Public health officials communicate the relevant risks of bushfire smoke exposure and associated health protection measures to affected populations. Increasing global bushfire incidence in the context of climate change motivated this scoping review. English-language publications related to adverse health outcomes following bushfire smoke exposure and publications relating to communication during natural disasters were included. Bushfire smoke events potentially increase healthcare contact, especially presentations triggered by respiratory illness. At-risk populations include those with underlying cardiorespiratory disease, elderly, paediatric, pregnant persons, and First Nations people. We found that social media, television, and radio are among the most common information sources utilised in bushfire smoke events. Message style, content, and method of delivery can directly influence message uptake and behaviour modification. Age, rurality, and geographical location influence information source preferences. Culturally and linguistically diverse groups and those with hearing, vision, and mobility-related disabilities may benefit from targeted health recommendations. This review emphasises the health effects of bushfire smoke exposure and related communication recommendations during and after bushfire smoke events. Additional investigation may further clarify the health effects of bushfire smoke exposure and efficacy of related health messaging, particularly in at-risk populations. Quantitative comparison of communication methods may yield more specific recommendations for future bushfire smoke events.
Wildfires are increasing in frequency, size, and intensity, and increasingly affect highly populated areas. Wildfire smoke impacts cardiorespiratory health; children are at increased risk due to smaller airways, a higher metabolic rate and ongoing development. The objective of this systematic review was to describe the risk of pediatric respiratory symptoms and healthcare visits following exposure to wildfire smoke. Medical and scientific databases and the grey literature were searched from inception until December 2020. Included studies evaluated pediatric respiratory-related healthcare visits or symptoms associated with wildfire smoke exposure. Prescribed burns, non-respiratory symptoms and non-pediatric studies were excluded. Risk of bias was evaluated using the National Toxicology Program’s Office of Health Assessment and Translation Risk of Bias Rating Tool. Data are presented narratively due to study heterogeneity. Of 2138 results, 1167 titles and abstracts were screened after duplicate removal; 65 full text screens identified 5 pre-post and 11 cross-sectional studies of rural, urban and mixed sites from the USA, Australia, Canada and Spain. There is a significant increase in respiratory emergency department visits and asthma hospitalizations within the first 3 days of exposure to wildfire smoke, particularly in children < 5 years old.
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.
Wildland firefighters work on wildfire incidents all over the United States and perform arduous work under extreme work conditions, including exposure to smoke. Wildland fire smoke is a mixture of hazardous air pollutants. For assessing wildland firefighter exposure to smoke, most studies measured carbon monoixde (CO) and particulate matter and reported changes in lung health by measured lung function, airway responsiveness, and respiratory symptoms across individual work shifts and single fire seasons. All fire personnel should understand the hazards of smoke and develop ways to mitigate exposure to smoke.
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.
Since air pollutants are difficult and expensive to control, a strong scientific underpinning to policies is needed to guide mitigation aimed at reducing the current burden on public health. Much of the evidence concerning hazard identification and risk quantification related to air pollution comes from epidemiological studies. This must be reinforced with mechanistic confirmation to infer causality. In this review we focus on data generated from four contrasting sources of particulate air pollution that result in high population exposures and thus where there remains an unmet need to protect health: urban air pollution in developing megacities, household biomass combustion, wildfires and desert dust storms. Taking each in turn, appropriate measures to protect populations will involve advocating smart cities and addressing economic and behavioural barriers to sustained adoption of clean stoves and fuels. Like all natural hazards, wildfires and dust storms are a feature of the landscape that cannot be removed. However, many efforts from emission containment (land/fire management practices), exposure avoidance and identifying susceptible populations can be taken to prepare for air pollution episodes and ensure people are out of harm’s way when conditions are life-threatening. Communities residing in areas affected by unhealthy concentrations of any airborne particles will benefit from optimum communication via public awareness campaigns, designed to empower people to modify behaviour in a way that improves their health as well as the quality of the air they breathe.
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.
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.
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.
Natural disasters are potentially traumatic events due to their disruptive nature and high impact on social and physical environments, particularly for children and adolescents. The present study aimed to examine the psychometric properties of the Children’s Revised Impact of Event Scale (CRIES-13) in a sample of Portuguese children and adolescents exposed to a specific type of natural disaster (i.e., wildfire). The sample was recruited at six school units of the Central region of Portugal following wildfires in the summer of 2017 and included children and adolescents without a clinical diagnosis of a psychopathological condition associated with exposure to the traumatic event (i.e., nonclinical sample, n = 486) and those with a clinical diagnosis of a trauma- and/or stress-related disorder (i.e., posttraumatic stress disorder [PTSD], adjustment disorder, separation anxiety disorder, or grief; clinical sample, n = 54). Confirmatory factor analyses indicated that a two-factor model (i.e., Intrusion/Arousal and Avoidance) provided a better fit than a three-factor model (i.e., Intrusion, Arousal, and Avoidance) and was found to be invariant across gender and age groups. The CRIES-13 showed good reliability for all subscales, with Cronbach’s alpha s > .79. Higher CRIES-13 scores were associated with poorer health and well-being and more internalizing and externalizing problems. The clinical sample presented with significantly higher CRIES-13 scores than the nonclinical sample, eta(2)(p) = .13. These results contribute to the cross-cultural validation of the CRIES-13 and support its use as a reliable and valid measure for assessing posttraumatic symptoms in children and adolescents.
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.
During the summer of 2018 Sweden experienced a high occurrence of wildfires, most intense in the low-densely populated Jämtland Härjedalen region. The aim of this study was to investigate any short-term respiratory health effects due to deteriorated air quality generated by the smoke from wildfires. For each municipality in the region Jämtland Härjedalen, daily population-weighted concentrations of fine particulate matter (PM(2.5)) were calculated through the application of the MATCH chemistry transport model. Modelled levels of PM(2.5) were obtained for two summer periods (2017, 2018). Potential health effects of wildfire related levels of PM(2.5) were examined by studying daily health care contacts concerning respiratory problems in each municipality in a quasi-Poisson regression model, adjusting for long-term trends, weekday patterns and weather conditions. In the municipality most exposed to wildfire smoke, having 9 days with daily maximum 1-h mean of PM(2.5) > 20 ?g/m(3), smoke days resulted in a significant increase in daily asthma visits the same and two following days (relative risk (RR) = 2.64, 95% confidence interval (CI): 1.28-5.47). Meta-estimates for all eight municipalities revealed statistically significant increase in asthma visits (RR = 1.68, 95% CI: 1.09-2.57) and also when grouping all disorders of the lower airways (RR = 1.40, 95% CI: 1.01-1.92).
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.
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.
In Fort McMurray, Alberta, Canada, the wildfire of May 2016 forced the population of 88,000 to rapidly evacuate in a traumatic and chaotic manner. Ten percentage of the homes in the city were destroyed, and many more structures were damaged. Since youth are particularly vulnerable to negative effects of natural disasters, we examined possible long-term psychological impacts. To assess this, we partnered with Fort McMurray Public and Catholic Schools, who surveyed Grade 7-12 students (aged 11-19) in November 2017, 2018, and 2019-i.e., at 1.5, 2.5, and 3.5 years after the wildfire. The survey included validated measurement scales for post-traumatic stress disorder (PTSD), depression, anxiety, drug use, alcohol use, tobacco use, quality of life, self-esteem, and resilience. Data analysis was done on large-scale anonymous surveys including 3,070 samples in 2017; 3,265 samples in 2018; and 3,041 samples in 2019. The results were unexpected and showed that all mental health symptoms increased from 2017 to 2019, with the exception of tobacco use. Consistent with this pattern, self-esteem and quality of life scores decreased. Resilience scores did not change significantly. Thus, mental health measures worsened, in contrast to our initial hypothesis that they would improve over time. Of note, we observed higher levels of mental health distress among older students, in females compared to male students, and in individuals with a minority gender identity, including transgender and gender-non-conforming individuals. These findings demonstrate that deleterious mental health effects can persist in youth for years following a wildfire disaster. This highlights the need for multi-year mental health support programs for youth in post-disaster situations. The indication that multi-year, post-disaster support is warranted is relatively novel, although not unknown. There is a need to systematically investigate factors associated with youth recovery following a wildfire disaster, as well as efficacy of psychosocial strategies during later phases of disaster recovery relative to early post-disaster interventions.
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.
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.
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 air quality and human health impacts of wildfires depend on fire, meteorology, and demography. These properties vary substantially from one region to another in China. This study compared smoke from more than a dozen wildfires in Northeast, North, and Southwest China to understand the regional differences in smoke transport and the air quality and human health impacts. Smoke was simulated using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) with fire emissions obtained from the Global Fire Emission Database (GFED). Although the simulated PM2.5 concentrations reached unhealthy or more severe levels at regional scale for some largest fires in Northeast China, smoke from only one fire was transported to densely populated areas (population density greater than 100 people/km(2)). In comparison, the PM2.5 concentrations reached unhealthy level in local densely populated areas for a few fires in North and Southwest China, though they were very low at regional scale. Thus, individual fires with very large sizes in Northeast China had a large amount of emissions but with a small chance to affect air quality in densely populated areas, while those in North and Southwest China had a small amount of emissions but with a certain chance to affect local densely populated areas. The results suggest that the fire and air quality management should focus on the regional air quality and human health impacts of very large fires under southward/southeastward winds toward densely populated areas in Northeast China and local air pollution near fire sites in North and Southwest China.
The relationship between the fires occurrences and diseases is an essential issue for making public health policy and environment protecting strategy. Thanks to the Internet, today, we have a huge amount of health data and fire occurrence reports at our disposal. The challenge, therefore, is how to deal with 4 Vs (volume, variety, velocity and veracity) associated with these data. To overcome this problem, in this paper, we propose a method that combines techniques based on Data Mining and Knowledge Discovery from Databases (KDD) to discover spatial and temporal association between diseases and the fire occurrences. Here, the case study was addressed to Malaria, Leishmaniasis and respiratory diseases in Brazil. Instead of losing a lot of time verifying the consistency of the database, the proposed method uses Decision Tree, a machine learning-based supervised classification, to perform a fast management and extract only relevant and strategic information, with the knowledge of how reliable the database is. Namely, States, Biomes and period of the year (months) with the highest rate of fires could be identified with great success rates and in few seconds. Then, the K-means, an unsupervised learning algorithms that solves the well-known clustering problem, is employed to identify the groups of cities where the fire occurrences is more expressive. Finally, the steps associated with KDD is perfomed to extract useful information from mined data. In that case, Spearman’s rank correlation coefficient, a nonparametric measure of rank correlation, is computed to infer the statistical dependence between fire occurrences and those diseases. Moreover, maps are also generated to represent the distribution of the mined data. From the results, it was possible to identify that each region showed a susceptible behaviour to some disease as well as some degree of correlation with fire outbreak, mainly in the drought period.
This study aimed to examine the psychometric properties of the Child Post-Traumatic Cognitions Inventory (CPTCI) in a sample of Portuguese children and adolescents, following the exposition to a wildfire disaster. The sample included 533 children and adolescents living in regions exposed to the wildfire disaster (non-clinical sample: n = 483; clinical sample: n = 50). The short form of the instrument (CPTCI-SF) including two correlated factors (‘Sense of Disturbing and Permanent Change’ and ‘Sense of Being a Fragile Person in a Scary World’) showed good model fit and was invariant across gender and age-groups. Good internal consistency (> .70) was found, and higher CPTCI scores were associated with poorer adjustment indicators. The clinical sample presented significantly higher CPTCI scores than the non-clinical sample. These results contribute to the cross-cultural validation of the CPTCI and support the adequacy of its short form as a reliable and valid measure to be used with Portuguese children and adolescents.
The Cognitive Emotion Regulation Questionnaire-Kids (CERQ-Kids) is a self-report questionnaire that assesses cognitive emotional regulation strategies that children may employ when they face traumatic or stressful events. However, its psychometric properties were only analyzed among participants from the general community. The goal of this study is to examine the factor structure of the Portuguese CERQ-Kids and to explore its psychometric properties in a sample of children/adolescents exposed to a potentially traumatic event (wildfires). The sample included 488 children/adolescents (Mage = 13.02, SD = 2.5, range = 8-17) who lived in the areas affected by the 2017 Portugal wildfires and who did not receive a diagnosis of a mental disorder, and a clinical group of 50 children/adolescents (Mage = 12, SD = 2.62, range = 8-16) who lived in the same areas and who were diagnosed with a mental disorder. All participants completed the CERQ-Kids and measures of emotion regulation strategies, mental health, and quality of life. The best fitting model was the original nine-factor correlated model. This model was invariant across gender and age groups. With the exception of the Acceptance subscale, the remaining subscales presented adequate internal consistency. Participants from the clinical group scored higher on Self-blame, Rumination, Catastrophizing, and Acceptance than participants from the non-clinical group. Significant correlations were found between the CERQ-Kids subscales and measures of cognitive reappraisal, expressive suppression, prosocial behavior, mental health, and quality of life. The Portuguese version of the CERQ-Kids proved to be a psychometrically adequate measure of cognitive emotion regulation strategies that children and adolescents may use when exposed to a potentially traumatic event.
In October 2017, hundreds of wildfires ravaged the forests of the north and centre of Portugal. The fires were fanned by strong winds as tropical storm Ophelia swept the Iberian coast, dragging up smoke (together with Saharan dust from north-western Africa) into higher western European latitudes. Here we analyse the long-range transport of particulate matter (PM(10)) and study associations between PM(10) and short-term mortality in the Portuguese population exposed to PM(10) due to the October 2017 wildfires, the worst fire sequence in the country over the last decades. We analysed space- and ground-level observations to track the smoke plume and dust trajectory over Portugal and Europe, and to access PM(10) concentrations during the wildfires. The effects of PM(10) on mortality were evaluated using satellite data for exposure and Poisson regression models. The smoke plume covered most western European countries (including Spain, France, Belgium and the Netherlands), and reached the United Kingdom, where the population was exposed in average to an additional PM(10) level of 11.7 µg/m(3) during seven smoky days (three with dust) in relation to the reference days (days without smoke or dust), revealing the impact of the wildfires on distant populations. In Portugal, the population was exposed in average to additional PM(10) levels that varied from 16.2 to 120.6 µg/m(3) in smoky days with dust and from 6.1 to 20.9 µg/m(3) in dust-free smoky days. Results suggest that PM(10) had a significant effect on the same day natural and cardiorespiratory mortalities during the month of October 2017. For every additional 10 µg/m(3) of PM(10), there was a 0.89% (95% confidence interval, CI, 0-1.77%) increase in the number of natural deaths and a 2.34% (95% CI, 0.99-3.66%) increase in the number of cardiorespiratory-related deaths. With rising temperatures and a higher frequency of storms due to climate change, PM from Iberian wildfires together with NW African dust will tend to be more often transported into Northern European countries, which may carry health threats to areas far from the ignition sites.
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.
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.
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.
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.
Objectives To assess the likely prevalence rates of Major Depressive Disorder (MDD), Generalized Anxiety Disorder (GAD) and Post-Traumatic Stress Disorder (PTSD) in staff of Fort McMurray School Districts eighteen months after a May 2016 wildfire, and to determine possible predictors. Methods A quantitative cross-sectional survey was used to collect data through self-administered online questionnaires to determine likely MDD, GAD and PTSD using well validated self-report questionnaires. Results Of 1,446 staff who were sent the online survey link in an e-mail, 197 completed the survey, of which there were 168 females (85%) and 29 males (15%). The one-month prevalence rates for likely MDD, GAD and PTSD among the school staff were 18.3, 15.7 and 10.2% respectively. There were statistically significant associations between multiple socio-demographic and clinical variables likely MDD, GAD and PTSD among respondents. Conclusion Knowledge of key factors for MDD, GAD and PTSD may be helpful for policy makers when formulating population level social and clinical programs, to mitigate the mental health effects of future natural disasters.
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.
Background: Air pollution is a global problem and also linked to respiratory diseases. Wildfire smog is a major cause of air pollution in the upper northern area of Thailand. Thus, in the current study, we examined whether long-term exposure to wildfire smog induces lung function changes in a population from the upper northern area of Thailand. Methods: The lung function of 115 participants with long-term exposure smog was determined using peak flow meter. Results: Long-term smoke exposure participants decreased FEV1 (forced expiratory volume in 1 second)/FVC (forced vital capacity) ratio (56.49 +/- 23.88 in males and 56.29 +/- 28.23 in females) compared with general Thai population. Moreover, the reduction of FVC, FEV1, and peak expiratory flow rate (PEFR) values also showed in both male and female subjects. These results suggest that long-term smoke exposure induces obstructive lung abnormality. Moreover, itchy/watery nose, cough, phlegm, and chest pain also reported in these subjects. Conclusion: Wildfire smog could be induced respiratory pathway inflammation and easily collapsible respiratory airways.
The worst disaster of natural origin in recent Canadian history occurred in May 2016 in the northern Alberta community of Fort McMurray Wood Buffalo (FMWB). Among the 88,000 people abruptly evacuated amidst a raging wildfire were approximately 1850 pregnant or pre-conception women. Based on the Allostatic Load and Preterm Birth Conceptual Framework (Olson et al., 2015) [1], a simple, cost-effective expressive writing intervention following Pennebaker’s work (Pennebaker and Beall, 1986; Pennebaker et al., 2007) [2,3] was implemented in a primary study to help mitigate the negative effects of stress on a sample of these women and their unborn children. Journal writing served as an intervention in the primary study while the contents of the journal entries became the data analyzed in this qualitative study. This study utilized both inductive and deductive thematic analysis of journal entries completed by 54 women over four consecutive days (15 min/day). Deductive analysis followed a coding structure that was generated from two resilience scales. Themes that emerged during inductive analysis were also coded. The main themes that emerged described the women’s challenging experiences: fears for themselves and their offspring, fire-related and past trauma, and relationship changes. Resilience characteristics and practices also emerged from the writings and mirrored those found in the literature: (a) posttraumatic growth, (b) adaptability, (c) emotional/social connectedness, (d) composure, and (e) reasoning. This paper highlights the challenging experiences of pregnant women exposed to a disaster and the resilience they demonstrated in the face of the tragedy.
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.
Smoke from wildfires contains many air pollutants of concern and epidemiological studies have identified associations between exposure to wildfire smoke PM(2.5) and mortality and respiratory morbidity, and a possible association with cardiovascular morbidity. For this study, a retrospective analysis of air quality modelling was performed to quantify the exposure to wildfire-PM(2.5) across the Canadian population. The model included wildfire emissions from across North America for a 5-month period from May to September (i.e. wildfire season), between 2013 and 2015 and 2017-2018. Large variations in wildfire-PM(2.5) were noted year-to-year, geospatially, and within fire season. The model results were then used to estimate the national population health impacts attributable to wildfire-PM(2.5) and the associated economic valuation. The analysis estimated annual premature mortalities ranging from 54-240 premature mortalities attributable to short-term exposure and 570-2500 premature mortalities attributable to long-term exposure, as well as many non-fatal cardiorespiratory health outcomes. The economic valuation of the population health impacts was estimated per year at $410M-$1.8B for acute health impacts and $4.3B-$19B for chronic health impacts for the study period. The health impacts were greatest in the provinces with populations in close proximity to wildfire activity, though health impacts were also noted across many provinces indicating the long-range transport of wildfire-PM(2.5). Understanding the population health impacts of wildfire smoke is important as climate change is anticipated to increase wildfire activity in Canada and abroad.
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)).
Wildfires are an important ecological threat in Cote d’Ivoire with the northern half the most affected zone. This study assessed farmers’ perception of wildfire occurrence in the N’Zi River Watershed and compared this perception to remotely sensed fire data trends. To this end, 259 farmers were individually interviewed and 18 farmers were involved in three focus group discussions in three agro-ecological zones. A combination of descriptive statistics and regression analysis was used for data analysis. Results showed that 78.75% of farmers observed the upward trend in the annual wildfire activity identified by remote sensing data during 2001-2016. Most of the respondents identified hunting (65.83%), farm establishment (50%) and firebreaks establishment (46.67%) as main causes of wildfires. The perceived impacts of wildfires included immediate crop burning, crop growth delaying, mid-term post-fire crop destruction, destruction of material goods and loss of human life. Local population developed endogenous strategies to cope with this scourge. Amongst identified coping strategies, firebreaks establishment and maintenance around new clearings and farms and prohibition of fire-hunting during the dry season were highlighted. Therefore, policies and institutions that support local wildfires management initiatives must take advantage of the strong community knowledge and networks to strengthen their effectiveness and sustainability.
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.