is now range overlap in parts of California and Arizona. Rh. sanguineus in Europe are reportedly more aggressive toward humans during hot weather, increasing the risk of pathogen transmission to humans. The aim of this study was to assess the impact of hot weather on choice between humans and dog hosts among tropical and temperate lineage Rh. sanguineus individuals. Ticks in a two-choice olfactometer migrated toward a dog or human in trials at room (23.5°C) or high temperature (38°C). At 38°C, 2.5 times more tropical lineage adults chose humans compared with room temperature, whereas temperate lineage adults demonstrated a 66% reduction in preference for dogs and a slight increase in preference for humans. Fewer nymphs chose either host at 38°C than at room temperature in both lineages. These results demonstrate that risk of disease transmission to humans may be increased during periods of hot weather, where either lineage is present, and that hot weather events associated with climatic change may result in more frequent rickettsial disease outbreaks.
The range of ticks in North America has been steadily increasing likely, in part, due to climate change. Along with it, there has been a rise in cases of tick-borne disease. Among those medically important tick species of particular concern are Ixodes scapularis Say (Acari: Ixodidae), Dermacentor variabilis Say (Acari: Ixodidae), and Amblyomma americanum Linneaus (Acari: Ixodidae). The aim of this study was to determine if climate factors explain existing differences in abundance of the three aforementioned tick species between two climatically different regions of Illinois (Central and Southern), and if climate variables impact each species differently. We used both zero-inflated regression approaches and Bayesian network analyses to assess relationships among environmental variables and tick abundance. Results suggested that the maximum average temperature and total precipitation are associated with differential impact on species abundance and that this difference varied by region. Results also reinforced a differential level of resistance to desiccation among these tick species. Our findings help to further define risk periods of tick exposure for the general public, and reinforce the importance of responding to each tick species differently.
In recent decades, Lyme disease has been expanding to previous nonendemic areas. We hypothesized that infected I. scapularis nymphs that retain host-seeking behavior under optimal environmental conditions are fit to fulfil their transmission role in the enzootic cycle of B. burgdorferi. We produced nymphal ticks in the laboratory under controlled temperature (22-25°C), humidity (80-90%), and natural daylight cycle conditions to allow them to retain host-seeking/questing behavior for 1 year. We then analyzed differences in B. burgdorferi infection prevalence in questing and diapause nymphs at 6 weeks postmolting (prime questing) as well as differences in infection prevalence of questing nymphs maintained under prolonged environmental induced questing over 12 months (prolonged questing). Lastly, we analyzed the fitness of nymphal ticks subjected to prolonged questing in transmission of B. burgdorferi to naive mice over the course of the year. B. burgdorferi infected unfed I. scapularis nymphal ticks maintained under optimal environmental conditions in the laboratory not only survived for a year in a developmental state of prolonged questing (host-seeking), but they retained an infection prevalence sufficient to effectively fulfil transmission of B. burgdorferi to uninfected mice after tick challenge. Our study is important for understanding and modeling Lyme disease expansion into former nonendemic regions due to climate change. IMPORTANCE Lyme disease is rapidly spreading from its usual endemic areas in the Northeast, Midwest, and Midatlantic states into neighboring areas, which could be due to changing climate patterns. Our study shows that unfed I. scapularis nymphal ticks kept under optimal environmental conditions in the laboratory survived for a year while exhibiting aggressive host-seeking behavior, and they maintained a B. burgdorferi infection prevalence which was sufficient to infect naive reservoir hosts after tick challenge. Our study raises important questions regarding prolonged survival of B. burgdorferi infected host-seeking nymphal I. scapularis ticks that can potentially increase the risk of Lyme disease incidence, if conditions of temperature and humidity become amenable to the enzootic cycle of B. burgdorferi in regions currently classified as nonendemic.
In the western United States, Ixodes pacificus Cooley & Kohls (Acari: Ixodidae) is the primary vector of the agents causing Lyme disease and granulocytic anaplasmosis in humans. The geographic distribution of the tick is associated with climatic variables that include temperature, precipitation, and humidity, and biotic factors such as the spatial distribution of its primary vertebrate hosts. Here, we explore (1) how climate change may alter the geographic distribution of I. pacificus in California, USA, during the 21(st) century, and (2) the spatial overlap among predicted changes in tick habitat suitability, land access, and ownership. Maps of potential future suitability for I. pacificus were generated by applying climate-based species distribution models to a multi-model ensemble of climate change projections for the Representative Concentration Pathway (RCP) 4.5 (moderate emission) and 8.5 (high emission) scenarios for two future periods: mid-century (2026-2045) and end-of-century (2086-2099). Areas climatically-suitable for I. pacificus are projected to expand by 23% (mid-century RCP 4.5) to 86% (end-of-century RCP 8.5) across California, compared to the historical period (1980-2014), with future estimates of total suitable land area ranging from about 88 to 133 thousand km(2), or up to about a third of California. Regions projected to have the largest area increases in suitability by end-of-century are in northwestern California and the south central and southern coastal ranges. Over a third of the future suitable habitat is on lands currently designated as open access (i.e. publicly available), and by 2100, the amount of these lands that are suitable habitat for I. pacificus is projected to more than double under the most extreme emissions scenario (from ~23,000 to >51,000 km(2)). Of this area, most is federally-owned (>45,000 km(2)). By the end of the century, 26% of all federal land in the state is predicted to be suitable habitat for I. pacificus. The resulting maps may facilitate regional planning and preparedness by informing public health and vector control decision-makers.
Ixodes pacificus Cooley & Kohls is the primary vector of Lyme disease spirochetes to humans in the western United States. Although not native to Alaska, this tick species has recently been found on domestic animals in the state. Ixodes pacificus has a known native range within the western contiguous United States and southwest Canada; therefore, it is not clear if introduced individuals can successfully survive and reproduce in the high-latitude climate of Alaska. To identify areas of suitable habitat within Alaska for I. pacificus, we used model parameters from two existing sets of ensemble habitat distribution models calibrated in the contiguous United States. To match the model input covariates, we calculated climatic and land cover covariates for the present (1980-2014) and future (2070-2100) climatologies in Alaska. The present-day habitat suitability maps suggest that the climate and land cover in Southeast Alaska and portions of Southcentral Alaska could support the establishment of I. pacificus populations. Future forecasts suggest an increase in suitable habitat with considerable uncertainty for many areas of the state. Repeated introductions of this non-native tick to Alaska increase the likelihood that resident populations could become established.
Human cases of tick-borne diseases have been increasing in the United States. In particular, the incidence of Lyme disease, the major vector-borne disease in Rhode Island, has risen, along with cases of babesiosis and anaplasmosis, all vectored by the blacklegged tick. These increases might relate, in part, to climate change, although other environmental changes in the northeastern U.S. (land use as it relates to habitat; vertebrate host populations for tick reproduction and enzootic cycling) also contribute. Lone star ticks, formerly southern in distribution, have been spreading northward, including expanded distributions in Rhode Island. Illnesses associated with this species include ehrlichiosis and alpha-gal syndrome, which are expected to increase. Ranges of other tick species have also been expanding in southern New England, including the Gulf Coast tick and the introduced Asian longhorned tick. These ticks can carry human pathogens, but the implications for human disease in Rhode Island are unclear.
Influenza typically causes mild infection but can lead to severe outcomes for those with compromised lung health. Flooding, a seasonal problem in Iowa, can expose many Iowans to molds and allergens shown to alter lung inflammation, leading to asthma attacks and decreased viral clearance. Based on this, the hypothesis for this research was that there would be geographically specific positive associations in locations with flooding with influenza diagnosis. An ecological study was performed using influenza diagnoses and positive influenza polymerase chain reaction tests from a de-identified large private insurance database and Iowa State Hygienic Lab. After adjustment for multiple confounding factors, Poisson regression analysis resulted in a consistent 1% associated increase in influenza diagnoses per day above flood stage (95% confidence interval: 1.00-1.04). This relationship remained after removal of the 2009-2010 influenza pandemic year. There was no associated risk between flooding and influenza-like illness as a nonspecific diagnosis. Associated risks between flooding and increased influenza diagnoses were geographically specific, with the greatest risk in the most densely populated areas. This study indicates that populations who live, work, or volunteer in flooded environments should consider preventative measures to avoid environmental exposures to mitigate illness from influenza in the following year.
INTRODUCTION: Cryptococcus gattii (C. gatti) is a rare cause of meningitis in the United States. Outbreaks in new geographic distributions in the past few decades raise concern that climate change may be contributing to a broader distribution of this pathogen. We review a case of C. gattii in a 23-year-old woman in Northern California who was diagnosed via lumbar puncture after six weeks of headache, blurred vision, and tinnitus. CASE REPORT: A 23-year-old previously healthy young woman presented to the emergency department (ED) after multiple visits to primary care, other EDs, and neurologists, for several weeks of headache, nausea, tinnitus, and blurred vision. On examination the patient was found to have a cranial nerve VI palsy (impaired abduction of the left eye) and bilateral papilledema on exam. Lumbar puncture had a significantly elevated opening pressure. Cerebrospinal fluid studies were positive for C. gattii. The patient was treated with serial lumbar punctures, followed by lumbar drain, as well as amphotericin and flucytosine. The patient had improvement in headache and neurologic symptoms and was discharged to another facility that specializes in management of this disease to undergo further treatment with immunomodulators and steroids. CONCLUSION: Fungal meningitis is uncommon in the US, particularly among immunocompetent patients. Due to climate change, C. gattii may be a new pathogen to consider. This finding raises important questions to the medical community about the way global climate change affects day to day medical care now, and how it may change in the future.
BACKGROUND: This paper represents, to our knowledge, the first national-level (United States) estimate of the economic impacts of vibriosis cases as exacerbated by climate change. Vibriosis is an illness contracted through food- and waterborne exposures to various Vibrio species (e.g., nonV. cholerae O1 and O139 serotypes) found in estuarine and marine environments, including within aquatic life, such as shellfish and finfish. OBJECTIVES: The objective of this study was to project climate-induced changes in vibriosis and associated economic impacts in the United States related to changes in sea surface temperatures (SSTs). METHODS: For our analysis to identify climate links to vibriosis incidence, we constructed three logistic regression models by Vibrio species, using vibriosis data sourced from the Cholera and Other Vibrio Illness Surveillance system and historical SSTs. We relied on previous estimates of the cost-per-case of vibriosis to estimate future total annual medical costs, lost income from productivity loss, and mortality-related indirect costs throughout the United States. We separately reported results for V. parahaemolyticus, V. vulnificus, V. alginolyticus, and “V. spp.,” given the different associated health burden of each. RESULTS: By 2090, increases in SST are estimated to result in a 51% increase in cases annually relative to the baseline era (centered on 1995) under Representative Concentration Pathway (RCP) 4.5, and a 108% increase under RCP8.5. The cost of these illnesses is projected to reach $5.2 billion annually under RCP4.5, and $7.3 billion annually under RCP8.5, relative to $2.2 billion in the baseline (2018 U.S. dollars), equivalent to 140% and 234% increases respectively. DISCUSSION: Vibriosis incidence is likely to increase in the United States under moderate and unmitigated climate change scenarios through increases in SST, resulting in a substantial burden of morbidity and mortality, and costing billions of dollars. These costs are mostly attributable to deaths, primarily from exposure to V. vulnificus. Evidence suggests that other factors, including sea surface salinity, may contribute to further increases in vibriosis cases in some regions of the United States and should also be investigated. https://doi.org/10.1289/EHP9999a.
The Pacific Northwest (PNW) is one of the largest commercial harvesting areas for Pacific oysters (Crassostrea gigas) in the United States. Vibrio parahaemolyticus, a bacterium naturally present in estuarine waters accumulates in shellfish and is a major cause of seafood-borne illness. Growers, consumers, and public-health officials have raised concerns about rising vibriosis cases in the region. Vibrio parahaemolyticus genetic markers (tlh, tdh, and trh) were estimated using an most-probable-number (MPN)-PCR technique in Washington State Pacific oysters regularly sampled between May and October from 2005 to 2019 (N = 2,836); environmental conditions were also measured at each sampling event. Multilevel mixed-effects regression models were used to assess relationships between environmental measures and genetic markers as well as genetic marker ratios (trh:tlh, tdh:tlh, and tdh:trh), accounting for variation across space and time. Spatial and temporal dependence were also accounted for in the model structure. Model fit improved when including environmental measures from previous weeks (1-week lag for air temperature, 3-week lag for salinity). Positive associations were found between tlh and surface water temp, specifically between 15 and 26°C, and between trh and surface water temperature up to 26°C. tlh and trh were negatively associated with 3-week lagged salinity in the most saline waters (> 27 ppt). There was also a positive relationship between tissue temperature and tdh, but only above 20°C. The tdh:tlh ratio displayed analogous inverted non-linear relationships as tlh. The non-linear associations found between the genetic targets and environmental measures demonstrate the complex habitat suitability of V. parahaemolyticus. Additional associations with both spatial and temporal variables also suggest there are influential unmeasured environmental conditions that could further explain bacterium variability. Overall, these findings confirm previous ecological risk factors for vibriosis in Washington State, while also identifying new associations between lagged temporal effects and pathogenic markers of V. parahaemolyticus.
Diverse snail species serve as intermediate hosts of the parasitic nematode Angiostrongylus cantonensis, the etiological agent of human neuroangiostrongyliasis. However, levels of A. cantonensis infection prevalence and intensity vary dramatically among these host species. Factors contributing to this variation are largely unknown. Environmental factors, such as precipitation and temperature, have been correlated with overall A. cantonensis infection levels in a locale, but the influence of environment on infection in individual snail species has not been addressed. We identified levels of A. cantonensis prevalence and intensity in 16 species of snails collected from 29 sites along an environmental gradient on the island of Oahu, Hawaii. The relationship between infection levels of individual species and their environment was evaluated using AIC model selection of Generalized Linear Mixed Models incorporating precipitation, temperature, and vegetation cover at each collection site. Our results indicate that different mechanisms drive parasite prevalence and intensity in the intermediate hosts. Overall, snails from rainy, cool, green sites had higher infection levels than snails from dry, hot sites with less green vegetation. Intensity increased at the same rate along the environmental gradient in all species, though at different levels, while the relation between prevalence and environmental variables depended on species. These results have implications for zoonotic transmission, as human infection is a function of infection in the intermediate hosts, ingestion of which is the main pathway of transmission. The probability of human infection is greater in locations with higher rainfall, lower temperature and more vegetation cover because of higher infection prevalence in the gastropod hosts, but this depends on the host species. Moreover, severity of neuroangiostrongyliasis symptoms is likely to be greater in locations with higher rainfall, lower temperature, and more vegetation because of the higher numbers of infectious larvae (infection intensity) in all infected snail species. This study highlights the variation of infection prevalence and intensity in individual gastropod species, the individualistic nature of interactions between host species and their environment, and the implications for human neuroangiostrongyliasis in different environments.
Freshwater can support the survival of the enteric pathogen Salmonella, though temporal Salmonella diversity in a large watershed has not been assessed. At 28 locations within the Susquehanna River basin, 10-liter samples were assessed in spring and summer over 2 years. Salmonella prevalence was 49%, and increased river discharge was the main driver of Salmonella presence. The amplicon-based sequencing tool, CRISPR-SeroSeq, was used to determine serovar population diversity and detected 25 different Salmonella serovars, including up to 10 serovars from a single water sample. On average, there were three serovars per sample, and 80% of Salmonella-positive samples contained more than one serovar. Serovars Give, Typhimurium, Thompson, and Infantis were identified throughout the watershed and over multiple collections. Seasonal differences were evident: serovar Give was abundant in the spring, whereas serovar Infantis was more frequently identified in the summer. Eight of the ten serovars most commonly associated with human illness were detected in this study. Crucially, six of these serovars often existed in the background, where they were masked by a more abundant serovar(s) in a sample. Serovars Enteritidis and Typhimurium, especially, were masked in 71 and 78% of samples where they were detected, respectively. Whole-genome sequencing-based phylogeny demonstrated that strains within the same serovar collected throughout the watershed were also very diverse. The Susquehanna River basin is the largest system where Salmonella prevalence and serovar diversity have been temporally and spatially investigated, and this study reveals an extraordinary level of inter- and intraserovar diversity.IMPORTANCE Salmonella is a leading cause of bacterial foodborne illness in the United States, and outbreaks linked to fresh produce are increasing. Understanding Salmonella ecology in freshwater is of importance, especially where irrigation practices or recreational use occur. As the third largest river in the United States east of the Mississippi, the Susquehanna River is the largest freshwater contributor to the Chesapeake Bay, and it is the largest river system where Salmonella diversity has been studied. Rainfall and subsequent high river discharge rates were the greatest indicators of Salmonella presence in the Susquehanna and its tributaries. Several Salmonella serovars were identified, including eight commonly associated with foodborne illness. Many clinically important serovars were present at a low frequency within individual samples and so could not be detected by conventional culture methods. The technologies employed here reveal an average of three serovars in a 10-liter sample of water and up to 10 serovars in a single sample.
BACKGROUND: Infections with nontyphoidal Salmonella cause an estimated 19,336 hospitalizations each year in the United States. Sources of infection can vary by state and include animal and plant-based foods, as well as environmental reservoirs. Several studies have recognized the importance of increased ambient temperature and precipitation in the spread and persistence of Salmonella in soil and food. However, the impact of extreme weather events on Salmonella infection rates among the most prevalent serovars, has not been fully evaluated across distinct U.S. regions. METHODS: To address this knowledge gap, we obtained Salmonella case data for S. Enteriditis, S. Typhimurium, S. Newport, and S. Javiana (2004-2014; n = 32,951) from the Foodborne Diseases Active Surveillance Network (FoodNet), and weather data from the National Climatic Data Center (1960-2014). Extreme heat and precipitation events for the study period (2004-2014) were identified using location and calendar day specific 95(th) percentile thresholds derived using a 30-year baseline (1960-1989). Negative binomial generalized estimating equations were used to evaluate the association between exposure to extreme events and salmonellosis rates. RESULTS: We observed that extreme heat exposure was associated with increased rates of infection with S. Newport in Maryland (Incidence Rate Ratio (IRR): 1.07, 95% Confidence Interval (CI): 1.01, 1.14), and Tennessee (IRR: 1.06, 95% CI: 1.04, 1.09), both FoodNet sites with high densities of animal feeding operations (e.g., broiler chickens and cattle). Extreme precipitation events were also associated with increased rates of S. Javiana infections, by 22% in Connecticut (IRR: 1.22, 95% CI: 1.10, 1.35) and by 5% in Georgia (IRR: 1.05, 95% CI: 1.01, 1.08), respectively. In addition, there was an 11% (IRR: 1.11, 95% CI: 1.04-1.18) increased rate of S. Newport infections in Maryland associated with extreme precipitation events. CONCLUSIONS: Overall, our study suggests a stronger association between extreme precipitation events, compared to extreme heat, and salmonellosis across multiple U.S. regions. In addition, the rates of infection with Salmonella serovars that persist in environmental or plant-based reservoirs, such as S. Javiana and S. Newport, appear to be of particular significance regarding increased heat and rainfall events.
As the nation’s public health leader, the Centers for Disease Control and Prevention (CDC) is actively engaged in a national effort to protect the public’s health from the harmful effects of climate change. Scientists from CDC’s National Center for Emerging and Zoonotic Infectious Diseases (NCEZID) are at the forefront of many of these efforts. This report highlights some of that work and also looks ahead to the important work yet to come. Lyme disease, West Nile virus disease, and Valley fever. These are just some of the infectious diseases that are on the rise and spreading to new areas of the United States. Milder winters, warmer summers, and fewer days of frost make it easier for these and other infectious diseases to expand into new geographic areas and infect more people. To understand climate change’s impact, it’s important to look at some of the common ways these diseases spread—through mosquito and tick bites, contact with animals, fungi, and water.
Ticks rank high among arthropod vectors in terms of numbers of infectious agents that they transmit to humans, including Lyme disease, Rocky Mountain spotted fever, Colorado tick fever, human monocytic ehrlichiosis, tularemia, and human granulocytic anaplasmosis. Increasing temperature is suspected to affect tick biting rates and pathogen developmental rates, thereby potentially increasing risk for disease incidence. Tick distributions respond to climate change, but how their geographic ranges will shift in future decades and how those shifts may translate into changes in disease incidence remain unclear. In this study, we have assembled correlative ecological niche models for eight tick species of medical or veterinary importance in North America (Ixodes scapularis, I. pacificus, I. cookei, Dermacentor variabilis, D. andersoni, Amblyomma americanum, A. maculatum, and Rhipicephalus sanguineus), assessing the distributional potential of each under both present and future climatic conditions. Our goal was to assess whether and how species’ distributions will likely shift in coming decades in response to climate change. We interpret these patterns in terms of likely implications for tick-associated diseases in North America.
In California, the western blacklegged tick, Ixodes pacificus Cooley and Kohls, is the principal vector of the Borrelia burgdorferi sensu lato (sl) complex (Spirochaetales: Spirochaetaceae, Johnson et al.), which includes the causative agent of Lyme disease (B. burgdorferi sensu stricto). Ixodes pacificus nymphs were sampled from 2015 to 2017 at one Sierra Nevada foothill site to evaluate our efficiency in collecting this life stage, characterize nymphal seasonality, and identify environmental factors affecting their abundance and infection with B. burgdorferi sl. To assess sampling success, we compared the density and prevalence of I. pacificus nymphs flagged from four questing substrates (logs, rocks, tree trunks, leaf litter). Habitat characteristics (e.g., canopy cover, tree species) were recorded for each sample, and temperature and relative humidity were measured hourly at one location. Generalized linear mixed models were used to assess environmental factors associated with I. pacificus abundance and B. burgdorferi sl infection. In total, 2,033 substrates were sampled, resulting in the collection of 742 I. pacificus nymphs. Seasonal abundance of nymphs was bimodal with peak activity occurring from late March through April and a secondary peak in June. Substrate type, collection year, month, and canopy cover were all significant predictors of nymphal density and prevalence. Logs, rocks, and tree trunks had significantly greater nymphal densities and prevalences than leaf litter. Cumulative annual vapor pressure deficit was the only significant climatic predictor of overall nymphal I. pacificus density and prevalence. No associations were observed between the presence of B. burgdorferi sl in nymphs and environmental variables.
The impacts of wildfires on the health of children are becoming a more urgent matter as wildfires become more frequent, intense and affecting, not only forested areas, but also urban locations. It is important that medical professionals be prepared to provide information to patients and families on how to minimize the adverse health effects on children of wildfire smoke and ash from wildfires. (C) 2021 Elsevier Inc. All rights reserved.
AIM: The purpose of this retrospective, correlational pilot study was to explore the relationship between historical weekly weather data including temperature, dew point, humidity, barometric pressure, visibility, and cloud cover compared to weekly influenza-like illness reports over a four year period. BACKGROUND: Climate and weather-related conditions may affect the viral activity and transmission of influenza, although this relationship has not been widely studied in nursing. Some research suggests that there are causal links between cold temperatures, low indoor humidity, minimal sun exposure, and influenza outbreaks. Additionally, rapid weather variability in a warming climate can increase influenza epidemic risk. METHODS: Data from a local public health district were extracted and used to correlate with weekly weather averages for the area. RESULTS: Findings showed that current influenza reports are significantly associated with temperature and visibility, both lagged two weeks. CONCLUSIONS: Though more research is needed, nurses must understand, recognize, and act upon weather and climate factors that affect the health of populations. With a greater understanding of the relationship between weather and influenza-like illness, nurses and other healthcare providers can potentially work to respond to and mitigate the consequences of weather-related illness as well as anticipate and prepare for increased flu burden. Furthermore, nurses can remain engaged in climate protective initiatives and policy development at their local community and/or organizational levels to underscore and advocate for the needs of populations and groups they serve.
The soil-borne fungal disease coccidioidomycosis (Valley fever) is prevalent across the southwestern United States (US). Previous studies have suggested that the occurrence of this infection is associated with anomalously wet or dry soil moisture states described by the “grow and blow” hypothesis. The growth of coccidioidomycosis is favored by moist conditions both at the surface and in the root zone. A statistical analysis identified two areas in Arizona and central California, with a moderate-to-high number of coccidioidomycosis cases. A Wavelet Transform Coherence (WTC) analysis between El Nino Southern Oscillation (ENSO), coccidioidomycosis cases, surface soil moisture (SSM; 0 to 5 cm) from European Space Agency-Climate Change Initiative (ESA-CCI), and shallow root zone soil moisture (RZSM; 0 to 40 cm depth) from Soil MERGE (SMERGE) was executed for twenty-four CA and AZ counties. In AZ, only SSM was modulated by ENSO. When case values were adjusted for overreporting between 2009 to 2012, a moderate but significant connection between ENSO and cases was observed at a short periodicity (2.1 years). In central CA, SSM, RZSM, and cases all had a significant link to ENSO at longer periodicities (5-to-7 years). This study provides an example of how oceanic-atmospheric teleconnections can impact human health.
Legionellosis is an infection acquired through inhalation of aerosols that are contaminated with environmental bacteria Legionella spp. The bacteria require warm temperature for proliferation in bodies of water and moist soil. The legionellosis incidence in the United States has been rising rapidly in the past two decades without a clear explanation. In the meantime, the US has recorded consecutive years of above-norm temperature since 1997 and precipitation surplus since 2008. The present study analyzed the legionellosis incidence in the US during the 20-year period of 1999 to 2018 and correlated with concurrent temperature, precipitation, solar ultraviolet B (UVB) radiation, and vehicle mileage data. The age-adjusted legionellosis incidence rates rose exponentially from 0.40/100,000 in 1999 (with 1108 cases) to 2.69/100,000 in 2018 (with 9933 cases) at a calculated annual increase of 110%. In regression analyses, the rise correlated with an increase in vehicle miles driven and with temperature and precipitation levels that have been above the 1901-2000 mean since 1997 and 2008, respectively, suggesting more road exposure to traffic-generated aerosols and promotive effects of anomalous climate. Remarkably, the regressions with cumulative anomalies of temperature and precipitation were robust (R2 ≥ 0.9145, P ≤ 4.7E-11), implying possible changes to microbial ecology in the terrestrial and aquatic environments. An interactive synergy between annual precipitation and vehicle miles was also found in multiple regressions. Meanwhile, the bactericidal UVB radiation has been decreasing, which also contributed to the rising incidence in an inverse correlation. The 2018 legionellosis incidence peak corresponded to cumulative effects of the climate anomalies, vast vehicle miles (3,240 billion miles, 15904 km per capita), record high precipitation (880.1 mm), near record low UVB radiation (7488 kJ/m2), and continued above-norm temperature (11.96°C). These effects were examined and demonstrated in California, Florida, New Jersey, Ohio, and Wisconsin, states that represent diverse incidence rates and climates. The incidence and above-norm temperature both rose most in cold Wisconsin. These results suggest that warming temperature and precipitation surplus have likely elevated the density of Legionella bacteria in the environment, and together with road exposure explain the rapidly rising incidence of legionellosis in the United States. These trends are expected to continue, warranting further research and efforts to prevent infection.
Elevated ambient temperatures and extreme weather events have increased the incidence of wildfires world-wide resulting in increased wood smoke particle (WSP). Epidemiologic data suggests that WSP exposure associates with exacerbations of respiratory diseases, and with increased respiratory viral infections. To assess the impact of WSP exposure on host response to viral pneumonia, we performed WSP exposures in rodents followed by infection with mouse adapted influenza (HINI-PR8). C57BL/6 male mice aged 6-8 weeks were challenged with WSP or PBS by oropharyngeal aspiration in acute (single dose) or sub-acute exposures (day 1, 3, 5, 7 and 10). Additional groups underwent sub-acute exposure followed by infection by influenza or heat-inactivated (HI) virus. Following exposures/infection, bronchoalveolar lavage (BAL) was performed to assess for total cell counts/differentials, total protein, protein carbonyls and hyaluronan. Lung tissue was assessed for viral counts by real time PCR. When compared to PBS, acute WSP exposure associated with an increase in airspace macrophages. Alternatively, sub-acute exposure resulted in a dose dependent increase in airspace neutrophils. Sub-acute WSP exposure followed by influenza infection was associated with improved respiratory viral outcomes including reduced weight loss and increased blood oxygen saturation, and decreased protein carbonyls and viral titers. Flow cytometry demonstrated dynamic changes in pulmonary macrophage and T cell subsets based on challenge with WSP and influenza. This data suggests that sub-acute WSP exposure can improve host response to acute influenza infection.
Big Events are periods during which abnormal large-scale events like war, economic collapse, revolts, or pandemics disrupt daily life and expectations about the future. They can lead to rapid change in health-related norms, beliefs, social networks and behavioural practices. The world is undergoing such Big Events through the interaction of COVID-19, a large economic downturn, massive social unrest in many countries, and ever-worsening effects of global climate change. Previous research, mainly on HIV/AIDS, suggests that the health effects of Big Events can be profound, but are contingent: Sometimes Big Events led to enormous outbreaks of HIV and associated diseases and conditions such as injection drug use, sex trading, and tuberculosis, but in other circumstances, Big Events did not do so. This paper discusses and presents hypotheses about pathways through which the current Big Events might lead to better or worse short and long term outcomes for various health conditions and diseases; considers how pre-existing societal conditions and changing ‘pathway’ variables can influence the impact of Big Events; discusses how to measure these pathways; and suggests ways in which research and surveillance might be conducted to improve human capacity to prevent or mitigate the effects of Big Events on human health.
Racial and ethnic minority and lower-income groups are disproportionately affected by environmental hazards and suffer worse health outcomes than other groups in the United States. Relative to whites and higher-income groups, racial-ethnic minority and lower-income Americans also frequently express greater concern about high-profile global environmental threats like climate change, but they are widely misperceived as being less concerned about these issues than white and higher-income Americans. We use new survey research to explore public perceptions of COVID-19-another global threat marked by substantial racial, ethnic, and class disparities-finding a distinct pattern of misperceptions regarding groups’ concerns. We then discuss how these misperceptions represent a unique form of social misinformation that may pose a threat to science and undermine the cooperation and trust needed to address collective problems.
This research aims to look at the link between environmental pollutants and the coronavirus disease (COVID-19) outbreak in California. To illustrate the COVID-19 outbreak, weather, and environmental pollution, we used daily confirmed cases of COVID-19 patients, average daily temperature, and air quality Index, respectively. To evaluate the data from March 1 to May 24, 2020, we used continuous wavelet transform and then applied partial wavelet coherence (PWC), wavelet transform coherence (WTC), and multiple wavelet coherence (MWC). Empirical estimates disclose a significant association between these series at different time-frequency spaces. The COVID-19 outbreak in California and average daily temperature show a negative (out phase) coherence. Similarly, the air quality index and COVID-19 also show a negative association circle during the second week of the observed period. Our findings will serve as policy implications for state and health officials and regulators to combat the COVID-19 outbreak.
INTRODUCTION: The spatiotemporal patterns of Corona Virus Disease 2019 (COVID-19) is detected in the United States, which shows temperature difference (TD) with cumulative hysteresis effect significantly changes the daily new confirmed cases after eliminating the interference of population density. METHODOLOGY: The nonlinear feature of updated cases is captured through Generalized Additive Mixed Model (GAMM) with threshold points; Exposure-response curve suggests that daily confirmed cases is changed at the different stages of TD according to the threshold points of piecewise function, which traces out the rule of updated cases under different meteorological condition. RESULTS: Our results show that the confirmed cases decreased by 0.390% (95% CI: -0.478 ~ -0.302) for increasing each one degree of TD if TD is less than 11.5°C; It will increase by 0.302% (95% CI: 0.215 ~ 0.388) for every 1°C increase in the TD (lag0-4) at the interval [11.5, 16]; Meanwhile the number of newly confirmed COVID-19 cases will increase by 0.321% (95% CI: 0.142 ~ 0.499) for every 1°C increase in the TD (lag0-4) when the TD (lag0-4) is over 16°C, and the most fluctuation occurred on Sunday. The results of the sensitivity analysis confirmed our model robust. CONCLUSIONS: In US, this interval effect of TD reminds us that it is urgent to control the spread and infection of COVID-19 when TD becomes greater in autumn and the ongoing winter.
Understanding whether and how wildfires exacerbate COVID-19 outcomes is important for assessing the efficacy and design of public sector responses in an age of more frequent and simultaneous natural disasters and extreme events. Drawing on environmental and emergency management literatures, we investigate how wildfire smoke (PM(2.5)) impacted COVID-19 infections and deaths during California’s 2020 wildfire season and how public housing resources and hospital capacity moderated wildfires’ effects on COVID-19 outcomes. We also hypothesize and empirically assess the differential impact of wildfire smoke on COVID-19 infections and deaths in counties exhibiting high and low social vulnerability. To test our hypotheses concerning wildfire severity and its disproportionate impact on COVID-19 outcomes in socially vulnerable communities, we construct a county-by-day panel dataset for the period April 1 to November 30, 2020, in California, drawing on publicly available state and federal data sources. This study’s empirical results, based on panel fixed effects models, show that wildfire smoke is significantly associated with increases in COVID-19 infections and deaths. Moreover, wildfires exacerbated COVID-19 outcomes by depleting the already scarce hospital and public housing resources in local communities. Conversely, when wildfire smoke doubled, a one percent increase in the availability of hospital and public housing resources was associated with a 2 to 7 percent decline in COVID-19 infections and deaths. For California communities exhibiting high social vulnerability, the occurrence of wildfires worsened COVID-19 outcomes. Sensitivity analyses based on an alternative sample size and different measures of social vulnerability validate this study’s main findings. An implication of this study for policymakers is that communities exhibiting high social vulnerability will greatly benefit from local government policies that promote social equity in housing and healthcare before, during, and after disasters.
The 2020 California wildfire season coincided with the peak of the COVID-19 pandemic affecting many counties in California, with impacts on air quality. We quantitatively analyzed the short-term effect of air pollution on COVID-19 transmission using county-level data collected during the 2020 wildfire season. Using time-series methodology, we assessed the relationship between short-term exposure to particulate matter (PM(2.5)), carbon monoxide (CO), nitrogen dioxide (NO(2)), and Air Quality Index (AQI) on confirmed cases of COVID-19 across 20 counties impacted by wildfires. Our findings indicate that PM(2.5), CO, and AQI are positively associated with confirmed COVID-19 cases. This suggests that increased air pollution could worsen the situation of a health crisis such as the COVID-19 pandemic. Health policymakers should make tailored policies to cope with situations that may increase the level of air pollution, especially during a wildfire season.
Background: Air pollution has been linked to increased susceptibility to SARS-CoV-2. Thus, it has been suggested that wildfire smoke events may exacerbate the COVID-19 pandemic. Objectives: Our goal was to examine whether wildfire smoke from the 2020 wildfires in the western United States was associated with an increased rate of SARS-CoV-2 infections in Reno, Nevada. Methods: We conducted a time-series analysis using generalized additive models to examine the relationship between the SARS-CoV-2 test positivity rate at a large regional hospital in Reno and ambient PM2.5 from 15 May to 20 Oct 2020. Results: We found that a 10 µg/m3 increase in the 7-day average PM2.5 concentration was associated with a 6.3% relative increase in the SARS-CoV-2 test positivity rate, with a 95% confidence interval (CI) of 2.5 to 10.3%. This corresponded to an estimated 17.7% (CI: 14.4-20.1%) increase in the number of cases during the time period most affected by wildfire smoke, from 16 Aug to 10 Oct. Significance: Wildfire smoke may have greatly increased the number of COVID-19 cases in Reno. Thus, our results substantiate the role of air pollution in exacerbating the pandemic and can help guide the development of public preparedness policies in areas affected by wildfire smoke, as wildfires are likely to coincide with the COVID-19 pandemic in 2021.
Individually, both droughts and pandemics cause disruptions to global food supply chains. The 21st century has seen the frequent occurrence of both natural and human disasters, including droughts and pandemics. Together their impacts can be compounded, leading to severe economic stress and malnutrition, particularly in developing countries. Understanding how droughts and pandemics interact, and identifying appropriate policies to address them together and separately, is important for maintaining a robust global food supply. Herein we assess the impacts of each of these disasters in the context of food and agriculture, and then discuss their compounded effect. We discuss the implications for policy, and suggest opportunities for future research.
BACKGROUND: In March 2020, the Louisiana Department of Health activated the Medical Monitoring Station (MMS) in downtown New Orleans. This alternative care site is designed to decompress hospitals and nursing homes overwhelmed by the coronavirus disease 2019 (COVID-19) pandemic. Given the city’s historic vulnerability to hurricanes, planning for possible tropical weather events has been a priority for MMS leadership. METHODS: The planning process incorporated input from all sectors/agencies working at the facility, to ensure consistency and cohesion. The MMS Shelter-in-Place Plan (MSIPP) was created, and a comprehensive tabletop exercise was conducted. RESULTS: Six planning topics emerged as a result of the planning process and were used to create a comprehensive plan for sheltering-in-place. These topics address hurricane preparedness for patient care, interfacility coordination, wrap-around services, medical logistics, essential staffing, and incident command during a shelter-in-place scenario. CONCLUSIONS: The MSIPP created by the MMS helped to maximize patient safety and continuity of operations during a real-world event. Select pieces of the plan were activated to meet the needs and threat level of Tropical Storm Cristobal. This experience reinforced the need for originality, scalability, and flexibility in building emergency operations plans in the midst of an unprecedented pandemic.
BACKGROUND: Drought is an understudied driver of infectious disease dynamics. Amidst the ongoing southwestern North American megadrought, California (USA) is having the driest multi-decadal period since 800 CE, exacerbated by anthropogenic warming. In this study, we aimed to examine the influence of drought on coccidioidomycosis, an emerging infectious disease in southwestern USA. METHODS: We analysed California census tract-level surveillance data from 2000 to 2020 using generalised additive models and distributed monthly lags on precipitation and temperature. We then developed an ensemble prediction algorithm of incident cases of coccidioidomycosis per census tract to estimate the counterfactual incidence that would have occurred in the absence of drought. FINDINGS: Between April 1, 2000, and March 31, 2020, there were 81 448 reported cases of coccidioidomycosis throughout California. An estimated 1467 excess cases of coccidioidomycosis were observed in California in the 2 years following the drought that occurred between 2007 and 2009, and an excess 2649 drought-attributable cases of coccidioidomycosis were observed in the 2 years following the drought that occurred between 2012 and 2015. These increased numbers of cases more than offset the declines in cases that occurred during drought. An IQR increase in summer temperatures was associated with 2·02 (95% CI 1·84-2·22) times higher incidence in the following autumn (September to November), and an IQR increase in precipitation in the winter was associated with 1·45 (1·36-1·55) times higher incidence in the autumn. The effect of winter precipitation was 36% (25-48) stronger when preceded by two dry, rather than average, winters. Incidence in arid counties was most sensitive to precipitation fluctuations, while incidence in wetter counties was most sensitive to temperature. INTERPRETATION: In California, multi-year cycles of dry conditions followed by a wet winter increases transmission of coccidioidomycosis, especially in historically wetter areas. With anticipated increasing frequency of drought in southwestern USA, continued expansion of coccidioidomycosis, along with more intense seasons, is expected. Our results motivate the need for heightened precautions against coccidioidomycosis in seasons that follow major droughts. FUNDING: National Institutes of Health.
From hampering the ability of water utilities to fill their reservoirs to leaving forests parched and ready to burn, drought is a unique natural hazard that impacts many human and natural systems. A great deal of research and synthesis to date has been devoted to understanding how drought conditions harm agricultural operations, leaving other drought-vulnerable sectors relatively under-served. This review aims to fill in such gaps by synthesizing literature from a diverse array of scientific fields to detail how drought impacts nonagricultural sectors of the economy: public water supply, recreation and tourism, forest resources, and public health. We focus on the Intermountain West region of the United States, where the decadal scale recurrence of severe drought provides a basis for understanding the causal linkages between drought conditions and impacts. This article is categorized under: Human Water & Value of Water Science of Water & Water Extremes.
BACKGROUND: Research on temperature and respiratory hospitalizations is lacking in the southeastern U.S. where cold weather is relatively rare. This retrospective study examined the association between cold waves and pneumonia and influenza (P&I) emergency department (ED) visits and hospitalizations in three metro-Atlanta hospitals. METHODS: We used a case-crossover design, restricting data to the cooler seasons of 2009-2019, to determine whether cold waves influenced ED visits and hospitalizations. This analysis considered effects by race/ethnicity, age, sex, and severity of comorbidities. We used generalized additive models and distributed lag non-linear models to examine these relationships over a 21-day lag period. RESULTS: The odds of a P&I ED visit approximately one week after a cold wave were increased by as much as 11%, and odds of an ED visit resulting in hospitalization increased by 8%. For ED visits on days with minimum temperatures >20 °C, there was an increase of 10-15% in relative risk (RR) for short lags (0-2 days), and a slight decrease in RR (0-5%) one week later. For minimum temperatures <0 °C, RR decreased at short lags (5-10%) before increasing (1-5%) one week later. Hospital admissions exhibited a similar, but muted, pattern. CONCLUSION: Unusually cold weather influenced ED visits and admissions in this population.
Coccidioidomycosis, or valley fever, is an infectious fungal disease currently endemic to the southwestern United States. Symptoms of valley fever range in severity from flu-like illness to severe morbidity and mortality. Warming temperatures and changes in precipitation patterns may cause the area of endemicity to expand northward throughout the western United States, putting more people at risk for contracting valley fever. This may increase the health and economic burdens from this disease. We developed an approach to describe the relationship between climate conditions and valley fever incidence using historical data and generated projections of future incidence in response to both climate change and population trends using the Climate Change Impacts and Risk Analysis (CIRA) framework developed by the U.S. Environmental Protection Agency. We also developed a method to estimate economic impacts of valley fever that is based on case counts. For our 2000-15 baseline time period, we estimated annual medical costs, lost income, and economic welfare losses for valley fever in the United States were $400,000 per case, and the annual average total cost was $3.9 billion per year. For a high greenhouse gas emission scenario and accounting for population growth, we found that total annual costs for valley fever may increase up to 164% by year 2050 and up to 380% by 2090. By the end of the twenty-first century, valley fever may cost $620,000 per case and the annual average total cost may reach $18.5 billion per year. This work contributes to the broader effort to monetize climate change-attributable damages in the United States.
BACKGROUND: Increasing number of studies have linked air pollution exposure with renal function decline and disease. However, there is a lack of data on its impact among end-stage kidney disease (ESKD) patients and its potential modifying effect from extreme heat events (EHE). METHODS: Fresenius Kidney Care records from 28 selected northeastern US counties were used to pool daily all-cause mortality (ACM) and all-cause hospital admissions (ACHA) counts. County-level daily ambient PM(2.5) and ozone (O(3)) were estimated using a high-resolution spatiotemporal coupled climate-air quality model and matched to ESKD patients based on ZIP codes of treatment sites. We used time-stratified case-crossover analyses to characterize acute exposures using individual and cumulative lag exposures for up to 3 days (Lag 0-3) by using a distributed lag nonlinear model framework. We used a nested model comparison hypothesis test to evaluate for interaction effects between air pollutants and EHE and stratification analyses to estimate effect measures modified by EHE days. RESULTS: From 2001 to 2016, the sample population consisted of 43,338 ESKD patients. We recorded 5217 deaths and 78,433 hospital admissions. A 10-unit increase in PM(2.5) concentration was associated with a 5% increase in ACM (rate ratio [RR(Lag0)(-)(3)]: 1.05, 95% CI: 1.00-1.10) and same-day O(3) (RR(Lag0): 1.02, 95% CI: 1.01-1.03) after adjusting for extreme heat exposures. Mortality models suggest evidence of interaction and effect measure modification, though not always simultaneously. ACM risk increased up to 8% when daily ozone concentrations exceeded National Ambient Air Quality Standards established by the United States, but the increases in risk were considerably higher during EHE days across lag periods. CONCLUSION: Our findings suggest interdependent effects of EHE and air pollution among ESKD patients for all-cause mortality risks. National level assessments are needed to consider the ESKD population as a sensitive population and inform treatment protocols during extreme heat and degraded pollution episodes.
BACKGROUND/OBJECTIVE: Research suggests gestational exposure to particulate matter ≤2.5 μm (PM(2.5)) and extreme heat may independently increase risk of birth defects. We investigated whether duration of gestational extreme heat exposure modifies associations between PM(2.5) exposure and specific congenital heart defects (CHDs). We also explored nonlinear exposure-outcome relationships. METHODS: We identified CHD case children (n = 2824) and non-malformed live-birth control children (n = 4033) from pregnancies ending between 1999 and 2007 in the National Birth Defects Prevention Study, a U.S. population-based multicenter case-control study. We assigned mothers 6-week averages of PM(2.5) exposure during the cardiac critical period (postconceptional weeks 3-8) using the closest monitor within 50 km of maternal residence. We assigned a count of extreme heat days (EHDs, days above the 90th percentile of daily maximum temperature for year, season, and weather station) during this period using the closest weather station. Using generalized additive models, we explored logit-nonlinear exposure-outcome relationships, concluding logistic models were reasonable. We estimated joint effects of PM(2.5) and EHDs on six CHDs using logistic regression models adjusted for mean dewpoint and maternal age, education, and race/ethnicity. We assessed multiplicative and additive effect modification. RESULTS: Conditional on the highest observed EHD count (15) and at least one critical period day during spring/summer, each 5 μg/m(3) increase in average PM(2.5) exposure was significantly associated with perimembranous ventricular septal defects (VSDpm; OR: 1.54 [95% CI: 1.01, 2.41]). High EHD counts (8+) in the same population were positively, but non-significantly, associated with both overall septal defects and VSDpm. Null or inverse associations were observed for lower EHD counts. Multiplicative and additive effect modification estimates were consistently positive in all septal models. CONCLUSIONS: Results provide limited evidence that duration of extreme heat exposure modifies the PM(2.5)-septal defects relationship. Future research with enhanced exposure assessment and modeling techniques could clarify these relationships.
BACKGROUND: Individuals with respiratory conditions, such as asthma, are particularly susceptible to adverse health effects associated with higher levels of ambient air pollution and temperature. This study evaluates whether hourly levels of fine particulate matter (PM2.5) and dry bulb globe temperature (DBGT) are associated with the lung function of adult participants with asthma. METHODS AND FINDINGS: Global positioning system (GPS) location, respiratory function (measured as forced expiratory volume at 1 second (FEV1)), and self-reports of asthma medication usage and symptoms were collected as part of the Exposure, Location, and Lung Function (ELF) study. Hourly ambient PM2.5 and DBGT exposures were estimated by integrating air quality and temperature public records with time-activity patterns using GPS coordinates for each participant (n = 35). The relationships between acute PM2.5, DBGT, rescue bronchodilator use, and lung function collected in one week periods and over two seasons (summer/winter) were analyzed by multivariate regression, using different exposure time frames. In separate models, increasing levels in PM2.5, but not DBGT, were associated with rescue bronchodilator use. Conversely DBGT, but not PM2.5, had a significant association with FEV1. When DBGT and PM2.5 exposures were placed in the same model, the strongest association between cumulative PM2.5 exposures and the use of rescue bronchodilator was identified at the 0-24 hours (OR = 1.030; 95% CI = 1.012-1.049; p-value = 0.001) and 0-48 hours (OR = 1.030; 95% CI = 1.013-1.057; p-value = 0.001) prior to lung function measure. Conversely, DBGT exposure at 0 hours (β = 3.257; SE = 0.879; p-value>0.001) and 0-6 hours (β = 2.885; SE = 0.903; p-value = 0.001) hours before a reading were associated with FEV1. No significant interactions between DBGT and PM2.5 were observed for rescue bronchodilator use or FEV1. CONCLUSIONS: Short-term increases in PM2.5 were associated with increased rescue bronchodilator use, while DBGT was associated with higher lung function (i.e. FEV1). Further studies are needed to continue to elucidate the mechanisms of acute exposure to PM2.5 and DBGT on lung function in asthmatics.
Air pollution risk assessments typically estimate ozone-attributable mortality counts using concentration-response (C-R) parameters from epidemiologic studies that treat temperature as a potential confounder. However, some recent epidemiologic studies have indicated that temperature can modify the relationship between short-term ozone exposure and mortality, which has potentially important implications when considering the impacts of climate change on public health. This proof-of-concept analysis quantifies counts of temperature-modified ozone-attributable mortality using temperature-stratified C-R parameters from a multicity study in which the pooled ozone-mortality effect coefficients change in concert with daily temperature. Meteorology downscaled from two global climate models is used with a photochemical transport model to simulate ozone concentrations over the 21st century using two emission inventories: one holding air pollutant emissions constant at 2011 levels and another accounting for reduced emissions through the year 2040. The late century climate models project increased summer season temperatures, which in turn yields larger total counts of ozone-attributable deaths in analyses using temperature-stratified C-R parameters compared to the traditional temperature confounder approach. This analysis reveals substantial heterogeneity in the magnitude and distribution of the temperature-stratified ozone-attributable mortality results, which is a function of regional variability in both the C-R relationship and the model-predicted temperature and ozone.
Wildfires can significantly impact air quality and human health. However, little is known about how different fuel bed components contribute to these impacts. This study investigates the air quality impacts of duff and peat consumption during wildfires in the southeastern United States, with a focus on the differing contributions of fine particulate matter less than 2.5 mu m in size (PM2.5) and ozone (O-3) to air quality episodes associated with the four largest wildfire events in the region during this century. The emissions of duff burning were estimated based on a field measurement of a 2016 southern Appalachian fire. The emissions from the burning of other fuels were obtained from the Fire INventory from NCAR (FINN). The air quality impacts were simulated using a three-dimensional regional air quality model. The results show the duff burning emitted PM2.5 comparable to the burning of the above-ground fuels. The simulated surface PM2.5 concentrations due to duff burning increased by 61.3% locally over a region approximately 300 km within the fire site and by 21.3% and 29.7% in remote metro Atlanta and Charlotte during the 2016 southern Appalachian fires and by 131.9% locally and by 17.7% and 24.8% in remote metro Orlando and Miami during the 2007 Okefenokee Fire. However, the simulated ozone impacts from the duff burning were negligible due to the small duff emission factors of ozone precursors such as NOx. This study suggests the need to improve the modeling of PM2.5 and the air quality, human health, and climate impacts of wildfires in moist ecosystems by including duff burning in global fire emission inventories.
Climate change-related disasters have drawn increased attention to the impact of air pollution on health. 122 children ages 9-11 years old, M(SD) = 9.91(.56), participated. Levels of particulate matter (PM2.5) near participants’ homes were obtained from the Environmental Protection Agency. Cytokines were assayed from 100 child serum samples: IL-6, IL-8, IL-10, and TNFα. Autonomic physiology was indexed by pre-ejection period (PEP), respiratory sinus arrhythmia (RSA), cardiac autonomic regulation (CAR), and cardiac autonomic balance (CAB). IL-6 was positively related to daily PM2.5 (r = .26, p = .009). IL-8 was negatively associated with monthly PM2.5 (r = -.23, p = .02). PEP was positively related to daily (r = .29, p = .001) and monthly PM2.5 (r = .18, p = .044). CAR was negatively associated with daily PM2.5 (r = -.29, p = .001). IL-10, TNFα, RSA, and CAB were not associated with PM2.5. Air pollution may increase risk of inflammation in children.
Major wildfires and heatwaves have begun to increase in frequency throughout much of the United States, particularly in western states such as California, causing increased risk to public health. Air pollution is exacerbated by both wildfires and warmer temperatures, thus adding to such risk. With climate change and the continued increase in global average temperatures, the frequency of major wildfires, heat days, and unhealthy air pollution episodes is projected to increase, resulting in the potential for compounding risks. Risks will likely vary by region and may disproportionately impact low-income communities and communities of color. In this study, we processed daily particulate matter (PM) data from over 18,000 low-cost PurpleAir sensors, along with gridMET daily maximum temperature data and government-compiled wildfire perimeter data from 2018-2020 in order to examine the occurrence of compound risk (CR) days (characterized by high temperature and high PM2.5) at the census tract level in California, and to understand how such days have been impacted by the occurrence of wildfires. Using American Community Survey data, we also examined the extent to which CR days were correlated with household income, race/ethnicity, education, and other socioeconomic factors at the census tract level. Results showed census tracts with a higher frequency of CR days to have statistically higher rates of poverty and unemployment, along with high proportions of child residents and households without computers. The frequency of CR days and elevated daily PM2.5 concentrations appeared to be strongly related to the occurrence of nearby wildfires, with over 20% of days with sensor-measured average PM2.5 > 35 mu g/m(3) showing a wildfire within a 100 km radius and over two-thirds of estimated CR days falling on such days with a nearby wildfire. Findings from this study are important to policymakers and government agencies who preside over the allocation of state resources as well as organizations seeking to empower residents and establish climate resilient communities.
Indoor flooding is a leading contributor to indoor dampness and the associated mold infestations in the coastal United States. Whether the prevalent mold genera that infest the coastal flood-prone buildings are different from those not flood-prone is unknown. In the current case study of 28 mold-infested buildings across the U.S. east coast, we surprisingly noted a trend of higher prevalence of indoor Aspergillus and Penicillium genera (denoted here as Asp-Pen) in buildings with previous flooding history. Hence, we sought to determine the possibility of a potential statistically significant association between indoor Asp-Pen prevalence and three building-related variables: (i) indoor flooding history, (ii) geographical location, and (iii) the building’s use (residential versus non-residential). Culturable spores and hyphal fragments in indoor air were collected using the settle-plate method, and corresponding genera were confirmed using phylogenetic analysis of their ITS sequence (the fungal barcode). Analysis of variance (ANOVA) using Generalized linear model procedure (GLM) showed that Asp-Pen prevalence is significantly associated with indoor flooding as well as coastal proximity. To address the small sample size, a multivariate decision tree analysis was conducted, which ranked indoor flooding history as the strongest determinant of Asp-Pen prevalence, followed by geographical location and the building’s use.
Rising emissions from wildfires over recent decades in the Pacific Northwest are known to counteract the reductions in human-produced aerosol pollution over North America. Since amplified Pacific Northwest wildfires are predicted under accelerating climate change, it is essential to understand both local and transported contributions to air pollution in North America. Here, we find corresponding increases for carbon monoxide emitted from the Pacific Northwest wildfires and observe significant impacts on both local and down-wind air pollution. Between 2002 and 2018, the Pacific Northwest atmospheric carbon monoxide abundance increased in August, while other months showed decreasing carbon monoxide, so modifying the seasonal pattern. These seasonal pattern changes extend over large regions of North America, to the Central USA and Northeast North America regions, indicating that transported wildfire pollution could potentially impact the health of millions of people.
The Great Plains drought of 1931-1939 was a prolonged socio-ecological disaster with widespread impacts on society, economy, and health. While its immediate impacts are well documented, we know much less about the disaster’s effects on distal human outcomes. In particular, the event’s effects on later life mortality remain almost entirely unexplored. Closing this gap would contribute to our understanding of the long-term effects of place-based stress. To help fill this gap, I use a new, massive, linked mortality dataset to investigate whether young men’s exposure to drought and dust storms in 341 Great Plains counties was linked to a higher risk of death in early-old age. Contrary to expectations, results suggest exposure to drought conditions had no obvious adverse effect among men aged 65 years or older at time of death-rather, the average age at death was slightly higher than for comparable men without exposure. This effect also appears to have been stronger among Plainsmen who stayed in place until the drought ended. A discussion of potential explanations for these counterintuitive results is provided.
California is one of the nation’s top agriculture producers and is vulnerable to extreme events such as droughts and heat waves. Concurrent extreme events may further stress water and energy resources, exerting greater adverse socioeconomic, environmental, and health impacts than individual events. Here we examine the features of compound drought, heat wave, and dust events in California during spring and summer. From 2003 to 2020, 16 compound events are found in warm seasons, with a mean duration of similar to 4 days. Compound events are characterized by enhanced surface temperature up to 4.5 degrees C over northern and western California, reduced soil moisture and vegetation density, and an increase in dust optical depth (DOD) by 0.05-0.1 over central and southern California. The enhanced DOD is largely associated with severe vegetation dieback that favors dust emissions and southeasterly wind anomalies that support northward transport of dust from source regions in southern California. Surface fine dust and PM2.5 concentrations also increase by more than 0.5 and 5 mu g m(-3), respectively, during compound events associated with both enhanced dust emissions and a relatively stable atmosphere that traps pollutants. The development of the compound events is related to an anomalous high over the west coast in the lower to middle troposphere, which is a pattern favoring sinking motion and dry conditions in California. The anomalous high is embedded in a wave train that develops up to 7 days before the events. In comparison with heat wave extremes alone, compound events show significantly higher DOD and lower vegetation density associated with droughts.
OBJECTIVE: The purpose of this study was to assess health-related responses to wildfire smoke on social media. We examined whether seasonal wildfire smoke is an active topic on Twitter, the correlation between fine particulate matter (PM(2.5) ) and Twitter search terms, and dimensions of community-level expression to wildfire smoke through tweets. DESIGN: Search terms were identified using a conceptual model developed and refined by healthcare providers and public health experts. Wildfire-related tweets were downloaded from Twitter users in Spokane, Washington during the 2017 and 2018 wildfire seasons. PM(2.5) data were correlated with the search terms. A subset of tweets was deductively and then inductively coded to identify perceptions and behavioral responses to wildfire smoke. RESULTS: Seasonal wildfire smoke is an active topic on Twitter. The term “smoke” was strongly correlated with poor air quality and “unhealthy” was moderately correlated. Deductive analyses revealed a multidimensional response to wildfire smoke. Inductive analysis identified new areas of concern, such as pet and animal health. CONCLUSIONS: Social media is a lens through which public health professionals can assess and respond to local community needs. Findings will be used to broaden the conceptual model, enhance ongoing surveillance of community-identified health risks, and communicate protective actions.
The purpose of this study was to assess the effect of wildland firefighting on measures of cardiovascular health. The study was carried out in two parts. Part one assessed relationships between years of wildland firefighting and cardiovascular variables (n = 28). Part two looked at cardiovascular variables pre and post a wildland firefighting season (n = 18). Independent of age, a statistically significant relationship between number of seasons firefighting and VO(2max) was found (r(2)=.140, p=.048). A statistically significant reduction in VO(2max) of -4.1 ± 5.7 ml·kg(-1) min(-1) was witnessed following fire season (95%CI=-6.9 to -1.3, p=.048). Year to date hazard pay was significantly correlated with ankle-brachial index (r=-.474, p=.040). Wildland firefighters who reported >640 h of hazard pay had a greater VO(2max) reduction than those reporting less hazard pay (-1.7 ± 5.7 ml·kg(-1)·min(-1) vs. -7.1 ± 4.3 ml·kg(-1)·min(-1), p=.037). Wildland firefighting may negatively impact cardiorespiratory fitness and arterial health.
Wildfires are becoming more frequent and destructive in a changing climate. Fine particulate matter, PM(2.5), in wildfire smoke adversely impacts human health. Recent toxicological studies suggest that wildfire particulate matter may be more toxic than equal doses of ambient PM(2.5). Air quality regulations however assume that the toxicity of PM(2.5) does not vary across different sources of emission. Assessing whether PM(2.5) from wildfires is more or less harmful than PM(2.5) from other sources is a pressing public health concern. Here, we isolate the wildfire-specific PM(2.5) using a series of statistical approaches and exposure definitions. We found increases in respiratory hospitalizations ranging from 1.3 to up to 10% with a 10 μg m(-3) increase in wildfire-specific PM(2.5), compared to 0.67 to 1.3% associated with non-wildfire PM(2.5). Our conclusions point to the need for air quality policies to consider the variability in PM(2.5) impacts on human health according to the sources of emission.
Fire Influence on Regional to Global Environments and Air Quality was a NOAA/NASA collaborative campaign conducted during the summer of 2019. The objectives included identifying and quantifying wildfire composition, smoke evolution, and climate and health impacts of wildfires and agricultural fires in the United States. Ground based mobile sampling via sorbent tubes occurred at the Nethker and Williams Flats fires (2019) and Chief Timothy and Whitetail Loop fires (2020) in Idaho and Washington. Air samples were analyzed through thermal desorption-gas chromatography-mass spectrometry for a variety of volatile organic compounds to elucidate both composition and health impacts. Benzene, toluene, ethylbenzene, xylenes, butenes, phenol, isoprene and pinenes were observed in the wildfire smoke, with benzene ranging from 0.04 to 25 ppbv. Health risk was assessed for each fire by determining sub-chronic (wildfire event) and projected chronic inhalation risk exposure from benzene, a carcinogen, as well as other non-carcinogenic compounds including toluene, ethylbenzene, xylenes, and hexane. The cancer risk of benzene from sub-chronic exposure was 1 extra cancer per million people and ranged from 1 to 19 extra cancers per million people for the projected chronic scenarios, compared to a background level of 1 extra cancer per million people. The hazard index of non-carcinogenic compounds was less than one for all scenarios and wildfires sampled, which was considered low risk for non-cancer health events.
Five-year retrospective analysis of respiratory viruses in children less than 18 years old at Tripler Army Medical Center and outlying clinics in Oahu. Respiratory syncytial virus and influenza A showed pronounced seasonality with peaks from September to December and December to March, respectively. Results provide a better understanding of the timing of viral preventive strategies in Oahu.
Exposure to wildfire smoke increases the risk of respiratory and cardiovascular hospital admissions. Health impact assessments, used to inform decision-making processes, characterize the health impacts of environmental exposures by combining preexisting epidemiological concentration-response functions (CRFs) with estimates of exposure. These two key inputs influence the magnitude and uncertainty of the health impacts estimated, but for wildfire-related impact assessments the extent of their impact is largely unknown. We first estimated the number of respiratory, cardiovascular, and asthma hospital admissions attributable to fire-originated PM2.5 exposure in central California during the October 2017 wildfires, using Monte Carlo simulations to quantify uncertainty with respect to the exposure and epidemiological inputs. We next conducted sensitivity analyses, comparing four estimates of fire-originated PM2.5 and two CRFs, wildfire and nonwildfire specific, to understand their impact on the estimation of excess admissions and sources of uncertainty. We estimate the fires accounted for an excess 240 (95% CI: 114, 404) respiratory, 68 (95% CI: -10, 159) cardiovascular, and 45 (95% CI: 18, 81) asthma hospital admissions, with 56% of admissions occurring in the Bay Area. Although differences between impact assessment methods are not statistically significant, the admissions estimates’ magnitude is particularly sensitive to the CRF specified while the uncertainty is most sensitive to estimates of fire-originated PM2.5. Not accounting for the exposure surface’s uncertainty leads to an underestimation of the uncertainty of the health impacts estimated. Employing context-specific CRFs and using accurate exposure estimates that combine multiple data sets generates more certain estimates of the acute health impacts of wildfires.
Wildfire smoke is one of the most significant concerns of human and environmental health, associated with its substantial impacts on air quality, weather, and climate. However, biomass burning emissions and smoke remain among the largest sources of uncertainties in air quality forecasts. In this study, we evaluate the smoke emissions and plume forecasts from 12 state-of-the-art air quality forecasting systems during the Williams Flats fire in Washington State, US, August 2019, which was intensively observed during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign. Model forecasts with lead times within 1 d are intercompared under the same framework based on observations from multiple platforms to reveal their performance regarding fire emissions, aerosol optical depth (AOD), surface PM2.5, plume injection, and surface PM2.5 to AOD ratio. The comparison of smoke organic carbon (OC) emissions suggests a large range of daily totals among the models, with a factor of 20 to 50. Limited representations of the diurnal patterns and day-to-day variations of emissions highlight the need to incorporate new methodologies to predict the temporal evolution and reduce uncertainty of smoke emission estimates. The evaluation of smoke AOD (sAOD) forecasts suggests overall underpredictions in both the magnitude and smoke plume area for nearly all models, although the high-resolution models have a better representation of the fine-scale structures of smoke plumes. The models driven by fire radiative power (FRP)-based fire emissions or assimilating satellite AOD data generally outperform the others. Additionally, limitations of the persistence assumption used when predicting smoke emissions are revealed by substantial underpredictions of sAOD on 8 August 2019, mainly over the transported smoke plumes, owing to the underestimated emissions on 7 August. In contrast, the surface smoke PM2.5 (sPM(2.5)) forecasts show both positive and negative overall biases for these models, with most members presenting more considerable diurnal variations of sPM(2.5). Overpredictions of sPM(2.5) are found for the models driven by FRP-based emissions during nighttime, suggesting the necessity to improve vertical emission allocation within and above the planetary boundary layer (PBL). Smoke injection heights are further evaluated using the NASA Langley Research Center’s Differential Absorption High Spectral Resolution Lidar (DIAL-HSRL) data collected during the flight observations. As the fire became stronger over 38 August, the plume height became deeper, with a day-today range of about 2-9 km a.g.l. However, narrower ranges are found for all models, with a tendency of overpredicting the plume heights for the shallower injection transects and underpredicting for the days showing deeper injections. The misrepresented plume injection heights lead to inaccurate vertical plume allocations along the transects corresponding to transported smoke that is 1 d old. Discrepancies in model performance for surface PM2.5 and AOD are further suggested by the evaluation of their ratio, which cannot be compensated for by solely adjusting the smoke emissions but are more attributable to model representations of plume injections, besides other possible factors including the evolution of PBL depths and aerosol optical property assumptions. By consolidating multiple forecast systems, these results provide strategic insight on pathways to improve smoke forecasts.
Background: Recent increases in wildfire frequency and severity necessitate better understanding of health effects of wildfire smoke to protect affected populations. Objectives: We examined relationships between fine particulate matter (PM2.5) and morbidity during wildfires in California, and whether those relationships differed during the fire compared to a similar non-fire period. Methods: For nine San Francisco Bay Area counties, daily county- level diagnosis-specific counts of emergency department visits (EDVs) and hospitalizations were linked with county-level estimates of daily mean PM2.5 during the October 2017 Northern California wildfires and similar October days in 2015, 2016, and 2017. Associations were estimated using Poisson regression. Results: The median difference between county PM2.5 during the fire versus the non-fire period was 23.4 mu g/ m3, with days exceeding 80 mu g/m3 in some counties. Over the entire study period, PM2.5 was most consistently linked to EDVs for respiratory disease ( RREDV(lag0) per 23.4 mu g/ m3 increase: 1.25, 95% CI: 1.21, 1.30), asthma, chronic lower respiratory disease (CLRD; RREDV(lag0): 1.18, 95% CI: 1.10, 1.27), and acute myocardial infarction (RREDV(lag0): 1.14, 95% CI: 1.03, 1.25). Increases in acute upper respiratory infections and decreases in mental/behavioral EDVs were observed but were sensitive to model specification, specifically the inclusion of time-related covariates. Comparing fire and non-fire period EDV associations, we observed indications that PM2.5 during the fire was more strongly associated with asthma (RRlag0: 1.46, 95% CI: 1.38, 1.55) compared to non-fire period PM2.5 (RRlag0: 0.77, 95% CI: 0.55, 1.08), and the opposite observed for dysrhythmia, with the asthma difference being particularly robust to model choice. For hospitalizations, the most robust PM2.5 relationships were positive associations with respiratory, CLRD, and diabetes, and inverse associations with pneumonia. Respiratory and CLRD effect estimates were generally similar or smaller than for EDVs. Conclusions: Elevated short-term PM2.5 levels from wildfire smoke appears to impact respiratory and other health domains. (c) 2021 Elsevier B.V. All rights reserved.
BACKGROUND AND OBJECTIVES: Exposure to airborne fine particles with diameters <= 2.5 mu m (PM2.5) pollution is a well-established cause of respiratory diseases in children; whether wildfire-specific PM2.5 causes more damage, however, remains uncertain. We examine the associations between wildfire-specific PM2.5 and pediatric respiratory health during the period 2011-2017 in San Diego County, California, and compare these results with other sources of PM2.5. METHODS: Visits to emergency and urgent care facilities of Rady's Children Hospital network in San Diego County, California, by individuals (aged <= 19 years) with >= 1 of the following respiratory conditions: difficulty breathing, respiratory distress, wheezing, asthma, or cough were regressed on daily, community-level exposure to wildfire-specific PM2.5 and PM2.5 from ambient sources (eg, traffic emissions). RESULTS: A 10-unit increase in PM2.5 (from nonsmoke sources) was estimated to increase the number of admissions by 3.7% (95% confidence interval: 1.2% to 6.1%). In contrast, the effect of PM2.5 attributable to wildfire was estimated to be a 30.0% (95% confidence interval: 26.6% to 33.4%) increase in visits. CONCLUSIONS: Wildfire-specific PM2.5 was found to be similar to 10 times more harmful on children’s respiratory health than PM2.5 from other sources, particularly for children aged 0 to 5 years. Even relatively modest wildfires and associated PM2.5 resolved on our record produced major health impacts, particularly for younger children, in comparison with ambient PM2.5.
Major wildfires starting in the summer of 2020 along the west coast of the United States made PM2.5 concentrations in this region rank among the highest in the world. Washington was impacted both by active wildfires in the state and aged wood smoke transported from fires in Oregon and California. This study aims to estimate the magnitude and disproportionate spatial impacts of increased PM2.5 concentrations attributable to these wildfires on population health. Daily PM2.5 concentrations for each county before and during the 2020 Washington wildfire episode (September 7-19) were obtained from regulatory air monitors. Utilizing previously established concentration-response function (CRF) of PM2.5 (CRF of total PM2.5) and odds ratio (OR) of wildfire smoke days (OR of wildfire smoke days) for mortality, we estimated excess mortality attributable to the increased PM2.5 concentrations in Washington. On average, daily PM2.5 concentrations increased 97.1 mu g/m(3) during the wildfire smoke episode. With CRF of total PM2.5, the 13-day exposure to wildfire smoke was estimated to lead to 92.2 (95% CI: 0.0, 178.7) more all-cause mortality cases; with OR of wildfire smoke days, 38.4 (95% CI: 0.0, 93.3) increased all-cause mortality cases and 15.1 (95% CI: 0.0, 27.9) increased respiratory mortality cases were attributable to the wildfire smoke episode. The potential impact of avoiding elevated PM2.5 exposures during wildfire events significantly reduced the mortality burden. Because wildfire smoke episodes are likely to impact the Pacific Northwest in future years, continued preparedness and mitigations to reduce exposures to wildfire smoke are necessary to avoid excess health burden.
Increases in wildfire activity across the Western US pose a significant public health threat. While there is evidence that wildfire smoke is detrimental for respiratory health, the impacts on cardiovascular health remain unclear. This study evaluates the association between fine particulate matter (PM(2.5)) from wildfire smoke and unscheduled cardiorespiratory hospital visits in California during the 2004-2009 wildfire seasons. We estimate daily mean wildfire-specific PM(2.5) with Goddard Earth Observing System-Chem, a global three-dimensional model of atmospheric chemistry, with wildfire emissions estimates from the Global Fire Emissions Database. We defined a “smoke event day” as cumulative 0-1-day lag wildfire-specific PM(2.5) ≥ 98th percentile of cumulative 0-1 lag day wildfire PM(2.5). Associations between exposure and outcomes are estimated using negative binomial regression. Results indicate that smoke event days are associated with a 3.3% (95% CI: [0.4%, 6.3%]) increase in visits for all respiratory diseases and a 10.3% (95% CI: [2.3%, 19.0%]) increase for asthma specifically. Stratifying by age, we found the largest effect for asthma among children ages 0-5 years. We observed no significant association between exposure and overall cardiovascular disease, but stratified analyses revealed increases in visits for all cardiovascular, ischemic heart disease, and heart failure among non-Hispanic white individuals and those older than 65 years. Further, we found a significant interaction between smoke event days and daily average temperature for all cardiovascular disease visits, suggesting that days with high wildfire PM(2.5) concentrations and high temperatures may pose greater risk for cardiovascular disease. These results suggest substantial increases in adverse outcomes from wildfire smoke exposure and indicate the need for improved prevention strategies and adaptations to protect vulnerable populations.
This study proposes an approach to improve the spatial resolution of ground-level concentrations of PM2.5 that is required to assess health risks associated with exposure to pollutants released during wildfires. We use this approach to analyze the impact on air quality of the wildfire complex consisting of the Atlas, Nuns, Tubbs, Pocket, and Redwood Valley fires in northern California that started on October 8, 2017 and the Camp Fire in northern California that was first reported on November 8, 2018. The PM2.5 concentrations measured in populated areas downwind of these fires were well above the 24-h standard of 35 mu g/m3 during several days of both fires. To estimate health risks at locations where ground-based monitors did not provide sufficient spatial coverage we first estimate the emissions from the fires by fitting concentration estimates from two models, a Lagrangian model and a segmented plume dispersion model, to corresponding concentrations from ground monitors. We also use a power law model to fit the measured PM2.5 concentrations to the ratio of aerosol optical depth (AOD) to planetary boundary layer measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried by NASA’s Terra and Aqua satellites. Dispersion model estimates are then combined with estimates from the AOD model to compute ground-level concentrations at a resolution of 1 km. Kriged residuals between estimates from the combined model and measured PM2.5 concentrations are then added to obtain high resolution maps that can be used for exposure studies.
Background: Wildfire smoke is responsible for around 20% of all particulate emissions in the U.S. and affects millions of people worldwide. Children are especially vulnerable, as ambient air pollution exposure during early childhood is associated with reduced lung function. Most studies, however, have focused on the short-term impacts of wildfire smoke exposures. We aimed to identify long-term baseline epigenetic changes associated with early-life exposure to wildfire smoke. We collected nasal epithelium samples for whole genome bisulfite sequencing (WGBS) from two groups of adult female rhesus macaques: one group born just before the 2008 California wildfire season and exposed to wildfire smoke during early-life (n = 8), and the other group born in 2009 with no wildfire smoke exposure during early-life (n = 14). RNA-sequencing was also performed on a subset of these samples. Results: We identified 3370 differentially methylated regions (DMRs) (difference in methylation ≥5%, empirical p < 0.05) and 1 differentially expressed gene (FLOT2) (FDR < 0.05, fold of change ≥ 1.2). The DMRs were annotated to genes significantly enriched for synaptogenesis signaling, protein kinase A signaling, and a variety of immune processes, and some DMRs significantly correlated with gene expression differences. DMRs were also significantly enriched within regions of bivalent chromatin (top odds ratio = 1.46, q-value < 3 x 10^(-6)) that often silence key developmental genes while keeping them poised for activation in pluripotent cells. Conclusions: These data suggest that early-life exposure to wildfire smoke leads to long-term changes in the methylome over genes impacting the nervous and immune systems. Follow-up studies will be required to test whether these changes influence transcription following an immune/respiratory challenge.
Objective: The California Emergency Medical Services Authority manages and deploys California Medical Assistance Teams (CAL-MAT) to disaster medical incidents in the state. This analysis reviews diagnoses for ambulatory medical visits at multiple wildland fire incident base camp field sites in California during the 2020 fire season. Methods: Clinical data without personal health information were extracted retrospectively from patient care records from all patients seen by a provider. Results were entered into Excel spreadsheets with calculation of summary statistics. Results: During the 2020 fire season, CAL-MAT teams deployed 21 times for a total of 327 days to base camps supporting large fire incidents and cared for 1756 patients. Impacts of heat and environmental smoke are a constant factor near wildfires; however, our most common medical problem was rhus dermatitis (54.5%) due to poison oak. All 2020 medical missions were further complicated by prevention and management of coronavirus disease (COVID-19). Conclusions: There is very little literature regarding the acute medical needs facing responders fighting wildland fires. Ninety-five percent of clinical conditions presenting to a field medical team at the wildfire incident base camp during a severe fire season in California can be managed by small teams operating in field tents.
Driven by climate change, wildfires are increasing in frequency, duration, and intensity across the Western United States. Outdoor workers are being exposed to increasing wildfire-related particulate matter and smoke. Recognizing this emerging risk, Washington adopted an emergency rule and is presently engaged in creating a permanent rule to protect outdoor workers from wildfire smoke exposure. While there are growing bodies of literature on the exposure to and health effects of wildfire smoke in the general public and wildland firefighters, there is a gap in knowledge about wildfire smoke exposure among outdoor workers generally and construction workers specifically-a large category of outdoor workers in Washington totaling 200,000 people. Several data sources were linked in this study-including state-collected employment data and national ambient air quality data-to gain insight into the risk of PM2.5 exposure among construction workers and evaluate the impacts of different air quality thresholds that would have triggered a new Washington emergency wildfire smoke rule aimed at protecting workers from high PM2.5 exposure. Results indicate the number of poor air quality days has increased in August and September in recent years. Over the last decade, these months with the greatest potential for particulate matter exposure coincided with an annual peak in construction employment that was typically 9.4-42.7% larger across Washington counties (one county was 75.8%). Lastly, the ‘encouraged’ threshold of the Washington emergency rule (20.5 mu g m(-3)) would have resulted in 5.5 times more days subject to the wildfire rule on average across all Washington counties compared to its ‘required’ threshold (55.5 mu g m(-3)), and in 2020, the rule could have created demand for 1.35 million N-95 filtering facepiece respirators among construction workers. These results have important implications for both employers and policy makers as rules are developed. The potential policy implications of wildfire smoke exposure, exposure control strategies, and data gaps that would improve understanding of construction worker exposure to wildfire smoke are also discussed.
Frequent and widespread wildfires in the northwestern United States and Canada have become the “new normal” during the Northern Hemisphere summer months, which significantly degrades particulate matter air quality in the United States. Using the mid-visible Multi Angle Implementation of Atmospheric Correction (MAIAC) satellitederived aerosol optical depth (AOD) with meteorological information from the European Centre for Medium-Range Weather Forecasts (ECMWF) and other ancillary data, we quantify the impact of these fires on fine particulate matter concentration (PM2.5) air quality in the United States. We use a geographically weighted regression (GWR) method to estimate surface PM2.5 in the United States between low (2011) and high (2018) fire activity years. Our results indicate an overall leave-one-out cross-validation (LOOCV) R-2 value of 0.797 with root mean square error (RMSE) between 3 and 5 mu gm(-3). Our results indicate that smoke aerosols caused significant pollution changes over half of the United States. We estimate that nearly 29 states have increased PM2.5 during the fire-active year and that 15 of these states have PM2.5 concentrations more than 2 times that of the inactive year. Furthermore, these fires increased the daily mean surface PM2.5 concentrations in Washington and Oregon by 38 to 259 mu gm(-3), posing significant health risks especially to vulnerable populations. Our results also show that the GWR model can be successfully applied to PM2.5 estimations from wildfires, thereby providing useful information for various applications such as public health assessment.
Introduction: Wildfire smoke (WFS) exposure is a growing threat to human health, and lower socioeconomic position (SEP) has been shown to increase pollution susceptibility. Studies of SEP-related susceptibility, however, are often compromised due to spatial confounding between lower-SEP and pollution. Here we examine outdoorhoused nonhuman primates, living in natural social hierarchy in a common location, born during years of high vs. low WFS, to examine the separate and combined effects of WFS and social rank, an analog to SEP, on lung and immune function. Methods: Twenty-one females were born during extreme WFS events in summer 2008; 22 were born in summer 2009, during low WFS. Pulmonary function and circulating cytokines were measured three years later, in adolescence. We estimated fine particulate (PM2.5) and ozone exposures during each animal’s first 90 days and three years of age using regulatory data. Early-life social status was estimated using maternal rank at birth, as rank in females is relatively stable throughout life, and closely approximates mother’s rank. We tested associations among WFS exposure, rank, and endpoints using linear regression and ANOVA. Results: Higher WFS exposure in infancy was, on average, associated with lower functional residual capacity (FRC), residual volume (RV), tissue compliance (Ct), and IL-8 secretion in adolescence. Higher social rank conferred significantly higher expiratory reserve volume (ERV) and functional residual capacity (FRC) solely among those born in the high-WFS year (2008). Differences in effects of rank between years were not significant after adjustment for multiple comparisons. Conclusions: Exposure to WFS in infancy generally conferred lower adolescent respiratory volumes and inflammatory cytokines. Higher rank conferred higher respiratory volumes only among females born during WFS, suggesting the possibility that the health benefits of rank may be more apparent under environmental challenge.
BACKGROUND: Global climate change has led to an increase in the prevalence and severity of wildfires. Pollutants released into air, soil and groundwater from wildfires may impact embryo development leading to gastroschisis. OBJECTIVE: The objective of this study was to determine the association between wildfire exposure before and during pregnancy and the risk of foetal gastroschisis development. METHODS: This was a retrospective cohort study using The California Office of Statewide Health Planning and Development Linked Birth File linked to The California Department of Forestry and Fire Protection data between 2007 and 2010. Pregnancies complicated by foetal gastroschisis were identified by neonatal hospital discharge ICD-9 code. Pregnancies were considered exposed to wildfire if the mother’s primary residence zip code was within 15 miles to the closest edge of a wildfire. The exposure was further stratified by trimester or if exposed within 30 days prior to pregnancy. Multivariable log-binomial regression analyses were performed to estimate the association between wildfire exposure in each pregnancy epoch and foetal gastroschisis. RESULTS: Between 2007 and 2010, 844,348 (40%) births were exposed to wildfire in California. Compared with births without wildfire exposure, those with first-trimester exposure were associated with higher rates of gastroschisis, 7.8 vs. 5.7 per 10,000 births (adjusted relative risk [aRR] 1.28, 95% confidence interval [CI] 1.07, 1.54). Furthermore, those with prepregnancy wildfire exposure were also found to have higher rates of gastroschisis, 12.5 vs. 5.7 per 10,000 births, (aRR 2.17, 95% CI 1.42, 3.52). In contrast, second- and third-trimester wildfire exposures were not associated with foetal gastroschisis. CONCLUSIONS: Wildfire exposure within 30 days before pregnancy was associated with more than two times higher risk of foetal gastroschisis, whereas a 28% higher risk was demonstrated if exposure was in the first trimester.
The increased risk of wildfires and associated smoke exposure in the United States is a growing public health problem, particularly along the Wildland-Urban Interface (WUI). Using the measure of fire danger, the Energy Release Component, we define fire danger as the onset and duration of fire season, in the continental US, between 1979 and 2016. We then combine the measure of fire danger with census data to quantify changes in population fire exposure across the WUI. We determined that the largest increases in fire danger were observed in the Southwest, Intermountain, and Pacific Southwest regions. The increased fire danger, specifically during peak fire season, accounted for 6.1 more fires each year and 78,000 more acres burned each year, underscoring the link between fire danger and the risks of large fire occurrence and burn acreage. Finally, we observed significant population growth (121.2% between 1990 and 2010) within high-danger WUI areas, further implying significant increases in potential fire exposure.
Alaskan wildfires have major ecological, social, and economic consequences, but associated health impacts remain unexplored. We estimated cardiorespiratory morbidity associated with wildfire smoke (WFS) fine particulate matter with a diameter less than 2.5 μm (PM(2.5)) in three major population centers (Anchorage, Fairbanks, and the Matanuska-Susitna Valley) during the 2015-2019 wildfire seasons. To estimate WFS PM(2.5), we utilized data from ground-based monitors and satellite-based smoke plume estimates. We implemented time-stratified case-crossover analyses with single and distributed lag models to estimate the effect of WFS PM(2.5) on cardiorespiratory emergency department (ED) visits. On the day of exposure to WFS PM(2.5), there was an increased odds of asthma-related ED visits among 15-65 year olds (OR = 1.12, 95% CI = 1.08, 1.16), people >65 years (OR = 1.15, 95% CI = 1.01, 1.31), among Alaska Native people (OR = 1.16, 95% CI = 1.09, 1.23), and in Anchorage (OR = 1.10, 95% CI = 1.05, 1.15) and Fairbanks (OR = 1.12, 95% CI = 1.07, 1.17). There was an increased risk of heart failure related ED visits for Alaska Native people (Lag Day 5 OR = 1.13, 95% CI = 1.02, 1.25). We found evidence that rural populations may delay seeking care. As the frequency and magnitude of Alaskan wildfires continue to increase due to climate change, understanding the health impacts will be imperative. A nuanced understanding of the effects of WFS on specific demographic and geographic groups facilitates data-driven public health interventions and fire management protocols that address these adverse health effects.
Context: Wildfire events are increasing in prevalence and intensity in the Pacific Northwest. Effective communication of health risks and actions to reduce exposure to wildfire smoke is imperative. Objective: We assessed the content of wildfire smoke risk messages from government organizations and mainstream media during a major wildfire smoke event in August 2018. Design: We conducted a content analysis of wildfire smoke risk information communicated by local and state government organizations and the mainstream media. Setting: Eight Washington State counties during a statewide wildfire smoke event in August 2018. Main Outcome Measure: Leveraging the Extended Parallel Process Model and information in the existing literature on wildfire smoke and health, we assessed messages for the presence of information regarding health risk, personal interventions, administrative interventions, vulnerable populations, and trusted sources of information. Summary statistics were calculated to identify common messages about recommended interventions, vulnerable populations cited, and trusted sources of public health information. Results: Of the 273 identified government and media messages on wildfire smoke, the majority (71% and 66%) contained information about health risks. However, only 46% and 33% of government and media messages contained information about personal interventions to reduce risk, and 37% and 14% of government and media messages contained information about administrative interventions to reduce risk. Less than half of government and media messages (28% and 31%) contained information specific to vulnerable populations, and 58% and 46% of government and media messages contained any reference to a trusted source of information. Conclusions: While information about wildfire smoke and health risks was communicated during Washington’s August 2018 wildfire smoke event, there remains considerable opportunity to include additional information about interventions, vulnerable populations, and trusted sources of information. We recommend several opportunities to improve and evaluate risk communication and risk reduction before, during, and after future wildfire smoke events.
Extreme heat and ozone are co-occurring exposures that independently and synergistically increase the risk of respiratory disease. To our knowledge, no joint warning systems consider both risks; understanding their interactive effect can warrant use of comprehensive warning systems to reduce their burden. We examined heterogeneity in joint effects (on the additive scale) between heat and ozone at small geographical scales. A within-community matched design with a Bayesian hierarchical model was applied to study this association at the zip code level. Spatially varying relative risks due to interaction (RERI) were quantified to consider joint effects. Determinants of the spatial variability of effects were assessed using a random effects metaregression to consider the role of demographic/neighborhood characteristics that are known effect modifiers. A total of 817,354 unscheduled respiratory hospitalizations occurred in California from 2004 to 2013 in the May to September period. RERIs revealed no additive interaction when considering overall joint effects. However, when considering the zip code level, certain areas observed strong joint effects. A lower median income, higher percentage of unemployed residents, and exposure to other air pollutants within a zip code drove stronger joint effects; a higher percentage of commuters who walk/bicycle, a marker for neighborhood wealth, showed decreased effects. Results indicate the importance of going beyond average measures to consider spatial variation in the health burden of these exposures and predictors of joint effects. This information can be used to inform early warning systems that consider both heat and ozone to protect populations from these deleterious effects in identified areas.
Wildfires can be detrimental to urban and rural communities, causing impacts in the form of psychological stress, direct physical injury, and smoke-related morbidity and mortality. This study examined the area burned by wildfires over the entire state of California from the years 2000 to 2020 in order to quantify and identify whether burned area and fire frequency differed across Census tracts according to socioeconomic indicators over time. Wildfire data were obtained from the California Fire and Resource Assessment Program (FRAP) and National Interagency Fire Center (NIFC), while demographic data were obtained from the American Community Survey. Results showed a doubling in the number of Census tracts that experienced major wildfires and a near doubling in the number of people residing in wildfire-impacted Census tracts, mostly due to an over 23,000 acre/year increase in the area burned by wildfires over the last two decades. Census tracts with a higher fire frequency and burned area had lower proportions of minority groups on average. However, when considering Native American populations, a greater proportion resided in highly impacted Census tracts. Such Census tracts also had higher proportions of older residents. In general, high-impact Census tracts tended to have higher proportions of low-income residents and lower proportions of high-income residents, as well as lower median household incomes and home values. These findings are important to policymakers and state agencies as it relates to environmental justice and the allocation of resources before, during, and after wildfires in the state of California.
The health impacts of wildfire smoke are an important and growing global issue, as extreme wildfire events are expected to increase in frequency and intensity throughout this century due to climate change. Research into individual protective health decision-making can elucidate how wildfire smoke exposure contributes to adverse health outcomes and aid in public health interventions to mitigate risks. In this study we investigate the role of psychological factors (threat and efficacy perceptions) and social processes (social norms and social support) in shaping protective behavior in response to wildfire smoke. Through semi-structured interviews of forty-five individuals in Northern California, we explore perceptions of threat and efficacy, social processes, and protective behaviors in response to wildfire smoke events between 2018 and 2020. We found that for many participants sensory experiences and engagement with wildfire smoke information were instrumental in forming perceptions of threat and efficacy. Three themes related to social processes emerged: interpreting information together, protecting vulnerable others, and questioning protective actions. Through these themes we show how social norms and social support interact in complex, non-linear ways to influence threat and efficacy perceptions, and directly affect protective health behavior. Finally, we propose a conceptual framework of wildfire smoke protective behavior. This study contributes to a growing body of knowledge within the disaster risk and protective health literatures related to wildfire smoke response. Our findings demonstrate how the study of psychological factors and social processes during natural hazards, like wildfire smoke events, is essential to understanding individual protective health decision-making pathways and ultimately, to developing a more comprehensive view of how individual actions affect exposure.
Western North American fires have been increasing in magnitude and severity over the last few decades. The complex coupling of fires with the atmospheric energy budget and meteorology creates short-term feedbacks on regional weather altering the amount of pollution to which Americans are exposed. Using a combination of model simulations and observations, this study shows that the severe fires in the summer of 2017 increased atmospheric aerosol concentrations leading to a cooling of the air at the surface, reductions in sensible heat fluxes, and a lowering of the planetary boundary layer height over land. This combination of lower-boundary layer height and increased aerosol pollution from the fires reduces air quality. We estimate that from start of August to end of October 2017, ∼400 premature deaths occurred within the western US as a result of short-term exposure to elevated PM2.5 from fire smoke. As North America confronts a warming climate with more fires the short-term climate and pollution impacts of increased fire activity should be assessed within policy aimed to minimize impacts of climate change on society.
Background and purpose: We describe a novel, interprofessional, experiential training involving pharmacy students in response to a health emergency in rural Montana (MT). Educational activity and setting: Fourth-year pharmacy students on clinical rotations were recruited to participate in screening events assessing effects of wildfire smoke in Seeley Lake, MT. Students were required to fulfill at least two hours of supplementary training in addition to education on human research guidelines. Students assisted with patient surveys (demographics, health, and respiratory), physiological testing with biomedical researchers, blood pressure and medication counseling, and spirometry specialists. Findings: At least 20 pharmacy students have participated in this project in addition to nursing (n = 8), public health (n = 1), and social work (n = 1) students. In initial and subsequent screenings, students worked alongside a team of biomedical researchers and faculty from the University of Montana. An initial cohort of 95 patients was recruited. Summary: This unique experiential training opportunity has affordedpharmacy students access to rural community patient interaction and exposure to and performance of a variety of tests in response to an environmental health emergency. Furthermore, it enabled health professionals and researchers to assess individual and overall community health following an extreme wildfire smoke event, providing the groundwork for utilization of pharmacy students in healthcare responses to public health emergencies. (c) 2021 Elsevier Inc. All rights reserved.
The increased frequency of wildfires in the Western United States has raised public awareness of the impact of wildfire smoke on air quality and human health. Exposure to wildfire smoke has been linked to an increased risk of cancer and cardiorespiratory morbidity. Evidence-driven interventions can alleviate the adverse health impact of wildfire smoke. During wildfires, public health guidance is based on regional air quality data with limited spatiotemporal resolution. Recently, low-cost air quality sensors have been used in air quality studies, given their ability to capture high-resolution spatiotemporal data. We demonstrate the use of a network of low-cost particulate matter (PM) sensors to gather indoor and outdoor PM2.5 data from seven locations in the urban Seattle area, along with a personal exposure monitor worn by a resident living in one of these locations during the 2020 Washington wildfire event. The data were used to determine PM concentration indoor/outdoor (I/O) ratios, PM reduction, and personal exposure levels. The result shows that locations equipped with high-efficiency particulate air (HEPA) filters and HVAC filtration systems had significantly lower I/O ratios (median I/O = 0.43) than those without air filtration (median I/O = 0.82). The median PM2.5 reduction for the locations with HEPA is 58% compared to 20% for the locations without HEPA. The outdoor PM sensor showed a high correlation to the nearby regional air quality monitoring stations (pre-calibration R-2 = 0.92). The personal monitor showed higher variance in PM measurements as the user moved through different microenvironments and could not be fully characterized by the network of indoor or outdoor monitors. The findings imply that evidence-based interventions can be developed to reduce pollution exposure when combining data from indoor and outdoor sensors. Personal exposure monitoring captured temporal spikes in PM exposure.
Exceptional events occur when air pollution in a specific location exceeds the National Ambient Air Quality Standards (NAAQS) due to an event that cannot be reasonably attributed to human activities, such as a wildland fire. Ground-level ozone (O-3) and particulate matter (PM) are Environmental Protection Agency (EPA) criteria pollutants regulated under the NAAQS. Smoke from wildland fires can increase PM and O-3 concentrations downwind of fire and impact air quality, visibility, and health. Our analysis shows that the frequency of exceptional event reporting for PM with aerodynamic diameters smaller than 2.5 mu m or 10 mu m (PM2.5 and PM10) had increased since 2007 when the air quality standards became more stringent. We also show that wildland fires and windblown dust drive many exceptional events in several EPA regions. We note the importance of growth in the number of exceptional event days due to wildfire smoke in the future due to climate change and point to possible changes to the NAAQS and implementations.
Increased wildland fire activity is producing extreme fine particulate matter (PM2.5) concentrations impacting millions of people every year, especially in the western United States (US). Recommendations for limiting exposure to PM2.5 and associated adverse health outcomes focus on staying inside, closing windows and doors, and increasing filtration; however, relatively little is known about indoor air quality (IAQ) during major smoke events. Indoor and outdoor hourly PM2.5 (µg m–3) measurements from the publicly available PurpleAir sensor (PAS) network were analyzed for 42 sites (26 residential, 6 school, 10 commercial) across the western US during a September 2020 period of heavy wildfire smoke influence. The fraction of ambient PM2.5 that penetrates indoors and remains airborne (Fin), as well as the ratio (I/O) and correlation coefficient (R2) of indoor to outdoor PM2.5 concentrations, were lower in residential compared to commercial and school buildings. Interventions to improve IAQ were highly influential in PM2.5 infiltration in residential case studies, with multiple, continuously run filter units associated with lower Fin, I/O, and R2. A low-cost PM2.5 filtration method consisting of a Minimum Efficiency Rating Value-13 (MERV-13) filter attached to a box fan is evaluated as an alternative for improving IAQ during wildland fire smoke events. The MERV-13 fan filter unit proved highly effective at reducing indoor PM2.5 and particles 0.3–1.0 µm measured by PAS and a particle counter, respectively, when recirculating air in a single room. Low-cost filtration methods can have significant benefit for filtering submicron smoke particles and may reduce exposure to PM2.5 during wildfire smoke events.
Objective(s): This study explored the feasibility, acceptability, preliminary impact, and functionality of two risk reduction mobile application (app) interventions on asthma outcomes as compared to a control arm during wildfire season. Design: Three-arm, 8-week randomized clinical trial. Sample: Sixty-seven young adults with asthma were enrolled. Measurements: The Asthma Control Test, forced expiratory volume in one second (FEV1) and the System Usability Scale were measured at baseline, 4, and 8 weeks. The Research Attitude Scale was administered at 8 weeks. Twenty participants from the two intervention arms completed an optional survey and six were interviewed after completing the study. Intervention: Both intervention arms could access Smoke Sense Urbanova, an app that supports reducing risks from breathing wildfire smoke. The Smoke Sense Urbanova Plus arm also monitored their daily FEV1, received air quality notifications, and accessed preventive tips and a message board. Results: Most participants agreed the app and spirometer were usable and their privacy and confidentiality were maintained. No adverse events were reported. Conclusions: Participant-identified recommendations will support intervention refinement and testing. This research supports asthma self-management tools that public health nurses and community health workers can recommend for at-risk populations.
Wildland fires are diminishing air quality on a seasonal and regional basis, raising concerns about respiratory health risks to the public and occupational groups. This American Thoracic Society (ATS) workshop was convened in 2019 to meet the growing health threat of wildland fire smoke. The workshop brought together a multidisciplinary group of 19 experts, including wildland fire managers, public health officials, epidemiologists, toxicologists, and pediatric and adult pulmonologists. The workshop examined the following four major topics: 1) the science of wildland fire incidence and fire management, 2) the respiratory and cardiovascular health effects of wildland fire smoke exposure, 3) communication strategies to address these health risks, and 4) actions to address wildland fire health impacts. Through formal presentations followed by group discussion, workshop participants identified top priorities for fire management, research, communication, and public policy to address health risks of wildland fires. The workshop concluded that short-term exposure to wildland smoke causes acute respiratory health effects, especially among those with asthma and chronic obstructive pulmonary disease. Research is needed to understand long-term health effects of repeated smoke exposures across fire seasons for children, adults, and highly exposed occupational groups (especially firefighters). Other research priorities include fire data collection and modeling, toxicology of different fire fuel sources, and the efficacy of health protective measures to prevent respiratory effects of smoke exposure. The workshop committee recommends a unified federal response to the growing problem of wildland fires, including investment in fire behavior and smoke air quality modeling, research on the health impacts of smoke, and development of robust clinical and public health communication tools.
Recent dramatic and deadly increases in global wildfire activity have increased attention on the causes of wildfires, their consequences, and how risk from wildfire might be mitigated. Here we bring together data on the changing risk and societal burden of wildfire in the United States. We estimate that nearly 50 million homes are currently in the wildland-urban interface in the United States, a number increasing by 1 million houses every 3 y. To illustrate how changes in wildfire activity might affect air pollution and related health outcomes, and how these linkages might guide future science and policy, we develop a statistical model that relates satellite-based fire and smoke data to information from pollution monitoring stations. Using the model, we estimate that wildfires have accounted for up to 25% of PM (2.5) (particulate matter with diameter <2.5 μm) in recent years across the United States, and up to half in some Western regions, with spatial patterns in ambient smoke exposure that do not follow traditional socioeconomic pollution exposure gradients. We combine the model with stylized scenarios to show that fuel management interventions could have large health benefits and that future health impacts from climate-change-induced wildfire smoke could approach projected overall increases in temperature-related mortality from climate change-but that both estimates remain uncertain. We use model results to highlight important areas for future research and to draw lessons for policy.
Wildland fire smoke contains hazardous levels of fine particulate mat-ter (PM2.5), a pollutant shown to adversely effect health. Estimating fire at-tributable PM2.5 concentrations is key to quantifying the impact on air quality and subsequent health burden. This is a challenging problem since only to-tal PM2.5 is measured at monitoring stations and both fire-attributable PM2.5 and PM2.5 from all other sources are correlated in space and time. We propose a framework for estimating fire-contributed PM2.5 and PM2.5 from all other sources using a novel causal inference framework and bias-adjusted chemical model representations of PM2.5 under counterfactual scenarios. The chemical model representation of PM2.5 for this analysis is simulated using Commu-nity Multiscale Air Quality Modeling System (CMAQ), run with and without fire emissions across the contiguous U.S. for the 2008-2012 wildfire seasons. The CMAQ output is calibrated with observations from monitoring sites for the same spatial domain and time period. We use a Bayesian model that ac-counts for spatial variation to estimate the effect of wildland fires on PM2.5 and state assumptions under which the estimate has a valid causal interpreta-tion. Our results include estimates of the contributions of wildfire smoke to PM2.5 for the contiguous U.S. Additionally, we compute the health burden associated with the PM2.5 attributable to wildfire smoke.
Smoke impacts from large wildfires are mounting, and the projection is for more such events in the future as the one experienced October 2017 in Northern California, and subsequently in 2018 and 2020. Further, the evidence is growing about the health impacts from these events which are also difficult to simulate. Therefore, we simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling with WRF-CMAQ, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses. To demonstrate these analyses, we estimated the health impacts from smoke impacts during wildfires in October 8-20, 2017, in Northern California, when over 7 million people were exposed to Unhealthy to Very Unhealthy air quality conditions. We investigated using the 5-min available GOES-16 fire detection data to simulate timing of fire activity to allocate emissions hourly for the WRF-CMAQ system. Interestingly, this approach did not necessarily improve overall results, however it was key to simulating the initial 12-hr explosive fire activity and smoke impacts. To improve these results, we applied one data fusion and three machine learning algorithms. We also had a unique opportunity to evaluate results with temporary monitors deployed specifically for wildfires, and performance was markedly different. For example, at the permanent monitoring locations, the WRF-CMAQ simulations had a Pearson correlation of 0.65, and the data fusion approach improved this (Pearson correlation = 0.95), while at the temporary monitor locations across all cases, the best Pearson correlation was 0.5. Overall, WRF-CMAQ simulations were biased high and the geostatistical methods were biased low. Finally, we applied the optimized PM2.5 exposure estimate in an exposure-response function. Estimated mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% CI: 0, 196) with 47% attributable to wildland fire smoke.Implications: Large wildfires in the United States and in particular California are becoming increasingly common. Associated with these large wildfires are air quality and health impact to millions of people from the smoke. We simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses from the October 2017 Northern California wildfires. Temporary monitors deployed for the wildfires provided an important model evaluation dataset. Total estimated regional mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% confidence interval: 0, 196) with 47% of these deaths attributable to the wildland fire smoke. This illustrates the profound effect that even a 12-day exposure to wildland fire smoke can have on human health.
Wildfire smoke is a growing public health concern in the United States. Numerous studies have documented associations between ambient smoke exposure and severe patient outcomes for single-fire seasons or limited geographic regions. However, there are few national-scale health studies of wildfire smoke in the United States, few studies investigating Intensive Care Unit (ICU) admissions as an outcome, and few specifically framed around hospital operations. This study retrospectively examined the associations between ambient wildfire-related PM2.5 at a hospital ZIP code with total hospital ICU admissions using a national-scale hospitalization data set. Wildfire smoke was characterized using a combination of kriged PM2.5 monitor observations and satellite-derived plume polygons from National Oceanic and Atmospheric Administration’s Hazard Mapping System. ICU admissions data were acquired from Premier, Inc. and encompass 15%-20% of all U.S. ICU admissions during the study period. Associations were estimated using a distributed-lag conditional Poisson model under a time-stratified case-crossover design. We found that a 10 mu g/m(3) increase in daily wildfire PM2.5 was associated with a 2.7% (95% CI: 1.3, 4.1; p = 0.00018) increase in ICU admissions 5 days later. Under stratification, positive associations were found among patients aged 0-20 and 60+, patients living in the Midwest Census Region, patients admitted in the years 2013-2015, and non-Black patients, though other results were mixed. Following a simulated severe 7-day 120 mu g/m(3) smoke event, our results predict ICU bed utilization peaking at 131% (95% CI: 43, 239; p < 10(-5)) over baseline. Our work suggests that hospitals may need to preposition vital critical care resources when severe smoke events are forecast. Plain Language Summary Wildfire smoke negatively affects people's health. Heavy smoke has been linked to higher rates of hospital admissions, emergency room, admissions, and death. However, we do not know the impact of smoke on Intensive Care Unit (ICU) admissions or on limited hospital resources like ICU beds. To fill this knowledge gap, we linked hospital ICU admissions to smoke levels near those hospitals. We also predicted how many ICU admissions would occur during a simulated severe week-long smoke event and how many ICU beds would be needed to care for the patients. We found that the link between smoke and ICU admissions was relatively modest, but a severe smoke event could more than double the number of ICU beds needed.
Wildfires are natural ecological processes that generate high levels of fine particulate matter (PM2.5) that are dispersed into the atmosphere. PM2.5 could be a potential health problem due to its size. Having adequate numerical models to predict the spatial and temporal distribution of PM2.5 helps to mitigate the impact on human health. The compositional data approach is widely used in the environmental sciences and concentration analyses (parts of a whole). This numerical approach in the modelling process avoids one common statistical problem: the spurious correlation. PM2.5 is a part of the atmospheric composition. In this way, this study developed an hourly spatio-temporal PM2.5 model based on the dynamic linear modelling framework (DLM) with a compositional approach. The results of the model are extended using a Gaussian-Mattern field. The modelling of PM2.5 using a compositional approach presented adequate quality model indices (NSE = 0.82, RMSE = 0.23, and a Pearson correlation coefficient of 0.91); however, the correlation range showed a slightly lower value than the conventional/traditional approach. The proposed method could be used in spatial prediction in places without monitoring stations.
We developed daily maps of surface fine particulate matter (PM(2.5)) for the western United States. We used geographically weighted regression fit to air quality station observations with Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) data, and meteorological data to produce daily 1-kilometer resolution PM(2.5) concentration estimates from 2003-2020. To account for impacts of stagnant air and inversions, we included estimates of inversion strength based on meteorological conditions, and inversion potential based on human activities and local topography. Model accuracy based on cross-validation was R(2) = 0.66. AOD data improve the model in summer and fall during periods of high wildfire activity while the stagnation terms capture the spatial and temporal dynamics of PM(2.5) in mountain valleys, particularly during winter. These data can be used to explore exposure and health outcome impacts of PM(2.5) across spatiotemporal domains particularly in the intermountain western United States where measurements from monitoring station data are sparse. Furthermore, these data may facilitate analyses of inversion impacts and local topography on exposure and health outcome studies.
We estimated cardiopulmonary morbidity and mortality associated with wildfire smoke (WFS) fine particulate matter (PM2.5) in the Front Range of Colorado from 2010 to 2015. To estimate WFS PM2.5, we developed a daily kriged PM2.5 surface at a 15 x 15 km resolution based on the Environmental Protection Agency Air Quality System monitors for the western United States; we subtracted out local seasonal-average PM2.5 of nonsmoky days, identified using satellite-based smoke plume estimates, from the local daily estimated PM2.5 if smoke was identified by National Oceanic and Atmospheric Administration’s Hazard Mapping System. We implemented time-stratified case-crossover analyses to estimate the effect of a 10 mu g/m(3) increase in WFS PM2.5 with cardiopulmonary hospitalizations and deaths using single and distributed lag models for lags 0-5 and distinct annual impacts based on local and long-range smoke during 2012, and long-range transport of smoke in 2015. A 10 mu g/m(3) increase in WFS was associated with all respiratory, asthma, and chronic obstructive pulmonary disease hospitalizations for lag day 3 and hospitalizations for ischemic heart disease at lag days 2 and 3. Cardiac arrest deaths were associated with WFS PM2.5 at lag day 0. For 2012 local wildfires, asthma hospitalizations had an inverse association with WFS PM2.5 (OR: 0.716, 95% CI: 0.517-0.993), but a positive association with WFS PM2.5 during the 2015 long-range transport event (OR: 1.455, 95% CI: 1.093-1.939). Cardiovascular mortality was associated with the 2012 long-range transport event (OR: 1.478, 95% CI: 1.124-1.944).
Wildfire activity in the western United States (US) has been increasing, a trend that has been correlated with changing patterns of temperature and precipitation associated with climate change. Health effects associated with exposure to wildfire smoke and fine particulate matter (PM(2.5)) include short- and long-term premature mortality, hospital admissions, emergency department visits, and other respiratory and cardiovascular incidents. We estimate PM(2.5) exposure and health impacts for the entire continental US from current and future western US wildfire activity projected for a range of future climate scenarios through the 21st century. We use a simulation approach to estimate wildfire activity, area burned, fine particulate emissions, air quality concentrations, health effects, and economic valuation of health effects, using established and novel methodologies. We find that climatic factors increase wildfire pollutant emissions by an average of 0.40% per year over the 2006-2100 period under Representative Concentration Pathway (RCP) 4.5 (lower emissions scenarios) and 0.71% per year for RCP8.5. As a consequence, spatially weighted wildfire PM(2.5) concentrations more than double for some climate model projections by the end of the 21st century. PM(2.5) exposure changes, combined with population projections, result in a wildfire PM2.5-related premature mortality excess burden in the 2090 RCP8.5 scenario that is roughly 3.5 times larger than in the baseline period. The combined effect of increased wildfire activity, population growth, and increase in the valuation of avoided risk of premature mortality over time results in a large increase in total economic impact of wildfire-related PM(2.5) mortality and morbidity in the continental US, from roughly $7 billion per year in the baseline period to roughly $36 billion per year in 2090 for RCP4.5, and $43 billion per year in RCP8.5. The climate effect alone accounts for a roughly 60% increase in wildfire PM2.5-related premature mortality in the RCP8.5 scenario, relative to baseline conditions.
BACKGROUND: In August 2017, Hurricane Harvey caused unprecedented flooding across the greater Houston area. Given the potential for widespread flood-related exposures, including mold and sewage, and the emotional and mental toll caused by the flooding, we sought to evaluate the short- and long-term impact of flood-related exposures on the health of Houstonians. Our objectives were to assess the association of flood-related exposures with allergic symptoms and stress among Houston-area residents at two time points: within approximately 30 days (T1) and 12 months (T2) after Hurricane Harvey’s landfall. METHODS: The Houston Hurricane Harvey Health (Houston-3H) Study enrolled a total of 347 unique participants from four sites across Harris County at two times: within approximately 1-month of Harvey (T1, n = 206) and approximately 12-months after Harvey (T2, n = 266), including 125 individuals who participated at both time points. Using a self-administered questionnaire, participants reported details on demographics, flood-related exposures, and health outcomes, including allergic symptoms and stress. RESULTS: The majority of participants reported hurricane-related flooding in their homes at T1 (79.1%) and T2 (87.2%) and experienced at least one allergic symptom after the hurricane (79.4% at T1 and 68.4% at T2). In general, flood-exposed individuals were at increased risk of upper respiratory tract allergic symptoms, reported at both the T1 and T2 time points, with exposures to dirty water and mold associated with increased risk of multiple allergic symptoms. The mean stress score of study participants at T1 was 8.0 ± 2.1 and at T2, 5.1 ± 3.2, on a 0-10 scale. Participants who experienced specific flood-related exposures reported higher stress scores when compared with their counterparts, especially 1 year after Harvey. Also, a supplementary paired-samples analysis showed that reports of wheezing, shortness of breath, and skin rash did not change between T1 and T2, though other conditions were less commonly reported at T2. CONCLUSION: These initial Houston-3H findings demonstrate that flooding experiences that occurred as a consequence of Hurricane Harvey had lasting impacts on the health of Houstonians up to 1 year after the hurricane.
Extensive flooding caused by Hurricane María in Puerto Rico (PR) created favorable conditions for indoor growth of filamentous fungi. These conditions represent a public health concern as contamination by environmental fungi is associated with a higher prevalence of inflammatory respiratory conditions. This work compares culturable fungal spore communities present in homes that sustained water damage after Hurricane María to those present in dry, non-flooded homes. We collected air samples from 50 houses in a neighborhood in San Juan, PR, 12 and 22 months after Hurricane María. Self-reported data was used to classify the homes as flooded, water-damage or dry non-flooded. Fungi abundances, composition and diversity were analyzed by culturing on two media. Our results showed no significant differences in indoor fungal concentrations (CFU/m(3)) one year after the Hurricane in both culture media studied (MEA and G25N). During the second sampling period fungal levels were 2.7 times higher in previously flooded homes (Median = 758) when compared to dry homes (Median = 283), (p-value < 0.005). Fungal profiles showed enrichment of Aspergillus species inside flooded homes compared to outdoor samples during the first sampling period (FDR-adjusted p-value = 0.05). In contrast, 22 months after the storm, indoor fungal composition consisted primarily of non-sporulated fungi, most likely basidiospores, which are characteristic of the outdoor air in PR. Together, this data highlights that homes that suffered water damage not only have higher indoor proliferation of filamentous fungi, but their indoor fungal populations change over time following the Hurricane. Ultimately, after nearly two years, indoor and outdoor fungal communities converged in this sample of naturally ventilated homes.
BACKGROUND: Rising temperatures due to climate change are expected to impact human adaptive response, including changes to home cooling and ventilation patterns. These changes may affect air pollution exposures via alteration in residential air exchange rates, affecting indoor infiltration of outdoor particles. We conducted a field study examining associations between particle infiltration and temperature to inform future studies of air pollution health effects. METHODS: We measured indoor fine particulate matter (PM(2.5)) in Atlanta in 60 homes (810 sampling-days). Indoor-outdoor sulfur ratios were used to estimate particle infiltration, using central site outdoor sulfur concentrations. Linear and mixed-effects models were used to examine particle infiltration ratio-temperature relationships, based on which we incorporated projected meteorological values (Representative Concentration Pathways intermediate scenario RCP 4.5) to estimate particle infiltration ratios in 20-year future (2046-2065) and past (1981-2000) scenarios. RESULTS: The mean particle infiltration ratio in Atlanta was 0.70 ± 0.30, with a 0.21 lower ratio in summer compared to transition seasons (spring, fall). Particle infiltration ratios were 0.19 lower in houses using heating, ventilation, and air conditioning (HVAC) systems compared to those not using HVAC. We observed significant associations between particle infiltration ratios and both linear and quadratic models of ambient temperature for homes using natural ventilation and those using HVAC. Future temperature was projected to increase by 2.1 °C in Atlanta, which corresponds to an increase of 0.023 (3.9%) in particle infiltration ratios during cooler months and a decrease of 0.037 (6.2%) during warmer months. DISCUSSION: We estimated notable changes in particle infiltration ratio in Atlanta for different 20-year periods, with differential seasonal patterns. Moreover, when stratified by HVAC usage, increases in future ambient temperature due to climate change were projected to enhance seasonal differences in PM(2.5) infiltration in Atlanta. These analyses can help minimize exposure misclassification in epidemiologic studies of PM(2.5), and provide a better understanding of the potential influence of climate change on PM(2.5) health effects.
Air pollution, climate change, and other environmental factors contribute to increasing asthma in many cities, including Washington, DC. This work provides a case study of how community input, neighborhood-level health surveys, and air quality monitoring can inform the understanding of asthma and air pollution. A partnership between residents, concerned citizens, scientists, and educators has been working for environmental health in a DC neighborhood located on a major roadway, next to concrete batch plants and close to several construction projects. A 2016 Community Health and Safety Study by the DC Department of Health, Office of Health Equity, recognized this particular neighborhood as more vulnerable to health impacts from recent construction in the area, compared with the surrounding areas, due to lower average income and higher percentage of seniors and children. This work presents neighborhood health surveys and air quality monitoring data at a more granular, local level than available from DC government agencies. The health surveys documented residents’ experiences around air pollution, asthma, and other health concerns. A key finding was evidence that asthma might be undercounted in this neighborhood; among residents who did not indicate a diagnosis of asthma, many discussed having symptoms that could reflect asthma. Air quality monitoring (particulate matter [PM]) did not indicate that federal air quality standards have been violated. Real-time PM data, however, illustrated how current PM standards, such as 1- and 24-hour averages, may fail to capture shorter duration high PM events that are consistent with resident concerns.
BACKGROUND: While ozone levels in the USA have decreased since the 1980s, the Denver Metro North Front Range (DMNFR) region remains in nonattainment of the National Ambient Air Quality Standard (NAAQS). OBJECTIVE: To estimate the warm season ozone climate penalty to characterize its impact on Colorado Front Range NAAQS attainment and health equity. METHODS: May to October ozone concentrations were estimated using spatio-temporal land-use regression models accounting for climate and weather patterns. The ozone climate penalty was defined as the difference between the 2010s concentrations and concentrations predicted using daily 2010s weather adjusted to match the 1950s climate, holding constant other factors affecting ozone formation. RESULTS: The ozone climate penalty was 0.5-1.0 ppb for 8-h max ozone concentrations. The highest penalty was around major urban centers and later in the summer. The penalty was positively associated with census tract-level percentage of Hispanic/Latino residents, children living within 100-200% of the federal poverty level, and residents with asthma, diabetes, fair or poor health status, or lacking health insurance. SIGNIFICANCE: The penalty increased the DMNFR ozone NAAQS design values, delaying extrapolated future attainment of the 2008 and 2015 ozone standards by approximately 2 years each, to 2025 and 2035, respectively.
BACKGROUND: Air pollution is linked to preterm birth (PTB), but existing studies are primarily focused on chronic exposures, conducted in areas with moderate pollution, and/or subject to confounding. OBJECTIVES: We investigated short-term associations between two pollutants [particulate matter <2.5 microns (PM(2.5) ) and ozone] and PTB, and estimated excess PTB cases potentially attributed to these pollutants. METHODS: This time-stratified case-crossover study includes 196,970 singleton pregnancies affected by PTB and early term birth from the San Joaquin Valley (SJV), California, USA (2007-2015). Daily ozone and PM(2.5) concentrations were estimated by the SJV Air Pollution Control District and geospatially linked to maternal zip code. We used conditional logistic regression models to estimate the odds ratio (OR) and 95% confidence intervals (CI) for the associations between an interquartile range (IQR) increase in pollutants and very preterm (VPTB, 20-34 weeks), moderate preterm (MPTB, 34-36 weeks) and early term births (ETB, 37-38 weeks). We adjusted all models for co-pollutants and meteorological factors. RESULTS: During warm seasons (May-October), an IQR increase in ozone was associated with 9-11% increased odds of VPTB from lag 0 (OR(lag0) 1.09, 95% CI 1.04,1.16) to lag 7 (OR(lag7) 1.11, 95% CI 1.04,1.16). Findings were consistent for MPTB and ETB. Ozone was potentially responsible for an excess of 3-6 VPTBs, 7-9 PTBs and 24-42 ETBs per 1,000 singleton deliveries. During cold seasons (November-April), increased PM(2.5) exposure was associated with 5-6% increased odds of VPTB beginning at lag 3 (OR(lag3) 1.06, 95% CI 1.02,1.11). PM(2.5) was associated with an excess of 1-3 VPTBs, 0-3 MPTBs and 6-18 ETBs per 1,000 singleton deliveries. CONCLUSIONS: PM(2.5) and ozone are associated with increased risk of VPTB, MPTB and ETB within one week of exposure and are potential contributors to the increasing PTB trend. More research is needed to further understand the role of air pollution on PTB risk.
Wildfires and meteorological conditions influence the co-occurrence of multiple harmful air pollutants including fine particulate matter (PM2.5) and ground-level ozone. We examine the spatiotemporal characteristics of PM2.5/ozone co-occurrences and associated population exposure in the western United States (US). The frequency, spatial extent, and temporal persistence of extreme PM2.5/ozone co-occurrences have increased significantly between 2001 and 2020, increasing annual population exposure to multiple harmful air pollutants by similar to 25 million person-days/year. Using a clustering methodology to characterize daily weather patterns, we identify significant increases in atmospheric ridging patterns conducive to widespread PM2.5/ozone co-occurrences and population exposure. We further link the spatial extent of co-occurrence to the extent of extreme heat and wildfires. Our results suggest an increasing potential for co-occurring air pollution episodes in the western US with continued climate change.
BACKGROUND: Long-term exposures to air pollution has been reported to be associated with inflammation and oxidative stress. However, the underlying metabolic mechanisms remain poorly understood. OBJECTIVES: We aimed to determine the changes in the blood metabolome and thus the metabolic pathways associated with long-term exposure to outdoor air pollution and ambient temperature. METHODS: We quantified metabolites using mass-spectrometry based global untargeted metabolomic profiling of plasma samples among men from the Normative Aging Study (NAS). We estimated the association between long-term exposure to PM(2.5), NO(2), O(3), and temperature (annual average of central site monitors) with metabolites and their associated metabolic pathways. We used multivariable linear mixed-effect regression models (LMEM) while simultaneously adjusting for the four exposures and potential confounding and correcting for multiple testing. As a reduction method for the intercorrelated metabolites (outcome), we further used an independent component analysis (ICA) and conducted LMEM with the same exposures. RESULTS: Men (N = 456) provided 648 blood samples between 2000 and 2016 in which 1158 metabolites were quantified. On average, men were 75.0 years and had an average body mass index of 27.7 kg/m(2). Almost all men (97%) were not current smokers. The adjusted analysis showed statistically significant associations with several metabolites (58 metabolites with PM(2.5), 15 metabolites with NO(2), and 6 metabolites with temperature) while no metabolites were associated with O(3). One out of five ICA factors (factor 2) was significantly associated with PM(2.5). We identified eight perturbed metabolic pathways with long-term exposure to PM(2.5) and temperature: glycerophospholipid, sphingolipid, glutathione, beta-alanine, propanoate, and purine metabolism, biosynthesis of unsaturated fatty acids, and taurine and hypotaurine metabolism. These pathways are related to inflammation, oxidative stress, immunity, and nucleic acid damage and repair. CONCLUSIONS: Using a global untargeted metabolomic approach, we identified several significant metabolites and metabolic pathways associated with long-term exposure to PM(2.5), NO(2) and temperature. This study is the largest metabolomics study of long-term air pollution, to date, the first study to report a metabolomic signature of long-term temperature exposure, and the first to use ICA in the analysis of both.
Exposure to fine particulate matter (PM(2.5)) is associated with asthma development as well as asthma exacerbation in children. PM(2.5) can be directly emitted or can form in the atmosphere from pollutant precursors. PM(2.5) emitted and formed in the atmosphere is influenced by meteorology; future changes in climate may alter the concentration and distribution of PM(2.5). Our aim is to estimate the future burden of climate change and PM(2.5) on new and exacerbated cases of childhood asthma. Projected concentrations of PM(2.5) are based on the Geophysical Fluid Dynamics Laboratory Coupled Model version 3 climate model, the Representative Concentration Pathway 8.5 greenhouse gas scenario, and two air pollution emissions datasets: a 2011 emissions dataset and a 2040 emissions dataset that reflects substantial reductions in emissions of PM(2.5) as compared to the 2011 inventory. We estimate additional PM(2.5)-attributable asthma as well as PM(2.5)-attributable albuterol inhaler use for four future years (2030, 2050, 2075, and 2095) relative to the year 2000. Exacerbations, regardless of the trigger, are counted as attributable to PM(2.5) if the incident disease is attributable to PM(2.5). We project 38 thousand (95% CI 36, 39 thousand) additional PM(2.5)-attributable incident childhood asthma cases and 29 million (95% CI 27, 31 million) additional PM(2.5)-attributable albuterol inhaler uses per year in 2030, increasing to 200 thousand (95% CI 190, 210 thousand) additional incident cases and 160 million (95% CI 150, 160 million) inhaler uses per year by 2095 relative to 2000 under the 2011 emissions dataset. These additional PM(2.5)-attributable incident asthma cases and albuterol inhaler use would cost billions of additional U.S. dollars per year by the late century. These outcomes could be mitigated by reducing air pollution emissions.
Particulate matter 2.5 (PM2.5) exposure induces oxidative stress associated with many negative health outcomes such as respiratory disorders, cardiovascular disease and neurodegenerative disease. Research shows that diet and exercise can improve antioxidant defense against oxidative stress. This study is the first to use an Arctic animal model to investigate the cumulative effects of two lifestyle interventions on the antioxidant response before, during, and after ambient PM 2.5 exposure from wildfire: antioxidant supplementation (Arthrospira platensis) and exercise. In a two-factorial, longitudinal design, this study divided sled dogs (n = 48) into four groups (exercise and supplemented, exercise, supplemented, and control) to (1) test the effects of a 30-day exercise and antioxidant supplementation protocol on antioxidant response; and (2) measure the antioxidant response of all groups during and after a natural wildfire event. Commercial assays for total antioxidant power (TAP) and the enzymatic antioxidant superoxide dismutase (SOD) were used as markers for antioxidant status and response. During the forest fire, SOD was increased 5- to 10-fold over pre/post-exposure levels in all groups suggesting an endogenous upregulation of defense systems in response to the acute environmental stress. TAP was lower in all groups at peak PM2.5 exposure compared to 48 h after peak exposure in all groups except the exercise alone group which may indicate that exercise offers improved endogenous defense.
Decarbonizing power systems is a critical component of climate change mitigation, which can have public health cobenefits by reducing air pollution. Many studies have examined strategies to decarbonize power grids and quantified their health cobenefits. However, few of them focus on near-term cobenefits at community levels, while comparing various decarbonization pathways. Here, we use a coupled power system and air quality modeling framework to quantify the costs and benefits of decarbonizing the Texas power grid through a carbon tax; replacing coal with natural gas, solar, or wind; and internalizing human health impacts into operations. Our results show that all decarbonization pathways can result in major reductions in CO(2) emissions and public health impacts from power sector emissions, leading to large net benefits when considering the costs to implement these strategies. Operational changes with existing infrastructure can serve as a transitional strategy during the process of replacing coal with renewable energy, which offers the largest benefits. However, we also find that Black and lower-income populations receive disproportionately higher air pollution damages and that none of the examined decarbonization strategies mitigate this disparity. These findings suggest that additional interventions are necessary to mitigate environmental inequity while decarbonizing power grids.
Local and state policymakers have become increasingly interested in developing policies that both reduce greenhouse gas (GHG) emissions and improve local air quality, along with public health. Interest in developing transportation-related policies has grown as transportation became the largest contributing sector to GHG emissions in the United States in 2017. Information on current emissions and health impacts, along with trends over time, is helpful to policymakers who are developing strategies to reduce emissions and improve public health, especially in areas with high levels of transportation-related emissions. Here, we provide a comprehensive assessment of the public health and climate social costs of on-road emissions by linking emissions data generated by the U.S. Environmental Protection Agency to reduced complexity models that provide impacts per ton emitted for pollutants which contribute to ambient fine particulate matter, and the social costs of GHG emissions from on-road transportation. For 2017, social costs totaled $184 billion (min: $78 billion; max: $280 billion) for all on-road emissions from the eight health and climate pollutants that we assessed in the continental U.S. (in $2017 USD). Within this total social cost estimate, health pollutants constituted $93 billion of the social costs (min: $52 billion; max: $146 billion), and climate pollutants constituted $91 billion (min: $26 billion; max: $134 billion). The majority of these social costs came from CO2 followed by NO (x) emissions from privately owned individual vehicles in urban counties (CO2 contributed $51 billion and NO (x) contributed $16 billion in social costs from individual vehicles in urban counties). However, it is important to note that not all the attention should be placed solely on individual vehicles. Although the climate social costs of individual vehicle emissions are higher than those from commercial vehicles in urban counties (by two to eight times depending on the climate pollutant), the health social costs of individual vehicle emissions are roughly equal to those from commercial vehicles in urban counties. Regardless of each pollutant’s contributions to the social costs, the highest social benefits from reducing 1 ton of CO2 and its co-pollutants would occur in urban counties, given their high population density.
Pollution from wildfires constitutes a growing source of poor air quality globally. To protect health, governments largely rely on citizens to limit their own wildfire smoke exposures, but the effectiveness of this strategy is hard to observe. Using data from private pollution sensors, cell phones, social media posts and internet search activity, we find that during large wildfire smoke events, individuals in wealthy locations increasingly search for information about air quality and health protection, stay at home more and are unhappier. Residents of lower-income neighbourhoods exhibit similar patterns in searches for air quality information but not for health protection, spend less time at home and have more muted sentiment responses. During smoke events, indoor particulate matter (PM(2.5)) concentrations often remain 3-4× above health-based guidelines and vary by 20× between neighbouring households. Our results suggest that policy reliance on self-protection to mitigate smoke health risks will have modest and unequal benefits.
The increasing number and severity of wildfires is negatively impacting air quality for millions of California residents each year. Community exposure to PM(2.5) in two main population centers (San Francisco Bay area and Los Angeles County area) was assessed using the low-cost PurpleAir sensor network for the record-setting 2020 California wildfire season. Estimated PM(2.5) concentrations in each study area were compared to census tract-level environmental justice vulnerability indicators, including environmental, health, and demographic data. Higher PM(2.5) concentrations were positively correlated with poverty, cardiovascular emergency department visits, and housing inequities. Sensors within 30 km of actively burning wildfires showed statistically significant increases in indoor (~800 %) and outdoor (~540 %) PM(2.5) during the fires. Results indicate that wildfire emissions may exacerbate existing health disparities as well as the burden of pollution in disadvantaged communities, suggesting a need to improve monitoring and adaptive capacity among vulnerable populations.
As wildfires increase in prevalence and intensity across California and globally, it is anticipated that more children will be exposed to wildfire smoke, and thus face associated adverse health outcomes. Here, we provide a concise summary of the respiratory effects of California’s wildfires on pediatric healthcare utilization, examine global examples of wildfire smoke exposure within the pediatric population and associated physiological effects, and assess the efficacy of metrics used to measure and communicate air quality during wildfires within the United States and elsewhere.
Climate change and human activities have drastically altered the natural wildfire balance in the Western US and increased population health risks due to exposure to pollutants from fire smoke. Using dynamically downscaled climate model projections, we estimated additional asthma emergency room visits and hospitalizations due to exposure to smoke fine particulate matter (PM2.5) in the Western US in the 2050s. Isolating the amount of PM2.5 from wildfire smoke is both difficult to estimate and, thus, utilized by relatively few studies. In this study, we use a sophisticated modeling approach to estimate future increase in wildfire smoke exposure over the reference period (2003-2010) and subsequent health care burden due to asthma exacerbation. Average increases in smoke PM2.5 during future fire season ranged from 0.05 to 9.5 mu g m(-3) with the highest increases seen in Idaho, Montana, and Oregon. Using the Integrated Climate and Land-Use Scenarios (ICLUS) A2 scenario, we estimated the smoke-related asthma events could increase at a rate of 15.1 visits per 10 000 persons in the Western US, with the highest rates of increased asthma (25.7-41.9 per 10 000) in Idaho, Montana, Oregon, and Washington. Finally, we estimated healthcare costs of smoke-induced asthma exacerbation to be over $1.5 billion during a single future fire season. Here we show the potential future health impact of climate-induced wildfire activity, which may serve as a key tool in future climate change mitigation and adaptation planning.
Biomass burning emits a wide range of carbona-ceous particles into the atmosphere and has negative impacts on human health and the Earth’s radiative balance. Nonvolatile spherical organic aerosol particles, commonly known as tar balls, represent one of the most abundant particles in aged biomass burning smoke. However, the detailed molecular level composition of ambient tar balls is largely unknown but critical to assess their environmental impacts. Ambient aerosol samples collected during a wildfire event, which were similar to 90% tar balls by number fraction, were analyzed using ultrahigh-resolution Orbitrap Elite mass spectrometry with four complementary ionization modes. Our results show the molecular composition of tar balls to be complex, composed of over 10,000 molecular formulas. Model estimated saturation mass concentrations and relative humidity-dependent glass-transition temperatures were consistent with low volatility and solid morphology as expected for tar balls. Room-temperature evaporation kinetics showed that these particles retained similar to 90% of their volume after 24 h of evaporation. The molecular complexity detected here signifies a continuum of carbonaceous species, ranging from C-3 to C-45 with continuous ranges of oxygenation and hydrogen saturation for each Cn. Approximately 24% of molecular formulas were estimated to be highly aromatic, which could indicate chemical compounds with negative health effects and which may contribute to visible light absorption. The carbon continuum observed here has significant implications for the molecular characterization of atmospheric organic matter. The level of complexity detected here should not be ignored in future studies, and we demonstrate that multiple analytical methods may be required to suitably interpret this complexity on a molecular level.
Heavy-duty trucks and buses continue to contribute significantly to air pollution at the local, regional, and national level, often disproportionally affecting communities of color and low-income populations.
To ensure the progress needed on cleaning trucks and buses and to harness improvements in vehicle technologies, EPA will issue two major regulations over the next three years—the “Clean Trucks Plan” that will result in decreasing emissions from new heavy-duty vehicles, including long-haul tractors, buses, commercial delivery trucks, and many other types of trucks. These new rules will be major steps towards improving air quality and addressing the climate crisis.
BACKGROUND: Short-term exposure to ambient nitrogen dioxide (NO(2)) is associated with adverse respiratory and cardiovascular outcomes. Supplementation of omega-3 polyunsaturated fatty acids (PUFA) has shown protection against exposure to fine particulate matter. This study aims to investigate whether habitual omega-3 PUFA intake differentially modify the associations between respiratory and cardiovascular responses and short-term exposure to ambient NO(2). METHODS: Sixty-two healthy participants were enrolled into low or high omega-3 groups based on their habitual omega-3 PUFA intake. Each participant was repeatedly assessed for lung function, blood lipids, markers of coagulation and fibrinolysis, vascular function, and heart rate variability (HRV) in up to five sessions, each separated by at least 7 days. This study was carried out in the Research Triangle area of North Carolina, USA between October 2016 and September 2019. Daily ambient NO(2) concentrations were obtained from an area air quality monitoring station on the day of outcome assessment (Lag0), 4 days prior (Lag1-4), as well as 5-day moving average (5dMA). The associations between short-term exposure to NO(2) and the measured indices were evaluated using linear mixed-effects models stratified by omega-3 levels and adjusted by covariates including relative humidity and temperature. RESULTS: The average concentration of ambient NO(2) during the study periods was 5.3??3.8 ppb which was below the National Ambient Air Quality Standards (NAAQS). In the high omega-3 group, an interquartile range (IQR) increase in short-term NO(2) concentrations was significantly associated with increased lung function [e.g. 1.2% (95%CI: 0.2%, 2.2%) in FVC at lag1, 2.6% (95%CI: 0.4%, 4.8%) in FEV1 at 5dMA], decreased blood lipids [e.g. -2.6% (95%CI: -4.4%, -0.9%) in total cholesterol at lag2, -3.1% (95%CI: -6.1%, 0.0%) in HDL at 5dMA, and -3.1% (95%CI: -5.5%, -0.7%) in LDL at lag2], improved vascular function [e.g. 8.9% (95%CI: 0.6%, 17.2%) increase in FMD and 43.1% (95%CI: -79.8%, -6.3%) decrease in endothelin-1 at 5dMA], and changed HRV parameters [e.g. -7.2% (95%CI: -13.6%, -0.8%) in HFn and 13.4% (95%CI: 0.2%, 28.3%) in LF/HF ratio at lag3]. In the low omega-3 group, an IQR increase in ambient NO(2) was associated with elevations in coagulation markers (von Willebrand Factor, D-dimer) and a decrease in HRV (very-low frequency); however, null associations were observed between short-term NO(2) exposure and changes in lung function, blood lipids, and vascular function. CONCLUSIONS: The results in this study imply that dietary omega-3 PUFA consumption may offer respiratory and vascular benefits in response to short-term exposure of healthy adults to NO(2) levels below the NAAQS. TRIAL REGISTRATION: ClinicalTrials.gov ( NCT02921048 ).
Carbon monoxide (CO) is a colorless, odorless gas that can cause injury or death if inhaled. CO is a frequent secondary hazard induced by the aftereffects of natural hazards as individuals, families, and communities often seek alternative power sources for heating, cooking, lighting, and cleanup during the emergency and recovery phases of a disaster. These alternative power sources-such as portable generators, petroleum-based heaters, and vehicles-exhaust CO that can ultimately build to toxic levels in enclosed areas. Ever-increasing environmental and societal changes combined with an aging infrastructure are growing the odds of power failures during hazardous weather events, which, in turn, are increasing the likelihood of CO exposure, illness, and death. This study analyzed weather-related CO fatalities from 2000 to 2019 in the United States using death-certificate data, providing one of the longest assessments of this mortality. Results reveal that over 8300 CO fatalities occurred in the United States during the 20-yr study period, with 17% of those deaths affiliated with weather perils. Cool-season perils such as ice storms, snowstorms, and extreme cold were the leading hazards that led to situations causing CO fatalities. States in the Southeast and Northeast had the highest CO fatality rates, with winter having the greatest seasonal mortality. In general, these preventable CO poisoning influxes are related to a deficiency of knowledge on generator safety and the absence of working detectors and alarms in the enclosed locations where poisonings occur. Education and prevention programs that target the most vulnerable populations will help prevent future weather-related CO fatalities. Significance StatementCarbon monoxide exposure is common after weather disasters when individuals, families, and communities seek alternative power sources-such as portable generators, petroleum-based heaters, and vehicles-that exhaust this deadly, colorless, and odorless gas. Initially, we catalog carbon monoxide fatalities associated with weather events in the United States over two decades; thereafter, we illustrate the characteristics and patterns affiliated with these deaths. Results will assist public officials, first responders, and individuals in their decision-making and response before, during, and after weather events so that these deaths may be prevented in the future.
Many studies project that climate change can cause a significant number of excess deaths. Yet, in integrated assessment models (IAMs) that determine the social cost of carbon (SCC) and prescribe optimal climate policy, human mortality impacts are limited and not updated to the latest scientific understanding. This study extends the DICE-2016 IAM to explicitly include temperature-related mortality impacts by estimating a climate-mortality damage function. We introduce a metric, the mortality cost of carbon (MCC), that estimates the number of deaths caused by the emissions of one additional metric ton of CO2. In the baseline emissions scenario, the 2020 MCC is 2.26 × 10(‒4) [low to high estimate -1.71× 10(‒4) to 6.78 × 10(‒4)] excess deaths per metric ton of 2020 emissions. This implies that adding 4,434 metric tons of carbon dioxide in 2020-equivalent to the lifetime emissions of 3.5 average Americans-causes one excess death globally in expectation between 2020-2100. Incorporating mortality costs increases the 2020 SCC from $37 to $258 [-$69 to $545] per metric ton in the baseline emissions scenario. Optimal climate policy changes from gradual emissions reductions starting in 2050 to full decarbonization by 2050 when mortality is considered.
OBJECTIVE: Ongoing environmental changes increasingly require public health nurses to understand how environmental factors impact the health of populations. One approach to researching these impacts is incorporating environmental research methods to determine associations between harmful exposures and health. We use the Salton Sea in Southern California as a demonstration of how environmental exposure can be examined using air parcel trajectory analysis. DESIGN: We demonstrate a methodology for public health nurses to better understand and apply data from the Hybrid Single-Particle Lagrangian Integrated Trajectory meteorological model to estimate the effect of airborne particulate matter from a single source. MEASUREMENTS: We explain a method for tracking air parcel trajectories to populations: selection of meterological data to identify air parcels, geographic identification of population centers, generation of trajectories, classification of trajectory dispersions, adjusting for atmospheric stability, and merging environmental variables with health data. CONCLUSIONS: Climate change-related environmental events are expected to become more commonplace and disproportionately affect those populations impacted by health disparities. Public health nurses can identify communities at risk so that public health nursing researchers can use these techniques in collaboration with environmental science to robustly examine health effects of proximal air pollution sources for communities at risk.
Nitrogen dioxide (NO2) is responsible for aggravating respiratory diseases, particularly asthma. The aim of this study is to investigate the association between NO2 exposure and asthma emergency department (ED) visits during the cold season (November-February) in five populated locations (Sacramento, San Francisco, Fresno, Los Angeles, and San Diego) of California from 2005 to 2015 (1320 Days). Conditional logistic regression models were used to obtain the odds ratio (OR) and 95% confidence interval Cl)( associated with a 5 ppb increase in NO2 concentration for the 19,735 ED visits identified. An increase in NO2 exposure increased the odds of having asthma ED visits for the studied population. The potential effect modification by sex (female and male), race (White, Black, Hispanic, and Asian), and age (2-5, 6-18, 19-40, 41-64, and ?65) was explored. A 5 ppb increase in the concentration of NO2 during lag 0-30 was associated with a 56% increase in the odds of having an asthma ED visit (OR 1.560, Cl: 1.428-1.703). Sex was not found lo be a modifier. Asthma ED visits among all the racesiehnicities (except Asians) were associated with NO2 exposure. Whiles had the highest OR 75% (OR 1.750, CI: 1A17-2.160) at lag 0-30 in response to NO2 exposure. The association between NO2 exposure and asthma ED visits was positive among all age groups except fur 19 to 40 years old; the OR was higher among 2 to 18 year old (al lag 0-30: age group 2-5 (OR – 1.699, CI: 1.399-2.062), and age group 6-18 (OR – 1.568, CII.348-1.825)). For stratification by location, San Diego and Fresno were found to have the highest OR, compared lo the other studied locations. (C) 2020 Elsevier B.V. All rights reserved.
BACKGROUND: Hurricane Harvey made landfall along the Texas Gulf Coast as a Category 4 hurricane on August 25, 2017, producing unprecedented precipitation that devastated coastal areas. Catastrophic flooding in the City of Houston inundated industrial and residential properties resulting in the displacement and transfer of soil, sediment, and debris and heightening existing environmental justice (EJ) concerns. OBJECTIVES: The primary aim of this study was to evaluate the presence, distribution, and potential human health implications of polycyclic aromatic hydrocarbons (PAHs) in a residential neighborhood of Houston, Texas following a major hurricane. METHODS: Concentrations of PAHs in 40 soil samples collected from a residential neighborhood in Houston, Texas were measured. Spatial interpolation was applied to determine the distribution of PAHs. Potential human health risks were evaluated by calculating toxicity equivalency quotients (TEQs) and incremental excess lifetime cancer risk (IELCR). RESULTS: Total priority PAH concentrations varied across samples (range: 9.7 × 10(1) ng/g-1.6 × 10(4) ng/g; mean: 3.0 × 10(3) ng/g ± 3.6 × 10(3) standard deviation). Spatial analysis indicated a variable distribution of PAH constituents and concentrations. The IELCR analysis indicated that nine of the 40 samples were above minimum standards. CONCLUSIONS: Findings from this study highlight the need for fine scale soil testing in residential areas as well as the importance of site-specific risk assessment. COMPETING INTERESTS: The authors declare no competing financial interests.
Unprecedented inland precipitation and catastrophic flooding associated with Hurricane Harvey potentially redistributed contaminants from industrial sites and transportation infrastructure to recreational areas that make up networks of green infrastructure, creeks, and waterways used for flood control throughout the Greater Houston Area. Sediment samples were collected in parks located near the Buffalo Bayou watershed 1 week after Hurricane Harvey made landfall and again 7 weeks later. Total concentrations of the U.S. Environmental Protection Agency’s (EPA’s) 16 priority polycyclic aromatic hydrocarbons (PAHs) were measured in each sample at both time points. Diagnostic ratios were calculated to improve understanding of potential sources of PAHs after flooding. Diagnostic ratios suggest vehicular traffic to be a potential source for PAHs in parks. Although the concentrations of PAHs in all samples were below EPA actionable levels, given that no background values were available for comparison, it is difficult to quantify the impact flooding from Hurricane Harvey had on PAH concentrations in Houston parks. However, given the high frequency of flooding in Houston, and the concentration of industrial facilities and transportation infrastructure adjacent to recreation areas, these data demonstrate that PAHs were still present after unprecedented flooding. This study may also serve as a baseline for future efforts to understand the environmental health impacts of disasters.
Hurricane Harvey was a category four storm that induced catastrophic flooding in the Houston metropolitan area. Following the hurricane there was increased concern regarding chemical exposures due to damage caused by flood waters and emergency excess emissions from industrial facilities. This study utilized personal passive samplers in the form of silicone wristbands in Houston, TX to both assess chemical exposure to endocrine disrupting chemicals (EDCs) immediately after the hurricane and determine participant characteristics associated with higher concentrations of exposure. Participants from the Houston-3H cohort (n = 172) wore a wristband for seven days and completed a questionnaire to determine various flood-related and demographic variables. Bivariate and multivariate analysis indicated that living in an area with a high Area Deprivation Index (ADI) (indicative of low socioeconomic status), identifying as Black/African American or Latino, and living in the Houston neighborhoods of Baytown and East Houston were associated with increased exposure to EDCs. These results provide evidence of racial/ethnic and socioeconomic injustices in exposure to EDCs in the Houston Metropolitan Area. Since the multiple regression models conducted did not fully explain exposure (0.047 < R2 < 0.34), more research is needed on the direct sources of EDCs within this area to create effective exposure mitigation strategies.
Airborne pollen has major respiratory health impacts and anthropogenic climate change may increase pollen concentrations and extend pollen seasons. While greenhouse and field studies indicate that pollen concentrations are correlated with temperature, a formal detection and attribution of the role of anthropogenic climate change in continental pollen seasons is urgently needed. Here, we use long-term pollen data from 60 North American stations from 1990 to 2018, spanning 821 site-years of data, and Earth system model simulations to quantify the role of human-caused climate change in continental patterns in pollen concentrations. We find widespread advances and lengthening of pollen seasons (+20 d) and increases in pollen concentrations (+21%) across North America, which are strongly coupled to observed warming. Human forcing of the climate system contributed ∼50% (interquartile range: 19-84%) of the trend in pollen seasons and ∼8% (4-14%) of the trend in pollen concentrations. Our results reveal that anthropogenic climate change has already exacerbated pollen seasons in the past three decades with attendant deleterious effects on respiratory health.
Pollen and molds are environmental allergens that are affected by climate change. As pollen and molds exhibit geographical variations, we sought to understand the impact of climate change (temperature, carbon dioxide (CO(2)), precipitation, smoke exposure) on common pollen and molds in the San Francisco Bay Area, one of the largest urban areas in the United States. When using time-series regression models between 2002 and 2019, the annual average number of weeks with pollen concentrations higher than zero increased over time. For tree pollens, the average increase in this duration was 0.47 weeks and 0.51 weeks for mold spores. Associations between mold, pollen and meteorological data (e.g., precipitation, temperature, atmospheric CO(2), and area covered by wildfire smoke) were analyzed using the autoregressive integrated moving average model. We found that peak concentrations of weed and tree pollens were positively associated with temperature (p < 0.05 at lag 0-1, 0-4, and 0-12 weeks) and precipitation (p < 0.05 at lag 0-4, 0-12, and 0-24 weeks) changes, respectively. We did not find clear associations between pollen concentrations and CO(2) levels or wildfire smoke exposure. This study's findings suggest that spore and pollen activities are related to changes in observed climate change variables.
There is clear evidence that climate change is occurring as there has been an acceleration of global temperatures since the mid-nineteenth century along with rising atmospheric carbon dioxide levels. It has been proposed that one of the most significant consequences of climate change on human health could be the impact on aeroallergens. Evidence from around globe has pointed to longer and more abundant pollen season associated with global warming. Additional studies have also suggested increased pollen allergenicity due to air pollution.
Rationale: Most studies of the healthcare utilization impact of pollen exposure have focused on emergency department visits or hospital admissions. However, other frequent but lower cost services-phone calls and e-mails to providers and office visits-may also be affected. Objectives: The objective of our study was to estimate the impact of tree and grass pollen exposures on respiratory-related healthcare utilization across a range of medical services, including calls and e-mails to providers, nonurgent face-to-face visits, urgent and emergent care visits, and hospitalizations. Methods: We conducted a retrospective observational study of daily tree and grass pollen counts linked to electronic health records of Kaiser Permanente beneficiaries in the metropolitan Washington, DC, area for 2013-2014. Results: The proportion of Kaiser Permanente beneficiaries with respiratory-related healthcare utilization was significantly greater (for P ⩽ 0.05) given a 1 standard deviation increase in same-day pollen exposure. For tree pollen, a 1 standard deviation increase in same-day pollen exposure was associated with relative increases in utilization ranging from 1.77% (95% confidence interval [CI], 0.07-4.17%) for urgent and emergent care visits to 12.84% (95% CI, 11.02-14.65%) for provider calls/e-mails. For grass pollen exposure, a 1 standard deviation increase in same-day pollen exposure was associated with relative increases in utilization ranging from 1.42% (95% CI, 0.39-2.46) for provider face-to-face visits to 11.09% (95% CI, 9.26-12.92) for provider calls/e-mails. Conclusions: Increased pollen exposure was associated with increases in healthcare utilization across a range of services, with relatively higher increases in provider calls/e-mails and lower increases in emergent or acute care. If climate change increases intensity and geographic scope of pollen exposure as predicted and if this study’s estimates of association of peak pollen exposure on healthcare utilization are generalizable, then the impact of climate change on healthcare utilization may be significant.
PURPOSE: Studies have implicated temperature and humidity in the pathogenesis of allergic conjunctivitis (AC), as these conditions facilitate air particulate and aeroallergen dispersion and tear film instability. Research also suggests that variation in temperature is associated with risk of asthma, but similar data are limited for AC. This study examined associations between several meteorologic conditions, including temperature variation, and AC visit risk. DESIGN: Retrospective, case-crossover study. METHODS: Data on individuals diagnosed with AC (via International Classification of Diseases-Ninth Edition [ICD-9]) at a Veterans Affairs clinic from January 2010-December 2013 was extracted. Local climate data were obtained from the National Climactic Data Center. Utilizing a case-crossover design, all cases were assigned a random control date 90-250 days prior to diagnosis. Daily time-lagged exposures were computed for 30-day lags. The associations between temperature, temperature variation (standard deviation [SD] of temperature), relative humidity (RH), and temperature-RH interaction with visit risk were examined via multivariate logistic regression models both at the national level and across domestic climate regions. RESULTS: Overall, 74,951 subjects made 116,162 visits for AC. Prevalence was highest in spring (>10% April-May) in the Northeast (NE) and Southeast (SE) (>15%), and lowest in winter (<6.1% December-February) in the Pacific Northwest (PNW) (<5%). AC visit risk was positively associated with temperature (OR 1.028, P < .001), SD of temperature (OR 1.054, P < .01), and temperature-RH interaction (OR 1.0003, P < .01), whereas it was negatively associated with RH (OR 0.998, P < .001). Regionally, the PNW, NE, and Lower Midwest (LMW) accounted for the strongest associations. CONCLUSION: Temperature, temperature variation, and RH associated with AC visit risk. Observed associations were strongest in northern regions, like the PNW.
Pollen grains may contain allergens that exacerbate allergic respiratory diseases like asthma and rhinitis. In the presence of water, pollen grains (10-100 μm) can rupture to produce sub-pollen particles (SPP) with diameters <2.5 μm, which in comparison to intact pollen grains, have longer atmospheric lifetimes and greater penetration to the lower lung. The current study examines SPP, fungal spores, and bacteria in size-resolved atmospheric particulate matter (PM) using chemical and biological tracers. During springtime tree pollen season in Iowa City, Iowa, fine particle (PM(2.5)) concentrations of fructose (a pollen chemical tracer) increased on rainy sampling periods, especially during severe thunderstorms, and peaked when a tornado struck nearby. Submicron fluorescent particles, measured by single-particle fluorescence spectroscopy, were also enhanced during rain events, particularly thunderstorms in agreement with the chemical tracer measurements. PM(2.5) sucrose (a pollen chemical tracer) concentrations were higher in early spring when nighttime temperatures were closer to freezing, while fructose concentrations were higher in late spring with warmer temperatures, consistent with chemical tracers being sensitive to seasonal temperature influences. The first co-located measurements of fructose and Bet v 1 (birch pollen allergen), indicated that SPP ranged in diameter from <0.25 to 2.5 μm during rainy sampling periods and that allergens and carbohydrates exhibited distinct size distributions. Meanwhile, mannitol (a fungal spore tracer) peaked on warm, dry days following rain and was primarily in supermicron particles (>1.0 μm), which is consistent with intact fungal spore diameters (1-30 μm). Bacterial endotoxins in PM also increased during extreme weather events, primarily in supermicron particles. While the concentrations of fructose, mannitol, and endotoxin all increased in PM(2.5) μm during thunderstorms, the greatest relative increase in concentration was observed for fructose. Together, these observations suggest that SPP containing starch granules and allergens (Bet v 1) were released during rainy sampling periods. This study advances the use of chemical tracers to track SPP and other bioaerosols in the atmosphere, by providing new insight to their size distribution and response to extreme weather conditions.
Though instances of arthropod-borne (arbo)virus co-infection have been documented clinically, the overall incidence of arbovirus co-infection and its drivers are not well understood. Now that dengue, Zika and chikungunya viruses are all in circulation across tropical and subtropical regions of the Americas, it is important to understand the environmental and biological conditions that make co-infections more likely to occur. To understand this, we developed a mathematical model of co-circulation of two arboviruses, with transmission parameters approximating dengue, Zika and/or chikungunya viruses, and co-infection possible in both humans and mosquitoes. We examined the influence of seasonal timing of arbovirus co-circulation on the extent of co-infection. By undertaking a sensitivity analysis of this model, we examined how biological factors interact with seasonality to determine arbovirus co-infection transmission and prevalence. We found that temporal synchrony of the co-infecting viruses and average temperature were the most influential drivers of co-infection incidence. Our model highlights the synergistic effect of co-transmission from mosquitoes, which leads to more than double the number of co-infections than would be expected in a scenario without co-transmission. Our results suggest that appreciable numbers of co-infections are unlikely to occur except in tropical climates when the viruses co-occur in time and space.
BACKGROUND: Estimates of the geographical distribution of Culex mosquitoes in the Americas have been limited to state and provincial levels in the United States and Canada and based on data from the 1980s. Since these estimates were made, there have been many more documented observations of mosquitoes and new methods have been developed for species distribution modeling. Moreover, mosquito distributions are affected by environmental conditions, which have changed since the 1980s. This calls for updated estimates of these distributions to understand the risk of emerging and re-emerging mosquito-borne diseases. METHODS: We used contemporary mosquito data, environmental drivers, and a machine learning ecological niche model to create updated estimates of the geographical range of seven predominant Culex species across North America and South America: Culex erraticus, Culex nigripalpus, Culex pipiens, Culex quinquefasciatus, Culex restuans, Culex salinarius, and Culex tarsalis. RESULTS: We found that Culex mosquito species differ in their geographical range. Each Culex species is sensitive to both natural and human-influenced environmental factors, especially climate and land cover type. Some prefer urban environments instead of rural ones, and some are limited to tropical or humid areas. Many are found throughout the Central Plains of the USA. CONCLUSIONS: Our updated contemporary Culex distribution maps may be used to assess mosquito-borne disease risk. It is critical to understand the current geographical distributions of these important disease vectors and the key environmental predictors structuring their distributions not only to assess current risk, but also to understand how they will respond to climate change. Since the environmental predictors structuring the geographical distribution of mosquito species varied, we hypothesize that each species may have a different response to climate change.
Amblyomma mixtum is a Neotropical generalist tick of medical and veterinary importance which is widely distributed from United States of America to Ecuador. The aim of this study was to evaluate changes in the geographic projections of the ecological niche models of A. mixtum in climate change scenarios in America. We constructed a database of published scientific publications, personal collections, personal communications, and online databases. Ecological niche modelling was performed with 15 Bioclimatic variables using kuenm in R and was projected to three time periods (Last Glacial Maximum, Current and 2050) for America. Our model indicated a wide distribution for A. mixtum, with higher probability of occurrence along the Gulf of Mexico and occurring in a lesser proportion in the Pacific states, Central America, and the northern part of South America. The areas of new invasion are located mainly on the border of Mexico with Guatemala and Belize, some regions of Central America and Colombia. We conclude that the ecological niche modelling are effective tools to infer the potential distribution of A. mixtum in America, in addition to helping to propose future measures of epidemiological control and surveillance in the new potential areas of invasion.
Heatwaves are increasing in frequency, duration, and intensity due to climate change. They are associated with high mortality rates and cross-sectional impacts including a reduction in crop yield and power outages. Here we demonstrate that there are large deficiencies in reporting of heatwave impacts in international disasters databases, international organization reports, and climate bulletins. We characterize the distribution of heat stress across the world focusing on August in the Northern Hemisphere, when notably heatwaves have taken place (i.e., 2003, 2010, and 2020) for the last 20 years using the ERA5-HEAT reanalysis of the Universal Thermal Comfort Index and establish heat stress has grown larger in extent, more so during a heatwave. Comparison of heat stress against the emergency events impacts database and climate reports reveals underreporting of heatwave-related impacts. This work suggests an internationally agreed protocol should be put in place for impact reporting by organizations and national government, facilitating implementation of preparedness measures, and early warning systems.
In the middle of the twentieth century, the from North America sooty bark disease (SBD) of maples was first discovered in England and has spread in the last decades in Central Europe, in particular. The trigger of SBD is the mould fungus Cryptostroma (C.) corticale. The most common infested maple is the sycamore, Acer pseudoplatanus, a common tree in woods and parks. The disease is characterised by peeling of the outer layer of the bark and brownish-black spores under the peeled off bark. These spores can cause maple bark disease (MBD) in humans, a hypersensitivity pneumonitis (HP) with similar symptoms like COPD, allergic asthma, influenza or flu-like infections and interstitial pneumonia. Persons who have intensive respectively occupational contact with infested trees or wood, e.g., woodman, foresters, sawyers or paper mill workers, are at risk in particular. Since C. corticale favours hot summers and host trees weakened by drought, SBD will increasingly spread in the future due to ongoing climate change. Consequently, the risk of developing MBD will increase, too. As with all HPs, e.g., farmer’s lung and pigeon breeder’s disease, the diagnosis of MBD is intricate because it has no clear distinguishing characteristics compared to other interstitial lung diseases. Therefore, the establishment of consistent diagnosis guidelines is required. For correct diagnosis and successful therapy, multidisciplinary expertise including pulmonologists, radiologists, pathologists and occupational physicians is recommended. If MBD is diagnosed in time, the removal of the triggering fungus or the infested maple wood leads to complete recovery in most cases. Chronic HP can lead to lung fibrosis and a total loss of lung function culminating in death. HP and, thus, MBD, is a disease with a very high occupational amount. To avoid contact with spores of C. corticale, persons working on infested wood or trees have to wear personal protective equipment. To protect the public, areas with infested maples have to be cordoned off, and the trees should be removed. This is also for impeding further spreading of the spores.
Ischemic heart disease (IHD) is one of the leading causes of death worldwide. While extreme summer surface air temperatures are thought to be a risk factor for IHD, it is unclear whether large-scale climate patterns also influence this risk. This multi-national population-based study investigated the association between summer Pacific and Atlantic sea surface temperature (SST) variability and annual acute myocardial infarction (AMI) or IHD event rates among older adults residing in North America and the United Kingdom. Overall, a shift from cool to warm phase of the El Niño Southern Oscillation (ENSO) was associated with reduced AMI admissions in western Canada (adjusted rate ratio [RR] 0.89; 95% CI, 0.80-0.99), where this climate pattern predominatly forces below-normal cloud cover and precipitation during summertime, and increased AMI deaths in western United States (RR 1.09; 95% CI, 1.04-1.15), where it forces increased cloud cover and precipitation. Whereas, the Atlantic Multidecadal Oscillation (AMO) during a strong positive phase was associated with reduced AMI admissions in eastern Canada (RR 0.93; 95% CI, 0.87-0.98) and increased IHD mortality during summer months in the United Kingdom (RR 1.08; 95% CI, 1.03-1.14). These findings suggest that SST variability can be used to predict changes in cardiovascular event rates in regions that are susceptible.
Tropical cyclones are highly destructive weather systems, especially in coastal areas. Tropical cyclones with maximum sustained winds exceeding 74 mph (≈119 kph) are classified as typhoons in the Northwest Pacific, whilst the term ‘hurricanes’ applies to other regions. This study aims to investigate the general characteristics of the most devastating and catastrophic tropical cyclones in the USA Europe, and Asia. To achieve the study objectives, the three most devastating typical tropical cyclones in each region were selected. The tropical cyclones were examined based on various features, such as the number of deaths, minimum pressure, highest wind speed, total financial losses, and frequency per year. In contrast to Europe and Asia, the USA has recorded the highest number of catastrophic tropical cyclones. The damage induced by hurricanes Katrina, Harvey, and Maria in the USA totalled approximately USD USD 380 billion. In addition, the present research highlights the demand to improve the public attitude and behaviour toward the impact of climate change along with the enhancement of climate change alleviation strategies. The number of intense tropical cyclones is expected to rise, and the tropical cyclone-related precipitation rate is expected to increase in warmer-climate areas. Stakeholders and industrial practitioners may use the research findings to design resilience and adaptation plans in the face of tropical cyclones, allowing them to assess the effects of climate change on tropical cyclone incidents from an academic humanitarian logistics viewpoint in the forthcoming years.
Wildfires can have rapid and long-term effects on air quality, human health, climate change, and the environment. Smoke from large wildfires can travel long distances and have a harmful effect on human health, the environment, and climate in other areas. More recently, in 2018-2019 there have been many large fires. This study focused on the wildfires that occurred in the United States of America (USA), Brazil, and Australia using Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP) and a TROPOspheric Monitoring Instrument (TROPOMI). Specifically, we analyzed the spatial-temporal distribution of black carbon (BC) and carbon monoxide (CO) and the vertical distribution of smoke. Based on the results, the highest detection of smoke (similar to 14 km) was observed in Brazil; meanwhile, Australia showed the largest BC column burden of similar to 1.5 mg/m(2). The meteorological conditions were similar for all sites during the fires. Moderate temperatures (between 32 and 42 degrees C) and relative humidity (30-50%) were observed, which resulted in drier conditions favorable for the burning of fires. However, the number of active fires was different for each site, with Brazil having 13 times more active fires than the USA and five times more than the number of active fires in Australia. However, the high number of active fires did not translate to higher atmospheric constituent emissions. Overall, this work provides a better understanding of wildfire behavior and the role of meteorological conditions in emissions at various sites.
There is limited knowledge about how crises are framed on different social media platforms specifically in a non-Western cultural context. This study compares how extreme environmental crises-Hurricane Maria and haze-were framed on Twitter and Weibo. Through word-cloud, co-occurrence, and thematic analyses with Hurricane Maria-related tweets, this study identified two major frames of this crisis: a disaster frame and a political frame. Similarly, by analyzing haze-related posts on Sina Weibo, two major frames emerged: an environmental frame and a health frame. Both crises were largely framed as environmental issues rather than health risks or crises. Such framing helps shape the existence of Hurricane Maria and haze as legitimate facts. The findings also reveal that cultural variances, eg, power distance, collectivist-individualist culture, and uncertainty avoidance, impact crisis framing. This study indicates the importance of designing culture-fit messages and incorporating social media strategies in crisis communication while developing emergency management plans and adds knowledge to the limited literature on social-mediated crisis communication in different cultural contexts. Such knowledge will provide theoretical and practical implications for crisis scholars, emergency management practitioners, and policymakers.
Aim The distribution of Yersinia pestis, the pathogen that causes plague in humans, is reliant upon transmission between host species; however, the degree to which host species distributions dictate the distribution of Y. pestis, compared with limitations imposed by the environmental niche of Y. pestis per se, is debated. We test whether the present-day environmental niche of Y. pestis differs between its native range and an invaded range and whether biotic factors (host distributions) can explain observed discrepancies. Location North America and Central Asia. Major taxa studied Yersinia pestis. Methods We use environmental niche models to determine whether the current climatic niche of Y. pestis differs between its native range in Asia and its invaded range in North America. We then test whether the inclusion of information on the distribution of host species improves the ability of models to capture the North American niche. We use geographical null models to guard against spurious correlations arising from spatially autocorrelated occurrence points. Results The current climatic niche of Y. pestis differs between its native and invaded regions. The Asian niche overpredicted the distribution of Y. pestis across North America. Including biotic factors along with the native climatic niche increased niche overlap between the native and invaded models, and models containing only biotic factors performed better than the native climatic niche alone. Geographical null models confirmed that the increased niche overlap through inclusion of biotic factors did not, with a couple of exceptions, arise solely from spatially autocorrelated occurrences. Main conclusions The current climatic niche in Central Asia differs from the current climatic niche in North America. Inclusion of biotic factors improved the fit of models to the Y. pestis distribution data in its invaded region better than climate variables alone. This highlights the importance of host species when investigating zoonotic disease introductions and suggests that climatic variables alone are insufficient to predict disease distribution in novel environments.
Several countries have been affected by natural hazards during the COVID-19 pandemic. The combination of the pandemic and natural hazards has led to serious challenges that include financial losses and psychosocial stress. Additionally, this compound disaster affected evacuation decision making, where to evacuate, volunteer participation in mitigation and recovery, volunteer support acceptance, and interest in other hazard risks. This study investigated the impact of COVID-19 on disaster response and recovery from various types of hazards, with regard to preparedness, evacuation, volunteering, early recovery, awareness and knowledge of different types of hazards, and preparedness capacity development. This study targets hazards such as Cyclone Amphan in India, the Kumamoto flood in Japan, Typhoon Rolly in the Philippines, and the California wildfires in the U.S. This study made several recommendations, such as the fact that mental health support must be taken into consideration during COVID-19 recovery. It is necessary to improve the genral condition of evacuation centers in order to encourage people to act immediately. A pandemic situation necessitates a strong communication strategy and campaign with particular regard to the safety of evacuation centers, the necessity of a lockdown, and the duration required for it to reduce the psychological impact. Both national and local governments are expected to strengthen their disaster risk reduction (DRR) capacity, which calls for the multi-hazard management of disaster risk at all levels and across all sectors.
INTRODUCTION: Global climate change (global warming) has been identified as the primary factor responsible for the observed increase in frequency and severity of wildfires (also known as bushfires in some countries) throughout the majority of the world’s vegetated environments. This trend is predicted to continue, causing significant adverse health effects to nearby residential populations and placing a potential strain on local emergency departments (EDs). STUDY OBJECTIVE: The aim of this literature review was to identify papers relating to wildfires and their impact on EDs, specifically patient presentation characteristics, resource utilization, and patient outcomes. METHOD: This integrative literature review was guided by the Preferred Reporting Items of Systematic Reviews and Meta-Analysis (PRISMA) guidelines for data collection, and Whittemore and Knafl’s framework for data analysis. Data were collected from OvidSP, MEDLINE, DARE, CINAHL, PubMed, and Scopus databases. Various Medical Subject Headings (MeSH) and keywords identified papers relevant to wildfires/bushfires and EDs. RESULTS: Literature regarding the relationship between ED presentations and wildfire events, however, is primarily limited to studies from the United States and Australia and indicates particulate matter (PM) is principally linked to adverse respiratory and cardiovascular outcomes. Observable trends in the literature principally included a significant increase in respiratory presentations, primarily with a lag of one to two days from the initial event. Respiratory and cardiovascular studies that stratified results by age indicated individuals under five, over 65, or those with pre-existing conditions formed the majority of ED presentations. CONCLUSION: Key learnings from this review included the need for effective and targeted community advisory programs/procedures, prior to and during wildfire events, as well as pre-event planning, development, and robust resilience strategies for EDs.
An outbreak of powerful tornadoes tore through multiple states in the central and southern United States from 10 to 11 December 2021. It is claimed the deadliest tornado outbreak that has taken place on December days. The National Oceanic and Atmospheric Administration had confirmed 66 tornadoes as of 21 December, producing at least 90 fatalities. Most tornadoes occurred at night and thus they were difficult to be visually located, which directly increases the risk for local residents. Two violent nighttime tornadoes were rated category 4 on the enhanced Fujita scale (EF4). Although a high death toll was caused during this event, the operational service actually presented an excellent performance. This tornado outbreak has aroused extensive discussion from both the public and the research community in China. This paper presents a brief discussion on the formation environment and warning services of the tornado outbreak. Recall the deadliest violent tornado in the past 45 years in China, the radar-based tornadic vortex signatures at the locations with EF4 damages show a comparable strength with those in the current cases. Some views on the tornado warning issuance and receiving and damage surveys in China are also presented.
Extreme weather and climate events are likely to increase in frequency and severity as a consequence of global climate change. These are events that can include flooding rains, prolonged heat waves, drought, wildfires, hurricanes, severe thunderstorms, tornadoes, storm surge, and coastal flooding. It is important to consider these events as they are not merely meteorologic occurrences but are linked to our health. We aim to address how these events are interconnected with asthma outcomes associated with thunderstorm asthma, pollen production, mold infestation from flooding events, and poor air quality during wildfires.
Climate change acts as a risk multiplier, meaning vulnerable populations bear a disproportionate burden of its effects. Improving climate resiliency is a key strategy to help the Rhode Island Department of Health meet its overarching goals of addressing the socio-economic and environmental determinants of health for all Rhode Islanders. The Climate Change and Health Program focuses on both the immediate health impacts of climate change and building resiliency. Part of the US Centers for Disease Control and Prevention’s Climate Ready States and Cities Initiative, the Program has partnered with community groups and other state and local agencies to bring technical assistance, educational resources, and funding to support community resilience to the challenges presented by the already changing climate. Specific projects discussed include the extreme heat communications plan and outdoor worker campaign; community-driven resiliency projects in response to flooding and natural hazards, and improving resilience in senior citizen housing.
Purpose This article examines US official and public responses to the COVID-19 pandemic for insights into future policy and pubic responses to global climate change. Design/methodology/approach This article compares two contemporary global threats to human health and well-being: the COVID-19 pandemic and climate change. We identify several similarities and differences between the two environmental phenomena and explore their implications for public and policy responses to future climate-related disasters and disruptions. Findings Our review of research on environmental and public health crises reveals that though these two crises appear quite distinct, some useful comparisons can be made. We analyze several features of the pandemic for their implications for possible future responses to global climate change: elasticity of public responses to crises; recognition of environmental, health, racial, and social injustice; demand for effective governance; and resilience of the natural world. Originality/value This paper examines public and policy responses to the coronavirus pandemic for their implications for mitigating and adapting to future climate crises.
The concept of emerging diseases is well understood; however, the concept of emerging injuries is not. We describe the introduction of two species of lionfish, native to the Indian and Pacific Oceans, into the warm shallow coastal waters of the Western Atlantic Ocean and the Caribbean Sea. Lionfish thrive in the same coastal waters that attract recreational swimmers, snorkelers, and divers. Because lionfish have ornate colors, people often swim close to have a better look. Lionfish have venomous spines and, in a defensive reaction, frequently envenomate curious humans. The fish are voracious predators and disrupt the coral ecosystems of the Atlantic. Furthermore, their range is spreading through a combination of lack of natural predators and the expansion of hospitable warm waters into higher latitudes as part of climate change.
Global atmospheric warming leads to climate change that results in a cascade of events affecting human mortality directly and indirectly. The factors that influence climate change-related mortality within the peer-reviewed literature were examined using Whittemore and Knafl’s framework for an integrative review. Ninety-eight articles were included in the review from three databases-PubMed, Web of Science, and Scopus-with literature filtered by date, country, and keywords. Articles included in the review address human mortality related to climate change. The review yielded two broad themes in the literature that addressed the factors that influence climate change-related mortality. The broad themes are environmental changes, and social and demographic factors. The meteorological impacts of climate change yield a complex cascade of environmental and weather events that affect ambient temperatures, air quality, drought, wildfires, precipitation, and vector-, food-, and water-borne pathogens. The identified social and demographic factors were related to the social determinants of health. The environmental changes from climate change amplify the existing health determinants that influence mortality within the United States. Mortality data, national weather and natural disaster data, electronic medical records, and health care provider use of International Classification of Disease (ICD) 10 codes must be linked to identify climate change events to capture the full extent of climate change upon population health.
The Fourth National Climate Assessment (NCA4) is the most comprehensive report to date assessing climate change science, impacts, risks, and adaptation in the United States. The 1,500 page report covers a breadth of topics, ranging from foundational physical science to climate change response options. Here we present information on indicators and impacts of climate change in the human environment featured in NCA4 Volume II, focusing on: air quality, forest disturbance and wildfire, energy systems, and water resources. Observations, trends, and impacts of these aspects of our changing climate will be discussed, along with implications for the future. Implications: People of the United States are already being affected by our changing climate. Information on observed changes and impacts that affect human welfare and society, along with projections for the future, is highly valuable for informing decision-makers, including utility managers, emergency planners, and other stakeholders, about climate risk assessment, adaptation, and mitigation options.
The United States has approximately 5 percent of the world’s population but incarcerates nearly 25 percent of the world’s incarcerated population and produces nearly 25 percent of global carbon dioxide emissions to date. Climate change and hyperincarceration are causes and consequences of structural racism and economic deprivation, which disproportionately affect structurally disenfranchised citizens, including lower-income communities, communities of color, and people with disabilities. Empirical evidence exists regarding the adverse health effects of climate change and mass incarceration, which occur in cascading and overlapping categories and include preventable death, illness, and injury. Researchers underscore the medical vulnerability of incarcerated populations, who are increasingly susceptible to climate-driven exposure pathways and mental and physical health outcomes involving extreme temperatures, natural disasters, infectious diseases, and displacement. Intersectional structural drivers, such as anthropogenic climate change and hyperincarceration, undermine social and political determinants of health equity. Policymakers and health professionals can advance understanding and mitigate present and anticipated public health threats by increasing transparency, accountability, and human rights protections with an emphasis on decarceration and decarbonization.
Anthropogenic emissions of greenhouse gases are warming the Earth. It is likely that the greatest impacts of climate change on human and natural systems will come from increasingly frequent and severe extreme weather and climate events. Some increases in such extremes are already being detected, and this trend is projected to continue as Earth warms. Here we review the overarching climate drivers of increases in extreme weather and address the context in which extremes occur and the challenges of projecting future changes. The observational evidence for climate-driven increases in extremes and the implications of model projections are reviewed for heat and drought and several types of storms: tropical cyclones, midlatitude storms, and severe local weather, focusing on those changes most relevant to the continental United States. We emphasize the overall observed and modeled trends in extreme weather in which we have the greatest confidence, because they are consistent with our fundamental understanding of weather and climate. Despite remaining uncertainty about many details, especially in model-based projections, the signal of increasing extremes is sufficiently clear that it demands a robust human response, in limiting future emissions of greenhouse gases and in making our human systems more resilient to further changes that are inevitable as Earth continues to warm.Implications: By placing observed and projected changes in extreme weather in the context of our fundamental understanding of physics and statistics, this review makes it clear that these are significant and impactful changes that demand a robust human response.
Purpose of review This review aims to identify the key factors, methods, and spatial units used in the development and validation of the heat vulnerability index (HVI) and discuss the underlying limitations of the data and methods by evaluating the performance of the HVI. Recent findings Thirteen studies characterizing the factors of the HVI development and relating the index with validation data were identified. Five types of factors (i.e., hazard exposure, demographic characteristics, socioeconomic conditions, built environment, and underlying health) of the HVI development were identified, and the top five were social cohesion, race, and/or ethnicity, landscape, age, and economic status. The principal component analysis/factor analysis (PCA/FA) was often used in index development, and four types of spatial units (i.e., census tracts, administrative area, postal code, grid) were used for establishing the relationship between factors and the HVI. Moreover, although most studies showed that a higher HVI was often associated with the increase in health risk, the strength of the relationship was weak. This review provides a retrospect of the major factors, methods, and spatial units used in development and validation of the HVI and helps to define the framework for future studies. In the future, more information on the hazard exposure, underlying health, governance, and protection awareness should be considered in the HVI development, and the duration and location of validation data should be strengthened to verify the reliability of HVI.
Air quality impacts from wildfires have been dramatic in recent years, with millions of people exposed to elevated and sometimes hazardous fine particulate matter (PM2.5) concentrations for extended periods. Fires emit particulate matter (PM) and gaseous compounds that can negatively impact human health and reduce visibility. While the overall trend in U.S. air quality has been improving for decades, largely due to implementation of the Clean Air Act, seasonal wildfires threaten to undo this in some regions of the United States. Our understanding of the health effects of smoke is growing with regard to respiratory and cardiovascular consequences and mortality. The costs of these health outcomes can exceed the billions already spent on wildfire suppression. In this critical review, we examine each of the processes that influence wildland fires and the effects of fires, including the natural role of wildland fire, forest management, ignitions, emissions, transport, chemistry, and human health impacts. We highlight key data gaps and examine the complexity and scope and scale of fire occurrence, estimated emissions, and resulting effects on regional air quality across the United States. The goal is to clarify which areas are well understood and which need more study. We conclude with a set of recommendations for future research. Implications In the recent decade the area of wildfires in the United States has increased dramatically and the resulting smoke has exposed millions of people to unhealthy air quality. In this critical review we examine the key factors and impacts from fires including natural role of wildland fire, forest management, ignitions, emissions, transport, chemistry and human health.
Climate change affects Arctic marine ecosystems, the ecosystem services they provide, and the human well-being that relies on these services. The impacts of climate change in the Arctic and elsewhere involve cascading effects and feedbacks that flow across social-ecological systems (SES), such as when sea ice loss alters food security through changes in the distribution of marine animals. These cascades and feedbacks across social and ecological systems can exacerbate the effects of climate change or lead to surprising outcomes. Identifying where cascades and feedbacks may occur in SES can help anticipate, or even prevent unexpected outcomes of climate change, and lead to improved policy or responses. Here, we perform a systematic literature review of multidisciplinary Arctic o research to determine the state of knowledge of the impacts of climate change on marine ecosystems. Then, in a case study corresponding to Inuit regions, we use network analysis to integrate research into a SES perspective and identify which linkages have been most sus least studied, and whether some potential cascades and feedbacks have been overlooked. Finally, we propose ways forward to advance knowledge of changing Arctic marine SES, including transdisciplinary approaches involving multiple disciplines and the collaboration of Indigenous and local knowledge holders.
Catastrophic wildfires are increasing around the globe as climate change continues to progress. Another risk factor for large wildfires in the western United States is a legacy of fire suppression that has allowed overgrowth of underbrush and small trees in forests where periodic lightning-sparked wildfires are part of the natural ecosystem. Wildfire smoke contains CO(2), CO, NOx, particulate matter, complex hydrocarbons (including polycyclic aromatic hydrocarbons), and irritant gases, including many of the same toxic and carcinogenic substances as cigarette smoke. The public need clear and consistent messaging to understand that wildland fire smoke poses a health risk.
The power to change the natural environment has received relatively little attention in public health law, yet is a core concern within environmental and agricultural law. Examples from environmental and agricultural law may inform efforts to change the natural environment in order to reduce the health impacts of climate change. Public health lawyers who attend to the natural environment may succeed in elevating health concerns within the environmental and agricultural law spheres, while gaining new tools for their public health law toolbox.
As climate change advances, communities across the United States are adapting to the increased threat of wildfires, drought, heatwaves, and infectious diseases. Such disasters are expected to become more frequent and severe. Now more than ever, it is crucial to understand how these events amplify existing inequalities, and how to lessen the resulting harms. Differences in human vulnerability to disaster stem from a range of social, economic, historical, and political factors. We argue that given their social status, undocumented Latino/a and Indigenous immigrants are particularly vulnerable to disasters and require special consideration in disaster planning. They are disproportionately affected by racial discrimination, exploitation, economic hardships, less English and Spanish proficiency, and fear of deportation in their everyday lives- their pre-disaster marginalized status. In the case of the Thomas Fire in California’s Ventura and Santa Barbara counties, we show that emergency response and recovery efforts ignored their needs. Resources were directed toward privileged individuals, leaving local immigrant rights and environmental justice groups to provide essential services such as language access to emergency information in Spanish and Indigenous tongues; labor protections for farmworkers endangered in the fields; and a private disaster relief fund for undocumented immigrants ineligible for federal aid. The article concludes with preliminary participant observations from the COVID-19 pandemic response in the region, indicating how lessons from the fire have informed official actions. As governments grapple with the increasing severity of disasters, understanding the differential impacts on undocumented immigrants can help improve disaster planning to protect the most vulnerable and stigmatized populations.
The Imperial Valley region of Southeastern California has become one of the most productive agricultural regions in the state and has the highest rates of childhood asthma in California. Lack of precipitation in the Imperial Valley has caused the water level of the Salton Sea to recede to a record low since its formation in the early 1900s. Previous studies of wind and dust deposition conducted in other regions have shown how reduced precipitation, ground heating, and the diminishing water level in an arid climate pose a risk of exposing previously sequestered toxic chemicals to open air, adversely affecting lung health. The purpose of this study is to draw historical parallels between the Aral Sea and Salton Sea in the context of geomorphology, ecology, human health, economics, and human migration, to inform an assessment of environmentally related health impacts of those living in the Imperial Valley region. Future droughts and heatwaves are expected to rise in frequency and severity, disproportionately affecting those impacted by financial and health disparities. Future research must include the implications of population health in the context of GeoHealth as a result of the most recent drought and the receding water levels of the Salton Sea.
Since the publication of the last American Heart Association scientific statement on air pollution and cardiovascular disease in 2010, unequivocal evidence of the causal role of fine particulate matter air pollution (PM2.5, or particulate matter <= 2.5 mu m in diameter) in cardiovascular disease has emerged. There is a compelling case to provide the public with practical personalized approaches to reduce the health effects of PM2.5. Such interventions would be applicable not only to individuals in heavily polluted countries, high-risk or susceptible individuals living in cleaner environments, and microenvironments with higher pollution exposures, but also to those traveling to locations with high levels of PM2.5. The overarching motivation for this document is to summarize the current evidence supporting personal-level strategies to prevent the adverse cardiovascular effects of PM2.5, guide the use of the most proven/viable approaches, obviate the use of ineffective measures, and avoid unwarranted interventions. The significance of this statement relates not only to the global importance of PM2.5, but also to its focus on the most tested interventions and viable approaches directed at particulate matter air pollution. The writing group sought to provide expert consensus opinions on personal-level measures recognizing the current uncertainty and limited evidence base for many interventions. In doing so, the writing group acknowledges that its intent is to assist other agencies charged with protecting public health, without minimizing the personal choice considerations of an individual who may decide to use these interventions in the face of ongoing air pollution exposure.
PURPOSE OF REVIEW: Power outages, a common and underappreciated consequence of natural disasters, are increasing in number and severity due to climate change and aging electricity grids. This narrative review synthesizes the literature on power outages and health in communities. RECENT FINDINGS: We searched Google Scholar and PubMed for English language studies with titles or abstracts containing “power outage” or “blackout.” We limited papers to those that explicitly mentioned power outages or blackouts as the exposure of interest for health outcomes among individuals living in the community. We also used the reference list of these studies to identify additional studies. The final sample included 50 articles published between 2004 and 2020, with 17 (34%) appearing between 2016 and 2020. Exposure assessment remains basic and inconsistent, with 43 (86%) of studies evaluating single, large-scale power outages. Few studies used spatial and temporal control groups to assess changes in health outcomes attributable to power outages. Recent research linked data from electricity providers on power outages in space and time and included factors such as number of customers affected and duration to estimate exposure. The existing literature suggests that power outages have important health consequences ranging from carbon monoxide poisoning, temperature-related illness, gastrointestinal illness, and mortality to all-cause, cardiovascular, respiratory, and renal disease hospitalizations, especially for individuals relying on electricity-dependent medical equipment. Nonetheless the studies are limited, and more work is needed to better define and capture the relevant exposures and outcomes. Studies should consider modifying factors such as socioeconomic and other vulnerabilities as well as how community resiliency can minimize the adverse impacts of widespread major power outages.
Vector Disease Control International (VDCI) has a long history of aiding mosquito control efforts necessary for recovery after natural disasters like hurricanes and major floods. As waters associated with these events begin to recede, both nuisance and vector mosquito species surge in abundance and consequently play an increased role in public health. When these situations arise, state and county agencies implement emergency response plans and many rely on Federal Emergency Management Agency or private contractors for assistance in reducing mosquito populations that can alter arbovirus transmission cycles, cause intolerable stress, hamper reconstruction efforts, and disrupt normal community functions. Vector Disease Control International owns the largest fleet of fixed-wing aircraft dedicated specifically to mosquito control and has worked every major storm event since Hurricane Bonnie in 1998. This article describes the logistics and operations required for implementing VDCI’s emergency management plan, including the relocation of equipment, adult mosquito surveillance, delivery of pesticides, assessment of efficacy, and filing of low-level waivers and congested-area plans with the Federal Aviation Administration.
Over the past century, anthropogenic activities have resulted in high levels of greenhouse gases in our environment, creating a warming effect on the Earth. As a result, global temperatures have risen, shifting climatic zones, influencing weather patterns, and intensifying storms. These changes include heavy precipitation, drought, wildfires, hurricanes, heat waves, and coastal flooding. The impacts from this climatic activity continue to contribute negatively to our environment while influencing human health.In this special issue of the North Carolina Medical Journal, authors from universities, governmental agencies, and not-for-profit organizations address how the global impacts of climate change are affecting the health of communities across our beautiful state. This issue offers our readers research and real-life stories that underscore the need for keeping the issue of climate change at the forefront of public health for North Carolina. The information provided in these articles gives policymakers and health care providers a deeper understanding of the public health implications and challenges of climate change while highlighting the health risks to our most susceptible populations.Because there are no direct clinical symptoms or signs, the effects of climate change are difficult to assess at the individual level. However, an abundance of peer-reviewed climate health research studies provides overwhelming scientific evidence that climate change is impacting population health with generalizable results. Mitigation and adaptability strategies are necessary for reducing carbon emissions and building climate-resilient communities. Policymakers and health care providers are in key positions for educating others, helping protect our planet, improving health outcomes, and moving North Carolina toward more sustainable solutions.
Over the last century, droughts have caused more deaths internationally than any other weather- or climate-related disaster. Like other natural disasters, droughts cause significant changes in the environment that can lead to negative health outcomes. As droughts are becoming more frequent and intense with climate change, public health systems need to address impacts associated with these events. Partnering with federal and local entities, we evaluated the state of knowledge of drought and health in the United States through a National Drought and Public Health Summit and a series of subsequent regional workshops. The intended outcome was to develop public health strategies for implementing activities to better support and prepare public health systems for future droughts. The information gathered from this work identified multiple policy and law options to address the public health issues associated with drought. These policy recommendations include the use of public health emergency declarations for drought events, increased usage of preparedness evaluations for drought emergencies, and engagement of drought and climate experts in state and local risk assessments. As drought events are projected to increase in frequency and magnitude with climate change, taking policy action now will help decrease the health impacts of drought and save lives.
Objective: Skin cancer is the most frequently diagnosed cancer and rates are increasing because of global warming. This article reports a meta-analysis of randomized controlled trials of behavioral interventions to reduce exposure to ultraviolet radiation (UVR). The review aimed to (a) quantify the magnitude of intervention effects on indoor tanning, sun exposure, and sunscreen use, and (b) determine which intervention strategies maximize behavior change. Method: Out of 17,437 records identified via literature searches, 190 independent tests (N = 89,365) met the inclusion criteria. Sample, intervention, and methodological characteristics, and change techniques were coded, and random effects meta-analyses and metaregressions were conducted. Results: The sample-weighted average effect size across all studies was d(+) = .193 (95% confidence interval, CI [.161, .226]), and there were significant effects on indoor tanning, sun exposure, and sunscreen use (d(+) = .080, .149, and .196, respectively). However, there was evidence of publication bias, and trim and fill analyses indicated that the corrected effects for sun exposure and sunscreen use were of very small magnitude (d(+) ~ .06) and were not significantly different from zero for indoor tanning (d(+) = -.011, 95% CI [-.096, .074]). Metaregression analyses identified several intervention strategies that predicted effect sizes. For instance, interventions delivered individually that promoted alternatives to tanning were associated with larger effect sizes for indoor tanning. Conclusion: Interventions to date have had only a modest impact on behavioral exposure to UVR. The present findings offer new insights into how the effectiveness of future interventions can be improved. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
INTRODUCTION: Natural hazards are elements of the physical environment caused by forces extraneous to human intervention and may be harmful to human beings. Natural hazards, such as weather events, can lead to natural disasters, which are serious societal disruptions that can disrupt dialysis provision, a life-threatening event for dialysis-dependent people. The adverse outcomes associated with missed dialysis sessions are likely exacerbated in island settings, where health care resources and emergency procedures are limited. The effect of natural disasters on dialysis patients living in geographically vulnerable areas such as the Cayman Islands is largely understudied. To inform predisaster interventions, we systematically reviewed studies examining the effects of disasters on dialysis patients and discussed the implications for emergency preparedness in the Cayman Islands. METHODS: Two reviewers independently screened 434 titles and abstracts from PubMed, Scopus, CINAHL, and Cochrane Library. We included studies if they were original researchs published in English from 2009 to 2019 and conducted in the Americas. RESULTS: Our search yielded 15 relevant articles, which we included in the final analysis. Results showed that disasters have both direct and indirect effects on dialysis patients. Lack of electricity, clean water, and transportation, and closure of dialysis centers can disrupt dialysis care, lead to missed dialysis sessions, and increase the number of hospitalizations and use of the emergency department. Additionally, disasters can exacerbate depression and lead to posttraumatic stress disorder among dialysis patients. CONCLUSION: To our knowledge, this systematic review is the first study that presents a synthesis of the scientific literature on the effects of disasters on dialysis populations. The indirect and direct effects of disasters on dialysis patients highlight the need for predisaster interventions at the patient and health care system levels. Particularly, educating patients about an emergency renal diet and offering early dialysis can help to mitigate the negative effects of disasters.
Research on air quality and human health “co-benefits” from climate mitigation strategies represents a growing area of policy-relevant scholarship. Compared to other aspects of climate and energy policy evaluation, however, there are still relatively few of these co-benefits analyses. This sparsity reflects a historical disconnect between research quantifying energy and climate, and research dealing with air quality and health. The air quality co-benefits of climate, clean energy, and transportation electrification policies are typically assessed with models spanning social, physical, chemical, and biological systems. This review article summarizes studies to date and presents methods used for these interdisciplinary analyses. Studies in the peer-reviewed literature (n = 26) have evaluated carbon pricing, renewable portfolio standards, energy efficiency, renewable energy deployment, and clean transportation. A number of major findings have emerged from these studies: [1] decarbonization strategies can reduce air pollution disproportionally on the most polluted days; [2] renewable energy deployment and climate policies offer the highest health and economic benefits in regions with greater reliance on coal generation; [3] monetized air quality health co-benefits can offset costs of climate policy implementation; [4] monetized co-benefits typically exceed the levelized cost of electricity (LCOE) of renewable energies; [5] Electric vehicle (EV) adoption generally improves air quality on peak pollution days, but can result in ozone dis-benefits in urban centers due to the titration of ozone with nitrogen oxides. Drawing from these published studies, we review the state of knowledge on climate co-benefits to air quality and health, identifying opportunities for policy action and further research.
Ideally, all mosquito control programs would have public health-driven and nuisance population-focused components in their mosquito control plan. However, due to resource limitations many mosquito control programs focus attention on one specific component of integrated mosquito control, i.e., adulticiding only. Programs run by public health departments with limited resources are frequently heavily focused on vector control, targeting a few mosquito species that are locally medically relevant in human and animal disease cycles. Focusing their mosquito management on these specific vector species can result in inefficiencies after hurricanes and severe flooding events that create a need for nuisance mosquito control. Floodwater nuisance species that emerge are not routinely a public health threat, but hinder operations related to response efforts and can negatively affect the lives of people in areas recovering from these disaster events. Staff, training, equipment, and facilities, when aimed at public health vector control, may not have the experience, knowledge, or tools to effectively respond to postdisaster, floodwater mosquito populations. As such, all mosquito management programs should have plans in place to handle not only known vectors of public health concern in response to mosquito-borne disease, but also to manage floodwater mosquito populations after natural disasters to safeguard public health and facilitate recovery operations. The current paper discusses the severe weather events in South Texas in 2018 and the resulting integrated nuisance floodwater mosquito control guidance developed by the Texas Department of State Health Services.
Coastal regions worldwide will be dramatically reshaped by the impacts of sea-level rise. Of particular concern are impacts on coastal wetlands, the loss of which would have consequences for both human and ecological communities. The future of many coastal wetlands will depend greatly on their capacities to migrate into uplands. Coastal resilience work within wetland sciences has increasingly focused on developing strategies to promote marsh migration into rural uplands; however, less attention has been given to the impacts that migrating marshes have on people in these landscapes. In this paper, we share rural perspectives and experiences with marsh migration through three case-studies from collaborative research with rural, low-lying communities on the Chesapeake Bay, USA. These case-studies demonstrate the complexities of the challenges facing rural communities as a result of marsh migration, and reveal important issues of equity and injustice that need attention in future coastal resilience work. We draw upon a socio-ecological systems (SES) approach to highlight potential human-ecological misalignments that emerge with marsh migration and to offer future research questions to inform socially-just and resilient wetland migration planning in rural coastal areas.
The occurrence of tropical storms and hurricanes is a certainty in the Atlantic Basin each year. Many of these never make landfall. Those that do can range in intensity from a weak tropical depression to a very destructive Category 5 hurricane. These storms often produce large amounts of rainfall and flooding, resulting in increases in the mosquito populations in the affected areas. In order to deal with this problem, aerial applications of insecticides over wide areas can provide relief to the impacted area, assisting in the recovery efforts. Meeting the demand for these sudden and large increases in the volume of the insecticide most commonly used in aerial applications requires great coordination, communication, and commitment. We describe the diverse entities involved in the manufacture, distribution, and use of the product and how this increase in need is recognized, managed, and satisfied in a compressed period of time.
PURPOSE OF REVIEW: Climate change has brought about many changes in our ecosystem. Prolongation of pollen seasons has been reported, related to earlier frost off in the spring and later onset of frost on in the fall. This review considers recent global evidence that stinging insects are redistributing toward the poles, thereby potentially increasing human exposure and risk of sting events. RECENT FINDINGS: With changing climate, particularly climate warming, range expansion of insects is occurring in both the Northern and Southern Hemispheres. Likewise, stinging insects, such as Hymenoptera and Lepidoptera, are also expanding range. Though there is scant data on associated increase of insect-related anaphylaxis, increased insect-human interaction is certain. SUMMARY: It is likely that climate change will continue to alter the distribution and population of Hymenoptera and other insects. As temperatures warm and regions become suitable for nesting and establishment of colonies, many insects will expand their territory. As already reported in Alaska, one would anticipate expansion of range, especially toward the poles, thereby increasing the probability of human encounters and likewise anaphylaxis.
One-fifth of the way through the 21st century, a commonality of factors with those of the last 50 years may offer the opportunity to address unfinished business and current challenges. The recommendations include: (1) Resisting the tendency to oversimplify scientific assessments by reliance on single disciplines in lieu of clear weight-of-evidence expressions, and on single quantitative point estimates of health protective values for policy decisions; (2) Improving the separation of science and judgment in risk assessment through the use of clear expressions of the range of judgments that bracket protective quantitative levels for public health protection; (3) Use of comparative risk to achieve the greatest gains in health and the environment; and (4) Where applicable, reversal of the risk assessment and risk management steps to facilitate timely and substantive improvements in public health and the environment. Lessons learned and improvements in the risk assessment process are applied to the unprecedented challenges of the 21st century such as, pandemics and climate change. The beneficial application of the risk assessment and risk management paradigm to ensure timely research with consistency and transparency of assessments is presented. Institutions with mandated stability and leadership roles at the national and international levels are essential to ensure timely interdisciplinary scientific assessment at the interface with public policy as a basis for organized policy decisions, to meet time sensitive goals, and to inform the public.
Sea level rise and the anthropogenic warming of the world’s oceans is not only an environmental tragedy, but these changes also result in a significant threat to public health. Along with coastal flooding and the encroachment of saltwater farther inland comes an increased risk of human interaction with pathogenic Vibrio species, such as Vibrio cholerae, V. vulnificus and V. parahaemolyticus. This minireview examines the current literature for updates on the climatic changes and practices that impact the location and duration of the presence of Vibrio spp., as well as the infection routes, trends and virulence factors of these highly successful pathogens. Finally, an overview of current treatments and methods for the mitigation of both oral and cutaneous exposures are presented.
National and international assessments have drawn attention to the substantial economic risks of climate change. The costs of climate-sensitive health outcomes responsive to meteorological or seasonal patterns are among the least studied of those risks. In this article we describe how cost valuation analyses that relate climate-sensitive health outcomes to damages in economic terms can illuminate the costs of inaction on the climate crisis and the economic savings of addressing this problem. We identify major challenges to expanding the application of climate-health valuation research and suggest solutions to overcome these obstacles to better characterize the burden of climate-sensitive health outcomes and health disparities. The projected health and economic harms of climate-sensitive risks could be enormous if climate change continues to accelerate and communities are not prepared to reduce or prevent their impact. Expanded valuation of climate-sensitive health outcomes can inform policies that slow climate change and promote stronger investments in health-protective climate change adaptation efforts.
When a disease outbreak occurs or there is increased threat for a disease outbreak to occur following a flooding disaster, it is important for government officials and mosquito abatement practitioners to know how to access federal financial, technical, or control activity assistance. In certain circumstances, the Federal Emergency Management Agency may provide reimbursement assistance to supplement state, territorial, tribal, or local governments’ extraordinary mosquito abatement activities in areas that have received an emergency or major disaster declaration under the Robert T. Stafford Disaster Relief and Emergency Assistance Act (Public Law 93-288). The Centers for Disease Control and Prevention are the lead federal agency after a disease outbreak occurs. Government officials and practitioners should know how to access available assistance before an event occurs. Building a plan to request federal assistance, coordination with stakeholders under the National Incident Management System, and documentation of steps taken are the most effective method to ensure a smooth community response while maximizing assistance and reimbursement from federal agencies.
The Research Action Team of Bridging Climate Change and Public Health investigated research related to climate sensitive public health hazards specific to Maricopa County, Arizona and the surrounding Southwest region. Examples of climate-sensitive public health hazards that are important for our area include extreme heat, poor air quality, vector-borne diseases, flooding, and dust storms. A review of the academic research literature revealed 102 relevant publications. Data were extracted from each study to identify gaps in research for potential future studies related to climate-sensitive public health hazards. The data extracted included study design, duration of the study, climate change outcomes, health outcomes, and Arizona county (county vs. All Arizona vs. Southwest). Studies were dated from 1950-2019, with the majority of research within Arizona happening in Maricopa County, Arizona. Heat and air quality are the climate change impacts that have dominated the literature for Arizona thus far. An intersection analysis of climate change impacts and health outcomes revealed these nine important gaps that represent opportunities for future research: 1) (built environment) AND (alternative ways of transportation) 2) (adaptation, mitigation, and interventions) AND (asthma and other respiratory illnesses) 3) (adaptation, mitigation, and interventions) AND (cardiovascular health) 4) (adaptation, mitigation, and interventions) AND (malnutrition) 5) (adaptation, mitigation, and interventions) AND (alternative ways of transportation) 6) (impacts of food supply) AND (malnutrition) 7) (occupational health) AND (asthma and other respiratory illnesses) 8) (occupational health) AND (Valley Fever) 9) (occupational health) AND (cardiovascular health)
In 2010, the American Heart Association published a statement concluding that the existing scientific evidence was consistent with a causal relationship between exposure to fine particulate matter and cardiovascular morbidity and mortality, and that fine particulate matter exposure is a modifiable cardiovascular risk factor. Since the publication of that statement, evidence linking air pollution exposure to cardiovascular health has continued to accumulate and the biological processes underlying these effects have become better understood. This increasingly persuasive evidence necessitates policies to reduce harmful exposures and the need to act even as the scientific evidence base continues to evolve. Policy options to mitigate the adverse health impacts of air pollutants must include the reduction of emissions through action on air quality, vehicle emissions, and renewable portfolio standards, taking into account racial, ethnic, and economic inequality in air pollutant exposure. Policy interventions to improve air quality can also be in alignment with policies that benefit community and transportation infrastructure, sustainable food systems, reduction in climate forcing agents, and reduction in wildfires. The health care sector has a leadership role in adopting policies to contribute to improved environmental air quality as well. There is also potentially significant private sector leadership and industry innovation occurring in the absence of and in addition to public policy action, demonstrating the important role of public-private partnerships. In addition to supporting education and research in this area, the American Heart Association has an important leadership role to encourage and support public policies, private sector innovation, and public-private partnerships to reduce the adverse impact of air pollution on current and future cardiovascular health in the United States.
Wildfire smoke is an increasing environmental health threat to which children are particularly vulnerable, for both physiologic and behavioral reasons. To address the need for improved public health messaging this review summarizes current knowledge and knowledge gaps in the health effects of wildfire smoke in children, as well as tools for public health response aimed at children, including consideration of low-cost sensor data, respirators, and exposures in school environments. There is an established literature of health effects in children from components of ambient air pollution, which are also present in wildfire smoke, and an emerging literature on the effects of wildfire smoke, particularly for respiratory outcomes. Low-cost particulate sensors demonstrate the spatial variability of pollution, including wildfire smoke, where children live and play. Surgical masks and respirators can provide limited protection for children during wildfire events, with expected decreases of roughly 20% and 80% for surgical masks and N95 respirators, respectively. Schools should improve filtration to reduce exposure of our nation’s children to smoke during wildfire events. The evidence base described may help clinical and public health authorities provide accurate information to families to improve their decision making.
BACKGROUND AND OBJECTIVES: This review synthesizes the current literature surrounding chronic disease outcomes after weather- and climate-related disasters among older adults. The associations between exposure of older adults to weather- and climate-related disasters and the primary outcomes of diabetes, end-stage renal disease (ESRD), congestive heart failure (CHF), and chronic obstructive pulmonary disease (COPD) were examined. RESEARCH DESIGN AND METHODS: A systematic review of studies reporting on clinical outcomes of four chronic diseases after disaster exposure was performed. Under the direction of an informationist, the databases PubMed, Scopus, EMBASE, and Web of Science (Science and Social Science Citation Index) were searched from inception to July 2019. RESULTS: Of 5,229 citations identified, 17 articles met the study criteria. Included articles were retrospective observational in nature and focused on earthquakes (24%, n = 4), hurricane (41%, n = 7), and wildfire (35%, n = 6) disasters. Outcome data by disease process included COPD (35%, n = 6), ESRD (41%, n = 7), CHF (24%, n = 4), and diabetes (29%, n = 5). Three main categories were identified: access to health care, postdisaster health care utilization, and study rigor. The age-stratified analyses reported in this review found multiple instances where disasters have limited or insignificant effects on older adults relative to younger populations. DISCUSSION AND IMPLICATIONS: Disaster research faces unique methodological challenges, and there remains a need for data-driven conclusions on how best to care for older adults before, during, and after disasters. To encourage consistent dialogue among studies, we advocate for the use of rigorous and standardized scientific methodology to examine the health impacts of disasters on adults with chronic disease.
Climate change directly threatens human health, with substantial impacts on Indigenous peoples, who are uniquely vulnerable as climate-related events affect their practices, lifeways, self-determination, and physical and cultural health. At the same time, Indigenous communities are leading the way in innovative health-related climate change adaptation work, using traditional knowledges and novel approaches. In 2016 the Centers for Disease Control and Prevention and the National Indian Health Board created the Climate-Ready Tribes Initiative to support these efforts. The initiative has funded tribes, shared information nationally, and supported a learning cohort, resulting in pioneering work to protect health from climate hazards. We describe how two tribes-the Pala Band of Mission Indians and the Swinomish Indian Tribal Community-implemented their Climate-Ready Tribes Initiative projects, and we provide recommendations for making climate and health policy more effective for tribes. Lessons learned from the Climate-Ready Tribes Initiative can inform climate and health policy and practice nationwide.
A new generation of activists is calling for bold responses to the climate crisis. Although young people are motivated to act on climate issues, existing educational frameworks do not adequately prepare them by addressing the scope and complexity of the human health risks associated with climate change. We adapted the US government’s climate literacy principles to propose a definition and corresponding set of elements for a concept we term climate and health literacy. We conducted a scoping review to assess how the peer-reviewed literature addresses these elements. Our analysis reveals a focus on training health professionals; more international than US domestic content; and limited information about data and models, fossil fuels, and equity. We propose developing a framework that builds on the elements to support a broader educational agenda that prepares students and future leaders to recognize the complex health ramifications of a changing climate.
Wildfire smoke harms health. We add to this literature by evaluating the health effects of California’s 2018 Carr Fire and preceding wildfire seasons in Shasta County. METHODS: With data from the Shasta County Health and Human Services Agency, we examined the link between weekly wildfire fine particulate matter (PM(2.5)) exposure estimated using a spatiotemporal multiple imputation approach and emergency department (ED) visits and mortality using time-series models that controlled for temporal trends and temperature. RESULTS: Between 2013 and 2018, Shasta County experienced 19 weeks with average wildfire PM(2.5) ?5.5 ?g/m(3) (hereafter, “high wildfire PM(2.5) concentration”). Among all Shasta County Zip Code Tabulation Areas (ZCTAs; n = 36), we detected no association between high wildfire PM(2.5) concentrations and respiratory or circulatory disease-related ED visits or mortality. Subsequent analyses were confined to valley ZCTAs (n = 11, lower elevation, majority of population, worse air quality in general). In valley ZCTAs, high wildfire PM(2.5) was associated with a 14.6% (95% confidence interval [CI] = 4.2, 24.9) increase in same-week respiratory disease-related ED visits but no increase in the subsequent 2 weeks nor on circulatory disease-related mortality or ED visits or all-cause mortality. Two weeks after high wildfire PM(2.5) weeks, respiratory disease-related deaths decreased (-31.5%, 95% CI = -64.4, 1.5). The 2018 Carr Fire appeared to increase respiratory disease-related ED visits by 27.0% (95% CI = 4.0, 50.0) over expectation and possibly reduce circulatory disease-related deaths (-18.2%, 95% CI = -39.4, 2.9). CONCLUSIONS: As climate change fuels wildfire seasons, studies must continue to evaluate their health effects, particularly in highly exposed populations.
Indigenous communities are often on the front-lines of climate change, and for tribes such as the Pointe-au-Chien Indian Tribe (PACIT) that make their homes and livelihoods in the dynamic landscapes of Coastal Louisiana (USA), sea-level rise, subsidence, and land loss are very real reminders of why they must continue to hone their adaptive capacity that has evolved over many generations and continues to evolve as the pace of change quickens. PACIT members have an inherited wisdom about their surrounding environment and continue to build on that body of observational knowledge that is passed from generation to generation to sustain themselves in this dynamic landscape. This knowledge is woven through their culture and is sometimes referred to as traditional ecological knowledge (TEK). The PACIT and other Indigenous communities around the world are using creative strategies to adapt to the impacts of climate change that include partnering with researchers to combine their TEK with science in approaches to enhance strategies dealing with climate change impacts, mitigation, and adaptation. Tribes and other Indigenous communities often have a strong connection to place that helps to inspire innovative ideas to promote greater sustainability of vulnerable ecosystems and the communities that depend on them, but not the institutional support to implement them. Overcoming this barrier requires a better understanding of their perception of the issues and what they prioritize in sustaining their cultures and the ecosystems on which they depend. Better inclusion of their knowledge into applied research is necessary to support these communities in their efforts to make sure their knowledge is recognized, understood, and valued in environmental management applications. The primary goal for this study was to develop a decision-support tool that aids the PACIT in assessing local ecological change and associated risks to the Tribe’s resilience. Using remote sensing datasets and geographic information systems (GIS) processes to represent aspects of the Tribe’s TEK to achieve this goal, we developed methods for producing interactive maps that reflect local perceptions of landscape features within the Tribe’s ecosystem-dependent livelihood base that contribute most to the community’s physical vulnerability to coastal hazards. This case study is offered to consider how Indigenous communities like the PACIT are shaping their own coastal hazards mitigation planning efforts in line with their unique needs, cultural practices, and values. The results of this study can provide relevant insight to applied environmental scientists and others working with Indigenous communities that are facing similar circumstances around the world.
Heat-related mortality is one of the leading causes of weather-related deaths in the United States. With changing climates and an aging population, effective adaptive strategies to address public health and environmental justice issues associated with extreme heat will be increasingly important. One effective adaptive strategy for reducing heat-related mortality is increasing tree cover. Designing such a strategy requires decision-support tools that provide spatial and temporal information about impacts. We apply such a tool to estimate spatially and temporally explicit reductions in temperature and mortality associated with a 10% increase in tree cover in 10 U.S. cities with varying climatic, demographic, and land cover conditions. Two heat metrics were applied to represent tree impacts on moderately and extremely hot days (relative to historical conditions). Increasing tree cover by 10% reduced estimated heat-related mortality in cities significantly, with total impacts generally greatest in the most populated cities. Mortality reductions vary widely across cities, ranging from approximately 50 fewer deaths in Salt Lake City to about 3800 fewer deaths in New York City. This variation is due to differences in demographics, land cover, and local climatic conditions. In terms of per capita estimated impacts, hotter and drier cities experience higher percentage reductions in mortality due to increased tree cover across the season. Phoenix potentially benefits the most from increased tree cover, with an estimated 22% reduction in mortality from baseline levels. In cooler cities such as Minneapolis, trees can reduce mortality significantly on days that are extremely hot relative to historical conditions and therefore help mitigate impacts during heat wave conditions. Recent studies project highest increases in heat-related mortality in the cooler cities, so our findings have important implications for adaptation planning. Our estimated spatial and temporal distributions of mortality reductions for each city provide crucial information needed for promoting environmental justice and equity. More broadly, the methods and model can be applied by both urban planners and the public health community for designing targeted, effective policies to reduce heat-related mortality. Additionally, land use managers can use this information to optimize tree plantings. Public stakeholders can also use these impact estimates for advocacy.
The urban heat island is a representative urban climate characteristic, which can affect heat-stress conditions and extreme precipitation that are closely connected with human life. Better understanding of urban-climate interactions, therefore, is crucial to ultimately support better planning and adaptation in various application fields. This study assesses urban-climate interactions during summer for eastern North America using regional climate model simulations at 0.22° resolution. Two regional climate model experiments, with and without realistic representation of urban regions, are performed for the 1981–2010 period. Comparison of the two experiments shows higher mean temperatures and reduced mean precipitation in the simulation with realistic urban representation, which can be attributed primarily to reduced albedo and soil moisture for the urban regions in this simulation. Furthermore, the mean temperature and precipitation in the simulation with improved urban representation is also closer to that observed. Analysis of short-duration precipitation extremes for climatologically different sub-regions, however, suggests that, for higher temperatures, the magnitudes of precipitation extremes are generally higher in the simulation with realistic urban representation, particularly for coastal urban regions, and are collocated with higher values of convective available potential energy and cloud fraction. Enhanced sea and lake breezes associated with lower sea level pressure found around these regions, contribute additional water vapor and further enhance dynamic convective development, leading to higher precipitation intensities. Analysis of temperature extremes clearly demonstrates that urban regions experience aggravated heat-stress conditions due to relatively higher temperatures despite reduced relative humidity. Double the number of extreme heat spells lasting six or more days are noted for the coastal urban regions in the study domain. This study, in addition to demonstrating the differences in urban-climate interactions for climatologically different regions, also demonstrates the need for better representation of urban regions in climate models to generate realistic climate information.
OBJECTIVES: Climate variables are implied in the pathogenesis of certain otologic diseases, including benign paroxysmal positional vertigo (BPPV). Using internet search data obtained through Google Trends (GT), we explored the relationship between climate patterns and symptom search frequencies for BPPV. We hypothesized that increased latitude, as a proxy for decreased sunlight exposure, would lead to increase in BPPV symptom searches. METHODS: GT searches for symptoms related to BPPV were obtained for five U.S. cities of different latitudes via the Google Trends online interface. Comparisons were made using SPSS via ANOVA analysis. Figures were made using Microsoft Excel. RESULTS: Searches for BPPV-related symptoms increased with increasing latitude. BPPV-related symptoms did show seasonal variations, but not in predictable manners. CONCLUSIONS: GT may be a viable research tool when comparing geographical differences in searches, but may be less sensitive in detecting time dependent changes. We offer suggestions as to how big data tools may be altered for research purposes. LEVEL OF EVIDENCE: NA.
PURPOSE: The incidence of urinary tract infections is seasonal, peaking in summer months. One possible mechanism for the observed seasonality of urinary tract infections is warmer weather. MATERIALS AND METHODS: We identified all urinary tract infection cases located in approximately 400 metropolitan statistical areas in the contiguous United States between 2001 and 2015 using the Truven Health MarketScan® databases. A total of 167,078,882 person-years were included in this data set and a total of 15,876,030 urinary tract infection events were identified by ICD-9 code 599.0. Weather data for each metropolitan statistical area and date were obtained from the National Centers for Environmental Information. We computed the mean temperature during the period 0 to 7 days prior to the urinary tract infection diagnosis. We used a quasi-Poisson generalized linear model. The primary outcome was the number of urinary tract infections each day in a metropolitan statistical area in each age group. Covariates considered included age group, day of week, year and the temperature during the previous 7 days. RESULTS: Warmer weather increases the risk of urinary tract infections among women treated in outpatient settings in a dose-response fashion. On days when the prior week’s average temperature was between 25 and 30C, the incidence of urinary tract infections was increased by 20% to 30% relative to when the prior week’s temperature was 5 to 7.5C. CONCLUSIONS: The incidence of urinary tract infections increases with the prior week’s temperature. Our results indicate that warmer weather is a risk factor for urinary tract infections. Furthermore, as temperatures rise, the morbidity attributable to urinary tract infections may increase.
After a disaster, it is common to equate repopulation and rebuilding with recovery. Numerous studies link post-disaster relocation to adverse social, economic, and health outcomes. However, there is a need to reconsider these relationships in light of accelerating climate change and associated social and policy shifts in the USA, including the rising cost of flood insurance, the challenge of obtaining aid to rebuild, and growing interest in “managed retreat” from places at greatest risk. This article presents data from a survey of individuals who opted either to rebuild in place or relocate with the help of a voluntary home buyout after Hurricane Sandy. Findings show those who lived in buyout-eligible areas and relocated were significantly less likely to report worsened stress than those who rebuilt in place. This suggests access to a government-supported voluntary relocation option may, under certain circumstances, lessen the negative mental health consequences associated with disaster-related housing damage.
The 2018 Camp Fire caused significant damages to the education and healthcare systems in the town of Paradise, CA. This paper presents the findings of a qualitative case study about disaster impacts and disparities, interdependencies, and recovery strategies of schools and hospitals in Paradise. Four major themes of findings emerged from the qualitative analysis of interviews with teachers, counselors, and administrators in Paradise education and healthcare systems and extensive archival research. First, complex and long-standing mental health challenges are the dominant impact on the educational system. Second, educational and healthcare impacts are shaped by social vulnerability. Third, educational and healthcare systems play a critical role for recovery of socially vulnerable groups due to the interconnectedness of community components. Fourth, adapting to new communication norms and technologies is effective for supporting educational and community recovery. Several specific recommendations are provided based on the findings for building back more resilient and equitable education and healthcare services.
Climate change will necessitate evermore frequent and complex managed retreats in the future, and drafting policies that are equitable and just for those residents who are relocating will be essential. The USA’s first federally funded, community-scale, climate-driven resettlement is currently underway in coastal Louisiana. In January 2016, the U.S. Department of Housing and Urban Development (HUD) awarded the state of Louisiana $48.3 million to plan, design, and implement a structured, just, and scalable resettlement with former and current Isle de Jean Charles residents. Most Island households are multi-generational and directly descended from Jean Marie Naquin, after whose father the Island is named. Using interviews, ethnographic data, and policy documents, this paper will delineate and analyze the dimensions of sense of place, which, in this case, prompted policy changes dramatically different from standard relocation policies: assurance that the properties and land from which residents are departing will remain in their possession as long as the land remains. For most Island residents, this was non-negotiable. The intangible connection to place-feelings of belonging, lifestyle, family connections, and culture-plays a central role in many families’ decision to stay or go. The choice to relocate is rooted in this complex entanglement of identity, familial ties, land loss, historical and current marginalization, and a way of life passed on by multiple generations. In forthcoming community resettlements, continued access and ownership of the properties being left behind should be considered as a critical component for planning just retreats.
Compositional and contextual characteristics of a place capture the collective fnancial, physical, human, and social capital of an area and its ability to prevent, plan for, and recover from severe weather events. Research that examines the compositional and contextual characteristics of places with elevated food risk is largely limited to urban-centric analyses and case studies. However, rural areas of the USA are not immune to fooding. In this paper, we integrate social and physical data to identify the social correlates of food risk and determine if and how they vary across the rural–urban continuum for all census tracts in the coterminous USA. Our results show that risk of fooding is higher in rural tracts, in tracts with larger relative shares of socioeconomically vulnerable populations, and in tracts reliant on food-vulnerable industries. We also show that compositional social correlates of fooding are not consistent across rural–urban areas. This work widens the scope of discourse on fooding to attend to the heterogeneity of social correlates and the implications for policy and future research.
BACKGROUND: Ambient temperature observations from single monitoring stations (usually located at the major international airport serving a city) are routinely used to estimate heat exposures in epidemiologic studies. This method of exposure assessment does not account for potential spatial variability in ambient temperature. In environmental health research, there is increasing interest in utilizing spatially-resolved exposure estimates to minimize exposure measurement error. METHODS: We conducted time-series analyses to investigate short-term associations between daily temperature metrics and emergency department (ED) visits for well-established heat-related morbidities in five US cities that represent different climatic regions: Atlanta, Los Angeles, Phoenix, Salt Lake City, and San Francisco. In addition to airport monitoring stations, we derived several exposure estimates for each city using a national meteorology data product (Daymet) available at 1?km spatial resolution. RESULTS: Across cities, we found positive associations between same-day temperature (maximum or minimum) and ED visits for heat-sensitive outcomes, including acute renal injury and fluid and electrolyte imbalance. We also found that exposure assessment methods accounting for spatial variability in temperature and at-risk population size often resulted in stronger relative risk estimates compared to the use of observations at airports. This pattern was most apparent when examining daily minimum temperature and in cities where the major airport is located further away from the urban center. CONCLUSION: Epidemiologic studies based on single monitoring stations may underestimate the effect of temperature on morbidity when the station is less representative of the exposure of the at-risk population.
PURPOSE: Millions of workers exposed to the outdoor environment are extremely susceptible to extreme heat. Although several articles analyzed heat-related illnesses, injuries, fatalities at the country level, few investigated regional and state statistics especially for OSHA Region 4 and the state of Alabama, U.S, which we explored in this study. METHODS: We studied the number of heat-days over 90 °F (32.2 °C) heat-index within our study area, analyzed heat-related injury and illnesses to calculate their incidence rate during 2015 to 2019, observed the nature of such incidents, their monthly occurrence, and incidence trend over average air temperature. We conducted a comparative analysis of heat-related fatalities between construction and all industries. The existing heat regulations by OSHA and some state agencies have also been summarized. RESULTS: We observed the highest mean, maximum heat-days and injury-illness rate in the south and southeast part of Region 4; increase in incidence rate from 0.03 in 2017 to 0.28 per 10,000 employees in 2018 for the contiguous U.S; highest injury-illness rate (HIR) in OSHA Region 1, 4 and 6; highest HIR in Lee, Montgomery, Mobile and Madison counties of Alabama; 34.7% (construction) and 31.3% (all industries) of all cases experiencing nonclassifiable heat-light effects; high fatalities in construction industry with a trend of 1 death/5 years; increased mortality in all occupations with 1 death/2.4 years. We also proposed a Heat-Stress Index (HSI) as a routine heat-stress measure on jobsite. CONCLUSION: The findings from this research and the proposed index can help in understanding heat-related risk at a regional level and implementing workplace interventions.
People experiencing homelessness (PEH) face extreme weather exposure and limited social support. However, few studies have empirically assessed biophysical and social drivers of health outcomes among unsheltered PEH. Social network, health, and outdoor exposure data were collected from a convenience sample of unsheltered PEH (n = 246) in Nashville, TN, from August 2018-June 2019. Using multivariate fixed-effects linear regression models, we examined associations between biophysical and social environments and self-reported general health and emotional well-being. We found that study participants reported the lowest general health scores during winter months-Nashville’s coldest season. We also found a positive association between the number of nights participants spent indoors during the previous week and general health. Participants who spent even one night indoors during the past week had 1.8-point higher general health scores than participants who spent zero nights indoors (p < 0.01). Additionally, participants who experienced a conflict with a social contact in the past 30 days had lower emotional well-being scores than participants who experienced no conflict. Finally, women had worse general health and emotional well-being than men. Ecologically framed research about health and well-being among PEH is critically needed, especially as climate change threatens to increase the danger of many homeless environments.
As climate change increases the frequency and severity of disasters, and population and social changes raise the public’s vulnerability to disaster events, societies face additional risk of multiple disaster events or other hazards occurring simultaneously. Such hazards involve significant uncertainty, which must be translated into concrete plans able to be implemented by disaster workers. Little research has explored how disaster managers incorporate different forms of knowledge and uncertainty into preparations for simultaneous hazards or disaster events, or how front-line disaster workers respond to and implement these plans. In this paper I draw on ethnographic research working as a wildland firefighter, interviews with firefighters and fire managers, and state and agency planning documents to examine preparations for two events occurring in Central Oregon in August 2017: (1) the height of wildfire season and (2) hundreds of thousands of anticipated visitors for a total solar eclipse. I find that different qualities of risk, hazard, and uncertainty across these two events were central to the development and implementation of disaster plans. Agency leaders devised worst-case scenario plans for the eclipse based on uncertain predictions regarding hazards from the eclipse and the occurrence of severe wildfires, aiming to eliminate the potential for unknown hazards. These plans were generally met with skepticism by front-line disaster workers. Despite the uncertainties that dominated eclipse-planning rhetoric, firefighters largely identified risks from the eclipse that were risks they dealt with in their daily work as firefighters. I conclude by discussing implications of these findings for conceptual understandings of disaster planning as well as contemporary concerns about skepticism and conspiracy theories directed at government planning and response to disaster events.
Many cities aim to progress toward their sustainability and public health goals by increasing use of their public transit systems. However, without adequate protective infrastructure that provides thermally comfortable conditions for public transit riders, it can be challenging to reach these goals in hot climates. We took micrometeorological measurements and surveyed riders about their perceptions of heat and heat-coping behaviors at bus stops with a variety of design attributes in Phoenix, AZ, USA, during the summer of 2018. We identified the design attributes and coping behaviors that made riders feel cooler. We observed that current infrastructure standards and material choices for bus stops in Phoenix are insufficient to provide thermal comfort, and can even expose riders to health risks. Almost half of the study participants felt hot or very hot at the time they were surveyed, and more than half reported feeling thermally uncomfortable. On average, shade reduced the physiological equivalent temperature (PET) by 19 °C. Moreover, we found significant diurnal differences in PET reductions from the shade provided by various design attributes. For instance, all design attributes were effective in reducing PET in the morning; however, a vegetated awning did not provide statistically significant shade reductions in the afternoon. Temperatures of sun-exposed surfaces of man-made materials exceeded skin burn thresholds in the afternoon, but shade was effective in bringing the same surfaces to safe levels. Aesthetically pleasing stops were rated as cooler than stops rated as less beautiful. We conclude that cities striving to increase public transit use should prioritize thermal comfort when designing public transit stops in hot climates.
In recent years, the frequency, intensity, and severity of wildfires have been on the rise due to various environmental factors. Several studies show that the strategic application of fuel treatments is effective at altering fire behavior and its spread patterns. Effective planning for mitigating future expected losses under wildfire risk is a complex challenge that requires the integration of fire spread, simulation, and optimization models as well as the inclusion of multiple objectives into a unified framework. Previous works simplify the analysis by valuing the landscape regions using a unique objective (e.g., minimize the average expected area burned) or a predefined objective function. However, such an assumption is a simplification of the real system as multiple parts of the landscape have different values based on factors such as the presence of human settlements and infrastructure, availability of environmental services, and forest health. In this work, we expand these previous attempts by providing an integrated framework to naturally include and weight multiple objectives into the optimization model and analyze the trade-off between present objectives and future protection against wildfire risk. We study three key regions based on their recent fire history, landscape diversity, and demographic variety to quantify the impact of multiple objectives in landscape management. We obtain treatment plans using various combinations of these layers reflecting how different priorities of the decision-makers could affect treatment policies.
Household flooding has wide ranging social, economic and public health impacts particularly for people in resource poor communities. The determinants and public health outcomes of recurrent home flooding in urban contexts, however, are not well understood. A household survey was used to assess neighborhood and household level determinants of recurrent home flooding in Detroit, MI. Survey activities were conducted from 2012 to 2020. Researchers collected information on past flooding, housing conditions and public health outcomes. Using the locations of homes, a “hot spot” analysis of flooding was performed to find areas of high and low risk. Survey data were linked to environmental and neighborhood data and associations were tested using regression methods. 4803 households participated in the survey. Flooding information was available for 3842 homes. Among these, 2085 (54.26%) reported experiencing pluvial flooding. Rental occupied units were more likely to report flooding than owner occupied homes (Odd ratio (OR) 1.72 [95% Confidence interval (CI) 1.49, 1.98]). Housing conditions such as poor roof quality and cracks in basement walls influenced home flooding risk. Homes located in census tracts with increased percentages of owner occupied units (vs. rentals) had a lower odds of flooding (OR 0.92 [95% (CI) 0.86, 0.98]). Household factors were found the be more predictive of flooding than neighborhood factors in both univariate and multivariate analyses. Flooding and housing conditions associated with home flooding were associated with asthma cases. Recurrent home flooding is far more prevalent than previously thought. Programs that support recovery and which focus on home improvement to prevent flooding, particularly by landlords, might benefit the public health. These results draw awareness and urgency to problems of urban flooding and public health in other areas of the country confronting the compounding challenges of aging infrastructure, disinvestment and climate change.
We analyzed two historical extreme heat events in Los Angeles to explore the potential of increasing vegetative cover and surface solar reflectance (albedo) to reduce total exposure (indoor and outdoor) to dangerously hot conditions. We focus on three population subgroups, the elderly, office workers, and outdoor workers, and explore the extreme case where each subgroup does not have functioning air conditioning in their residences. For each heat event, we conducted atmospheric model simulations for a control case and four mitigation cases with varying levels of increased albedo and vegetation cover. Simultaneously, we conducted building simulations of representative residential buildings that lacked mechanical air conditioning. These simulations factored in both the indirect cooling effects associated with neighborhood implementation of mitigation strategies and the direct effects of high albedo roofing on the individual buildings. From both the atmospheric and building models, we exported hourly values of air temperature and dew point temperature, and used this information in combination with various scenarios of occupant behavior to create profiles of individual heat exposure. We also gathered heat-mortality data for the two heat events and developed a synoptic climatology-based relationship between exposure and excess mortality. This relationship was then applied to the scenarios in which albedo and canopy cover were increased. The results suggest that improvements in indoor thermal conditions are responsible for a sizable portion of the health benefit of large-scale implementation of heat mitigation strategies.
Individuals around the world believe global climate change is a major threat, with media attention and polling suggesting young adults may decide to go childfree as a result. Yet, there is limited research on the link between environmental concern and reproductive attitudes. The purpose of this research was to explore how climate change-related concerns affect reproductive attitudes and motivations to remain childfree. Two studies were conducted: study 1 consisted of a content analysis of reader comments on articles discussing going childfree in response to climate change, and study 2 featured semi-structured interviews conducted in New Zealand and the USA. The impact of future children on the planet, in the context of overpopulation and overconsumption, was a major theme in both studies. Perspectives of doom and hope emerged simultaneously, indicating how climate anxiety influences reproductive attitudes. Study findings point at implications for public policy makers regarding this largely neglected perspective on climate change adaptation and mitigation and potential psychological and societal effects.
A more precise understanding of individual-level heat exposure may be helpful to advance knowledge about heat-health impacts and effective intervention strategies, especially in light of projected increases in the severity and frequency of extreme heat events. We developed and interrogated different metrics for quantifying personal heat exposure and explored their association with social risk factors. To do so, we collected simultaneous personal heat exposure data from 64 residents of metropolitan Phoenix, Arizona. From these data, we derived five exposure metrics: Mean Individually Experienced Temperature (IET), Maximum IET, Longest Exposure Period (LEP), Percentage Minutes Above Threshold (PMAT), and Degree Minutes Above Threshold (DMAT), and calculated each for Day Hours, Night Hours, and All Hours of the study period. We then calculated effect sizes for the associations between those metrics and four social risk factors: neighborhood vulnerability, income, home cooling type, and time spent outside. We also investigated exposure misclassification by constructing linear regression models of observations from a regional weather station and hourly IET for each participant. Our analysis revealed that metric choice and timeframe added depth and nuance to our understanding of differences in exposure within and between populations. We found that time spent outside and income were the two risk factors most strongly associated with personal heat exposure. We also found evidence that Mean IET is a good, but perhaps not optimal, measure for assessing group differences in exposure. Most participants’ IETs were poorly correlated with regional weather station observations and the slope and correlation coefficient for linear regression models between regional weather station data and IETs varied widely among participants. We recommend continued efforts to investigate personal heat exposure, especially in combination with physiological indicators, to improve our understanding of links between ambient temperatures, social risk factors, and health outcomes.
A large and growing segment of the United States population resides in nursing homes. Many nursing home residents have multiple comorbidities, are unable to perform activities of daily living, and need assistance for their daily functioning. They are some of the most fragile and vulnerable members of the population. Disasters are increasing in frequency and severity. This makes it likely that disasters will strike nursing homes and affect their residents. The purpose of this study was to evaluate the characteristics of disasters in the United States that resulted in nursing home evacuations. There were 51 reported nursing home evacuations due to a disaster over 22.5 years between 1995 and 2017. Natural disasters were responsible for the majority of evacuations (58.8 percent) followed by man-made unintentional disasters (37.3 percent) and man-made intentional (arson) (3.9 percent). The single most common reason for evacuation was hurricanes (23.5 percent, N = 12) and internal fires (23.5 percent, N = 12). Water-related disasters accounted for nearly three-fourths of the natural disasters (hurricanes 40 percent, N = 12; floods, 33.3 percent, N = 10; total 73.3 percent, N = 22), then snow/ice storms (13.3 percent, N = 4). Of man-made disasters, over two-thirds (66.7 percent) were due to internal fires (internal fires, n = 12, 57.1 percent and arson n = 2, 9.5 percent; total N = 14, 66.7 percent). The highest number of evacuations occurred in Texas, Louisiana, Missouri, New York, and Pennsylvania. This knowledge should enable nursing home administrators, disaster planners, public health officials, and others to improve preparedness for disasters that lead to nursing home evacuations.
The California state government put restrictions on outdoor residential water use, including landscape irrigation, during the 2012-2016 drought. The public health implications of these actions are largely unknown, particularly with respect to mosquito-borne disease transmission. While residential irrigation facilitates persistence of mosquitoes by increasing the availability of standing water, few studies have investigated its effects on vector abundance. In two study sub-regions in the Los Angeles Basin, we examined the effect of outdoor residential water use restrictions on the abundance of the most important regional West Nile virus vector, Culex quinquefasciatus. Using spatiotemporal random forest models fit to Cx. abundance during drought and non-drought years, we generated counterfactual estimates of Cx. abundance under a hypothetical drought scenario without water use restrictions. We estimate that Cx. abundance would have been 44% and 39% larger in West Los Angeles and Orange counties, respectively, if outdoor water usage had remained unchanged. Our results suggest that drought, without mandatory water use restrictions, may counterintuitively increase the availability of larval habitats for vectors in naturally dry, highly irrigated settings and such mandatory water use restrictions may constrain Cx. abundance, which could reduce the risk of mosquito-borne disease while helping urban utilities maintain adequate water supplies.
Despite perceptions of high water availability, adequate access to sufficient water resources remains a major challenge in Alaska. This paper uses a participatory modeling approach to investigate household water vulnerability in remote Alaska and to examine factors that affect water availability and water access. Specifically, the work asks: how do water policy stakeholders conceptualize the key processes that affect household water vulnerability in the context of rural Alaska? Fourteen water policy stakeholders participated in the modeling process, which included defining the problem of household water vulnerability and constructing individual causal loop diagrams (CLDs) that represent their conceptualization of household water vulnerability. Individual CLDs were subsequently combined and five sub-models emerged: environmental, economic, infrastructure, social, and health. The environmental and economic sub-models of the CLD are explored in depth. In the environmental sub-model, climate change and environmental barriers due to geography influence household water vulnerability. In the economic sub-model, four processes and one feedback loop affect household water vulnerability, including operations and maintenance funding, the strength of the rural Alaskan economy, and the impact of regulations. To overcome household water vulnerability and make households more resilient, stakeholders highlighted policy solutions under five themes: economics, social, regulatory, technological, and environmental.
Climate risk is a consequence of climate hazards, exposure, and the vulnerability (IPCC 2014). Here, we assess future (2040-2049) climate risk for the entire contiguous US at the county level with a novel climate risk index integrating multiple hazards, exposures and vulnerabilities. Future, weather and climate hazards are characterized as frequency of heat wave, cold spells, dryer, and heavy precipitation events along with anomalies of temperature and precipitation using high resolution (4 km) downscaled climate projections. Exposure is characterized by projections of population, infrastructure, and built surfaces prone to multiple hazards including sea level rise and storm surges. Vulnerability is characterized by projections of demographic groups most sensitive to climate hazards. We found Florida, California, the central Gulf Coast, and North Atlantic at high climate risk in the future. However, the contributions to this risk vary regionally. Florida is projected to be equally hard hit by the three components of climate risk. The coastal counties in the Gulf states of Louisiana, Texas, Mississippi and Alabama are at high climate risk due to high exposure and hazard. High exposure and vulnerability drive high climate risk in California counties. This approach can guide planners in targeting counties at most risk and where adaptation strategies to reduce exposure or protect vulnerable populations might be best applied.
People experiencing homelessness during the 2017-2018 California wildfires faced significant risks of disruption. Homeless service organizations (HSOs) are an essential safety net for this population. To learn about how HSOs performed during the wildfires, this study interviewed U.S. Department of Veterans Affairs (VA) staff overseeing HSOs providing transitional housing under the VA’s Grant and Per Diem (GPD) program to Veterans experiencing homelessness. We employed a comparative case study approach exploring GPD organizations’ disaster response actions, including evacuating Veterans from wildfire-affected areas or taking in disaster-displaced Veterans. This article presents three themes in the GPD organizations’ disaster response: (1) Organizations benefitted from close collaboration and communication with the VA during the disaster, creating a safety net to ensure Veterans’ well-being and enact rapid re-housing to prevent homelessness; (2) Organization staff performed heroically under stressful disaster conditions; and (3) Organizations benefitted from the written disaster plans that VA requires them to create, but were not as well-prepared for wildfires as they had been for earthquakes. As emergent threats such as the COVID-19 pandemic, wildfires, and a very active 2020 hurricane season amplify the importance of mitigating risks, comprehensive disaster planning is needed to ensure the safety and support of people experiencing homelessness.
Livability, resilience, and justice in cities are challenged by climate change and the historical legacies that together create disproportionate impacts on human communities. Urban green infrastructure has emerged as an important tool for climate change adaptation and resilience given their capacity to provide ecosystem services such as local temperature regulation, stormwater mitigation, and air purification. However, realizing the benefits of ecosystem services for climate adaptation depend on where they are locally supplied. Few studies have examined the potential spatial mismatches in supply and demand of urban ecosystem services, and even fewer have examined supply-demand mismatches as a potential environmental justice issue, such as when supply-demand mismatches disproportionately overlap with certain socio-demographic groups. We spatially analyzed demand for ecosystem services relevant for climate change adaptation and combined results with recent analysis of the supply of ecosystem services in New York City (NYC). By quantifying the relative mismatch between supply and demand of ecosystem services across the city we were able to identify spatial hot- and coldspots of supply-demand mismatch. Hotspots are spatial clusters of census blocks with a higher mismatch and coldspots are clusters with lower mismatch values than their surrounding blocks. The distribution of mismatch hot- and coldspots was then compared to the spatial distribution of socio-demographic groups. Results reveal distributional environmental injustice of access to the climate-regulating benefits of ecosystem services provided by urban green infrastructure in NYC. Analyses show that areas with lower supply-demand mismatch tend to be populated by a larger proportion of white residents with higher median incomes, and areas with high mismatch values have lower incomes and a higher proportion of people of color. We suggest that urban policy and planning should ensure that investments in “nature-based” solutions such as through urban green infrastructure for climate change adaptation do not reinforce or exacerbate potentially existing environmental injustices.
The study of the relationships between freshwater organisms, pollution and public awareness has been little researched. The public’s perception of risk from pollution is a fundamental component in determining consumer behavior and promoting healthy habits. For instance, understanding how consumers perceive the risks associated with pollution can help with adoption of safe behaviors to reduce the health hazard associated with pollutant exposure. This study focused on the southeastern United States, a region predicted to be exposed to high mercury stress by increasing mercury deposition and methylation. First, we placed our study region in the world map of regions more prone to suffer from increasing mercury stress in a climate change scenario. Second, mercury levels in fish tissues was quantified by direct mercury analyzer (DMA). Third, we explored human fish consumption habits and risk social perception, including willingness to adapt fish consumption based on two future hypothetical scenarios of mercury stress. From a global perspective, our analysis demonstrates that the southern US is one of five world areas of greatest conservation concern for mercury stress. In this region, the average mono-methyl mercury concentration in fish tissues exceeded the limits considered safe for human consumption. Even though many in the local population were aware of the health hazards associated with fish consumption, only women of reproductive age were willing to adopt safe consumption habits. Altogether, these results show how bringing together field data, social perceptions, and consumption habits can help in designing an adaptive strategy to confront mercury pollution. Although our results are for the United States, other world regions prone to suffer increasing mercury stress have been identified and should be the focus of future studies and prescriptions.
Background This study aimed to assess inpatient prevalence, characteristics, outcomes, and resource utilisation of hospitalisation for heatstroke in the United States. Additionally, this study aimed to explore factors associated with in-hospital mortalities of heatstroke. Methods The 2003-2014 National Inpatient Sample database was used to identify hospitalised patients with a principal diagnosis of heatstroke. The inpatient prevalence, clinical characteristics, in-hospital treatments, outcomes, length of hospital stay, and hospitalisation cost were studied. Multivariable logistic regression was performed to identify independent factors associated with in-hospital mortality. Results A total of 3372 patients were primarily admitted for heatstroke, accounting for an overall inpatient prevalence of heatstroke amongst hospitalised patients of 36.3 cases per 1 000 000 admissions in the United States with an increasing trend during the study period (P < .001). Age 40-59 was the most prevalent age group. During the hospital stay, 20% required mechanical ventilation, and 2% received renal replacement therapy. Rhabdomyolysis was the most common complication. Renal failure was the most common end-organ failure, followed by neurological, respiratory, metabolic, hematologic, circulatory, and liver systems. The in-hospital mortality rate of heatstroke hospitalisation was 5% with a decreasing trend during the study period (P < .001). The presence of end-organ failure was associated with increased in-hospital mortality, whereas more recent years of hospitalisation was associated with decreased in-hospital mortality. The median length of hospital stay was 2 days. The median hospitalisation cost was $17 372. Conclusion The inpatient prevalence of heatstroke in the United States increased, while the in-hospital mortality of heatstroke decreased.
Cities are experiencing more and more frequent extreme heat events in hot summers in the context of rising global temperatures. A precise understanding of the spatial distribution of the human outdoor heat exposure across neighborhoods in cities is of great importance for urban heat management. Different from remote sensing based the land surface temperature, this study calculated the mean radiant temperature, which is more objective to indicate human heat stress, to study the spatial distribution of human outdoor heat exposure in Philadelphia, Pennsylvania. The SOLWEIG (SOlar and LongWave Environmental Irradiance Geometry) model was applied to estimate the mean radiant temperature based on the high-resolution urban 3D model and meteorological data. This study further examined the spatial distributions of heat exposure levels across neighborhoods of different groups in Philadelphia. Results show that there is no significant disparity in terms of outdoor heat exposure levels for different racial/ethnic groups in Philadelphia. Generally, the elderly, who usually are more vulnerable to extreme heat, tend to live in neighborhoods with less outdoor heat exposure in summer (p<0.001). The higherincome people tend to live in thermally more comfortable neighborhoods (p<0.001). The study provides a precise understanding of the heat distribution across neighborhoods, which would further help to develop strategies to allocate resources to the most needed neighborhoods to maximumly mitigate the negative impact of urban heat.
Although aflatoxin (AF) exposure has not been recognized as a major problem in the United States and other developed nations, recent global climate change may have a profound impact on distribution of toxigenic fungi growth and production of AFs in grain and groundnuts. Alterations in the contamination pattern can increase human dietary exposure, and further invoke public health concerns and associated disease risks. In this study, two populations from East and West Texas, known for their high risk of liver cancer, were examined for their AF exposure at three different time periods from 2004 to 2014. Serum samples (n = 1124) were collected from participants recruited for various studies from Bexar County and Lubbock County, TX, over the span of 2004 through 2014. The exposure biomarker, serum AFB(1)-lysine adduct, was analyzed by HPLC-FLD and confirmed by LC-MS. Both populations showed a significant increase in detection rate, as well as median levels of serum AFB(1)-lysine adduct over time, from 2.35 to 4.34 pg/mg albumin in East Texas (2007-2014), and 0.63-3.98 pg/mg albumin in West Texas (2004-2010). This observed shift in exposure likely represents a shift in the AF contamination pattern in the State of Texas, and may warrant further studies on risk assessment for the potential etiological effects of such increased exposures.
Heat exposure of a population is often estimated by applying temperatures from outdoor monitoring stations. However, this can lead to exposure misclassification if residents do not live close to the monitoring station and temperature varies over small spatial scales due to land use/built environment variability, or if residents generally spend more time indoors than outdoors. Here, we compare summertime temperatures measured inside 145 homes in low-income households in Baltimore city with temperatures from the National Weather Service weather station in Baltimore. There is a large variation in indoor temperatures, with daily-mean indoor temperatures varying from 10 °C lower to 10 °C higher than outdoor temperatures. Furthermore, there is only a weak association between the indoor and outdoor temperatures across all houses, indicating that the outdoor temperature is not a good predictor of the indoor temperature for the residences sampled. It is shown that much of the variation is due to differences in the availability of air conditioning (AC). Houses with central AC are generally cooler than outdoors (median difference of -?3.4 °C) while those with no AC are generally warmer (median difference of 1.4 °C). For the collection of houses with central or room AC, there is essentially no relationship between indoor and outdoor temperatures, but for the subset of houses with no AC, there is a weak relationship (correlation coefficient of 0.36). The results presented here suggest future epidemiological studies of indoor exposure to heat would benefit from information on the availability of AC within the population.
Lyme disease is the most common vector-borne disease in temperate zones and a growing public health threat in the United States (US). The life cycles of the tick vectors and spirochete pathogen are highly sensitive to climate, but determining the impact of climate change on Lyme disease burden has been challenging due to the complex ecology of the disease and the presence of multiple, interacting drivers of transmission. Here we incorporated 18 years of annual, county-level Lyme disease case data in a panel data statistical model to investigate prior effects of climate variation on disease incidence while controlling for other putative drivers. We then used these climate-disease relationships to project Lyme disease cases using CMIP5 global climate models and two potential climate scenarios (RCP4.5 and RCP8.5). We find that interannual variation in Lyme disease incidence is associated with climate variation in all US regions encompassing the range of the primary vector species. In all regions, the climate predictors explained less of the variation in Lyme disease incidence than unobserved county-level heterogeneity, but the strongest climate-disease association detected was between warming annual temperatures and increasing incidence in the Northeast. Lyme disease projections indicate that cases in the Northeast will increase significantly by 2050 (23,619 ± 21,607 additional cases), but only under RCP8.5, and with large uncertainty around this projected increase. Significant case changes are not projected for any other region under either climate scenario. The results demonstrate a regionally variable and nuanced relationship between climate change and Lyme disease, indicating possible nonlinear responses of vector ticks and transmission dynamics to projected climate change. Moreover, our results highlight the need for improved preparedness and public health interventions in endemic regions to minimize the impact of further climate change-induced increases in Lyme disease burden.
BACKGROUND: People working in agriculture, fishing, and forestry have elevated risks of suicide. The suicide rates for the occupations of “agriculture, fishing, and forestry” are significantly higher than any other occupation. AIMS OF STUDY: This study evaluates whether the variability in socioeconomic and demographic factors and in climate as well as the support from mental health providers and social associations affected the suicide rates of farmers in the US. METHODS: We estimate Poisson count data regression and county level-fixed effects regressions using data from the National Center for Health Statistics complemented with relevant socio-economic, climate data and data on mental health providers from a variety of sources. RESULTS: The results show more suicides in counties with more farms and with higher share of population without health insurance, lower agricultural wages and, in non-rural counties higher poverty rate. Surprisingly, we find more suicides in counties with more social associations, while the availability of mental health providers is associated with fewer suicides in non-rural counties, and lower suicide rate in southern counties. DISCUSSION: These results highlight the need for innovative targeted policy interventions instead of relying on one-size-fits-all approach. Farmers and farm workers are yet to be reached with modern and effective tools to improve mental health and prevent suicide. At the same time, factors such as the weather and climate as well as some more traditional factors such as social associations or religious participation play a limited role. IMPLICATIONS FOR HEALTH POLICIES: Support mechanisms have a differential effect in rural and urban areas. It is important to identify the specific demographic, climate, and policy changes that serve as external stressors and affect farm workers’ suicide and accidental death from on-farm injury. IMPLICATION FOR FURTHER RESEARCH: Ideally, individual level data on farmers would be best in a study that evaluates what factors cause suicides.
Human exposure to floods continues to increase, driven by changes in hydrology and land use. Adverse impacts amplify for socially vulnerable populations, who disproportionately inhabit flood-prone areas. This study explores the geography of flood exposure and social vulnerability in the conterminous United States based on spatial analysis of fluvial and pluvial flood extent, land cover, and social vulnerability. Using bivariate Local Indicators of Spatial Association, we map hotspots where high flood exposure and high social vulnerability converge and identify dominant indicators of social vulnerability within these places. The hotspots, home to approximately 19 million people, occur predominantly in rural areas and across the US South. Mobile homes and racial minorities are most overrepresented in hotspots compared to elsewhere. The results identify priority locations where interventions can mitigate both physical and social aspects of flood vulnerability. The variables that most distinguish the clusters are used to develop an indicator set of social vulnerability to flood exposure. Understanding who is most exposed to floods and where, can be used to tailor mitigation strategies to target those most in need.
This article contributes to research on social vulnerability to natural hazards by analyzing the relationship between spatial patterns of flooding caused by Hurricane Harvey and subsidized rental housing residents. Our study area is Harris County, the most populous county in Texas, which includes the city of Houston and was severely impacted by Harvey-induced flooding. We sought to determine whether: (1) federally subsidized housing units and residents were disproportionately located in areas with greater flood extent and (2) areal extent of flooding around subsidized housing developments was greater for developments where higher proportions of socially vulnerable households reside. We integrated information from the US Federal Emergency Management Agency’s Harvey flood depths grid with US Department of Housing and Urban Development data on relevant rental assistance programs. Results from multivariable generalized estimating equations indicated significantly higher percentages of subsidized housing units and residents in neighborhoods with greater flood extent, after accounting for pertinent spatial and social factors. We also found subsidized housing developments with more extensive flooding nearby to contain significantly higher percentages of extremely low income, female-headed and older (62 + years) households. Findings have important implications for future research and policy, since these socio-spatial inequalities are likely to be reproduced through climate change-related disasters projected to affect many cities within and outside Texas.
Extreme heat has been responsible for more deaths in the United States than any other weather-related phenomenon over the past decade. The frequency and intensity of extreme heat events are projected to increase over the course of this century. In this work, we examine historical patterns of extreme heat exposure and mortality in the continental United States. We examine spatial variation in the mortality response to exposure, consider the contribution of key demographic and socio-economic factors in driving heat-related mortality, and test three different extreme heat thresholds using a national-level spatial autoregressive model and a geographically weighted regression approach. We find that the mortality response to exposure is higher in areas that do not routinely experience heat extremes, and that exposure itself is a stronger driver of heat-related mortality across the larger urban areas of the Midwest and Northeast. The importance of demographic/socio-economic factors varies substantially over space, and results are robust across alternative measures of heat extremes, suggesting that no single definition is necessarily superior. The baseline relationships established here are potentially useful for future predictions of exposure and heat-related mortality under alternative population and climate change scenarios, and may aid policy makers and planners in implementing effective adaptation and mitigation strategies.
BACKGROUND: Excessive heat is a leading weather-related cause of fatalities in the USA. Vulnerable populations can face greater exposure to health risks during extreme heat events. The aim of this study is to examine the effects of excessive heat and community-level social vulnerability on morbidity in San Antonio, Texas, in 2018. METHODS: Heat Index (HI) data are from the National Oceanic and Atmospheric Administration. Social vulnerability is measured using the Centres for Disease Control and Prevention’s Social Vulnerability Index (SVI). Morbidity is measured as the number of emergency medical service (EMS) incidents. Sixty-one zip codes were analysed for the 153 constrained calendar days from 1 May to 30 September 2018. Negative binomial regression analysis with the time-stratified case-crossover design was conducted to predict the effects of HI and SVI on the rate of EMS incidents. RESULTS: HI is significantly and positively associated with the rate of EMS incidents. Social vulnerability has a statistically significant association with EMS incidents, with higher levels of community-level social vulnerability associated with higher rates of EMS incidents. The effect of the HI on the rate of EMS incidents is significantly and positively moderated by the SVI. CONCLUSIONS: Social vulnerability and excessive heat increase the rate of EMS incidents. As the number of excessive heat days increases and San Antonio continues to have extreme disparities by location, there will be an effect on health systems, including EMSs.
Marching band (MB) artists frequently spend many hours engaged in outdoor physical activity. Anecdotal evidence and small studies have indicated that MB artists do experience heat-related health problems. Yet, unlike athletes, military personnel, or workers, there is very little research on heat-related hazards among this unique population. Here, we seek to understand the incidence and circumstances under which exertional heat illnesses (EHIs) occur among MB artists over a 31-year period (1990-2020) across the USA. Using an on-line news dataset, we identified 34 separate events and at least 393 total EHIs. Heat syncope (~?55%) and heat exhaustion (~?44%) comprised the majority of EHIs, although a small number of exertional heat stroke cases were also reported. EHIs were reported in all types of MB activities with?~?32% during rehearsal,?~?29% during parades,?~?21% during competition, and?~?15% during a performance. Also, the vast majority of events occurred with high school (~?88%) marching bands. Finally, EHIs overwhelmingly occurred when the weather was unusually hot by local conditions. In light of these findings, we emphasize the need for MB specific heat polices that incorporate weather-based activity modification, acclimatization, education about EHIs, and access to on-site medical professionals.
Relatively few studies investigated the effects of extreme temperatures (both heat and cold) on mental health (ICD-9: 290-319; ICD-10: F00-F99) and the potential effect modifications by individuals’ age, sex, and race. We aimed to explore the effect of extreme temperatures of both heat and cold on the emergency room (ER) visits for mental health disorders, and conducted a stratified analysis to identify possible susceptible population in Erie and Niagara counties, NY, USA. To assess the short-term impacts of daily maximum temperature on ER visits related to mental disorders (2009-2015), we applied a quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM). The model was adjusted for day of the week, precipitation, long-term time trend, and seasonality. We found that there were positive associations between short-term exposure to extreme ambient temperatures and increased ER visits for mental disorders, and the effects can vary by individual factors. We found heat effect (relative risk (RR) =?1.16; 95% confidence intervals (CI), 1.06-1.27) on exacerbated mental disorders became intense in the study region and subgroup of population (the elderly) being more susceptible to extreme heat than any other age group. For extreme cold, we found that there is a substantial delay effect of 14 days (RR =?1.25; 95% CI =?1.08-1.45), which is particularly burdensome to the age group of 50-64 years old and African-Americans. Our findings suggest that there is a positive association between short-term exposure to extreme ambient temperature (heat and cold) and increased ER visits for mental disorders, and the effects vary as a function of individual factors, such as age and race.
Hazard mitigation plans (HMP) inform residents and policymakers of the risks a community is vulnerable to, as well as prioritize measures implemented to minimize hazard damage. HMP development emphasizes the importance of creating plans with a strong fact base and analysis of risk exposure, while also facilitating participatory planning with residents. This paper discusses the intersection of citizen perception of extreme heat risk, policy implementation concerning extreme heat risk and actual extreme heat risk exposure in four coastal counties in Texas, Brazoria, Cameron, Galveston and Nueces Counties. Through surveying county residents and analyzing the counties’ HMPs, it was observed that residents perceive extreme heat risk as very high but HMPs have very little information on extreme heat mitigation. By examining three major components of hazard mitigation planning (actual/projected risk exposure, policy implementation and citizen perception), planners can better understand possible disconnects and fallacies that decrease the efficacy of mitigation plans. As HMPs are updated, officials should ensure that resident perceptions, which may change over time and as the result of specific events, are reflected.
The impacts of wildfires in the western United States have been increasing for decades. Combining physical, epidemiological and economic models, this study finds that the economic damage of California wildfires in 2018 was roughly 1.5% of California’s annual gross domestic product. Recent increases in the frequency and scale of wildfires worldwide have raised concerns about the influence of climate change and associated socioeconomic costs. In the western United States, the hazard of wildfire has been increasing for decades. Here, we use a combination of physical, epidemiological and economic models to estimate the economic impacts of California wildfires in 2018, including the value of destroyed and damaged capital, the health costs related to air pollution exposure and indirect losses due to broader economic disruption cascading along with regional and national supply chains. Our estimation shows that wildfire damages in 2018 totalled $148.5 (126.1-192.9) billion (roughly 1.5% of California’s annual gross domestic product), with $27.7 billion (19%) in capital losses, $32.2 billion (22%) in health costs and $88.6 billion (59%) in indirect losses (all values in US$). Our results reveal that the majority of economic impacts related to California wildfires may be indirect and often affect industry sectors and locations distant from the fires (for example, 52% of the indirect losses-31% of total losses-in 2018 were outside of California). Our findings and methods provide new information for decision makers tasked with protecting lives and key production sectors and reducing the economic damages of future wildfires.
In this study the authors examined how maternal health workers (MHWs) perceive the health risks of extreme heat exposure to pregnant women and fetuses. The authors conducted interviews with 12 MHWs (including midwives and doulas) in El Paso, Texas. Using qualitative analysis, the researchers identified numerous themes. Although heat was not communicated as a major health risk, participants expressed some concern with growing heat exposure and communicated standard protective measures. While all participants were familiar with some heat illness symptoms, they were generally unaware of their clients’ vulnerability. MHWs’ minimal heat-risk knowledge leaves pregnant women and developing fetuses at risk of preventable harm.
OBJECTIVE: This study evaluated the relationships between the occurrence of recent and recurring natural disasters on the incidence of acute and chronic health outcomes at the census tract level in 500 cities across the United States between 2001 and 2015. METHODS: Using the Centers for Disease Control and Prevention (CDC) 500 cities data set, the CDC Social Vulnerability Index, and the US Small Business Administration (SBA) Disaster Loan Database, we modeled the incidence of self-reported, poor mental and physical health, or a clinical diagnosis of high blood pressure or asthma in census tracts (N = 27 204 tracts in 500 cities) that had experienced recent or recurring natural disasters while controlling for social and environmental risk factors. RESULTS: Communities that experienced a natural disaster in the previous 5 years compared to those that had not had a higher incidence of poor mental health (RR: 1.02, 95% CI: 1.01-1.02), poor physical health (RR: 1.03, 95% CI: 1.02-1.04), high blood pressure (RR: 1.04, 95% CI: 1.02-1.05), and asthma (RR: 1.01, 95% CI: 1.01-1.02). The incidence of these poor health outcomes increased 1-2% with each additional year that a community experienced a disaster. CONCLUSIONS: Prevention and preparedness plans that work to build resilience in communities before disasters should focus on closing the gap in environmental and social determinants that have been linked with disproportionate health burdens and slow recovery post-disaster.
Extreme heat is one of the most pressing climate risks in the United States and is exacerbated by a warming climate and aging population. Much work in heat health has focused only on temperature-based metrics, which do not fully measure the physiological impact of heat stress on the human body. The U.S. Climate Reference Network (USCRN) consists of 139 sites across the United States and includes meteorological parameters that fully encompass human tolerance to heat, including relative humidity, wind, and solar radiation. Hourly and 5-min observations from USCRN are used to develop heat exposure products, including heat index (HI), apparent temperature (AT), and wet-bulb globe temperature (WBGT). Validation of this product is conducted with nearby airport and mesonet stations, with reanalysis data used to fill in data gaps. Using these derived heat products, two separate analyses are conducted. The first is based on standardized anomalies, which place current heat state in the context of a long-term climate record. In the second study, heat events are classified by time spent at various levels of severity of conditions. There is no consensus as to what defines a heat event, so a comparison of absolute thresholds (i.e., >= 30.0 degrees, 35.0 degrees, and 40.0 degrees C) and relative thresholds (>= 90th, 95th, and 98th percentile) will be examined. The efficacy of the product set will be studied using an extreme heat case study in the southeastern United States. While no heat exposure metric is deemed superior, each has their own advantages and caveats, especially in the context of public communication.
The persistence of high values of relative humidity for several hours to a few days has wide-ranging implications for natural and human systems. Among its many impacts, persistent high relative humidity contributes to reduced atmospheric visibility, fog frequency and duration, road and powerline icing, the occurrence of foliar plant disease and the temperature at which heat-related morbidity and mortality can occur. Despite this, the characteristics of humidity spells-including shifts with climate change-are rarely investigated and consequently poorly understood. Hourly relative humidity, precipitation and temperature for 35 locations in the Lower Peninsula (LP) of Michigan during 2003-2017, and for seven locations during 1973-2017, were used to assess, by biweekly periods, spatial, intra-annual and inter-annual variations in the characteristics of relative humidity spells. Two humidity thresholds that accommodate a wide range of applications were used: (1) high relative humidity (HRH), defined as hourly values >= 60%, and extremely high relative humidity (EHRH), defined as hourly values >= 85%. Extended HRH and EHRH spells are frequent across the LP, with HRH spells often spanning 36 hr or longer and EHRH spells commonly persisting more than 12 hr. The probability of HRH and EHRH spells generally decreased with time during 1973-2017, particularly later in the period. Although most spells initiate in the late afternoon and early evening hours, this diurnal preference is less evident as spell length increases, especially for EHRH spells. Furthermore, precipitation is more likely to occur with EHRH spells compared to HRH spells. The orientation and strength of spatial gradients in average annual spell frequency are highly dependent on the choice of humidity and duration thresholds and the temperatures accompanying the spells. This study represents the first comprehensive analysis of the persistence of humidity spells and illustrates the potential usefulness of temporally-flexible climatological summaries relevant for a wide range of applications.
The environment plays a significant role in the global burden of disease for children. Climate-related disasters such as the 2017 Atlantic hurricane season are increasingly contributing to this burden. United Nations designated Small Island Developing States (SIDS) like Puerto Rico and the U.S. Virgin Islands are particularly at risk due to environmental health hazards caused by natural disasters, and health care structure vulnerabilities. United Nations’ Sustainable Development Goals (UN SDG), specifically UN SDG 3, 13 and 17, focus on climate impacts via promotion of health preparedness and building partnerships between different sectors of society, respectively. The Pediatric Environmental Health Specialty Unit’s (PEHSU) work is consistent with these most notably via the delivery of environmental health services along with training nurses, doctors, and other health professionals, formation of partnerships and linking resources. Therefore, training a diverse array of health professionals and linking these groups to relevant community resources is of utmost importance and has the potential to enhance the effective management and early prevention of top environmental health (EH) risks. Nursing is identified as a key health sector to engage for this initiative. This article describes the work of the Federal Region 2 PEHSU in Puerto Rico and the U.S. Virgin Islands that supports health professionals’ knowledge building, development of environmental health services, and promotion of wide scale access to such services for children and families. The PEHSU’s work is consistent with these most notably with regards to the delivery of environmental health services in pediatrics.
Introduction. Weather-related disasters, such as wildfires exacerbated by a rise in global temperatures, need to be better studied in terms of their mental health impacts. This study focuses on the mental health sequelae of the deadliest wildfire in California to date, the Camp Fire of 2018. Methods. We investigated a sample of 725 California residents with different degrees of disaster exposure and measured mental health using clinically validated scales for post-traumatic stress disorder (PTSD), major depressive disorder (MDD) and generalized anxiety disorder (GAD). Data were collected at a chronic time-point, six months post-wildfire. We used multiple regression analyses to predict the mental health outcomes based on self-reported fire exposure. Additionally, we included vulnerability and resilience factors in hierarchical regression analyses. Results. Our primary finding is that direct exposure to large scale fires significantly increased the risk for mental health disorders, particularly for PTSD and depression. Additionally, the inclusion of vulnerability and resilience factors in the hierarchical regression analyses led to the significantly improved prediction of all mental health outcomes. Childhood trauma and sleep disturbances exacerbated mental health symptoms. Notably, self-reported resilience had a positive effect on mental health, and mindfulness was associated with significantly lower depression and anxiety symptoms. Conclusion. Overall, our study demonstrated that climate-related extreme events, such as wildfires, can have severe mental illness sequelae. Moreover, we found that pre-existing stressful life events, resilient personality traits and lifestyle factors can play an important role in the prevalence of psychopathology after such disasters. Unchecked climate change projected for the latter half of this century may severely impact the mental wellbeing of the global population, and we must find ways to foster individual resiliency.
As awareness of climate change increases, U.S. cities are beginning to implement climate mitigation and adaptation initiatives to reduce population vulnerabilities to climate risks. This study contributes to a growing literature that quantitatively describes the relationships between sociodemographic variables and climate adaptation interventions in U.S. cities. Ordinary linear and simultaneous autoregressive models are used to evaluate early flood adaptation actions in Austin, Texas, to assess relationships between flood risk, green infrastructure, and measures of race and income. Findings of unequal exposure to flood risk and uneven access to flood resilience initiatives contribute to our understanding of color-blind urban planning responses to climate change and their potential to amplify inequitable protection from climate risks.
BACKGROUND: Rural health professionals stand at the forefront of community response to climate change, but few studies have assessed their perceptions of the threat. Further, no previous study has compared the opinions of environmental to public health professionals or extensively analyzed the factors related to these experts’ climate beliefs, risk perceptions, and issue prioritization. METHODS: In conjunction with the Montana Climate Assessment’s 2021 Special Report on Climate Change and Human Health, the 479 members of the Montana Public Health Association and Montana Environmental Health Association were surveyed during September-October 2019, with 39% completing the survey. We summarized descriptive data about their perceptions of local climate-related changes and their beliefs that global warming is happening, is mostly human-caused, is a risk to human health, and that their offices and others should take action. We also evaluated which sociodemographic and risk perception factors related to these climate beliefs, risk perceptions, and workplace issue prioritization. RESULTS: Health professionals in Montana, a politically conservative state, demonstrated high levels of awareness that global warming is happening, human-caused, and a threat to human health, well above reported rates of public concern. Eighty-eight percent said that global warming is occurring and 69% that it is mostly anthropogenic. Sixty-nine percent said that their own health was already affected by climate, and 86% said they were already seeing at least one climate change-related event in their communities. Seventy-two percent said that their departments should be preparing to deal with climate change’s health effects, but just 30% said that it is currently happening. We found no statistically significant differences between Montana environmental health and public health professionals in regression models predicting climate beliefs, risk perception, and prioritization. As in studies of the public, political ideology and the observation of local climate-related changes were the strongest factors. CONCLUSIONS: Montana environmental and public health officials said that departmental action was needed on climate change, indicating the readiness of rural health professionals to take action. Further studies of health professionals in rural regions are warranted.
IMPORTANCE: Future changes in climate are likely to adversely affect human health by affecting concentrations of particulate matter sized less than 2.5 ?m (PM2.5) and ozone (O3) in many areas. However, the degree to which these outcomes may be mitigated by reducing air pollutant emissions is not well understood. OBJECTIVE: To model the associations between future changes in climate, air quality, and human health for 2 climate models and under 2 air pollutant emission scenarios. DESIGN, SETTING, AND PARTICIPANTS: This modeling study simulated meteorological conditions over the coterminous continental US during a 1995 to 2005 baseline and over the 21st century (2025-2100) by dynamically downscaling representations of a high warming scenario from the Community Earth System Model (CESM) and the Coupled Model version 3 (CM3) global climate models. Using a chemical transport model, PM2.5 and O3 concentrations were simulated under a 2011 air pollutant emission data set and a 2040 projection. The changes in PM2.5 and O3-attributable deaths associated with climate change among the US census-projected population were estimated for 2030, 2050, 2075, and 2095 for each of 2 emission inventories and climate models. Data were analyzed from June 2018 to June 2020. MAIN OUTCOMES AND MEASURES: The main outcomes were simulated change in summer season means of the maximum daily 8-hour mean O3, annual mean PM2.5, population-weighted exposure, and the number of avoided or incurred deaths associated with these pollutants. Results are reported for 2030, 2050, 2075, and 2095, compared with 2000, for 2 climate models and 2 air pollutant emissions data sets. RESULTS: The projected increased maximum daily temperatures through 2095 were up to 7.6 °C for the CESM model and 11.8 °C for the CM3 model. Under each climate model scenario by 2095, compared with 2000, an estimated additional 21?000 (95% CI, 14?000-28?000) PM2.5-attributable deaths and 4100 (95% CI, 2200-6000) O3-attributable deaths were projected to occur. These projections decreased to an estimated 15?000 (95% CI, 10?000-20?000) PM2.5-attributable deaths and 640 (95% CI, 340-940) O3-attributable deaths when simulated using a future emission inventory that accounted for reduced anthropogenic emissions. CONCLUSIONS AND RELEVANCE: These findings suggest that reducing future air pollutant emissions could also reduce the climate-driven increase in deaths associated with air pollution by hundreds to thousands.
INTRODUCTION: Climate change presents unprecedented health threats. It is imperative that medical trainees understand the implications of climate change/planetary health on the physical and mental health and well-being of their patients. Medical professionals generally are not trained to consider climate change impacts in patient encounters. Hence, there is a need to train climate-aware providers who will be at the forefront of patient care in managing these current and emerging health impacts. METHODS: We created a standardized patient (SP) case enhanced with details of risks and health impacts due to exposure to wildfire smoke. This session was deployed to 11 internal medicine clerkship students as part of a standard OSCE already included in our curriculum to evaluate core clinical and communication skills. Two cohorts, a group activity, and a one-on-one encounter were deployed and followed with a faculty debrief and learner assessments. RESULTS: Students had increased awareness and knowledge of health impacts of climate change and potential actions for adaptation and mitigation. The improvements were statistically significant for the one-on-one cohort (p = .006). Postsimulation comments were favorable; students were more inclined to consider health impacts, risks, and vulnerabilities exacerbated by climate change. DISCUSSION: Students had an increased recognition of climate change as a force impacting their patients’ health which should be considered in patient care. This format allowed retention of well established curricular content, but also the inclusion of other crucial emerging issues that will impact public health locally and globally and foster the development of climate-aware health care providers.
INTRODUCTION: Climate change is heightening both long-term adverse risks to human health and the immediate-term risk of injuries and illness following climate-related disaster events that are becoming more frequent and severe. In addition to its direct health effects, climate change poses new threats to the nation’s health care infrastructure – with potential to negatively impact healthcare capacity amidst increasing demand – through risks of flooding, wind damage, heat stress, power outages, and other physical harm to facilities. The typical Hazard Vulnerability Analyses conducted annually by hospitals use historical data to assess risks; these analyses are likely now inadequate for future preparation due to the impact of climate change. This article describes one approach to how healthcare leaders can better assess both near-term and long-term risks due to climate change, to mitigate against unprecedented but foreseeable threats. METHODS: In our large health system in the US Northeast, a process was undertaken to gather updated data and expert projections to forecast threats faced by each of our facilities in different climate-related disaster scenarios. Hazards examined in our setting included precipitation-based and coastal flooding events, heat waves, and high wind events, in addition to seismic events. Probabilities of occurrence and extents of different hazards were projected for the near term (2030) and the long term (2070). We then performed detailed vulnerability analyses for each facility with the predicted amount of rainfall, storm surge, heat stress, and windspeed, in collaboration with leaders at each facility. This was followed by a process to understand what would be needed to mitigate each vulnerability along with the associated costs. Ultimately, a cost/benefit analysis was performed – incorporating the relative likelihood and impact of different scenarios – to decide which improvement projects to embark on immediately, and what to defer and/or incorporate into future building plans. RESULTS: In our system, all facilities were vulnerable to the effects of increased temperatures, and multiple hospitals were noted to be vulnerable to extreme precipitation, storm surge, and high winds. Specific damaging scenarios identified included flooding of basements and building infrastructure spaces, water entry through windows during high winds, and overheating of power systems during heat waves. Potential solutions included improved power redundancy for cooling systems, enhancements to roof and window systems, and the acquisition of deployable flood barriers. We identified four categories for prioritization of action based on projected impact: 1) priorities in need of urgent mitigation, 2) priorities in need of investigative study for medium-term mitigation, 3) priorities for planned capital improvement projects, and 4) priorities to integrate into new facility construction. DISCUSSION: While the specific risks and vulnerabilities for each facility will differ according to its location and structural features, the approach we describe is broadly applicable. By forecasting specific risks, diagnosing vulnerabilities, developing potential solutions, and using a risk/benefit approach to decision making, hospitals can work toward protecting facilities and patients in the face of potential climate related natural disasters in an economically sound manner.
Climate change affects Michigan’s public health in several primary ways, including increased incidences of vector-borne, waterborne, heat-related, and respiratory illness. Because local health departments (LHDs) play a central role in surveillance and preventative health services, they are among the first institutions to contend with the local impacts of climate change. To assess current perceptions among Michigan public health officials, an online survey was conducted in partnership with the Michigan Association for Local Public Health (MALPH). Most of the Michigan respondents (62%, n = 34) agreed that their jurisdictions have experienced climate change in the last 20 years, and 77% agreed that climate change will impact their jurisdictions in the coming 20 years. However, only 35% (n = 34) of Michigan officials agreed that climate change is a priority in their departments. About one quarter (25%, n = 34) of Michigan LHD respondents did not know about the level of expertise of either the state and federal agencies, responsible for assisting them with information and programs related to climate change and health. Uncertainty regarding the resources available to them may hinder LHDs from developing necessary preparedness, so meeting this need could bolster the public health response to climate change. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13412-021-00679-0.
Urban areas are increasingly affected by extreme heat in the face of climate change, while the size and vulnerability of exposed populations are shifting due to economic development, demographic change, and urbanization. In addition to the need to assess future urban heat-related health risks, there is also an increasing need to design adaptation strategies that will be effective under varying levels of socioeconomic development and climate change. We use the case study of Houston, Texas, to develop and demonstrate a scenario-based approach to explore the effectiveness of both autonomous and planned heat-related adaptations under multiple plausible futures. We couple a heat risk model with urban climate projections (under the Representative Concentration Pathways) and vulnerability projections (under locally extended Shared Socioeconomic Pathways) to investigate the impact of different adaptation strategies under multiple scenario combinations. We demonstrate that, in the context of Houston, community-based adaptation strategies aiming to reduce social isolation are the most effective and the least challenging to implement across all plausible futures. Scenario-based approaches can provide local policymakers with context-specific assessments of possible adaptation strategies that account for uncertain futures.
BACKGROUND: There is growing evidence suggesting that extreme temperatures have an impact on mental disorders. We aimed to explore the effect of extreme temperatures on emergency room (ER) visits for mental health disorders using 2.8 million records from New York State, USA (2009-2016), and to examine potential effect modifications by individuals’ age, sex, and race/ethnicity through a stratified analysis to determine if certain populations are more susceptible. METHOD: To assess the short-term impact of daily average temperature on ER visits related to mental disorders, we applied a quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM). The model was adjusted for day of the week, precipitation, as well as long-term and seasonal time trends. We also conducted a meta-analysis to pool the region-specific risk estimates and construct the overall cumulative exposure-response curves for all regions. RESULTS: We found positive associations between short-term exposure to extreme heat (27.07 (?)C) and increased ER visits for total mental disorders, as well as substance abuse, mood and anxiety disorders, schizophrenia, and dementia. We did not find any statistically significant difference among any subgroups of the population being more susceptible to extreme heat than any other. CONCLUSIONS: Our findings suggest that there is a positive association between short-term exposure to extreme heat and increased ER visits for total mental disorders. This extreme effect was also found across all sub-categories of mental disease, although further research is needed to confirm our finding for specific mental disorders, such as dementia, which accounted for less than 1% of the total mental disorders in this sample.
IMPORTANCE Air pollution is a worldwide public health issue that has been exacerbated by recent wildfires, but the relationship between wildfire-associated air pollution and inflammatory skin diseases is unknown. OBJECTIVE To assess the associations between wildfire-associated air pollution and clinic visits for atopic dermatitis (AD) or itch and prescribed medications for AD management. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional time-series study assessed the associations of air pollution resulting from the California Camp Fire in November 2018 and 8049 dermatology clinic visits (4147 patients) at an academic tertiary care hospital system in San Francisco, 175 miles from the wildfire source. Participants included pediatric and adult patients with AD or itch from before, during, and after the time of the fire (October 2018 through February 2019), compared with those with visits in the same time frame of 2015 and 2016, when no large wildfires were near San Francisco. Data analysis was conducted from November 1, 2019, to May 30, 2020. EXPOSURES Wildfire-associated air pollution was characterized using 3 metrics: fire status, concentration of particulate matter less than 2.5 mu m in diameter (PM2.5), and satellite-based smoke plume density scores. MAIN OUTCOMES AND MEASURES Weekly clinic visit counts for AD or itch were the primary outcomes. Secondary outcomes were weekly numbers of topical and systemic medications prescribed for AD in adults. RESULTS Visits corresponding to a total of 4147 patients (mean [SD] age, 44.6 [21.1] years; 2322 [56%] female) were analyzed. The rates of visits for AD during the Camp Fire for pediatric patients were 1.49 (95% CI, 1.07-2.07) and for adult patients were 1.15 (95% CI, 1.02-1.30) times the rate for nonfire weeks at lag 0, adjusted for temperature, relative humidity, patient age, and total patient volume at the clinics for pediatric patients. The adjusted rate ratios for itch clinic visits during the wildfire weeks were 1.82 (95% CI, 1.20-2.78) for the pediatric patients and 1.29 (95% CI, 0.96-1.75) for adult patients. A 10-mu g/m(3) increase in weekly mean PM2.5 concentration was associated with a 7.7% (95% CI, 1.9%-13.7%) increase in weekly pediatric itch clinic visits. The adjusted rate ratio for prescribed systemic medications in adults during the Camp Fire at lag 0 was 1.45 (95% CI, 1.03-2.05). CONCLUSIONS AND RELEVANCE This cross-sectional study found that short-term exposure to air pollution due to the wildfire was associated with increased health care use for patients with AD and itch. These results may provide a better understanding of the association between poor air quality and skin health and guide health care professionals’ counseling of patients with skin disease and public health practice.
Prevalence of allergic diseases has been increasing due to multiple factors, among which climate change has had the most impact. Climate factors increase production of pollen, which also exhibits increased allergenicity. Also, as a result of climate change, there has been a shift in flowering phenology and pollen initiation causing prolonged pollen exposure. Various numerical models have been developed to understand the effect of climate change on pollen emission and transport and the impact on allergic airway diseases.
Air pollution is considered as an important concern all over the world. It disturbs the whole environment and produces more harmful effects to human’s healthy life. Relevant statistical reports from World Health Organization notify that air pollution play a major role in cause of diseases like asthma, lung cancer, stroke, early death and premature birth. Apart from diseases pollution also influence dangerous climate, weather conditions and may cause acid rain, global warming, ozone layer depletion, rainfall declines, etc. Therefore, it is essential to take necessary and preventive measures against air pollution. A comprehensive study is required to assess quality of ambient (outdoor) air, based on the observations of the major pollutants concentration drawn from different monitoring stations. Aiming at this problem, we proposed an ensemble based model to assess the air quality of United States from the period 2000 to 2016. In this article, we resolved the issues related to preprocessing of imbalanced dataset and improved the performance of the entire system through ensemble methods. We compared the recommended model with the existing ones. The experimental results show that the suggested model is superior to other systems and yield high accuracy, low error rate.
BACKGROUND: As the global climate changes in response to anthropogenic greenhouse gas emissions, weather and temperature are expected to become increasingly variable. Although heat sensitivity is a recognized clinical feature of multiple sclerosis (MS), a chronic demyelinating disorder of the central nervous system, few studies have examined the implications of climate change for patients with this disease. METHODS AND FINDINGS: We conducted a retrospective cohort study of individuals with MS ages 18-64 years in a nationwide United States patient-level commercial and Medicare Advantage claims database from 2003 to 2017. We defined anomalously warm weather as any month in which local average temperatures exceeded the long-term average by ?1.5°C. We estimated the association between anomalously warm weather and MS-related inpatient, outpatient, and emergency department visits using generalized log-linear models. From 75,395,334 individuals, we identified 106,225 with MS. The majority were women (76.6%) aged 36-55 years (59.0%). Anomalously warm weather was associated with increased risk for emergency department visits (risk ratio [RR] = 1.043, 95% CI: 1.025-1.063) and inpatient visits (RR = 1.032, 95% CI: 1.010-1.054). There was limited evidence of an association between anomalously warm weather and MS-related outpatient visits (RR = 1.010, 95% CI: 1.005-1.015). Estimates were similar for men and women, strongest among older individuals, and exhibited substantial variation by season, region, and climate zone. Limitations of the present study include the absence of key individual-level measures of socioeconomic position (i.e., race/ethnicity, occupational status, and housing quality) that may determine where individuals live-and therefore the extent of their exposure to anomalously warm weather-as well as their propensity to seek treatment for neurologic symptoms. CONCLUSIONS: Our findings suggest that as global temperatures rise, individuals with MS may represent a particularly susceptible subpopulation, a finding with implications for both healthcare providers and systems.
BACKGROUND: As global temperatures rise, increasing numbers of individuals will work in hot environments. Interventions to protect their health are critical, as are reliable methods to measure the physiological strain experienced from heat exposure. The physiological strain index (PSI) is a measure of heat strain that relies on heart rate and core temperature but is challenging to calculate in a real-world occupational setting. METHODS: We modified the PSI for use in field settings where resting temperature and heart rate are not available and used the modified physiological strain index (mPSI) to describe risk factors for high heat strain (mPSI???7) experienced by agricultural workers in Florida during the summers of 2015 through 2017. mPSI was calculated for 221 workers, yielding 465 days of data. RESULTS: A higher heat index (??=?0.185; 95% CI: 0.064, 0.307) and higher levels of physical activity at work (0.033; 95% CI: 0.017, 0.050) were associated with a higher maximum mPSI. More years worked in US agriculture (-0.041; 95% CI: -0.061, -0.020) were protective against a higher maximum mPSI. Out of 23 workdays that a participant experienced a maximum mPSI???7,?22 were also classified as strained by at least one other measure of high heat strain (core temperature [Tc] >38.5°C, sustained heart rate >(180?-?age), and mean heart rate?>?115?bpm). CONCLUSIONS: This study provides critical information on risk factors for elevated heat strain for agricultural workers and suggests a practical approach for using PSI in field-based settings.
Characterizing the future risks of climate change is a key goal of climate impacts analysis. Temperature binning provides a framework for analyzing sector-specific impacts by degree of warming as an alternative or complement to traditional scenario-based approaches in order to improve communication of results, comparability between studies, and flexibility to facilitate scenario analysis. In this study, we estimate damages for nine climate impact sectors within the contiguous United States (US) using downscaled climate projections from six global climate models, at integer degrees of US national warming. Each sector is analyzed based on socioeconomic conditions for both the beginning and the end of the century. The potential for adaptive measures to decrease damages is also demonstrated for select sectors; differences in damages across adaptation response scenarios within some sectors can be as much as an order of magnitude. Estimated national damages from these sectors based on a reactive adaptation assumption and 2010 socioeconomic conditions range from $600 million annually per degree of national warming for winter recreation to $8 billion annually per degree of national warming for labor impacts. Results are also estimated per degree of global temperature change and for 2090 socioeconomic conditions.
Admissions of newborn infants into Neonatal Intensive Care Units (NICU) has increased in the US over the last decade yet the role of environmental exposures as a risk factor for NICU admissions is under studied. Our study aims to determine the ecologic association between acute and intermediate ambient PM2.5 exposure durations and rates of NICU admissions, and to explore whether this association differs by area-level social stressors and meteorological factors. We conducted an ecologic time-series analysis of singleton neonates (N = 1,027,797) born in Florida hospitals between December 26, 2011 to April 30, 2019. We used electronic medical records (EMRs) in the OneFlorida Data Trust and included infants with a ZIP code in a Metropolitan Statistical Areas (MSA) and excluded extreme preterm births (<24wks gestation). The study outcome is the number of daily NICU admission at 28 days old or younger for each ZIP code in the study area. The exposures of interest are average same day, 1- and 2-day lags, and 1-3 weeks ambient PM2.5 concentration at the ZIP code-level estimated using inverse distance weighting (IDW) for each day of the study period. We used a zero-inflated Poisson regression mixed effects models to estimate adjusted associations between acute and intermediate PM2.5 exposure durations and NICU admissions rates. NICU admissions rates increased over time during the study period. Ambient 7-day average PM2.5 concentrations was significantly associated with incidence of NICU admissions, with an interquartile range (IQR = 2.37 ?g/m(3)) increase associated with a 1.4% (95% CI: 0.4%, 2.4%) higher adjusted incidence of daily NICU admissions. No other exposure duration metrics showed a significant association with daily NICU admission rates. The magnitude of the association between PM2.5 7-day average concentrations with NICU admissions was significantly (p < 0.05) higher among ZIP codes with higher proportions of non-Hispanic Blacks, ZIP codes with household incomes in the lowest quartile, and on days with higher relative humidity. Our data shows a positive relationship between acute (7-day average) PM2.5 concentrations and daily NICU admissions in Metropolitan Statistical Areas of Florida. The observed associations were stronger in socioeconomically disadvantaged areas, areas with higher proportions with non-Hispanic Blacks, and on days with higher relative humidity. Further research is warranted to study other air pollutants and multipollutant effects and identify health conditions that are driving these associations with NICU admissions.
The purpose of this study was to assess autonomic and hemodynamic recovery in women who performed moderate-intensity exercise in heat. Seven women (31.7 ± 7.6 years, 67.5 ± 4.4 kg, 25.7 ± 5.6% Fat, 43.9 ± 5.1 mL/kg/min) completed two identical bouts of graded treadmill walking (~60% VO(2)peak). One bout was hot (37.5 ± 1.4°C, 46.5 ± 4.6% relative humidity (RH)), and the other was moderate (20.7 ± 1.1°C, 29.9 ± 4.1% RH). For 24 h before and one h after each bout, participants had heart rate variability monitored. After each exercise bout HR and BP were measured during 30 min of supine recovery and 10 min of orthostatic challenge. HF power and RMSSD were lower and LF power and LF:HF ratio greater following exercise in the heat and remained different from the moderate condition for 30 min (p < 0.05). During supine recovery, heat exposure led to higher HR (p = 0.002) and lower DBP (p = 0.016). SBP (p = 0.037) and DBP (p = 0.008) were both lower after 10 min of supine recovery following hot exercise than after moderate temperature. Average response did not reveal orthostatic hypotension despite heat causing a higher HR (p = 0.011) and lower SBP (p = 0.026) after 10 min of orthostatic exposure. Trained women exhibit an autonomic shift toward sympathetic dominance for at least 30 min after exercise in heat. Women who exercise in heat should be wary of an exacerbated HR response after exercise and low recovery blood pressures.
Although families can be a source of support post-disaster, depending on how they communicate about their stress, their attempts at support can be helpful or harmful. This study explored the moderating role of topic avoidance and co-rumination on post-disaster mental health (MH) in a sample of 485 parent-child dyads following severe floods affecting Texas. Parents (69.0% female) and their oldest child between the ages of 10-19 years (M?=?13.75 years, SD?=?2.56) completed online surveys approximately one-year post-flooding. Participants reported their flood exposure, life stressors since the disaster, topic avoidance, co-rumination, and MH symptoms (posttraumatic stress symptoms [PTSS], depression, anxiety). Structural equation models tested a moderated-mediation model of whether communication processes moderated the associations of flood exposure and life stressors on MH. They did not moderate the association of flood exposure to PTSS, but did have a moderating role for depression and anxiety. At low levels of topic avoidance, there was no association between flood exposure and child anxiety or depression. However, at mean and high levels of topic avoidance, there was a significant, positive association between flood exposure and child anxiety and depression. Co-rumination impacted both parents and children. For parents, there was no association between flood exposure and depression or anxiety when co-rumination was low or mean-level. However, flood exposure increased risk for depression and anxiety at high levels of co-rumination. A similar pattern emerged for children. Results for life stressors were nuanced. Overall, this suggests that communication can influence post-disaster MH.
OBJECTIVE: The wildfire allied environmental pollution is highly toxic and can cause significant wide-ranging damage to the regional environment, weather conditions, and it can facilitate the transmission of microorganisms and diseases. The present study aims to investigate the effect of wildfire allied pollutants, particulate matter (PM-2.5 ?m), and carbon monoxide (CO) on the dynamics of daily cases and deaths due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in San Francisco, USA. MATERIALS AND METHODS: For this study, we selected San Francisco, one of the regions affected by the wildfires allied pollution in California, USA. The data on the COVID-19 pandemic in San Francisco, including daily new cases and new deaths were recorded from Worldometer Web. The daily environmental pollutants particulate matter (PM-2.5 ?m) and carbon monoxide (CO) were recorded from the metrological web “BAAQMD”. The daily cases, deaths, particulate matter (PM-2.5 ?m) and carbon monoxide were documented from the date of the occurrence of the first case of (SARS-CoV-2) in San Francisco, CA, USA, from March 20, 2020 to Sept 16, 2020. RESULTS: The results revealed a significant positive correlation between the environmental pollutants particulate matter (PM2.5 ?m) and the number of daily cases (r=0.203, p=0.007), cumulative cases (r=0.567, p<0.001) and cumulative deaths (r=0.562, p<0.001); whereas the PM2.5 ?m and daily deaths had no relationship (r=-0.015, p=0.842). In addition, CO was also positively correlated with cumulative cases (r=0.423, p<0.001) and cumulative deaths (r=0.315, p<0.001), however, CO had no correlation with the number of daily cases (r=0.134, p=0.075) and daily deaths (r=0.030, p=0.693). In San Francisco, one micrometer (?g/m3) increase in PM2.5 caused an increase in the daily cases, cumulative cases and cumulative deaths of SARS-COV-2 by 0.5%, 0.9% and 0.6%, respectively. Moreover, with a 1 part per million (ppm) increase in carbon monoxide level, the daily number of cases, cumulative cases and cumulative deaths increased by 5%, 9.3% and 5.3%, respectively. On the other hand, CO and daily deaths had no significant relationship. CONCLUSIONS: The wildfire allied pollutants, particulate matter PM-2.5?m and CO have a positive association with an increased number of SARS-COV-2 daily cases, cumulative cases and cumulative deaths in San Francisco. The metrological, disaster management and health officials must implement the necessary policies and assist in planning to minimize the wildfire incidences, environmental pollution and COVID-19 pandemic both at regional and international levels.
We estimate the effects of wildfire smoke exposure on infant health. Exposure to wildfire smoke is determined using the latitude and longitude coordinates corresponding to each infant’s home address and a fine-scaled spatial dataset of wildfire smoke plumes constructed in GIS from satellite images of the landscape. Using a difference-in-differences estimation strategy, model estimates show that exposure to wildfire smoke leads to a .034 increase in the probability of low birthweight.
Objective: The study examines how wildfire smoke exposure may impact health and safety in the agricultural workplace. Methods: Semi-structured interviews were conducted with agricultural employers and focus group discussions were held with farmworkers in three regions of California. Results: Agricultural employers had varying knowledge about and experience responding to poor air quality due to wildfire smoke. Respirators or masks were not mentioned as a potential protective measure when describing their safety practices. Farmworkers reported experiencing poor air quality due to wildfire smoke, although knowledge of safety precautions varied. Farmworkers reported employer and supervisors’ attitudes toward safety as having the greatest impact on the implementation of workplace safety measures. Conclusion: Adapting health promotion and workplace safety strategies to meet the multiple vulnerabilities and diverse needs of farmworkers is critical to successful implementation of workplace protection and safety measures. Given limited familiarity with the topic, wildfire smoke exposure resources are needed to assist employers and supervisors in their compliance with a new wildfire smoke safety regulation in California. To the best of our knowledge, this is the first study to explore agricultural employer and farmworker perceptions of the health and safety impacts of wildfire smoke and workplace exposure.
The over one million agricultural workers in the United States (U.S.) are amongst the populations most vulnerable to the health impacts of extreme heat. Climate change will further increase this vulnerability. Here we estimate the magnitude and spatial patterns of the growing heat exposure and health risk faced by U.S. crop workers and assess the effect of workplace adaptations on mitigating that risk. We find that the average number of days spent working in unsafe conditions will double by mid-century, and, without mitigation, triple by the end of it. Increases in rest time and the availability of climate-controlled recovery areas can eliminate this risk but could affect farm productivity, farm worker earnings, and/or labor costs much more than alternative measures. Safeguarding the health and well-being of U.S. crop workers will therefore require systemic change beyond the worker and workplace level.
The purpose of this study is to analyze and compare the human suffering exacerbation processes in the coastal metropolitan areas of Nagoya, New Orleans and Metro Manila caused by 1959 Typhoon Isewan, 2005 Hurricane Katrina and 2009 Tropical Storm Ondoy, respectively, in order to understand disasters. The research method applied was firstly to create a timeline of each disaster process with disaster responses by referring to newspapers, literature, and others, then the facts were categorized with similar social conditions and government responses to establish a hypothesis. Field surveys were conducted to verify the hypothesis. The research outcome shows the human suffering exacerbation processes of these three large-scale disasters can be seen that the pattern of the process is the same; however, the duration and content of each disaster are quite different. These differences mainly depend on social backgrounds, disaster subculture, and disaster management by local and national governments. Based on the above research findings, a useful view for disaster investigation and disaster management is clarified, along with the possible contributions of disaster countermeasures’ timeline development, especially for the disaster management in metropolitan areas.
Rain, snow, or ice may discourage older adults from leaving their homes with potential consequences for social isolation, decreased physical activity, and cognitive decline. This study is the first to examine potential links between annual precipitation exposure and cognitive function in a large population-based cohort of older Americans. We examined the association between precipitation (percent of days with snow or rain in the past year) and cognitive function in 25,320 individuals aged 45+ from the Reasons for Geographic and Racial Differences in Stroke Study. Linear mixed models assessed the relationship between precipitation and cognitive function, as well as rates of change in cognitive function with age. We found a non-linear relationship between precipitation and cognitive function. Compared to those exposed to infrequent precipitation (less than 20% of days with rain/snow in the past year), cognitive function was higher among older adults experiencing moderately frequent precipitation (20-40% of annual days with precipitation). However, beyond more than about 45% of days with precipitation in the past year, there was a negative association between precipitation and cognitive function, with faster rates of cognitive decline with age. These exploratory findings motivate further research to better understand the complex role of precipitation for late-life cognitive function.
Communities worldwide will increasingly be called upon to bear the burden of the direct impact of climate change, and also the externalities associated with avoiding the worst. This begs the question: How do we protect the well-being of populations living with climate impacts without causing unintentional harm via poorly planned or managed adaptation actions? This Perspective presenting an exploratory pilot study surveyed populations affected by the historic and unprecedented widespread public safety power shutoffs (PSPS) to mitigate the risk of wildfires by Pacific Gas & Electric (PG&E) and Southern California Edison (SCE) in October and November 2019 that left millions without power. The results suggest that PSPS likely represents a ‘looming threat’ that is associated with reported poorer recent physical and mental health, exacerbated by self-reported trauma lingering from previous experience with wildfires, especially among the most vulnerable. This threat is apparently most acute in northern California, where people experienced greater widespread shutoffs, more recent experience with devastating wildfires, and expressed anger toward how their utility contributed and responded to recent wildfires. Despite this, people are largely supportive of PSPS as an important way to reduce the bigger risk of wildfires, even as they report suffering from this adaptation measure. These results suggest that people understand and are sympathetic regarding the need for PSPS; yet without holistic consideration of the consequences of climate adaptation, unintended health impacts may arise.
Feeling affected by climate change related disasters has the potential to mobilize belief in climate change, concern about the issue, and support for mitigation policies – even when accounting for the effects of physically living through a disaster. In this study we use a two-wave survey design where respondents in the United States were interviewed before and after Hurricane Florence to better understand who feels affected by such disasters. First, we find that being worried about climate change increases the feeling of being affected by the hurricane among those who regularly discuss climate change. Second, we find that those who are high in perspective taking are more likely to feel affected. However, those who are high in empathic concern, but feel obligated to help victims of disasters, are less likely to feel affected. This suggests that hurricanes may cause a collapse of compassion, where those who are especially sensitive to the suffering of others down-regulate their emotional response to costly disasters.
Objectives. To examine the relationships among environmental characteristics, temperature, and health outcomes during heat advisories at the geographic scale of street segments.Methods. We combined multiple data sets from Boston, Massachusetts, including remotely sensed measures of temperature and associated environmental characteristics (e.g., canopy cover), 911 dispatches for medical emergencies, daily weather conditions, and demographic and physical context from the American Community Survey and City of Boston Property Assessments. We used multilevel models to analyze the distribution of land surface temperature and elevated vulnerability during heat advisories across streets and neighborhoods.Results. A substantial proportion of variation in land surface temperature existed between streets within census tracts (38%), explained by canopy, impervious surface, and albedo. Streets with higher land surface temperature had a greater likelihood of medical emergencies during heat advisories relative to the frequency of medical emergencies during non-heat advisory periods. There was no independent effect of the average land surface temperature of the census tract.Conclusions. The relationships among environmental characteristics, temperature, and health outcomes operate at the spatial scale of the street segment, calling for more geographically precise analysis and intervention. (Am J Public Health. Published online ahead of print May 21, 2020: e1-e8. doi:10.2105/AJPH.2020.305636).
We used monthly precipitation and temperature data to give early warning of years with higher West Nile Virus (WNV) risk in Nebraska. We used generalized additive models with a negative binomial distribution and smoothing curves to identify combinations of extremes and timing that had the most influence, experimenting with all combinations of temperature and drought data, lagged by 12, 18, 24, 30, and 36 months. We fit models on data from 2002 through 2011, used Akaike’s Information Criterion (AIC) to select the best-fitting model, and used 2012 as out-of-sample data for prediction, and repeated this process for each successive year, ending with fitting models on 2002-2017 data and using 2018 for out-of-sample prediction. We found that warm temperatures and a dry year preceded by a wet year were the strongest predictors of cases of WNV. Our models did significantly better than random chance and better than an annual persistence naïve model at predicting which counties would have cases. Exploring different scenarios, the model predicted that without drought, there would have been 26% fewer cases of WNV in Nebraska through 2018; without warm temperatures, 29% fewer; and with neither drought nor warmth, 45% fewer. This method for assessing the influence of different combinations of extremes at different time intervals is likely applicable to diseases other than West Nile, and to other annual outcome variables such as crop yield.
OBJECTIVES: Preterm births (PTBs) represent significant health risks, and several studies have found associations between high outdoor temperatures and PTB. We estimated both the total and natural direct effects (independent of particulate matter, ozone and nitrogen dioxide air pollutants) of the prior 2-day mean apparent temperature (AT) on PTB. We evaluated effect modification by maternal age, race, education, smoking status and prenatal care. DESIGN AND SETTING: We obtained birth records and meteorological data for the Detroit, Michigan, USA area, for the warm months (May to September), 1991 to 2001. We used a time series Poisson regression with splines of AT, wind speed, solar radiation and citywide average precipitation to estimate total effects. To accommodate multiple mediators and exposure-mediator interactions, AT inverse odds weights, predicted by meteorological and air pollutant covariates, were added in a subsequent model to estimate direct effects. RESULTS: At 24.9°C relative to 18.6°C, 10.6% (95% CI: 3.8% to 17.2%) of PTBs were attributable to the total effects of AT, and 10.4% (95% CI: 2.2% to 17.5%) to direct effects. Relative excess risks of interaction indicated that the risk of PTB with increasing temperature above 18.6°C was significantly lower among black mothers and higher among mothers less than 19, older than 30, with late or no prenatal care and who smoked. CONCLUSION: This additional evidence of a direct association between high temperature and PTB may motivate public health interventions to reduce extreme heat exposures among pregnant women, particularly among those who may have enhanced vulnerability.
Climate change is imposing substantial consequences across physical and social infrastructures. The extent of social disruption and risk to human health are, however, potentially much broader than these general consequences, taken individually, would suggest. To address this gap, we assess the distribution of contaminated sites in the United States (US) and then estimate the impact that flood hazards in urban areas will have on these contaminated sites. Using these measures, we draw inferences about the risk of contamination from climate impacted extreme weather events, climate adaptation at the local level, social risk and how it is distributed, and a broader understanding of the potential global consequences of climate change. In this paper we address three critical points: 1) the role classification of contaminated sites on our understanding of risk due to climate change; 2) the relationship between contaminated sites and flood risk; and 3) the potential for climate adaption strategies to mediate this risk. We estimate that of the roughly one-third of the US population living in urban areas, up to 3,338,518 people, are living in high-risk flood zones near contaminated sites. Our results suggest severe potential implications for estimates of the negative consequences from climate change and contamination and provide critical insights into the relationship between climate change and the built environment for urban planners and environmental policy makers and managers alike.
BACKGROUND: The public health impacts of tropical cyclones (TCs) are expected to increase due to the continued growth of coastal populations and the increasing severity of these events. However, the impact of TCs on pregnant women, a vulnerable population, remains largely unknown. We aimed to estimate the association between prenatal exposure to TCs and risk of preterm birth in the eastern United States (US) and to assess whether the association varies by individual- and area-level characteristics. METHODS: We included data on 19,529,748 spontaneous singleton births from 1989 to 2002 across 378 US counties. In each county, we classified days as exposed to a TC when TC-associated peak sustained winds at the county’s population-weighted center were >17.2 m/s (gale-force winds or greater). We defined preterm birth as births delivered prior to 37 completed weeks of gestation. We used distributed lag log-linear mixed-effects models to estimate the relative risk (RR) and absolute risk difference (ARD) for TC exposure by comparing preterm births occurring in TC-periods (from 2 days before to 30 days after the TC’s closest approach to the county’s population center) to matched non-TC periods. We conducted secondary analyses using other wind thresholds (12 m/s and 22 m/s) and other exposure metrics: county distance to storm track (30 km, 60 km, and 100 km) and cumulative rainfall within the county (75 mm, 100 mm, and 125 mm). RESULTS: During the study period, there were 1,981,797 (10.1%) preterm births and 58 TCs that affected at least one US county on which we had birth data. The risk of preterm birth was positively associated with TC exposure defined as peak sustained wind speed >17.2 m/s (gale-force winds or greater) [RR: 1.01 (95% CI: 0.99, 1.03); ARD: 9 (95% CI: -7, 25) per 10,000 pregnancies], distance to storm track <60 km [RR: 1.02 (95% CI: 1.01, 1.04); ARD: 23 (95% CI: 9, 38) per 10,000 pregnancies], and cumulative rainfall >100 mm [RR: 1.04 (95% CI: 1.02, 1.06); ARD: 36 (95% CI: 16, 56) per 10,000 pregnancies]. Results were comparable when considering other wind, distance, or rain thresholds. The association was more pronounced among early preterm births and mothers living in more socially vulnerable counties but did not vary across strata of other hypothesized risk factors. CONCLUSIONS: Maternal exposure to TC was associated with a higher risk of preterm birth. Our findings provide initial evidence that severe storms may trigger preterm birth.
OBJECTIVE: Hurricane Harvey made landfall on August 25, 2017 and resulted in widespread flooding in Houston and the surrounding areas. This study aimed to explore the associations between exposure to Hurricane Harvey and various mental health symptoms. METHODS: Self-reported demographics, hurricane exposure, and mental health symptomatology were obtained from residents of the greater Houston area through convenience sampling for a pilot study, 5 months after the storm from January 25-29, 2018 (N = 161). RESULTS: Increased hurricane exposure score was significantly associated with increased odds for probable depression, probable anxiety, and probable posttraumatic stress disorder after adjusting for other factors associated with mental health. No significant associations were found between demographic characteristics and risk of mental health difficulties. CONCLUSIONS: Mental health difficulties associated with exposure to Hurricane Harvey were still present 5 months after the storm. Future disaster response programs should focus on providing long-term mental health services to hurricane survivors.
Extreme temperature events (ETEs) pose a significant risk to society, especially vulnerable populations with limited access to shelter and water and those with pre-existing respiratory and cardiovascular ailments. This research examines the relationship of atmospheric circulation with a myriad of metrics related to ETEs to better understand which synoptic-scale circulations are likely to have negative health/thermal comfort outcomes. Daily sea-level pressure (SLP) and 500-hPa geopotential height (z500) data from the North American Regional Reanalysis (NARR) were used to identify circulation patterns over North America. Self-organizing maps were used to partition the variability in circulation patterns over five distinct domains covering North America for both variables. Daily 2-m temperature, 2-m dewpoint temperature, and 10-m wind data from the NARR were used to derive five major categories of ETEs based on 95th percentiles: temperature events, apparent temperature events, dew point events, and excess heat and excess cold temperature events. The relationship of circulation pattern frequencies (SOM nodes) leading up to ETEs were assessed using point biserial correlations, accounting for spatial and temporal autocorrelation. The results show that z500 has a stronger association with ETEs than does SLP. A great deal of spatial variability exists in the strength of relationship for many ETE variables with circulation patterns likely due to the local geographical influence (e.g., leeside mountain adiabatic warming and low-level maritime flow). Generally, high extremes are associated with broad ridging and anticyclonic flow and cold extremes are associated with high amplitude trough patterns with low-level flow originating from the continental interior. The use of self-organizing maps presents a unique way of examining the potential for human health risks related ETEs and may be an effective method for statistically downscaling climate model data to assess the potential for ETEs in the future.
Climate change is resulting in heatwaves that are more frequent, severe, and longer lasting, which is projected to double-to-triple the heat-related mortality in Boston, MA if adequate climate change mitigation and adaptation strategies are not implemented. A case-only analysis was used to examine subject and small-area neighborhood characteristics that modified the association between hot days and mortality. Deaths of Boston, Massachusetts residents that occurred from 2000-2015 were analyzed in relation to the daily temperature and heat index during the warm season as part of the case-only analysis. The modification by small-area (census tract, CT) social, and environmental (natural and built) factors was assessed. At-home mortality on hot days was driven by both social and environmental factors, differentially across the City of Boston census tracts, with a greater proportion of low-to-no income individuals or those with limited English proficiency being more highly represented among those who died during the study period; but small-area built environment features, like street trees and enhanced energy efficiency, were able to reduce the relative odds of death within and outside the home. At temperatures below current local thresholds used for heat warnings and advisories, there was increased relative odds of death from substance abuse and assault-related altercations. Geographic weighted regression analyses were used to examine these relationships spatially within a subset of at-home deaths with high-resolution temperature and humidity data. This revealed spatially heterogeneous associations between at-home mortality and social and environmental vulnerability factors.
High air temperatures are a public health threat, causing 1300 deaths annually in the United States (US) along with heat-related morbidity and increased electricity consumption for air-conditioning (AC). Increasing tree canopy cover has been proposed as one way to reduce urban air temperatures. Here, we assemble tree cover and developed land-cover information for 97 US cities, housing 59 million people, and use regression relationships to analyze how much current urban tree cover reduces summer (JJA) air temperatures and associated heat-related mortality, morbidity, and electricity consumption. We find that 78% of urban dwellers are in neighborhoods with less than 20% tree cover. Some 15.0 million people (25% of total) experience a reduction of 0.5-1.0 degrees C from tree cover, with another 7.9 million (13% of total) experiencing a reduction of greater than 1.0 degrees C. Current relationships between temperature and health outcomes imply that urban tree cover helps avoid 245-346 deaths annually. Heat-mortality relationships in the 1980s, when a smaller fraction of US households had AC, imply a greater role in the past for urban tree cover in avoiding heat-related mortality. As AC availability has increased, the value of tree cover for avoiding heat-related mortality has decreased, while the value of tree cover for reducing electricity consumption likely has increased. Currently, for the 97 cities studied, the total annual economic value of avoided mortality, morbidity, and electricity consumption is an estimated $1.3-2.9 billion, or $21-49 annually per capita. Applying our results to the entire US urban population, we estimate urban tree cover annually supplies heat-reduction services worth $5.3-12.1 billion.
Temperature is widely known to influence the spatio-temporal dynamics of vector-borne disease transmission, particularly as temperatures vary across critical thermal thresholds. When temperature conditions exhibit such ‘transcritical variation’, abrupt spatial or temporal discontinuities may result, generating sharp geographical or seasonal boundaries in transmission. Here, we develop a spatio-temporal machine learning algorithm to examine the implications of transcritical variation for West Nile virus (WNV) transmission in the Los Angeles metropolitan area (LA). Analysing a large vector and WNV surveillance dataset spanning 2006-2016, we found that mean temperatures in the previous month strongly predicted the probability of WNV presence in pools of Culex quinquefasciatus mosquitoes, forming distinctive inhibitory (10.0-21.0°C) and favourable (22.7-30.2°C) mean temperature ranges that bound a narrow 1.7°C transitional zone (21-22.7°C). Temperatures during the most intense months of WNV transmission (August/September) were more strongly associated with infection probability in Cx. quinquefasciatus pools in coastal LA, where temperature variation more frequently traversed the narrow transitional temperature range compared to warmer inland locations. This contributed to a pronounced expansion in the geographical distribution of human cases near the coast during warmer-than-average periods. Our findings suggest that transcritical variation may influence the sensitivity of transmission to climate warming, and that especially vulnerable locations may occur where present climatic fluctuations traverse critical temperature thresholds.
Objectives. To examine the impact of extreme heat on emergency services in Boston, MA.Methods. We conducted relative risk and time series analyses of 911 dispatches of the Boston Police Department (BPD), Boston Emergency Medical Services (BEMS), and Boston Fire Department (BFD) from November 2010 to April 2014 to assess the impact of extreme heat on emergency services.Results. During the warm season, there were 2% (95% confidence interval [CI]?=?0%, 5%) more BPD dispatches, 9% (95% CI?=?7%, 12%) more BEMS dispatches, and 10% (95% CI?=?5%, 15%) more BFD dispatches on days when the maximum temperature was 90°F or higher, which remained consistent when we considered multiple days of heat. A 10°F increase in daily maximum temperature, from 80° to 90°F, resulted in 1.016, 1.017, and 1.002 times the expected number of daily BPD, BEMS, and BFD dispatch calls, on average, after adjustment for other predictors.Conclusions. The burden of extreme heat on local emergency medical and police services may be agency-wide, and impacts on fire departments have not been previously documented.Public Health Implications. It is important to account for the societal burden of extreme heat impacts to most effectively inform climate change adaptation strategies and planning.
The impacts of heat waves in a warming climate depend not only on changing temperatures but also on changing humidity. Using 35 simulations from the Community Earth System Model Large Ensemble (CESM LENS), we investigate the long-term evolution of the joint distribution of summer relative humidity (RH) and daily maximum temperature (Tmax) near four U.S. cities (New York City, Chicago, Phoenix, and New Orleans) under the high-emissions Representative Concentration Pathway (RCP) 8.5. We estimate the conditional quantiles of RH givenTmaxwith quantile regression models, using functions of temperature for each city in July for three time periods (1990-2005, 2026-2035, and 2071-2080). Quality-of-fit diagnostics indicate that these models accurately estimate conditional quantiles for each city. As expected, each quantile ofTmaxincreases from 1990-2005 to 2071-2080, while mean RH decreases modestly. Conditional upon a fixed quantile ofTmax, the median and high quantiles of RH decrease, while those of the Heat Index (HI) and dew point both increase. This result suggests that, despite a modest decrease in median relative humidity, heat stress measured by metrics considering both humidity and temperature in a warming climate will increase faster than that measured by temperatures alone would indicate. For a fixedTmax, the high quantiles of RH (and thus of HI and dew point) increase from 1990-2005 to 2071-2080 in all four cities. This result suggests that the heat stress of a day at a givenTmaxwill increase in a warming climate due to the increase of RH.
Background: Extreme heat is associated with increased morbidity but most studies examine this relationship in warm seasons. In Southern California, Santa Ana winds (SAWs) are associated with high temperatures during the fall, winter and spring, especially in the coastal region. Objectives: Our aim was to examine the relationship between hospitalizations and extreme heat events in the fall, winter and spring, and explore the potential interaction with SAWs. Methods: Hospitalizations from 1999-2012 were obtained from the Office of Statewide Health Planning and Development Patient Discharge Data. A time-stratified case crossover design was employed to investigate the association between off-season heat and hospitalizations for various diagnoses. We examined the additive interaction of SAWs and extreme heat events on hospitalizations. Results: Over 1.5 million hospitalizations occurred in the Southern California coastal region during non-summer seasons. The 99th percentile-based thresholds that we used to define extreme heat events varied from a maximum temperature of 22.8 degrees C to 35.1 degrees C. In the fall and spring, risk of hospitalization increased for dehydration (OR: 1.23, 95% CI: 1.04, 1.45 and OR: 1.47 95% CI: 1.25, 1.71, respectively) and acute renal failure (OR: 1.35, 95% CI: 1.15, 1.58 and OR: 1.39, 95% CI: 1.19, 1.63, respectively) during 1-day extreme heat events. We also found an association between 1-day extreme heat events and hospitalization for ischemic stroke, with the highest risk observed in December. The results indicate that SAWs correspond to extreme heat events, particularly in the winter. Finally, we found no additive interaction with SAWs. Discussion: Results suggest that relatively high temperatures in non-summer months are associated with health burdens for several hospitalization outcomes. Heat action plans should consider decreasing the health burden of extreme heat events year-round.
Hot weather can cause early childbirth, meaning shorter gestation. Daily US birth-rate data from 1969 to 1988 show that deliveries increased on hot days and that those births occurred up to two weeks early. Around 25,000 infants were born early each year, representing over 150,000 gestational days lost annually. Evidence suggests that heat exposure increases delivery risk for pregnant women. Acceleration of childbirth leads to shorter gestation, which has been linked to later health and cognitive outcomes. However, estimates of the aggregate gestational losses resulting from hot weather are lacking in the literature. Here, we use estimated shifts in daily county birth rates to quantify the gestational losses associated with heat in the United States from 1969 to 1988. We find that extreme heat causes an increase in deliveries on the day of exposure and on the following day and show that the additional births were accelerated by up to two weeks. We estimate that an average of 25,000 infants per year were born earlier as a result of heat exposure, with a total loss of more than 150,000 gestational days annually. Absent adaptation, climate projections suggest additional losses of 250,000 days of gestation per year by the end of the century.
Climate change is a global threat that poses significant risks to pregnant women and to their developing fetus and newborn. Educating pregnant women about the risks to their pregnancy may improve maternal and child health outcomes. Prior research suggests that presenting health information in narrative format can be more effective than a didactic format. Hence, the purpose of this study was to test the effectiveness of two brief educational interventions in a diverse group of pregnant women (n = 151). Specifically, using a post-test only randomized experiment, we compared the effectiveness of brief information presented in a narrative format versus a didactic format; both information formats were also compared to a no information control group. Outcome measures included pregnant women’s actual and perceived knowledge, risk perception, affective assessment, self-efficacy, intention to take protective behaviors, and subsequent information seeking behavior. As hypothesized, for all outcome measures, the narrative format was more effective than the didactic format. These results suggest the benefits of a narrative approach (versus a didactic approach) to educating pregnant women about the maternal and child health threats posed by climate change. This study adds to a growing literature on the effectiveness of narrative-based approaches to health communication.
Exposure to high ambient temperatures is an important cause of avoidable, premature death that may become more prevalent under climate change. Though extensive epidemiological data are available in the United States, they are largely limited to select large cities, and hence, most projections estimate the potential impact of future warming on a subset of the U.S. population. Here we utilize evaluations of the relative risk of premature death associated with temperature in 10 U.S. cities spanning a wide range of climate conditions to develop a generalized risk function. We first evaluate the performance of this generalized function, which introduces substantial biases at the individual city level but performs well at the large scale. We then apply this function to estimate the impacts of projected climate change on heat-related nationwide U.S. deaths under a range of scenarios. During the current decade, there are 12,000 (95% confidence interval 7,400-16,500) premature deaths annually in the contiguous United States, much larger than most estimates based on totals for select individual cities. These values increase by 97,000 (60,000-134,000) under the high-warming Representative Concentration Pathway (RCP) 8.5 scenario and by 36,000 (22,000-50,000) under the moderate RCP4.5 scenario by 2100, whereas they remain statistically unchanged under the aggressive mitigation scenario RCP2.6. These results include estimates of adaptation that reduce impacts by ~40-45% as well as population increases that roughly offset adaptation. The results suggest that the degree of climate change mitigation will have important health impacts on Americans.
Hurricane Katrina caused unprecedented flood damage to New Orleans, Louisiana, and has been the costliest hurricane in US history. We analyzed the environmental and public health outcomes of Hurricane Katrina by using Internet searches to identify epidemiological, sociodemographic, and toxicological measurements provided by regulatory agencies.Atmospheric scientists have now warned that global warming will increase the proportion of stronger hurricanes (categories 4-5) by 25% to 30% compared with weaker hurricanes (categories 1-2).With the new $14.6 billion Hurricane Storm Damage Risk Reduction System providing a 100-year storm surge-defensive wall across the Southeast Louisiana coast, New Orleans will be ready for stronger storms in the future.
Particularly in rural settings, there has been little research regarding the health impacts of fine particulate matter (PM2.5) during the wildfire season smoke exposure period on respiratory diseases, such as influenza, and their associated outbreaks months later. We examined the delayed effects of PM2.5 concentrations for the short-lag (1-4 weeks prior) and the long-lag (during the prior wildfire season months) on the following winter influenza season in Montana, a mountainous state in the western United States. We created gridded maps of surface PM2.5 for the state of Montana from 2009 to 2018 using spatial regression models fit with station observations and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness data. We used a seasonal quasi-Poisson model with generalized estimating equations to estimate weekly, county-specific, influenza counts for Montana, associated with delayed PM2.5 concentration periods (short-lag and long-lag effects), adjusted for temperature and seasonal trend. We did not detect an acute, short-lag PM2.5 effect nor short-lag temperature effect on influenza in Montana. Higher daily average PM2.5 concentrations during the wildfire season was po- sitively associated with increased influenza in the following winter influenza season (expected 16% or 22% increase in influenza rate per 1 mu g/m(3) increase in average daily summer PM2.5 based on two analyses, p = 0.04 or 0.008). This is one of the first observations of a relationship between PM2.5 during wildfire season and influenza months later.
West Nile virus (WNV) has consistently been reported to be associated with human cases of illness in the region near Chicago, Illinois. However, the number of reported cases of human illness varies across years, with intermittent outbreaks. Several dynamic factors, including temperature, rainfall, and infection status of vector mosquito populations, are responsible for much of these observed variations. However, local landscape structure and human demographic characteristics also play a key role. The geographic and temporal scales used to analyze such complex data affect the observed associations. Here, we used spatial and statistical modeling approaches to investigate the factors that drive the outcome of WNV human illness on fine temporal and spatial scales. Our approach included multi-level modeling of long-term weekly data from 2005 to 2016, with weekly measures of mosquito infection, human illness and weather combined with more stable landscape and demographic factors on the geographical scale of 1000m hexagons. We found that hot weather conditions, warm winters, and higher MIR in earlier weeks increased the probability of an area of having a WNV human case. Higher population and the proportion of urban light intensity in an area also increased the probability of observing a WNV human case. A higher proportion of open water sources, percentage of grass land, deciduous forests, and housing built post 1990 decreased the probability of having a WNV case. Additionally, we found that cumulative positive mosquito pools up to 31 weeks can strongly predict the total annual human WNV cases in the Chicago region. This study helped us to improve our understanding of the fine-scale drivers of spatiotemporal variability of human WNV cases.
Hurricane Harvey has been recorded as the wettest cyclone in United States history, resulting in devastating and catastrophic flooding for the Texas Gulf Coast. The nature of the path of the hurricane, with multiple landfalls along the Texas Gulf Coast, resulted in the largest aerial mosquito control effort for one single storm. Two mosquito control contractors and the Air Force Aerial Spray Unit of the US Air Force Reserve were used to aerial treat 6,765,971 acres (3,075,441 ha) in 29 of the 60 disaster-declared counties in Texas. During the response, 101,253 liters of Dibrom® (active ingredient [AI]: naled) and 48,735 liters of Duet™ (AI: 1% prallethrin and 5% sumithrin) were used. In 23/29 counties requesting aerial spraying, mosquito control contractors were used to conduct pre- and postaerial application mosquito surveillance. The remaining 6 counties conducted their own surveillance during the response. A total of 105,153 mosquitoes in 7 genera and 35 species were collected during this response with the major floodwater nuisance mosquito being Psorophora columbiae. The most abundant vector mosquito collected was Culex nigripalpus. Duet at the 0.8% and 1% application rates resulted in 49% and 69% control of Ps. columbiae, respectively. Dibrom application resulted in 95% and 93% control of Ps. Columbia and Cx. nigripalpus populations, respectively.
Objective: Dissociation and trauma have a well-documented relationship, and dissociation is assumed to result from trauma exposure. If trauma generates dissociative psychopathology, it should be observed after exposure to disaster and be associated with disaster-related psychopathology. Few studies have focused specifically on dissociation as an outcome of disaster trauma. This study examined dissociation and its association with disaster-related psychopathology in survivors of five different disasters. Methods: In the first 6 postdisaster months, directly exposed survivors (N = 216) of mass shootings, floods, or a firestorm completed structured diagnostic interviews providing lifetime predisaster and postdisaster prevalent/incident psychiatric diagnoses and the Dissociative Experiences Scale (DES) 1-3 years after baseline. Results: DES scores were very low; only 1% met the DES Taxon signifying pathological dissociation. In multivariate models including predisaster lifetime major depression, lifetime panic disorder, lifetime generalized anxiety disorder, and lifetime alcohol use disorder; disaster-related PTSD; and number of incident somatoform symptoms as independent covariates, predisaster lifetime major depression and alcohol use disorder were independently associated with both general (DES score) and pathological (DES Taxon) dissociation, and postdisaster incident somatization symptoms were also associated with general dissociation, but postdisaster psychopathology including disaster-related PTSD was not associated with general or pathological dissociation. Conclusions: Neither general nor pathological dissociation was independently associated with disaster-related PTSD or other incident psychopathology. The only psychiatric disorders associated with dissociation were present before the disasters. Coupled with the low dissociation rates, these findings indicate that dissociation does not appear to be a mental health outcome of disaster trauma.
Flooding displaces large populations each season, which potentially increases the exposure of the vulnerable societies. Having failed to curve down the number of people infected with COVID-19 in the first wave of the pandemic, many states in the United States (U.S.) are now at high risk of the concurrence of the two disasters. Assessing this compound risk before the country enters the flood season is of vital importance. Therefore, we provide a prompt tool to assess the compound risk of COVID-19 at the county level over the U.S. We find that (1) the number of flood insurance house claims can proxy the displaced population accurately with more spatiotemporal detail, and (2) the high-risk areas of both flooding and COVID-19 are concentrated along the southern and eastern coasts and some parts of the Mississippi River. Our findings may trigger the interest of further exploring the topics related to the concurrence of COVID-19 and flooding.
From 2011 through 2018, there was a notable increase in sporadic Legionnaires’ disease in the state of Minnesota. Sporadic cases are those not associated with a documented outbreak. Outbreak-related cases are typically associated with a common identified contaminated water system; sporadic cases typically do not have a common source that has been identified. Because of this, it is hypothesised that weather and environmental factors can be used as predictors of sporadic Legionnaires’ disease. An ecological design was used with case report surveillance data from the state of Minnesota during 2011 through 2018. Over this 8-year period, there were 374 confirmed Legionnaires’ disease cases included in the analysis. Precipitation, temperature and relative humidity (RH) data were collected from weather stations across the state. A Poisson regression analysis examined the risk of Legionnaires’ disease associated with precipitation, temperature, RH, land-use and age. A lagged average 14-day precipitation had the strongest association with Legionnaires’ disease (RR 2.5, CI 2.1-2.9), when accounting for temperature, RH, land-use and age. Temperature, RH and land-use also had statistically significant associations to Legionnaires’ disease, but with smaller risk ratios. This study adds to the body of evidence that weather and environmental factors play an important role in the risk of sporadic Legionnaires’ disease. This is an area that can be used to target additional research and prevention strategies.
Wildfire smoke (WFS) increases the risk of respiratory hospitalizations. We evaluated the association between WFS and asthma healthcare utilization (AHCU) during the 2013 wildfire season in Oregon. WFS particulate matter <= 2.5 mu m in diameter (PM2.5) was estimated using a blended model of in situ monitoring, chemical transport models, and satellite-based data. Asthma claims and place of service were identified from Oregon All Payer All Claims data from 1 May 2013 to 30 September 2013. The association with WFS PM2.5 was evaluated using time-stratified case-crossover designs. The maximum WFS PM2.5 concentration during the study period was 172 mu g/m(3). A 10 mu g/m(3) increase in WFS increased risk in asthma diagnosis at emergency departments (odds ratio [OR]: 1.089, 95% confidence interval [CI]: 1.043-1.136), office visit (OR: 1.050, 95% CI: 1.038-1.063), and outpatient visits (OR: 1.065, 95% CI: 1.029-1.103); an association was observed with asthma rescue inhaler medication fills (OR: 1.077, 95% CI: 1.065-1.088). WFS increased the risk for asthma morbidity during the 2013 wildfire season in Oregon. Communities impacted by WFS could see increases in AHCU for tertiary, secondary, and primary care.
More than 330 million people around the world suffer from asthma, a chronic respiratory disease that is produced by environmental conditions such as air pollution, mold, and seasonal change. In Philadelphia, Pennsylvania, high asthma prevalence rates and poor asthma control is attributed to urban air pollution and substandard housing, both of which will be made worse by climate change in the Mid-Atlantic region. Climate change will increase air pollution, worsen indoor environmental conditions, and bring more unpredictable weather, all of which will make asthma more difficult to manage. This article describes a public education project designed to teach vulnerable local communities about climate change and its impact on asthma management. The Climate Ready Philly project provided basic information on the mechanisms of global climate change, presented research on how climate change would impact the city of Philadelphia, and facilitated hands-on activities to help workshop participants learn what they could do to address climate change at home. Our workshops paired healthy homes and energy efficiency strategies, for example, to explore relationships between outdoor and indoor environments, as well as impacts on occupant health. By utilizing climate learning science, our workshops allowed participants to explore relationships between existing health and environmental conditions-such as asthma-and the anticipated impacts of climate change. Using surveys, interviews, and ethnographic data collection, we found that more resources are needed to repair housing infrastructure and help low-income community members access resources that can improve indoor air quality. We conclude by highlighting the need for climate adaptation programs that provide support for housing, in addition to other public infrastructures, which will be needed to reduce the burden of asthma in Philadelphia.
Defining vulnerability and identifying vulnerable areas and populations is critical to climate adaptation and resilience. Neighbourhoods are not homogeneous in terms of their socio-economic and physical vulnerability to flooding and other climate related impacts resulting in diverse challenges. Working with communities to better identify their concerns, liabilities, and strengths in the face of climate challenges will help build resiliency for all residents of the Tampa Bay area. This research identifies the weaknesses in knowledge, preparedness and ability to adapt in two communities in Pinellas County, Florida: examining a neighbourhood that is socio-economically vulnerable and a neighbourhood that experiences only physical (locational) vulnerability. We also identify opportunities for inclusive disaster planning, climate adaptation plans and to increase resiliency through long-term interactions between residents, community leaders, and local officials.
RATIONALE: Unprecedented heatwaves over the past several years are getting worse with longer duration in the course of global warming. Heatstroke is a medical emergency with multiple organ involvement and life-threatening illness with a high mortality rate of up to 71%. Uncontrolled damage to the central nervous system can result in severe cerebral edema, permanent neurological sequelae, and death. However, regarding the therapeutic aspects of heat stroke, there was no therapeutic strategy after the rapid cooling of the core body temperature to <39°C to prevent further injury. PATIENT CONCERNS: Each of 3 patients developed a change of mental statuses after the exposure to summer heatwaves or relatively high environmental temperatures with high humidity in the sauna. DIAGNOSES: The patients were diagnosed with severe heatstroke since they showed cerebral edema and multiple organ dysfunction based on the results from laboratory tests and the findings in brain computed tomography scan. INTERVENTIONS: The patients underwent induced therapeutic hypothermia (<36°C) between 24 and 36?hours in the management of severe heatstroke. OUTCOMES: The patients survived from cerebral edema and multiple organ dysfunction. LESSONS: We believe that targeted temperature management (<36°C) will help treat severe heatstroke. Thus it should be considered for reducing the chance of development of complications in multiple organs, especially in the central nervous system, when managing patients with severe heatstroke.
BACKGROUND: For the past decade, hand, foot and mouth disease (HFMD), caused by entero and coxsackie viruses, has been spreading in Asia, particularly among children, overloading healthcare settings and creating economic hardships for parents. Recent studies have found meteorological factors, such as temperature, are associated with HFMD in Asia. However, few studies have explored the relationship in the United States, although HFMD cases have steadily increased recently. As concerns of climate change grow, we explored the association between temperature and HFMD admissions to the Emergency Department (ED) in California. METHODS: Weekly counts of HFMD for 16 California climate zones were collected from 2005 to 2013. We calculated weekly temperature for each climate zone using an inverse distance-weighting method. For each climate zone stratified by season, we conducted a time-series using Poisson regression models. We adjusted models for weekly averaged relative humidity, average number of HFMD cases in previous weeks and long-term temporal trends. Climate zone estimates were combined to obtain an overall seasonal estimate. We attempted stratified analyses by region, race/ethnicity, and sex to identify sensitive subpopulations. RESULTS: Risk of ED visits for HFMD per 1 °F increase in mean temperature during the same week increased 2.00% (95% confidence intervals 1.15, 2.86%) and 2.35% (1.38, 3.33%) during the warm and cold seasons, respectively. The coastal region showed a higher, though not statistically different, association during the cold season [3.18% (1.99, 4.39)] than the warm season [1.64% (0.47, 2.82)]. CONCLUSIONS: Our findings indicated an association between temperature and ED visits for HFMD, with variation by season and region. Thus, the causative pathogen’s ability to persist in the atmosphere may vary by season. Furthermore, the mild and wet winter in the coastal region of California may contribute to different results than studies in Asia. With the onset of climate change, HFMD cases will likely grow in California, warranting further investigation on this relationship, including new populations at-risk.
This study estimates the association between temperature and self-reported mental health. We match individual-level mental health data for over three million Americans between 1993 and 2010 to historical daily weather information. We exploit the random fluctuations in temperature over time within counties to identify its effect on a 30-day measure of self-reported mental health. Compared to the temperature range of 60-70°F, cooler days in the past month reduce the probability of reporting days of bad mental health while hotter days increase this probability. We also find a salience effect: cooler days have an immediate effect, whereas hotter days tend to matter most after about 10 days. Using our estimates, we calculate the willingness to pay to avoid an additional hot day in terms of its impact on self-reported mental health.
Identifying ecological drivers of disease transmission is central to understanding disease risks. For vector-borne diseases, temperature is a major determinant of transmission because vital parameters determining the fitness of parasites and vectors are highly temperature-sensitive, including the extrinsic incubation period required for parasites to develop within the vector. Temperature also underlies dramatic differences in the individual-level variation in the extrinsic incubation period, yet the influence of this variation in disease transmission is largely unexplored. We incorporate empirical estimates of dengue virus extrinsic incubation period and its variation across a range of temperatures into a stochastic model to examine the consequences for disease emergence. We find that such variation impacts the probability of disease emergence because exceptionally rapid, but empirically observed incubation – typically ignored by modelling only the average – increases the chance of disease emergence even at the limits of the temperature range for dengue transmission. We show that variation in the extrinsic incubation period causes the greatest proportional increase in the risk of disease emergence at cooler temperatures where the mean incubation period is long, and associated variation is large. Thus, ignoring EIP variation will likely lead to underestimation of the risk of vector-borne disease emergence in temperate climates.
As heat waves become more extreme, there is a growing concern for the health of elderly city dwellers who have poor living conditions and limited access to resources. Much research has documented socioeconomic links to heat vulnerability, but limited studies have investigated the detailed living conditions of vulnerable populations, despite increasing requests from local communities. In this paper, we examine the summertime thermal performance of 24 senior apartments within 3 public housing sites (2 conventional multifamily and 1 LEED-rated building), and the seniors’ adaptive responses in Elizabeth, NJ, USA. Time-series data were collected from sensors, interviews and observations on the thermal environment and behavior, from May-October 2017. Our multi-level, occupant-centric approach utilizes the indoor heat index as a proxy for heat stress, against site and building characteristics, and environmental and personal variables. Panel regressions show thermal variations among sites/apartments and illustrate the significant effect of actions, such as window opening and air conditioner use. Results also show how the seniors’ adaptive responses vary by site; residents with central air-conditioning use it, while residents from the two older sites engage in a wider range of adaptive actions, and in some cases achieve similar indoor heat indexes as apartments from the green building. Indoor heat stress experienced by low-income seniors can be greatly reduced through cost-effective strategies that target individual behaviors and outdoor amenities. This implies the need for integrated solutions to the heat waves problem across scales; including changes to residents’ habits, building envelopes, building operations, and outdoor spaces.
Extreme wildfire events are becoming more common and while the immediate risks of particulate exposures to susceptible populations (i.e., elderly, asthmatics) are appreciated, the long-term health effects are not known. In 2017, the Seeley Lake (SL), MT area experienced unprecedented levels of wildfire smoke from July 31 to September 18, with a daily average of 220.9 mu g/m(3). The aim of this study was to conduct health assessments in the community and evaluate potential adverse health effects. The study resulted in the recruitment of a cohort (n= 95, average age: 63 years), for a rapid response screening activity following the wildland fire event, and two follow-up visits in 2018 and 2019. Analysis of spirometry data found a significant decrease in lung function (FEV1/FVC ratio: forced expiratory volume in first second/forced vital capacity) and a more than doubling of participants that fell below the lower limit of normal (10.2% in 2017 to 45.9% in 2018) one year following the wildfire event, and remained decreased two years (33.9%) post exposure. In addition, observed FEV(1)was significantly lower than predicted values. These findings suggest that wildfire smoke can have long-lasting effects on human health. As wildfires continue to increase both here and globally, understanding the health implications is vital to understanding the respiratory impacts of these events as well as developing public health strategies to mitigate the effects.
Heat waves have pronounced impacts on human health, ecosystems, and society. Heat waves have become more frequent and intense globally and are likely to intensify further in a warming climate. Across the United States there is a warming trend in average surface temperatures, but concordant increase in heat wave severity appears absent. Limitations in heat waves studies may be responsible for limited detection of a heat wave warming signal. We track daily spatiotemporal evolution of heat waves using geometric concepts and clustering algorithms to investigate how heat manifests on the land surface. We develop a spatial metric combining heat wave frequency, magnitude, duration, and areal extent. We find mixed trends in some individual heat wave characteristics across the United States during 1981-2018. However, exploration of the spatiotemporal evolution of combined heat wave characteristics shows considerable increases during this period and indicates a substantial increase in heat wave hazard across the United States.
The causes and consequences of indoor heat exposure are receiving growing attention as global temperature rises and people seek respite from the heat in indoor spaces. In this study, we measured indoor temperatures of 46 air-conditioned residences in Phoenix, Arizona, United States. Temperatures were collected concurrently at 5-min intervals from August 21 to September 19, 2016. Indoor temperatures exhibited significant heterogeneity across all residences, ranging from 16.5 to 37.2 degrees C with a mean (SD) of 26.4 degrees C (2.2 degrees C). On average, the 5-min indoor temperatures were moderately correlated with outdoor temperature (r = 0.421), although individual household correlations were highly variable, ranging from r = -0.244 to r = 0.924. Households were grouped into six clusters using K-means based on 19 temperature metrics. We tested for differences in demographic, behavior, and infrastructure indicators between those six clusters based on responses to a social survey. Nearly half the variance in preferred thermostat setting was explained by cluster (R-2 = 0.455, p < .001). For the most part, measures of air-conditioning use, limitations on air-conditioning use, and household resources (e.g., income) did not vary significantly by cluster. The same was true for heat-related health and comfort outcomes. Two households that did not pay their own electric bill were by far the coldest homes (average temperature of 20.0 degrees C). We conclude that indoor temperature preference may supersede concerns related to the cost of using air-conditioning and that resource-constrained households may be sacrificing other necessities to keep their homes comfortable.
Using our professional experiences with natural disaster relief, as well as existing theory, the authors introduce an equity-oriented framework -Social Justice Disaster Relief, Counseling, and Advocacy. We then present the case of the 2017 Northern California wildfires using responses from 259 individuals who were living in the region of the Northern California wildfires – the most destructive fires in California state history. We collected qualitative and demographic data on each participant 3 months after the fires ended. Qualitative data included detailed written reflections to a prompt from each participant in response to an online questionnaire. A thematic analysis using open, axial, and selective coding was conducted to gain a deeper understanding of the context, circumstances, and outcomes of recurring themes, concepts, categories, and their relationship to core themes. Results reveal six themes including: loss and displacement; physical and psychological impact; exploitation; social inequities against vulnerable communities; community strengths and support; and the need for support and services. The themes highlight essential directions for Counseling Psychologists working with survivors of a natural disaster. We offer recommendations for training, theory, counseling, and research, as a means for supporting and advocating for clients psychologically, socially, and emotionally in the context of a natural disaster.
Wildfires constitute a serious threat for both the environment and human well-being. The US fire policy aims to tackle this problem, devoting a sizeable amount of resources and resorting extensively to fire suppression strategies. The theoretical literature has established a link between climate conditions and wildfire incidence. Using state-level data from 2002 to 2013 for the USA, this work proposes a wildfire incidence indicator and runs a generalized spatial ordered probit model in order to test the findings of the previous literature empirically. Moreover, this article investigates the extent of spatial spillovers in the climatic covariates. The results highlight a significant impact of precipitation and temperature on fire incidence and provide some evidence of the role of spatial spillovers. In particular, transitions from lower to higher wildfire incidence levels are significantly encouraged by increases in local temperature and significantly discouraged by increases in both local precipitation and lagged precipitation. The present analysis complements the recent literature, confirming the previous findings with a solid empirical investigation and offering a policy-oriented picture of wildfire risks all over the USA.
Heat-related illness, an environmental exposure-related outcome commonly treated in U.S. hospital emergency departments (ED), is likely to rise with increased incidence of heat events related to climate change. Few studies demonstrate the spatial and statistical relationship of social vulnerability and heat-related health outcomes. We explore relationships of Georgia county-level heat-related ED visits and mortality rates (2002–2008), with CDC’s Social Vulnerability Index (CDC SVI). Bivariate Moran’s I analysis revealed significant clustering of high SVI rank and high heat-related ED visit rates (0.211, p <0.001) and high smoothed mortality rates (0.210, p <0.001). Regression revealed that for each 10% increase in SVI ranking, ED visit rates significantly increased by a factor of 1.18 (95% CI ¼1.17–1.19), and mortality rates significantly increased by a factor of 1.31 (95% CI ¼1.16–1.47). CDC SVI values are spatially linked and significantly associated with heat-related ED visit, and mortality rates in Georgia.
Heat is known to cause illness and death not only at extreme temperatures, but also at moderate levels. Although substantial research has shown how summertime temperature distributions have changed over recent decades in the United States, less is known about howthe heat index-a potentially more health applicable metric of heat-has similarly evolved over this period. Moreover, the extent to which these distributional changes have overlapped with indicators of social vulnerability has not been established, despite the applicability of co-varying climatic and sociodemographic characteristics to heat-related health adaptations. Presented here is an analysis of trends in the median, 95th percentile, and ‘warm-tail spread’ (i.e., intra-seasonal range between the upper extreme andmedian) of warm-season (May-September) maximum heat index between 1979 and 2018 across the conterminous US. Using 40 years of data from the North American Regional Reanalysis dataset, it is shown that most of the US has experienced statistically significant positive trends in summertime heat, and that both the magnitude of trends and the shape of the frequency distributions of these measures vary regionally. Comparisons with data from the Social Vulnerability Index show that the most socially vulnerable counties appear to be warming faster than the least vulnerable, but that opposite patterns hold for trends in warm-tail spread. These findings may be applicable to further studies on climate change, heat adaptations, and environmental justice in the US.
Many of the six million residents of unincorporated communities in the United States depend on well-water to meet their needs. One group of unincorporated communities is the colonias, located primarily in several southwestern U.S. states. Texas is home to the largest number of these self-built communities, of mostly low-income families, lacking basic infrastructure. While some states have regulations that mandate minimum infrastructure for these communities, water and sewage systems are still lacking for many of their residents. Unprotected wells and self-built septic/cesspool systems serve as the primary infrastructure for many such colonias. This research was designed to probe how wells and septic/cesspool systems are influenced by heavy rainfall events. Such events are hypothesized to impact water quality with regard to human health. Inorganic and microbiological water quality of the wells in nine colonias located in Nueces County, Texas, were evaluated during dry and wet periods. Nueces County was selected as an example based on its flooding history and the fact that many colonias there depend entirely on well-water and septic/cesspool systems. The results demonstrate that well-water quality in these communities varies seasonally with respect to arsenic (up to 35 ?g/L) and bacterial contamination (Escherichia coli), dependent on the amount of rainfall, which leaves this population vulnerable to health risks during both wet and dry periods. Microbial community analyses were also conducted on selected samples. To explore similar seasonal contamination of well-water, an analysis of unincorporated communities, flooding frequency, and arsenic contamination in wells was conducted by county throughout the United States. This nationwide analysis indicates that unincorporated communities elsewhere in the United States are likely experiencing comparable challenges for potable water access because of a confluence of socioeconomic, infrastructural, and policy realities.
Repeated exposure to hurricanes and tropical storms likely impacts the mental and physical health of populations living along the U.S. Gulf Coast. In this study, the self-rated physical and mental health of residents in the U.S. Gulf Coast was estimated and factors associated with differences in self-rated health were identified. The 12-item Short Form Health Survey (SF-12) was administered online to a sample of 3030 residents of the U.S. Gulf Coast in December 2017. Responses were scored to calculate mental component summary scores and physical component summary scores. Multiple linear regression models were fitted to identify predictors of self-rated health among the residents. Residents of U.S. Gulf Coast States have poorer self-rated physical and mental health compared to the U.S. population. Women and respondents reporting higher perception of flood risk had worse self-rated mental health, while hurricane evacuees, adults of at least 25 years of age, those with self-reported hurricane damage, and respondents reporting higher perception of surge risk had worse self-rated physical health. Residents of U.S. Gulf Coast States have poorer self-rated health compared to national standards. These findings may have practical implications for hurricane-associated physical and mental health services planning and delivery.
This study combines wearable sensors, weather data, and self-reported mood surveys to assess mental stress on older adults from heat experience. It is designed as a pilot and feasibility study in preparation for a large-scale experiment of older adults; mental wellbeing during extreme heat events. Results show that on-body temperatures from two i-Button sensors coupled with heart rate monitored from a smart watch are important indicators to evaluate individualized heat stress given a relatively uniform outdoor temperature. Furthermore, assessing their mood in their own environment demonstrates potential for understanding mental wellbeing that can change with varying time and location.
The frequency and intensity of heat waves in the United States is projected to increase in the 21st century. We investigate dry and humid heat waves in a pair of high-resolution model simulations that constrain large-scale atmospheric circulation, to isolate the thermodynamic impacts on characteristics of present and future heat waves over the United States. The two kinds of heat waves show differences in mean intensity, amplitude, duration, and frequency over the Southeast, Northeast, and Midwest, while their characteristics are largely similar in the drier central and western United States. In a warmer climate, relative humidity is projected to decrease during dry heat waves, whereas it remains unchanged during humid heat waves. However, the overall increase in daily maximum temperature intensifies the heat stress during future humid and dry heat waves across all regions. With large-scale circulation constrained, these simulations emphasize the importance of thermodynamic drivers in determining future heat wave characteristics.
BACKGROUND: As climate change increases global temperatures, heat-related morbidity and mortality are projected to rise. Outdoor workers and those who perform exertional tasks are particularly susceptible to heat-related illness (HRI). Using workers’ compensation data, we aimed to describe rates of occupational HRI in California and identify demographic and occupational risk factors to inform prevention efforts. METHODS: We identified HRI cases during 2000-2017 in the California Workers’ Compensation Information System (WCIS) using International Classification of Diseases Ninth and Tenth Revision codes, WCIS nature and cause of injury codes, and HRI keywords. We assigned industry and occupation codes using the NIOSH Industry and Occupation Computerized Coding System (NIOCCS). We calculated HRI rates by sex, age group, year, county, industry, and occupation, and estimated confidence intervals using generalized linear models. RESULTS: We identified 15,996 HRI cases during 2000-2017 (6.0 cases/100,000 workers). Workers aged 16-24 years had the highest HRI rate (7.6) among age groups, and men (8.1) had a higher rate than women (3.5). Industry sectors with the highest HRI rates were Agriculture, Farming, Fishing, and Forestry (38.6), and Public Administration (35.3). Occupational groups with the highest HRI rates were Protective Services (56.6) and Farming, Fishing, and Forestry (36.6). Firefighters had the highest HRI rate (389.6) among individual occupations. CONCLUSIONS: Workers in certain demographic and occupational groups are particularly susceptible to HRI. Additional prevention efforts, including outreach and enforcement targeting high-risk groups, are needed to reduce occupational HRI. Workers’ compensation data can provide timely information about temporal trends and risk factors for HRI.
Morbidity and mortality impacts of extreme heat amplified by climate change will be unequally distributed among communities given pre-existing differences in socioeconomic, health, and environmental conditions. Many governments are interested in adaptation policies that target those especially vulnerable to the risks, but there are important questions about how to effectively identify and support communities most in need of heat adaptations. Here, we use an equity-oriented adaptation program from the state of California as a case study to evaluate the implications of the currently used environmental justice index (CalEnviroScreen 3.0) for the identification of socially vulnerable communities with climate change adaptation needs. As CalEnviroScreen is geared towards air and water pollution, we assess how community heat risks and adaptation needs would be evaluated differently under two more adaptation-relevant vulnerability indices: the Social Vulnerability Index and the Heat-Health Action Index. Our analysis considers communities at the census tract scale, as well as the patterns emerging at the regional scale. Using the current index, the state designates 25% of its census tracts as “disadvantaged” communities eligible for special adaptation funds. However, an additional 12.6% of the state’s communities could be considered vulnerable if the two other indices were considered instead. Only 13.4% of communities are vulnerable across all three vulnerability indices studied. Choice of vulnerability index shapes statewide trends in extreme heat risk and is linked to a community’s likelihood of receiving heat-related California Climate Investments (CCI) projects. Tracts that are vulnerable under the current pollution-focused index, but not under the heat-health specific index, received four times the number of heat-related interventions as tracts vulnerable under the reverse scenario. This study demonstrates important nuances relevant to implementing equity-oriented adaptation and explores the challenges, trade-offs, and opportunities in quantifying vulnerability.
Fine particulate matter (PM2.5) raises human health concerns since it can deeply penetrate the respiratory system and enter the bloodstream, thus potentially impacting vital organs. Strong winds transport and disperse PM2.5, which can travel over long distances. Smoke from wildfires is a major episodic and seasonal hazard in Southern California (SoCal), where the onset of Santa Ana winds (SAWs) in early fall before the first rains of winter is associated with the region’s most damaging wildfires. However, SAWs also tend to improve visibility as they sweep haze particles from highly polluted areas far out to sea. Previous studies characterizing PM2.5 in the region are limited in time span and spatial extent, and have either addressed only a single event in time or short time series at a limited set of sites. Here we study the space-time relationship between daily levels of PM2.5 in SoCal and SAWs spanning 1999-2012 and also further identify the impact of wildfire smoke on this relationship. We used a rolling correlation approach to characterize the spatial-temporal variability of daily SAW and PM2.5. SAWs tend to lower PM2.5 levels, particularly along the coast and in urban areas, in the absence of wildfires upwind. On the other hand, SAWs markedly increase PM2.5 in zip codes downwind of wildfires. These empirical relationships can be used to identify windows of vulnerability for public health and orient preventive measures.
Reducing the impacts and risk of weather hazards requires better knowledge of the regions that are most affected in terms of economic damage, fatality and injury. While understanding of weather hazards has greatly improved, regional vulnerability to weather hazards of various types has not been well assessed in the United States. Through a compilation of event-based records of eight types of weather hazards for 1996-2016 at the national, regional and state levels, our analysis shows large differences in the change trends in economic damage, fatality and injury caused by drought, coastal flood, hail and wildfire, demonstrating the inconsistent responses of economic and human systems to weather hazards of various types at the state level. Despite a general increase in annual occurrences, spatial analysis shows that vulnerability to tornado and hail has decreased significantly in most of the country. Our results have great implications for adaptation and mitigation strategies, through identifying the vulnerable regions and types of hazards that require more urgent efforts for reducing economic and human losses. It is, however, important to keep in mind that the results may depend on the records, indicators and time periods used for the analysis.
A small number of studies suggest atmospheric particulate matter with diameters 2.5 micron and smaller (PM(2.5)) may possibly play a role in the transmission of influenza and influenza-like illness (ILI) symptoms. Those studies were predominantly conducted under moderately to highly polluted outdoor atmospheres. The purpose of this study was to extend the data set to include a less polluted atmospheric environment. A relationship between PM2.5 and ILI activity extended to include lightly to moderately polluted atmospheres could imply a more complicated mechanism than that suggested by existing studies. We obtained concurrent PM(2.5) mass concentration data, meteorological data and reported Influenza and influenza-like illness (ILI) activity for the light to moderately polluted atmospheres over the Tucson, AZ region. We found no relation between PM2.5 mass concentration and ILI activity. There was an expected relation between ILI, activity, temperature, and relative humidity. There was a possible relation between PM2.5 mass concentration anomalies and ILI activity. These results might be due to the small dataset size and to the technological limitations of the PM measurements. Further study is recommended since it would improve the understanding of ILI transmission and thereby improve ILI activity/outbreak forecasts and transmission model accuracies.
Parks benefit public health in many ways, from improving stormwater management to mitigating disparities associated with physical and mental health. Parks and recreational areas can be adversely impacted by disasters. Perceptions of postdisaster environmental contamination of parks can limit residents’ willingness to use parks and thus their benefits. In this study, teams of trained interviewers surveyed residents in Houston, Texas, who were using parks in the months following Hurricane Harvey. Data about resident perception of and emotional response to environmental pollution, as well as self-rated postdisaster mental and physical health, were collected. Respondents felt certain that Hurricane Harvey caused environmental contamination in their communities and that this contamination would impact health. Of respondents, 40% reported anger, while only 21.4% felt afraid. Survey respondents had significantly lower mental health composite scores than a national comparison group. Although residents report strong concerns and need information about hurricane-associated environmental contamination, little data have been collected or made available to residents by federal or state agencies. The use of recreational areas for flood mitigation potentially exposes residents to environmental contamination after flooding. More information is needed about risks to health from these exposures.
Non-point stormwater runoff is a major contamination source of receiving waterbodies. Heightened incidence of waterborne disease outbreaks related to recreational use and source water contamination is associated with extreme rainfall events. Such extreme events are predicted to increase in some regions due to climate change. Consequently, municipal separate storm sewer systems (MS4s) conveying pathogens to receiving waters are a growing public health concern. In addition, the spread of antibiotic resistance genes (ARGs) and antibiotic resistant bacteria in various environmental matrices, including urban runoff, is an emerging threat. The resistome and microbiota profile of MS4 discharges has yet to be fully characterized. To address this knowledge gap, we first analyzed the relationship between rainfall depth and intensity and E. coli densities (fecal indicator) in stormwater from four MS4 outflows in Columbus, Ohio, USA during the spring and summer of 2017. Microbial source tracking (MST) was conducted to examine major fecal contamination sources in the study sewersheds. A subset of samples was analyzed for microbial and resistome profiles using a metagenomic approach. The results showed a significant positive relationship between outflow E. coli density and rainfall intensity. MST results indicate prevalent fecal contamination from ruminant populations in the study sites (91% positive among the samples tested). Protobacteria and Actinobacteria were two dominant bacteria at a phylum level. A diverse array of ARGs and potentially pathogenic bacteria (e.g. Salmonella enterica Typhimurium), fungi (e.g. Scedosporium apiospermum), and protists (e.g. Acanthamoeba palestinensis) were found in urban stormwater outflows that discharge into adjacent streams. The most prevalent ARGs among samples were ?-lactam resistance genes and the most predominant virulence genes within bacterial community were related with Staphylococcus aureus. A comprehensive contamination profile indicates a need for sustainable strategies to manage urban stormwater runoff amid increasingly intense rainfall events to protect public and environmental health.
Aedes aegypti is the main vector of dengue, Zika, chikungunya, and yellow fever viruses. Controlling populations of vector mosquito species in urban environments is a major challenge and being able to determine what aquatic habitats should be prioritized for controlling Ae. aegypti populations is key to the development of more effective mosquito control strategies. Therefore, our objective was to leverage on the Miami-Dade County, Florida immature mosquito surveillance system based on requested by citizen complaints through 311 calls to determine what are the most important aquatic habitats in the proliferation of Ae. aegypti in Miami. We used a tobit model for Ae. aegypti larvae and pupae count data, type and count of aquatic habitats, and daily rainfall. Our results revealed that storm drains had 45% lower percentage of Ae. aegypti larvae over the total of larvae and pupae adjusted for daily rainfall when compared to tires, followed by bromeliads with 33% and garbage cans with 17%. These results are indicating that storm drains, bromeliads and garbage cans had significantly more pupae in relation to larvae when compared to tires, traditionally know as productive aquatic habitats for Ae. aegypti. Ultimately, the methodology and results from this study can be used by mosquito control agencies to identify habitats that should be prioritized in mosquito management and control actions, as well as to guide and improve policies and increase community awareness and engagement. Moreover, by targeting the most productive aquatic habitats this approach will allow the development of critical emergency outbreak responses by directing the control response efforts to the most productive aquatic habitats.
Meteorological and even human-made disasters are increasing every year in frequency and magnitude. The passage of a disaster affects a society without distinction, but groups with social vulnerability (low socioeconomic status, chronic medical, or psychological conditions, limited access to resources) face the most significant impact. As a result, psychological and behavioral symptoms (eg, depression and anxiety) can ensue, making the immediate response of mental health services crucial. Secondary data from a database of a temporary healthcare unit were analyzed. A total of 54 records were reviewed to collect information; univariate and bivariate analyses were done. The purpose of this article is to present our experience regarding the incorporation of a mental health services model, with its respective benefits and challenges, into a temporary healthcare unit, after Hurricane Maria in 2017.
IMPORTANCE: Crisis text lines have proven to be an effective and low-cost means for delivering texting-based mental health support to youth. Yet there has been limited research examining the use of these services in capturing the psychological impact on youth affected by a weather-related disaster. OBJECTIVE: This ecologic study examined changes in help-seeking behavior for adolescents and young adults in North and South Carolina, USA, before and after Hurricane Florence (2018). DESIGN AND MAIN OUTCOMES: A retrospective, interrupted time-series design was used to examine pre- and post-hurricane changes in crisis text volume among youth help seekers in the Carolinas for the following outcomes: (1) text for any reason; (2) stress & anxiety; (3) depression; and (4) suicidal thoughts. RESULTS: Results showed an immediate and sustained increase in crisis texts for stress/anxiety and suicidal thoughts in the six weeks following Florence. Overall, an immediate 15% increase in crisis texts for anxiety/stress (SE = 0.05, p = .005) and a 17% increase in suicidal thoughts (SE = 0.07, p = .02) occurred during the week of the storm. Text volume for anxiety/stress increased 17% (SE = 0.08, p = .005) and 23% for suicidal ideation (SE = 0.08, p = .01) in the 6-week post-hurricane period. Finally, forecast models revealed observed text volume for all mental health outcomes was higher than expected in the 6 weeks post-Florence. CONCLUSIONS AND RELEVANCE: A low-cost, crisis texting platform provided 24/7 mental health support available to young people in the Carolinas impacted by Hurricane Florence. These findings highlight a new application for text-based crisis support services to address the mental health consequences in youth following a weather-related disaster, as well as the potential for these types of crisis platforms to measure situational awareness in impacted communities.
Paralytic shellfish poison toxins (PSTs) produced by the dinoflagellate in the genus Alexandrium are a threat to human health and subsistence lifestyles in Southeast Alaska. It is important to understand the drivers of Alexandrium blooms to inform shellfish management and aquaculture, as well as to predict trends of PST in a changing climate. In this study, we aggregate environmental data sets from multiple agencies and tribal partners to model and predict concentrations of PSTs in Southeast Alaska from 2016 to 2019. We used daily PST concentrations interpolated from regularly sampled blue mussels (Mytilus trossulus) analyzed for total PSTs using a receptor binding assay. We then created random forest models to classify shellfish above and below a threshold of toxicity (80 µg 100 g(-1)) and used two methods to determine variable importance. We obtained a multivariate model with key variables being sea surface temperature, salinity, freshwater discharge, and air temperature. We then used a similar model trained using lagged environmental variables to hindcast out-of-sample (OOS) shellfish toxicities during April-October in 2017, 2018, and 2019. Hindcast OOS accuracies were low (37-50%); however, we found forecasting using environmental variables may be useful in predicting the timing of early summer blooms. This study reinforces the efficacy of machine learning to determine important drivers of harmful algal blooms, although more complex models incorporating other parameters such as toxicokinetics are likely needed for accurate regional forecasts.
There is a lack of evidence on causal effects of air pollution on gestational age (GA) at delivery. METHODS: Inverse probability weighting (IPW) quantile regression was applied to derive causal marginal population-level GA reduction for GA percentiles associated with increased ambient particulate matter with diameter <2.5 ?m (PM(2.5)) levels at maternal residential address for each trimester and the month preceding delivery using Massachusetts birth registry 2001 to 2015. Stratified analyses were conducted for neonatal sex, maternal age/race/education, and extreme ambient temperature conditions. RESULTS: For neonates at 2.5th, 10th, 25th, 50th, 75th, and 97.5th percentiles of GA at delivery, we estimated an adjusted GA reduction of 4.2 days (95% confidence interval [CI] = 3.4, 5.0), 1.9 days (1.6, 2.1), 1.2 days (1.0, 1.4), 0.82 days (0.72, 0.92), 0.74 days (0.54, 0.94), and 0.54 days (0.15, 0.93) for each 5 ?g/m3 increment in third trimester average PM(2.5) levels. Final gestational month average exposure yielded a similar effect with greater magnitude. Male neonates and neonates of younger (younger than 35 years) and African American mothers as well as with high/low extreme temperature exposure in third trimester were more affected. Estimates were consistently higher at lower GA percentiles, indicating preterm/early-term births being more affected. Low-exposure analyses yielded similar results, restricting to areas with PM(2.5) levels under US ambient annual standard of 12 ?g/m(3). CONCLUSIONS: Prenatal exposure to PM(2.5) in late pregnancy reduced GA at delivery among Massachusetts neonates, especially among preterm/early-term births, male neonates, and neonates of younger and African American mothers. Exposure to extremely high/low temperature amplifies the effect of PM(2.5) on GA.
INTRODUCTION: Findings concerning the relationship between maternal prenatal and child cortisol concentrations are inconsistent. This study examined whether the influence of an objective traumatic stressor during pregnancy, distance from a natural flood disaster, moderated the association between prenatal maternal diurnal cortisol and 9-year old offspring hair cortisol concentrations. METHODS: Data were collected from 56 of the mothers who took part in a study of flood-related pregnancy outcomes in 2009 and their children. Data included distance of the maternal home from evacuation areas, four maternal saliva cortisol assessments (waking, 30 min after waking, afternoon, and before bed) provided within 3-months of the flood crest and child hair samples to assess cortisol secretion over the past month. RESULTS: There was a significant interaction between proximity to flooding during pregnancy and maternal cortisol AUC predicting child hair cortisol, after controlling for maternal age, gestational age at cortisol sampling, sex of the child, current socioeconomic status and current maternal stress. At greater distance from flooding (lower stress conditions) there was a non-statistically significant positive association between maternal cortisol and child cortisol. In contrast, living closer to flooding (higher stress conditions) produced a significant negative association between maternal and child cortisol. CONCLUSION: Experiencing a traumatic stressor during pregnancy may alter maternal-fetal programming of the hypothalamic-pituitary-adrenal axis. The direct threat of flooding led to offspring cortisol concentrations that resembled cortisol production seen in mothers with symptoms of PTSD and their offspring. This alteration is evident in nine-year-old offspring and may help explain inconsistencies in the previous literature.
BACKGROUND: Large-scale natural disasters disproportionally affect both the medically complex and the older old, groups that are responsible for most medical surge after a disaster. To understand how to ameliorate this surge, we examined the activities of the nine US Department of Veterans Affairs (VA) Home Based Primary Care (HBPC) programs impacted during the 2017 Fall Hurricane Season. METHODS: Convergent mixed methods design, incorporating independently conducted qualitative and quantitative analyses. Phase One: 34 clinical staff were interviewed from the nine VA HBPC programs impacted by Hurricanes Harvey, Irma, and Maria to examine the experiences of their HBPC programs in response to the Hurricanes. Phase Two: Secondary quantitative data analysis used the VA’s Corporate Data Warehouse (CDW) to examine the electronic health records of patients for these same nine sites. RESULTS: The emergency management activities of the HBPC programs emerged as two distinct phases: preparedness, and response and recovery. The early implementation of preparedness procedures, and coordinated post-Hurricane patient tracking, limited disruption in care and prevented significant hospitalizations among this population. CONCLUSIONS: Individuals aged 75 or older, who often present with multiple comorbidities and decreased functional status, typically prefer to age in their homes. Additionally, as in-home medical equipment evolves, more medically vulnerable individuals are able to receive care at home. HBPC programs, and similar programs under Medicare, connect the homebound, medically complex, older old to the greater healthcare community. Engaging with these programs both pre- and post-disasters is central to bolstering community resilience for these at-risk populations.
Global environmental change is having profound effects on the ecology of infectious disease systems, which are widely anticipated to become more pronounced under future climate and land use change. Arthropod vectors of disease are particularly sensitive to changes in abiotic conditions such as temperature and moisture availability. Recent research has focused on shifting environmental suitability for, and geographic distribution of, vector species under projected climate change scenarios. However, shifts in seasonal activity patterns, or phenology, may also have dramatic consequences for human exposure risk, local vector abundance and pathogen transmission dynamics. Moreover, changes in land use are likely to alter human-vector contact rates in ways that models of changing climate suitability are unlikely to capture. Here we used climate and land use projections for California coupled with seasonal species distribution models to explore the response of the western blacklegged tick (Ixodes pacificus), the primary Lyme disease vector in western North America, to projected climate and land use change. Specifically, we investigated how environmental suitability for tick host-seeking changes seasonally, how the magnitude and direction of changing seasonal suitability differs regionally across California, and how land use change shifts human tick-encounter risk across the state. We found vector responses to changing climate and land use vary regionally within California under different future scenarios. Under a hotter, drier scenario and more extreme land use change, the duration and extent of seasonal host-seeking activity increases in northern California, but declines in the south. In contrast, under a hotter, wetter scenario seasonal host-seeking declines in northern California, but increases in the south. Notably, regardless of future scenario, projected increases in developed land adjacent to current human population centers substantially increase potential human-vector encounter risk across the state. These results highlight regional variability and potential nonlinearity in the response of disease vectors to environmental change.
Urgent and ambitious climate action is required to avoid catastrophic climate change and consequent health impacts. Political will is a critical component of the ambitious climate action equation. The current level of political will observed for many national governments is considered inadequate, with numerous political leaders yet to commit to climate action commensurate with the projected risks and responsibilities for their respective jurisdictions. Under the leadership of the Obama administration, however, the United States of America arguably provided an example to the contrary. Strategically utilising an available legislative lever, the Obama administration pursued comparatively ambitious climate change mitigation policies, with health as a core motivation. Analysis of Obama-led climate policies and policy-making strategies provides valuable insight into the utility of health as a motivator for climate action. It also reaffirms that strong political leadership constitutes an essential element in the pursuit of increasingly ambitious climate change policies, particularly in the face of strong opposition.
Climate change projections indicate that mosquito distributions will expand to include new areas of North America, increasing human exposure to mosquito-borne disease. Controlling these vectors is imperative, as mosquito-borne disease incidence will rise in response to expansion of mosquito range and increased seasonality. One means of mosquito control used in the USA is the biocontrol agent, Toxorhynchites rutilus. Climate change will open new habitats for its use by vector control organizations, but the extent of this change in habitat is currently unknown. We used a maximum entropy approach to create species distribution models for Tx. rutilus under 4 climate change scenarios by 2070. Mean temperature of warmest quarter (22.6°C to 29.1°C), annual precipitation (1,025.15 mm to 1,529.40 mm), and precipitation seasonality (?17.86) are the most important bioclimatic variables for suitable habitat. The center of current possible habitat distribution of Tx. rutilus is in central Tennessee. Depending upon the scenario, we expect centroids to shift north-northeast by 97.68 km to 280.16 km by 2070. The extreme change in area of greater than 50% suitable habitat probability is 141.14% with 99.44% area retained. Our models indicate limited change in current habitat as well as creation of new habitat. These results are promising for North American mosquito control programs for the continued and potential combat of vector mosquitoes using Tx. rutilus.
Many cities are developing mitigation plans in an effort to reduce the population health impacts from expected future increases in the frequency and intensity of heat waves. To inform heat mitigation and adaptation planning, information is needed on the extent to which available mitigation strategies, such as reflective and green roofs, could result in significant reductions in heat exposure. Using the Weather Research and Forecasting (WRF) model, we analysed the impact of green and cool (reflective) roofs on the urban heat island (UHI) and temperature-related deaths in the Greater Boston area (GBA) and New England area (NEA) in summer and winter. In the GBA, green and cool roofs reduced summertime population-weighted temperature by 0.35 degrees C and 0.40 degrees C, respectively. In winter, green roofs did not affect temperature, whereas cool roofs caused a temperature reduction of 0.40 degrees C. In the NEA, the cooler summers induced by green and cool roofs were estimated to reduce the heat-related mortality rates by 0.21% and 0.17%, respectively, compared to baseline. Cool-roof-induced temperature reduction in winter could increase the cold-related mortality rate by 0.096% compared to baseline. These results suggest that both green and cool roofing strategies have the potential to reduce the impact of heat on premature deaths. Additionally, the differing effects in winter suggest the need for a careful consideration of health trade-offs in choosing heat island mitigation strategies.
BACKGROUND AND AIMS: Future climate change may adversely impact human health. The direct effects of extreme hot temperatures on mortality are well established, and their future impact well modelled. However, less extreme changes in ambient temperature (Ta) have been previously associated with increased mortality from circulatory and metabolic diseases, but their future impact is less clear. METHODS: We evaluated the spatial association between cardiovascular diseases (CVD) and stroke mortality with average Ta across the US mainland, and then used this relationship to model future temporal trends in mortality from CVD and stroke until the end of the century (2099), using different warming scenarios for each US county. RESULTS: Ta was significantly associated with crude levels of CVD mortality (R(2) = 0.269) and stroke mortality (R(2) = 0.264). Moreover, there was a strong positive link between Ta and physical inactivity (PIA) (R(2) = 0.215). Once adjusted for PIA the associations between Ta and CVD and stroke mortality were much reduced (R(2) = 0.054 and R(2) = 0.091 respectively) but still highly significant. CONCLUSIONS: By 2099 modelling suggests between 8844 and 25,486 extra deaths each year from CVD, and between 2,063 and 13,039 extra deaths for stroke, beyond the increases expected from population expansion. Mortality due to changes in the mean Ta may be as, or more, significant than the impacts of extreme hot weather events.
Stakeholder participation at the intersection of climate and health is essential to assess and plan for the human health impacts of current and projected climate-sensitive hazards. Using the Maricopa County Department of Public Health (MCDPH) Coalition on Climate Change and Public Health workgroup and the Climate Assessment for the Southwest (CLIMAS) program as examples, this paper describes the important role of scientist-public health stakeholder collaboratives in addressing the public health impacts of climate-sensitive hazards. Using the MCDPH and CLIMAS stakeholder groups, stakeholder connections were mapped to show relationships between the organization types and connections between scientists and public health stakeholders. Stakeholders, defined as meeting attendees, were primarily individuals from academic institutions (n = 175), government agencies (n = 114), non-profits (n = 90), and health departments (n = 85). Engaging public health stakeholders in transdisciplinary regional climate initiatives and addressing gaps in their networks helped these programs to develop more collaborative projects over time.
Infectious diseases are emerging and re-emerging due to climate change. Understanding how climate variability affects the transmission of infectious diseases is important for both researchers and the general public. Yet, the widespread knowledge of the general public on this matter is unknown, and quantitative research is still lacking. A survey was designed to assess the knowledge and perception of 1) infectious diseases, 2) climate change and 3) the effect of climate change on infectious diseases. Participants were recruited via convenience sampling, and an anonymous cross-sectional survey with informed consent was distributed to each participant. Descriptive and inferential analyses were performed primarily focusing on the occupational background as well as nationality of participants. A total of 458 individuals participated in this study, and most participants were originally from Myanmar, the Netherlands, Spain, United Kingdom and the United States. Almost half (44%) had a background in natural sciences and had a higher level of knowledge on infectious diseases compared to participants with non-science background (mean score of 12.5 and 11.2 out of 20, respectively). The knowledge of the effect of climate change on infectious diseases was also significantly different between participants with and without a background in natural sciences (13.1 and 11.8 out of 20, respectively). The level of knowledge on various topics was highly correlated with nationality but not associated with age. The general population demonstrated a high awareness and strong knowledge of climate change regardless of their background in natural sciences. This study exposes a knowledge gap in the general public regarding the effect of climate change on infectious diseases, and highlights that different levels of knowledge are observed in groups with differing occupations and nationalities. These results may help to develop awareness interventions for the general public.
The continuous increase of Coccidioidomycosis cases requires reliable detection methods of the causal agent, Coccidioides spp., in its natural environment. This has proven challenging because of our limited knowledge on the distribution of this soil-dwelling fungus. Knowing the pathogen’s geographic distribution and its relationship with the environment is crucial to identify potential areas of risk and to prevent disease outbreaks. The maximum entropy (Maxent) algorithm, Geographic Information System (GIS) and bioclimatic variables were combined to obtain current and future potential distribution models (DMs) of Coccidioides and its putative rodent reservoirs for Arizona, California and Baja California. We revealed that Coccidioides DMs constructed with presence records from one state are not well suited to predict distribution in another state, supporting the existence of distinct phylogeographic populations of Coccidioides. A great correlation between Coccidioides DMs and United States counties with high Coccidioidomycosis incidence was found. Remarkably, under future scenarios of climate change and high concentration of greenhouse gases, the probability of habitat suitability for Coccidioides increased. Overlap analysis between the DMs of rodents and Coccidioides, identified Neotoma lepida as one of the predominant co-occurring species in all three states. Considering rodents DMs would allow to implement better surveillance programs to monitor disease spread.
Three studies investigated habitual worry about global warming as an example of ‘eco-anxiety’. The key question was whether such worrying is constructive (a motivated pro-environmental response) or unconstructive (a symptom of pathological worry). Pathological worry and worry about global warming were assessed together with two other worry sources, that is, personal issues and the world economy (Study 1) and personal issues and the corona virus (Study 2). In both studies a statistically significant correlation was found between pathological worry and global warming worry. However, this relationship was nonsignificant when controlled for the other two worry sources. Comparisons between Studies 1 and 2 conducted one month before and during the COVID-19 crisis, respectively, as well as between order conditions within Study 2 suggested that global warming worry was unaffected by the COVID-19 context. Study 3 demonstrated that global warming worry was associated with the perception of a proximal as well as a distal threat, and correlated positively with determinants of pro-environmental behaviour, that is, a pro-ecological worldview, pro-environmental values, past pro-environmental behaviour and a ‘green’ identity. Global warming worry also correlated positively with emotion clusters signifying determination, anxiety, and anger, respectively. The three studies together suggest that while habitual global warming worry may be unconstructive and part of intrapersonal dysfunction for some individuals, for many others it is a constructive adaptive pro-environmental response.
Background The natural cycle of large-scale wildfires is accelerating, increasingly exposing both rural and populous urban areas to wildfire emissions. While respiratory health effects associated with wildfire smoke are well established, cardiovascular effects have been less clear. Methods and Results We examined the association between out-of-hospital cardiac arrest and wildfire smoke density (light, medium, heavy smoke) from the National Oceanic Atmospheric Association’s Hazard Mapping System. Out-of-hospital cardiac arrest data were provided by the Cardiac Arrest Registry to Enhance Survival for 14 California counties, 2015-2017 (N=5336). We applied conditional logistic regression in a case-crossover design using control days from 1, 2, 3, and 4 weeks before case date, at lag days 0 to 3. We stratified by pathogenesis, sex, age (19-34, 35-64, and >= 65 years), and socioeconomic status (census tract percent below poverty). Out-of-hospital cardiac arrest risk increased in association with heavy smoke across multiple lag days, strongest on lag day 2 (odds ratio, 1.70; 95% CI, 1.18-2.13). Risk in the lower socioeconomic status strata was elevated on medium and heavy days, although not statistically significant. Higher socioeconomic status strata had elevated odds ratios with heavy smoke but null results with light and medium smoke. Both sexes and age groups 35 years and older were impacted on days with heavy smoke. Conclusions Out-of-hospital cardiac arrests increased with wildfire smoke exposure, and lower socioeconomic status appeared to increase the risk. The future trajectory of wildfire, along with increasing vulnerability of the aging population, underscores the importance of formulating public health and clinical strategies to protect those most vulnerable.
Global climate change is an environmental hazard with significant public health impacts. High-impact weather events including periods of extreme temperature or extreme precipitation are frequently associated with adverse effects on human health. This study evaluates the impact of extreme weather events on injuries across New Hampshire. A set of five daily extreme weather metrics (EWMs) was analyzed: daily maximum temperature <= 32 degrees F (0 degrees C), daily maximum temperature >= 90 degrees F (32 degrees C), daily maximum temperature >= 95 degrees F (35 degrees C), daily precipitation >= 1 ”, and daily precipitation >= 2 ”. Exposure to these EWMs was defined by linking the population within 10 miles of nine weather stations distributed across the state. Injuries were defined as hospitalizations categorized as: all-cause injury, vehicle accidents, accidental falls, accidents due to natural and environmental causes (including excessive heat, excessive cold, exposure due to weather conditions, lightning, and storms and floods), accidental drowning, and carbon monoxide poisoning. The associations between all injury categories and all EWMs as well as daily maximum temperature and daily precipitation were explored. A quasi-Poisson regression model was used to evaluate the relationship between the four strongest exposure-outcome pairs linking maximum temperature to all-cause injury-, vehicle accident-, accidental fall-, and heat-related hospital visits. Results indicate that daily maximum temperature (>90 degrees F) was most strongly associated with heat-related hospital visits and was also associated with all-cause injury-related hospital visits. Future work should include further analysis of cold weather metrics and incorporate these findings into public health planning and response efforts.
Ozone exposure is associated with higher risk of asthma-related emergency department visits. The meteorological conditions that govern ozone concentration are projected to be more favorable to ozone formation over much of the United States due to continued climate change, even as emissions of anthropogenic ozone precursors are expected to decrease by 2050. Our goal is to quantify the health benefits of a climate change mitigation scenario versus a “business-as-usual” scenario, defined by the United Nations Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs) 4.5 and 8.5, respectively, using the health impact analytical program Benefits Mapping and Analysis Program – Community Edition (BenMAP – CE) to project the number of asthma ED visits in 2045-2055. We project an annual average of 3100 averted ozone-related asthma ED visits during the 2045-2055 period under RCP4.5 versus RCP8.5, with all other factors held constant, which translates to USD $1.7 million in averted costs annually. We identify counties with tens to hundreds of avoided ozone-related asthma ED visits under RCP4.5 versus RCP8.5. Overall, we project a heterogeneous distribution of ozone-related asthma ED visits at different spatial resolutions, specifically national, regional, and county levels, and a substantial net health and economic benefit of climate change mitigation.
Background Wildfire events are increasing in prevalence in the western United States. Research has found mixed results on the degree to which exposure to wildfire smoke is associated with an increased risk of mortality. Methods We tested for an association between exposure to wildfire smoke and non-traumatic mortality in Washington State, USA. We characterized wildfire smoke days as binary for grid cells based on daily average PM2.5 concentrations, from June 1 through September 30, 2006-2017. Wildfire smoke days were defined as all days with assigned monitor concentration above a PM2.5 value of 20.4 mu g/m(3), with an additional set of criteria applied to days between 9 and 20.4 mu g/m(3). We employed a case-crossover study design using conditional logistic regression and time-stratified referent sampling, controlling for humidex. Results The odds of all-ages non-traumatic mortality with same-day exposure was 1.0% (95% CI: – 1.0 – 4.0%) greater on wildfire smoke days compared to non-wildfire smoke days, and the previous day’s exposure was associated with a 2.0% (95% CI: 0.0-5.0%) increase. When stratified by cause of mortality, odds of same-day respiratory mortality increased by 9.0% (95% CI: 0.0-18.0%), while the odds of same-day COPD mortality increased by 14.0% (95% CI: 2.0-26.0%). In subgroup analyses, we observed a 35.0% (95% CI: 9.0-67.0%) increase in the odds of same-day respiratory mortality for adults ages 45-64. Conclusions This study suggests increased odds of mortality in the first few days following wildfire smoke exposure. It is the first to examine this relationship in Washington State and will help inform local and state risk communication efforts and decision-making during future wildfire smoke events.
Hard defenses, such as levees or land berms, are often considered the most effective approach to reduce flood risk. This study reveals a potential increase in mortality when hard protections cannot defend a location against low-probability, extreme flood events. Staten Island, New York, suffered devastating damage from Hurricane Sandy, including 23 fatalities, of which 18 occurred in the neighborhoods along the island’s eastern shore. This study demonstrates that the elevated berm along the eastern shore may have contributed to the concentration of fatalities in the area by increasing the speed at which seawater rose, causing some people to be trapped in places where they could not escape rising waters. The study uses a hydrodynamic model to simulate Hurricane Sandy flood conditions, providing water depth, rise rate, and velocity. Statistical analyses show that water rise rate influences mortality, while other flood characteristics and several demographic and socioeconomic factors do not. A model experiment that qualitatively examines flood conditions in the presence of a lower discontinuous berm that historically existed at the location in Midland Beach finds that the increased height and continuity of the berm increased probability of mortality by worsening the water rise rate during Sandy by about 50%. The potential increase in mortality needs to be taken into account when designing coastal protections. If a protection strategy does not prevent low-probability, extreme floods, then there is a trade-off between protection against more frequent floods and increased risk of mortality during extreme floods.
Background Wildfires are increasingly a significant source of fine particulate matter (PM2.5), which has been linked to adverse health effects and increased mortality. ESKD patients are potentially susceptible to this environmental stressor. Methods We conducted a retrospective time-series analysis of the association between daily exposure to wildfire PM2.5 and mortality in 253 counties near a major wildfire between 2008 and 2012. Using quasi-Poisson regression models, we estimated rate ratios (RRs) for all-cause mortality on the day of exposure and up to 30 days following exposure, adjusted for background PM2.5, day of week, seasonality, and heat. We stratified the analysis by causes of death (cardiac, vascular, infectious, or other) and place of death (clinical or nonclinical setting) for differential PM2.5 exposure and outcome classification. Results We found 48,454 deaths matched to the 253 counties. A 10-mu g/m(3) increase in wildfire PM2.5 associated with a 4% increase in all-cause mortality on the same day (RR, 1.04; 95% confidence interval [95% CI], 1.01 to 1.07) and 7% increase cumulatively over 30 days following exposure (RR, 1.07; 95% CI, 1.01 to 1.12). Risk was elevated following exposure for deaths occurring in nonclinical settings (RR, 1.07; 95% CI, 1.02 to 1.12), suggesting modification of exposure by place of death. “Other” deaths (those not attributed to cardiac, vascular, or infectious causes) accounted for the largest portion of deaths and had a strong same-day effect (RR, 1.08; 95% CI, 1.03 to 1.12) and cumulative effect over the 30-day period. On days with a wildfire PM2.5 contribution >10 mu g/m(3), exposure accounted for 8.4% of mortality. Conclusions Wildfire smoke exposure was positively associated with all-cause mortality among patients receiving in-center hemodialysis.
Heat waves are extreme climate events that have the potential to cause immense stress on human health, agriculture, and energy systems, so understanding the processes leading to their onset is crucial. There is no single accepted definition for heat waves, but they are generally described as a sustained amount of time over which temperature exceeds a local threshold. Multiple different temperature variables are potentially relevant, because high values of both daily maximum and minimum temperatures can be detrimental to human health. In this study, we focus explicitly on the different mechanisms associated with summertime heat waves manifested during daytime hours versus nighttime hours over the contiguous United States. Heat waves are examined using the National Aeronautics and Space Administration Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Over 1980-2018, the increase in the number of heat-wave days per summer was generally stronger for nighttime heat-wave days than for daytime heat-wave days, with localized regions of significant positive trends. Processes linked with daytime and nighttime heat waves are identified through composite analysis of precipitation, soil moisture, clouds, humidity, and fluxes of heat and moisture. Daytime heat waves are associated with dry conditions, reduced cloud cover, and increased sensible heating. Mechanisms leading to nighttime heat waves differ regionally across the United States, but they are typically associated with increased clouds, humidity, and/or low-level temperature advection. In the midwestern United States, enhanced moisture is transported from the Gulf of Mexico during nighttime heat waves.
Exposure to air pollution is one of the primary global health risk factors, yet individuals lack the knowledge to engage in individual risk mitigation and the skills to mobilize for the change necessary to reduce such risks. News media is an important tool for influencing individual actions and support for public policies to reduce environmental threats; thus, a lack of news coverage of such issues may exacerbate knowledge deficits. This study examines the reporting of health risks and precautionary measures regarding air pollution in national and regional print news. We conducted a content analysis of two national and two local newspapers covering the USA’s most polluted region during a 5-year period. Coders identified information on threat, self-efficacy, protective measures and information sources. Nearly 40% of air pollution news articles mentioned human health risks. Fewer than 10% of news stories about air pollution provided information on the precautionary measures necessary for individuals to take action to mitigate their risk. Local newspapers did not report more threat (X-2= 1.931,p= 0.165) and efficacy (X-2= 1.118,p= 0.209) information. Although air pollution levels are high and continue to rise at alarming rates, our findings suggest that news media reporting is not conducive to raising environmental health literacy.
The connection between mental health and weather extremes is a public health concern, but less studied to date than physical health. This exploratory study examines the mental health impacts of two kinds of weather extremes increasingly linked to climate change-summer heat waves and extreme winter weather-in a low- to middle-income population in the Southeastern U.S. The distribution of mental health impacts, and potential pathways to them, are examined with a focus on race. Data are from a random-sample survey of 426 participants and are analyzed with bivariate statistics and path analysis. Self-reported mental health impacts, in both seasons, were common in our study, with White participants tending to report worse impacts than participants who identified with other racial groups. Physical health had direct effects on mental health across several models, overall and by racial group. For summer heat waves, concern about climate change and social cohesion had direct and indirect effects, respectively, on mental health in White participants only. For extreme winter weather, preparedness had a direct negative effect on mental health in White, but not Black, participants. Results suggest that there may be racial differences in the influence of human and social capital factors on mental health related to weather extremes, warranting further study of this critical topic and with larger racial subgroup samples.
Floods are a prominent risk factor in the world of public health, as there is a risk of dispersal of harmful biological and chemical contaminants in floodwater. As climate change increases, the occurrence of natural disasters and risk of adverse health outcomes due to flash flooding also increases. Fecal indicator bacteria, such as Escherichia coli and Enterococci, are often encountered in contaminated floodwater and can cause gastrointestinal illnesses as well as a variety of infections. In August 2016, East Baton Rouge and surrounding parishes in Louisiana suffered heavy floods due to intense rainfall. No study of water quality during flooding has been conducted previously in Baton Rouge, Louisiana. Twenty-three pre-flush and post-flush water samples were collected immediately from accessible homes that had been affected by the floods in order to quantify concentrations of fecal indicator bacteria. These samples were analyzed for the presence of E. coli and Enterococci through both quantitative polymerase chain reaction (qPCR) and the IDEXX enzyme substrate method. The qPCR results indicated that 30% of the samples contained Enterococci and 61% of the samples contained E. coli, with the highest concentrations found in the pre-flush outdoor hose and the pre-flush kitchen tap. The IDEXX method yielded total coliforms in 65% of the samples, E. coli in 4%, and Enterococci in 35%, with the highest concentrations in the pre-flush outdoor faucet and the pre-flush post-filtration kitchen tap. Physical parameters including temperature, barometer pressure, dissolved oxygen, oxidation reduction potential, pH, conductivity, and salinity of these samples were also recorded. Of these parameters, conductivity and salinity were significant, suggesting they may positively influence E. coli and Enterococci growth.
Climate change exacerbates the severity of natural disasters, which disproportionately affect vulnerable populations. Mitigating disasters’ health consequences is critical to promoting health equity, but few studies have isolated the short- and long-term effects of disasters on vulnerable groups. We filled this gap by conducting a fifteen-year (2003-2018) prospective study of low-income, predominantly Black parents who experienced Hurricane Katrina: the Resilience in Survivors of Katrina (RISK) Project. Here we describe this project and synthesize lessons from work that has resulted from it. Our findings can guide policy makers, service providers, and health officials in disaster planning and response. We synthesize them into an organizational schema of five priorities: Primary efforts should be aimed at preventing exposure to trauma through investments in climate resilience and by eliminating impediments to evacuation, health care policies should promote uninterrupted and expanded access to care, social services should integrate and strive to reduce the administrative burden on survivors, programs should aid survivors in forging or strengthening connections to their communities, and policy makers should fund targeted long-term services for highly affected survivors.
Extreme heat threatens desert city residents throughout the hot summer months and inhibits outdoor recreation and activity. Ecosystem services provide various benefits for urban environments. For desert cities, few are more critical than microclimate regulation and water treatment and conservation. This study evaluates the degree to which artificial wetlands support cooler microclimates and reduce the local urban heat island effect. The authors use (a) remotely sensed temperature data for Avondale, Arizona, to measure temperature differences between neighborhoods with and without water features and (b) resident surveys to evaluate perceptions of potential cooling effects. Results show substantial differences in the daytime surface temperatures for the wetland neighborhood compared to those without water features. More than a third of residents perceived a cooling effect throughout the year. The authors conclude that artificial wetlands within a desert city increase human comfort by reducing surface and air temperature and should be considered an urban heat island mitigation strategy.
BACKGROUND: Extreme heat poses current and future risks to human health. Heat vulnerability indices (HVIs), commonly developed using principal components analysis (PCA), are mapped to identify populations vulnerable to extreme heat. Few studies critically assess implications of analytic choices made when employing this methodology for fine-scale vulnerability mapping. OBJECTIVE: We investigated sensitivity of HVIs created by applying PCA to input variables and whether training input variables on heat-health data produced HVIs with similar spatial vulnerability patterns for Detroit, Michigan, USA. METHODS: We acquired 2010 Census tract and block group level data, land cover data, daily ambient apparent temperature, and all-cause mortality during May-September, 2000-2009. We used PCA to construct HVIs using: a) “unsupervised”-PCA applied to variables selected a priori as risk factors for heat-related health outcomes; b) “supervised”-PCA applied only to variables significantly correlated with proportion of all-cause mortality occurring on extreme heat days (i.e., days with 2-d mean apparent temperature above month-specific 95th percentiles). RESULTS: Unsupervised and supervised HVIs yielded differing spatial vulnerability patterns, depending on selected land cover input variables. Supervised PCA explained 62% of variance in the input variables and was applied on half the variables used in the unsupervised method. Census tract-level supervised HVI values were positively associated with increased proportion of mortality occurring on extreme heat days; supervised PCA could not be applied to block group data. Unsupervised HVI values were not associated with extreme heat mortality for either tracts or block groups. DISCUSSION: HVIs calculated using PCA are sensitive to input data and scale. Supervised HVIs may provide marginally more specific indicators of heat vulnerability than unsupervised HVIs. PCA-derived HVIs address correlation among vulnerability indicators, although the resulting output requires careful contextual interpretation beyond generating epidemiological research questions. Methods with reliably stable outputs should be leveraged for prioritizing heat interventions. https://doi.org/10.1289/EHP4030.
Individuals who survive natural hazards often develop posttraumatic stress symptoms or other forms of psychological distress. However, some experience psychological growth. Given that natural hazards will increase in the near future due to global warming, it would be helpful to examine predictors of growth across different kinds of natural hazards. The present study examined positive psychological factors that may serve as buffers against the negative effects of exposure to a natural hazard, specifically following the Louisiana flooding of August 2016. Volunteer participants (N = 120) self-reported perceived presence and search for meaning in life, social support, resilience, and posttraumatic growth (PTG). After controlling for amount of property damaged, posttraumatic stress symptoms, gender, religion, and ethnicity or race, presence and search for meaning, social support, and resilience explained significant additional variance in PTG scores. This research adds to the growing understanding of how individuals respond to natural hazards. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
The effects of atmospheric black carbon (BC) on climate and public health have been well established, but large uncertainties remain regarding the extent of the impacts of BC at different temporal and spatial scales. These uncertainties are largely due to the heterogeneous nature of BC in terms of its spatiotemporal distribution, mixing state, and coating composition. Here, we seek to further understand the size and mixing state of BC emitted from various sources and aged over different timescales using field measurements in the Los Angeles region. We measured refractory black carbon (rBC) with a single-particle soot photometer (SP2) on Catalina Island, California (similar to 70 km southwest of downtown Los Angeles) during three different time periods. During the first campaign (September 2017), westerly winds were dominant and measured air masses were representative of wellaged background over the Pacific Ocean. In the second and third campaigns (December 2017 and November 2018, respectively), atypical Santa Ana wind conditions allowed us to measure biomass burning rBC (BCbb) from air masses dominated by large biomass burning events in California and fossil fuel rBC (BCff) from the Los Angeles Basin. We observed that the emissions source type heavily influenced both the size distribution of the rBC cores and the rBC mixing state. BCbb had thicker coatings and larger core diameters than BBff. We observed a mean coating thickness (CTBc) of similar to 40-70 nm and a count mean diameter (CMD) of similar to 120 nm for BCbb. For BCff, we observed a CTBc of similar to 5-15 nm and a CMD of similar to 100 nm. Our observations also provided evidence that aging led to an increased CTBc for both BCbb and BCff . Aging timescales < similar to 1 d were insufficient to thickly coat freshly emitted BCff. However, CTBc for aged B-ff within aged background plumes was similar to 35 nm thicker than CTBc for fresh BCff. Likewise, we found that CTBc for aged BCbb was similar to 18 nm thicker than CTBc for fresh BCbb. The results presented in this study highlight the wide variability in the BC mixing state and provide additional evidence that the emissions source type and aging influence rBC microphysical properties.
Central to public health risk communication is understanding the perspectives and shared values among individuals who need the information. Using the responses from a Smoke Sense citizen science project, we examined perspectives on the issue of wildfire smoke as a health risk in relation to an individual’s preparedness to adopt recommended health behaviors. The Smoke Sense smartphone application provides wildfire-related health risk resources and invites participants to record their perspectives on the issue of wildfire smoke. Within the app, participants can explore current and forecasted daily air quality, maps of fire locations, satellite images of smoke plumes, and learn about health consequences of wildfire smoke. We used cluster analysis to identify perspective trait-clusters based on health status, experience with fire smoke, risk perception, self-efficacy, access to exposure-reducing resources, health information needs, and openness to health risk messaging. Differences between traits were examined based on demographics, health status, activity level and engagement with the app. We mapped these traits to the Precaution Adoption Process Model (PAPM) to indicate where each trait lies in adopting recommended health behaviors. Finally, we suggest messaging strategies that may be suitable for each trait. We determined five distinct perspective traits which included individuals who were Protectors and have decided to engage on the issue by adopting new behaviors to protect their health; Cautious, Proactive, and Susceptible individuals who were at a Deciding stage but differed based on risk perceptions and information needs; and the Unengaged who did not perceive smoke as a health issue and were unlikely to change behavior in response to messaging. Across all five traits, the level of engagement and information needs differed substantially, but were not defined by demographics. Individuals in the Susceptible trait had the highest level of engagement and the highest information needs. Messaging that emphasizes self-efficacy and benefits of reducing exposure may be effective in motivating individuals from the deciding stage to taking health protective action. Shared perspectives define an individual’s propensity for acting on recommended health behaviors, therefore, health risk message content should be tailored based on these perspectives.
Wildfires have been affecting California greatly, and vulnerable patients in neonatal intensive care units (NICUs) are not exempt. Our aim was to learn how personnel working in NICUs of California hospitals handled issues of neonatal transfer during wildfire disasters in recent years, with an ultimate goal to share lessons learned with healthcare teams on disaster preparedness. We identified California fires through newspaper articles and the CalFire.gov list. We determined which hospitals were affected and contacted members of the healthcare team through connections via the California Perinatal Quality Care Collaborative (CPQCC) database. We audio recorded interviews over phone or remote conferencing software or by written survey. We coded and analyzed transcripts and survey responses. While describing disaster preparedness, equipment (such as bassinets and backpacks), ambulance access/transport and documentation/charting were noted as important and essential. Teamwork, willingness to do other tasks that are not part of typical job descriptions, and unconventional strategies contribute to the success of keeping NICU babies safe when California wildfire strikes. Healthcare teams developed ingenious and surprising ways to evacuate NICU babies.
Exposure to extreme heat contributes to high morbidity and mortality relative to other climate hazards. The city of Philadelphia, PA is particularly vulnerable to the impacts of extreme heat, due to the urban heat island effect and high prevalence of sensitive populations. We developed a heat vulnerability index, which identified priority areas that are most at-risk of experiencing adverse heat-related health outcomes and in need of preparedness and mitigation interventions. An interactive website was created to display the maps and allow the public to navigate the data with links to potential resources for relief from extreme heat days. Such methods can be adapted for other cities that wish to identify and target long-term priority areas.
BACKGROUND: Differences in multiple sclerosis (MS) risk by latitude have been observed worldwide; however, the exposures driving these associations are unknown. Ultraviolet radiation (UV) has been explored as a risk factor, and ambient temperature has been correlated with disease progression. However, no study has examined the impact of all three exposures. We examined the association between these exposures and incidence of MS within two nationwide prospective cohorts of women, the Nurses’ Health Study (NHS) and Nurses’ Health Study II (NHSII). METHODS: Both cohorts were followed with biennial questionnaires to ascertain new diagnoses and risk factors. Time-varying exposures to latitude, cumulative average July temperature (°C), and cumulative average July erythemal UV (mW/m(2)) were predicted at each participant’s biennially updated residential addresses. Using Cox proportional hazards models adjusted for MS risk factors, we calculated hazard ratios (HR) and 95% confidence intervals (CIs) within each cohort and pooled via meta-analyses. RESULTS: In multivariable models, there were suggestions that decreasing latitude (meta-analysis multivariable-adjusted HR = 0.72; 95% CI 0.55, 0.94 for women living <35.73° compared with those ?42.15°, P-for-trend = 0.007) and increasing cumulative average July temperature (meta-analysis multivariable-adjusted HR = 0.81; 95% CI 0.72, 0.91 for each interquartile range increase [3.91°]) were associated with decreasing risk of MS. There was no evidence of heterogeneity between cohorts. We did not observe consistent associations with cumulative average UV. CONCLUSION: Our results suggest that adult exposures to decreasing latitude and increasing temperature, but not UV, were associated with reduced MS risk in these two cohorts of women. Studies of MS incidence may want to consider temperature as a risk factor.
Historical declines in multiple insect taxa have been documented across the globe in relation to landscape-level changes in land use and climate. However, declines have either not been universally observed in all regions or examined for all species. Because mosquitoes are insects of public health importance, we analyzed a longitudinal mosquito surveillance data set from Connecticut (CT), United States (U.S.) from 2001 to 2019 to identify changes in mosquito community composition over time. We first analyzed annual site-level collections and metrics of mosquito community composition with generalized linear/additive mixed effects models; we also examined annual species-level collections using the same tools. We then examined correlations between statewide collections and weather variables as well as site-level collections and land cover classifications. We found evidence that the average trap night collection of mosquitoes has increased by ~?60% and statewide species richness has increased by ~?10% since 2001. Total species richness was highest in the southern portion of CT, likely due to the northward range expansion of multiple species within the Aedes, Anopheles, Culex, and Psorophora genera. How the expansion of mosquito populations in the northeast U.S. will alter mosquito-borne pathogen transmission in the region will require further investigation.
Rapid and significant range expansion of both Zika virus (ZIKV) and its Aedes vector species has resulted in ZIKV being declared a global health threat. Mean temperatures are projected to increase globally, likely resulting in alterations of the transmission potential of mosquito-borne pathogens. To understand the effect of diurnal temperature range on the vectorial capacity of Ae. aegypti and Ae. albopictus for ZIKV, longevity, blood-feeding and vector competence were assessed at two temperature regimes following feeding on infectious blood meals. Higher temperatures resulted in decreased longevity of Ae. aegypti [Log-rank test, ?2, df 35.66, 5, P < 0.001] and a decrease in blood-feeding rates of Ae. albopictus [Fisher's exact test, P < 0.001]. Temperature had a population and species-specific impact on ZIKV infection rates. Overall, Ae. albopictus reared at the lowest temperature regime demonstrated the highest vectorial capacity (0.53) and the highest transmission efficiency (57%). Increased temperature decreased vectorial capacity across groups yet more significant effects were measured with Ae. aegypti relative to Ae. albopictus. The results of this study suggest that future increases in temperature in the Americas could significantly impact vector competence, blood-feeding and longevity, and potentially decrease the overall vectorial capacity of Aedes mosquitoes in the Americas.
The frequency and magnitude of extreme summer temperature events in the United States have increased in the past few decades. Long-term exposure to extreme summer temperatures can be detrimental to human health, due to potential risks of dehydration and thermoregulation strains on the cardiovascular system, which may often lead to heat-related mortality (HRM). The summer climate of the United States is influenced by variability in Atlantic and Pacific sea surface temperatures, driven in part by Atlantic Multidecadal Oscillation (AMO) and El-Nino Southern Oscillation (ENSO), respectively. However, the influence of AMO and ENSO on HRM in the United States has not been investigated. Here the longest time series of HRM spanning the past five decades is analyzed in relation with AMO and ENSO. We find that HRM doubled in the early-1990s, coinciding with the positive phase of the AMO. Furthermore, we note a positive association between the variability in HRM and summer temperatures across all regions of the United States, with the strongest association found over the Southern United States. Therefore, this research suggests that variability in Atlantic and Pacific sea surface temperatures has both a nationwide and regional impact on HRM in the United States. Hence, by understanding variability in sea surface temperatures, the future burden of heat-attributed emergencies during extreme summer temperature events can be reduced not only for the United States, but also worldwide.
OBJECTIVES: Human sexual dimorphism is frequently assessed through skull and pelvic size and shape. Researchers suggest that climatic variation and the associated stress may be significant factors in sexual dimorphism’s etiology. However, little research has specifically investigated climatic effects on nonmetric skeletal indicators of sex. To further appreciate the plasticity of human biology, a comparative study of standard skull and pelvic nonmetric sex indicators is presented. METHODS: A Native Alaskan archeological sample (n = 104) and a component of the Terry collection (n = 99) represent populations originating from different climatic environments in recent history. These sex-balanced groups are compared through Tukey-Kramer’s method and Greene’s t-test to determine any variation in degree of sexual dimorphism within and between samples. RESULTS: The results reinforce the complex and multifaceted relationship between climate and sexual dimorphism. The Terry sample demonstrated a greater degree of sexual dimorphism with statistically significant differences in robusticity of the mastoid process and nuchal crest compared with the Native Alaskans. A more “male” morphotype and reduced dimorphism are appreciated in the pelves of Native Alaskans than the Terry sample. CONCLUSIONS: This research highlights a reduction in sexual dimorphism in populations under greater climatic stress and contributes to the production of more accurate skeletal assessments in future investigations. Discussion of confounding factors suggest more research is necessary to untangle climate and human morphology’s complex relationship. This study contributes to a greater appreciation of human biological plasticity, ecogeographic variation, and the evolution of modern human diversity.
BACKGROUND: This study examines the impact of climate, socio-economic and demographic factors on the incidence of dengue in regions of the United States and Mexico. We select factors shown to predict dengue at a local level and test whether the association can be generalized to the regional or state level. In addition, we assess how different indicators perform compared to per capita gross domestic product (GDP), an indicator that is commonly used to predict the future distribution of dengue. METHODS: A unique spatial-temporal dataset was created by collating information from a variety of data sources to perform empirical analyses at the regional level. Relevant regions for the analysis were selected based on their receptivity and vulnerability to dengue. A conceptual framework was elaborated to guide variable selection. The relationship between the incidence of dengue and the climate, socio-economic and demographic factors was modelled via a Generalized Additive Model (GAM), which also accounted for the spatial and temporal auto-correlation. RESULTS: The socio-economic indicator (representing household income, education of the labour force, life expectancy at birth, and housing overcrowding), as well as more extensive access to broadband are associated with a drop in the incidence of dengue; by contrast, population growth and inter-regional migration are associated with higher incidence, after taking climate into account. An ageing population is also a predictor of higher incidence, but the relationship is concave and flattens at high rates. The rate of active physicians is associated with higher incidence, most likely because of more accurate reporting. If focusing on Mexico only, results remain broadly similar, however, workforce education was a better predictor of a drop in the incidence of dengue than household income. CONCLUSIONS: Two lessons can be drawn from this study: first, while higher GDP is generally associated with a drop in the incidence of dengue, a more granular analysis reveals that the crucial factors are a rise in education (with fewer jobs in the primary sector) and better access to information or technological infrastructure. Secondly, factors that were shown to have an impact of dengue at the local level are also good predictors at the regional level. These indices may help us better understand factors responsible for the global distribution of dengue and also, given a warming climate, may help us to better predict vulnerable populations on a larger scale.
OBJECTIVES: This study sought to understand factors related to weather-related disaster survivors’ health information and mental health-care-seeking behaviors. METHODS: In November 2017, we conducted a quantitative survey of 170 Gulf Coast residents who experienced weather-related disasters. The survey assessed how individual and psychosocial factors affect health-care-seeking behavior. RESULTS: Nearly 66% of participants reported a high frequency of depression and/or anxiety symptoms, yet only 39% saw a medical professional. Of participants who visited a medical professional, 76% sought information from nonmedical sources. Seeking medical care was strongly correlated with seeking information from nonmedical sources and previous healthcare experiences, but not with fear and stigma. CONCLUSIONS: Positive communication and strong support systems have the potential to mitigate the reluctance people have in seeking help for mental health problems. Although it is discouraging that few people seek professional care, it is promising that participants were not avoiding care due to fear of being stigmatized. Less opposition to mental health care by survivors offers opportunity for mental health professionals to treat the psychological problems survivors experience. Providing necessary information may make headway to mental health care where it is greatly needed.
The sensitivities of meteorological and chemical predictions to urban effects over four major North American cities are investigated using the high-resolution (2.5-km) Environment and Climate Change Canada’s air quality model with the Town Energy Balance (TEB) scheme. Comparisons between the model simulation results with and without the TEB effect show that urbanization has great impacts on surface heat fluxes, vertical diffusivity, air temperature, humidity, atmospheric boundary layer height, land-lake circulation, air pollutants concentrations and Air Quality Health Index. The impacts have strong diurnal variabilities, and are very different in summer and winter. While the diurnal variations of the impacts share some similarities over each city, the magnitudes can be very different. The underlying mechanisms of the impacts are investigated. The TEB impacts on the predictions of meteorological and air pollutants over Toronto are evaluated against ground-based observations. The results show that the TEB scheme leads to a great improvement in biases and root-mean-square deviations in temperature and humidity predictions in downtown, uptown and suburban areas in the early morning and nighttime. The scheme also leads to a big improvement of predictions of NOx, PM2.5 and ground-level ozone in the downtown, uptown and industrial areas in the early morning and nighttime.
Rationale: There is significant evidence of increased healthcare utilization from cardiopulmonary causes in adults from exposure to wildfire smoke, but evidence in pediatric age groups is limited.Objectives: To quantify and examine the healthcare utilization effects of the December 2017 Lilac Fire in San Diego County among pediatric patients at the Rady Children’s Hospital (RCH) emergency department and urgent care (UC) clinics.Methods: Using data from 2011 to 2017, including data on daily particulate matter <2.5 ?m (PM(2.5)) in an inverse-distance interpolation model and RCH electronic medical records, we retrospectively analyzed pediatric respiratory visits at the RCH emergency department and UC clinics during the Santa Ana wind (SAW)-driven Lilac Fire from December 7 to 16, 2017. An interrupted time series study design was applied as our primary analysis to compare the observed pediatric respiratory visits from December 7 to 16, 2017 to what would have occurred in a counterfactual situation, namely, if the Lilac Fire had not occurred. A complementary descriptive spatial analysis was also used to evaluate the geographic distribution of respiratory visits in relationship to satellite imaging of the Lilac Fire and the associated wind pattern.Results: The Lilac Fire was associated with 16.0 (95% confidence interval [CI], 11.2-20.9) excess respiratory visits per day at the RCH emergency department across all pediatric age groups. Children aged 0 to 5 years had the highest absolute excess respiratory visits per day with 7.3 (95% CI, 3.0-11.7), whereas those aged 6 to 12 years had the highest relative increase in visits, with 3.4 (95% CI, 2.3-4.6). RCH UC clinics had similar results. The top five ZIP codes in San Diego County with the highest standard deviations of age-adjusted respiratory visits were all located generally downwind of the fire perimeter, as expected for the SAW pattern.Conclusions: We have demonstrated an increase in pediatric respiratory visits during the SAW-driven Lilac Fire in San Diego County in a patterned geographic distribution that is attributable to an increase in PM(2.5) exposure. Younger children were particularly affected. Climate change is expected to result in more frequent and extensive wildfires in the region and will require greater preparedness and adaptation efforts to protect vulnerable populations, such as young children.
Precipitation extremes are increasing globally due to anthropogenic climate change. However, there remains uncertainty regarding impacts upon flood occurrence and subsequent population exposure. Here, we quantify changes in population exposure to flood hazard across the contiguous United States. We combine simulations from a climate model large ensemble and a high-resolution hydrodynamic flood model-allowing us to directly assess changes across a wide range of extreme precipitation magnitudes and accumulation timescales. We report a mean increase in the 100-year precipitation event of similar to 20% (magnitude) and >200% (frequency) in a high warming scenario, yielding a similar to 30-127% increase in population exposure. We further find a nonlinear increase for the most intense precipitation events-suggesting accelerating societal impacts from historically rare or unprecedented precipitation events in the 21st century. Plain Language Summary Heavy rainfall is increasing globally due to human-caused global warming. However, it is still unclear how these increases in heavy rainfall might affect flood risk. In this paper, we investigate how global warming and population changes together may be affecting the number of people at risk from floods in the United States. We combine simulations from a climate model and flood model-allowing us to consider a wide range of heavy rainfall events. We report a similar to 20% increase in the size and a >200% increase in the frequency of very heavy and rare rainfall events, which leads to a similar to 30-127% increase in the number of people at risk from floods. Finally, we find that the heaviest rainfall events increase by the widest margin-suggesting the possibility of major increases in damage and disruption caused by severe floods in the 21st century.
Major perturbations in soil and water quality are factors that can negatively impact human health. In soil environments of urban areas, changes in antibiotic-resistance profiles may represent an increased risk of exposure to antibiotic-resistant bacteria via oral, dermal, or inhalation routes. We studied the perturbation of antibiotic-resistance profiles and microbial communities in soils following a major flooding event in Houston, Texas, caused by Hurricane Harvey. The main objective of this study was to examine the presence of targeted antibiotic-resistance genes and changes in the diversity of microbial communities in soils a short time (3-5?months) and a long time (18?months) after the catastrophic flooding event. Using polymerase chain reaction, we surveyed fourteen antibiotic-resistance elements: intI1, intI2, sul1, sul2, tet(A) to (E), tet(M), tet(O), tet(W), tet(X), and bla(CMY-2). The number of antibiotic-resistance genes detected were higher in short-time samples compared to samples taken a long time after flooding. From all the genes surveyed, only tet(E), bla(CMY-2), and intI1 were prevalent in short-time samples but not observed in long-time samples; thus, we propose these genes as indicators of exogenous antibiotic resistance in the soils. Sequencing of the V3-V4 region of the bacterial 16S rRNA gene was used to find that flooding may have affected bacterial community diversity, enhanced differences among bacterial lineages profiles, and affected the relative abundance of Actinobacteria, Verrucomicrobia, and Gemmatimonadetes. A major conclusion of this study is that antibiotic resistance profiles of soil bacteria are impacted by urban flooding events such that they may pose an enhanced risk of exposure for up to three to five months following the hurricane. The occurrence of targeted antibiotic-resistance elements decreased eighteen months after the hurricane indicating a reduction of the risk of exposure long time after Harvey.
Urban heat island (UHI) is the best acknowledged climate-change related phenomenon also because it affects population health conditions in dense urban areas, even exacerbated during heat waves. While most of field studies are performed by means of permanent weather stations, this paper presents an intra-urban microclimate analysis through wearable sensing techniques for monitoring and characterizing granular peculiarities as perceived by urban pedestrians. The study is implemented in four areas of New York City presenting already mitigation techniques. These strategies are specifically analyzed from the pedestrians’ perspective, who may walk along parks and sidewalks, to better study real boundary conditions responsible for thermal perception, even in those areas where vehicles are not allowed. A novel cluster analysis procedure is then carried out to perform data-driven identification of urban microclimate peculiarities in relation to its morphology (e.g. urban canyons etc.). Results show a non-negligible dependency from urban configuration both in winter and in summer. Measurements in the high-packed district winter daytime show a drop off of 0.6 degrees C in air temperature close to small parks. The packed low-rise district presents highest values of CO2, with respect to the other monitored areas both in winter and in summer. The same areas are automatically recognized through the data-driven clustering process. The data-driven approach may be therefore successfully integrated into classic measurements to investigate UHI and heat stress in dense anthropized areas.
The negative effects of urban heat islands (UHIs) on citizens’ well-being and life quality are widely acknowledged, but they still represent critical challenges, particularly since urban population is predicted to rise to 60% of the world population by 2030. Computational models have become useful tools for addressing these challenges and investigating urban microclimate repercussions on citizens’ comfort and urban liveability. Despite that, humans typically remain absent from such models. This work bridges this gap, moving beyond purely thermodynamic Urban Canopy Models (UCMs) to highlight the importance of integrating even simplified pedestrians’ biophysics for comfort assessment. Human physiology parameterization is therefore introduced into the Princeton Urban Canopy Model (PUCM), which had been designed to investigate the effect of greenery and novel materials on the UHI. Human thermal comfort is assessed in terms of the skin temperature and then evaluated against the apparent temperature, a widely-used thermal comfort indicator. Different configurations of the same urban canyon are therefore tested to assess the effectiveness of cool materials and trees for human thermal comfort enhancement. Results show that cool skins in the canyon’s built environment lead to an air temperature reduction up to 1.92 K, but slightly worsen human comfort in terms of a warmer computed skin temperature by 0.27 K. The indirect effect of trees, that exclude shading, are negligible for human thermal comfort. The new integrated human-centric model can help policymakers and urban planners to easily assess the potential benefits or threats to citizens’ well-being associated with specific urban configurations.
OBJECTIVE: The aim of this study is to determine the response of home-based primary care programs to the fall 2017 Atlantic hurricane season. METHODS: This study examines the experiences of 9 Veterans Health Administration (VHA) Home-Based Primary Care (HBPC) programs in their responses to Hurricanes Harvey, Irma, and Maria. Thirty-four phone interviews with HBPC leadership and staff were conducted from April to July 2018. RESULTS: The total census of impacted HBPC programs was 3118. No program reported loss of life due to these hurricanes. Early preparedness was key to an effective program response. Response included prompt tracking of the patients. In the most affected areas, respondents noted limited resources to support basic patient needs. CONCLUSIONS: Medically complex patients served by programs such as the VHA’s HBPC program represent a subset of the population, yet they have an outsized impact on health care resources that could be exacerbated by inadequate disaster preparedness. HBPC programs serve a unique role in supporting the “older old.” They are tasked with supporting disaster preparedness activities of patients. Understanding what is involved in actualizing their requirements shows communities how to effectively engage with these programs.
INTRODUCTION: Hurricanes have increased in severity over the past 35 years, and climate change has led to an increased frequency of catastrophic flooding. The impact of floods on emergency department (ED) operations and patient health has not been well studied. We sought to detail challenges and lessons learned from the severe weather event caused by Hurricane Harvey in Houston, Texas, in August 2017. METHODS: This report combines narrative data from interviews with retrospective data on patient volumes, mode of arrival, and ED lengths of stay (LOS). We compared the five-week peri-storm period for the 2017 hurricane to similar periods in 2015 and 2016. RESULTS: For five days, flooding limited access to the hospital, with a consequent negative impact on provider staffing availability, disposition and transfer processes, and resource consumption. Interruption of patient transfer capabilities threatened patient safety, but flexibility of operations prevented poor outcomes. The total ED patient census for the study period decreased in 2017 (7062 patients) compared to 2015 (7665 patients) and 2016 (7770) patients). Over the five-week study period, the arrival-by-ambulance rate was 12.45% in 2017 compared to 10.1% in 2016 (p < 0.0001) and 13.7% in 2015 (p < 0.0001). The median ED length of stay (LOS) in minutes for admitted patients was 976 minutes in 2015 (p < 0.0001) compared to 723 minutes in 2016 and 591 in 2017 (p < 0.0001). For discharged patients, median ED LOS was 336 minutes in 2016 compared to 356 in 2015 (p < 0.0001) and 261 in 2017 (p < 0.0001). Median boarding time for admitted ED patients was 284 minutes in 2016 compared to 470 in 2015 (p < 0.0001) and 234.5 in 2017 (p < 0.001). Water damage resulted in a loss of 133 of 179 inpatient beds (74%). Rapid and dynamic ED process changes were made to share ED beds with admitted patients and to maximize transfers post-flooding to decrease ED boarding times. CONCLUSION: A number of pre-storm preparations could have allowed for smoother and safer ride-out functioning for both hospital personnel and patients. These measures include surplus provisioning of staff and supplies to account for limited facility access. During a disaster, innovative flexibility of both ED and hospital operations may be critical when disposition and transfer capibilities or bedding capacity are compromised.
OBJECTIVES: Maricopa County, Arizona (2017 population about 4.3 million), is located in the Sonoran Desert. In 2005, the Maricopa County Department of Public Health (MCDPH) established a heat-associated mortality surveillance system that captures data on circumstances of death for Maricopa County residents and visitors. We analyzed 2006-2016 surveillance system data to understand the characteristics and circumstances of heat-associated deaths. METHODS: We classified heat-associated deaths based on International Classification of Diseases, Tenth Revision codes (X30, T67.X, and P81.0) and phrases (heat exposure, environ, exhaustion, sun, heat stress, heat stroke, or hyperthermia) in part I or part II of the death certificate. We summarized data on decedents’ demographic characteristics, years lived in Arizona, location of death (indoors vs outdoors), presence and functionality of air conditioning, and whether the decedent had been homeless. We examined significant associations between variables by using the Pearson ?(2) tests and logistic regression. RESULTS: During 2006-2016, MCDPH recorded data on 920 heat-associated deaths, 912 of which included location of injury. Of 565 (62%) heat-associated deaths that occurred outdoors, 458 (81%) were among male decedents and 243 (43%) were among decedents aged 20-49. Of 347 (38%) heat-associated deaths that occurred indoors, 201 (58%) were among decedents aged ?65. Non-Arizona residents were 5 times as likely as Arizona residents to have a heat-associated death outdoors (P < .001). Of 727 decedents with data on duration of Arizona residency, 438 (60%) had resided in Arizona ?20 years. CONCLUSIONS: Ongoing evaluation of interventions that target populations at risk for both outdoor and indoor heat-associated deaths can further inform refinement of the surveillance system and identify best practices to prevent heat-associated deaths.
BACKGROUND: Heatwaves kill more people than floods, tornadoes, and earthquakes combined and disproportionally affect older persons and those with chronic conditions. Commonly used medications for chronic conditions, e.g., diuretics, antipsychotics disrupt thermoregulation or fluid/electrolyte balance and may sensitive patients to heat. However, the effect of heat-sensitizing medications and their interactions with heatwaves are not well-quantified. We evaluated effects of potentially heat-sensitizing medications in vulnerable older patients. METHODS: US Medicare data were linked at the zip code level to climate data with surface air temperatures for June-August of 2007-2012. Patients were Medicare beneficiaries aged ?65 years with chronic conditions including diabetes, dementia, and cardiovascular, lung, or kidney disease. Exposures were potentially heat-sensitizing medications including diuretics, anticholinergics, antipsychotics, beta blockers, stimulants, and anti-hypertensives. A heatwave was defined as ?2 days above the 95th percentile of historical zip code-specific surface air temperatures. We estimated associations of heat-sensitizing medications and heatwaves with heat-related hospitalization using self-controlled case series analysis. RESULTS: We identified 9,721 patients with at least one chronic condition and heat-related hospitalization; 42.1% of these patients experienced a heatwave. Heatwaves were associated with an increase in heat-related hospitalizations ranging from 21% (95% CI: 7% to 38%) to 33% (95% CI: 14% to 55%) across medication classes. Several drug classes were associated with moderately elevated risk of heat-related hospitalization in the absence of heatwaves, with rate ratios ranging from 1.16 (95% CI: 1.00 to 1.35) to 1.37 (95% CI: 1.14 to 1.66). We did not observe meaningful synergistic interactions between heatwaves and medications. CONCLUSIONS: Older patients with chronic conditions may be at heightened risk for heat-related hospitalization due to the use of heat-sensitizing medications throughout the summer months, even in the absence of heatwaves. Further studies are needed to confirm these findings and also to understand the effect of milder and shorter heat exposure.
Extreme precipitation events may be an important environmental trigger for asthma exacerbations in children. We used a time stratified case-crossover design and data from a large electronic health record database at the Children’s Hospital of Philadelphia (CHOP) to estimate associations of daily heavy precipitation (defined as > 95th percentile of the summertime distribution) with asthma exacerbation among children. We defined control days as those falling on the same day of the week within the same month and year as the case. We restricted our primary analyses to the summer months in years 2011-2016 and used conditional logistic regression models to estimate associations between heavy precipitation and acute asthma exacerbations in both outpatient (primary care, specialty care, and emergency department) and inpatient settings. We investigated numerous individual-level (e.g., age, sex, eczema diagnosis) and environmental measures (e.g., greenspace, particulate matter) as potential effect modifiers. The analysis include 13,483 asthma exacerbations in 10,434 children. Odds of asthma exacerbation were 11% higher on heavy precipitation vs. no precipitation days (95% CI: 1.02-1.21). There was little evidence of effect modification by most measures. These results suggest that heavy summertime precipitation events may contribute to asthma exacerbations. Further research using larger datasets from other health systems is needed to confirm these results, and to explore underlying mechanisms.
Runoff from heavy precipitation events can lead to microbiological contamination of source waters for public drinking water supplies. Philadelphia is a city of interest for a study of waterborne acute gastrointestinal illness (AGI) because of frequent heavy precipitation, extensive impervious landcover, and combined sewer systems that lead to overflows. We conducted a time-series analysis of the association between heavy precipitation and AGI incidence in Philadelphia, served by drinking water from Delaware River and Schuylkill River source waters. AGI cases on each day during the study period (2015-2017) were captured through syndromic surveillance of patients’ chief complaint upon presentation at local emergency departments. Daily precipitation was represented by measurements at the Philadelphia International Airport and by modeled precipitation within the watershed boundaries, and we also evaluated stream flowrate as a proxy of precipitation. We estimated the association using distributed lag nonlinear models, assuming a quasi-Poisson distribution of the outcome variable and with adjustment for potential confounding by seasonal and long-term time trends, ambient temperature, day-of-week, and major holidays. We observed an association between heavy precipitation and AGI incidence in Philadelphia that was primarily limited to the spring season, with significant increases in AGI that peaked from 8 to 16 days following a heavy precipitation event. For example, the increase in AGI incidence related to airport precipitation above the 95th percentile (vs no precipitation) during spring reached statistical significance on lag day 7, peaked on day 16 (102% increase, 95% confidence interval: 16%, 252%), and declined while remaining significantly elevated through day 28. Similar associations were observed in analyses of watershed-specific precipitation in relation to AGI cases within the populations served by drinking water from each river. Our results suggest that heavy precipitation events in Philadelphia result in detectable local increases in waterborne AGI.
BACKGROUND: Heat related illness (HRI) places a significant burden on the health and safety of working populations and its impacts will likely increase with climate change. The aim of this study was to characterize the demographic and occupational characteristics of Washington workers who suffered from HRI from 2006 to 2017 using workers’ compensation claims data. METHODS: We used Washington workers’ compensation data linked to weather station data to identify cases of work-related HRI. We utilized Occupational Injury and Illness Classification System codes, International Classification of Diseases 9/10 codes, and medical review to identify accepted and rejected Washington State (WA) workers’ compensation claims for HRI from 2006 to 2017. We estimated rates of HRI by industry and evaluated patterns by ambient temperature. RESULTS: We detected 918 confirmed Washington workers’ compensation HRI claims from 2006 to 2017, 654 were accepted and 264 were rejected. Public Administration had the highest third quarter rate (131.3 per 100?000 full time employees [FTE]), followed by Agriculture, Forestry, Fishing, and Hunting (102.6 per 100?000 FTE). The median maximum daytime temperature was below the Washington heat rule threshold for 45% of the accepted HRI claims. Latinos were estimated to be overrepresented in HRI cases. CONCLUSION: The WA heat rule threshold may not be adequately protecting workers and racial disparities are present in occupational HRI. Employers should take additional precautions to prevent HRI depending on the intensity of heat exposure. States without heat rules and with large industry sectors disproportionately affected by HRI should consider regulations to protect outdoor workers in the face of more frequent and extreme heat waves.
Heat waves are the deadliest type of natural hazard among all weather extremes in the United States. Given the observed and anticipated increase in heat risks associated with ongoing climate change, this study examines community vulnerability to extreme heat and the degree to which heat island mitigation (HIM) actions by state/local governments reduce heat-induced fatalities. The analysis uses all heat events that occurred over the 1996-2011 period for all United States counties to model heat vulnerability. Results show that: (1) Higher income reduces extreme heat vulnerability, while poverty intensifies it; (2) living in mobile homes or rental homes heightens susceptibility to extreme heat; (3) increased heat vulnerability due to the growth of the elderly population is predicted to result in a two-fold increase in heat-related fatalities by 2030; and (4) community heat island mitigation measures reduce heat intensities and thus heat-related fatalities. Findings also show that an additional locally implemented measure reduces the annual death rate by 15%. A falsification test rules out the possibility of spurious inference on the life-saving role of heat island mitigation measures. Overall, these findings inform efforts to protect the most vulnerable population subgroups and guide future policies to counteract the growing risk of deadly heat waves.
Purpose The purpose of this paper is to examine the seasonal performance, occupants’ comfort and cold stress in cross-laminated timber school buildings located in the USA (Northeast region). Design/methodology/approach The Fall survey was done from October-November 2017. In the Winter, it was considered from December 2017-February 2018. The study measured environmental parameters in the chosen spaces. The research applied the wet-bulb globe temperature (WBGT) model to determine the indexes in various seasons. Findings In the Fall, the average inside temperature was 21.2 degrees C, the average RH was 50.7 per cent, and the mean dew-point was 9.3 degrees C. The mean inside temperature was 20.5 degrees C in the Winter while the mean RH was 23.9 per cent and the average dew-point was -1.9 degrees C. The overall mean inside temperatures in both seasons were within the ASHRAE comfort temperature limits for cold seasons. During the surveys, higher average values of temperature, RH and dew-point were measured in the offices than the other spaces. Practical implications The research showed people might be subject to lower temperatures in the hall than the other spaces. Some design parameters and occupation hours may contribute to the lower temperatures reported in the hall than the different spaces. Originality/value The study proposes the WBGT of 16.0 degrees C and 13.7 degrees C as the stress indexes in the Fall and Winter seasons correspondingly. Last, the research suggests a WBGT of 14.9 degrees C as the overall mean stress index within the spaces considered in this study.
The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop.
BACKGROUND: Sport organizations must comprehensively assess the degree to which their athletes are susceptible to exertional heat illnesses (i.e. vulnerable) to appropriately plan and adapt for heat-related hazards. Yet, no heat vulnerability framework has been applied in practice to guide decision making. OBJECTIVES: We quantify heat vulnerability of state-level requirements for health and safety standards affecting United States (US) high school athletes as a case study. DESIGN: Observational. METHODS: We utilize a newly developed climate vulnerability to sports organizations framework (CVSO), which considers the heat hazard of each state using summer maximum wet bulb globe temperature (WBGT) in combination with an 18-point heat safety scoring system (18 = best policy). Heat vulnerability is categorized as “problem” [higher heat (>27.9°C) and lower policy score (?9)], “fortified” [higher heat (>27.9°C) and higher policy score (>9)], “responsive” [lower heat (<27.9°C) and lower policy score (?9)], and “proactive” [lower heat (<27.9°C) and higher policy score (>9)]. RESULTS: Across the US, the mean WBGT was 28.4±2.4°C and policy score was 6.9±4.7. In combination, we observed organizations within each of the four vulnerability categories with 16% (n=8) in fortified, 16% (n=8) in proactive, 29% (n=15) in problem, and 39% (n=20) in responsive. CONCLUSIONS: The CSVO framework allowed us to identify different degrees of vulnerability among the state’s and to highlight the 29% (n=15) of states with immediate needs for policy revisions. We found the CSVO framework to be highly adaptable in our application, suggesting feasibility for use with other sports governing bodies.
Hurricane Harvey made a landfall on the Texas Gulf Coast on August 25, 2017, stalling over Harris County as a tropical storm for 4 days (August 26-29), dumping approximately 127 cm of rain. This tremendous amount of rainfall overwhelmed the county’s natural and man-made drainage systems, resulting in unprecedented widespread flooding. Immediately following, Harris County Public Health Mosquito and Vector Control Division conducted a countywide emergency vector control response by integrating surveillance, control, and education strategies. This included landing rate counts, mosquito and avian surveillance, arbovirus testing, ground-based ultra-low volume (ULV) and aerial pesticide spraying, and community outreach. The immediate response lasted for 4 wk through September, resulting in 774 landing rates, 49,342 ha treated by ground-based ULV, 242,811 ha treated by aerial ULV, 83,241 mosquitoes collected, 1,807 mosquito pools tested, and 20 education/outreach sessions. Recovery activities of 3 additional education/outreach events continued through October while surveillance and control activities returned to routine status.
Wildfires have a significant adverse impact on air quality in the United States (US). To understand the potential health impacts of wildfire smoke, many epidemiology studies rely on concentrations of fine particulate matter (PM) as a smoke tracer. However, there are many gas-phase hazardous air pollutants (HAPs) identified by the Environmental Protection Agency (EPA) that are also present in wildfire smoke plumes. Using observations from the Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE-CAN), a 2018 aircraft-based field campaign that measured HAPs and PM in western US wildfire smoke plumes, we identify the relationships between HAPs and associated health risks, PM, and smoke age. We find the ratios between acute, chronic noncancer, and chronic cancer HAPs health risk and PM in smoke decrease as a function of smoke age by up to 72% from fresh (<1 day of aging) to old (>3 days of aging) smoke. We show that acrolein, formaldehyde, benzene, and hydrogen cyanide are the dominant contributors to gas-phase HAPs risk in smoke plumes. Finally, we use ratios of HAPs to PM along with annual average smoke-specific PM to estimate current and potential future smoke HAPs risks.
Extreme heat events can lead to increased risk of heat-related deaths. Furthermore, urban areas are often hotter than their rural surroundings, exacerbating heat waves. Unfortunately, validation is difficult; to our knowledge, most validations, even if they control for temperatures, really only validate a social vulnerability index instead of a heat vulnerability index. Here we investigate how to construct and validate a heat vulnerability index given uncertainty ranges in data for the city of Rio de Janeiro. First, we compare excess deaths of certain types of circulatory diseases during heat waves. Second, we use demographic and environmental data and factor analysis to construct a set of unobserved factors and respective weightings related to heat vulnerability, including a Monte Carlo analysis to represent the uncertainty ranges assigned to the input data. Finally, we use distance to hospital and clinics and their health record data as an instrumental variable to validate our factors. We find that we can validate the Rio de Janeiro heat vulnerability index against excess deaths during heat waves; specifically, we use three types of regressions coupled with difference in difference calculations to show this is indeed a heat vulnerability index as opposed to a social vulnerability index. The factor analysis identifies two factors that contribute to >70% of the variability in the data; one socio-economic factor and one urban form factor. This suggests it is necessary to add a step to existing methods for validation of heat vulnerability indices, that of the difference-in-difference calculation.
Exposure to wildfire smoke causes adverse health outcomes, suggesting the importance of accurately estimating smoke concentrations. Geostatistical methods can combine observed, modeled, and satellite-derived concentrations to produce accurate estimates. Here, we estimate daily average ground-level PM2.5 concentrations at a 1 km resolution during the October 2017 California wildfires, using the Constant Air Quality Model Performance (CAMP) and Bayesian Maximum Entropy (BME) methods to bias-correct and fuse three concentration datasets: permanent and temporary monitoring stations, a chemical transport model (CTM), and satellite-derived estimates. Four BME space/time kriging and data fusion methods were evaluated. All BME methods produce more accurate estimates than the standalone CTM and satellite products. Adding temporary station data increases the R-2 by 36%. The data fusion of observations with the CAMP-corrected CTM and satellite-derived concentrations provides the best estimate (R-2 = 0.713) in fire-impacted regions, emphasizing the importance of combining multiple datasets. We estimate that approximately 65,000 people were exposed to very unhealthy air (daily average PM2.5 >= 150.5 mu g/m(3)).
Thermal comfort is an important determinant of quality of life and economic vitality in cities. Strategies to improve thermal comfort may become a more critical part of urban sustainability efforts with projections of continued urban growth and climate change. A case study was performed in the hot, dry summertime climate of Tempe, Arizona to quantify the influence of evaporative misters on the thermal environment in outdoor restaurants and to understand business managers’ motivations to use misters. Microclimate measurements (air temperature (T(a)), wind speed, relative humidity, globe temperature) were taken at five restaurants midday within four exposures: misted sun, misted shade, sun only, and shade only. We assessed T(a), mean radiant temperature (MRT), universal thermal climate index (UTCI), and physiological equivalent temperature (PET) between these four conditions within each location. Misters improved thermal comfort across all days, sites, and exposure conditions. MRT was on average 7.6 °C lower in misted locations, which significantly lowered average PET (- 6.5 °C) and UTCI (- 4.4 °C) (p < 0.05). Thermal comfort was most improved using mist in combination with shade. Under such conditions, PET and UTCI were reduced by 15.5 °C and 9.7 °C (p < 0.05), respectively. Business managers identified customer comfort and increased seating capacity as the principal factors for mister use. Esthetics of misters further encouraged use, while cost and environmental concerns were perceived to be less important. While this case study demonstrates value in outdoor misting in a hot, dry climate, additional work is needed to more fully evaluate tradeoffs between cost, water use, and comfort with continuing urban growth.
Background.Exposure to high air temperature in late pregnancy is increasingly recognized as a risk factor for preterm birth (PTB). However, the combined effects of heatwaves with air pollution and green space are still unexplored. In the context of climate change, investigating the interaction between environmental factors and identifying communities at higher risk is important to better understand the etiological mechanisms and design targeted interventions towards certain women during pregnancy.Objectives.To examine the combined effects of heatwaves, air pollution and green space exposure on the risk of PTB.Methods.California birth certificate records for singleton births (2005-2013) were obtained. Residential zip code-specific daily temperature during the last week of gestation was used to create 12 definitions of heatwave with varying temperature thresholds and durations. We fit multi-level Cox proportional hazard models with time to PTB as the outcome and gestational week as the temporal unit. Relative risk due to interaction (RERI) was applied to estimate the additive interactive effect of air pollution and green space on the effect of heatwaves on PTB.Results.In total, 1 967 300 births were included in this study. For PM2.5, PM(10)and O-3, we found positive additive interactions (RERIs >0) between heatwaves and higher air pollution levels. Combined effects of heatwaves and green space indicated negative interactions (RERIs <0) for less intense heatwaves (i.e. shorter duration or relatively low temperature), whereas there were potential positive interactions (RERIs >0) for more intense heatwaves.Conclusion.This study found synergistic harmful effects for heatwaves with air pollution, and potential positive interactions with lack of green space on PTB. Implementing interventions, such as heat warning systems and behavioral changes, targeted toward pregnant women at risk for high air pollution and low green space exposures may optimize the benefits of reducing acute exposure to extreme heat before delivery.
Although heat exposure is the leading cause of mortality for undocumented immigrants attempting to traverse the Mexico-U.S. border, there has been little work in quantifying risk. Therefore, our study aims to develop a methodology projecting increase in core temperature over time and space for migrants in Southern Arizona using spatial analysis and remote sensing in combination with the heat balance equation-adapting physiological formulae to a multi-step geospatial model using local climate conditions, terrain, and body specifics. We sought to quantitatively compare the results by demographic categories of age and sex and qualitatively compare them to known terrestrial conditions and prior studies of those conditions. We demonstrated a more detailed measure of risk for migrants than those used most recently: energy expenditure and terrain ruggedness. Our study not only gives a better understanding of the ‘funnel effect’ mechanisms, but also provides an opportunity for relief and rescue operations.
Wildfires, which are becoming more frequent and intense in many countries, pose serious threats to human health. To determine health impacts and provide public health messaging, satellite-based smoke plume data are sometimes used as a proxy for directly measured particulate matter levels. We collected data on particulate matter <2.5 mu m in diameter (PM2.5) concentration from 16 ground-level monitoring stations in the San Francisco Bay Area and smoke plume density from satellite imagery for the 2017-2018 California wildfire seasons. We tested for trends and calculated bootstrapped differences in the median PM2.5 concentrations by plume density category on a 0-3 scale. The median PM2.5 concentrations for categories 0, 1, 2, and 3 were 16, 22, 25, and 63 mu g/m(3), respectively, and there was much variability in PM2.5 concentrations within each category. A case study of the Camp Fire illustrates that in San Francisco, PM2.5 concentrations reached their maximum many days after the peak for plume density scores. We found that air pollution characterization by satellite imagery did not precisely align with ground-level PM2.5 concentrations. Public health practitioners should recognize the need to combine multiple sources of data regarding smoke patterns when developing public guidance to limit the health effects of wildfire smoke.
Media reports and public polls suggest that young people in many countries are increasingly factoring climate change into their reproductive choices, but empirical evidence about this phenomenon is lacking. This article reviews the scholarship on this subject and discusses the results of the first empirical study focused on it, a quantitative and qualitative survey of 607 US-Americans between the ages of 27 and 45. While 59.8% of respondents reported being “very” or “extremely concerned” about the carbon footprint of procreation, 96.5% of respondents were “very” or “extremely concerned” about the well-being of their existing, expected, or hypothetical children in a climate-changed world. This was largely due to an overwhelmingly negative expectation of the future with climate change. Younger respondents were more concerned about the climate impacts their children would experience than older respondents, and there was no statistically significant difference between the eco-reproductive concerns of male and female respondents. These and other results are situated within scholarship about growing climate concern in the USA, the concept of the carbon footprint, the carbon footprint of procreation, individual actions in response to climate change, temporal perceptions of climate change, and expectations about the future in the USA. Potential implications for future research in environmental psychology, environmental sociology, the sociology of reproduction, demography, and climate mitigation are discussed.
Arboviruses transmitted by Aedes aegypti and Aedes albopictus have been introduced to Florida on many occasions. Infrequently, these introductions lead to sporadic local transmission and, more rarely, sustained local transmission. Both mosquito species are present in Florida, with spatio-temporal variation in population composition. We developed a two-vector compartmental, deterministic model to investigate factors influencing Chikungunya virus (CHIKV) establishment. The model includes a nonlinear, temperature-dependent mosquito mortality function based on minimum mortality in a central temperature region. Latin Hypercube sampling was used to generate parameter sets used to simulate transmission dynamics, following the introduction of one infected human. The analysis was repeated for three values of the mortality function central temperature. Mean annual temperature was consistently important in the likelihood of epidemics, and epidemics increased as the central temperature increased. Ae. albopictus recruitment was influential at the lowest central temperature while Ae. aegypti recruitment was influential at higher central temperatures. Our results indicate that the likelihood of CHIKV establishment may vary, but overall Florida is permissive for introductions. Model outcomes were sensitive to the specifics of mosquito mortality. Mosquito biology parameters are variable, and improved understanding of this variation will improve our ability to predict the outcome of introductions.
Introduction: Hypothermia at admission in trauma patients has been significantly associated with worse outcomes and increased blood usage. Previous studies have found variably significant associations between ambient temperatures and incidence of hypothermia in trauma patients. Methods: The trauma quality improvement registry was queried for data on trauma patients admitted direct from the scene over a 5-year period. This database was matched to daily weather data taken from the nearest National Oceanic and Atmospheric Administration land-based climate monitoring center, and further combined with blood usage data from the laboratory information system. Results: Multivariate logistic regression models predicted significant associations between ambient temperature and patient admission temperature for severely injured patients. No significant direct associations were predicted between ambient temperature and in-hospital mortality or blood usage. Models predicted a significant association between decreased admission temperature and increased likelihood of both blood transfusion and mortality for a severely injured subgroup. Conclusions: Ambient temperature is a significant contributor to the rate of admission hypothermia in trauma patients. Most of the variability in admission temperatures for severely injured trauma patients remains unaccounted for by models using standard markers of anatomic and physiologic severity. Decreasing admission temperature is significantly associated with increased mortality and likelihood of blood transfusion for severely injured patients.
The 2020 Atlantic hurricane season was extremely active and included, as of early November, six hurricanes that made landfall in the United States during the global coronavirus disease 2019 (COVID-19) pandemic. Such an event would necessitate a large-scale evacuation, with implications for the trajectory of the pandemic. Here we model how a hypothetical hurricane evacuation from four counties in southeast Florida would affect COVID-19 case levels. We find that hurricane evacuation increases the total number of COVID-19 cases in both origin and destination locations; however, if transmission rates in destination counties can be kept from rising during evacuation, excess evacuation-induced case numbers can be minimized by directing evacuees to counties experiencing lower COVID-19 transmission rates. Ultimately, the number of excess COVID-19 cases produced by the evacuation depends on the ability of destination counties to meet evacuee needs while minimizing virus exposure through public health directives. These results are relevant to disease transmission during evacuations stemming from additional climate-related hazards such as wildfires and floods.
BACKGROUND: Adverse health effects among agricultural workers due to chronic heat exposure have been characterized in the literature as not only due to high ambient temperatures but also due to intensive manual labor in hot and humid conditions. The aim of this study was to use biomonitoring equipment to examine the effectiveness of selected cooling devices at preventing agricultural workers from exceeding the core body temperature threshold of 38.0°C (Tc38) and attenuating heat-related illness symptoms. METHODS: A convenience sample of 84 agricultural workers in Florida was randomized to one of four groups: (a) no intervention, clothing as usual; (b) cooling bandana; (c) cooling vest; and (d) both the cooling bandana and cooling vest. Biomonitoring equipment worn by the participants included core body temperature monitor and an accelerometer to capture physical activity. FINDINGS: A total of 78 agricultural workers completed one intervention workday trial. Compared with the control group, the bandana group had lower odds of exceeding Tc38 (odds ratio [OR] = 0.7, 90% confidence interval [CI] = [0.2, 3.2]) and the vest group had higher odds of exceeding Tc38 (OR = 1.8, 90% CI = [0.4, 7.9]). The simultaneous use of cooling vest and bandana showed an effect little different from the control group (OR = 1.3, 90% CI = [0.3, 5.6]). CONCLUSION/APPLICATION TO PRACTICE: This is the first field-based study to examine cooling intervention among agricultural workers in the United States using biomonitoring equipment. This study found that using a bandana while working in a hot agricultural environment has the potential to be protective against exceeding the recommended Tc38 threshold.
In today’s urban environments with complex design and configurations, heterogeneous spatial clusters of communities with different socioeconomic characteristics may result in disproportionate exposure of some groups of citizens to natural hazards. The objective of this study was to compare the associations between communities’ socioeconomic characteristics and exposure to different types of natural hazards in New York City (NYC) to examine whether commonly accepted indicators of social vulnerability are associated with similar levels of exposure across various natural hazards. First, we collected socioeconomic data (e.g., population, median income, unemployment rate) at a zip code level of granularity provided by the United States Census Bureau. Next, we identified and gathered spatial data for coastal storms, flooding, extreme heat, and pandemic disease in NYC. We then conducted a pairwise Kendall’s tau-b test to compare the associations. The outcomes showed that the significance and direction of the associations depend on the type of natural hazard. Particularly, the results indicated that zip codes with lower socioeconomic factors and greater percentage of minority ethnicities are exposed disproportionately to extreme heat and COVID-19. On the other hand, zip codes with higher percentage of areas prone to flooding have relatively higher socioeconomic factors. Furthermore, the results did not show any statistically significant association between socioeconomic factors and exposure to coastal storm inundations. The outcomes of this study will help decision makers design and implement better optimized and effective emergency preparedness plans by prioritizing their target areas based on socioeconomic factors in order to enhance social justice.
BACKGROUND: Tropical cyclone epidemiology can be advanced through exposure assessment methods that are comprehensive and consistent across space and time, as these facilitate multiyear, multistorm studies. Further, an understanding of patterns in and between exposure metrics that are based on specific hazards of the storm can help in designing tropical cyclone epidemiological research. OBJECTIVES: a) Provide an open-source data set for tropical cyclone exposure assessment for epidemiological research; and b) investigate patterns and agreement between county-level assessments of tropical cyclone exposure based on different storm hazards. METHODS: We created an open-source data set with data at the county level on exposure to four tropical cyclone hazards: peak sustained wind, rainfall, flooding, and tornadoes. The data cover all eastern U.S. counties for all land-falling or near-land Atlantic basin storms, covering 1996-2011 for all metrics and up to 1988-2018 for specific metrics. We validated measurements against other data sources and investigated patterns and agreement among binary exposure classifications based on these metrics, as well as compared them to use of distance from the storm’s track, which has been used as a proxy for exposure in some epidemiological studies. RESULTS: Our open-source data set was typically consistent with data from other sources, and we present and discuss areas of disagreement and other caveats. Over the study period and area, tropical cyclones typically brought different hazards to different counties. Therefore, when comparing exposure assessment between different hazard-specific metrics, agreement was usually low, as it also was when comparing exposure assessment based on a distance-based proxy measurement and any of the hazard-specific metrics. DISCUSSION: Our results provide a multihazard data set that can be leveraged for epidemiological research on tropical cyclones, as well as insights that can inform the design and analysis for tropical cyclone epidemiological research. https://doi.org/10.1289/EHP6976.
Air pollution and the urban heat island effect are consistently linked to numerous respiratory and heat-related illnesses. Additionally, these stressors disproportionately impact low-income and historically marginalized communities due to their proximity to emissions sources, lack of access to green space, and exposure to other adverse environmental conditions. Here, we use relatively low-cost stationary sensors to analyze PM2.5 and temperature data throughout the city of Richmond, Virginia, on the ten hottest days of 2019. For both hourly means within the ten hottest days of 2019 and daily means for the entire record for the year, the temperature was found to exhibit a positive correlation with PM2.5. Analysis of hourly means on the ten hottest days yielded a diurnal pattern in which PM2.5 levels peaked in the early morning and reached their minima in the mid-afternoon. Spatially, sites exhibiting higher temperatures consistently had higher PM2.5 readings, with vulnerable communities in the east end and more intensely developed parts of the city experiencing significantly higher temperatures and PM2.5 concentrations than the suburban neighborhoods in the west end. These findings suggest an uneven distribution of air pollution in Richmond during extreme heat events that are similar in pattern but less pronounced than the temperature differences during these events, although further investigation is required to verify the extent of this relationship. As other studies have found both of these environmental stressors to correlate with the distribution of green space and other land-use factors in cities, innovative and sustainable planning decisions are crucial to the mitigation of these issues of inequity going forward.
Importance Nursing home residents are at heightened risk for morbidity and mortality following an exposure to a disaster such as a hurricane or the COVID19 pandemic. Previous research has shown that nursing home resident mortality related to disasters is frequently underreported. There is a need to better understand the consequences of disasters on nursing home residents and to differentiate vulnerability based on patient characteristics. Objective To evaluate mortality and morbidity associated with exposure to Hurricane Irma, a Category 4 storm that made landfall on September 10, 2017, in Cudjoe Key, Florida, among short-stay (<90-day residence) and long-stay (>= 90-day residence) residents of nursing homes. Design, Setting, and Participants Cohort study of Florida nursing home residents comparing residents exposed to Hurricane Irma in September 2017 to a control group of residents residing at the same nursing homes over the same time period in calendar year 2015. Data were analyzed from August 28, 2019, to July 22, 2020. Exposure Residents who experienced Hurricane Irma were considered exposed; those who did not were considered unexposed. Main Outcome and Measures Outcome variables included 30-day and 90-day mortality and first hospitalizations after the storm in both the short term and the long term. Results A total of 61564 residents who were present in 640 Florida nursing home facilities on September 7, 2017, were identified. A comparison cohort of 61813 residents was evaluated in 2015. Both cohorts were mostly female (2015, 68%; 2017, 67%), mostly White (2015, 79%; 2017, 78%), and approximately 40% of the residents in each group were over the age of 85 years. Compared with the control group in 2015, an additional 262 more nursing home deaths were identified at 30 days and 433 more deaths at 90 days. The odds of a first hospitalization for those exposed (vs nonexposed) were 1.09 (95% CI, 1.05-1.13) within the first 30 days after the storm and 1.05 (95% CI, 1.02-1.08) at 90 days; the odds of mortality were 1.12 (95% CI, 1.05-1.18) at 30 days and 1.07 (95% CI, 1.03-1.11) at 90 days. Among long-stay residents, the odds of mortality for those exposed to Hurricane Irma were 1.18 (95% CI, 1.08-1.29) times those unexposed and the odds of hospitalization were 1.11 (95% CI, 1.04-1.18) times those unexposed in the post 30-day period. Conclusions and Relevance The findings of this study suggest that nursing home residents are at considerable risk to the consequences of disasters. These risks may be underreported by state and federal agencies. Long-stay residents, those who have resided in a nursing home for 90 days or more, may be most vulnerable to the consequences of hurricane disasters. This cohort study assess the association between exposure to Hurricane Irma and 30- and 90-day mortality and morbidity among short- and long-term residents of nursing homes in Florida. Question Was exposure to Hurricane Irma associated with an increased risk of hospitalization and mortality among nursing home residents in the 30 and 90 days after the storm compared with a control group? Findings In this cohort study of 61564 nursing home residents exposed to Hurricane Irma and a control group of 61813 nonexposed residents, the odds of a first hospitalization and mortality increased significantly at 30 and 90 days for those exposed. A long nursing home stay was associated with a greater risk for mortality compared with a short stay. Meaning Findings suggest that prioritizing heightened emergency preparedness in disaster situations for nursing home residents is warranted.
Objective: Given the lack of studies examining the associations between daily weather and air pollution with nightly objective sleep over multiple weeks, we quantified these associations in a prospective cohort of healthy participants with episodic migraine. Methods: Ninety-eight participants completed daily electronic diaries and wore an actigraph for an average of 45 ds, and a total 4406 nights of data were collected. Nightly sleep characteristics including duration, wake after sleep onset (WASO), and efficiency were assessed using wrist actigraphy. Daily weather parameters and air pollution levels were collected from local weather station and ground-level air quality monitors. We used linear fixed effects models adjusting for participant, day of the week, and day of the year (for weather analysis), and additionally adjusted for temperature and relative humidity (for air pollution analysis). Results: The participants were 35 +/- 12 yrs old and 86 were women. A 10 degrees F higher daily average temper-ature was associated with 0.88 (95% CI: 0.06, 1.70) minutes longer WASO and 0.14% (95% CI:-0.01%, 0.30%) lower sleep efficiency on that night. A 14 parts per billion (ppb) (interquartile range) higher daily maximum eight-h ozone was associated with 7.51 (95% CI: 3.23, 11.79) minutes longer sleep duration on that night. Associations did not differ between cold (October-March) and warm (April-September) seasons. Conclusions: Higher daily ozone was associated with longer sleep duration and modest associations were observed between higher temperature and lower WASO and lower efficiency. (c) 2020 Elsevier B.V. All rights reserved.
BACKGROUND: Despite the substantial role indoor exposure has played in heat wave-related mortality, few epidemiological studies have examined the health effects of exposure to indoor heat. As a result, knowledge gaps regarding indoor heat-health thresholds, vulnerability, and adaptive capacity persist. OBJECTIVE: We evaluated the role of indoor heat exposure on mortality and morbidity among the elderly ( ? 65?years of age) in Houston, Texas. METHODS: Mortality and emergency hospital admission data were obtained through the Texas Department of State Health Services. Summer indoor heat exposure was modeled at the U.S. Census block group (CBG) level using building energy models, outdoor weather data, and building characteristic data. Indoor heat-health associations were examined using time-stratified case-crossover models, controlling for temporal trends and meteorology, and matching on CBG of residence, year, month, and weekday of the adverse health event. Separate models were fitted for three indoor exposure metrics, for individual lag days 0-6, and for 3-d moving averages (lag 0-2). Effect measure modification was explored via stratification on individual- and area-level vulnerability factors. RESULTS: We estimated positive associations between short-term changes in indoor heat exposure and cause-specific mortality and morbidity [e.g., circulatory deaths, odds ratio per?5°C?increase = 1.16 (95% CI: 1.03, 1.30)]. Associations were generally positive for earlier lag periods and weaker across later lag periods. Stratified analyses suggest stronger associations between indoor heat and emergency hospital admissions among African Americans compared with Whites. DISCUSSION: Findings suggest excess mortality among certain elderly populations in Houston who are likely exposed to high indoor heat. We developed a novel methodology to estimate indoor heat exposure that can be adapted to other U.S. LOCATIONS: In locations with high air conditioning prevalence, simplified modeling approaches may adequately account for indoor heat exposure in vulnerable neighborhoods. Accounting for indoor heat exposure may improve the estimation of the total impact of heat on health. https://doi.org/10.1289/EHP6340.
Compared with mortality, the impact of weather and climate on human morbidity is less well understood, especially in the cold season. We examined the relationships between weather and emergency department (ED) visitation at hospitals in Roanoke and Charlottesville, Virginia, two locations with similar climates and population demographic profiles. Using patient-level data obtained from electronic medical records, each patient who visited the ED was linked to that day’s weather from one of 8 weather stations in the region based on each patient’s ZIP code of residence. The resulting 2010-2017 daily ED visit time series were examined using a distributed lag non-linear model to account for the concurrent and lagged effects of weather. Total ED visits were modeled separately for each location along with subsets based on gender, race, and age. The relationship between the relative risk of ED visitation and temperature or apparent temperature over lags of one week was positive and approximately linear at both locations. The relative risk increased about 5% on warm, humid days in both cities (lag 0 or lag 1). Cold conditions had a protective effect, with up to a 15% decline on cold days, but ED visits increased by 4% from 2 to 5 days after the cold event. The effect of thermal extremes tended to be larger for non-whites and the elderly, and there was some evidence of a greater lagged response for non-whites in Roanoke. Females in Roanoke were more impacted by winter cold conditions than males, who were more likely to show a lagged response at high temperatures. In Charlottesville, males sought ED attention at lower temperatures than did females. The similarities in the ED response patterns between these two hospitals suggest that certain aspects of the response may be generalizable to other locations that have similar climates and demographic profiles.
Harris County, Texas, is home to thousands of documented sources of environmental pollution. It is also highly vulnerable to impacts from natural hazards, including floods. Building on the Toxics Mobility Inventory (TMI), this article discusses how the authors developed a Toxics Mobility Vulnerability Index (TMVI) and applied it to Harris County to assess potential exposure risks to residents from the transfer of toxic materials during flood events. The TMI concept was operationalized and standardized by combining multiple spatial data sets to simultaneously evaluate various factors in the weather hazards-extant toxics-social vulnerability nexus (e.g., floodplain area, industrial land use, social vulnerability measures). Findings indicated hot spots of vulnerability to hazard-induced toxics transfer concentrated in Northeast Houston US Census tracts in Harris County. The main drivers of increased risk in these areas include the proportion of the area that is impervious surface, consistently high social vulnerabilities, and poor health. However, the most vulnerable areas also have overlapping exposure to both industrial land use and floodplains. Assessing the contribution of a set of industrial land use, social vulnerability, natural hazard, emergency response, and topography variables in a single index on the same spatial scale (e.g., US Census tract) provides detailed information for policy makers tasked with mitigating risk. Applying tools such as the TMVI to highly vulnerable urban and coastal locations may help identify changes needed for preparedness and mitigation planning and highlight areas where limited resources for investment- and policy-related remediation should be focused, both before and after disasters.
