BACKGROUND: Wildfire imposes a high mortality burden on Brazil. However, there is a limited assessment of the health economic losses attributable to wildfire-related fine particulate matter (PM(2.5)). METHODS: We collected daily time-series data on all-cause, cardiovascular, and respiratory mortality from 510 immediate regions in Brazil during 2000-2016. The chemical transport model GEOS-Chem driven with Global Fire Emissions Database (GFED), in combination with ground monitored data and machine learning was used to estimate wildfire-related PM(2.5) data at a resolution of 0.25° × 0.25°. A time-series design was applied in each immediate region to assess the association between economic losses due to mortality and wildfire-related PM(2.5) and the estimates were pooled at the national level using a random-effect meta-analysis. We used a meta-regression model to explore the modification effect of GDP and its sectors (agriculture, industry, and service) on economic losses. RESULTS: During 2000-2016, a total of US$81.08 billion economic losses (US$5.07 billion per year) due to mortality were attributable to wildfire-related PM(2.5) in Brazil, accounting for 0.68% of economic losses and equivalent to approximately 0.14% of Brazil’s GDP. The attributable fraction (AF) of economic losses due to wildfire-related PM(2.5) was positively associated with the proportion of GDP from agriculture, while negatively associated with the proportion of GDP from service. CONCLUSION: Substantial economic losses due to mortality were associated with wildfires, which could be influenced by the agriculture and services share of GDP per capita. Our estimates of the economic losses of mortality could be used to determine optimal levels of investment and resources to mitigate the adverse health impacts of wildfires.
OBJECTIVES: Flooding is the most frequent extreme-weather disaster and disproportionately burdens marginalized populations. This article examines how food and water insecurity, blood pressure (BP), nutritional status, and diarrheal and respiratory illnesses changed during the 2 months following a historic flood in lowland Bolivia. METHODS: Drawing on longitudinal data from Tsimane’ forager-horticulturalist (n = 118 household heads; n = 129 children) directly after a historic 2014 flood and ~2 months later, we use fixed effects linear regression and random effects logistic regression models to test changes in the markers of well-being and health over the recovery process. RESULTS: Results demonstrated that water insecurity scores decreased significantly 2 month’s postflood, while food insecurity scores remained high. Adults’ systolic and diastolic BP significantly declined 2 months after the flood’s conclusion. Adults experienced losses in measures of adiposity (BMI, sum of four skinfolds, waist circumference). Children gained weight and BMI-for-age Z-scores indicating buffering of children by adults from food stress that mainly occurred in the community closer to the main market town with greater access to food aid. Odds of diarrhea showed a nonsignificant decline, while cough increased significantly for both children and adults 2 months postflood. CONCLUSIONS: Water insecurity and BP improved during the recovery process, while high levels of food insecurity persisted, and nutritional stress and respiratory illness worsened. Not all indicators of well-being and health recover at the same rate after historic flooding events. Planning for multiphase recovery is critical to improve health of marginalized populations after flooding.
This study analyzes the weather-related health damage of present and future extreme temperatures in Argentina. Focusing on mortality, short-term impacts of temperature are obtained by regressing monthly mortality rates on inter-annual monthly weather variability. For this purpose, a countrywide panel dataset at the municipal level was constructed from the universe of deaths between 2010 and 2019, and daily meteorological records from the ERA5 weather dataset. Then, NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) are used to project future mortality by 2085 under two climate scenarios. Finally, present and future mortality-related economic damages are assessed using the Value of a Statistical Life. The results show that one additional day of extreme temperatures increase all-cause mortality rates relative to mild weather and that the impact of hotter-than-average temperatures is greater in magnitude than that of colder ones. Substantial heterogeneity exists between causes of death and age groups, with older people facing greater risks, while the results for gender are inconclusive. All days of extreme cold in a year generate damage equivalent to 0.64% of GDP, while heat damage is 0.11% of GDP. The total damage by extreme temperatures adds up to 0.75% of the 2019 GDP. When future temperatures are valued, the total damage increases by an additional 1.45% under scenario RCP8.5 because the lower mortality occurring on cold days only partially offsets the increase in the number of hot days. On the contrary, if temperature changes were to be mild (i.e., under scenario RCP4.5), overall mortality would be lower at the national level and the corresponding damages would decrease by 0.02%.
The current trends of climate change will increase people’s exposure to urban risks related to events such as landslides, floods, forest fires, food production, health, and water availability, which are stochastic and very localized in nature. This research uses a Bayesian network (BN) approach to analyze the intensity of such urban risks for the Andean municipality of Pasto, Colombia, under climate change scenarios. The stochastic BN model is linked to correlational models and local scenarios of representative concentration trajectories (RCP) to project the possible risks to which the municipality of Pasto will be exposed in the future. The results show significant risks in crop yields, food security, water availability and disaster risks, but no significant risks on the incidence of acute diarrheal diseases (ADD) and acute respiratory infections (ARI), whereas positive outcomes are likely to occur in livestock production, influenced by population growth. The advantage of the BN approach is the possibility of updating beliefs in the probabilities of occurrence of events, especially in developing, intermediate cities with information-limited contexts.
INTRODUCTION: This study aimed to identify what indigenous university students in Brazil perceived to be important and feasible actions to protect the survival of indigenous peoples from climate change-related impacts. METHODS: Concept mapping, which is a participatory mixed methodology, was conducted virtually with 20 indigenous students at two universities in Brazil. A focus prompt was developed from consultations with indigenous stakeholders and read “To protect the survival of the Indigenous Peoples from climate change, it is necessary to…”. Students brainstormed 46 statements, which they then sorted into clusters based on conceptual similarity. They rated each statement for importance and feasibility. Quantitative multivariate analyses of clusters and ratings were conducted to produce multiple visual maps of perceived actionable priorities. These analyses used the Group Wisdom TM software. RESULTS: Students agreed on 8 clusters that reflect the factors that influence the survival of indigenous peoples-preservation of lands 0.16 (SD 0.13), protection of demarcated lands 0.31 (SD 0.10), indigenous health and wellbeing 0.35 (SD 0.14), ancestral customs 0.46 (SD 0.04), global and national actions 0.61 (SD 0.13), indigenous rights 0.64 (SD 0.23), collective living 0.71 (SD 0.21), and respect 0.75 (SD 0.14). DISCUSSION: The most actionable priorities are related to the respect for their lands and customs, educational initiatives in schools about the importance of indigenous peoples to society, guarantees for basic health rights, and culturally appropriate provision of care, with specific mention of mental healthcare. The findings aligned closely with the concept of indigenous self-determination, which is rooted in autonomy and respect for cultural diversity, and the right to make decisions that impact their lives, land, and resources.
Leptospirosis is a zoonotic disease with a high burden in Latin America, including northeastern Argentina, where flooding events linked to El Niño are associated with leptospirosis outbreaks. The aim of this study was to evaluate the value of using hydrometeorological indicators to predict leptospirosis outbreaks in this region. We quantified the effects of El Niño, precipitation, and river height on leptospirosis risk in Santa Fe and Entre Ríos provinces between 2009 and 2020, using a Bayesian modelling framework. Based on several goodness of fit statistics, we selected candidate models using a long-lead El Niño 3.4 index and shorter lead local climate variables. We then tested predictive performance to detect leptospirosis outbreaks using a two-stage early warning approach. Three-month lagged Niño 3.4 index and one-month lagged precipitation and river height were positively associated with an increase in leptospirosis cases in both provinces. El Niño models correctly detected 89% of outbreaks, while short-lead local models gave similar detection rates with a lower number of false positives. Our results show that climatic events are strong drivers of leptospirosis incidence in northeastern Argentina. Therefore, a leptospirosis outbreak prediction tool driven by hydrometeorological indicators could form part of an early warning and response system in the region.
Toxic and harmful algal blooms (HABs) are a global problem affecting human health, marine ecosystems, and coastal economies, the latter through their impact on aquaculture, fisheries, and tourism. As our knowledge and the techniques to study HABs advance, so do international monitoring efforts, which have led to a large increase in the total number of reported cases. However, in addition to increased detections, environmental factors associated with global change, mainly high nutrient levels and warming temperatures, are responsible for the increased occurrence, persistence, and geographical expansion of HABs. The Chilean Patagonian fjords provide an “open-air laboratory” for the study of climate change, including its impact on the blooms of several toxic microalgal species, which, in recent years, have undergone increases in their geographical range as well as their virulence and recurrence (the species Alexandrium catenella, Pseudochattonella verruculosa, and Heterosigma akashiwo, and others of the genera Dinophysis and Pseudo-nitzschia). Here, we review the evolution of HABs in the Chilean Patagonian fjords, with a focus on the established connections between key features of HABs (expansion, recurrence, and persistence) and their interaction with current and predicted global climate-change-related factors. We conclude that large-scale climatic anomalies such as the lack of rain and heat waves, events intensified by climate change, promote the massive proliferation of these species by creating ideal conditions for their growth and persistence, as they affect water-column stratification, nutrient inputs, and reproductive rates.
Although malaria control investments worldwide have resulted in dramatic declines in transmission since 2000, progress has stalled. In the Amazon, malaria resurgence has followed withdrawal of Global Fund support of the Project for Malaria Control in Andean Border Areas (PAMAFRO). We estimate intervention-specific and spatially-explicit effects of the PAMAFRO program on malaria incidence across the Loreto region of Peru, and consider the influence of the environmental risk factors in the presence of interventions. METHODS: We conducted a retrospective, observational, spatial interrupted time series analysis of malaria incidence rates among people reporting to health posts across Loreto, Peru between the first epidemiological week of January 2001 and the last epidemiological week of December 2016. Model inference is at the smallest administrative unit (district), where the weekly number of diagnosed cases of Plasmodium vivax and Plasmodium falciparum were determined by microscopy. Census data provided population at risk. We include as covariates weekly estimates of minimum temperature and cumulative precipitation in each district, as well as spatially- and temporally-lagged malaria incidence rates. Environmental data were derived from a hydrometeorological model designed for the Amazon. We used Bayesian spatiotemporal modeling techniques to estimate the impact of the PAMAFRO program, variability in environmental effects, and the role of climate anomalies on transmission after PAMAFRO withdrawal. FINDINGS: During the PAMAFRO program, incidence of P. vivax declined from 42.8 to 10.1 cases/1000 people/year. Incidence for P. falciparum declined from 14.3 to 2.5 cases/1000 people/year over this same period. The effects of PAMAFRO-supported interventions varied both by geography and species of malaria. Interventions were only effective in districts where interventions were also deployed in surrounding districts. Further, interventions diminished the effects of other prevailing demographic and environmental risk factors. Withdrawal of the program led to a resurgence in transmission. Increasing minimum temperatures and variability and intensity of rainfall events from 2011 onward and accompanying population displacements contributed to this resurgence. INTERPRETATION: Malaria control programs must consider the climate and environmental scope of interventions to maximize effectiveness. They must also ensure financial sustainability to maintain local progress and commitment to malaria prevention and elimination efforts, as well as to offset the effects of environmental change that increase transmission risk. FUNDING: National Aeronautics and Space Administration, National Institutes of Health, Bill and Melinda Gates Foundation.
Forest fires cause many environmental impacts, including air pollution. Brazil is a very fire-prone region where few studies have investigated the impact of wildfires on air quality and health. We proposed to test two hypotheses in this study: i) the wildfires in Brazil have increased the levels of air pollution and posed a health hazard in 2003-2018, and ii) the magnitude of this phenomenon depends on the type of land use and land cover (e.g., forest area, agricultural area, etc.). Satellite and ensemble models derived data were used as input in our analyses. Wildfire events were retrieved from Fire Information for Resource Management System (FIRMS), provided by NASA; air pollution data from the Copernicus Atmosphere Monitoring Service (CAMS); meteorological variables from the ERA-Interim model; and land use/cover data were derived from pixel-based classification of Landsat satellite images by MapBiomas. We used a framework that infers the “wildfire penalty” by accounting for differences in linear pollutant annual trends (β) between two models to test these hypotheses. The first model was adjusted for Wildfire-related Land Use activities (WLU), considered as an adjusted model. In the second model, defined as an unadjusted model, we removed the wildfire variable (WLU). Both models were controlled by meteorological variables. We used a generalized additive approach to fit these two models. To estimate mortality associated with wildfire penalties, we applied health impact function. Our findings suggest that wildfire events between 2003 and 2018 have increased the levels of air pollution and posed a significant health hazard in Brazil, supporting our first hypothesis. For example, in the Pampa biome, we estimated an annual wildfire penalty of 0.005 μg/m(3) (95%CI: 0.001; 0.009) on PM(2.5). Our results also confirm the second hypothesis. We observed that the greatest impact of wildfires on PM(2.5) concentrations occurred in soybean areas in the Amazon biome. During the 16 years of the study period, wildfires originating from soybean areas in the Amazon biome were associated with a total penalty of 0.64 μg/m(3) (95%CI: 0.32; 0.96) on PM(2.5), causing an estimated 3872 (95%CI: 2560; 5168) excess deaths. Sugarcane crops were also a driver of deforestation-related wildfires in Brazil, mainly in Cerrado and Atlantic Forest biomes. Our findings suggest that between 2003 and 2018, fires originating from sugarcane crops were associated with a total penalty of 0.134 μg/m(3) (95%CI: 0.037; 0.232) on PM(2.5) in Atlantic Forest biome, resulting in an estimated 7600 (95%CI: 4400; 10,800) excess deaths during the study period, and 0.096 μg/m(3) (95%CI: 0.048; 0.144) on PM(2.5) in Cerrado biome, resulting in an estimated 1632 (95%CI: 1152; 2112) excess deaths during the study period. Considering that the wildfire penalties observed during our study period may continue to be a challenge in the future, this study should be of interest to policymakers to prepare future strategies related to forest protection, land use management, agricultural activities, environmental health, climate change, and sources of air pollution.
Recent research suggests that over 75% of resources extracted globally now go toward creating, maintaining, or operating material stocks (MS) to provide societal services like housing, transport, education, and health. However, the integrity of current and future built environments, and the capacity of the system to continue providing services, are threatened by extreme events and sea-level rise (SLR). This is especially significant for the most disaster-prone countries in the world: Small Island Developing States. In the aftermath of disasters, complex rebuilding efforts require substantial material and economic resources, oftentimes incurring massive debt. Understanding the composition and dynamics of MS and environmental threats is essential for current and future sustainable development. Drawing on open-source OpenStreetMap (OSM) data, we conducted a spatially explicit material stock analysis (MSA) for The Bahamas for 2021, where we included buildings and transport MS, and SLR exposure scenarios. Total MS was estimated at 76 million tonnes (Mt) or 191 tonnes per capita (t/cap) of which transport comprises 43%. These MS are likely to increase by 36 Mt in the future. Simulations show that under 1-, 2-, or 3-m SLR scenarios, around 4, 6, and 9 Mt of current MS will be exposed, with transport MS at greatest risk, with over 80% of total exposure in each scenario. Our findings highlight the critical role that key MS play in sustainability and resilience, contributing to the emphasis on effective development planning and climate change adaptation strategies, and to the exploration of the use of OSM data for studying these objectives.
Important development partners encouraged and supported the development of Caribbean islands’ recent action plans and targets on climate change and health. These developments are part of larger global trends around mainstreaming climate change adaptation into national health policy. Including community voices is crucial, yet the responsiveness of regional and national processes around climate change adaptation and health governance to local community concerns is poorly understood. This case study in rural Trinidad and Tobago sought to contribute to better understanding community led action on health and climate change adaptation by investigating community groups’ perceptions of the challenges faced and addressed by their community. The study contributes to climate change adaptation and health debates in three main ways. First, it develops a conceptual framework around agency in the context of health and climate change adaptation in community groups and local spaces. Second, it fills a gap in the literature by registering the voices and perspectives of coastal community groups regarding their development priorities in the context of climate change adaptation and health. Third, using the lens of agency, it highlights the disconnect between local voices and the urgency around the mainstreaming of climate change adaptation and health into regional and national climate change adaptation policies. This study contributes to wider debates around the power of external agents to shape local discourses and policy. The results contrast dominant global narratives underlying recent regional and national policies and suggest that this area is still one where there may be a disconnect between local development priorities and international policy.
Leishmaniasis is a dynamic disease in which transmission conditions change due to environmental and human behavioral factors. Epidemiological analyses have shown modifications in the spread profile and growing urbanization of the disease, justifying the expansion of endemic areas and increasing number of cases in dogs and humans. In the city of Belo Horizonte, located in the southeastern state of Minas Gerais (Brazil), visceral leishmaniasis (VL) is endemic, with a typical urban transmission pattern, but with different regional prevalence. This study was conducted at the Zoo of the Foundation of Municipal Parks and Zoobotany of Belo Horizonte (FPMZB-BH), located in the Pampulha region, which is among the areas most severely affected by VL. This study aimed to determine the taxonomic diversity of native phlebotomine sand flies (Diptera: Psychodidae), identify climatic variables that potentially affect the phenology of these insects, and determine the blood meal sources for female phlebotomine sand flies. To achieve this, 10 mammal enclosures in the zoo were selected using the presence of possible leishmaniasis reservoirs as a selection criterion, and sampled using light traps between August 2019 and August 2021. A total of 6034 phlebotomine sand flies were collected, indicating nine species, with Lutzomyia longipalpis being the very abundant species (65.35% of the total). Of the 108 engorged phlebotomine collected females, seven samples (6.5%) were positive for blood meals from humans, marsupials, canids, and birds. Relative humidity and rainfall increased the phenology of phlebotomine sand flies, with population increases in the hottest and wettest months. The data obtained will provide guidelines for competent health agencies to implement vector control measures to reduce the risk of leishmaniasis transmission in the FPMZB-BH.
BACKGROUND: Scorpion stings in Brazil represent a major public health problem due to their incidence and their potential ability to lead to severe and often fatal clinical outcomes. A better understanding of scorpionism determinants is essential for a precise comprehension of accident dynamics and to guide public policy. Our study is the first to model the spatio-temporal variability of scorpionism across municipalities in São Paulo (SP) and to investigate its relationship with demographic, socioeconomic, environmental, and climatic variables. METHODOLOGY: This ecological study analyzed secondary data on scorpion envenomation in SP from 2008 to 2021, using the Integrated Nested Laplace Approximation (INLA) to perform Bayesian inference for detection of areas and periods with the most suitable conditions for scorpionism. PRINCIPAL FINDINGS: From the spring of 2008 to 2021, the relative risk (RR) increased eight times in SP, from 0.47 (95%CI 0.43-0.51) to 3.57 (95%CI 3.36-3.78), although there has been an apparent stabilization since 2019. The western, northern, and northwestern parts of SP showed higher risks; overall, there was a 13% decrease in scorpionism during winters. Among the covariates considered, an increase of one standard deviation in the Gini index, which captures income inequality, was associated with a 11% increase in scorpion envenomation. Maximum temperatures were also associated with scorpionism, with risks doubling for temperatures above 36°C. Relative humidity displayed a nonlinear association, with a 50% increase in risk for 30-32% humidity and reached a minimum of 0.63 RR for 75-76% humidity. CONCLUSIONS: Higher temperatures, lower humidity, and social inequalities were associated with a higher risk of scorpionism in SP municipalities. By capturing local and temporal relationships across space and time, authorities can design more effective strategies that adhere to local and temporal considerations.
The effects extreme air temperature events are related with an increase in cardiovascular mortality among vulnerable groups worldwide. Therefore, we identify spatiotemporal mortality clusters associated with diseases of the cardiovascular system among people ≥ 65 years in São Paulo, from 2006 to 2015, and investigate whether high-risk mortality clusters occurred during or following extreme air temperature events. To detect the clusters, we used daily mortality data and a retrospective space-time scan analysis with a discrete Poisson model. Extreme air temperature events were defined by daily mean temperatures, below the 10th percentile for cold spells and above the 90th percentile for heatwaves, with two or more consecutive days. We found statistically significant high-risk mortality clusters located in the peripheral areas. The spatiotemporal clusters of risk areas for cardiovascular and ischemic heart disease occurred during or following cold spell events, whereas those for stroke and ischemic stroke events were related to heatwaves.
INTRODUCTION: Leptospirosis is a globally distributed zoonotic and environmentally mediated disease that has emerged as a major health problem in urban slums in developing countries. Its aetiological agent is bacteria of the genus Leptospira, which are mainly spread in the urine of infected rodents, especially in an environment where adequate sanitation facilities are lacking, and it is known that open sewers are key transmission sources of the disease. Therefore, we aim to evaluate the effectiveness of a simplified sewerage intervention in reducing the risk of exposure to contaminated environments and Leptospira infection and to characterise the transmission mechanisms involved. METHODS AND ANALYSIS: This matched quasi-experimental study design using non-randomised intervention and control clusters was designed to assess the effectiveness of an urban simplified sewerage intervention in the low-income communities of Salvador, Brazil. The intervention consists of household-level piped sewerage connections and community engagement and public involvement activities. A cohort of 1400 adult participants will be recruited and grouped into eight clusters consisting of four matched intervention-control pairs with approximately 175 individuals in each cluster in baseline. The primary outcome is the seroincidence of Leptospira infection assessed through five serological measurements: one preintervention (baseline) and four postintervention. As a secondary outcome, we will assess Leptospira load in soil, before and after the intervention. We will also assess Leptospira exposures before and after the intervention, through transmission modelling, accounting for residents’ movement, contact with flooding, contaminated soil and water, and rat infestation, to examine whether and how routes of exposure for Leptospira change following the introduction of sanitation. ETHICS AND DISSEMINATION: This study protocol has been reviewed and approved by the ethics boards at the Federal University of Bahia and the Brazilian National Research Ethics Committee. Results will be disseminated through peer-reviewed publications and presentations to implementers, researchers and participating communities. TRIAL REGISTRATION NUMBER: Brazilian Clinical Trials Registry (RBR-8cjjpgm).
Large Brazilian cities, such as Rio de Janeiro, suffer serious environmental problems caused by informal settlements (IS), such as advances in the degradation of surface waters involving anthropic pressures resulting from uncontrolled urban growth, lack of sanitation or disasters related to climate events, creating a gap in relevant information about environmental health in urban IS. Therefore, it is essential to assess the health conditions of IS and the local population’s perception of their living conditions. This study aimed to evaluate, by online form and public data, the sanitary conditions of the third largest IS in Brazil, the Rio das Pedras community, which was located on the banks of the Jacarepagua Lagoon complex. The analysis revealed that 35% of respondents reported releasing domestic sewage directly into the river near their homes. In addition, 83% of the participants reported that they disposed of urban solid waste inappropriately. About 21% of residents reported falling ill due to direct contact with unsafe water after flood events. Public managers, concerned with advancing sustainability agendas and mitigating the risks to environmental health related to the lack of adequate sanitation services, should invest in actions that reflect the perception of the local population, proposing more appropriate socio-environmental solutions.
This work aims to discuss thermal comfort and school architecture in Brazil, within the Anthropocene framework. The objective traverses the fields of school management, curriculum, and educational policy. The importance of the environmental emergency in the context of the Anthropocene is recognized, understanding it as a space-time in which climate change biopolitically impacts both local and global daily life. In this way, we consider that the curricular dimension together with school architecture, in the Anthropocene scenario, tends to respond to the demands of biosecurity. The methodology of this article is the analysis of documentary sources, particularly current Brazilian legislation on school architecture, thermal comfort, and public funding. The initial hypothesis of this work operates with the argument that in Brazilian legislation there is a predominance of HVAC (Heating, Ventilating and Air Conditioning) systems over sustainable forms such as natural ventilation, design of classrooms, placement of windows, use of trees and vegetation and management of the student’s schedule. The assumption of the research lies in the need for reconfigurations of the principles of school architecture, considering both biosecurity and bioclimatic architecture essential for the future in the scenario of climate extremes along the Anthropocene.
Climate-related phenomena in Peru have been slowly but continuously changing in recent years beyond historical variability. These include sea surface temperature increases, irregular precipitation patterns and reduction of glacier-covered areas. In addition, climate scenarios show amplification in rainfall variability related to the warmer conditions associated with El Niño events. Extreme weather can affect human health, increase shocks and stresses to the health systems, and cause large economic losses. In this article, we study the characteristics of El Niño events in Peru, its health and economic impacts and we discuss government preparedness for this kind of event, identify gaps in response, and provide evidence to inform adequate planning for future events and mitigating impacts on highly vulnerable regions and populations. This is the first case study to review the impact of a Coastal El Niño event on Peru’s economy, public health, and governance. The 2017 event was the third strongest El Niño event according to literature, in terms of precipitation and river flooding and caused important economic losses and health impacts. At a national level, these findings expose a need for careful consideration of the potential limitations of policies linked to disaster prevention and preparedness when dealing with El Niño events. El Niño-related policies should be based on local-level risk analysis and efficient preparedness measures in the face of emergencies.
Climate change is an important driver of the increased spread of dengue from tropical and subtropical regions to temperate areas around the world. Climate variables such as temperature and precipitation influence the dengue vector’s biology, physiology, abundance, and life cycle. Thus, an analysis is needed of changes in climate change and their possible relationships with dengue incidence and the growing occurrence of epidemics recorded in recent decades. OBJECTIVES: This study aimed to assess the increasing incidence of dengue driven by climate change at the southern limits of dengue virus transmission in South America. METHODS: We analyzed the evolution of climatological, epidemiological, and biological variables by comparing a period of time without the presence of dengue cases (1976-1997) to a more recent period of time in which dengue cases and important outbreaks occurred (1998-2020). In our analysis, we consider climate variables associated with temperature and precipitation, epidemiological variables such as the number of reported dengue cases and incidence of dengue, and biological variables such as the optimal temperature ranges for transmission of dengue vector. RESULTS: The presence of dengue cases and epidemic outbreaks are observed to be consistent with positive trends in temperature and anomalies from long-term means. Dengue cases do not seem to be associated with precipitation trends and anomalies. The number of days with optimal temperatures for dengue transmission increased from the period without dengue cases to the period with occurrences of dengue cases. The number of months with optimal transmission temperatures also increased between periods but to a lesser extent. CONCLUSIONS: The higher incidence of dengue virus and its expansion to different regions of Argentina seem to be associated with temperature increases in the country during the past two decades. The active surveillance of both the vector and associated arboviruses, together with continued meteorological data collection, will facilitate the assessment and prediction of future epidemics that use trends in the accelerated changes in climate. Such surveillance should go hand in hand with efforts to improve the understanding of the mechanisms driving the geographic expansion of dengue and other arboviruses beyond the current limits. https://doi.org/10.1289/EHP11616.
Non-optimal temperatures are associated with premature deaths globally. However, the evidence is limited in low- and middle-income countries, and the productivity losses due to non-optimal temperatures have not been quantified. We aimed to estimate the work-related impacts and economic losses attributable to non-optimal temperatures in Brazil. We collected daily mortality data from 510 immediate regions in Brazil during 2000 and 2019. A two-stage time-series analysis was applied to evaluate the association between non-optimum temperatures and the Productivity-Adjusted Life-Years (PALYs) lost. The temperature-PALYs association was fitted for each location in the first stage and then we applied meta-analyses to obtain the national estimations. The attributable fraction (AF) of PALY lost due to ambient temperatures and the corresponding economic costs were calculated for different subgroups of the working-age population. A total of 3,629,661 of PALYs lost were attributed to non-optimal temperatures during 2000-2019 in Brazil, corresponding to 2.90 % (95 % CI: 1.82 %, 3.95 %) of the total PALYs lost. Non-optimal temperatures have led to US$104.86 billion (95 % CI: 65.95, 142.70) of economic costs related to PALYs lost and the economic burden was more substantial in males and the population aged 15-44 years. Higher risks of extreme cold temperatures were observed in the South region in Brazil while extreme hot temperatures were observed in the Central West and Northeast regions. In conclusion, non-optimal temperatures are associated with considerable labour losses as well as economic costs in Brazil. Tailored policies and adaptation strategies should be proposed to mitigate the impacts of non-optimal temperatures on the labour supply in a changing climate.
Dengue is a global problem that seems to be worsening, as hyper-urbanization associated with climate change has led to a significant increase in the abundance and geographical spread of its principal vector, the Aedes aegypti mosquito. Currently available solutions have not been able to stop the spread of dengue which shows the urgent need to implement alternative technologies as practical solutions. In a previous pilot trial, we demonstrated the efficacy and safety of the method ‘Natural Vector Control’ (NVC) in suppressing the Ae. aegypti vector population and in blocking the occurrence of an outbreak of dengue in the treated areas. Here, we expand the use of the NVC program in a large-scale 20 months intervention period in an entire city in southern Brazil. METHODS: Sterile male mosquitoes were produced from locally sourced Ae. aegypti mosquitoes by using a treatment that includes double-stranded RNA and thiotepa. Weekly massive releases of sterile male mosquitoes were performed in predefined areas of Ortigueira city from November 2020 to July 2022. Mosquito monitoring was performed by using ovitraps during the entire intervention period. Dengue incidence data was obtained from the Brazilian National Disease Surveillance System. FINDINGS: During the two epidemiological seasons, the intervention in Ortigueira resulted in up to 98.7% suppression of live progeny of field Ae. aegypti mosquitoes recorded over time. More importantly, when comparing the 2020 and 2022 dengue outbreaks that occurred in the region, the post-intervention dengue incidence in Ortigueira was 97% lower compared to the control cities. INTERPRETATION: The NVC method was confirmed to be a safe and efficient way to suppress Ae. aegypti field populations and prevent the occurrence of a dengue outbreak. Importantly, it has been shown to be applicable in large-scale, real-world conditions. FUNDING: This study was funded by Klabin S/A and Forrest Innovations Ltd.
Global climate change poses a significant challenge in contemporary society, particularly affecting vulnerable populations like small farmers residing in arid and semiarid regions. This study aims to investigate the perception of health risks and adaptive responses in the semiarid region of Northeast Brazil (NEB). Four questions were formulated: (1) How do socioeconomic factors influence the perception of health risks during extreme climate events? (2) How do socioeconomic factors impact the adoption of adaptive responses to mitigate health risks during extreme weather events? (3) How does the perceived risk level affect the utilization of adaptive responses? (4) What is the influence of extreme climate events on the perceived risks and the adoption of adaptive responses? METHOD: The research was conducted in the rural community of Carão, situated in the Agreste region of the State of Pernambuco, NEB. Semi-structured interviews were conducted with 49 volunteers aged 18 and above. The interviews aimed to gather socioeconomic information, including sex, age, income, access to healthcare services, family size, and education level. Additionally, the interviews explored the perceived risks and responses employed during different extreme climate events such as droughts or heavy rainfall. The perceived risks and adaptive responses data were quantified to address the research questions. Generalized linear models were employed to analyze the data for the first three questions, while the nonparametric Mann-Whitney test was used for the fourth question. RESULTS: The study found no significant differences in the level of perceived risk and adaptive responses between the two climate extremes. However, the quantity of adaptive responses was found to be directly influenced by the perceived risks, regardless of the type of extreme climate event. CONCLUSION: The study concludes that risk perception is influenced by various complex factors, including socioeconomic variables, and plays a critical role in the adoption of adaptive responses during extreme climate events. The findings suggest that specific socioeconomic variables have a more pronounced influence on how individuals perceive and adapt to risks. Furthermore, the results indicate a cause-and-effect relationship between perceived risks and the generation of adaptive responses. These findings contribute to a better understanding of the factors shaping risk perception and provide valuable insights for future studies in regions prone to extreme climate events.
Geographic isolation and strict control limits in border areas have kept Chile free from various pathogens, including Flavivirus. However, the scenario is changing mainly due to climate change, the reintroduction of more aggressive mosquitoes, and the great wave of migration of people from endemic countries in recent years. Hence, it is necessary to surveillance mosquitoes to anticipate a possible outbreak in the population and take action to control it. This study aimed to investigate the presence of Flavivirus RNA by molecular tools with consensus primers in mosquitoes collected in the extreme north and central Chile. From 2019 to 2021, a prospective study was carried out in localities of Northern and part of Central Chile. Larvae, pupae, and adults of mosquitoes were collected in rural and urban sites in each locality. The collected samples were pooled by species and geographical location and tested using RT-PCR and RT-qPCR to determine presence of Flavivirus. 3085 specimens were collected, the most abundant specie Culex quinquefasciatus in the North and Aedes (Ochlerotatus) albifasciatus in the Center of Chile. Both genera are associated with Flavivirus transmission. However, PCR and RT-PCR did not detect Flavivirus RNA in the mosquitoes studied. These negative results indicate we are still a free Flavivirus country, which is reaffirmed by the non-existence of endemic human cases. Despite this, routine surveillance of mosquitoes and the pathogens they carry is highly recommended to evaluate each area-specific risk of vector-borne transmission.
Dengue is a vector-borne disease that is endemic to several countries, including the Dominican Republic, which has experienced dengue outbreaks for over four decades. With outbreaks growing in incidence in recent years, it is becoming increasingly important to develop better tools to understand drivers of dengue transmission. Such tools are critical for providing timely information to assist healthcare authorities in preparing human, material, and medical resources for outbreaks. Here, we investigate associations between meteorological variables and dengue transmission in the Dominican Republic in 2019, the year in which the country’s largest outbreak to date ocurred. We apply generalized linear mixed modelling with gamma family and log link to model the weekly dengue incidence rate. Because correlations in lags between climate variables and dengue cases exhibited different behaviour among provinces, a backward-type selection method was executed to find a final model with lags in the explanatory variables. We find that in the best models, meteorological conditions such as temperature and rainfall have an impact with a delay of 2-5 weeks in the development of an outbreak, ensuring breeding conditions for mosquitoes.
The impact of natural hazards on nations and societies is a global challenge and concern. Worldwide, studies have been conducted within and between countries, to examine the spatial distribution and temporal evolution of fatalities and their impact on societies. In Brazil, no studies have comprehensively identified the fatalities associated with all natural hazards and their specificities by decade, region, sex, age, and other victim characteristics. This study carries out an in-depth analysis of the Brazilian Mortality Data of the Brazilian Ministry of Health, from 1979 to 2019, identifying the natural hazards that kill the most people in Brazil and their particularities. Lightning is the deadliest natural hazard in Brazil during this period, with a gradual decrease in the number of fatalities. The number of hydro-meteorological fatalities increases from 2000 onwards, with the highest number of fatalities occurring between 2010 and 2019. Although Brazil is a tropical country affected by severe droughts, extreme heat has the lowest number of fatalities compared to other natural hazards. The period from December to March has a higher number of fatalities, and the southeast is the most populous region where most people die. The number of male victims is twice as high as the number of female victims, across all ages groups, and unmarried victims are the most likely to die. It is therefore essential to recognize and disseminate the knowledge about the impact of different natural hazards on communities and societies, namely on people and their livelihoods, in order to assess the challenges and identify opportunities for reducing the effects of natural hazards in Brazil.
BACKGROUND: Hantavirus Pulmonary Syndrome (HPS) is a rodent-borne zoonosis in the Americas, with up to 50% mortality rates. In Argentina, the Northwestern endemic area presents half of the annually notified HPS cases in the country, transmitted by at least three rodent species recognized as reservoirs of Orthohantavirus. The potential distribution of reservoir species based on ecological niche models (ENM) can be a useful tool to establish risk areas for zoonotic diseases. Our main aim was to generate an Orthohantavirus risk transmission map based on ENM of the reservoir species in northwest Argentina (NWA), to compare this map with the distribution of HPS cases; and to explore the possible effect of climatic and environmental variables on the spatial variation of the infection risk. METHODS: Using the reservoir geographic occurrence data, climatic/environmental variables, and the maximum entropy method, we created models of potential geographic distribution for each reservoir in NWA. We explored the overlap of the HPS cases with the reservoir-based risk map and a deforestation map. Then, we calculated the human population at risk using a census radius layer and a comparison of the environmental variables’ latitudinal variation with the distribution of HPS risk. RESULTS: We obtained a single best model for each reservoir. The temperature, rainfall, and vegetation cover contributed the most to the models. In total, 945 HPS cases were recorded, of which 97,85% were in the highest risk areas. We estimated that 18% of the NWA population was at risk and 78% of the cases occurred less than 10 km from deforestation. The highest niche overlap was between Calomys fecundus and Oligoryzomys chacoensis. CONCLUSIONS: This study identifies potential risk areas for HPS transmission based on climatic and environmental factors that determine the distribution of the reservoirs and Orthohantavirus transmission in NWA. This can be used by public health authorities as a tool to generate preventive and control measures for HPS in NWA.
Studies have shown that climate may affect the distribution of coronavirus disease (COVID-19) and its incidence and fatality rates. Here, we applied an ensemble niche modeling approach to project the climatic suitability of COVID-19 cases in Brazil. We estimated the cumulative incidence, mortality rate, and fatality rate of COVID-19 between 2020 and 2021. Seven statistical algorithms (MAXENT, MARS, RF, FDA, CTA, GAM, and GLM) were selected to model the climate suitability for COVID-19 cases from diverse climate data, including temperature, precipitation, and humidity. The annual temperature range and precipitation seasonality showed a relatively high contribution to the models, partially explaining the distribution of COVID-19 cases in Brazil based on the climatic suitability of the territory. We observed a high probability of climatic suitability for high incidence in the North and South regions and a high probability of mortality and fatality rates in the Midwest and Southeast regions. Despite the social, viral, and human aspects regulating COVID-19 cases and death distribution, we suggest that climate may play an important role as a co-factor in the spread of cases. In Brazil, there are regions with a high probability that climatic suitability will contribute to the high incidence and fatality rates of COVID-19 in 2020 and 2021.
Studies have shown that larger temperature-related health impacts may be associated with cold rather than with hot temperatures. Although it remains unclear the cold-related health burden in warmer regions, in particular at the national level in Brazil. We address this gap by examining the association between low ambient temperature and daily hospital admissions for cardiovascular and respiratory diseases in Brazil between 2008 and 2018. We first applied a case time series design in combination with distributed lag non-linear modeling (DLNM) framework to assess the association of low ambient temperature with daily hospital admissions by Brazilian region. Here, we also stratified the analyses by sex, age group (15-45, 46-65, and >65 years), and cause (respiratory and cardiovascular hospital admissions). In the second stage, we performed a meta-analysis to estimate pooled effects across the Brazilian regions. Our sample included more than 23 million hospitalizations for cardiovascular and respiratory diseases nationwide between 2008 and 2018, of which 53% were admissions for respiratory diseases and 47% for cardiovascular diseases. Our findings suggest that low temperatures are associated with a relative risk of 1.17 (95% CI: 1.07; 1.27) and 1.07 (95% CI: 1.01; 1.14) for cardiovascular and respiratory admissions in Brazil, respectively. The pooled national results indicate robust positive associations for cardiovascular and respiratory hospital admissions in most of the subgroup analyses. In particular, for cardiovascular hospital admissions, men and older adults (>65 years old) were slightly more impacted by cold exposure. For respiratory admissions, the results did not indicate differences among the population groups by sex and age. This study can help decision-makers to create adaptive measures to protect public health from the effects of cold temperature.
There is increasing evidence that climate change impacts have been particularly critical in the case of heat waves during the last years. Many cities around the globe have been affected by heat waves and their cascading effects, threatening public health and urban life and disrupting services and infrastructure. Unfortunately, cities in developing countries are not paying attention to heatwaves’ impacts. This is the case in Mexico. Although there are studies on extreme heat exposure, there are no vulnerability assessments. The central research question of our study is the analysis of social vulnerability to extreme temperature and heatwaves in two Mexican cities at the U.S.-Mexico border, Tijuana, and Mexicali. Our results show that urban planning and state and municipal development policies in both cities have neglected the impact of heat waves despite their increasing frequency, intensity, and duration in the last two decades. The results also show significant differences in exposure, sensitivity, and adaptive capacity to extreme temperatures within each city. Areas with higher vulnerability in both cities are informal settlements and low-income neighborhoods. This information can support local governments in making sound use of scarce resources to create efficient responses to current impacts and future risks of climate change.
For vector-borne diseases the basic reproduction number [Formula: see text], a measure of a disease’s epidemic potential, is highly temperature-dependent. Recent work characterizing these temperature dependencies has highlighted how climate change may impact geographic disease spread. We extend this prior work by examining how newly emerging diseases, like Zika, will be impacted by specific future climate change scenarios in four diverse regions of Brazil, a country that has been profoundly impacted by Zika. We estimated a [Formula: see text], derived from a compartmental transmission model, characterizing Zika (and, for comparison, dengue) transmission potential as a function of temperature-dependent biological parameters specific to Aedes aegypti. We obtained historical temperature data for the five-year period 2015-2019 and projections for 2045-2049 by fitting cubic spline interpolations to data from simulated atmospheric data provided by the CMIP-6 project (specifically, generated by the GFDL-ESM4 model), which provides projections under four Shared Socioeconomic Pathways (SSP). These four SSP scenarios correspond to varying levels of climate change severity. We applied this approach to four Brazilian cities (Manaus, Recife, Rio de Janeiro, and São Paulo) that represent diverse climatic regions. Our model predicts that the [Formula: see text] for Zika peaks at 2.7 around 30°C, while for dengue it peaks at 6.8 around 31°C. We find that the epidemic potential of Zika will increase beyond current levels in Brazil in all of the climate scenarios. For Manaus, we predict that the annual [Formula: see text] range will increase from 2.1-2.5, to 2.3-2.7, for Recife we project an increase from 0.4-1.9 to 0.6-2.3, for Rio de Janeiro from 0-1.9 to 0-2.3, and for São Paulo from 0-0.3 to 0-0.7. As Zika immunity wanes and temperatures increase, there will be increasing epidemic potential and longer transmission seasons, especially in regions where transmission is currently marginal. Surveillance systems should be implemented and sustained for early detection.
This paper analyzes the relationship between temperature, mortality, and adaptation oppor-tunities in a tropical country. Such countries host almost 40% of the world’s population and face inherently different environmental, demographic, and socio-economic conditions than their counterparts in temperate areas. Using detailed data from all Colombian municipalities, I show that anomalously hot or cold days increase mortality even at narrow temperature ranges, which are characteristic of the tropics. An additional day with a mean temperature above 27 degrees C (80.6 degrees F) increases mortality rates by approximately 0.24 deaths per 100,000, equivalent to 0.7% of monthly death rates. Unlike temperate locations, I find that deaths attributed to infectious diseases and respiratory illnesses drive this relationship in the hot part of the distribution, mainly affecting children aged 0-9. These findings uncover new factors and populations at risk and imply that the average person who dies after a hot temperature shock loses approximately 30 years of life. I also provide evidence that access to health care and quality of services could mediate between temperature and mortality.
Traditional ecological knowledge of indigenous groups in the southeastern Colombian Amazon coincides in identifying the two main hydrological transition periods (wet-dry: August-November; dry-wet: March-April) as those with greater susceptibility to disease in humans. Here we analyze the association between indigenous knowledge about these two periods and the incidence of two vector-borne diseases: malaria and dengue. We researched seven “ecological calendars” from three regions in the Colombian Amazon, malaria and dengue cases reported from 2007 to 2019 by the Colombian National Institute of Health, and daily temperature and precipitation data from eight meteorological stations in the region from 1990-2019 (a climatological normal). Malaria and dengue follow a seasonal pattern: malaria has a peak from August to November, corresponding with the wet-dry transition (the “season of the worms” in the indigenous calendars), and dengue has a peak in March and April, coinciding with the dry-wet transition. Previous studies have shown a positive correlation between rainfall and dengue and a negative correlation between rainfall and malaria. However, as the indigenous ecological knowledge codified in the calendars suggests, disease prediction cannot be reduced to a linear correlation with a single environmental variable. Our data show that two major aspects of the indigenous calendars (the time of friaje as a critical marker of the year and the hydrological transition periods as periods of greater susceptibility to diseases) are supported by meteorological data and by the available information about the incidence of malaria and dengue.
OBJECTIVES: Quantify the risk of mental health (MH)-related emergency department visits (EDVs) due to heat, in the city of Curitiba, Brazil. DESIGN: Daily time series analysis, using quasi-Poisson combined with distributed lag non-linear model on EDV for MH disorders, from 2017 to 2021. SETTING: All nine emergency centres from the public health system, in Curitiba. PARTICIPANTS: 101 452 EDVs for MH disorders and suicide attempts over 5 years, from patients residing inside the territory of Curitiba. MAIN OUTCOME MEASURE: Relative risk of EDV (RR(EDV)) due to extreme mean temperature (24.5°C, 99th percentile) relative to the median (18.02°C), controlling for long-term trends, air pollution and humidity, and measuring effects delayed up to 10 days. RESULTS: Extreme heat was associated with higher single-lag EDV risk of RR(EDV) 1.03(95% CI 1.01 to 1.05-single-lag 2), and cumulatively of RR(EDV) 1.15 (95% CI 1.05 to 1.26-lag-cumulative 0-6). Strong risk was observed for patients with suicide attempts (RR(EDV) 1.85, 95% CI 1.08 to 3.16) and neurotic disorders (RR(EDV) 1.18, 95% CI 1.06 to 1.31). As to demographic subgroups, females (RR(EDV) 1.20, 95% CI 1.08 to 1.34) and patients aged 18-64 (RR(EDV) 1.18, 95% CI 1.07 to 1.30) were significantly endangered. Extreme heat resulted in lower risks of EDV for patients with organic disorders (RR(EDV) 0.60, 95% CI 0.40 to 0.89), personality disorders (RR(EDV) 0.48, 95% CI 0.26 to 0.91) and MH in general in the elderly ≥65 (RR(EDV) 0.77, 95% CI 0.60 to 0.98). We found no significant RR(EDV) among males and patients aged 0-17. CONCLUSION: The risk of MH-related EDV due to heat is elevated for the entire study population, but very differentiated by subgroups. This opens avenue for adaptation policies in healthcare: such as monitoring populations at risk and establishing an early warning systems to prevent exacerbation of MH episodes and to reduce suicide attempts. Further studies are welcome, why the reported risk differences occur and what, if any, role healthcare seeking barriers might play.
Work accidents result in consequences to the employment of the population and increasing public spendings. Caused by workplace and work activity characteristics, occupational accidents may also derive from ergonomics and comfort issues. Heat stress is a discomfort factor that affects workers when exposed to temperatures above the body limits, resulting in exhaustion, dizziness, reduced cognitive performance and, eventually, injuries and accidents. Under the current climate change scenario characterized by increase of temperature projections all around the world, the heat stress issue becomes even more significant. However, in Brazil, this topic is yet little explored, especially regarding the investigation of historical data on occupational accidents considering the climatic variables. This paper aims at filling a part of this gap by presenting a new database that unifies a work accident database -recording from 2006 to 2019 -with meteorological data of the place and time of the accident. We investigate the relationship between these two datasets through the application of Multiple Correspondence Analysis (MCA) in the R Software. Our results show some association between accident variables and heat stress variables. We identify some of the more critical workers’ characteristics in this context and the most exposed regions of Brazil. Our database allows the continuity and expansion of this type of research in Brazil, and the MCA results point to a positive association between the occurrence of accidents with climatic variables. It may pave a new path for research that can detail and deepen the discussion on the behavior of these variables.
This study investigates the impact of hurricanes on fertility and the role of family structure in early 20th century Jamaica. Importantly, this was a time period in which there were no storm warnings or other formal disaster mitigation policies in place, allowing one to arguably identify the causal effect of storms on births without any policy interference. To this end, historical hurricane tracks and an exhaustive register of births are used to create a parish level monthly data set on births and hurricane destruction for the period 1901 to 1929. The regression analysis reveals that hurricanes impact excess births for close to 2 years after the event, with the average damaging storm causing a reduction in births of around 13%. Most of the negative effect is due to lower post-storm fertility rather than a fall in births by women affected while pregnant. There is no evidence that the fall in births was driven by fertile females dying as a result of the hurricane. Similarly, there was no discernible differential impact between single mother and two parent registered births, where the impact on the latter appears to be driven by non-marital conjugal unions.
Chagas disease, considered a neglected disease, was initially confined to rural localities in endemic areas; however, in recent years through the process of urbanization and migration of infected people, the disease is gaining importance in urban environments. The presence of the vector in urban areas in most cases is due to the passive transport of vectors, but recently, its presence seems to be linked to vector adaptation processes associated with climate change. This paper reports the occurrence of an infected triatomine in the peridomicile of a house in an urban area of Córdoba, Veracruz, Mexico, where the species found is described, the molecular characteristics and resistance to BZN and NFX of the Trypanosoma cruzi isolate obtained, as well as serological data of the dwelling inhabitants. These urban disease scenarios make it possible to generate new scientific knowledge and enable the creation of new control strategies for Chagas disease vectors.
This paper explores the linkages between exposure to household shocks across early life and children’s educational and well-being outcomes in Peru. We use longitudinal survey data for a sample of 1713 children from five rounds of the Young Lives Survey to investigate how exposure to shocks across early life is linked to test scores and well-being in adolescence and to determine the extent to which critical periods of shock exposure exist. We expand on prior work by assessing the relationship between early childhood shocks and broader metrics of adolescent well-being beyond cognitive outcomes and by evaluating the cumulative impact of shocks over the course of a child’s early life. We find that exposure to a greater number of shocks across early life is negatively associated with reading and vocabulary test scores. In addition, shock exposure in adolescence-versus earlier in childhood-has the strongest negative association with testing and well-being outcomes, suggesting that older children’s time and household resources may be diverted away from learning and well-being in response to shocks. In light of increasingly frequent and severe weather events associated with climate change, as well as recent large-scale economic and health crises, policies aimed at supporting the most vulnerable children should be considered to alleviate the negative consequences of shocks on children’s educational outcomes and well-being. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11113-023-09787-x.
Introduction Climate change has significant impacts on society, including the environment, economy, and human health. To effectively address this issue, it is crucial for both research and news media coverage to align their efforts and present accurate and comprehensive information to the public. In this study, we use a combination of text-mining and web-scrapping methods, as well as topic-modeling techniques, to examine the similarities, discrepancies, and gaps in the coverage of climate change in academic and general-interest publications in Chile.Methods We analyzed 1,261 academic articles published in the Web of Science and Scopus databases and 5,024 news articles from eight Chilean electronic platforms, spanning the period from 2012 to 2022.Results The findings of our investigation highlight three key outcomes. Firstly, the number of articles on climate change has increased substantially over the past decade, reflecting a growing interest and urgency surrounding the issue. Secondly, while both news media and academic research cover similar themes, such as climate change indicators, climate change impacts, and mitigation and adaptation strategies, the news media provides a wider variety of themes, including climate change and society and climate politics, which are not as commonly explored in academic research. Thirdly, academic research offers in-depth insights into the ecological consequences of global warming on coastal ecosystems and their inhabitants. In contrast, the news media tends to prioritize the tangible and direct impacts, particularly on agriculture and urban health.Discussion By integrating academic and media sources into our study, we shed light on their complementary nature, facilitating a more comprehensive communication and understanding of climate change. This analysis serves to bridge the communication gap that commonly, exists between scientific research and news media coverage. By incorporating rigorous analysis of scientific research with the wider reach of the news media, we enable a more informed and engaged public conversation on climate change.
The Brazilian Amazon faces overlapping socio-environmental, sanitary, and climate challenges, and is a hotspot of concern due to projected increases in temperature and in the frequency of heat waves. Understanding the effects of extreme events on health is a central issue for developing climate policies focused on the population’s health. OBJECTIVES: We investigated the effects of heat waves on mortality in the Brazilian Amazon, examining effect modification according to various heat wave definitions, population subgroups, and causes of death. METHODS: We included all 32 Amazonian municipalities with more than 100,000 inhabitants. The study period was from 2000 to 2018. We obtained mortality data from the Information Technology Department of the Brazilian Public Healthcare System, and meteorological data were derived from the ERA5-Land reanalysis dataset. Heat waves were defined according to their intensity (90th; 92.5th; 95th; 97.5th and 99th temperature percentiles) and duration (≥2, ≥3, and ≥4 days). In each city, we used a time-stratified case-crossover study to estimate the effects of each heat wave definition on mortality, according to population subgroup and cause of death. The lagged effects of heat waves were estimated using conditional Poisson regression combined with distributed lag non-linear models. Models were adjusted for specific humidity and public holidays. Risk ratios were pooled for the Brazilian Amazon using a univariate random-effects meta-analysis. RESULTS: The pooled relative risks (RR) for mortality from total non-external causes varied between 1.03 (95% CI: 1.01-1.06), for the less stringent heat wave definition, and 1.18 (95% CI: 1.04-1.33) for the more stringent definition. The mortality risk rose as the heat wave intensity increased, although the increase from 2 to 3, and 3-4 days was small. Although not statistically different, our results suggest a higher mortality risk for the elderly, this was also higher for women than men, and for cardiovascular causes than for non-external or respiratory ones. CONCLUSIONS: Heat waves were associated with a higher risk of mortality from non-external causes and cardiovascular diseases. Heat wave intensity played a more important role than duration in determining this risk. Suggestive evidence indicated that the elderly and women were more vulnerable to the effects of heat waves on mortality.
Climate change is increasing human exposure to heat, especially in tropical regions such as Brazil where temperature reaches up to 40 degrees C in summer. However, the association between heat exposure and epileptic seizures has not been well demonstrated in Brazil, where lifetime preva-lence of epilepsy can range from 11.9/1000 to 21/1000. We collected a total of 225,699 hospi-talisation records for epileptic seizures of 1816 municipalities in Brazil, during the hot season from 2000 to 2015, covering nearly 79% of the national population. We implemented a time -stratified case-crossover design combined with distributed lag model with further stratified in-vestigations regarding sex, age, socioeconomic status and region. We found temperature impact threshold was 26 degrees C in Brazil nationally. Every 1 degrees C increase from the threshold was associated with an overall 4.3% increased risk of hospitalisation for epileptic seizures on the current day of hospital admission and up to seven days before, which was most pronounced on the second-day exposure to heat. Females, individuals aged 20-30 and persons living in high-income or Southeast regions were more vulnerable. Our results highlight the enhanced risk of heat exposure for epi-lepsy patients and could contribute to epilepsy management, such as forecasting epileptic sei-zures. Multi-dimensional adaptive strategies were proposed, covering individual protection, occupational health surveillance, and urban planning management, aiming to reduce heat -induced hospitalisations for epilepsy, and be generalizable to other heat-related diseases.
The Peruvian Andes has experienced widely publicized, climate change induced glacial lake outburst floods (GLOFs), which increasingly threaten the lives of thousands of the region’s residents. However, the everyday adaptations of the most historically marginalized populations in the Andes-often Quechua women in highland communities-are frequently obscured by a singular focus on glacier and water management to prevent highimpact but infrequent GLOFs. This focus on glacier hazards downplays and renders invisible the ways that Quechua women actually adapt to climate change by labeling them ‘highly vulnerable’ despite a limited understanding of their daily lives. Through a case study in the Cordillera Blanca mountain range, this article advances a feminist framework of everyday adaptation called ‘futuremaking’ that challenges the current ice-andwater-focused paradigm of adaptation policy in glaciated regions. We draw on interviews with Quechua women, participant observation on adaptation planning teams, and informal expert interviews to advance the futuremaking framework, which prioritizes the everyday and future desires of women and households over technical adaptations that view people as vulnerable. Futuremaking is a feminist process of everyday adaptation in a disaster zone that relies on A) Prioritizing the everyday over the someday; B) Intergenerational well-being and community networks of care, and; C) Dynamic and embodied adaptations to uncertainty. We argue that futuremaking both challenges the efficacy of adaptation projects currently underway in the Andes and charts a path towards more transformative adaptation interventions by prioritizing capabilities and feminist networks of care over managing damage and disaster.
Forest fires are a potential threat to life, as they contribute to reducing forest areas, impact on the services we expect from ecosystems, the health of the inhabitants is affected by smoke and the economic costs for the recovery of affected areas is high. The objective of the study is to apply fuzzy logic to model the risk of forest fires in the Cajamarca-Peru region, incorporating variables that represent biological, topographic, socioeconomic, and meteorological factors. The analysis was based on the acquisition, editing and rasterization of the database, application of fuzzy membership functions and image fuzzification, fuzzy superposition and spatial reclassification of forest fire risk. The results obtained show that 71.68% of the area is under very low or medium forest fire risk. However, 28.32% of the study area has a high to very high fire risk, which makes the occurrence of fires susceptible to the lack of rain and water in the soil. It was found that biological, topographic, and socioeconomic factors with their respective variables are directly influenced by meteorological factor variables such as temperature, rainfall and water availability. Fuzzy logic offered flexibility in modeling wildfire risk in the region, proving to be a useful tool for predicting and mapping wildfire risk.(c) 2023 by the authors; licensee Growing Science, Canada.
This study identifies the environmental and socio-economic determinants of clusters of high malaria incidence in Colombia during the period of 2008-2019. The malaria cases were obtained from the National System of Surveillance in Public Health, with 798,897 cases reported in the 986 Colombian municipalities evaluated during the study period. Spatial autocorrelation of incidence was examined with global and local indices. Clusters were identified in the Amazon, Pacific, and Uraba-Bajo Cauca-Alto Sinú regions. The factors associated with a municipality belonging to a high-incidence cluster were identified using a logistic regression model with mixed effects and showed a positive association for the variables (forest coverage and minimum multi-year average rainfall). An inverse relationship was observed for aqueduct coverage and the odds of belonging to a cluster. A 1% increase in forest coverage was associated with a 4.2% increase in the odds of belonging to a malaria cluster. The association with minimum multi-year average rainfall was positive (OR = 1.0011; 95% CI 1.0005-1.0027). A 1% increase in aqueduct coverage was associated with a 4.3% decrease in the odds of belonging to malaria cluster. The identification of malaria cluster determinants in Colombia could help guide surveillance and disease control policies.
OBJECTIVE: To evaluate the association between the risk of death from COPD and air temperature events in ten major Brazilian microregions. METHODS: This was a time series analysis of daily COPD deaths and daily mean air temperatures between 1996 and 2017. Using distributed nonlinear lag models, we estimated the cumulative relative risks of COPD mortality for four temperature percentiles (representing moderate and extreme cold and heat events) in relation to a minimum mortality temperature, with a lag of 21 days, in each microregion. RESULTS: Significant associations were found between extreme air temperature events and the risk of death from COPD in the southern and southeastern microregions in Brazil. There was an association of extreme cold and an increased mortality risk in the following microregions: 36% (95% CI, 1.12-1.65), in Porto Alegre; 27% (95% CI, 1.03-1.58), in Curitiba; and 34% (95% CI, 1.19-1.52), in São Paulo; whereas moderate cold was associated with an increased risk of 20% (95% CI, 1.01-1.41), 33% (95% CI, 1.09-1.62), and 24% (95% CI, 1.12-1.38) in the same microregions, respectively. There was an increased COPD mortality risk in the São Paulo and Rio de Janeiro microregions: 17% (95% CI, 1.05-1.31) and 12% (95% CI, 1,02-1,23), respectively, due to moderate heat, and 23% (95% CI, 1,09-1,38) and 32% (95% CI, 1,15-1,50) due to extreme heat. CONCLUSIONS: Non-optimal air temperature events were associated with an increased risk of death from COPD in tropical and subtropical areas of Brazil.
OBJECTIVES: This study aimed to analyse hospitalisations for respiratory diseases in the Western Region of Bahia, Northeast Brazil, from 2010 to 2019, and to explore possible correlations with meteorological data. STUDY DESIGN: This descriptive, epidemiological, ecological study analysed data from 37 municipalities in the Western Bahia health macro-region, defined according to geographical, administrative, demographic, epidemiological, social and cultural criteria, and accounting for availability of health resources. METHODS: Hospitalisation data for respiratory diseases, including total admissions and disease frequency, mean and prevalence, were obtained from DATASUS (Ministry of Health). The data were evaluated by sex, age group and city. Statistical tests, such as the Chi-squared test and analysis of variance, were used for data analysis. Meteorological data were compared using the t-test and Mann-Whitney test. Correlations between health indicators and weather data were assessed using the Pearson and Spearman correlation coefficients. RESULTS: Over the investigated period, there were 536,195 hospitalisation records in the region, with respiratory diseases accounting for 17.1% of admissions. Notably, 40% of respiratory hospitalisations were among children aged 0-9 years. The most prevalent respiratory conditions were pneumonia and asthma, which together constituted 73% of all respiratory hospitalisations. A significant negative correlation was observed between respiratory diseases and rainfall (r = -0.70, P = 0.011). CONCLUSIONS: Pneumonia and asthma remain important causes of hospitalisation among children in the Western Bahia Region. The study findings suggest that respiratory diseases are influenced by rainfall, possibly due to increased atmospheric pollutants during time of low rainfall. These findings emphasise the importance of environmental factors in the development and exacerbation of respiratory diseases.
Heat waves are becoming more intense and extreme as a consequence of global warming. Epidemiological evidence reveals the health impacts of heat waves in mortality and morbidity outcomes, however, few studies have been conducted in tropical regions, which are characterized by high population density, low income and low health resources, and susceptible to the impacts of extreme heat on health. The aim of this paper is to estimate the effects of heat waves on cardiovascular and respiratory mortality in the city of Rio de Janeiro, Brazil, according to sex, age, and heat wave intensity. METHODS: We carried out a time-stratified case-crossover study stratified by sex, age (0-64 and 65 or above), and by sex for the older group. Our analyses were restricted to the hot season. We included 42,926 participants, 29,442 of whom died from cardiovascular and 13,484 from respiratory disease, between 2012 and 2017. The death data were obtained from Rio de Janeiro’s Municipal Health Department. We estimated individual-level exposure using the inverse distance weighted (IDW) method, with temperature and humidity data from 13 and 12 stations, respectively. We used five definitions of heat waves, based on temperature thresholds (90th, 92.5th, 95th, 97.5th, and 99th of individual daily mean temperature in the hot season over the study period) and a duration of two or more days. Conditional logistic regression combined with distributed lag non-linear models (DLNM) were used to estimate the short-term and delayed effects of heat waves on mortality over a lag period (5 days for cardiovascular and 10 for respiratory mortality). The models were controlled for daily mean absolute humidity and public holidays. RESULTS: The odds ratios (OR) increase as heat waves intensify, although some effect estimates are not statistically significant at 95% level when we applied the most stringent heat wave criteria. Although not statistically different, our central estimates suggest that the effects were greater for respiratory than cardiovascular mortality. Results stratified by sex and age were also not statistically different, but suggest that older people and women were more vulnerable to the effects of heat waves, although for some heat wave definitions, the OR for respiratory mortality were higher among the younger group. The results also indicate that older women are the most vulnerable to heat wave-related cardiovascular mortality. CONCLUSION: Our results show an increase in the risk of cardiovascular and respiratory mortality on heat wave days compared to non-heat wave ones. These effects increase with heat wave intensity, and evidence suggests that they were greater for respiratory mortality than cardiovascular mortality. Furthermore, the results also suggest that women and the elderly constitute the groups most vulnerable to heat waves.
The community structure of sand flies indicates the level of adaptation of vector species in a region, and in the context of vector management and control, this information allows for identifying the potential risks of pathogen transmission. This study aimed to analyze sand fly diversity and spatial-temporal distribution in an endemic area of cutaneous leishmaniasis. The study was carried out in the Carrizales hamlet (Caldas), between September 2019 and October 2021. The monthly distribution of sand fly species was evaluated through collections with CDC traps. Shannon and evenness indices were calculated and used to compare species frequencies at each house. The association between climatic variables and the frequency of sand flies was evaluated using Spearman’s correlation. A total of 6,265 females and 1,958 males belonging to 23 species were found. Low diversity and evenness were observed, with the dominance of Nyssomyia yuilli yuilli (Young & Porter). Ecological and diversity indices did not reveal differences between the houses. The sand fly community was composed of 3 dominant species, Ny. yuilli yuilli, Psychodopygus ayrozai (Barretto & Coutinho), and Ps. panamensis (Shannon), representing 75.8% of the total catches. No statistical association was found between the absolute frequency of sand flies, rainfall, and temperature. The results show one dominant species, this fact has epidemiological relevance since density influences parasite-vector contact. The high densities of sand flies recorded in peri- and intradomiciliary areas highlight the necessity of periodic monitoring of vector populations and control activities to reduce the risk of Leishmania transmission in this endemic area.
Climate change constitutes an unprecedented challenge for public health and one of its main direct effects are extreme temperatures. It varies between intra-urban areas and this difference is called surface urban heat island (SUHI) effect. We aimed to assess SUHI distribution among socioeconomic levels in Lima, Peru by conducting a cross-sectional study at the block-level. The mean land surface temperature (LST) from 2017 to 2021 were estimated using the TIRS sensor (Landsat-8 satellite [0.5 km scale]) and extracted to block level. SUHI was calculated based on the difference on mean LST values (2017-2021) per block and the lowest LST registered in a block. Socioeconomic data were obtained from the 2017 Peruvian census. A principal component analysis was performed to construct a socioeconomic index and a mixture analysis based on quantile g-computation was conducted to estimate the joint and specific effects of socioeconomic variables on SUHI. A total of 69 618 blocks were included in the analysis. In the Metropolitan Lima area, the mean SUHI estimation per block was 6.44 (SD = 1.44) Celsius degrees. We found that blocks with high socioeconomic status (SES) showed a decreased exposure to SUHI, compared to those blocks where the low SES were predominant (p-value < 0.001) and that there is a significant SUHI exposure variation (p-value < 0.001) between predominant ethnicities per block (Non-White, Afro-American, and White ethnicities). The mixture analysis showed that the overall mixture effect estimates on SUHI was -1.01 (effect on SUHI of increasing simultaneously every socioeconomic variable by one quantile). Our study highlighted that populations with low SES are more likely to be exposed to higher levels of SUHI compared to those who have a higher SES and illustrates the importance to consider SES inequalities when designing urban adaptation strategies aiming at reducing exposure to SUHI.
Prior research has shown that climate literacy is sparse among low- and middle-income countries. Additionally, no standardized questionnaire exists for researchers to measure climate literacy among general populations, particularly with regards to climate change effects on vector-borne diseases (VBDs). We developed a comprehensive literacy scale to assess current knowledge, attitudes, and behaviors towards climate change and VBD dynamics among women enrolled in the Caribbean Consortium for Research in Environmental and Occupational Health (CCREOH) cohort in Suriname. Items were generated by our research team and reviewed by a group of six external climate and health experts. After the expert review, a total of 31 climate change and 21 infectious disease items were retained. We estimated our sample size at a 10:1 ratio of participants to items for each scale. In total, 301 women were surveyed. We validated our scales through exploratory (n = 180) and confirmatory factor analyses (n = 121). An exploratory factor analysis for our general Climate Change Scale provided a four-construct solution of 11 items. Our chi-squared value (X(2) = 74.32; p = 0.136) indicated that four factors were sufficient. A confirmatory factor analysis reinforced our findings, providing a good model fit (X(2) = 39.03; p = 0.23; RMSEA = 0.015). Our Infectious Disease Scale gave a four-construct solution of nine items (X(2) = 153.86; p = 0.094). A confirmatory factor analysis confirmed these results, with a chi-squared value of 19.16 (p = 0.575) and an RMSEA of 0.00. This research is vitally important for furthering climate and health education, especially with increases in VBDs spread by Aedes mosquitoes in the Caribbean, South America, and parts of the southern United States.
Climate change has increased the frequency of extreme weather events and, consequently, the number of oc-currences of natural disasters. In Brazil, among these disasters, floods, flash floods, and landslides account for the highest number of deaths, the latter being the most lethal. Bearing in mind the importance of monitoring areas susceptible to disasters, the REMADEN/REDEGEO project of the National Center for Monitoring and Natural Disaster Alerts (Cemaden) has promoted the installation of a network of soil moisture sensors in regions with a long history of landslides. This network was used in the present paper as a base to develop a system for moisture forecasting in those critical zones. The time series of rainfall and moisture were used in an inversion algorithm to obtain the geotechnical parameters of the soil. Then the geotechnical model was used in a forward calculation with the rainfall prediction to obtain the soil moisture forecast. The landslide events of March 2020 and May 2022 in Guaruj ‘ a and Recife, respectively, were used as study cases for the developed system. The obtained results indicate that the proposed methodology has the potential to be used as an important tool in the decision-making process for issuing landslide alerts.
Varicella causes a major health burden in many low- to middle-income countries located in tropical regions. Because of the lack of surveillance data, however, the epidemiology of varicella in these regions remains uncharacterized. In this study, based on an extensive dataset of weekly varicella incidence in children ≤10 during 2011-2014 in 25 municipalities, we aimed to delineate the seasonality of varicella across the diverse tropical climates of Colombia. METHODS: We used generalized additive models to estimate varicella seasonality, and we used clustering and matrix correlation methods to assess its correlation with climate. Furthermore, we developed a mathematical model to examine whether including the effect of climate on varicella transmission could reproduce the observed spatiotemporal patterns. RESULTS: Varicella seasonality was markedly bimodal, with latitudinal changes in the peaks’ timing and amplitude. This spatial gradient strongly correlated with specific humidity (Mantel statistic = 0.412, P = .001) but not temperature (Mantel statistic = 0.077, P = .225). The mathematical model reproduced the observed patterns not only in Colombia but also México, and it predicted a latitudinal gradient in Central America. CONCLUSIONS: These results demonstrate large variability in varicella seasonality across Colombia and suggest that spatiotemporal humidity fluctuations can explain the calendar of varicella epidemics in Colombia, México, and potentially in Central America.
Dengue is a vector borne disease caused by virus serotypes DENV-1, DENV-2, DENV-3, and DENV-4, representing a significant public health concern in the Region of the Americas (2,997,097 cases in 2023). This study explores the relationship between dengue incidence and climate changes in the city of São Paulo-Brazil. During the first semester of 2023, Brazil reported the highest number of dengue cases in Americas’ Region. Our data reveals a correlation between the high temperature and rainfall season persistence and the extension of dengue incidence into the winter season. The findings highlight the importance of understanding the relationship between climate change and disease transmission patterns to develop effective strategies for prevention and control.
Young people today are predicted to experience more climate change related stressors and harms than the previous generation, yet they are often excluded from climate research, policy, and advocacy. Increasingly, this exposure is associated with experience of common mental health disorders (CMD). The VoCes-19 study collected surveys from 168,407 young people across Mexico (ages 15-24 years) through an innovative online platform, collecting information on various characteristics including CMD and experience of recent climate harms. Logistic regression models were fit to explore characteristics associated with CMD. Structural equation models were fit to explore pathways between exposure, feeling of concern about climate change, and a sense of agency (meaning the respondent felt they could help address the climate crisis) and how these relate to CMD. Of the respondents, 42% (n = 50,682) were categorized as experiencing CMD, higher among those who experienced a climate stressor (51%, n = 4,808) vs those not experiencing climate stressors (41%, n = 43,872). Adjusting for key demographic characteristics, exposure to any climate event increased the odds of CMD by 50% (Odd Ratio = 1.57; 95% Confidence Interval (CI) 1.49, 1.64), highest for heatwaves. Specific climate impacts such as housing damage, loss of or inability to work, damage to family business, leaving school and physical health affected were adversely related to CMD, though for different climate hazards. More concern and less agency were related to CMD through different pathways, particularly for those exposed to recent events. Future research regarding the cumulative exposures to climate change, not just acute events but as an ongoing crisis, and various pathways that influence the mental health and well-being of young people must be clearly understood to develop programs and policies to protect the next generation.
Cities in the global south face dire climate impacts. It is in socioeconomically marginalized urban communities of the global south that the effects of climate change are felt most deeply. Santiago de Chile, a major mid-latitude Andean city of 7.7 million inhabitants, is already undergoing the so-called “climate penalty” as rising temperatures worsen the effects of endemic ground-level ozone pollution. As many cities in the global south, Santiago is highly segregated along socioeconomic lines, which offers an opportunity for studying the effects of concurrent heatwaves and ozone episodes on distinct zones of affluence and deprivation. Here, we combine existing datasets of social indicators and climate-sensitive health risks with weather and air quality observations to study the response to compound heat-ozone extremes of different socioeconomic strata. Attributable to spatial variations in the ground-level ozone burden (heavier for wealthy communities), we found that the mortality response to extreme heat (and the associated further ozone pollution) is stronger in affluent dwellers, regardless of comorbidities and lack of access to health care affecting disadvantaged population. These unexpected findings underline the need of a site-specific hazard assessment and a community-based risk management.
Despite being perceived as a warm country, winters in the Central Mexican Plateau frequently reach temperatures below zero Celsius. Prolonged exposures to low temperatures resulting in heart and respiratory morbidities are estimated to be responsible for 50% of the reported illness in the plateau, attributable primarily to the design of homes ill-suited to extreme temperatures. Consequently, there is a growing need to ensure that dwellings provide adequate indoor thermal conditions in the region. Hence, on-site sensors were used to collect temperature and relative humidity data every five minutes in 26 living rooms in the Plateau for 11 months. From these data, a subsample was determined, resulting in dwelling-level thermal comfort and health surveys on 15 homes. Computer simulations were used to investigate whether the building itself could provide thermal comfort under different retrofitting scenarios. Multiple linear regression relating the Predicted Percentage Dissatisfaction (PPD) index to self-perceived health was undertaken. Both monitored and simulated results were matched against our underheating model, finding that 92% of the homes had cold indoor environments, some even during summer. High PPD and intense levels of underheating were positive predictors of higher self-reported health problems. More self-reported health problems were correlated with both lower life satisfaction and self-worth, and with subjects’ use of more adaptive strategies against environmental dissatisfaction. Dynamic computer simulations suggested that indoor thermal environments could be improved by enforcing the non-utilised standard NOM-ENER-020, which recommends the addition of insulation on walls and roofs. These findings suggest that the cold environments within homes of the plateau influence the self-perceived physical and mental health of its population. Hence, the application of adequate measures, such as retrofitting homes with stronger standards than the existing NOM-ENER-020 are needed in place.
Dengue transmission poses significant challenges for public health authorities worldwide due to its susceptibility to various factors, including environmental and climate variability, affecting its incidence and geographic spread. This study focuses on Costa Rica, a country characterized by diverse microclimates nearby, where dengue has been endemic since its introduction in 1993. Using wavelet coherence and clustering analysis, we performed a time-series analysis to uncover the intricate connections between climate, local environmental factors, and dengue occurrences. The findings indicate that multiannual dengue frequency (3 yr) is correlated with the Oceanic Niño Index and the Tropical North Atlantic Index. This association is particularly prominent in cantons located along the North and South Pacific Coast, as well as in the Central cantons of the country. Furthermore, the time series of these climate indices exhibit a leading phase of approximately nine months ahead of dengue cases. Additionally, the clustering analysis uncovers non-contiguous groups of cantons that exhibit similar correlation patterns, irrespective of their proximity or adjacency. This highlights the significance of climate factors in influencing dengue dynamics across diverse regions, regardless of spatial closeness or distance between them. On the other hand, the annual dengue frequency was correlated with local environmental indices. A persistent correlation between dengue cases and local environmental variables is observed over time in the North Pacific and the Central Region of the country’s Northwest, with environmental factors leading by less than three months. These findings contribute to understanding dengue transmission’s spatial and temporal dynamics in Costa Rica, highlighting the importance of climate and local environmental factors in dengue surveillance and control efforts.
For policies and programs aiming at reducing climate risk, it is important to obtain vulnerability information at the sub-national level to identify hotspots. For the case of Costa Rica, no sub-national climate vulnerability index exists to date. To fill this gap, we constructed a climate vulnerability index at the canton level. We ground our work in the conceptual framework that vulnerability is a function of exposure, sensitivity, and adaptive capacity. Making extensive use of geographic information systems and publicly available data, we constructed 13 spatial layers to reflect the multi-dimensionality of vulnerability. Layers reflect for example, changes in climatic extremes, flood risk, vegetation cover, access to infrastructure (road density) and health services (distance to hospitals), as well as various socioeconomic (wealth level, employment rates, remittances, literacy rate) and demographic (infant mortality) characteristics. Following normalization, we constructed an inverse variance weighted index of canton-level climate vulnerability. We confirmed the validity of our climate vulnerability index through correlation with disaster damage data. We find the strongest climate vulnerability not only in the rural, agricultural producing border cantons (Los Chiles, Matina, Talamanca, Buenos Aires), but also for a few central urban cantons (Tibas, San Jose). Projects and interventions in these hot spot cantons may reduce sensitivity through strengthening hydrological infrastructure and economic development, while adaptive capacity may be improved through addressing barriers of remittance transfer, and via public health programs.
Given the lack of publications and public policies addressing the relationship between cli-mate change and cancer care in Colombia, we present an exploration of the perspectives and communication practices of a group of nurses from Valle del Cauca and Antioquia. We provide a context based on the available literature on climate change and general health then provide an overview of cancer in the country. Next, we present how oncology nurses have incorporated information about strategies their patients can use to mitigate the effects of climate change on their health. We highlight the centrality of patient -centered communication using a framework from the US National Cancer Institute) and the fundamental role nurses have in patients’ experiences throughout their treatment. We conclude with the need to investigate oncology nurse communication practices in other Colombian hospitals, with consideration of culture, cancer stigma, barriers to care and other factors that may influence successful climate change mitigation and to bet-ter understand how other Latin American oncology nurses are addressing this serious challenge.
One of the climate problems that causes the most environmental impact worldwide is the trend of increasing occurrence of events of maximum extreme temperature, signaled by indicators such as hot extremes (HE) and maximum maximorum (highest maximum) temperature (MmT). These events can cause conditions ranging from severe droughts to heat stroke, which can cause death in any population. Indicators of maximum extreme temperature in one of the most important agricultural areas in northwestern Mexico were calculated based on significant trends (ST) and adjusted return periods. To calculate the trends of the maximum extreme tempera-ture, frequency (FR), annual average duration (AAD), annual daily duration (ADD), intensity (IN) of HE, and MmT, the Mann-Kendall and Sen’s slope tests were applied to data obtained for 19 weather stations from the CLImate COMputing database for the period 1982-2014. Adjusted return periods (ARP) were calculated for each indicator of maximum extreme temperature by fitting a probability distribution function. For the study area, the ST and maximum extreme temperature shows a prevailing cooling trend. This can be deduced by observing the proportion of negative ST compared with positive ST. The highest positive magnitudes of ST were recorded at stations CUL (FR = 3.44 HE dec-1), GUT (AAD = 6.15 day HE-1 dec-1and IN = 13.62 degrees C dec-1), IXP (ADD = 35.00 day dec-1) and POT (MmT = 2.50 degrees C day-1 dec-1). For ARP, the estimate of the average occurrence frequency of extreme events per100 years are FR = 6.11 HE dec-1 (1 time), AAD = 6.64 day HE-1 dec-1 (4 times), ADD = 38.68 day dec-1 (1 time), IN = 39.09 degrees C dec-1 (6 times) and MmT = 41.95 degrees C day-1 dec-1 (1 time). These findings are of key importance for the economic sectors related to agricultural production in the state known, at least to date, as “the breadbasket of Mexico” (Sinaloa). The results will help to develop adaptation/prevention measures before the coming socioeconomic and hydrological disasters.
PurposeSocieties go through complex challenges in the face of the vertiginous increase in disasters, mostly produced by the effects of extreme events. The lack of capacity to deal with disasters is evident, especially in developing countries, as in the case of Peru. Under such a premise, this paper contributes to strengthening the country’s capacities, through an evaluation of national disaster resilience to the El Nino-Southern Oscillation-driven hazards caused by the El Nino disaster event between 2016 and 2017 on the Peruvian coast. Design/methodology/approachBy reviewing the literature, various hazards were identified, such as heavy rainfalls and cascading hazards, such as floods and landslides. Even though risk assessments were carried out, 169 people died and essential infrastructure was severely impacted and lost. Through a 12-criteria resilience assessment framework sub-divided into sustainable development and disaster risk reduction, a diagnosis of national disaster resilience was carried out, along with a disaster risk management evaluation. Under such assessments, strategic recommendations were proposed to enhance the resilience of the country. FindingsThe lack of resilience of the country is reflected in the evaluated criteria, the most negative being the built environment due to infrastructure system’s vulnerability to hazards, and the lack of social development, despite national economic growth in Peru. Originality/valueThe research is extremely valuable because it bridges the knowledge gap on disaster resilience in Peru. In addition, the methodology, as well as the multi-topic assessment framework, can be used for other analyses, which are key to building greater capacity in nations around the globe.
Due to the rapid geographic spread of the Aedes mosquito and the increase in dengue incidence, dengue fever has been an increasing concern for public health authorities in tropical and subtropical countries worldwide. Significant challenges such as climate change, the burden on health systems, and the rise of insecticide resistance highlight the need to introduce new and cost-effective tools for developing public health interventions. Various and locally adapted statistical methods for developing climate-based early warning systems have increasingly been an area of interest and research worldwide. Costa Rica, a country with microclimates and endemic circulation of the dengue virus (DENV) since 1993, provides ideal conditions for developing projection models with the potential to help guide public health efforts and interventions to control and monitor future dengue outbreaks. Climate information was incorporated to model and forecast the dengue cases and relative risks using a Bayesian spatio-temporal model, from 2000 to 2021, in 32 Costa Rican municipalities. This approach is capable of analyzing the spatio-temporal behavior of dengue and also producing reliable predictions.
Further research is needed to examine the nationwide impact of temperature on health in Brazil, a region with particular challenges related to climate conditions, environmental characteristics, and health equity. To address this gap, in this study, we looked at the relationship between high ambient temperature and hospital admissions for circulatory and respiratory diseases in 5572 Brazilian municipalities between 2008 and 2018. We used an extension of the two-stage design with a case time series to assess this relationship. In the first stage, we applied a distributed lag non-linear modeling framework to create a cross-basis function. We next applied quasi-Poisson regression models adjusted by PM(2.5), O(3), relative humidity, and time-varying confounders. We estimated relative risks (RRs) of the association of heat (percentile 99th) with hospitalization for circulatory and respiratory diseases by sex, age group, and Brazilian regions. In the second stage, we applied meta-analysis with random effects to estimate the national RR. Our study population includes 23,791,093 hospital admissions for cardiorespiratory diseases in Brazil between 2008 and 2018. Among those, 53.1% are respiratory diseases, and 46.9% are circulatory diseases. The robustness of the RR and the effect size varied significantly by region, sex, age group, and health outcome. Overall, our findings suggest that i) respiratory admissions had the highest RR, while circulatory admissions had inconsistent or null RR in several subgroup analyses; ii) there was a large difference in the cumulative risk ratio across regions; and iii) overall, women and the elderly population experienced the greatest impact from heat exposure. The pooled national results for the whole population (all ages and sex) suggest a relative risk of 1.29 (95% CI: 1.26; 1.32) associated with respiratory admissions. In contrast, national meta-analysis for circulatory admissions suggested robust positive associations only for people aged 15-45, 46-65, >65 years old; for men aged 15-45 years old; and women aged 15-45 and 46-65 years old. Our findings are essential for the body of scientific evidence that has assisted policymakers to promote health equity and to create adaptive measures and mitigations.
Extreme temperatures are a major public health concern, as they have been linked to an increased risk of mortality from circulatory and respiratory diseases. Brazil, a country with vast geographic and climatic variations, is particularly vulnerable to the health impacts of extreme temperatures. In this study, we examined the nationwide (considering 5572 municipalities) association of low and high ambient temperature (1st and 99th percentiles) with daily mortality for circulatory and respiratory diseases in Brazil between 2003 and 2017. We used an extension of the two-stage time-series design. First, we applied a case time series design in combination with distributed lag non-linear modeling (DLMN) framework to assess the association by Brazilian region. Here, the analyses were stratified by sex, age group (15-45, 46-65, and >65 years), and cause of death (respiratory and circulatory mortality). In the second stage, we performed a meta-analysis to estimate pooled effects across the Brazilian regions. Our study population included 1,071,090 death records due to cardiorespiratory diseases in Brazil over the study period. We found increased risk of respiratory and circulatory mortality associated with low and high ambient temperatures. The pooled national results for the whole population (all ages and sex) suggest a relative risk (RR) of 1.27 (95% CI: 1.16; 1.37) and 1.11 (95% CI: 1.01; 1.21) associated with circulatory mortality during cold and heat exposure, respectively. For respiratory mortality, we estimated a RR of 1.16 (95% CI: 1.08; 1.25) during cold exposure and a RR of 1.14 (95% CI: 0.99; 1.28) during heat exposure. The national meta-analysis indicated robust positive associations for circulatory mortality on cold days across several subgroups by sex and age, while only a few subgroups presented robust positive associations for circulatory mortality on warm days and respiratory mortality on both cold and warm days. These findings have important public health implications for Brazil and suggest the need for targeted interventions to mitigate the adverse effects of extreme temperatures on human health.
Dengue fever is a vector-borne disease affecting millions yearly, mostly in tropical and subtropical countries. Driven mainly by social and environmental factors, dengue incidence and geographical expansion have increased in recent decades. Therefore, understanding how climate variables drive dengue outbreaks is challenging and a problem of interest for decision-makers that could aid in improving surveillance and resource allocation. Here, we explore the effect of climate variables on relative dengue risk in 32 cantons of interest for public health authorities in Costa Rica. Relative dengue risk is forecast using a Generalized Additive Model for location, scale, and shape and a Random Forest approach. Models use a training period from 2000 to 2020 and predicted climatic variables obtained with a vector auto-regressive model. Results show reliable projections, and climate variables predictions allow for a prospective instead of a retrospective study.
Natural disasters have been responsible for thousands of deaths in recent decades that, added to the environmental, social and economic impacts, require the implementation of prevention strategies. The largest share of disasters is of hydrological origin. In this context, hydrological models are potential alternatives for monitoring and preventing events of this nature. The objective of this study was to analyze the applicability of the semi-distributed model SWAT (Soil and Water Assessment Tool) and the concentrated model SMAP (soil moisture accounting procedure) in predicting the extreme flood event that occurred in Brazil in the mountainous region of Rio de Janeiro in 2011. The results showed that the mean relative error in calibration and validation was 12% and 53% for SMAP, and 18.46% and 88.73% for SWAT, respectively. The better performance of SMAP in validation integrated with its ease of data collection, simplicity of execution and semi-automatic calibration included in its routine, allows for the conclusion that this model proved to be more suitable for hydrological monitoring. In this study, for the first time, a model of SWAT’s complexity was applied to a watershed located in the mountainous region of the state of Rio de Janeiro, a region that, unfortunately, has accounted for thousands of deaths over the past decades associated with mass movements and floods. The SWAT model, besides being able to predict the level and flow of the main course of the river and its tributaries, also enables the calculation of sediment transport in extreme events. Looking from an operational point of view, the work clearly shows how poor hydro-meteorological monitoring, as is the case in this region, makes a good quality prediction for extreme events impossible. It was demonstrated that under these conditions, a simpler and concentrated modeling approach, such as the SMAP model, is able to obtain better results than SWAT.
In recent years, the morbidity and mortality rates caused by stings and bites of poisonous species have been constant in Mexico; such a phenomenon has been emphasized due to the dominance or modification of the natural geosystem. The modification in the availability of water resources has caused changes in the climate, extreme droughts, and floods that influence the distribution of species, generating risks where they did not occur before. With the aforementioned, it is important to identify risky points through the development of new cartography in the country, which allows an analysis from a spatial and geostatistical perspective. Based on the number of victims of stings or bites, there will be a sharp increase in exposure to poisonous animals where the distribution of these species overlaps with areas of high vulnerability as well as social and natural contact in Mexico. The aim of this study is to model the anthropogenic risk of poisonous species in Mexico in a spatial way (data from 2010-2017). The spatial analyses of this study were carried out throughout the Mexican territory and focused on species such as coral snakes, rattlesnakes, scorpions, and centipedes. The variables of vulnerability, danger, and exposure were considered to create a generalized risk model using the core area alternative in the zonation program, allowing a spatial analysis. The methodology consisted of six stages: (1) the identification of threats and records collected from chosen poisonous animals; (2) obtaining risk models by using the Zonation software that summarized all the species distribution modeling (SDM); (3) the development of a general anthropogenic vulnerability indicator; (4) obtaining the general exposure model with the index of accessibility to medical services; (5) obtaining risk models; and (6) the validation of risk models with morbidity and mortality rates by obtaining geostatistical models. The highlighted risk areas are the Pacific Ocean coast from Southern Sinaloa to the border of Michoacan, a corridor from central Veracruz to northern Oaxaca, central Guerrero, northern Michoacan, and northwestern Nuevo Leon.
Norovirus is a major cause of acute diarrheal disease (ADD) outbreaks worldwide. In the present study, we investigated an ADD outbreak caused by norovirus in several municipalities of Santa Catarina state during the summer season, southern Brazil in 2023. As of the 10th epidemiological week of 2023, approximately 87 000 ADD cases were reported, with the capital, Florianópolis, recording the highest number of cases throughout the weeks. By using RT-qPCR and sequencing, we detected 10 different genotypes, from both genogroups (G) I and II. Some rare genotypes were also identified. Additionally, rotavirus and human adenovirus were sporadically detected among the ADD cases. Several features of the outbreak suggest that sewage-contaminated water could played a role in the surge of ADD cases. Storm events in Santa Catarina state that preceded the outbreak likely increased the discharge of contaminated wastewater and stormwater into water bodies, such as rivers and beaches during a high touristic season in the state. Climate change-induced extreme weather events, including intensified rainfall and frequent floods, can disturb healthcare and sanitation systems. Implementing public policies for effective sanitation, particularly during peak times, is crucial to maintain environmental equilibrium and counter marine pollution.
Pathogen strain diversity is an important driver of the trajectory of epidemics. The role of bioclimatic factors on the spatial distribution of dengue virus (DENV) serotypes has, however, not been previously studied. Hence, we developed municipality-scale environmental suitability maps for the four dengue virus serotypes using maximum entropy modeling. We fit climatic variables to municipality presence records from 2012 to 2020 in Mexico. Bioclimatic variables were explored for their environmental suitability to different DENV serotypes, and the different distributions were visualized using three cutoff probabilities representing 90%, 95%, and 99% sensitivity. Municipality-level results were then mapped in ArcGIS. The overall accuracy for the predictive models was 0.69, 0.68, 0.75, and 0.72 for DENV-1, DENV-2, DENV-3, and DENV-4, respectively. Important predictors of all DENV serotypes were the growing degree days for December, January, and February, which are an indicator of higher temperatures and the precipitation of the wettest month. The minimum temperature of the coldest month between -5 & DEG;C and 20 & DEG;C was found to be suitable for DENV-1 and DENV-2 serotypes. Respectively, above 700-900 mm of rainfall, the suitability for DENV-1 and DENV-2 begins to decline, while higher humidity still favors DENV-3 and DENV-4. The sensitivity concerning the suitability map was developed for Mexico. DENV-1, DENV-2, DENV-3, and DENV-4 serotypes will be found more commonly in the municipalities classified as suitable based on their respective sensitivity of 91%, 90%, 89%, and 85% in Mexico. As the microclimates continue to change, specific bioclimatic indices may be used to monitor potential changes in DENV serotype distribution. The suitability for DENV-1 and DENV-2 is expected to increase in areas with lower minimum temperature ranges, while DENV-3 and DENV-4 will likely increase in areas that experience higher humidity. Ongoing surveillance of municipalities with predicted suitability of 89% and 85% should be expanded to account for the accurate DENV serotype prevalence and association between bioclimatic parameters.
Sugarcane cutters are vulnerable to extreme heat and are at risk for heat-related illness and chronic kidney disease, potentially due to high heat strain. We performed a comprehensive assessment of the physiological demands of sugarcane cutters via measurements of metabolic, thermal, and cardiovascular responses. In addition, we assessed cross-shift changes in markers of kidney function. Nine male sugarcane cutters were monitored while working during the spring harvest season in Brazil. Core temperature (Tcore) and heart rate (HR) were continuously recorded, and oxygen consumption was measured during the work shift. Urine and blood samples were collected pre- and postwork shifts. Total sweat loss was calculated using body weight changes and adjusting for water ingestion and urine output. A wet-bulb globe temperature (WBGT) station was used to monitor environmental heat stress. WBGT was ≥30°C on 7 of the 8 study days. Mean and peak Tcore during the work shift were 37.96 ± 0.47°C and 38.60 ± 0.41°C, respectively, with all participants surpassing a Tcore of 38°C. Mean and peak HR during the work shift were 137 ± 14 and 164 ± 11 beats/min, respectively. Percent of maximal oxygen consumption was, on average, 53 ± 11%. Workers had a total sweat loss of 7.63 ± 2.31 L and ingested 6.04 ± 1.95 L of fluid. Kidney function (estimated glomerular filtration rate) was reduced from pre- to postwork shift (Δ -20 ± 18 mL·min·1.73 m(2)). We demonstrated that sugarcane cutters performing prolonged work during a period of high environmental heat stress display high levels of heat strain, high water turnover, and reduced kidney function.NEW & NOTEWORTHY We demonstrate that a shift of sugarcane cutting performed outdoors during the spring harvest season results in a high level of heat strain. In fact, all the studied workers sustained core temperatures above 38°C and heart rates above 75% of the measured maximum heart rate. Additionally, workers displayed a high water turnover with sweat loss close to 10% of their body weight. Finally, we report elevated muscle damage and reductions in kidney function following the work shift.
Bioenergy can be part of strategies towards achieving climate and energy-related UN Sustainable Development Goals, especially for land abundant countries. Biofuel advocates argue that such strategies advance at least onethird of the SDGs, whereas opponents claim that they lead to negative trade-offs. Numerous studies have explored the benefits and risks of early bioenergy policies. Here we study the new Brazilian biofuel policy Renovabio, which was designed to increase the share of biofuels in the national energy mix of the world’s second largest biofuel producer to 18%. We use an impact score scheme to assess the potential effects of the policy on the SDGs based on expert opinions and triangulate our findings with a literature review. Our results indicate that these experts entertain high expectations for the policy’s mechanisms to increase bioenergy production and promote the substitution of fossil fuels. The policy is expected to support climate-related, economic and technological SDG targets, while potential impacts in other SDG dimensions, such as environmental, social, and health targets are contradictory. Our results reflect the positions in the debate around biofuels and indicate a need for effective sustainability safeguards to ensure that national policies like Renovabio actually live up to their declared objectives.
In this article we connect theoretically the concepts of structural vulnerabilities, recursive crises, and disasters through the linking-up of the COVID-19 pandemic with extreme hydrometeorological events in three municipalities in southern Yucatan, Mexico. The main research goal was to show the effects in productive and commercial systems in beekeeper and farmer households and their coping strategies to highlight the inter-relationships between historical vulnerabilities, crises, and disasters. The methodological approach included ethnographic fieldwork, 101 semi-structured interviews, and five focal groups. In the results, we reconstruct the agro-productive and commercial vulnerabilities built up since 1960 and contextualize the health and hydrometeorological crisis to show how some 87% of households suffered severe consequences to their incomes. The prices of main products (maize, fruit, honey) reached historically low levels as a result of conditions within local markets during the crisis. Half of the households surveyed had to make use of savings and more than 60% received no support from government or from development agencies. We conclude by pointing out the need for accompanying the design and implementation of community mitigation plans, which should take as a starting point the recovery of knowledge and local organization in order to demand from government co-managed, preventive programs, and capacities that would enable communities to confront increasing negative consequences in situations of global climate change and market instabilities in local peasant contexts. Our study aims to reach policy-makers, social organizations, and communities in order to highlight the importance of developing joint capabilities to respond to growing environmental, economic, and health vulnerabilities.
The Getis-Ord G(i)* statistic clustering technique was used to create a hot spot exposure map using 14 potentially toxic elements (PTEs) found in urban dust samples in a semiarid city in northwest Mexico. The dust distribution and deposition in this city are influenced by the seasonal wind and rain from the North American Monsoon. The spatial clustering patterns of hot spots were used in combination with a sensitivity analysis to determine which variables most influenced the PTE hot spot exposure base map. The hot spots areas (%) were used as indicators of environmental vulnerability, and a final integrated map was selected to represent the highest vulnerability of PTEs with a 99% level of confidence. The results of the sensitivity analysis indicated that the flood zones and pervious and impervious zones were the most sensitive variables due to their weight in the spatial distribution. The hot spot areas were reduced by 60.4% by not considering these variables. The hot spot analysis resulted in an effective tool that allowed the combination of different spatial layers with specific characteristics to determine areas that present greater vulnerability to the distribution of PTEs, with impacts on public and environmental health.
Chagas disease, caused by the protozoa Trypanosoma cruzi, is an important yet neglected disease that represents a severe public health problem in the Americas. Although the alteration of natural habitats and climate change can favor the establishment of new transmission cycles for T. cruzi, the compound effect of human-modified landscapes and current climate change on the transmission dynamics of T. cruzi has until now received little attention. A better understanding of the relationship between these factors and T. cruzi presence is an important step towards finding ways to mitigate the future impact of this disease on human communities. Here, we assess how wild and domestic cycles of T. cruzi transmission are related to human-modified landscapes and climate conditions (LUCC-CC). Using a Bayesian datamining framework, we measured the correlations among the presence of T. cruzi transmission cycles (sylvatic, rural, and urban) and historical land use, land cover, and climate for the period 1985 to 2012. We then estimated the potential range changes of T. cruzi transmission cycles under future land-use and -cover change and climate change scenarios for 2050 and 2070 time-horizons, with respect to “green” (RCP 2.6), “business-as-usual” (RCP 4.5), and “worst-case” (RCP 8.5) scenarios, and four general circulation models. Our results show how sylvatic and domestic transmission cycles could have historically interacted through the potential exchange of wild triatomines (insect vectors of T. cruzi) and mammals carrying T. cruzi, due to the proximity of human settlements (urban and rural) to natural habitats. However, T. cruzi transmission cycles in recent times (i.e., 2011) have undergone a domiciliation process where several triatomines have colonized and adapted to human dwellings and domestic species (e.g., dogs and cats) that can be the main blood sources for these triatomines. Accordingly, Chagas disease could become an emerging health problem in urban areas. Projecting potential future range shifts of T. cruzi transmission cycles under LUCC-CC scenarios we found for RCP 2.6 no expansion of favourable conditions for the presence of T. cruzi transmission cycles. However, for RCP 4.5 and 8.5, a significant range expansion of T. cruzi could be expected. We conclude that if sustainable goals are reached by appropriate changes in socio-economic and development policies we can expect no increase in suitable habitats for T. cruzi transmission cycles.
With the aging of the human body, some physiological changes occur, compromising thermoregulatory mechanisms, negatively influencing the individual’s thermal sensation. Given this fact, the present study aimed to build a predictive model to determine the thermal sensation index for elderly people (TSIEP) in a hot climate region, considering their sensitivity in the perception of climate change in the city of Campina Grande, in the semi-arid region of Paraíba/Brazil. For this purpose, an observational study was carried out from April to December 2016 with elderly people inside their homes. The responses of the sample units (elderly people) to the categories of thermal sensation (hot, comfortable, and cold) were transformed into probit estimates, and, using the multivariate modeling statistical technique (canonical correlation), the TSIEP was determined. Finally, TSIEP showed that the thermal sensation of elderly people residing in Campina Grande tends to be more sensitive to cold and less sensitive to heat.
Haiti has experienced many major natural disasters in the past decade that included Hurricane Matthew which led to mass damage to property, a depletion of basic resources, human fatalities and injuries, and mental health consequences that affected the poorest. The current study focused on the psychological effects of Hurricane Matthew on Haitian children and adolescents. Children display heightened depression, and PTSD symptoms in the aftermath of disasters (Hausman et al., Journal of Family Psychology 34:836-845, 2020), however, the researchers anticipated that children living in orphanages would display more severe mental health symptoms than those living with their families, because of their additional stressor of family loss. Using a convenience sample, quantitative data was collected using several instruments, in a survey format, that were individually administered to a sample of 77 adolescents. Participants had high depressive scores and reported multiple adverse events and limited access to basic needs. In comparing subgroups, we found children who were in orphanages reported significantly fewer adverse childhood experiences than those living with their families. This is likely because orphanages in Haiti consistently provide children with a safe and stable environment, buffering them against the traumatic effects of disasters. In contrast, children living with their families reported witnessing or experiencing interpersonal violence, neglect and abuse in addition to disaster-related stress. Before addressing the issues faced by disaster-affected children in Haiti, the systemic issues that maintain the socio-economic deprivation of so many citizens must be addressed. An important step is for policymakers to collaborate with mental health providers to develop community interventions that are low-cost and easily accessible. These interventions must consider and incorporate the social context and cultural patterns of help-seeking and treatment utilization in Haiti.
Cerebrovascular diseases (CVD) are one of the leading causes of mortality globally. Air temperature is one of the risk factors for CVD; however, few studies have investigated the relationship between air temperature and mortality from these diseases in Brazil. This time series study investigated the relationship between air temperature and CVD mortality in 10 microregions located across Brazil’s five regions during the period 1996 to 2017 using mortality data from the national health information system, DATASUS and daily mean temperature data. The association between mean air temperature and mortality from CVD was measured using generalized additive models with Poisson distribution and relative and attributable risks were estimated together with 95% confidence intervals using distributed lag non-linear models and a 14-day lag. There were 531,733 deaths from CVD during the study period, 21,220 of which (11,138-30,546) were attributable to air temperature. Minimum mortality temperatures ranged from 20.1ºC in Curitiba to 29.6ºC in Belém. Associations between suboptimal air temperatures and increased risk of death from CVD were observed in all of Brazil’s five regions. Relative risk from the cold was highest in Manaus (RR 1.53; 1.22-1.91) and Campo Grande (RR 1.52; 1.18-1.94), while relative risk from heat was highest in Manaus (RR 1.75; 1.35-2.26) and Brasília (RR 1.36; 1.15-1.60).
BACKGROUND: Dengue fever is the most common arboviral disease in humans, with an estimated 50-100 million annual infections worldwide. Dengue fever cases have increased substantially in the past four decades, driven largely by anthropogenic factors including climate change. More than half the population of Peru is at risk of dengue infection and due to its geography, Peru is also particularly sensitive to the effects of El Niño Southern Oscillation (ENSO). Determining the effect of ENSO on the risk for dengue outbreaks is of particular public health relevance and may also be applicable to other Aedes-vectored viruses. METHODS: We conducted a time-series analysis at the level of the district-month, using surveillance data collected from January 2000 to September 2018 from all districts with a mean elevation suitable to survival of the mosquito vector (<2,500m), and ENSO and weather data from publicly-available datasets maintained by national and international agencies. We took a Bayesian hierarchical modeling approach to address correlation in space, and B-splines with four knots per year to address correlation in time. We furthermore conducted subgroup analyses by season and natural region. RESULTS: We detected a positive and significant effect of temperature (°C, RR 1.14, 95% CI 1.13, 1.15, adjusted for precipitation) and ENSO (ICEN index: RR 1.17, 95% CI 1.15, 1.20; ONI index: RR 1.04, 95% CI 1.02, 1.07) on outbreak risk, but no evidence of a strong effect for precipitation after adjustment for temperature. Both natural region and season were found to be significant effect modifiers of the ENSO-dengue effect, with the effect of ENSO being stronger in the summer and the Selva Alta and Costa regions, compared with winter and Selva Baja and Sierra regions. CONCLUSIONS: Our results provide strong evidence that temperature and ENSO have significant effects on dengue outbreaks in Peru, however these results interact with region and season, and are stronger for local ENSO impacts than remote ENSO impacts. These findings support optimization of a dengue early warning system based on local weather and climate monitoring, including where and when to deploy such a system and parameterization of ENSO events, and provide high-precision effect estimates for future climate and dengue modeling efforts.
Exposure to ambient temperature has been linked to adverse birth outcomes in several regions, including the USA, Australia, China, countries in the Middle East, and European countries. To date, no studies were performed in South America, a region with serious challenges related to climate change. Our investigation addresses this literature lack by examining the association between Low Birth Weight (LBW) and ambient temperature exposure in the largest county in South America, Brazil. We applied a nationwide case-control study design using a logistic regression model to estimate the odds ratio (OR) for LBW associated with ambient temperature during a specific trimester of pregnancy (1-3 trimester). Our sample size includes 5,790,713 birth records nationwide over 18 years (2001-2018), of which 264,967 infants were included in the model as cases of LBW, representing 4.6% of our total sample. We adjusted our model for several confounding variables, including weather factors, air pollution, seasonality, and SES variables at the individual level. Our findings indicate that North was the only region with positive and statistically significant associations in the primary analysis and most of the sensitivity analysis, which is the region where the Amazon is located. In this region, we estimated an increase of 5.16% (95%CI: 3.60; 6.74) in the odds of LBW per 1 °C increase in apparent temperature when the exposure occurred in the second trimester. Our results may be explained by the climate conditions in the Amazon region in the past years. A large body of literature indicates that the Amazon region has been facing serious climate challenges including issues related to policy, governance, and deforestation. Specifically, regarding deforestation, it is suggested that land use change and deforestation is projected to increase heat stress in the Amazon region, because of Amazon savannization, increasing the risk of heat stress exposure in Northern Brazil. Our study can assist public sectors and clinicians in mitigating the risk and vulnerability of the Amazonian population.
Leptospirosis is a serious public health problem in Brazil, which can be observed after flooding events. Using an exploratory mixed clustering method, this ecological study analyzes whether spatial-temporal clustering patterns of leptospirosis occur in Brazil. Data from the Brazilian Unified Health System (SUS) were used to calculate the prevalence of leptospirosis between 2007 and 2017 in all counties of the country. Clustering techniques, including spatial association indicators, were used for analysis and evaluation of disease yearly spatial distribution. Based on Local Indicators of Spatial Association (LISA) with Empirical Bayesian rates detected spatial patterns of leptospirosis ranging from 0.137 (p = 0.001 in 2009) to 0.293 (p = 0.001 in 2008). Over the whole period, the rate was 0.388 (p = 0.001). The main pattern showed permanence of leptospirosis clusters in the South and emergence and permanence of such clusters in northern Brazil. The municipalities with leptospirosis cases and at least one flood occurrence registered in the Brazilian Integrated Disaster Information System were incorporated into the LISA cluster map with Empirical Bayesian rates. These counties were expected to exhibit clustering, not all did. The results of the cluster analysis suggest allocation of health resources in areas with leptospirosis clustering.
BACKGROUND: The intensity of transmission of Aedes-borne viruses is heterogeneous, and multiple factors can contribute to variation at small spatial scales. Illuminating drivers of heterogeneity in prevalence over time and space would provide information for public health authorities. The objective of this study is to detect the spatiotemporal clusters and determine the risk factors of three major Aedes-borne diseases, Chikungunya virus (CHIKV), Dengue virus (DENV), and Zika virus (ZIKV) clusters in Mexico. METHODS: We present an integrated analysis of Aedes-borne diseases (ABDs), the local climate, and the socio-demographic profiles of 2469 municipalities in Mexico. We used SaTScan to detect spatial clusters and utilize the Pearson correlation coefficient, Randomized Dependence Coefficient, and SHapley Additive exPlanations to analyze the influence of socio-demographic and climatic factors on the prevalence of ABDs. We also compare six machine learning techniques, including XGBoost, decision tree, Support Vector Machine with Radial Basis Function kernel, K nearest neighbors, random forest, and neural network to predict risk factors of ABDs clusters. RESULTS: DENV is the most prevalent of the three diseases throughout Mexico, with nearly 60.6% of the municipalities reported having DENV cases. For some spatiotemporal clusters, the influence of socio-economic attributes is larger than the influence of climate attributes for predicting the prevalence of ABDs. XGBoost performs the best in terms of precision-measure for ABDs prevalence. CONCLUSIONS: Both socio-demographic and climatic factors influence ABDs transmission in different regions of Mexico. Future studies should build predictive models supporting early warning systems to anticipate the time and location of ABDs outbreaks and determine the stand-alone influence of individual risk factors and establish causal mechanisms.
Air pollution is one of the foremost environmental threats to human health. However, the meteorological and social factors that lead to respiratory and cardiovascular diseases have not been fully elucidated. In this study, we use Principal Component Analysis and Generalized Linear Model (PCA-GLM) to investigate the combined effect of socioeconomic development and air pollution on cardiorespiratory hospitalization in southern Brazil. This region has the highest rates of hospitalization by cardiorespiratory diseases in the country. We analyze three main sources of data: (i) air pollutants density from TROPOMI/Sentinel-5p satellite; (ii) temperature, humidity, and planetary boundary layer height (PBLH) modeled with the Weather Research Forecast model; and (iii) hospitalization by cardiorespiratory diseases obtained from the Brazilian National Health System. We estimate the Relative Risk (RR) using the PCA-GLM coefficients and interquartile variations of air pollutants density and meteorological parameters. Our results show that the population living in colder and drier municipalities is more prone to cardiorespiratory hospitalization. Regarding respiratory hospitalization, municipalities with lower socioeconomic development are more sensitive to meteorology and pollution variability than highly developed ones. In less developed municipalities, we observe the highest rates of cardiorespiratory hospitalization even if air pollution is low, which we interpret in terms of higher vulnerability. The RR analysis suggests that air pollution is an important environmental risk to cardiovascular diseases and respiratory diseases is more sensitive to air pollution and meteorology than cardiovascular ones. Our findings corroborate the mounting evidence that social vulnerability is a significant factor affecting the increase of cardiorespiratory hospitalization in the world.
The Zika virus (ZIKV) epidemic, which was followed by an unprecedented outbreak of congenital microcephaly, emerged in Brazil unevenly, with apparent pockets of susceptibility. The present study aimed to detect high-risk areas for ZIKV infection and microcephaly in Goiania, a large city of 1.5 million inhabitants in Central-West Brazil. Using geocoded surveillance data from the Brazilian Information System for Notifiable Diseases (SINAN) and from the Public Health Event Registry (RESP-microcefalia), we analyzed the spatiotemporal distribution and socioeconomic indicators of laboratory confirmed (RT-PCR and/or anti-ZIKV IgM ELISA) symptomatic ZIKV infections among pregnant women and clinically confirmed microcephaly in neonates, from 2016 to 2020. We investigated temporal patterns by estimating the risk of symptomatic maternal ZIKV infections and microcephaly per 1000 live births per month. We examined the spatial distribution of maternal ZIKV infections and microcephaly cases across the 63 subdistricts of Goiania by manually plotting the geographical coordinates. We used spatial scan statistics estimated by discrete Poisson models to detect high clusters of maternal ZIKV infection and microcephaly and compared the distributions by socioeconomic indicators measured at the subdistrict level. In total, 382 lab-confirmed cases of maternal ZIKV infections, and 31 cases of microcephaly were registered in the city of Goiania. More than 90% of maternal cases were reported between 2016 and 2017. The highest incidence of ZIKV cases among pregnant women occurred between February and April 2016. A similar pattern was observed in the following year, although with a lower number of cases, indicating seasonality for ZIKV infection, during the local rainy season. Most congenital microcephaly cases occurred with a time-lag of 6 to 7 months after the peak of maternal ZIKV infection. The highest estimated incidence of maternal ZIKV infections and microcephaly were 39.3 and 2.5 cases per 1000 livebirths, respectively. Districts with better socioeconomic indicators and with higher proportions of self-identified white inhabitants were associated with lower risks of maternal ZIKV infection. Overall, the findings indicate heterogeneity in the spatiotemporal patterns of maternal ZIKV infections and microcephaly, which were correlated with seasonality and included a high-risk geographic cluster. Our findings identified geographically and socio-economically underprivileged groups that would benefit from targeted interventions to reduce exposure to vector-borne infections. Author summaryThe first wave of Zika virus (ZIKV) epidemic and its Congenital Zika Syndrome, has vanished. However, the consequences have remained for the affected children and families ever since.In Brazil, the first cases of microcephaly, detected in the end of 2015 in the Northeast region, especially in coastal cities, quickly spread to other regions and cities in countryside of Brazil. Understanding the temporal and spatial dynamics of cases distribution is essential to identify areas of greater risk and enable preparedness for a future wave of cases.In this study, we analyzed the spatiotemporal distribution of cases of ZIKV infection in pregnant women and cases of microcephaly in newborns by district, over a five-year period, in a large city in Midwest Brazil. Additionally, cases of microcephaly were correlated with the socioeconomic and structural conditions at the local level.Our findings indicate heterogeneity in the spatiotemporal patterns of maternal ZIKV infections and microcephaly, which were correlated with seasonality and included a persistent high-risk geographic location (cluster) in the city of Goiania. We could identify geographically and socio-economically underprivileged groups, with higher risk for ZIKV infection, that would benefit from targeted interventions to reduce exposure to new vector borne infections.
To assess mortality risks and burdens associated with short-term exposure to wildfire-related fine particulate matter with diameter ≤ 2.5 μm (PM(2.5)), we collect daily mortality data from 2000 to 2016 for 510 immediate regions in Brazil, the most wildfire-prone area. We integrate data from multiple sources with a chemical transport model at the global scale to isolate daily concentrations of wildfire-related PM(2.5) at a 0.25 × 0.25 resolution. With a two-stage time-series approach, we estimate (i) an increase of 3.1% (95% confidence interval [CI]: 2.4, 3.9%) in all-cause mortality, 2.6% (95%CI: 1.5, 3.8%) in cardiovascular mortality, and 7.7% (95%CI: 5.9, 9.5) in respiratory mortality over 0-14 days with each 10 μg/m(3) increase in daily wildfire-related PM(2.5); (ii) 0.65% of all-cause, 0.56% of cardiovascular, and 1.60% of respiratory mortality attributable to acute exposure to wildfire-related PM(2.5), corresponding to 121,351 all-cause deaths, 29,510 cardiovascular deaths, and 31,287 respiratory deaths during the study period. In this study, we find stronger associations in females and adults aged ≥ 60 years, and geographic difference in the mortality risks and burdens.
Child-centred disaster risk reduction aims to reduce child vulnerability and increase resilience to disasters. The 2015 Comprehensive School Safety Framework (CSSF) sought to decrease hazard risks to education. Between 2015 and 2017, Dominica was struck by Tropical Storm Erika and Hurricane Maria, which significantly affected the education system at the local and national scales. Since Maria, a couple of national initiatives (Safer Schools and Smart Schools) have been introduced to increase resilience and meet the CSSF’s objectives. This paper assesses progress made through a qualitative analysis of interviews with 29 school leaders, government officials, and disaster risk reduction stakeholders. Implementation of the climate resilience programme in 2018 resulted in nationwide teacher training and production of school disaster plans. Limited successes have improved social resilience, but short-term implementation due to COVID-19 and a lack of a teacher knowledge base have presented challenges to the scheme’s long-term sustainability and the implementation of the CSSF’s goals.
Arbovirus infections, such as dengue, zika, chikungunya, and yellow fever, are a major public health problem worldwide. As the main vectors, mosquitoes have been classified by the Center for Disease Control and Prevention as one of the deadliest animals alive. In this ecological study, we analyzed the population dynamics of important genera and species of mosquito vectors. Mosquito immatures were collected using ovitraps and at natural breeding sites: bamboos and bromeliads. Adult mosquitoes were captured using CDC traps with CO(2), Shannon traps, and manual suction tubes. Collections took place during the rainy and dry seasons from 2019 to 2020 in the Serra dos Órgãos National Park, Rio de Janeiro state, Brazil. The highest number of species was recorded in the ovitraps, followed by CDC and bromeliads. The breeding site with the lowest diversity was bamboo, though it showed the highest level of evenness compared to the other breeding sites. The medically important genera reported were Haemagogus spp., Aedes spp., Culex spp., and Wyeomyia spp. Culicid eggs increased in the rainy season, with a peak in November 2019 and January and February 2020, and lower abundance in the dry season, from September to October 2019. Mosquito eggs had a strong positive correlation (ρ = 0.755) with temperature and a moderate positive correlation (ρ = 0.625) with rainfall. This study shows how environmental variables can influence the ecology of disease-vector mosquitoes, which are critical in the maintenance of arbovirus circulation in a threatened biome within the most densely populated region of Brazil.
BACKGROUND: The 2017-2018 yellow fever virus (YFV) outbreak in southeastern Brazil marked a reemergence of YFV in urban states that had been YFV-free for nearly a century. Unlike earlier urban YFV transmission, this epidemic was driven by forest mosquitoes. The objective of this study was to evaluate environmental drivers of this outbreak. METHODOLOGY/PRINCIPAL FINDINGS: Using surveillance data from the Brazilian Ministry of Health on human and non-human primate (NHP) cases of YFV, we traced the spatiotemporal progression of the outbreak. We then assessed the epidemic timing in relation to drought using a monthly Standardized Precipitation Evapotranspiration Index (SPEI) and evaluated demographic risk factors for rural or outdoor exposure amongst YFV cases. Finally, we developed a mechanistic framework to map the relationship between drought and YFV. Both human and NHP cases were first identified in a hot, dry, rural area in northern Minas Gerais before spreading southeast into the more cool, wet urban states. Outbreaks coincided with drought in all four southeastern states of Brazil and an extreme drought in Minas Gerais. Confirmed YFV cases had an increased odds of being male (OR 2.6; 95% CI 2.2-3.0), working age (OR: 1.8; 95% CI: 1.5-2.1), and reporting any recent travel (OR: 2.8; 95% CI: 2.3-3.3). Based on this data as well as mosquito and non-human primate biology, we created the “Mono-DrY” mechanistic framework showing how an unusual drought in this region could have amplified YFV transmission at the rural-urban interface and sparked the spread of this epidemic. CONCLUSIONS/SIGNIFICANCE: The 2017-2018 YFV epidemic in Brazil originated in hot, dry rural areas of Minas Gerais before expanding south into urban centers. An unusually severe drought in this region may have created environmental pressures that sparked the reemergence of YFV in Brazil’s southeastern cities.
This work aims to analyze the relationship between meteorological conditions and the occurrence of hospital admissions for pneumonia in children under 5 years of age in the Metropolitan Region of Porto Alegre, Brazil, from 1998 to 2017. To this end, data from hospital admissions obtained from the Unified Health System database (DATASUS) were used and classified into two groups: acute respiratory infections (ARI) and asthma, according to the international classification of diseases, tenth edition (ICD-10). Data regarding meteorological variables were also used: temperature, relative humidity, atmospheric pressure and wind speed, at 12Z and 18Z, as well as the Thermal Comfort Index (TCI), Effective Temperature as a function of the wind (ETw) and Windchill (W). From the data obtained, a descriptive analysis of the diseases and a statistical analysis with the analysis of correlation and main components were performed. Results showed that pneumonia (catalogued in the ICD-10 as J12 to J18) was the main cause of hospitalizations in children. The annual, monthly and daily hospitalization frequency distributions showed higher rates of admissions occurring in the months of May to September. The peaks of admissions and high admissions (HA) occurred mainly in the winter months (June, July and August), and in 1998. Meanwhile, the correlation and principal component analysis showed an increase in hospital admissions due to pneumonia related to a decrease in temperature and ETw and W indices (negative anomalies) and an increase in atmospheric pressure and relative humidity (positive anomalies).
The burden of arbovirus diseases in Brazil has increased within the past decade due to the emergence of chikungunya and Zika and endemic circulation of all four dengue serotypes. Changes in temperature and rainfall patterns may alter conditions to favor vector-host transmission and allow for cyclic re-emergence of disease. We sought to determine the impact of climate conditions on arbovirus co-circulation in Rio de Janeiro, Brazil. We assessed the spatial and temporal distributions of chikungunya, dengue, and Zika cases from Brazil’s national notifiable disease information system (SINAN) and created autoregressive integrated moving average models (ARIMA) to predict arbovirus incidence accounting for the lagged effect of temperature and rainfall. Each year, we estimate that the combined arboviruses were associated with an average of 8429 to 10,047 lost Disability-Adjusted Life Years (DALYs). After controlling for temperature and precipitation, our model predicted a three cycle pattern where large arbovirus outbreaks appear to be primed by a smaller scale surge and followed by a lull of cases. These dynamic arbovirus patterns in Rio de Janeiro support a mechanism of susceptibility enhancement until the theoretical threshold of population immunity allows for temporary cross protection among certain arboviruses. This suspected synergy presents a major public health challenge due to overlapping locations and seasonality of arbovirus diseases, which may perpetuate disease burden and overwhelm the health system.
Climate change is increasing the severity of extreme weather events, particularly hurricanes, presenting a significant challenge to Caribbean coastal communities. In the aftermath of a major disaster, government interventions typically prioritise infrastructure, assets, and the economy through rebuilding roads, reviving economic sectors, and providing financial compensation. This is driven by a focus on macro-level quantitative indicators rather than by local, multidimensional subjective and relational factors, closer to lived experiences and livelihoods. Using frameworks outlining social well-being and agency, this paper explores strategies used by a fisheries-dependent community in Dominica to recover from Hurricane Maria in 2017 and pursue well-being. The findings highlight the importance of multidimensional well-being, particularly relational and subjective dimensions, including existing social networks, and personal relationships critical for recovery after Maria. Furthermore, the paper demonstrates how recovery initiatives that concentrate solely on material well-being, such as employment, can undermine agency in the capacity of a community to recover and build resilience.
Oropouche virus (OROV) is an emerging vector-borne arbovirus with high epidemic potential, causing illness in more than 500,000 people. Primarily contracted through its midge and mosquito vectors, OROV remains prevalent in its wild, non-human primate and sloth reservoir hosts as well. This virus is spreading across Latin America; however, the majority of cases occur in Brazil. The aim of this research is to document OROV’s presence in Brazil using the One Health approach and geospatial techniques. A scoping review of the literature (2000 to 2021) was conducted to collect reports of this disease in humans and animal species. Data were then geocoded by first and second subnational levels and species to map OROV’s spread. In total, 14 of 27 states reported OROV presence across 67 municipalities (second subnational level). However, most of the cases were in the northern region, within the tropical and subtropical moist broadleaf forests biome. OROV was identified in humans, four vector species, four genera of non-human primates, one sloth species, and others. Utilizing One Health was important to understand the distribution of OROV across several species and to suggest possible environmental, socioeconomic, and demographic drivers of the virus’s presence. As deforestation, climate change, and migration rates increase, further study into the spillover potential of this disease is needed.
Southern Brazil concentrates a considerable number of cases of cutaneous leishmaniasis reported since 1980, and Paraná is the state that most records CL cases in the region. The main sand fly species incriminated as vectors of Leishmania (Viannia) braziliensis (Vianna,1911) are Migonemyia (Migonemyia) migonei (França, 1920), Nyssomyia (Nyssomyia) neivai (Pinto, 1926) and Nyssomyia (Nyssomyia) whitmani (Antunes & Coutinho, 1936). In this study, we evaluated areas with climatic suitability for the distribution of these vectors and correlated these data with CL incidence in the state. The occurrence points of Mg. migonei, Ny. neivai, and Ny. whitmani were extracted from a literature review and field data. For CL analysis in the state of Paraná, data were obtained from the Informatics Department of the Unified Health System of Brazil (DATASUS), covering the period from 2001 to 2019. The layers of bioclimatic variables from the WorldClim database were used in the study. Species distribution modeling was developed using the MaxEnt Software version 3.4.4. ArcGIS software version 10.5 was used to develop suitability maps and the graphical representation of disease incidence. The AUC values were acceptable for all models (> 0,8). Bioclimatic variables BIO13 and BIO14 were the most influential in the distribution of Mg. migonei, while BIO19 and BIO6 were the variables that most influenced the distribution of Ny. neivai, and Ny. whitmani was most influenced by variables BIO5 and BIO9. During 19 years, 4992 cases of CL were reported in the state by 286 municipalities (71,6%). Northern Paraná showed the highest number of areas with very high and high climatic suitability for the occurrence of these species, coinciding with the highest number of CL cases. The modeling tools allowed analyzing the association between climatic variables and the geographical distribution of CL in the state. Moreover, they provided a better understanding of the climatic conditions related to the distribution of different species, favoring the monitoring of risk areas, the implementation of preventive measures, risk awareness, early and accurate diagnosis, and consequent timely treatment.
Progressive changes in local environmental scenarios, accelerated by global climate change, can negatively affect the mental health of people who inhabit these areas. The magnitude of these effects may vary depending on the socioeconomic conditions of people and the characteristics of the environment, so certain territories can be more vulnerable than others. In this context, the present study aimed to geographically analyse the levels of psychosocial impact and the types of disruptive responses related to the new territorial scenarios caused by climate change in the coastal drylands of the Maule region, Chile. For this purpose, 223 people from two communes (Curepto and Pencahue) were psychosocially evaluated for post-traumatic stress disorder (PTSD) together with a survey of the prevailing sociodemographic and socioeconomic conditions in relation to the environmental variables of the territory. All information was georeferenced, stored within an ArcGIS Desktop geographic information system (GIS) and then investigated by application of contingency tables, ANOVA and local clustering analysis using SSP statistical software. The results indicated a high level of PTSD in the population, with significant differences related to age and education as well as employment conditions and income. The spatial results showed high PTSD values in the communal capital of Curepto in the central agricultural valley near the estuary of the local river, while the existence of coldspots was observed in the central valley of the Pencahue commune. It was concluded that proximity to population centres and surface water sources played the greatest role for the development of PTSD.
Dipetalogaster maxima is a primary vector of Chagas disease in the Cape region of Baja California Sur, Mexico. The geographic distribution of D. maxima is limited to this small region of the Baja California Peninsula in Mexico. Our study aimed to construct the ecological niche models (ENMs) of this understudied vector species and the parasite responsible for Chagas disease (Trypanosoma cruzi). We modelled the ecological niches of both species under current and future climate change projections in 2050 using four Representative Concentration Pathways (RCPs): RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5. We also assessed the human population at risk of exposure to D. maxima bites, the hypothesis of ecological niche equivalency and similarity between D. maxima and T. cruzi, and finally the abundance centroid hypothesis. The ENM predicted a higher overlap between both species in the Western and Southern coastal regions of the Baja California Peninsula. The climate change scenarios predicted a Northern shift in the ecological niche of both species. Our findings suggested that the highly tourist destination of Los Cabos is a high-risk zone for Chagas disease circulation. Overall, the study provides valuable data to vector surveillance and control programs.
The presence, abundance, and distribution of sandflies are strongly influenced by climate and environmental changes. This study aimed to describe the sandfly fauna in an intense transmission area for visceral leishmaniasis and to evaluate the association between the abundance of Lutzomyia longipalpis sensu lato (Lutz & Neiva 1912) (Diptera: Psychodidae) and climatic variables. Captures were carried out 2 yr (July 2017 to June 2019) with automatic light traps in 16 sites of the urban area of Campo Grande, Mato Grosso do Sul state. The temperature (°C), relative humidity (%), precipitation (mm3), and wind speed (km/h) were obtained by a public domain database. The Wilcoxon test compared the absolute frequencies of the species by sex. The association between climatic variables and the absolute frequency of Lu. longipalpis s.l. was assessed using the Spearman’s correlation coefficient. A total of 1,572 sandflies into four species were captured. Lutzomyia longipalpis s.l. was the most abundant species and presented a significant correlation with the average temperature, humidity, and wind speed in different periods. Lutzomyia longipalpis s.l. was captured in all months, showing its plasticity in diverse weather conditions. We emphasize the importance of regular monitoring of vectors and human and canine cases, providing data for surveillance and control actions to continue to be carried out in the municipality.
INTRODUCTION: Cholera remains a significant public health threat for many countries, and the severity largely varies by the population and local conditions that drive disease spread, especially in endemic areas prone to natural disasters and flooding. Epidemiological models can provide useful information to military planners for understanding disease spread within populations and the effectiveness of response options for preventing the transmission among deployed and stationed personnel. This study demonstrates the use of epidemiological modeling to understand the dynamics of cholera transmission to inform emergency planning and military preparedness in areas with highly communicable diseases. MATERIALS AND METHODS: Areas with higher probability for a potential cholera outbreak in Haiti followed by a natural disaster were identified. The hotspots were then used to seed an extended compartmental model, EpiGrid, to simulate notional spread scenarios of cholera originating in three distinct areas in Haiti. Disease parameters were derived from the 2010 cholera outbreak in Haiti, and disease spread was simulated over a 12-week period under uncontrolled and controlled spread. RESULTS: For each model location, scenarios of mitigated (intervention with 30% transmission reduction via international aid) and unmitigated (without intervention) are simulated. The results depict the geographical spread and estimate the cumulative cholera infection for each notional scenario over the course of 3 months. Disease transmission differs considerably across origin site with an outbreak originating in the department of Nippes spanning the largest geographic area and resulting in the largest number of cumulative cases after 12 weeks under unmitigated (79,518 cases) and mitigated (35,667 cases) spread scenarios. CONCLUSIONS: We modeled the notional re-emergence and spread of cholera following the August 2021 earthquake in Haiti while in the midst of the global COVID-19 pandemic. This information can help guide military and emergency response decision-making during an infectious disease outbreak and considerations for protecting military personnel in the midst of a humanitarian response. Military planners should consider the use of epidemiological models to assess the health risk posed to deployed and stationed personnel in high-risk areas.
BACKGROUND: Since climate change, pandemics and population mobility are challenging healthcare systems, an empirical and integrative research to studying and help improving the health systems resilience is needed. We present an interdisciplinary and mixed-methods research protocol, ClimHB, focusing on vulnerable localities in Bangladesh and Haiti, two countries highly sensitive to global changes. We develop a protocol studying the resilience of the healthcare system at multiple levels in the context of climate change and variability, population mobility and the Covid-19 pandemic, both from an institutional and community perspective. METHODS: The conceptual framework designed is based on a combination of Levesque’s Health Access Framework and the Foreign, Commonwealth and Development Office’s Resilience Framework to address both outputs and the processes of resilience of healthcare systems. It uses a mixed-method sequential exploratory research design combining multi-sites and longitudinal approaches. Forty clusters spread over four sites will be studied to understand the importance of context, involving more than 40 healthcare service providers and 2000 households to be surveyed. We will collect primary data through questionnaires, in-depth and semi-structured interviews, focus groups and participatory filming. We will also use secondary data on environmental events sensitive to climate change and potential health risks, healthcare providers’ functioning and organisation. Statistical analyses will include event-history analyses, development of composite indices, multilevel modelling and spatial analyses. DISCUSSION: This research will generate inter-disciplinary evidence and thus, through knowledge transfer activities, contribute to research on low and middle-income countries (LMIC) health systems and global changes and will better inform decision-makers and populations.
Recent work by Kephart et al.(1) updates estimates for mortality burden attributable to non-optimal ambient temperatures in Latin America, which helps to understand the climate-related health risks and burden in less-developed areas. Here, we discuss the main findings and focus on methodology that remains controversial in heat health field.
This review article assesses evidences published in the past two years on the links among slow-onset events, food security and poverty as well as the strategies focused on reducing specific problems, those implemented in the countries of the Latin America and the Caribbean (LAC) region. It is here, where slow-onset events related to Climate Change pose significant challenges intricately linked to poverty and food security; mainly as a result of a great economic and social dependence, strongly conditioned by environmental factors. In this study, the authors include the main adaptive strategies they found in the literature reviewed: water improvement as a primary adaptive strategy for agriculture, apart from the ones that use geographic information systems technologies for monitoring vulnerable areas, diversification of cultures, adoption of agroecological practices, reduction of the gender gap in land governance, and implementation of educational strategies.
BACKGROUND: Collective risk factors such as climate and pollution impact on the risk of acute cardiovascular events, including ST-elevation myocardial infarction (STEMI). There is limited data however on the precise temporal and independent association between these factors and STEMI, and the potentially interacting role of government policies against Coronavrus Disease 2019 (COVID-19), especially for Latin America. METHODS: We retrospectively collected aggregate data on daily STEMI admissions at 10 tertiary care centers in the Buenos Aires metropolitan area, Argentina, from January 1, 2017 to November 30, 2020. Daily measurements for temperature, humidity, atmospheric pressure, wind direction, wind speed, and rainfall, as well as carbon monoxide (CO), nitrogen dioxide, and particulate matter <10 μm (PM10), were retrieved. Exploratory analyses focused on key COVID-19-related periods (eg first case, first lockdown), and stringency index quantifying the intensity of government policy response against COVID-19. RESULTS: A total of 1498 STEMI occurred over 1430 days, for an average of 0.12 STEMI per center (decreasing from 0.130 in 2018 to 0.102 in 2020, p=0.016). Time series analysis showed that lower temperature and higher concentration of CO and PM10 were all significantly associated with an increased rate of STEMI (all p<0.05), whereas COVID-19 outbreak, lockdown, and stringency of government policies were all inversely associated with STEMI (all p<0.05). Notably, environmental features impacted as early as 28 days before the event (all p<0.05), even if same or prior day associations proved stronger (all p<0.05). Multivariable analysis suggested that maximum temperature (p=0.001) and PM10 (p=0.033) were the strongest predictor of STEMI, even after accounting for COVID-19-related countermeasures (p=0.043). CONCLUSIONS: Lower temperature and higher concentrations of CO and PM10 are associated with significant increases in the rate of STEMI in a large Latin American metropolitan area. The reduction in STEMI cases seen during the COVID-19 pandemic is at least in part mediated by improvements in pollution, especially reductions in PM10.
The presented work analyzes the energy prices, climate shock, and health deprivation nexus in the BRICS economies for the period 1995-2020. Panel ARDL-PMG technique is used to reveal the underexplored linkages. The long-run estimates of energy prices are observed to be negatively significant to the health expenditure and life expectancy model, whereas, positively significant to the climate change model. These findings suggest that energy prices significantly reduce health expenditures and life expectancy and, thus, increase the death rate in the BRICS economies. The long-run country-wise estimate of energy prices is found negatively significant in case of Brazil, India, China, and South Africa. Alongside, the group-wise significance of CO2 emissions is discovered to be negatively, positively, and insignificant in the cases of life expectancy, death rate, and health expenditure models, respectively. Besides, country-wise long-run estimate of CO2 emissions witnesses negative significance for Russia, India, China, and South Africa.
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.
BACKGROUND: With the current climate change crisis and its influence on infectious disease transmission there is an increased desire to understand its impact on infectious diseases globally. Hantaviruses are found worldwide, causing infectious diseases such as haemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS)/hantavirus pulmonary syndrome (HPS) in tropical regions such as Latin America and the Caribbean (LAC). These regions are inherently vulnerable to climate change impacts, infectious disease outbreaks and natural disasters. Hantaviruses are zoonotic viruses present in multiple rodent hosts resident in Neotropical ecosystems within LAC and are involved in hantavirus transmission. METHODS: We conducted a systematic review to assess the association of climatic factors with human hantavirus infections in the LAC region. Literature searches were conducted on MEDLINE and Web of Science databases for published studies according to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) criteria. The inclusion criteria included at least eight human hantavirus cases, at least one climatic factor and study from > 1 LAC geographical location. RESULTS: In total, 383 papers were identified within the search criteria, but 13 studies met the inclusion criteria ranging from Brazil, Chile, Argentina, Bolivia and Panama in Latin America and a single study from Barbados in the Caribbean. Multiple mathematical models were utilized in the selected studies with varying power to generate robust risk and case estimates of human hantavirus infections linked to climatic factors. Strong evidence of hantavirus disease association with precipitation and habitat type factors were observed, but mixed evidence was observed for temperature and humidity. CONCLUSIONS: The interaction of climate and hantavirus diseases in LAC is likely complex due to the unknown identity of all vertebrate host reservoirs, circulation of multiple hantavirus strains, agricultural practices, climatic changes and challenged public health systems. There is an increasing need for more detailed systematic research on the influence of climate and other co-related social, abiotic, and biotic factors on infectious diseases in LAC to understand the complexity of vector-borne disease transmission in the Neotropics.
OBJECTIVE: Analyze the incorporation of climate change and environmental health courses in the curriculum grids of Medicine, Nursing, Nutrition and Clinical Psychology undergraduate courses in Latin American universities. METHODS: Descriptive and cross-sectional document review. Curriculum grids of the top ten Latin American universities were analyzed according to the rankings of QS Latin American University 2020, Times Higher Education World University 2020 and Academic Ranking of World Universities 2019. The presence of courses related to climate change and environmental health was sought in each curriculum grid. RESULTS: 104 of the 161 universities included in the study offered Medicine courses, 93 Nursing courses, 77 Nutrition courses and 118 Clinical Psychology courses. Most of the curriculum grids incorporated courses in public health and/or epidemiology (more than 70%); however, between 22% and 41% included courses on environmental health, and only one curriculum grid had a course on climate change in Medicine and Nursing (1%). CONCLUSIONS: Courses on climate change and environmental health have been scarcely introduced in the curriculum grids of the health field in Latin American universities. This could weaken the important role that health professionals play in providing health care to the population.
BACKGROUND: The application of molecular diagnostics has identified enteric group adenovirus serotypes 40 and 41 as important causes of diarrhea in children. However, many aspects of the epidemiology of adenovirus 40/41 diarrhea have not been described. METHODS: We used data from the 8-site Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development Project birth cohort study to describe site- and age-specific incidence, risk factors, clinical characteristics, and seasonality. RESULTS: The incidence of adenovirus 40/41 diarrhea was substantially higher by quantitative polymerase chain reaction than enzyme immunoassay and peaked at ∼30 episodes per 100 child-years in children aged 7-15 months, with substantial variation in incidence between sites. A significant burden was also seen in children 0-6 months of age, higher than other viral etiologies with the exception of rotavirus. Children with adenovirus 40/41 diarrhea were more likely to have a fever than children with norovirus, sapovirus, and astrovirus (adjusted odds ratio [aOR], 1.62; 95% CI, 1.16-2.26) but less likely than children with rotavirus (aOR, 0.66; 95% CI, 0.49-0.91). Exclusive breastfeeding was strongly protective against adenovirus 40/41 diarrhea (hazard ratio, 0.64; 95% CI, 0.48-0.85), but no other risk factors were identified. The seasonality of adenovirus 40/41 diarrhea varied substantially between sites and did not have clear associations with seasonal variations in temperature or rainfall. CONCLUSIONS: This study supports the situation of adenovirus 40/41 as a pathogen of substantial importance, especially in infants. Fever was a distinguishing characteristic in comparison to other nonrotavirus viral etiologies, and promotion of exclusive breastfeeding may reduce the high observed burden in the first 6 months of life.
CONTEXT: Tropical areas and small islands are identified as highly vulnerable to climate change, and already experiencing shifts in their temperature distribution. However, the knowledge on the health impacts of temperatures under tropical marine climate is limited. We explored the influence of temperature on mortality in four French overseas regions located in French Guiana, French West Indies, and in the Indian Ocean, between 2000 and 2015. METHOD: Distributed lag non-linear generalized models linking temperature and mortality were developed in each area, and relative risks were combined through a meta-analysis. Models were used to estimate the fraction of mortality attributable to non-optimal temperatures. The role of humidity was also investigated. RESULTS: An increased risk of mortality was observed when the temperature deviated from median. Results were not modified when introducing humidity. Between 2000 and 2015, 979 deaths [confidence interval (CI) 95% 531:1359] were attributable to temperatures higher than the 90th percentile of the temperature distribution, and 442 [CI 95% 178:667] to temperature lower than the 10th percentile. DISCUSSION: Heat already has a large impact on mortality in the French overseas regions. Results suggest that adaptation to heat is relevant under tropical marine climate.
Stillbirths and complications from preterm birth are two of the leading causes of neonatal deaths across the globe. Lower- to middle-income countries (LMICs) are experiencing some of the highest rates of these adverse birth outcomes. Research has suggested that environmental determinants, such as extreme heat, can increase the risk of preterm birth and stillbirth. Under climate change, extreme heat events have become more severe and frequent and are occurring in differential seasonal patterns. Little is known about how extreme heat affects the risk of preterm birth and stillbirth in LMICs. Thus, it is imperative to examine how exposure to extreme heat affects adverse birth outcomes in regions with some of the highest rates of preterm and stillbirths. Most of the evidence linking extreme heat and adverse birth outcomes has been generated from high-income countries (HICs) notably because measuring temperature in LMICs has proven challenging due to the scarcity of ground monitors. The paucity of health data has been an additional obstacle to study this relationship in LMICs. In this study, globally gridded meteorological data was linked with spatially and temporally resolved Demographic and Health Surveys (DHS) data on adverse birth outcomes. A global analysis of 14 LMICs was conducted per a pooled time-stratified case-crossover design with distributed-lag nonlinear models to ascertain the relationship between acute exposure to extreme heat and PTB and stillbirths. We notably found that experiencing higher maximum temperatures and smaller diurnal temperature range during the last week before birth increased the risk of preterm birth and stillbirth. This study is the first global assessment of extreme heat events and adverse birth outcomes and builds the evidence base for LMICs.
In this eight-year retrospective study, we evaluated the associations between climatic variations and the biological rhythms in plasma lipids and lipoproteins in a large population of Campinas, São Paulo state, Brazil, as well as temporal changes of outcomes of cardiovascular hospitalizations. Climatic variables were obtained at the Center for Meteorological and Climatic Research Applied to Agriculture (University of Campinas – Unicamp, Brazil). The plasma lipid databases surveyed were from 27,543 individuals who had their lipid profiles assessed at the state university referral hospital in Campinas (Unicamp). The frequency of hospitalizations was obtained from the Brazilian Public Health database (DATASUS). Temporal statistical analyses were performed using the methods Cosinor or Friedman (ARIMA) and the temporal series were compared by cross-correlation functions. In normolipidemic cases (n=11,892), significantly different rhythmicity was observed in low-density lipoprotein (LDL)- and high-density lipoprotein (HDL)-cholesterol (C) both higher in winter and lower in summer. Dyslipidemia (n=15,651) increased the number and amplitude of lipid rhythms: LDL-C and HDL-C were higher in winter and lower in summer, and the opposite occurred with triglycerides. The number of hospitalizations showed maximum and minimum frequencies in winter and in summer, respectively. A coincident rhythmicity was observed of lower temperature and humidity rates with higher plasma LDL-C, and their temporal series were inversely cross-correlated. This study shows for the first time that variations of temperature, humidity, and daylight length were strongly associated with LDL-C and HDL-C seasonality, but moderately to lowly associated with rhythmicity of atherosclerotic outcomes. It also indicates unfavorable cardiovascular-related changes during wintertime.
Introduction: Planetary health (PH) has emerged as a leading field for raising awareness, debating, and finding solutions for the health impacts of human-caused disruptions to Earth’s natural systems. PH education addresses essential questions of how humanity inhabits Earth, and how humans affect, and are affected by, natural systems. A pilot massive open online course (MOOC) in PH was created in Brazil in 2020. This MOOC capitalized on the global online pivot, to make the course accessible to a broader audience. This study describes the process of course creation and development and assesses the impact evaluation data and student outcomes of the PH MOOC. Methods: The PH MOOC pilot was launched in Brazilian Portuguese, using the Telessa??deRS-UFRGS platform on 4/27/2020 and concluded on 7/19/2020 with a total load of 80 h. It was composed of 8 content modules, pre and post-test, 10 topics in a forum discussion, and an optional action plan. This study analyzes the course database, profile of participants, answers to questionnaires, forum interaction, and action plans submitted. Results: Two thousand seven hundred seventy-seven participants enrolled in the course, of which 1,237 (44.54%) gave informed consent for this study. Of the 1,237 participants who agreed to participate in the research, 614 (49.8%) completed the course, and 569 (92.67%) were accredited by Telessa??deRS-UFRGS. The majority of the participants were concerned with climate change, trained in the health area, and worked in primary health care in places that lacked ongoing sustainability programs. Two hundred forty-one action plans were submitted, major topics identified were food and nutrition, infectious diseases, and garbage and recycling. Discussion: The use of the PH lens and open perspective of the course centered the need to communicate planetary health topics to individuals. The local plans reflected the motto of think global and act local. Brazil presents a context of an unprecedented social, political, and environmental crisis, with massive deforestation, extensive fires, and biomass burning altering the biomes, on top of an ongoing necropolitical infodemic and COVID-19 pandemic. In the face of these multiple challenges, this MOOC offers a timely resource for health professionals and communities, encouraging them to address planetary challenges as fundamental health determinants.
INTRODUCTION: Acute myocardial infarction (AMI) is one of the main causes of morbidity and mortality in Brazil and worldwide. Seasonality and climate change seem to be associated with hospitalization for AMI. OBJECTIVE: to analyze the effect that seasonality and temperature have on the number of hospitalizations and deaths due to AMI, stratified by gender and age group, from 2009 to 2018 in a region of southern Brazil. METHODS: An Ecological study, composed of cases of hospitalizations and deaths by AMI in the Association of Municipalities of the Laguna Region (AMUREL), SC, Brazil. Data on AMI were collected by the Department of Informatics of the Unified Health System (DATASUS) and data on average monthly temperature (degrees Celsius) of the Laguna region (SC, Brazil) were provided by the National Institute of Meteorology (INMET). The data analysis was performed through linear regression and ANOVA test with Tukey post-hoc. RESULTS: 2947 hospitalizations were analyzed. The monthly average hospitalization per AMI was 24.6±8.1 cases (7.0±2.2/100,000 inhabitants) with a lethality of 14.4±6.8%. The results showed that there is no difference in AMI hospitalization between the months of the year, but showed a significant negative correlation between temperature and AMI hospitalizations (r=-0.219; P=0.022; β=-0.165). It was also shown that men and elderly had more cases of AMI hospitalization, but women and elderly had more lethality. When the lethality rate was analyzed during the study period, there was a significant negative correlation, indicating the reduction of AMI deaths with time. CONCLUSION: There was an association between temperature reduction and AMI hospitalization, where each 6°C reduction in temperature was related to an increase of 1 hospitalization per AMI/100,000 inhabitants. It is hoped that the results may assist in the formulation of public environmental policies for the prevention of risk factors for AMI.
Scorpionic accidents are a major public health problem due to the high occurrence with potential seriousness. In this manner, the research aimed to analyze the occurrence of scorpionic accidents in a municipality in the northeastern of Brazil. An exploratory, descriptive study was made, with a quantitative approach, using secondary data which was gotten from the Notifiable Diseases Information System (SINAN), from 2008 to 2018. Data such as neighborhood, presence of street markets were also used, and the existence of sanitation and climatic data such as temperature and season. Geoprocessing was used to identify possible changes in the environment. In the analyzed period, 9,330 cases of scorpion accidents were recorded, with an average of 848 annual notifications. Scorpionic accidents occurred more frequently in women (5,686; 60.94%). Individuals aged 20 to 29 years (1.727; 18.51%) were more frequent to scorpion stings. Regarding the body parts where the stings were made, the highlights were on the foot (3.515; 37.67%) followed by the hand (2.818; 30.20%). No statistically significant relation was observed between climatic factors and scorpionic accidents. However, the high number of cases of scorpionic accidents was observed in the last 11 years studied. It was evident that during the study period there was no statistical relationship when climatic factors were correlated to scorpionic accidents. On its turn, when it was verified the results of the geoprocessing analysis, it was seen that anthropic factors have been motivating the potentiation of the occurrence of these accidents.
Water bodies are increasingly contaminated by industrial and anthropogenic activities, climate change, and major environmental accidents. Global awareness has led the United Nations to develop an action plan to increase individuals’ access to clean water. Mine-tailing spills have been reported worldwide, with serious implications for major watercourses, especially the release of high metal concentrations. More recently, two events with alarming proportions and effects occurred in Brazil (Mariana accident in 2015 and Brumadinho accident in 2019), which resulted in approximately 300 human deaths. Mine residues rich in metals (mainly iron, aluminum, and manganese) reached important freshwater sources and have traveled hundreds of kilometers to reach the Atlantic Ocean, causing environmental harm and human health issues. For example, in the Mariana disaster, studies using the zebrafish model reported toxicity in water samples collected 464 km from the dam rupture site. This study presents data on the magnitude of these events, focusing on concerns associated with high dissolved metal concentrations in watercourses, exposing the direct impacts reported to the local aquatic environment as well as other effects that could persist in the long term.
Recent studies report seasonality in healthcare-associated infections, especially those caused by Acinetobacter baumannii complex. We conducted an ecologic study aimed at analyzing the impact of seasons, weather parameters and climate control on the incidence and carbapenem-resistance in A. baumannii complex bloodstream infections (ABBSI) in hospitals from regions with different climates in Brazil. We studied monthly incidence rates (years 2006-2015) of ABBSI from hospitals in cities from different macro-regions in Brazil: Fortaleza (Ceara State, Northeast region), Goiania (Goias State, Middle-west) and Botucatu (Sao Paulo State, Southeast). Box-Jenkins models were fitted to assess seasonality, and the impact of weather parameters was analyzed in Poisson Regression models. Separate analyses were performed for carbapenem-resistant versus carbapenem-susceptible isolates, as well as for infections occurring in climate-controlled intensive care units (ICUs) versus non-climate-controlled wards. Seasonality was identified for ABSSI ICUs in the Hospitals from Botucatu and Goiania. In the Botucatu hospital, where there was overall seasonality for both resistance groups, as well as for wards without climate control. In that hospital, the overall incidence was associated with higher temperature (incidence rate ratio for each Celsius degree, 1.05; 95% Confidence Interval, 1.01-1.09; P = 0.006). Weather parameters were not associated with ABBSI in the hospitals from Goiania and Fortaleza. In conclusion, seasonality was found in the hospitals with higher ABBSI incidence and located in regions with greater thermal amplitude. Strict temperature control may be a tool for prevention of A. baumanii infections in healthcare settings.
Background Many factors related to susceptibility or vulnerability to temperature effects on mortality have been proposed in the literature. However, there is limited evidence of effect modification by some individual-level factors such as occupation, colour/race, education level and community-level factors. We investigated the effect modification of the temperature-cardiovascular mortality relationship by individual-level and neighbourhood-level factors in the city of Rio de Janeiro, Brazil. Methods We used a case-crossover study to estimate the total effect of temperature on cardiovascular mortality in Rio de Janeiro between 2001 and 2018, and the effect modification by individual-level and neighbourhood-level factors. Individual-level factors included sex, age, colour/race, education, and place of death. Neighbourhood-level characteristics included social development index (SDI), income, electricity consumption and demographic change. We used conditional Poisson regression models combined with distributed lag non-linear models, adjusted for humidity and public holidays. Results Our results suggest a higher vulnerability to high temperatures among the elderly, women, non-hospitalised deaths, and people with a lower education level. Vulnerability to low temperatures was higher among the elderly, men, non-white people, and for primary education level. As for neighbourhood-level factors, we identified greater vulnerability to low and high temperatures in places with lower SDI, lower income, lower consumption of electricity, and higher demographic growth. Conclusion The effects of temperature on cardiovascular disease mortality in Rio de Janeiro vary according to individual-level and neighbourhood-level factors. These findings are valuable to inform policymakers about the most vulnerable groups and places, in order to develop more effective and equitable public policies.
OBJECTIVE: To analyze the association between climate changes in the macroregions in the state of São Paulo and testicular torsion treated cases. METHODS: The cases were selected in the Brazilian Public Health Data System Database from January 2008 to November 2016. All surgical procedure records were identified by the Hospital Admission Authorization document. Two codes were selected to process the search: testicular torsion (surgical cure code) and acute scrotum (exploratory scrototomy code). The macroregions were grouped in five areas linked to climate characteristics by International Köppen Climate Classification. RESULTS: A total of 2,351 cases of testicular torsion were registered in the period. For the areas B, C and E (testicular torsion n=2,130) there were statistical differences found in association of testicular torsion cases and decreased temperature (p=0.019, p=0.001 and p=0.006, respectively), however, in analyses for the areas A and D statistical differences were not observed (p=0.066 and p=0.494). CONCLUSION: Decrease in temperature was associated with testicular torsion in three macroregions of São Paulo. The findings support the theory of cold weather like a trigger in occurrence of testicular torsion in a tropical climate region.
The undernutrition and obesity pandemics associated with climate change are a global syndemic. They have a point of convergence, which is the unsustainable current food systems. This paper aims to discuss the role of public health policies, particularly the Brazilian Unified Health System (SUS) in the context of Primary Health Care, in combating the global syndemic and in the development of sustainable food systems. In this scenario, the National Food and Nutrition Policy is a leading intersectoral tool for an adequate and healthy diet and food and nutrition security. Also, the Dietary Guidelines for the Brazilian population is a strategic tool to support food and nutrition education. We highlight the need to articulate health, agriculture, and environmental policies to achieve sustainable development. Thus, SUS can be the arena to promote the main discussions on this topic, potentiating individual, group, and institutional actions to provide a fairer, healthy, and sustainable food system.
This article discusses the uncertainty about water quality in the Province of Chacabuco (Santiago Metropolitan Region) in Chile, a region marked by very strong pressure on the resource, both natural (drought) and anthropogenic (urban growth, agricultural intensification, industrialisation, and mining activity). Our main objective was, through an interdisciplinary research approach, to understand how the uncertainty concerning the state of hydro systems becomes central in the social representations of the inhabitants, since there is no consensus amongst regional stakeholders about environmental impacts nor is there evidence of pollution. By cross-referencing geochemical data on water quality and the inhabitants’ discourse on the resource, we identified those factors that create uncertainty about water resources: institutional lack of knowledge of the state of the resource, scientific difficulties in understanding the functioning of the hydro system, water and ground quality data that are difficult to interpret given the persistent drought, and the inhabitants’ distrust of data producers, in a context of planned regulatory zoning of polluting activities in the area. We also show the negative effects that the lack of trustworthy information has on the daily lives of local communities living near industrial infrastructures: anxiety, health concerns, and mistrust of drinking water, even though it is potable.
Colombia’s 2016 Peace Agreement is innovative in many ways. Remarkably, the agreement places significant emphasis on gender as a guiding principle. Gender-related measures are at the core of Colombia’s peacebuilding efforts. Nevertheless, six years after, parties have not fully implemented these measures; a narrow understanding of the concept of violence could be one of the reasons behind this. The agreement mainly refers to the physical and dominant understanding of gender-based violence (GBV). However, this understanding is problematic. Environmental and climate-related causes are structural to the Colombian armed conflict, and critical in building peace. Environmental violence points to human-induced activities that cause harms to the environment. Climate violence, one manifestation of environmental violence, is a type of violence that worsens underlying conditions of inequalities through extreme climate conditions. Drawing on the 2016 Colombian Peace Agreement, this article focuses on the experiences of Colombian rural women to assess whether expanding dominant concepts of GBV help implement environmental peacebuilding commitments. Applying an intersectional ecofeminist reading could contribute to acknowledging particular forms of violence embedded in the climate and peace crises in Colombia during the implementation phase of gender-related peace commitments and push towards the recognition of environmental and climate violence as GBV.
Background Over the past ten years Amazon region has experienced multiple environmental changes including high rates of deforestation, and more frequent ‘once in a century’ extreme weather events. Despite this it is still not clear how these events effect food biodiversity, local diets and nutrition of Amazon Indigenous people. Information on food consumption is urgently needed, especially to identify key Amazonian Indigenous foods which may increase nutritional resilience to extreme climate events. Technological tools represent a potential feasible solution to measure diet for population studies. We have partnered with International researchers, local nutritionist, Indigenous leaders and community members to adapt a digital tool to support dietary measurement in Amazonian Indigenous communities. Methods The adaptation had three stages. First working with an international multidisciplinary committee, we identified and compiled existing food composition databases to create a database for the Peruvian myfood24 version to use with communities of Shawi ethnicity. Seven food composition tables were identified, and permission was requested for two cases where information was not public. Six food composition tables, one academic publication and one peruvian report about amazon food species, were used for generating a food composition database. Second, using myfood24 guidelines, we completed a data base using Access software. This process involved cleaning and removing duplicate food items, including conversion values (from raw to cooked foods) and calculations for potential nutrient losses on cooking. We used a series of six online focus groups meetings with three peruvian nutritionists, including one nutritionist expert on the Shawi diet, to identify portions, and combinations. Finally, during a workshop with five local community members, a list of Shawi foods were validated, and food preparation was characterised to develop recipes and to take pictures for use in the online tool. Results The peruvian food composition database to be used with the Shawi communities included a total of 1042 food items, with information for 14 key nutrients. These foods were split into fourteen food categories. Seventy-six possible options on how food is eaten together, and 43 portion measurements were validated in the focus groups. 114 food items were identified in the workshop as commonly consumed by Shawi, with five forest animal foods proving the highest level of iron per 100 g: palm larvae (3.6mg), armadillo (3.5mg), deer (3.5mg), paca (3.4mg) and agouti (3.4mg). Conclusion A comprehensive Peruvian Food Composition Database with a focus on Shawi diet has been created. This data has been incorporated within the online dietary assessment tool, myfood24. A photo Album and recipes will be completed over the next weeks. The new tool with be useful to understand how food and nutrient intakes in this vulnerable population are affected by climate change events.
In this review, seven pieces of research on climate variability and its impact on human health in Buenos Aires City between 1995 and 2015 were evaluated. The review highlighted continuities and ruptures in the methodology, variables, and statistics data of the research, considering their similarities and differences in the period of study and the methodology applied. Contributions, pending issues, and public policies on climate change challenges in the city aimed at improving living conditions were considered. Six studies contributed evidence on the relationship between climate and health and its impacts on the population; two studies suggested the development of early warning systems and one study is a preliminary approach.
(1) Background: Increasing and improving green spaces have been suggested to enhance health and well-being through different mechanisms. Latin America is experiencing fast population and urbanization growth; with rising demand for interventions to improve public health and mitigate climate change. (2) Aim: This study aimed to review the epidemiological evidence on green spaces and health outcomes in Latin America. (3) Methods: A systematic literature review of green spaces and health outcomes was carried out for studies published in Latin America before 28 September 2020. A search strategy was designed to identify studies published in Medline via PubMed and LILACS. The search strategy included terms related to green spaces combined with keywords related to health and geographical location. No time limit for the publication was chosen. The search was limited to English, Spanish, Portuguese, and French published articles and humans’ studies. (4) Findings: This systematic review found 19 epidemiological studies in Latin America related to green spaces and health outcomes. Nine studies were conducted in Brazil, six in Mexico, three in Colombia, and one in Chile. In terms of study design, 14 were cross-sectional studies, 3 ecological, and 2 cohort studies. The population included among the studies ranged from 120 persons to 103 million. The green space definition used among studies was green density or proximity (eight studies), green presence (five studies), green spaces index (four studies), and green space visit (two studies). The health outcomes included were mental health (six studies), overweight and obesity (three studies), quality of life (three studies), mortality (two studies), cardiorespiratory disease (one study), disability (one study), falls (one study), and life expectancy (one study). Eleven studies found a positive association between green spaces and health, and eight studies found no association. (5) Conclusion: This systematic review identified 19 epidemiological studies associating green spaces and health outcomes in Latin America. Most of the evidence suggests a positive association between green spaces and health in the region. However, most of the evidence was supported by cross-sectional studies. Prioritizing longitudinal studies with harmonized exposure and outcome definitions and including vulnerable and susceptible populations is needed in the region.
OBJECTIVE: Humidity and temperature are fundamental for the balance in the life cycle of living beings and, consequently, for maintaining the well-being of the human population and reducing the prevalence of infectious diseases. Thus, in order to mitigate the impact of climate change, especially in the period when humidity is not the ideal, it is necessary to adopt some assistance measures. The present experimental study aims to elucidate what would be the recommended option to improve the quality of life of the human being and to clarify which resources (air humidifier, bucket of water or wet towel) will be effective to improve the humidity of the air in times of drought and low moisture. METHODS: The experimental study was carried out with INKBIRD hygrometers allowing the analysis of the variation of air humidity throughout the day. Three forms of treatment were established: humidifier, wet towel and bucket of water. In each room, two hygrometers were placed equidistant from the occupant of the room and their respective treatment that varied between 1m and 2m away from the headboard indoor each room. In addition, two environments were used as controls, one being an external environment and the other an internal closed environment, totaling five rooms for the study. The rooms were monitored between the end of July and the end of August 2019 in Goiania (GO). RESULTS: Although assistance measures are used to significantly improve air pollution in times of extreme drought, there was a significant difference between them. The humidifier and a wet towel had 7.50% and 5.71% more humidity in the external relation (external control), respectively, more efficient. The volume of water, however, did not show significant difference (p>0.05) and, therefore, there was no variation. CONCLUSION: The humidifier and the towel are treatments considered more efficient, and that there was a significant effect of distance on humidity. Therefore, 1m of distance is more efficient in increasing and/or maintaining air humidity, inducing improvements in the populations’ health.
This article, an essay, and narrative review, analyzes the relationship between the 2030 Agenda, food systems, and their relevance to global and collective health. The concept of syndemics contextualizes the COVID-19 pandemic in relation to poverty and social injustice, as it also reveals the synergy with other pandemics related to the advancement of the global food system: malnutrition, obesity, and climate change, which all have strong influence of the dominant model of agriculture. We also use four strategic concepts to think about the transition towards healthy and sustainable food systems: food system, food and nutrition security (FNS), human right to adequate food (HRAF) and agroecology. Then, we gather international reports and data that systematize studies on the growing threats imposed by the dominant agricultural model, often denied by powerful economic sectors and neoconservative groups. We also highlight challenges imposed at different scales, from global to local, so that public policies and social mobilizations developed in the last two decades can resist and reinvent themselves in the construction of fairer societies.
In 2017, extreme rainfall events occurred in the northern portion of Peru, causing nearly 100,000 victims, according to the National Emergency Operations Center (COEN). This climatic event was attributed to the occurrence of the El Nino Southern Oscillation (ENSO). Therefore, the main objective of this study was to determine and differentiate between the occurrence of canonical ENSO, with a new type of ENSO called “El Nino Costero” (Coastal El Nino). The polynomial equation method was used to analyze the data from the different types of existing ocean indices to determine the occurrence of ENSO. It was observed that the anomalies of sea surface temperature (SST) 2.5 degrees C (January 2016) generated the “Modoki El Nino” and that the anomaly of SST -0.3 degrees C (January 2017) generated the “Modoki La Nina”; this sequential generation generated El Nino Costero. This new knowledge about the sui generis origin of El Nino Costero, based on the observations of this analysis, will allow us to identify and obtain important information regarding the occurrence of this event. A new oceanic index called the Pacific Regional Equatorial Index (PREI) was proposed to follow the periodic evolution and forecast with greater precision a new catastrophic event related to the occurrence of El Nino Costero and to implement prevention programs.
Environmental air pollution is a major risk factor for morbidity and mortality worldwide. Environmental air pollution has a direct impact on human health, being responsible for an increase in the incidence of and number of deaths due to cardiopulmonary, neoplastic, and metabolic diseases; it also contributes to global warming and the consequent climate change associated with extreme events and environmental imbalances. In this review, we present articles that show the impact that exposure to different sources and types of air pollutants has on the respiratory system; we present the acute effects-such as increases in symptoms and in the number of emergency room visits, hospitalizations, and deaths-and the chronic effects-such as increases in the incidence of asthma, COPD, and lung cancer, as well as a rapid decline in lung function. The effects of air pollution in more susceptible populations and the effects associated with physical exercise in polluted environments are also presented and discussed. Finally, we present the major studies on the subject conducted in Brazil. Health care and disease prevention services should be aware of this important risk factor in order to counsel more susceptible individuals about protective measures that can facilitate their treatment, as well as promoting the adoption of environmental measures that contribute to the reduction of such emissions.
BACKGROUND: Environmental risk assessments and interventions to mitigate environmental risks are essential to protect public health. While the objective measurement of environmental hazards is important, it is also critical to address the subjective perception of health risks. A population’s perception of environmental health hazards is a powerful driving force for action and engagement in safety and health behaviors and can also inform the development of effective and more sustainable environmental health policies. To date, no instruments are available to assess risk perception of environmental health hazards in South America even though there are many concerning issues in the region, including mining. OBJECTIVE: We aimed to adapt and validate an environmental health risk perception questionnaire in a Chilean population affected by mining activity among other risks frequently reported in Latin American countries and included the collection of information on trust on public information sources. METHODS: We adapted an Australian risk perception questionnaire for validation in an adult population from a Chilean mining community. This adaptation included two blinded translations (direct, inverse), a pre-test study (n = 20) and a review by environmental health experts. Principal Component Analyses (PCA) was used to identify factors within major domains of interest. The Bartlett test of sphericity, Kaiser-Meyer-Olkin (KMO) measure and the Cronbach α test were used to assess the instrument’s validity and reliability. The instrument was pilot tested in 205 adults from a mining community in Chañaral. RESULTS: The final adapted questionnaire proved to be a good instrument to measure risk perception in a community chronically exposed to mining waste. For community risks, four factors explained 59.4% of the variance. “Global Issues” (30.2%) included air pollution, contamination of mining, ozone layer depletion and vector diseases. For personal risks, the first two components explained 59.5% of the variance, the main factor (36.7%) was “unhealthy behaviors within the household”. For trust in information, the first factor (36.2%) included as main sources “Media and authorities”. The Cronbach α ranged between 0.68 and 0.75; and the KMO test between 0.7 to 0.79 for community and personal risks and trust. CONCLUSIONS: The final questionnaire is a simple, reliable and useful instrument that can assist in evaluating environmental health risk perceptions in Latin American countries.
OBJECTIVE: To examine the impact of climate variability on the occurrence of exercise-induced bronchospasm in the rainy and dry seasons of a Brazilian semi-arid region. METHODS: This sample comprised 82 adolescents aged 15 to 18 years, who were submitted to exercise-induced bronchospasm assessment on a treadmill and outdoors, during the rainy and the dry season. Anthropometric variables, sexual maturity and forced expiratory volume in the first second were analyzed. Air temperature and humidity, decline in forced expiratory volume in the first second (%) and frequency of bronchospasm were compared between seasons using the independent Student’s t test, the Wilcoxon and McNemar tests, respectively. The level of significance was set at p<0.05. RESULTS: The mean age was 15.65±0.82 years. Air temperature, air humidity and decline in forced expiratory volume in the first second (%) differed between seasons, with higher air temperature and humidity in the rainy season (29.6ºC±0.1 and 70.8%±0.6 versus 28.5ºC±0.2 and 48.5%±0.6; p<0.05). The decline in forced expiratory volume in the first second (%) was greater in the dry season (9.43%±9.97 versus 12.94%±15.65; p<0.05). The frequency of bronchospasm did not differ between seasons. CONCLUSION: The dry season had a negative impact on forced expiratory volume in the first second in adolescents, with greater decrease detected during this period. Findings of this study suggested bronchospasm tends to be more severe under low humidity conditions.
The role of climate driving zoonotic diseases’ population dynamics has typically been addressed via retrospective analyses of national aggregated incidence records. A central question in epidemiology has been whether seasonal and interannual cycles are driven by climate variation or generated by socioeconomic factors. Here, we use compartmental models to quantify the role of rainfall and temperature in the dynamics of snakebite, which is one of the primary neglected tropical diseases. We took advantage of space-time datasets of snakebite incidence, rainfall, and temperature for Colombia and combined it with stochastic compartmental models and iterated filtering methods to show the role of rainfall-driven seasonality modulating the encounter frequency with venomous snakes. Then we identified six zones with different rainfall patterns to demonstrate that the relationship between rainfall and snakebite incidence was heterogeneous in space. We show that rainfall only drives snakebite incidence in regions with marked dry seasons, where rainfall becomes the limiting resource, while temperature does not modulate snakebite incidence. In addition, the encounter frequency differs between regions, and it is higher in regions where Bothrops atrox can be found. Our results show how the heterogeneous spatial distribution of snakebite risk seasonality in the country may be related to important traits of venomous snakes’ natural history.
Wildfires have increased in the last years and, when caused by intentional illegal burnings, are frequently run out of control. Wildfire has been pointed out as an important source of polycyclic aromatic hydrocarbons (PAHs) and trace elements (TEs) – such as, As, Ni, and Pb – to environmental compartments, and thus may pose a risk to human health and to the ecosystem. In 2020, the Brazilian biome, Pantanal, faced the largest losses by wildfires in the last 22 years. Ashes from the topsoil layer in Pantanal were collected after these wildfires at 20 sites divided into the sediment, forest, PF, PS, and degraded sites. Toxicity and associated risks for human health were also evaluated. The areas highly impacted by wildfires and by artisanal gold mining activities showed higher concentrations for TEs and PAHs than the protected areas. Pb varied from 8 ± 4 to 224 ± 81 mg kg(-1), and total PAH concentration ranged between 880 ± 314 and 1350 ± 70 ng g(-1), at sites impacted by anthropogenic activities. Moreover, health risk assessments for TE and PAH indicated a potentially great risk for children and adults, via ingestion, inhalation, and dermal pathway. The carcinogenic risks exceeded reference values, for both TE and PAH, suggesting harmful conditions, especially for vulnerable groups, such as children and the elderly. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11869-022-01248-2.
BACKGROUND: Brazil has faced two simultaneous problems related to respiratory health: forest fires and the high mortality rate due to COVID-19 pandemics. The Amazon rain forest is one of the Brazilian biomes that suffers the most with fires caused by droughts and illegal deforestation. These fires can bring respiratory diseases associated with air pollution, and the State of Par?í in Brazil is the most affected. COVID-19 pandemics associated with air pollution can potentially increase hospitalizations and deaths related to respiratory diseases. Here, we aimed to evaluate the association of fire occurrences with the COVID-19 mortality rates and general respiratory diseases hospitalizations in the State of Para, Brazil. METHODS: We employed machine learning technique for clustering k-means accompanied with the elbow method used to identify the ideal quantity of clusters for the k-means algorithm, clustering 10 groups of cities in the State of Para where we selected the clusters with the highest and lowest fires occurrence from the 2015 to 2019. Next, an Auto-regressive Integrated Moving Average Exogenous (ARIMAX) model was proposed to study the serial correlation of respiratory diseases hospitalizations and their associations with fire occurrences. Regarding the COVID-19 analysis, we computed the mortality risk and its confidence level considering the quarterly incidence rate ratio in clusters with high and low exposure to fires. FINDINGS: Using the k-means algorithm we identified two clusters with similar DHI (Development Human Index) and GDP (Gross Domestic Product) from a group of ten clusters that divided the State of Para but with diverse behavior considering the hospitalizations and forest fires in the Amazon biome. From the auto-regressive and moving average model (ARIMAX), it was possible to show that besides the serial correlation, the fires occurrences contribute to the respiratory diseases increase, with an observed lag of six months after the fires for the case with high exposure to fires. A highlight that deserves attention concerns the relationship between fire occurrences and deaths. Historically, the risk of mortality by respiratory diseases is higher (about the double) in regions and periods with high exposure to fires than the ones with low exposure to fires. The same pattern remains in the period of the COVID-19 pandemic, where the risk of mortality for COVID-19 was 80% higher in the region and period with high exposure to fires. Regarding the SARS-COV-2 analysis, the risk of mortality related to COVID-19 is higher in the period with high exposure to fires than in the period with low exposure to fires. Another highlight concerns the relationship between fire occurrences and COVID-19 deaths. The results show that regions with high fire occurrences are associated with more cases of COVID deaths. INTERPRETATION: The decision-make process is a critical problem mainly when it involves environmental and health control policies. Environmental policies are often more cost-effective as health measures than the use of public health services. This highlight the importance of data analyses to support the decision making and to identify population in need of better infrastructure due to historical environmental factors and the knowledge of associated health risk. The results suggest that The fires occurrences contribute to the increase of the respiratory diseases hospitalization. The mortality rate related to COVID-19 was higher for the period with high exposure to fires than the period with low exposure to fires. The regions with high fire occurrences is associated with more COVID-19 deaths, mainly in the months with high number of fires. FUNDING: No additional funding source was required for this study.
2015 saw the strongest El Nino event in the historical record, resulting in extreme drought conditions in Brazil. As drought conditions may also lead to greater fire danger, this study uses the 2015 fire in Brazil as a case study to examine whether and to what extent human-induced climate change has contributed to the fire weather conditions in the Cerrado and the southern Amazonia transitional forests known as the Arc of deforestation. Our results show that anthropogenic climate change is indeed a driver of meteorological conditions conducive to strong fire weather in these two regions, measured by fire weather index (FWI), especially on shorter timescales of daily and weekly. The anthropogenic climate change signal of FWI on short timescales corresponds to a similar order of increase in the FWI sub-indices (initial spread index and fine fuel moisture code) that can rapidly change due to the influence of the instantaneous weather conditions. For both regions the changes in fire weather in response to anthropogenic climate change are dominated by the combination of temperature and relative humidity responses. High FWI is more likely to occur under El Nino conditions, less likely under La Nina conditions, although the impacts of El Nino vs La Nina conditions are not symmetric when compared with El Nino Southern Oscillation neutral states. To summarize, both human-induced climate change and the presence of El Nino increased the likelihood of occurrence for the strong fire weather condition in 2015. Our results suggest that local and regional adaptation measures, such as improved drought monitoring and warning systems, could help with effective planning of fire prevention, firefighting actions, and disaster preparedness.
Assessing disaster impacts is the pathway to attain informed decision making to mitigate damages. Currently, these impacts are generally analyzed excluding the environmental consequences of disasters. Thus, this study proposes a novel quantitative method, named multi-dimensional damage assessment (MDDA), that integrates the disaster-related environmental impacts with economic and social losses. For this, Life Cycle Assessment was used to measure environmental impacts at the endpoint level for the human health area of protection. The unit of assessment used to merge the three damage dimensions was the disability-adjusted life year equivalent (DALYeq). The damages exerted by floods in Peru linked to El Nino in recent decades were selected as the main case study. Furthermore, other natural disasters (e.g., earthquakes) were included in the assessment for the sake of comparability. The results show that El Nino floods in Peru in 1982-83 and 1997-98 presented higher damage per capita, approximately 2.8 times higher, than the event in 2017. Additionally, the assessment showed that economic damages are the most relevant in El Nino floods, whereas social damages are those prevalent for earthquakes. The results demonstrate that MDDA is an effective measurement for the purpose of damage comparison and, therefore, to implement mitigation strategies. The proposed methodology will allow the development of disaster risk mitigation strategies that will cover all damage dimensions and enable the adoption of improved public policies. Finally, MDDA can be applied to compute any complex array of damages that humans may suffer or infringe as a consequence of their interaction with the environment.
The literature documents that individual behavior and climatic change have recently been given more and more space in the definition of company strategies. However, in terms of preparing for catastrophes, few inquiries have been made into the individual propensity to acquire insurance, especially in terms of People with Disabilities (PwD). In this study, we assess the effect of information on the propensity of heads of households to acquire home insurance against forms of natural disasters, particularly flooding. We conduct a survey of over 500 individuals, including blind individuals, to verify the intuition that there is a causal link between the existence of information and the willingness of individuals to acquire flood insurance. The results reveal that visually deficient individuals are approximately 300% more likely to buy this insurance than other individuals. However, when PwD have information regarding the potential risk and harm caused by floods, this marginal effect is attenuated.
People with visual impairments (PwVI) represent a heterogeneous social group who often experience significant disabling barriers in exercising their rights throughout their life course. Understanding dimensions of vulnerability of PwVI to disasters and climate change is an important issue to reduce the culture of neglected disasters. To date, few studies have analyzed visual impairment and disaster risk reduction (DRR) in the countries of Latin America and the Caribbean. This exploratory qualitative research project analyzed how to include PwVI in the DRR policies of Brazil. The research question is: how can we include PwVI in the discussion of DRR and climate change? The response to this question is part of a joint effort that involved a university, a hazard monitoring agency, and three institutions that work with PwVI. The three main results of the project are: (1) a mapping method to identify the exposure of PwVI to landslides and floods, and to create tactile risk maps tailored to them; (2) incorporating the voices of PwVI regarding their vulnerabilities and capacities with respect to disasters and climate change, achieved through shared interaction during 15 face to face interviews and one workshop attended by 100 people; and (3) an initiative of inclusive education to reduce some of the disabling barriers that intensify vulnerability.
Landslides typify one of the most hazardous natural phenomena fostering economic and even human losses worldwide. Several countries like Colombia, in South America, are hotspots for fatal landslides. In this contribution, we thoroughly reviewed four available databases, articles, grey literature and web resources, in order to build up a new catalogue of fatal landslides in Colombia. We gathered a catalogue of 2351 individual fatal landslides which caused about 37,959 deaths. Of these, we found 11 fatal events in historical times (pre-twentieth century). In modern times (1912-2020), we analysed landslides’ spatial and temporal distribution, finding that in central-western Colombia, particularly in the departments of Caldas, Risaralda, Quindio and Antioquia, these kinds of events are more frequent. Upward trends in these areas and a nationwide increase in the number of events in the last 20 years suggest that fatal landslides are far from being effectively mitigated. Our findings also show a strong correlation between the climate variability phenomenon known as El Nino Southern Oscillation (ENSO) and fatal landslides, particularly during those years when strong La Nina (cold phase of ENSO) events occur. Despite rainfall being the most common trigger for fatal landslides, we observed an increasing trend in anthropogenically related events in the last decade. Finally, we obtained multiple socio-economic indices and ran a statistical analysis at the departmental level in order to assess whether impoverished and vulnerable people are more affected by fatal landslides. We propose that in most cases, departments with low income, high levels of corruption and inequality are usually more affected.
Environmental factors such as solar ultraviolet radiation (UV), air pollution, and variations in the air temperature (T) and relative humidity (RH) affect skin health. However, it is still unclear what effects on the skin may occur as the result of these combined exposures. This study was designed to quantify environmental exposures during routine daily activities to provide quantitative metrics that inspire future studies on exposome and human health. Two bicyclists were equipped with instruments to collect specific data concerning UV (at different angles), T, RH, ground-level ozone (O-3), and chemical exposures. Measurements were conducted in the summer and winter seasons of 2016-2017 in four touristic and urban Brazilian cities. Erythemal UV doses (EryD) exceeding the minimal erythemal doses (MED) for phototype V (EryD > 600 Jm(-2)) were registered inmost tours, including cloudy weather and during the winter. Significant EryD were also observed in tilted body parts. Humidex Index (HI) higher than 30 degrees C revealed great thermal discomfort in most regions, mainly during the summer. O-3 amounts were generally below the thresholds established by the World Health Organization (WHO), except for two instances in which the peak of O-3 concentrations exceeded the 100 mu gm(-3). More than 10% of chemicals sampled during the tours were identified as Polycyclic Aromatic Hydrocarbons (PAH), including anthracene (peak of 207 ng per gram of air). There was a combination of EryD exceeding the MED, thermal discomfort, and PAH exposure in most studied areas. We concluded that this exposome could accelerate and amplify skin-related damages generally associated with a single environmental factor exposure, such as sunlight exposure at any time of the year, for example. (C) 2021 The Authors. Published by Elsevier B.V.
BACKGROUND: Natural disasters and public health crises can disrupt communities’ capacities to implement important public health programs. A nationwide implementation of an evidence-based HIV prevention program, Focus on Youth in The Caribbean (FOYC) and Caribbean Informed Parents and Children Together (CImPACT), in The Bahamas was disrupted by Hurricane Dorian and the COVID-19 pandemic, especially in its more remote, Family Islands. We explored the teacher- and school-level factors that affected implementation of the program in these islands during those disruptions. METHODS: Data were collected from 47 Grade 6 teachers and 984 students in 34 government elementary schools during the 2020-2021 school year. Teachers completed a pre-implementation questionnaire to record their characteristics and perceptions that might affect their implementation fidelity and an annual program training workshop. School coordinators and high-performing teachers acting as mentors received additional training to provide teachers with monitoring, feedback, and additional support. Teachers submitted data on their completion of the 9 sessions and 35 core activities of FOYC + CImPACT. The fidelity outcomes were the number of sessions and core activities taught by teachers. RESULTS: On average, teachers taught 60% of sessions and 53% of core activities. Teachers with “very good” school coordinators (34% of teachers) taught more activities than those with “satisfactory” (43%) or no (34%) school coordinator (27.5 vs. 16.8 vs. 14.8, F = 12.86, P < 0.001). Teachers who had attended online training or both online and in-person training taught more sessions (6.1 vs. 6.2 vs. 3.6, F = 4.76, P < 0.01) and more core activities (21.1 vs. 20.8 vs. 12.6, F = 3.35, P < 0.05) than those who received no training. Teachers’ implementation was associated with improved student outcomes (preventive reproductive health skills, self-efficacy, and intention). CONCLUSIONS: The Hurricane Dorian and the COVID-19 pandemic greatly disrupted education in The Bahamas Family Islands and affected implementation of FOYC + CImPACT. However, we identified several strategies that supported teachers’ implementation following these events. Teacher training and implementation monitoring increased implementation fidelity despite external challenges, and students achieved the desired learning outcomes. These strategies can better support teachers’ implementation of school-based interventions during future crises.
Purpose The purpose of this paper is to analyze the context of the emergence of a skin infection outbreak in the aftermath of Hurricane Matthew in Haiti and detail the role of community-based participatory research in mobilizing local action in a country with low state capacity. Design/methodology/approach While implementing a post-disaster study that combined a survey of 984 households and 69 community leaders with 23 focus groups, 60 ethnographic interviews and community mapping, a skin infection outbreak was detected. Using study results, the research team in partnership with different stakeholders responded to the outbreak with a health intervention. Findings The findings illustrate how pre-existing conditions shape local communities’ vulnerability to health crises in the aftermath of disasters and the critical role research can play in informing the recovery processes. Community-based approaches to emergency health reinforced by multi-stakeholder partnerships with local government can strengthen post-disaster response and governance structures setting the groundwork for the development of local resilience. Research limitations/implications The health intervention was implemented as a result of the study. Patients served were not derived from the study sample but were self-selected based on their need for skin-related medical treatment. Originality/value This article highlights the integral role research can play in identifying the health impacts of disaster events in vulnerable, hard-to-reach communities and strengthening government involvement in disaster governance.
Indigenous people are among the populations most vulnerable to climate change. However, indigenous societies’ potential contributions to addressing climate change and related issues of food security are vast but poorly recognized. The objective of this report is to inform the nutrition and public health communities about the potential contributions of ancient Andean technologies to address these contemporary challenges. Our research examines these ancient farming technologies within the frame of climate change and dietary potential. Specifically, we focus on 4 technologies derived from 3 case studies from Ecuador. These technologies were analyzed using evidence mainly of adaptation to climate change in indigenous-based agriculture. Our examination of these technologies suggests they could be effective mechanisms for adapting to climate change and protecting food sovereignty. Thus, although highly vulnerable to climate change, indigenous peoples in the Andes should also be seen as “agents of change.”
Climate change has been recognised as a multiplier of risk factors affecting public health. Disruptions caused by natural disasters and other climate-driven impacts are placing increasing demands on healthcare systems. These, in turn, impact the wellness and performance of healthcare workers (HCWs) and hinder the accessibility, functionality and safety of healthcare systems. This study explored factors influencing HCWs’ disaster management capabilities with the aim of improving their resilience and adaptive capacity in the face of climate change. In-depth, semi-structured interviews were conducted with thirteen HCWs who dealt with disasters within two hospitals in Queensland, Australia. Analysis of the results identified two significant themes, HCWs’ disaster education and HCWs’ wellness and needs. The latter comprised five subthemes: HCWs’ fear and vulnerability, doubts and uncertainty, competing priorities, resilience and adaptation, and needs assessment. This study developed an ‘HCWs Resilience Toolkit’, which encourages mindfulness amongst leaders, managers and policymakers about supporting four priority HCWs’ needs: ‘Wellness’, ‘Education’, ‘Resources’ and ‘Communication’. The authors focused on the ‘Education’ component to detail recommended training for each of the pre-disaster, mid-disaster and post-disaster phases. The authors conclude the significance of the toolkit, which provides a timely contribution to the healthcare sector amidst ongoing adversity.
Biodiversity and ecosystem conservation in the Amazon play a critical role in climate-change mitigation. However, institutional responses have had conflicted and complex relations with Indigenous peoples. There is a growing need for meaningful engagement with-and recognition of-the centrality of Indigenous peoples’ perceptions and understanding of the changes they are experiencing to inform successful and effective place-based adaptation strategies. To fill this gap, this study focuses on the value-based perspectives and pragmatic decision-making of Shawi Indigenous men in the Peruvian Amazon. We are specifically interested in their perceptions of how their food system is changing, why it is changing, its consequences, and how/whether they are coping with and responding to this change. Our results highlight that Shawi men’s agency and conscious envisioning of their future food system intersect with the effects of government policy. Shawi men perceive that the main driver of their food-system changes, i.e., less forest food, is self-driven population growth, leading to emotions of guilt and shame. During our study, they articulated a conscious belief that future generations must transition from forest-based to agricultural foods, emphasising education as central to this transition. Additionally, results suggest that the Peruvian government is indirectly promoting Shawi population growth through policies linking population size to improved service delivery, particularly education. Despite intentional Shawi moves to transition to agriculture, this results in a loss of men’s cultural identity and has mental-health implications, creating new vulnerabilities due to increasing climatic extremes, such as flooding and higher temperatures.
Fascioliasis is a worldwide emerging snail-borne zoonotic trematodiasis with a great spreading capacity linked to animal and human movements, climate change, and anthropogenic modifications of freshwater environments. South America is the continent with more human endemic areas caused by Fasciola hepatica, mainly in high altitude areas of Andean regions. The Peruvian Cajamarca area presents the highest human prevalences reported, only lower than those in the Bolivian Altiplano. Sequencing of the complete rDNA ITS-2 allowed for the specific and haplotype classification of lymnaeid snails collected in seasonal field surveys along a transect including 2007-3473 m altitudes. The species Galba truncatula (one haplotype preferentially in higher altitudes) and Pseudosuccinea columella (one haplotype in an isolated population), and the non-transmitting species Lymnaea schirazensis (two haplotypes mainly in lower altitudes) were found. Climatic seasonality proved to influence G. truncatula populations in temporarily dried habitats, whereas L. schirazensis appeared to be more climatologically independent due to its extreme amphibious ecology. Along the southeastern transect from Cajamarca city, G. truncatula and L. schirazensis shared the same site in 7 localities (46.7% of the water collections studied). The detection of G. truncatula in 11 new foci (73.3%), predominantly in northern localities closer to the city, demonstrate that the Cajamarca transmission risk area is markedly wider than previously considered. Lymnaea schirazensis progressively increases its presence when moving away from the city. Results highlight the usefulness of lymnaeid surveys to assess borders of the endemic area and inner distribution of transmission foci. Similar lymnaeid surveys are still in need to be performed in the wide northern and western zones of the Cajamarca city. The coexistence of more than one lymnaeid transmitting species, together with a morphologically indistinguishable non-transmitting species and livestock movements inside the area, conform a complex scenario which poses difficulties for the needed One Health control intervention.
Inequalities in benefits from ecosystem services (ES) challenge the achievement of sustainability goals, because they increase the vulnerability of socio-ecological systems to climate hazards. Yet the unequal effects of changes in ES, and of climate change more generally, on human well-being (HWB) are still poorly accounted for in decision-making around adaptation, particularly in tropical countries. Here, we investigate these dynamics through the lens of local peoples’ perceptions of ES in relation to human well-being (HWB), and how these are affected by climate change in three distinct regional case studies in the Atlantic Forest in Southeast of Brazil. Through structured questionnaires, we found that the local perceptions of important ES are region-dependent, particularly identifying services regulating local climate and air quality, water flow and quality, food provisioning, and cultural services of landscape esthetics related to forest regeneration. HWB was expressed through material (e.g., economic security, environmental conditions) and higher accounts of non-material (e.g., feelings, health and social connections) dimensions. Specific environmental changes were identified by 95% of those responding, 40% of whom included climate change as one of these. When asked about climate directly, 97% of those responding identified relevant changes in regionally relevant ways. Rising temperatures, unbalanced seasons, altered rainfall patterns, drought, increase of extreme events, and sea level rise are negatively affecting both material and non-material dimensions of HWB across regions. These perceived changes aligned with observed and projected climate changes in the regions. Benefits from ES accrue for HWB at different scales depending on the specific ES and region. For example, crop production by small farmers or exported in sugar cane, water captured for agricultural irrigation or used for urban supplies, and fish resources for local consumption and lifestyle or as a recreational attraction for visitors. Policy choices about such balances will affect local vulnerabilities to the expected future climate and other environmental changes in the region. This place fine-scale observations and the empowerment of local knowledge at the core of policy decisions about adaptation to support a climate-resilient future for traditional communities and small farmers.
BACKGROUND: Both cold and hot temperature have been associated with the onset of asthma, but it remains largely unknown about the risk of asthma hospitalisation associated with short-term temperature fluctuation or temperature variability (TV). OBJECTIVE: To explore the association between short-term exposure to TV and asthma hospitalisation in Brazil. METHODS: Data for asthma hospitalisation and weather conditions were collected from 1816 Brazilian cities between 2000 and 2015. TV was calculated as the SD of all daily minimum and maximum temperatures within 0-7 days prior to current day. A time-stratified case-crossover design was performed to quantify the association between TV and hospitalisation for asthma. RESULTS: A total of 2 818 911 hospitalisations for asthma were identified during the study period. Each 1°C increase in 0-7 days’ TV exposure was related to a 1.0% (95% CI 0.7% to 1.4%) increase in asthma hospitalisations. The elderly were more vulnerable to TV than other age groups, while region and season appeared to significantly modify the associations. There were 159 305 (95% CI 55 293 to 2 58 054) hospitalisations, US$48.41 million (95% CI US$16.92 to US$78.30 million) inpatient costs at 2015 price and 450.44 thousand inpatient days (95% CI 156.08 to 729.91 thousand days) associated with TV during the study period. The fraction of asthma hospitalisations attributable to TV increased from 5.32% in 2000 to 5.88% in 2015. CONCLUSION: TV was significantly associated with asthma hospitalisation and the corresponding substantial health costs in Brazil. Our findings suggest that preventive measures of asthma should take TV into account.
Urban ecosystem services have become a main issue in contemporary urban sustainable development, whose efforts are challenged by the phenomena of world urbanization and climate change. This article presents a study about the ecosystem services of green infrastructure towards better respiratory health in a socioeconomic scenario typical of the Global South countries. The study involved a data science approach comprising basic and multivariate statistical analysis, as well as data mining, for the municipalities of the state of Parana, in Brazil’s South region. It is a cross-sectional study in which multiple data sets are combined and analyzed to uncover relationships or patterns. Data were extracted from national public domain databases. We found that, on average, the municipalities with more area of biodiversity per inhabitant have lower rates of hospitalizations resulting from respiratory diseases (CID-10 X). The biodiversity index correlates inversely with the rates of hospitalizations. The data analysis also demonstrated the importance of socioeconomic issues in the environmental-respiratory health phenomena. The data mining analysis revealed interesting associative rules consistent with the learning from the basic statistics and multivariate analysis. Our findings suggest that green infrastructure provides ecosystem services towards better respiratory health, but these are entwined with socioeconomics issues. These results can support public policies towards environmental and health sustainable management.
The advance of human activities in a disorderly way has accelerated in recent decades, intensifying the environmental impacts directly linked to these practices. The atmosphere, essential for the maintenance of life, is increasingly saturated with pollutants, offering risks to practically all the inhabitants of the planet, a process that, in addition to causing illness and early mortality, is related to serious financial losses (including in the production of goods), dangerous temperature increase and severe natural disasters. Although this perception is not recent, the global initiative to control the different mechanisms that trigger the commitment of biodiversity and irreversible climate changes arising from pollution is still very incipient, given that global initiatives on the subject emerged just over 50 years ago. Brazil is a territory that centralizes many of these discussions, as it still faces both political and economic obstacles in achieving a sustainable growth model as it was agreed through the United Nations 2030 Agenda. Even though there is little time left for the completion of these goals, much remains to be done, and despite the fulfillment of this deadline, the works will certainly need to be extended for much longer until an effective reorientation of consciousness occurs. Scientific researches and discussions are fundamental tools to the understanding of issues still little explored in this field.
Background Climate change is increasing the risks of injuries, diseases, and deaths globally. However, the association between ambient temperature and renal diseases has not been fully characterized. This study aimed to quantify the risk and attributable burden for hospitalizations of renal diseases related to ambient temperature. Methods Daily hospital admission data from 1816 cities in Brazil were collected during 2000 and 2015. A time-stratified case-crossover design was applied to evaluate the association between temperature and renal diseases. Relative risks (RRs), attributable fractions (AFs), and their confidence intervals (CIs) were calculated to estimate the associations and attributable burden. Findings A total of 2,726,886 hospitalizations for renal diseases were recorded during the study period. For every (1) over barC increase in daily mean temperature, the estimated risk of hospitalization for renal diseases over lag 0-7 days increased by 0 center dot 9% (RR = 1 center dot 009, 95% CI: 1 center dot 008-1 center dot 010) at the national level. The associations between temperature and renal diseases were largest at lag 0 days but remained for lag 1-2 days. The risk was more prominent in females, children aged 0-4 years, and the elderly >= 80 years. 7 center dot 4% ( 95% CI: 5 center dot 2-9 center dot 6%) of hospitalizations for renal diseases could be attributable to the increase of temperature, equating to 202,093 (95% CI: 141,554- 260,594) cases. Interpretation This nationwide study provides robust evidence that more policies should be developed to prevent heat-related hospitalizations and mitigate climate change. Copyright (c) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Climate change is drastically altering the frequency, duration, and severity of compound drought-heatwave (CDHW) episodes, which present a new challenge in environmental and socioeconomic sectors. These threats are of particular importance in low-income regions with growing populations, fragile infrastructure, and threatened ecosystems. This review synthesizes emerging progress in the understanding of CDHW patterns in Brazil while providing insights about the impacts on fire occurrence and public health. Evidence is mounting that heatwaves are becoming increasingly linked with droughts in northeastern and southeastern Brazil, the Amazonia, and the Pantanal. In those regions, recent studies have begun to build a better understanding of the physical mechanisms behind CDHW events, such as the soil moisture-atmosphere coupling, promoted by exceptional atmospheric blocking conditions. Results hint at a synergy between CDHW events and high fire activity in the country over the last decades, with the most recent example being the catastrophic 2020 fires in the Pantanal. Moreover, we show that HWs were responsible for increasing mortality and preterm births during record-breaking droughts in southeastern Brazil. This work paves the way for a more in-depth understanding on CDHW events and their impacts, which is crucial to enhance the adaptive capacity of different Brazilian sectors.
People living in areas vulnerable to diseases caused by extreme climate change events, such as semiarid regions, tend to recognize them quickly and, consequently, develop strategies to cope with their effects. Our study investigated the perception of diseases by farmers living in the semiarid region of Northeastern Brazil and the adaptive strategies locally developed and used. To this end, the effect of the incidence and severity of locally perceived diseases on the frequency of adaptive responses adopted by the farmers was tested. The research was conducted in rural communities in the Pernambuco State, Northeastern Region of Brazil. Semi-structured interviews with 143 farmers were conducted to collect information about major drought and rainfall events, the perceived diseases related to these events, and the adaptive strategies developed to mitigate them. The incidence and severity of diseases perceived by farmers were calculated using the Participatory Risk Mapping method and the frequency of adaptive strategies. Our findings demonstrated that few climate change-related diseases were frequently mentioned by farmers, indicating low incidence rates. Among them, direct transmission diseases were the most frequently mentioned. Adaptive strategies to deal with the mentioned diseases related to prophylactic behavior were less mentioned, except if already utilized. Our model demonstrated that incidence was the only explanatory variable with a significant impact on the adaptive strategies used to deal with the effects of these risks on health. Our findings suggest that the estimated incidence of diseases should be considered in the development of predictive climate change models for government policy measures for the public health security of populations in areas of greater socio-environmental vulnerability.
The gradual increase in temperatures and changes in relative humidity, added to the aging and socioeconomic conditions of the population, may represent problems for public health, given that future projections predict even more noticeable changes in the climate and the age pyramid, which require analyses at an appropriate spatial scale. To our knowledge, an analysis of the synergic effects of several climatic and socioeconomic conditions on hospital admissions and deaths by cardiorespiratory and mental disorders has not yet been performed in Brazil. Statistical analyses were performed using public time series (1996-2015) of daily health and meteorological data from 16 metropolitan regions (in a subtropical climate zone in South America). Health data were stratified into six groups according to gender and age ranges (40-59; 60-79; and ≥80 years old) for each region. For the regression analysis, two distributions (Poisson and binomial negative) were tested with and without zero adjustments for the complete series and percentiles. Finally, the relative risks were calculated, and the effects based on exposure-response curves were evaluated and compared among regions. The negative binomial distribution fit the data best. High temperatures and low relative humidity were the most relevant risk factors for hospitalizations for cardiovascular diseases (lag = 0), while minimum temperatures were important for respiratory diseases (lag = 2 or 3 days). Temperature extremes, both high and low, were the most important risk factors for mental illnesses at lag 0. Groups with people over 60 years old presented higher risks for cardiovascular and respiratory diseases, while this was observed for the adult group (40-59 years old) in relation to mental disorders. In general, no major differences were found in the results between men and women. However, regions with higher urbanization levels presented risks, mainly for respiratory diseases, while the same was observed for cardiovascular diseases for regions with lower levels of urbanization. The Municipal Human Development Index is an important factor for the occurrence of diseases and deaths for all regions, depending on the evaluated group, representing high risks for health outcomes (the value for hospitalization for cardiovascular diseases was 1.6713 for the female adult group in the metropolitan region Palmas, and the value for hospitalization for respiratory diseases was 1.7274 for the female adult group in the metropolitan region Campo Mourão). In general, less developed regions have less access to adequate health care and better living conditions.
BACKGROUND: There is an urgent need for more information about the climate change impact on health in order to strengthen the commitment to tackle climate change. However, few studies have quantified the health impact of climate change in Brazil and in the Latin America region. In this paper, we projected the impacts of temperature on cardiovascular (CVD) mortality according to two climate change scenarios and two regionalized climate model simulations in Brazilian cities. METHODS: We estimated the temperature-CVD mortality relationship in 21 Brazilian cities, using distributed lag non-linear models in a two-stage time-series analysis. We combined the observed exposure-response functions with the daily temperature projected under two representative concentration pathways (RCP), RCP8.5 and RCP4.5, and two regionalized climate model simulations, Eta-HadGEM2-ES and Eta-MIROC5. RESULTS: We observed a trend of reduction in mortality related to low temperatures and a trend of increase in mortality related to high temperatures, according to all the investigated models and scenarios. In most places, the increase in mortality related to high temperatures outweighed the reduction in mortality related to low temperatures, causing a net increase in the excess temperature-related mortality. These trends were steeper according to the higher emission scenario, RCP8.5, and to the Eta-HadGEM2-ES model. According to RCP8.5, our projections suggested that the temperature-related mortality fractions in 2090-99 compared to 2010-2019 would increase by 8.6% and 1.7%, under Eta-HadGEM2-ES and Eta-MIROC5, respectively. According to RCP4.5, these values would be 0.7% and -0.6%. CONCLUSIONS: For the same climate model, we observed a greater increase trend in temperature-CVD mortality according to RCP8.5, highlighting a greater health impact associated with the higher emission scenario. Our results may be useful to support public policies and strategies for mitigation of and adaptation to climate change, particularly in the health sector.
BACKGROUND: Extreme temperatures may lead to adverse pregnancy and birth outcomes, including low birthweight. Studies on the impact of temperature on birthweight have been inconclusive due to methodological challenges related to operationalizing temperature exposure, the definitions of exposure windows, accounting for gestational age, and a limited geographic scope. METHODS: We combined data on individual-level term live births (N≈15 million births) from urban areas in Brazil, Chile, and Mexico from 2010 to 2015 from the SALURBAL study (Urban Health in Latin America) with high-resolution daily air temperature data and computed average ambient temperature for every month of gestation for each newborn. Associations between full-term birthweight and average temperature during gestation were analyzed using multi-level distributed lag non-linear models that adjusted for newborn’s sex, season of conception, and calendar year of child’s birth; controlled for maternal age, education, partnership status, presence of previous births, and climate zone; and included a random term for the sub-city of mother’s residence. FINDINGS: Higher temperatures during the entire gestation are associated with lower birthweight, particularly in Mexico and Brazil. The cumulative effect of temperature on birthweight is mostly driven by exposure to higher temperatures during months 7-9 of gestation. Higher maternal education can attenuate the temperature-birthweight associations. INTERPRETATION: Our work shows that climate-health impacts are likely to be context- and place-specific and warrants research on temperature and birthweight in diverse climates to adequately anticipate global climate change. Given the high societal cost of suboptimal birthweight, public health efforts should be aimed at diminishing the detrimental effect of higher temperatures on birthweight. FUNDING: The Wellcome Trust.
Climate change and urbanization are rapidly increasing human exposure to extreme ambient temperatures, yet few studies have examined temperature and mortality in Latin America. We conducted a nonlinear, distributed-lag, longitudinal analysis of daily ambient temperatures and mortality among 326 Latin American cities between 2002 and 2015. We observed 15,431,532 deaths among ≈2.9 billion person-years of risk. The excess death fraction of total deaths was 0.67% (95% confidence interval (CI) 0.58-0.74%) for heat-related deaths and 5.09% (95% CI 4.64-5.47%) for cold-related deaths. The relative risk of death was 1.057 (95% CI 1.046-1.067%) per 1 °C higher temperature during extreme heat and 1.034 (95% CI 1.028-1.040%) per 1 °C lower temperature during extreme cold. In Latin American cities, a substantial proportion of deaths is attributable to nonoptimal ambient temperatures. Marginal increases in observed hot temperatures are associated with steep increases in mortality risk. These risks were strongest among older adults and for cardiovascular and respiratory deaths.
BACKGROUND: In Latin America, where climate change and rapid urbanization converge, non-optimal ambient temperatures contribute to excess mortality. However, little is known about area-level characteristics that confer vulnerability to temperature-related mortality. OBJECTIVES: Explore city-level socioeconomic and demographic characteristics associated with temperature-related mortality in Latin American cities. METHODS: The dependent variables quantify city-specific associations between temperature and mortality: heat- and cold-related excess death fractions (EDF, or percentages of total deaths attributed to cold/hot temperatures), and the relative mortality risk (RR) associated with 1 °C difference in temperature in 325 cities during 2002-2015. Random effects meta-regressions were used to investigate whether EDFs and RRs associated with heat and cold varied by city-level characteristics, including population size, population density, built-up area, age-standardized mortality rate, poverty, living conditions, educational attainment, income inequality, and residential segregation by education level. RESULTS: We find limited effect modification of cold-related mortality by city-level demographic and socioeconomic characteristics and several unexpected associations for heat-related mortality. For example, cities in the highest compared to the lowest tertile of income inequality have all-age cold-related excess mortality that is, on average, 3.45 percentage points higher (95% CI: 0.33, 6.56). Higher poverty and higher segregation were also associated with higher cold EDF among those 65 and older. Large, densely populated cities, and cities with high levels of poverty and income inequality experience smaller heat EDFs compared to smaller and less densely populated cities, and cities with little poverty and income inequality. DISCUSSION: Evidence of effect modification of cold-related mortality in Latin American cities was limited, and unexpected patterns of modification of heat-related mortality were observed. Socioeconomic deprivation may impact cold-related mortality, particularly among the elderly. The findings of higher levels of poverty and income inequality associated with lower heat-related mortality deserve further investigation given the increasing importance of urban adaptation to climate change.
Changes in climatic patterns are expected to have significant effects on health and wellbeing. However, the literature on the effect of climate on subjective wellbeing remains scant and existing studies focus mostly on developed countries or cross-country analyses. This paper aims to identify the relationship between climate conditions on happiness after controlling for individual and social characteristics. Ecuador, a geographically fragmented country with varying climate conditions across municipalities, constitutes an ideal case study to assess the effect of climate variables on happiness. We employ a cross-section analysis to identify the effect of temperature, precipitation and humidity on happiness. The paper shows that climate conditions constitute an important determinant of people’s subjective wellbeing. The results also suggest that income and education attenuate the effect of temperature on happiness and that substantial differences are observed depending on whether places are hot/humid or cold/dry.
Extreme heat events result in higher indoor temperatures in buildings, increased energy consumption, and more frequent health problems, mainly between the children, the elderly over 65, and vulnerable low-income people. The indoor environment plays a key role in reducing the effects of extreme heat events. While the benefits of passive cooling measures on thermal and environmental aspects are well known, their effects on resilience are less well explored. This paper aims at studying the indoor environment in low-income housing from the energy and heat resilience points of view, during extreme hot periods, together with possible passive cooling measures to be applied in the houses in order to improve both, heat resilience and energy efficiency. A low-income neighbourhood in La Pampa, central Argentina, was selected as a case study. Transient thermal simulation, electricity consumption bills obtained from the Energy Company, and health statistics from the data-base of the nearby hospital were used. We conclude that the houses are not capable to manage hot/heat wave periods in a resilient way because of their energy inefficient design. Moreover, the cooling equipment is sub-used due to economic reasons. Indoor temperatures exceeded 33 degrees C and Heat Index reached “Extreme caution” health risk level. Sudden changes in the meteorological conditions seems to increase the number of consultations of health disorders previous or after the hot periods. The best set of passive strategies is to favour night ventilation together with shading of the envelope (i.e., by trees, climbing plants, green walls, or by installing ventilated opaque facades) and an improved roof (light colour coating and addition of thermal insulation). These strategies could both, improve the heat resilience and the thermal behavior of the indoor environment while reducing the electricity consumption in the hottest months of summer. (C) 2020 Elsevier B.V. All rights reserved.
Increased frequency of heat waves (HWs) is one of the prominent consequences of climate change. Its impact on human health has been mostly reported in the northern hemisphere but has been poorly studied in the southern hemisphere. The aim of this study was to analyze the effects of the HWs waves occurred in the warm season 2013-14 on mortality in the center-north region of Argentina, where 22 million people live. It was carried out an observational study of ecological-type contrasting the mortality occurred during the HWs of the summer 2013-14 with the mortality in the summers 2010-11 to 2012-13, free from HWs. The mortality was analyzed according to the following variables: place of residence, age, sex and cause of death. During the HWs of the summer 2013-14, 1877 (RR=1.23, 95%CI 1.20-1.28) deaths in excess were registered. Moreover, the death risk significantly increased in 13 of the 18 provinces analyzed. The mortality rates by sex revealed heterogeneous behaviour regarding both the time and spatial scale. The death risk increased with age; it was particularly significant in four provinces for the 60-79 years group and in six provinces in people of 80 years and over. The death causes that showed significantly increments were respiratory, cardiovascular, renal diseases and diabetes.
Complete savannization of the Amazon Basin would enhance the effects of climate change on local heat exposure and pose a risk to human health, according to climate model projections. Land use change and deforestation can influence local temperature and climate. Here we use a coupled ocean-atmosphere model to assess the impact of savannization of the Amazon Basin on the wet-bulb globe temperature heat stress index under two climate change scenarios (RCP4.5 and RCP8.5). We find that heat stress exposure due to deforestation was comparable to the effect of climate change under RCP8.5. Our findings suggest that heat stress index could exceed the human adaptation limit by 2100 under the combined effects of Amazon savannization and climate change. Moreover, we find that risk of heat stress exposure was highest in Northern Brazil and among the most socially vulnerable. We suggest that by 2100, savannization of the Amazon will lead to more than 11 million people will be exposed heat stress that poses an extreme risk to human health under a high emission scenario.
The aim of this study was to evaluate heat exposure, dehydration, and kidney function in rice workers over the course of three months, in Guanacaste, Costa Rica. We collected biological and questionnaire data across a three-month-period in male field (n = 27) and other (n = 45) workers from a rice company where chronic kidney disease of unknown origin (CKDu) is endemic. We used stepwise forward regression to determine variables associated with estimated glomerular filtration rate eGFR at enrollment and/or change in eGFR, and Poisson regression to assess associations with incident kidney injury (IKI) over the course of three months. Participants were 20−62 years old (median = 40 in both groups). Dehydration was common (≥37%) in both groups, particularly among other workers at enrollment, but field workers were more exposed to heat and had higher workloads. Low eGFR (<60 mL/min/1.73 m2) was more prevalent in field workers at enrollment (19% vs. 4%) and follow-up (26% vs. 7%). Field workers experienced incident kidney injury (IKI) more frequently than other workers: 26% versus 2%, respectively. Age (β = −0.71, 95%CI: −1.1, −0.4), current position as a field worker (β = −2.75, 95%CI: −6.49, 0.99) and past work in construction (β = 3.8, 95%CI: −0.1, 7.6) were included in the multivariate regression model to explain eGFR at enrollment. The multivariate regression model for decreased in eGFR over three month included current field worker (β = −3.9, 95%CI: −8.2, 0.4), current smoking (β= −6.2, 95%CI: −13.7−1.3), dehydration (USG ≥ 1.025) at both visits (β= −3.19, 95%CI: −7.6, 1.2) and pain medication at follow-up (β= −3.2, 95%CI: −8.2, 1.95). Current fieldwork [IR (incidence rate) = 2.2, 95%CI 1.1, 5.8) and being diabetic (IR = 1.8, 95%CI 0.9, 3.6) were associated with IKI. Low eGFR was common in field workers from a rice company in Guanacaste, and being a field worker was a risk factor for IKI, consistent with the hypothesis that occupational heat exposure is a critical risk factor for CKDu in Mesoamerica.
Extreme weather conditions, including intense heat stress due to higher temperatures, could trigger an increase in mortality risk. One way to evaluate the increase in mortality risk due to higher temperatures is the high risk warming (HRW) index, which evaluates the difference between the future and base period of a given percentile of daily maximum temperature (Tmax). Another is to calculate the future increase in the number of days over the temperature of such percentile, named high risk days (HRD) index. Previous studies point to the 84th percentile as the optimum temperature. Thus, this study aims to evaluate HRW and HRD indexes in Ecuador from 2011 to 2070 over the three natural climate zones, e.g., Coast, Andes, and Amazon. This climate analysis is based on historical data from meteorological stations and projections from CSIRO-MK36, GISS-E2, and IPSL-CM5A-MR, CMIP5 global climate models with dynamical scale reduction through weather research forecasting (WRF). The representative concentration pathways (RCPs), 8.5, were considered, which are related to the highest increases in future temperature. The results indicate that HRW and HRD will experience a larger increase in the period 2041-2070 compared with the period 1980-2005; in particular, these two indices will have a progressively increasing trend from 2011 onward. Specifically, the HRW calculated from the CMIP5 models for all stations is expected to grow from 0.6 degrees C to 1.4 degrees C and 1.8 degrees C to 4.6 degrees C for 2010-2040 and 2041-2070, respectively. Also, it is expected that the HRD for all stations will increase from 42 to 74 and 120 to 227 warming days for 2011-2040 and 2041-2070, respectively. The trends derived using Sen’s slope test show an increase in the HRW between 0.5 degrees C and 0.9 degrees C/decade and of the HRD between 2.88 and 4.9 days/decade since 1985. These results imply a high increase in heat-related mortality risks related to climate change in Ecuador. In terms of spatial distribution, three Ecuadorian regions experienced more critical temperature conditions with higher values of HRW and HRD for 2070. As a response to the increased frequency trends of warming periods in tropical areas, urgent measures should be taken to review public policies and legislation to mitigate the impacts of heat as a risk for human health in Ecuador.
An ongoing epidemic of chronic kidney disease of uncertain etiology (CKDu) afflicts large parts of Central America and is hypothesized to be linked to heat stress at work. Mortality rates from CKDu appear to have increased dramatically since the 1970s. To explore this relationship, we assessed trends in maximum and minimum temperatures during harvest months between 1973 and 2014 as well as in the number of days during the harvest season for which the maximum temperature surpassed 35 °C. Data were collected at a weather station at a Nicaraguan sugar company where large numbers of workers have been affected by CKDu. Monthly averages of the daily maximum temperatures between 1996 and 2014 were also compared to concurrent weather data from eight Automated Surface Observing System Network weather stations across Nicaragua. Our objectives were to assess changes in temperature across harvest seasons, estimate the number of days that workers were at risk of heat-related illness and compare daily maximum temperatures across various sites in Nicaragua. The monthly average daily maximum temperature during the harvest season increased by 0.7 °C per decade between 1973 and 1990. The number of days per harvest season with a maximum temperature over 35 °C increased by approximately five days per year between 1974 and 1990, from 32 days to 114 days. Between 1991 and 2013, the number of harvest days with a maximum temperature over 35 °C decreased by two days per year, and the monthly average daily maximum temperature decreased by 0.3 °C per decade. Comparisons with weather stations across Nicaragua demonstrate that this company is located in one of the consistently hottest regions of the country.
Climate change has increased heat exposure in many parts of the tropics, negatively impacting outdoor worker productivity and health. Although it is known that tropical deforestation is associated with local warming, the extent to which this additional heat exposure affects people across the tropics is unknown. In this modeling study, we combine worker health guidelines with satellite, reanalysis, and population data to investigate how warming associated with recent deforestation (2003-2018) affects outdoor working conditions across low-latitude countries, and how future global climate change will magnify heat exposure for people in deforested areas. We find that the local warming from 15 years of deforestation was associated with losses in safe thermal working conditions for 2.8 million outdoor workers. We also show recent large-scale forest loss was associated with particularly large impacts on populations in locations such as the Brazilian states of Mato Grosso and Para ‘. Future global warming and additional forest loss will magnify these impacts.
BACKGROUND: Mesoamerica is severely affected by an epidemic of Chronic Kidney Disease of non-traditional origin (CKDnt), an epidemic with a marked variation within countries. We sought to describe the spatial distribution of CKDnt in Mesoamerica and examine area-level crop and climate risk factors. METHODS: CKD mortality or hospital admissions data was available for five countries: Mexico, Guatemala, El Salvador, Nicaragua and Costa Rica and linked to demographic, crop and climate data. Maps were developed using Bayesian spatial regression models. Regression models were used to analyze the association between area-level CKD burden and heat and cultivation of four crops: sugarcane, banana, rice and coffee. RESULTS: There are regions within each of the five countries with elevated CKD burden. Municipalities in hot areas and much sugarcane cultivation had higher CKD burden, both compared to equally hot municipalities with lower intensity of sugarcane cultivation and to less hot areas with equally intense sugarcane cultivation, but associations with other crops at different intensity and heat levels were not consistent across countries. CONCLUSION: Mapping routinely collected, already available data could be a first step to identify areas with high CKD burden. The finding of higher CKD burden in hot regions with intense sugarcane cultivation which was repeated in all five countries agree with individual-level studies identifying heavy physical labor in heat as a key CKDnt risk factor. In contrast, no associations between CKD burden and other crops were observed.
Recife is recognized as the 16th most vulnerable city to climate change in the world. In addition, the city has levels of air pollutants above the new limits proposed by the World Health Organization (WHO) in 2021. In this sense, the present study had two main objectives: (1) To evaluate the health (and economic) benefits related to the reduction in mean annual concentrations of PM(10) and PM(2.5) considering the new limits recommended by the WHO: 15 µg/m(3) (PM(10)) and 5 µg/m(3) (PM(2.5)) and (2) To simulate the behavior of these pollutants in scenarios with increased temperature (2 and 4 °C) using machine learning. The averages of PM(2.5) and PM(10) were above the limits recommended by the WHO. The scenario simulating the reduction in these pollutants below the new WHO limits would avoid more than 130 deaths and 84 hospital admissions for respiratory or cardiovascular problems. This represents a gain of 15.2 months in life expectancy and a cost of almost 160 million dollars. Regarding the simulated temperature increase, the most conservative (+ 2 °C) and most drastic (+ 4 °C) scenarios predict an increase of approximately 6.5 and 15%, respectively, in the concentrations of PM(2.5) and PM(10), with a progressive increase in deaths attributed to air pollution. The study shows that the increase in temperature will have impacts on air particulate matter and health outcomes. Climate change mitigation and pollution control policies must be implemented for meeting new WHO air quality standards which may have health benefits.
This research concerns the identification of a pattern between the occurrence of extreme weather conditions, such as cold waves and heat waves, and hospitalization for cardiovascular diseases (CVDs), in the University Hospital of Santa Maria (HUSM) in southern Brazil between 2012 and 2017. The research employed the field experiment method to measure the biometeorological parameters associated with hospital admissions in different seasons, such as during extreme weather conditions such as a cold wave (CW) or a heat wave (HW), using five thermal comfort indices: physiologically equivalent temperature (PET), new standard effective temperature (SET), predicted mean vote (PMV), effective temperatures (ET), and effective temperature with wind (ETW). The hospitalizations were recorded as 0.775 and 0.726 admissions per day for the winter and entire study periods, respectively. The records for extreme events showed higher admission rates than those on average days. The results also suggest that emergency hospitalizations for heart diseases during extreme weather events occurred predominantly on days with thermal discomfort. Furthermore, there was a particularly high risk of hospitalization for up to seven days after the end of the CW. Further analyses showed that cardiovascular hospitalizations were higher in winter than in summer, suggesting that CWs are more life threatening in wintertime.
A thermal comfort index for the Northeast of Brazil was analyzed for two scenarios of climatic changes, A1B and A2, for 2021-2080, and compared with the reference period 1961-1990. A technique of regionalization was applied to rainfall, maximum and minimum temperature data from meteorological stations, obtained by statistical downscaling of projections from four global climate models. The results pointed to a significant reduction of rainfall and an increase of temperature for three different climatically homogeneous subregions. Regarding the thermal comfort index, the results point to an increase in days with heat discomfort between 2021 and 2080. In the northern portion, the higher percentage of days with heat discomfort will be significant since the first half of the period under appreciation, i.e., from 2021 to 2050. Conversely, in the eastern of northeastern Brazil, the increase of days with heat discomfort should happen in the period from 2051 to 2080, whereas the central-western part of the region, which, in the reference period, had recorded less than 1% of days with heat discomfort, might see an elevation of that percentage to 7% between 2021 and 2050, potentially reaching 48% of its days made uncomfortable by heat between 2051 and 2080.
This work is taken up to evaluate the relationship between the thermal comfort of spectators and athletes and the prevailing meteorological conditions during Rio 2016 Olympic Games. Empirical and physiological thermal comfort indices are calculated from data collected from an automatic weather station installed near the Olympic Stadium and interviews with the spectators. The study period was marked by a gradual rise in air temperature and by the occurrence of two significant weather events associated with wind gusts, which caused disturbances in some areas of the competitions. ET and NET were below the air temperature, indicating that both humidity and wind contributed to the reduction of the human-biometeorological indices. Majority of the interviewed persons reported comfortable sensation and weather conditions. These perceptions corroborate results of the thermal comfort indices calculated for these resting spectators. The comfort indices calculated for the athletes with high level of physical activity showed that PET estimated hotter thermal sensation those for the individuals at rest, indicating that the physical type of a person may strongly influence the thermal sensation and comfort during intense physical activity. Increasing trend observed in all the indices of human thermal comfort during the period of study shows consistency among them.
The present analysis uses the data of confirmed incidence of dengue cases in the metropolitan region of Panama from 1999 to 2017 and climatic variables (air temperature, precipitation, and relative humidity) during the same period to determine if there exists a correlation between these variables. In addition, we compare the predictive performance of two regression models (SARIMA, SARIMAX) and a recurrent neural network model (RNN-LSTM) on the dengue incidence series. For this data from 1999-2014 was used for training and the three subsequent years of incidence 2015-2017 were used for prediction. The results show a correlation coefficient between the climatic variables and the incidence of dengue were low but statistical significant. The RMSE and MAPE obtained for the SARIMAX and RNN-LSTM models were 25.76, 108.44 and 26.16, 59.68, which suggest that any of these models can be used to predict new outbreaks. Although, it can be said that there is a limited role of climatic variables in the outputs the models. The value of this work is that it helps understand the behaviour of cases in a tropical setting as is the Metropolitan Region of Panama City, and provides the basis needed for a much needed early alert system for the region.
Dengue fever has been endemic in Paraguay since 2009 and is a major cause of public-health-management-related burdens. However, Paraguay still lacks information on the association between climate factors and dengue fever. We aimed to investigate the association between climatic factors and dengue fever in Asuncion. Cumulative dengue cases from January 2014 to December 2020 were extracted weekly, and new cases and incidence rates of dengue fever were calculated. Climate factor data were aggregated weekly, associations between dengue cases and climate factors were analyzed, and variables were selected to construct our model. A generalized additive model was used, and the best model was selected based on Akaike information criteria. Piecewise regression analyses were performed for non-linear climate factors. Wind and relative humidity were negatively associated with dengue cases, and minimum temperature was positively associated with dengue cases when the temperature was less than 21.3 °C and negatively associated with dengue when greater than 21.3 °C. Additional studies on dengue fever in Asuncion and other cities are needed to better understand dengue fever.
Climate is considered an important factor in the temporal and spatial distribution of vector-borne diseases. Dengue transmission involves many factors: although it is not yet fully understood, climate is a critical factor as it facilitates risk analysis of epidemics. This study analyzed the effect of seasonal factors and the relationship between climate variables and dengue risk in the municipality of Campo Grande, from 2008 to 2018. Generalized linear models with negative binomial and Poisson distribution were used. The most appropriate model was the one with “minimum temperature” and “precipitation”, both lagged by one month, controlled by “year”. In this model, a 1 degrees C rise in the minimum temperature of one month led to an increase in dengue cases the following month, while a 10 mm increase in precipitation led to an increase in dengue cases the following month.
Dengue fever is a serious and growing public health problem in Latin America and elsewhere, intensified by climate change and human mobility. This paper reviews the approaches to the epidemiological prediction of dengue fever using the One Health perspective, including an analysis of how Machine Learning techniques have been applied to it and focuses on the risk factors for dengue in Latin America to put the broader environmental considerations into a detailed understanding of the small-scale processes as they affect disease incidence. Determining that many factors can act as predictors for dengue outbreaks, a large-scale comparison of different predictors over larger geographic areas than those currently studied is lacking to determine which predictors are the most effective. In addition, it provides insight into techniques of Machine Learning used for future predictive models, as well as general workflow for Machine Learning projects of dengue fever.
The expansion of the invasive mosquito Aedes aegypti L. (Diptera: Culicidae) towards temperate regions in the Americas is causing concern because of its public health implications. As for other insects, the distribution limits of Ae. aegypti have been suggested to be related to minimum temperatures and to be controlled mainly by cold tolerance. The aim of this study was to assess the daily mortality of immature stages of Ae. aegypti under natural winter conditions in Buenos Aires, Argentina, in relation to preceding thermal conditions. The experiment was performed outdoors, and one cohort of larvae was started each week for 16 weeks, and reared up to the emergence of the adults. Three times a week, larvae, pupae and emerged adults were counted, and these data were used to calculate the daily mortality of larvae, pupae and adults and to analyze their relationship with thermal conditions. The results showed that mortality was generally low, with a few peaks of high mortality after cold front events. The mortality of pupae and larvae showed a higher correlation with the cooling degree hours of previous days than with the minimum, maximum or mean temperatures. Pupae and adults showed to be more vulnerable to low temperatures than larvae. A delay in mortality was observed in relation to the low temperature events, with a proportion of individuals dying in a later stage after the end of the cold front. These results suggest that thermal conditions during cold fronts in Buenos Aires are close to the tolerance limit of the local Ae. aegypti population. The wide range of responses of different individuals suggests that low winter temperatures may constitute a selective force, leading the population to a higher tolerance to low temperatures, which might favor the further expansion of this species towards colder regions.
BACKGROUND: Temperature and rainfall patterns are known to influence seasonal patterns of dengue transmission. However, the effect of severe drought and extremely wet conditions on the timing and intensity of dengue epidemics is poorly understood. In this study, we aimed to quantify the non-linear and delayed effects of extreme hydrometeorological hazards on dengue risk by level of urbanisation in Brazil using a spatiotemporal model. METHODS: We combined distributed lag non-linear models with a spatiotemporal Bayesian hierarchical model framework to determine the exposure-lag-response association between the relative risk (RR) of dengue and a drought severity index. We fit the model to monthly dengue case data for the 558 microregions of Brazil between January, 2001, and January, 2019, accounting for unobserved confounding factors, spatial autocorrelation, seasonality, and interannual variability. We assessed the variation in RR by level of urbanisation through an interaction between the drought severity index and urbanisation. We also assessed the effect of hydrometeorological hazards on dengue risk in areas with a high frequency of water supply shortages. FINDINGS: The dataset included 12 895 293 dengue cases reported between 2001 and 2019 in Brazil. Overall, the risk of dengue increased between 0-3 months after extremely wet conditions (maximum RR at 1 month lag 1·56 [95% CI 1·41-1·73]) and 3-5 months after drought conditions (maximum RR at 4 months lag 1·43 [1·22-1·67]). Including a linear interaction between the drought severity index and level of urbanisation improved the model fit and showed the risk of dengue was higher in more rural areas than highly urbanised areas during extremely wet conditions (maximum RR 1·77 [1·32-2·37] at 0 months lag vs maximum RR 1·58 [1·39-1·81] at 2 months lag), but higher in highly urbanised areas than rural areas after extreme drought (maximum RR 1·60 [1·33-1·92] vs 1·15 [1·08-1·22], both at 4 months lag). We also found the dengue risk following extreme drought was higher in areas that had a higher frequency of water supply shortages. INTERPRETATION: Wet conditions and extreme drought can increase the risk of dengue with different delays. The risk associated with extremely wet conditions was higher in more rural areas and the risk associated with extreme drought was exacerbated in highly urbanised areas, which have water shortages and intermittent water supply during droughts. These findings have implications for targeting mosquito control activities in poorly serviced urban areas, not only during the wet and warm season, but also during drought periods. FUNDING: Royal Society, Medical Research Council, Wellcome Trust, National Institutes of Health, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, and Conselho Nacional de Desenvolvimento Científico e Tecnológico. TRANSLATION: For the Portuguese translation of the abstract see Supplementary Materials section.
Leishmaniasis is a public health problem worldwide. We aimed to predict ecological niche models (ENMs) for visceral (VL) and cutaneous (CL) leishmaniasis and the sand flies involved in the transmission of leishmaniasis in São Paulo, Brazil. Phlebotomine sand flies were collected between 1985 and 2015. ENMs were created for each sand fly species using Maximum Entropy Species Distribution Modeling software, and 20 climatic variables were determined. Nyssomyia intermedia (Lutz & Neiva, 1912) and Lutzomyia longipalpis (Lutz & Neiva, 1912), the primary vectors involved in CL and VL, displayed the highest suitability across the various regions, climates, and topographies. L. longipalpis was found in the border of Paraná an area currently free of VL. The variables with the greatest impact were temperature seasonality, precipitation, and altitude. Co-presence of multiple sand fly species was observed in the cuestas and coastal areas along the border of Paraná and in the western basalt areas along the border of Mato Grosso do Sul. Human CL and VL were found in 475 of 546 (86.7%) and 106 of 645 (16.4%) of municipalities, respectively. Niche overlap between N. intermedia and L. longipalpis was found with 9208 human cases of CL and 2952 cases of VL. ENMs demonstrated that each phlebotomine sand fly species has a unique geographic distribution pattern, and the occurrence of the primary vectors of CL and VL overlapped. These data can be used by public authorities to monitor the dispersion and expansion of CL and VL vectors in São Paulo state.
INTRODUCTION: Zika virus (ZIKV) is primarily transmitted byAedes aegypti and Aedes albopictus mosquitoes between humans and non-human primates. Climate change may enhance virus reproduction in Aedes spp. mosquito populations, resulting in intensified ZIKV outbreaks. The study objective was to explore how an outbreak similar to the 2016 ZIKV outbreak in Brazil might unfold with projected climate change. METHODS: A compartmental infectious disease model that included compartments for humans and mosquitoes was developed to fit the 2016 ZIKV outbreak data from Brazil using least squares optimization. To explore the impact of climate change, published polynomial relationships between temperature and temperature-sensitive mosquito population and virus transmission parameters (mosquito mortality, development rate, and ZIKV extrinsic incubation period) were used. Projections for future outbreaks were obtained by simulating transmission with effects of projected average monthly temperatures on temperature-sensitive model parameters at each of three future time periods: 2011-2040, 2041-2070, and 2071-2100. The projected future climate was obtained from an ensemble of regional climate models (RCMs) obtained from the Co-Ordinated Regional Downscaling Experiment (CORDEX) that used Representative Concentration Pathways (RCP) with two radiative forcing values, RCP4.5 and RCP8.5. A sensitivity analysis was performed to explore the impact of temperature-dependent parameters on the model outcomes. RESULTS: Climate change scenarios impacted the model outcomes, including the peak clinical case incidence, cumulative clinical case incidence, time to peak incidence, and the duration of the ZIKV outbreak. Comparing 2070-2100 to 2016, using RCP4.5, the peak incidence was 22,030 compared to 10,473; the time to epidemic peak was 12 compared to 9 weeks, and the outbreak duration was 52 compared to 41 weeks. Comparing 2070-2100 to 2016, using RCP8.5, the peak incidence was 21,786 compared to 10,473; the time to epidemic peak was 11 compared to 9 weeks, and the outbreak duration was 50 compared to 41weeks. The increases are due to optimal climate conditions for mosquitoes, with the mean temperature reaching 28 °C in the warmest months. Under a high emission scenario (RCP8.5), mean temperatures extend above optimal for mosquito survival in the warmest months. CONCLUSION: Outbreaks of ZIKV in locations similar to Brazil are expected to be more intense with a warming climate. As climate change impacts are becoming increasingly apparent on human health, it is important to quantify the effect and use this knowledge to inform decisions on prevention and control strategies.
In Brazil, approximately 99% of malaria cases are concentrated in the Amazon region. An acute febrile infectious disease, malaria is closely related to climatic and hydrological factors. Environmental variables such as rainfall, flow, level, and color of rivers, the latter associated with the suspended sediment concentration, are important factors that can affect the dynamics of the incidence of some infectious diseases, including malaria. This study explores the possibility that malaria incidence is influenced by precipitation, fluctuations in river levels, and suspended sediment concentration. The four studied municipalities are located in two Brazilian states (Amazonas and Para) on the banks of rivers with different hydrological characteristics. The results suggest that precipitation and river level fluctuations modulate the seasonal pattern of the disease and evidence the existence of delayed effects of river floods on malaria incidence. The seasonality of the disease has a different influence in each municipality studied. However, municipalities close to rivers with the same characteristic color of waters (as a function of the concentration of suspended sediments) have similar responses to the disease.
BACKGROUND: Human leptospirosis is responsible for great losses and deaths, especially in developing countries, which can be mitigated by knowing the correct health indicators and climate influence on the disease. METHODS: Leptospirosis cases and deaths, population and precipitation were recovered from different databases (2007-2019). Annual incidence, mortality and case fatality rates (CFRs) of human leptospirosis and average precipitation were calculated for Brazil and its regions. Time series analysis using an moving average with external variable (ARMAX) model was used to analyse the monthly contribution and precipitation influence over leptospirosis cases for each Brazilian region and for the whole country. A forecast model to predict cases for 2020 was created for Brazil. RESULTS: Human leptospirosis exhibited heterogeneous distribution among Brazilian regions, with most cases occurring during the rainy season and precipitation influenced the disease occurrence in all regions but the South. The forecast model predicted 3276.99 cases for 2020 (mean absolute percentage error 14.680 and root mean square error 53.013). Considering the annual average for the period, the leptospirosis incidence was 1913 cases per 100 000 inhabitants, mortality was 0.168 deaths per 100 000 inhabitants and the CFR was 8.83%. CONCLUSIONS: The models built can be useful for planning leptospirosis surveillance and control actions for the whole country and its regions and, together with the health indicators, revealed no uniform epidemiological situation of leptospirosis in Brazil.
Leptospirosis is a zoonosis with epidemic potential, especially after heavy rainfall causing river, urban and flash floods. Certain features of Santa Catarina’s coastal region influence these processes. Using negative binomial regression, we investigated trends in the incidence of leptospirosis in the six municipalities with the highest epidemic peaks between 2000 and 2015 and the climatic and environmental variables associated with the occurrence of the disease. Incidence was highest in 2008 and 2011, and peaks occurred in the same month or month after disasters. Incidence showed a strong seasonal trend, being higher in summer months. There was a decrease trend in incidence across the six municipalities (3.21% per year). The climatic and environmental factors that showed the strongest associations were number of rainy days, maximum temperature, presence of flash floods, and river flooding. The impact of these variables varied across the municipalities. Significant interactions were found, indicating that the effect of river flooding on incidence is not the same across all municipalities and differences in incidence between municipalities depend on the occurrence of river flooding.
Leptospirosis is an acute febrile disease that mainly affects developing countries with tropical climates. The complexity and magnitude of this disease is attributed to socioeconomic, climatic, and environmental conditions. In this study, in a 10-year period from 2008 to 2017, the relationship between human leptospirosis cases and climatic factors in Cartagena de Indias, Colombia were evaluated. Monthly leptospirosis cases, climatic variables, and macroclimatic phenomena (El Nino and La Nina) were obtained from public datasets. Local climatic factors included temperature (maximum, average, and minimum), relative humidity, precipitation, and the number of precipitation days. Time series graphs were drawn and correlations between cases of leptospirosis and climatic variables considering lags from 0 to 10 months were examined. A total of 360 cases of leptospirosis were reported in Cartagena during the study period, of which 192 (53.3%) were systematically notified between October and December. Several correlations were detected between the number of cases, local climatic variables, and macroclimatic phenomena. Mainly, the increase of cases correlated with increased precipitation and humidity during the La Nina periods. Herein, seasonal patterns and correlations suggest that the climate in Cartagena could favor the incidence of leptospirosis. Our findings suggest that prevention and control of human leptospirosis in Cartagena should be promoted and strengthened, especially in the last quarter of the year.
The way newspapers frame infectious disease outbreaks and their connection to the environmental determinants of disease transmission matter because they shape how we understand and respond to these major events. In 2017, following an unexpected climatic event named “El Niño Costero,” a dengue epidemic in Peru affected over seventy-five thousand people. This paper examines how the Peruvian news media presented dengue, a climate-sensitive disease, as a public health problem by analyzing a sample of 265 news stories on dengue from two major newspapers published between January 1st and December 31st of 2017. In analyzing the construction of responsibility for the epidemic, I find frames that blamed El Niño Costero’s flooding and Peru’s poorly prepared cities and public health infrastructure as the causes of the dengue outbreak. However, when analyzing frames that offer solutions to the epidemic, I find that news articles call for government-led, short-term interventions (e.g., fogging) that fail to address the decaying public health infrastructure and lack of climate-resilient health systems. Overall, news media tended to over-emphasize dengue as requiring technical solutions that ignore the root causes of health inequality and environmental injustice that allow dengue to spread in the first place. This case speaks to the medicalization of public health and to a long history of disease-control programs in the Global South that prioritized top-down technical approaches, turning attention away from the social and environmental determinants of health, which are particularly important in an era of climate change.
The 2030 Agenda for Sustainable Development is a plan of action for people, planet and prosperity. Thousands of years and centuries of colonisation have passed the precarious housing conditions, food insecurity, lack of sanitation, the limitation of surveillance, health care programs and climate change. Chagas disease continues to be a public health problem. The control programs have been successful in many countries in reducing transmission by T. cruzi; but the results have been variable. WHO makes recommendations for prevention and control with the aim of eliminating Chagas disease as a public health problem. Climate change, deforestation, migration, urbanisation, sylvatic vectors and oral transmission require integrating the economic, social, and environmental dimensions of sustainable development, as well as the links within and between objectives and sectors. While the environment scenarios change around the world, native vector species pose a significant public health threat. The man-made atmosphere change is related to the increase of triatomines’ dispersal range, or an increase of the mobility of the vectors from their sylvatic environment to man-made constructions, or humans getting into sylvatic scenarios, leading to an increase of Chagas disease infection. Innovations with the communities and collaborations among municipalities, International cooperation agencies, local governmental agencies, academic partners, developmental agencies, or environmental institutions may present promising solutions, but sustained partnerships, long-term commitment, and strong regional leadership are required. A new world has just opened up for the renewal of surveillance practices, but the lessons learned in the past should be the basis for solutions in the future.
The transmission of leptospirosis is conditioned by climatic variables. In northeastern Argentina leptospirosis outbreaks occur mainly in coincidence with periods of abundant precipitation and high hydrometric level. A Susceptible-Infectious-Recovered Epidemiological Model (SIR) is proposed, which incorporates hydroclimatic variables for the three most populated cities in the area (Santa Fe, Paraná and Rosario), during the 2009-2018 period. Results obtained by solving the proposed SIR model for the 2010 outbreak are in good agreement with the actual data, capturing the dynamics of the leptospirosis outbreak wave. However, the model does not perform very well in the last months of the year when isolated cases appear outside the outbreak periods, probably due to non- climatic factors not explicitly considered in the present version of the model. Nevertheless, the dynamic modeling of infectious diseases considering hydroclimatic variables constitutes a climatic service for the public health system, not yet available in Argentina.
The relationship between hydrometeorological disasters and the health of affected populations is still hardly discussed in Rio Grande do Sul (RS), Brazil. Hepatitis A is a disease that involves health and urban environment issue and is an avoidable disease. This study aims to analyze the relationship between flood areas and waterborne diseases, in this case, Hepatitis A. A database of confirmed cases of Hepatitis A and flood events in the municipality of Encantado-RS, Brazil between 2012 and 2014 was structured. These data were analyzed spatially from the kernel estimator of the occurrence points of Hepatitis A cases and correlated to the urban perimeter. It was verified that 44 cases were registered in the three months following the occurrence of flood, an increase of almost 300% in the records of Hepatitis A. The results identified that all the confirmed cases are in the urban area located in the floodplain. This reaffirms the importance of encouraging the formulation and implementation of policies to prevent outbreaks of waterborne diseases post hydrometeorological disaster.
This article compares urban and rural household water insecurity experiences during the last major drought period (2011-17) in the semi-arid interior region of Ceara, Brazil. Using data from a household survey (N = 322), we determined that households in small urban areas are more and differently water insecure than rural counterparts. Factor analysis and an ordinal logistic regression pinpoint key dimensions, such as water distress, water-sharing and intermittency, contribute differently to water insecurity in rural and urban households. Policy recommendations are made.
A significant fraction of Brazil’s population has been exposed to drought in recent years, a situation that is expected to worsen in frequency and intensity due to climate change. This constitutes a current key environmental health concern, especially in densely urban areas such as several big cities and suburbs. For the first time, a comprehensive assessment of the short-term drought effects on weekly non-external, circulatory, and respiratory mortality was conducted in 13 major Brazilian macro-urban areas across 2000-2019. We applied quasi-Poisson regression models adjusted by temperature to explore the association between drought (defined by the Standardized Precipitation-Evapotranspiration Index) and the different mortality causes by location, sex, and age groups. We next conducted multivariate meta-analytical models separated by cause and population groups to pool individual estimates. Impact measures were expressed as the attributable fractions among the exposed population, from the relative risks (RRs). Overall, a positive association between drought exposure and mortality was evidenced in the total population, with RRs varying from 1.003 [95% CI: 0.999-1.007] to 1.010 [0.996-1.025] for non-external mortality related to moderate and extreme drought conditions, from 1.002 [0.997-1.007] to 1.008 [0.991-1.026] for circulatory mortality, and from 1.004 [0.995-1.013] to 1.013 [0.983-1.044] for respiratory mortality. Females, children, and the elderly population were the most affected groups, for whom a robust positive association was found. The study also revealed high heterogeneity between locations. We suggest that policies and action plans should pay special attention to vulnerable populations to promote efficient measures to reduce vulnerability and risks associated with droughts.
Understanding the influence of climate change and population pressure on human conflict remains a critically important topic in the social sciences. Long-term records that evaluate these dynamics across multiple centuries and outside the range of modern climatic variation are especially capable of elucidating the relative effect of—and the interaction between—climate and demography. This is crucial given that climate change may structure population growth and carrying capacity, while both climate and population influence per capita resource availability. This study couples paleoclimatic and demographic data with osteological evaluations of lethal trauma from 149 directly accelerator mass spectrometry 14C-dated individuals from the Nasca highland region of Peru. Multiple local and supraregional precipitation proxies are combined with a summed probability distribution of 149 14C dates to estimate population dynamics during a 700-y study window. Counter to previous findings, our analysis reveals a precipitous increase in violent deaths associated with a period of productive and stable climate, but volatile population dynamics. We conclude that favorable local climate conditions fostered population growth that put pressure on the marginal and highly circumscribed resource base, resulting in violent resource competition that manifested in over 450 y of internecine warfare. These findings help support a general theory of intergroup violence, indicating that relative resource scarcity—whether driven by reduced resource abundance or increased competition—can lead to violence in subsistence societies when the outcome is lower per capita resource availability.
Amazonia and the Northeast region of Brazil exhibit the highest levels of climate vulnerability in the country. While Amazonia is characterized by an extremely hot and humid climate and hosts the world largest rainforest, the Northeast is home to sharp climatic contrasts, ranging from rainy areas along the coast to semiarid regions that are often affected by droughts. Both regions are subject to extremely high temperatures and are susceptible to many tropical diseases. This study develops a multidimensional Extreme Climate Vulnerability Index (ECVI) for Brazilian Amazonia and the Northeast region based on the Alkire-Foster method. Vulnerability is defined by three components, encompassing exposure (proxied by seven climate extreme indicators), susceptibility (proxied by sociodemographic indicators), and adaptive capacity (proxied by sanitation conditions, urbanization rate, and healthcare provision). In addition to the estimated vulnerability levels and intensity, we break down the ECVI by indicators, dimensions, and regions, in order to explore how the incidence levels of climate-sensitive infectious and parasitic diseases correlate with regional vulnerability. We use the Grade of Membership method to reclassify the mesoregions into homoclimatic zones based on extreme climatic events, so climate and population/health data can be analyzed at comparable resolutions. We find two homoclimatic zones: Extreme Rain (ER) and Extreme Drought and High Temperature (ED-HT). Vulnerability is higher in the ED-HT areas than in the ER. The contribution of each dimension to overall vulnerability levels varies by homoclimatic zone. In the ER zone, adaptive capacity (39%) prevails as the main driver of vulnerability among the three dimensions, in contrast with the approximately even dimensional contribution in the ED-HT. When we compare areas by disease incidence levels, exposure emerges as the most influential dimension. Our results suggest that climate can exacerbate existing infrastructure deficiencies and socioeconomic conditions that are correlated with tropical disease incidence in impoverished areas.
Arboviruses transmitted by Aedes aegypti (e.g., dengue, chikungunya, Zika) are of major public health concern on the arid coastal border of Ecuador and Peru. This high transit border is a critical disease surveillance site due to human movement-associated risk of transmission. Local level studies are thus integral to capturing the dynamics and distribution of vector populations and social-ecological drivers of risk, to inform targeted public health interventions. Our study examines factors associated with household-level Ae. aegypti presence in Huaquillas, Ecuador, while accounting for spatial and temporal effects. From January to May of 2017, adult mosquitoes were collected from a cohort of households (n = 63) in clusters (n = 10), across the city of Huaquillas, using aspirator backpacks. Household surveys describing housing conditions, demographics, economics, travel, disease prevention, and city services were conducted by local enumerators. This study was conducted during the normal arbovirus transmission season (January-May), but during an exceptionally dry year. Household level Ae. aegypti presence peaked in February, and counts were highest in weeks with high temperatures and a week after increased rainfall. Univariate analyses with proportional odds logistic regression were used to explore household social-ecological variables and female Ae. aegypti presence. We found that homes were more likely to have Ae. aegypti when households had interruptions in piped water service. Ae. aegypti presence was less likely in households with septic systems. Based on our findings, infrastructure access and seasonal climate are important considerations for vector control in this city, and even in dry years, the arid environment of Huaquillas supports Ae. aegypti breeding habitat.
Vector-borne diseases are some of the leading public health problems in the tropics, and their association with climatic anomalies is well known. The current study aimed to evaluate the trend of American cutaneous leishmaniasis cases in the municipality of Manaus, Amazonas-Brazil, and its relationship with climatic extremes (ENSO). The study was carried out using a series of secondary data from notifications on the occurrence of several American cutaneous leishmaniasis cases in the municipality of Manaus between 1990 and 2017 obtained through the Sistema de Informação de Agravos de Notificação. Data regarding temperature, relative humidity, and precipitation for this municipality were derived from the Instituto Nacional de Meteorologia (INMET) and the National Oceanic and Atmospheric Administration (NOAA) websites. Coherence and wavelet phase analysis was conducted to measure the degree of relationship of the occurrence of the cases of cutaneous leishmaniasis and the El Niño-Southern Oscillation (ENSO). The results show that during La Niña events, an increase in American cutaneous leishmaniasis (ACL) cases is anticipated after the increase in rainfall from November, resulting in a more significant number of cases in January, February, and March. It was observed that in the municipality of Manaus, the dynamics of ACL cases are directly influenced by ENSO events that affect environmental variables such as precipitation, temperature, and humidity. Therefore, climatic variations consequently change the ACL incidence dynamics, leading to subsequent increases or decreases in the incidence of ACL cases in the area.
Due to the global increase in mosquito-borne diseases outbreaks it is recommended to increase surveillance and monitoring of vector species to respond swiftly and with early warning indicators. Usually, however, the information about vector presence and activity seems to be insufficient to implement timely and effective control strategies. Here we present an improved mathematical model of Aedes aegypti population dynamics with the aim of making the Dengue surveillance system more proactive. The model considers the four life stages of the mosquito: egg, larva, pupa and adult. As driving factors, it incorporates temperature which affects development and mortality rates at certain stages, and precipitation which is known to affect egg submergence and hatching, as well as larval mortality associated with desiccation. Our mechanistic model is implemented as a free and stand-alone system that automatically retrieves all needed inputs, runs a simulation and shows the results. A major improvement in our implementation is the capacity of the system to predict the population dynamics of Ae. aegypti in the near future, given that it uses gridded weather forecast data. Hence, it is independent by meteorological station proximity. The model predictions are compared with field data from C ‘ ordoba City, Argentina. Although field data have high variability, an overall accordance has been observed. The comparison of results obtained using observed weather data, with the simulations based on forecasts, suggests that the modeled dynamics are accurate up to 15 days in advance. Preliminary results of Ae. aegypti population dynamics for a consecutive three-year period, spanning different eco-regions of Argentina, are presented, and demonstrate the flexibility of the system.
Dengue is steadily increasing worldwide and expanding into higher latitudes. Current non-endemic areas are prone to become endemic soon. To improve understanding of dengue transmission in these settings, we assessed the spatiotemporal dynamics of the hitherto largest outbreak in the non-endemic metropolis of Buenos Aires, Argentina, based on detailed information on the 5,104 georeferenced cases registered during summer-autumn of 2016. The highly seasonal dengue transmission in Buenos Aires was modulated by temperature and triggered by imported cases coming from regions with ongoing outbreaks. However, local transmission was made possible and consolidated heterogeneously in the city due to housing and socioeconomic characteristics of the population, with 32.8% of autochthonous cases occurring in slums, which held only 6.4% of the city population. A hierarchical spatiotemporal model accounting for imperfect detection of cases showed that, outside slums, less-affluent neighborhoods of houses (vs. apartments) favored transmission. Global and local spatiotemporal point-pattern analyses demonstrated that most transmission occurred at or close to home. Additionally, based on these results, a point-pattern analysis was assessed for early identification of transmission foci during the outbreak while accounting for population spatial distribution. Altogether, our results reveal how social, physical, and biological processes shape dengue transmission in Buenos Aires and, likely, other non-endemic cities, and suggest multiple opportunities for control interventions.
Cutaneous Leishmaniasis (CL) is the most prevalent form of Leishmaniasis and is widely endemic in the Americas. Several species of Leishmania are responsible for CL, a severely neglected tropical disease and the treatment of CL vary according to the different species of Leishmania. We proposed to map the distribution of the Leishmania species reported in French Guiana (FG) using a biogeographic approach based on environmental predictors. We also measured species endemism i.e., the uniqueness of species to a defined geographic location. Our results show that the distribution patterns varied between Leishmania spp. and were spatially dependent on climatic covariates. The species distribution modelling of the eco-epidemiological spatial patterns of Leishmania spp. is the first to measure endemism based on bioclimatic factors in FG. The study also emphasizes the impact of tree cover loss and climate on the increasing distribution of L. (Viannia) braziliensis in the most anthropized regions. Detection of high-risk regions for the different between Leishmania spp. is essential for monitoring and active surveillance of the vector. As climate plays a major role in the spatial distribution of the vector and reservoir and the survival of the pathogen, climatic covariates should be included in the analysis and mapping of vector-borne diseases. This study underscores the significance of local land management and the urgency of considering the impact of climate change in the development of vector-borne disease management strategies at the global scale.
BACKGROUND: West Nile virus (WNV) is a vector-borne pathogen of global relevance and is currently the most widely distributed flavivirus causing encephalitis worldwide. Climate conditions have direct and indirect impacts on vector abundance and virus dynamics within the mosquito. The significance of environmental variables as drivers in WNV epidemiology is increasing under the current climate change scenario. In this study we used a machine learning algorithm to model WNV distributions in South America. METHODS: Our model evaluated eight environmental variables for their contribution to the occurrence of WNV since its introduction in South America in 2004. RESULTS: Our results showed that environmental variables can directly alter the occurrence of WNV, with lower precipitation and higher temperatures associated with increased virus incidence. High-risk areas may be modified in the coming years, becoming more evident with high greenhouse gas emission levels. Countries such as Bolivia, Paraguay and several Brazilian areas, mainly in the northeast and midwest regions and the Pantanal biome, will be greatly affected, drastically changing the current WNV distribution. CONCLUSIONS: Understanding the linkages between climatological and ecological change as determinants of disease emergence and redistribution will help optimize preventive strategies. Increased virus surveillance, integrated modelling and the use of geographically based data systems will provide more anticipatory measures by the scientific community.
Dengue is an endemic disease in more than 100 countries, but there are few studies about the effects of hydroclimatic variability on dengue incidence (DI) in tropical dryland areas. This study investigates the association between hydroclimatic variability and DI (2008-2018) in a large tropical dryland area. The area studied comprehends seven municipalities with populations ranging from 32,879 to 2,545,419 inhabitants. First, the precipitation and temperature impacts on interannual and seasonal DI were investigated. Then, the monthly association between DI and hydroclimatic variables was analyzed using generalized least squares (GLS) regression. The model’s capability to reproduce DI given the current hydroclimatic conditions and DI seasonality over the entire time period studied were assessed. No association between the interannual variation of precipitation and DI was found. However, seasonal variation of DI was shaped by precipitation and temperature. February-July was the main dengue season period. A precipitation threshold, usually above 100 mm, triggers the rapid DI rising. Precipitation and minimum air temperature were the main explanatory variables. A two-month-lagged predictor was relevant for modeling, occurring in all regressions, followed by a non-lagged predictor. The climate predictors differed among the regression models, revealing the high spatial DI variability driven by hydroclimatic variability. GLS regressions were able to reproduce the beginning, development, and end of the dengue season, although we found underestimation of DI peaks and overestimation of low DI. These model limitations are not an issue for climate change impact assessment on DI at the municipality scale since historical DI seasonality was well simulated. However, they may not allow seasonal DI forecasting for some municipalities. These findings may help not only public health policies in the studied municipalities but also have the potential to be reproducible for other dryland regions with similar data availability.
In the last 20 years yellow fever (YF) has seen dramatic changes to its incidence and geographic extent, with the largest outbreaks in South America since 1940 occurring in the previously unaffected South-East Atlantic coast of Brazil in 2016-2019. While habitat fragmentation and land-cover have previously been implicated in zoonotic disease, their role in YF has not yet been examined. We examined the extent to which vegetation, land-cover, climate and host population predicted the numbers of months a location reported YF per year and by each month over the time-period. Two sets of models were assessed, one looking at interannual differences over the study period (2003-2016), and a seasonal model looking at intra-annual differences by month, averaging over the years of the study period. Each was fit using hierarchical negative-binomial regression in an exhaustive model fitting process. Within each set, the best performing models, as measured by the Akaike Information Criterion (AIC), were combined to create ensemble models to describe interannual and seasonal variation in YF. The models reproduced the spatiotemporal heterogeneities in YF transmission with coefficient of determination (R2) values of 0.43 (95% CI 0.41-0.45) for the interannual model and 0.66 (95% CI 0.64-0.67) for the seasonal model. For the interannual model, EVI, land-cover and vegetation heterogeneity were the primary contributors to the variance explained by the model, and for the seasonal model, EVI, day temperature and rainfall amplitude. Our models explain much of the spatiotemporal variation in YF in South America, both seasonally and across the period 2003-2016. Vegetation type (EVI), heterogeneity in vegetation (perhaps a proxy for habitat fragmentation) and land cover explain much of the trends in YF transmission seen. These findings may help understand the recent expansions of the YF endemic zone, as well as to the highly seasonal nature of YF.
In the last two decades dengue cases increased significantly throughout the world, giving place to more frequent outbreaks in Latin America. In the non-endemic city of San Ramón de la Nueva Orán, located in Northwest Argentina, large dengue outbreaks alternate with several years of smaller ones. This pattern, as well as the understanding of the underlying mechanisms, could be essential to design proper strategies to reduce epidemic size. We develop a stochastic model that includes climate variables, social structure, and mobility between a non-endemic city and an endemic area. Climatic variables were input of a mosquito population ecological model, which in turn was coupled to a meta-population, spatially explicit, epidemiological model. Human mobility was included into the model given the high border crossing to the northern country of Bolivia, where dengue transmission is sustained during the whole year. We tested different hypotheses regarding people mobility as well as climate variability by fitting numerical simulations to weekly clinical data reported from 2009 to 2016. After assessing the number of imported cases that triggered the observed outbreaks, our model allows to explain the observed epidemic pattern. We found that the number of vectors per host and the effective reproductive number are proxies for large epidemics. Both proxies are related with climate variability such as rainfall and temperature, opening the possibility to test these meteorological variables for forecast purposes.
Dengue is a re-emerging disease, currently considered the most important mosquito-borne arbovirus infection affecting humankind, taking into account both its morbidity and mortality. Brazil is considered an endemic country for dengue, such that more than 1,544,987 confirmed cases were notified in 2019, which means an incidence rate of 735 for every 100 thousand inhabitants. Climate is an important factor in the temporal and spatial distribution of vector-borne diseases, such as dengue. Thus, rainfall and temperature are considered macro-factors determinants for dengue, since they directly influence the population density of Aedes aegypti, which is subject to seasonal fluctuations, mainly due to these variables. This study examined the incidence of dengue fever related to the climate influence by using temperature and rainfall variables data obtained from remote sensing via artificial satellites in the metropolitan region of Rio de Janeiro, Brazil. The mathematical model that best fits the data is based on an auto-regressive moving average with exogenous inputs (ARMAX). It reproduced the values of incidence rates in the study period and managed to predict with good precision in a one-year horizon. The approach described in present work may be replicated in cities around the world by the public health managers, to build auxiliary operational tools for control and prevention tasks of dengue, as well of other arbovirus diseases.
Efficient and accurate dengue risk prediction is an important basis for dengue prevention and control, which faces challenges, such as downloading and processing multi-source data to generate risk predictors and consuming significant time and computational resources to train and validate models locally. In this context, this study proposed a framework for dengue risk prediction by integrating big geospatial data cloud computing based on Google Earth Engine (GEE) platform and artificial intelligence modeling on the Google Colab platform. It enables defining the epidemiological calendar, delineating the predominant area of dengue transmission in cities, generating the data of risk predictors, and defining multi-date ahead prediction scenarios. We implemented the experiments based on weekly dengue cases during 2013-2020 in the Federal District and Fortaleza, Brazil to evaluate the performance of the proposed framework. Four predictors were considered, including total rainfall (R(sum)), mean temperature (T(mean)), mean relative humidity (RH(mean)), and mean normalized difference vegetation index (NDVI(mean)). Three models (i.e., random forest (RF), long-short term memory (LSTM), and LSTM with attention mechanism (LSTM-ATT)), and two modeling scenarios (i.e., modeling with or without dengue cases) were set to implement 1- to 4-week ahead predictions. A total of 24 models were built, and the results showed in general that LSTM and LSTM-ATT models outperformed RF models; modeling could benefit from using historical dengue cases as one of the predictors, and it makes the predicted curve fluctuation more stable compared with that only using climate and environmental factors; attention mechanism could further improve the performance of LSTM models. This study provides implications for future dengue risk prediction in terms of the effectiveness of GEE-based big geospatial data processing for risk predictor generation and Google Colab-based risk modeling and presents the benefits of using historical dengue data as one of the input features and the attention mechanism for LSTM modeling.
Dengue fever is re-emerging worldwide, however the reasons of this new emergence are not fully understood. Our goal was to report the incidence of dengue in one of the most populous States of Brazil, and to assess the high-risk areas using a spatial and spatio-temporal annual models including geoclimatic, demographic and socioeconomic characteristics. An ecological study with both, a spatial and a temporal component was carried out in Sao Paulo State, Southeastern Brazil, between January 1st, 2007 and December 31st, 2019. Crude and Bayesian empirical rates of dengue cases following by Standardized Incidence Ratios (SIR) were calculated considering the municipalities as the analytical units and using the Integrated Nested Laplace Approximation in a Bayesian context. A total of 2,027,142 cases of dengue were reported during the studied period. The spatial model allocated the municipalities in four groups according to the SIR values: (I) SIR<0.8; (II) SIR 0.8<1.2; (III) SIR 1.2<2.0 and SIR>2.0 identified the municipalities with higher risk for dengue outbreaks. “Hot spots” are shown in the thematic maps. Significant correlations between SIR and two climate variables, two demographic variables and one socioeconomical variable were found. No significant correlations were found in the spatio-temporal model. The incidence of dengue exhibited an inconstant and unpredictable variation every year. The highest rates of dengue are concentrated in geographical clusters with lower surface pressure, rainfall and altitude, but also in municipalities with higher degree of urbanization and better socioeconomic conditions. Nevertheless, annual consolidated variations in climatic features do not influence in the epidemic yearly pattern of dengue in southeastern Brazil.
BACKGROUND: This research addresses two questions: (1) how El Niño Southern Oscillation (ENSO) affects climate variability and how it influences dengue transmission in the Metropolitan Region of Recife (MRR), and (2) whether the epidemic in MRR municipalities has any connection and synchronicity. METHODS: Wavelet analysis and cross-correlation were applied to characterize seasonality, multiyear cycles, and relative delays between the series. This study was developed into two distinct periods. Initially, we performed periodic dengue incidence and intercity epidemic synchronism analyses from 2001 to 2017. We then defined the period from 2001 to 2016 to analyze the periodicity of climatic variables and their coherence with dengue incidence. RESULTS: Our results showed systematic cycles of 3-4 years with a recent shortening trend of 2-3 years. Climatic variability, such as positive anomalous temperatures and reduced rainfall due to changes in sea surface temperature (SST), is partially linked to the changing epidemiology of the disease, as this condition provides suitable environments for the Aedes aegypti lifecycle. CONCLUSION: ENSO may have influenced the dengue temporal patterns in the MRR, transiently reducing its main way of multiyear variability (3-4 years) to 2-3 years. Furthermore, when the epidemic coincided with El Niño years, it spread regionally and was highly synchronized.
Tropical countries face urgent public health challenges regarding epidemic control of Dengue. Since effective vector-control efforts depend on the timing in which public policies take place, there is an enormous demand for accurate prediction tools. In this work, we improve upon a recent approach of coarsely predicting outbreaks in Brazilian urban centers based solely on their yearly climate data. Our methodological advancements encompass a judicious choice of data pre-processing steps and usage of modern computational techniques from signal-processing and manifold learning. Altogether, our results improved earlier prediction accuracy scores from 0.72 to 0.80, solidifying manifold learning on climate data alone as a viable way to make (coarse) dengue outbreak prediction in large urban centers. Ultimately, this approach has the potential of radically simplifying the data required to do outbreak analysis, as municipalities with limited public health funds may not monitor a large number of features needed for more extensive machine learning approaches.
This study investigated a model to assess the role of climate fluctuations on dengue (DENV) dynamics from 2010 to 2019 in four Brazilian municipalities. The proposed transmission model was based on a preexisting SEI-SIR model, but also incorporates the vector vertical transmission and the vector’s egg compartment, thus allowing rainfall to be introduced to modulate egg-hatching. Temperature and rainfall satellite data throughout the decade were used as climatic model inputs. A sensitivity analysis was performed to understand the role of each parameter. The model-simulated scenario was compared to the observed dengue incidence and the findings indicate that the model was able to capture the observed seasonal dengue incidence pattern with good accuracy until 2016, although higher deviations were observed from 2016 to 2019. The results further demonstrate that vertical transmission fluctuations can affect attack transmission rates and patterns, suggesting the need to investigate the contribution of vertical transmission to dengue transmission dynamics in future assessments. The improved understanding of the relationship between different environment variables and dengue transmission achieved by the proposed model can contribute to public health policies regarding mosquito-borne diseases.
Environmental changes are among the main factors that contribute to the emergence or re-emergence of viruses of public health importance. Here, we show the impact of environmental modifications on cases of infections by the dengue, chikungunya and Zika viruses in humans in the state of Tocantins, Brazil, between the years 2010 and 2019. We conducted a descriptive and principal component analysis (PCA) to explore the main trends in environmental modifications and in the cases of human infections caused by these arboviruses in Tocantins. Our analysis demonstrated that the occurrence of El Niño, deforestation in the Cerrado and maximum temperatures had correlations with the cases of infections by the Zika virus between 2014 and 2016. El Niño, followed by La Niña, a gradual increase in precipitation and the maximum temperature observed between 2015 and 2017 were shown to have contributed to the infections by the chikungunya virus. La Niña and precipitation were associated with infections by the dengue virus between 2010 and 2012 and El Niño contributed to the 2019 outbreak observed within the state. By PCA, deforestation, temperatures and El Niño were the most important variables related to cases of dengue in humans. We conclude from this analysis that environmental changes (deforestation and climate change) presented a strong influence on the human infections caused by the dengue, chikungunya and Zika viruses in Tocantins from 2010 to 2019.
Dengue is a serious public health concern in Brazil and globally. In the absence of a universal vaccine or specific treatments, prevention relies on vector control and disease surveillance. Accurate and early forecasts can help reduce the spread of the disease. In this study, we developed a model for predicting monthly dengue cases in Brazilian cities 1 month ahead, using data from 2007-2019. We compared different machine learning algorithms and feature selection methods using epidemiologic and meteorological variables. We found that different models worked best in different cities, and a random forests model trained on monthly dengue cases performed best overall. It produced lower errors than a seasonal naive baseline model, gradient boosting regression, a feed-forward neural network, or support vector regression. For each city, we computed the mean absolute error between predictions and true monthly numbers of dengue cases on the test data set. The median error across all cities was 12.2 cases. This error was reduced to 11.9 when selecting the optimal combination of algorithm and input features for each city individually. Machine learning and especially decision tree ensemble models may contribute to dengue surveillance in Brazil, as they produce low out-of-sample prediction errors for a geographically diverse set of cities.
According to the World Health Organization, dengue is a neglected tropical disease. Latin America, specifically Colombia is in alert regarding this arbovirosis as there was a spike in the number of reported dengue cases at the beginning of 2019. Although there has been a worldwide decrease in the number of reported dengue cases, Colombia has shown a growing trend over the past few years. This study performed a Poisson multilevel analysis with mixed effects on STATA® version 16 and R to assess sociodemographic, climatic, and entomological factors that may influence the occurrence of dengue in three municipalities for the period 2010-2015. Information on dengue cases and their sociodemographic variables was collected from the National Public Health Surveillance System (SIVIGILA) records. For climatic variables (temperature, relative humidity, and precipitation), we used the information registered by the weather stations located in the study area, which are managed by the Instituto de Hidrologia, Meteorologia y Estudios Ambientales (IDEAM) or the Corporación Autónoma Regional (CAR). The entomological variables (house index, container index, and Breteau index) were provided by the Health office of the Cundinamarca department. SIVIGILA reported 1921 dengue cases and 56 severe dengue cases in the three municipalities; of them, three died. One out of four cases occurred in rural areas. The age category most affected was adulthood, and there were no statistical differences in the number of cases between sexes. The Poisson multilevel analysis with the best fit model explained the presentation of cases were temperature, relative humidity, precipitation, childhood, live in urban area and the contributory healthcare system. The temperature had the biggest influence on the presentation of dengue cases in this region between 2010 and 2015.
Dengue virus (DENV) is an endemic disease in the hot and humid low-lands of Colombia. We characterize the association of monthly series of dengue cases with indices of El Niño/Southern Oscillation (ENSO) at the tropical Pacific and local climatic variables in Colombia during the period 2007-2017 at different temporal and spatial scales. For estimation purposes, we use lagged cross-correlations (Pearson test), cross-wavelet analysis (wavelet cross spectrum, and wavelet coherence), as well as a novel nonlinear causality method, PCMCI, that allows identifying common causal drivers and links among high dimensional simultaneous and time-lagged variables. Our results evidence the strong association of DENV cases in Colombia with ENSO indices and with local temperature and rainfall. El Niño (La Niña) phenomenon is related to an increase (decrease) of dengue cases nationally and in most regions and departments, with maximum correlations occurring at shorter time lags in the Pacific and Andes regions, closer to the Pacific Ocean. This association is mainly explained by the ENSO-driven increase in temperature and decrease in rainfall, especially in the Andes and Pacific regions. The influence of ENSO is not stationary, given the reduction of DENV cases since 2005, and that local climate variables vary in space and time, which prevents to extrapolate results from one region to another. The association between DENV and ENSO varies at national and regional scales when data are disaggregated by seasons, being stronger in DJF and weaker in SON. Overall, the Pacific and Andes regions control the relationship between dengue dynamics and ENSO at national scale. Cross-wavelet analysis indicates that the ENSO-DENV relation in Colombia exhibits a strong coherence in the 12 to 16-months frequency band, which implies the frequency locking between the annual cycle and the interannual (ENSO) timescales. Results of nonlinear causality metrics reveal the complex concomitant effects of ENSO and local climate variables, while offering new insights to develop early warning systems for DENV in Colombia.
BACKGROUND: The influence of climate on the epidemiology of dengue has scarcely been studied in Cartagena. METHODS: The relationship between dengue cases and climatic and macroclimatic factors was explored using an ecological design and bivariate and time-series analyses during lag and non-lag months. Data from 2008-2017 was obtained from the national surveillance system and meteorological stations. RESULTS: Cases correlated only with climatic variables during lag and non-lag months. Decreases in precipitation and humidity and increases in temperature were correlated with an increase in cases. CONCLUSIONS: Our findings provide useful information for establishing and strengthening dengue prevention and control strategies.
BACKGROUND: There is currently a scarcity of air pollution epidemiologic data from low- and middle-income countries (LMICs) due to the lack of air quality monitoring in these countries. Additionally, there is limited capacity to assess the health effects of wildfire smoke events in wildfire-prone regions like Brazil’s Amazon Basin. Emerging low-cost air quality sensors may have the potential to address these gaps. OBJECTIVES: We investigated the potential of PurpleAir PM2.5 sensors for conducting air pollution epidemiologic research leveraging the United States Environmental Protection Agency’s United States-wide correction formula for ambient PM(2.5). METHODS: We obtained raw (uncorrected) PM(2.5) concentration and humidity data from a PurpleAir sensor in Rio Branco, Brazil, between 2018 and 2019. Humidity measurements from the PurpleAir sensor were used to correct the PM(2.5) concentrations. We established the relationship between ambient PM(2.5) (corrected and uncorrected) and daily all-cause respiratory hospitalization in Rio Branco, Brazil, using generalized additive models (GAM) and distributed lag non-linear models (DLNM). We used linear regression to assess the relationship between daily PM(2.5) concentrations and wildfire reports in Rio Branco during the wildfire seasons of 2018 and 2019. RESULTS: We observed increases in daily respiratory hospitalizations of 5.4% (95%CI: 0.8%, 10.1%) for a 2-day lag and 5.8% (1.5%, 10.2%) for 3-day lag, per 10 μg/m(3) PM(2.5) (corrected values). The effect estimates were attenuated when the uncorrected PM(2.5) data was used. The number of reported wildfires explained 10% of daily PM2.5 concentrations during the wildfire season. DISCUSSION: Exposure-response relationships estimated using corrected low-cost air quality sensor data were comparable with relationships estimated using a validated air quality modeling approach. This suggests that correcting low-cost PM(2.5) sensor data may mitigate bias attenuation in air pollution epidemiologic studies. Low-cost sensor PM(2.5) data could also predict the air quality impacts of wildfires in Brazil’s Amazon Basin.
One of the central problems in large cities is air pollution, mainly caused by vehicular emissions. Tropospheric ozone is an atmospheric oxidizing gas that forms in minimal amounts naturally, affecting peoples’ health. This pollutant is formed by the NO2 photolysis, creating a main peak during the day. Nighttime secondary peaks occur in several parts of the world, but their intensity and frequency depend on the local condition. In this sense, this works aims to study the local characteristics for tropospheric nocturnal ozone levels in the Metropolitan Area of Sao Paulo, in Brazil, using the Simple Photochemical Module coupled to the Brazilian Developments on the Regional Atmospheric Modeling System. For this, three different situations of nocturnal occurrence were studied. The results show that the nocturnal maximum of ozone concentrations is related to the vertical transport of this pollutant from higher levels of the atmosphere to the surface and is not related to the synoptic condition.
BACKGROUND: Long-term exposure to fine particles ≤2.5 μm in diameter (PM2.5) has been linked to cancer mortality. However, the effect of wildfire-related PM2.5 exposure on cancer mortality risk is unknown. This study evaluates the association between wildfire-related PM2.5 and site-specific cancer mortality in Brazil, from 2010 to 2016. METHODS AND FINDINGS: Nationwide cancer death records were collected during 2010-2016 from the Brazilian Mortality Information System. Death records were linked with municipal-level wildfire- and non-wildfire-related PM2.5 concentrations, at a resolution of 2.0° latitude by 2.5° longitude. We applied a variant difference-in-differences approach with quasi-Poisson regression, adjusting for seasonal temperature and gross domestic product (GDP) per capita. Relative risks (RRs) and 95% confidence intervals (CIs) for the exposure for specific cancer sites were estimated. Attributable fractions and cancer deaths were also calculated. In total, 1,332,526 adult cancer deaths (age ≥ 20 years), from 5,565 Brazilian municipalities, covering 136 million adults were included. The mean annual wildfire-related PM2.5 concentration was 2.38 μg/m3, and the annual non-wildfire-related PM2.5 concentration was 8.20 μg/m3. The RR for mortality from all cancers was 1.02 (95% CI 1.01-1.03, p < 0.001) per 1-μg/m3 increase of wildfire-related PM2.5 concentration, which was higher than the RR per 1-μg/m3 increase of non-wildfire-related PM2.5 (1.01 [95% CI 1.00-1.01], p = 0.007, with p for difference = 0.003). Wildfire-related PM2.5 was associated with mortality from cancers of the nasopharynx (1.10 [95% CI 1.04-1.16], p = 0.002), esophagus (1.05 [95% CI 1.01-1.08], p = 0.012), stomach (1.03 [95% CI 1.01-1.06], p = 0.017), colon/rectum (1.08 [95% CI 1.05-1.11], p < 0.001), larynx (1.06 [95% CI 1.02-1.11], p = 0.003), skin (1.06 [95% CI 1.00-1.12], p = 0.003), breast (1.04 [95% CI 1.01-1.06], p = 0.007), prostate (1.03 [95% CI 1.01-1.06], p = 0.019), and testis (1.10 [95% CI 1.03-1.17], p = 0.002). For all cancers combined, the attributable deaths were 37 per 100,000 population and ranged from 18/100,000 in the Northeast Region of Brazil to 71/100,000 in the Central-West Region. Study limitations included a potential lack of assessment of the joint effects of gaseous pollutants, an inability to capture the migration of residents, and an inability to adjust for some potential confounders. CONCLUSIONS: Exposure to wildfire-related PM2.5 can increase the risks of cancer mortality for many cancer sites, and the effect for wildfire-related PM2.5 was higher than for PM2.5 from non-wildfire sources.
We quantified the impacts of wildfire-related PM2.5 on 2 million hospital admissions records due to cardiorespiratory diseases in Brazil between 2008 and 2018. The national analysis shows that wildfire waves are associated with an increase of 23% (95%CI: 12%-33%) in respiratory hospital admissions and an increase of 21% (95%CI: 8%-35%) in circulatory hospital admissions. In the North (where most of the Amazon region is located), we estimate an increase of 38% (95%CI: 30%-47%) in respiratory hospital admissions and 27% (95%CI: 15%-39%) in circulatory hospital admissions. Here we report epidemiological evidence that air pollution emitted by wildfires is significantly associated with a higher risk of cardiorespiratory hospital admissions. Brazil is a wildfire-prone region, and few studies have investigated the health impacts of wildfire exposure. Here, the authors show that wildfire waves are associated with an increase of 23% in respiratory hospital admissions and an increase of 21% in circulatory hospital admissions in Brazil.
Background Birth defects are a major cause of poor health outcomes during both childhood and adulthood. A growing body of evidence demonstrated associations between air pollution exposure during pregnancy and birth defects. To date, there is no study looking at birth defects and exposure to wildfire-related air pollution, which is suggested as a type of air pollution source with high toxicity for reproductive health. Objective Our study addresses this gap by examining the association between birth defects and wildfire smoke exposure in Brazil between 2001 and 2018. Based on known differences of impacts of wildfires across different regions of Brazil, we hypothesized differences in risks of birth defects for different regions. Methods We used a logistic regression model to estimate the odds ratios (ORs) for individual birth defects (12 categories) associated with wildfire exposure during each trimester of pregnancy. Results Among the 16,825,497 birth records in our study population, there were a total of 7595 infants born in Brazil between 2001 and 2018 with birth defects in any of the selected categories. After adjusting for several confounders in the primary analysis, we found statistically significant OR for three birth defects, including cleft lip/cleft palate [OR: 1.007 (95% CI: 1.001; 1.013)] during the second trimester of exposure, congenital anomalies of the respiratory system [OR: 1.013 (95% CI: 1.002; 1.023)] in the second trimester of exposure, and congenital anomalies of the nervous system [OR: 1.002 (95% CI: 1.001; 1.003)] during the first trimester of exposure for the regions South, North, and Midwest, respectively. Significance Our results suggest that maternal exposure to wildfire smoke during pregnancy may increase the risk of an infant being born with some congenital anomaly. Considering that birth defects are associated with long-term disability, impacting families and the healthcare system (e.g., healthcare costs), our findings should be of great concern to the public health community. Impact statement Our study focused on the association between maternal exposure to wildfire smoke in Brazil during pregnancy and the risk of an infant being born with congenital anomalies, which presents serious public health and environmental challenges.
Air pollution from Amazon fires has adverse impacts on human health. The number of fires in the Amazon has increased in recent years, but whether this increase was driven by deforestation or climate has not been assessed. We analyzed relationships between fire, deforestation, and climate for the period 2003 to 2019 among selected states across the Brazilian Legal Amazon (BLA). A statistical model including deforestation, precipitation and temperature explained ∼80% of the variability in dry season fire count across states when totaled across the BLA, with positive relationships between fire count and deforestation. We estimate that the increase in deforestation since 2012 increased the dry season fire count in 2019 by 39%. Using a regional chemistry-climate model combined with exposure-response associations, we estimate this increase in fire resulted in 3,400 (95UI: 3,300-3,550) additional deaths in 2019 due to increased exposure to particulate air pollution. If deforestation in 2019 had increased to the maximum recorded during 2003-2019, the number of active fire counts would have increased by an additional factor of 2 resulting in 7,900 (95UI: 7,600-8,200) additional premature deaths. Our analysis demonstrates the strong benefits of reduced deforestation on air quality and public health across the Amazon.
The March 2015 extraordinary hydrometeomlogical event in the Andes cordillera caused severe floods in the southern Atacama Desert. One of the most affected cities was CopiapO (northern Chile) located downstream of the junction between the CopiapO river and its ephemeral tributary Quebrada Paipote. This work analyses the features of this catastrophic flood and relates them with the identified impacts. A large volume of water mixed with fine sediments overflowed the tributary channel generating a flood that affected 72% of the urban area. The rheological (velocity, density and flow regime) and sedimentary features of the flow reveal the occurrence of massive mudflows that infilled the space available inside the buildings, buried the streets with a sandy mud deposit of more than 30 cm medium thickness and collapsed the sewer network. The post-event survey carried out by the Ministry of Housing and Urban Planning (MINVU) was used for the development of fragility curves that allows modelling the probability of damage. Results indicate that the greatest probability of building damage is generated by the accumulation of sediments instead of by the flow depth. On the other hand, once the very fine grain sediments of the top of the deposit dried up, it increased the concentration of post-event suspension particulate matter, causing a health issue. This work highlights the need to understand mudflow processes and their consequences in arid environments to improve urban planning and mitigate future damages since their impacts strongly affect infrastructures and communities.
BACKGROUND: In the context of climate change and deforestation, Brazil is facing more frequent and unprecedented wildfires. Wildfire-related PM(2·5) is associated with multiple adverse health outcomes; however, the magnitude of these associations in the Brazilian context is unclear. We aimed to estimate the association between daily exposure to wildfire-related PM(2·5) and cause-specific hospital admission and attributable health burden in the Brazilian population using a nationwide dataset from 2000 to 2015. METHODS: In this nationwide time-series analysis, data for daily all-cause, cardiovascular, and respiratory hospital admissions were collected through the Brazilian Unified Health System from 1814 municipalities in Brazil between Jan 1, 2000, and Dec 31, 2015. Daily concentrations of wildfire-related PM(2·5) were estimated using the 3D chemical transport model GEOS-Chem at a 2·0° latitude by 2·5° longitude resolution. A time-series analysis was fitted using quasi-Poisson regression to quantify municipality-specific effect estimates, which were then pooled at the regional and national levels using random-effects meta-analyses. Analyses were stratified by sex and ten age groups. The attributable fraction and attributable cases of hospital admissions due to wildfire-related PM(2·5) were also calculated. FINDINGS: At the national level, a 10 μg/m(3) increase in wildfire-related PM(2·5) was associated with a 1·65% (95% CI 1·51-1·80) increase in all-cause hospital admissions, a 5·09% (4·73-5·44) increase in respiratory hospital admissions, and a 1·10% (0·78-1·42) increase in cardiovascular hospital admissions, over 0-1 days after the exposure. The effect estimates for all-cause hospital admission did not vary by sex, but were particularly high in children aged 4 years or younger (4·88% [95% CI 4·47-5·28]), children aged 5-9 years (2·33% [1·77-2·90]), and people aged 80 years and older (3·70% [3·20-4·20]) compared with other age groups. We estimated that 0·53% (95% CI 0·48-0·58) of all-cause hospital admissions were attributable to wildfire-related PM(2·5), corresponding to 35 cases (95% CI 32-38) per 100 000 residents annually. The attributable rate was greatest for municipalities in the north, south, and central-west regions, and lowest in the northeast region. Results were consistent for all-cause and respiratory diseases across regions, but remained inconsistent for cardiovascular diseases. INTERPRETATION: Short-term exposure to wildfire-related PM(2·5) was associated with increased risks of all-cause, respiratory, and cardiovascular hospital admissions, particularly among children (0-9 years) and older people (≥80 years). Greater attention should be paid to reducing exposure to wildfire smoke, particularly for the most susceptible populations. FUNDING: Australian Research Council and Australian National Health and Medical Research Council.
BACKGROUND: Respiratory Syncytial Virus (RSV) is the main cause of pediatric morbidity and mortality. The complex evolution of RSV creates a need for worldwide surveillance, which may assist in the understanding of multiple viral aspects. OBJECTIVES: This study aimed to investigate RSV features under the Brazilian Influenza Surveillance Program, evaluating the role of viral load and genetic diversity in disease severity and the influence of climatic factors in viral seasonality. METHODOLOGY: We have investigated the prevalence of RSV in children up to 3 years of age with severe acute respiratory infection (SARI) in the state of Espirito Santo (ES), Brazil, from 2016 to 2018. RT-qPCR allowed for viral detection and viral load quantification, to evaluate association with clinical features and mapping of local viral seasonality. Gene G sequencing and phylogenetic reconstruction demonstrated local genetic diversity. RESULTS: Of 632 evaluated cases, 56% were caused by RSV, with both subtypes A and B co-circulating throughout the years. A discrete inverse association between average temperature and viral circulation was observed. No correlation between viral load and disease severity was observed, but children infected with RSV-A presented a higher clinical severity score (CSS), stayed longer in the hospital, and required intensive care, and ventilatory support more frequently than those infected by RSV-B. Regarding RSV diversity, some local genetic groups were observed within the main genotypes circulation RSV-A ON1 and RSV-B BA, with strains showing modifications in the G gene amino acid chain. CONCLUSION: Local RSV studies using the Brazilian Influenza Surveillance Program are relevant as they can bring useful information to the global RSV surveillance. Understanding seasonality, virulence, and genetic diversity can aid in the development and suitability of antiviral drugs, vaccines, and assist in the administration of prophylactic strategies.
OBJECTIVE: The frequency and seasonality of viruses in tropical regions are scarcely reported. We estimated the frequency of seven respiratory viruses and assessed seasonality of respiratory syncytial virus (RSV) and influenza viruses in a tropical city. METHODS: Children (age ≤ 18 years) with acute respiratory infection were investigated in Salvador, Brazil, between July 2014 and June 2017. Respiratory viruses were searched by direct immunofluorescence and real-time polymerase chain reaction for detection of RSV, influenza A virus, influenza B virus, adenovirus (ADV) and parainfluenza viruses (PIV) 1, 2 and 3. Seasonal distribution was evaluated by Prais-Winsten regression. Due to similar distribution, influenza A and influenza B viruses were grouped to analyse seasonality. RESULTS: The study group comprised 387 cases whose median (IQR) age was 26.4 (10.5-50.1) months. Respiratory viruses were detected in 106 (27.4%) cases. RSV (n = 76; 19.6%), influenza A virus (n = 11; 2.8%), influenza B virus (n = 7; 1.8%), ADV (n = 5; 1.3%), PIV 1 (n = 5; 1.3%), PIV 3 (n = 3; 0.8%) and PIV 2 (n = 1; 0.3%) were identified. Monthly count of RSV cases demonstrated seasonal distribution (b3 = 0.626; P = 0.003). More than half (42/76 [55.3%]) of all RSV cases were detected from April to June. Monthly count of influenza cases also showed seasonal distribution (b3 = -0.264; P = 0.032). Influenza cases peaked from November to January with 44.4% (8/18) of all influenza cases. CONCLUSIONS: RSV was the most frequently detected virus. RSV and influenza viruses showed seasonal distribution. These data may be useful to plan the best time to carry out prophylaxis and to increase the number of hospital beds.
The emergence of the COVID-19 pandemic reinforced the central role of the One Health (OH) approach, as a multisectoral and multidisciplinary perspective, to tackle health threats at the human-animal-environment interface. This study assessed Brazilian preparedness and response to COVID-19 and zoonoses with a focus on the OH approach and equity dimensions. We conducted an environmental scan using a protocol developed as part of a multi-country study. The article selection process resulted in 45 documents: 79 files and 112 references on OH; 41 files and 81 references on equity. The OH and equity aspects are poorly represented in the official documents regarding the COVID-19 response, either at the federal and state levels. Brazil has a governance infrastructure that allows for the response to infectious diseases, including zoonoses, as well as the fight against antimicrobial resistance through the OH approach. However, the response to the pandemic did not fully utilize the resources of the Brazilian state, due to the lack of central coordination and articulation among the sectors involved. Brazil is considered an area of high risk for emergence of zoonoses mainly due to climate change, large-scale deforestation and urbanization, high wildlife biodiversity, wide dry frontier, and poor control of wild animals’ traffic. Therefore, encouraging existing mechanisms for collaboration across sectors and disciplines, with the inclusion of vulnerable populations, is required for making a multisectoral OH approach successful in the country.
The 2020 Atlantic hurricane season was notable for a record-setting 30 named storms while, contemporaneously, the COVID-19 pandemic was circumnavigating the globe. The active spread of COVID-19 complicated disaster preparedness and response actions to safeguard coastal and island populations from hurricane hazards. Major hurricanes Eta and Iota, the most powerful storms of the 2020 Atlantic season, made November landfalls just two weeks apart, both coming ashore along the Miskito Coast in Nicaragua’s North Caribbean Coast Autonomous Region. Eta and Iota bore the hallmarks of climate-driven storms, including rapid intensification, high peak wind speeds, and decelerating forward motion prior to landfall. Hurricane warning systems, combined with timely evacuation and sheltering procedures, minimized loss of life during hurricane impact. Yet these protective actions potentially elevated risks for COVID-19 transmission for citizens sharing congregate shelters during the storms and for survivors who were displaced post-impact due to severe damage to their homes and communities. International border closures and travel restrictions that were in force to slow the spread of COVID-19 diminished the scope, timeliness, and effectiveness of the humanitarian response for survivors of Eta and Iota. Taken together, the extreme impacts from hurricanes Eta and Iota, compounded by the ubiquitous threat of COVID-19 transmission, and the impediments to international humanitarian response associated with movement restrictions during the pandemic, acted to exacerbate harms to population health for the citizens of Nicaragua.
Foodborne diseases are a neglected research area, and despite the existence of many tools for diagnosis and genetic studies, very little is known about the effect of the landscape on the genetic diversity and presence of parasites. One of these foodborne disease is paragonimiasis, caused by trematodes of the genus Paragonimus, which is responsible for a high number of infections in humans and wild animals. The main Paragonimus sp reported in Mesoamerica is Paragonimus mexicanus, yet there are doubts about its correct identification as a unique species throughout the region. This, together with a lack of detailed knowledge about their ecology, evolution and differentiation, may complicate the implementation of control strategies across the Mesoamerican region. We had the goal of delimiting the species of P. mexicanus found throughout Mesoamerica and determining the effect of landscape and geology on the diversity and presence of the parasite. We found support for the delimitation of five genetic groups. The genetic differentiation among these groups was positively affected by elevation and the isolation of river basins, while the parasite’s presence was affected negatively only by the presence of human settlements. These results suggest that areas with lower elevation, connected rivers basins, and an absence of human settlements have low genetic differentiation and high P. mexicanus presence, which may increase the risk of Paragonimus infection. These demonstrate the importance of accurate species delimitation and consideration of the effect of landscape on Paragonimus in the proposal of adequate control strategies. However, other landscape variables cannot be discarded, including temperature, rainfall regime, and spatial scale (local, landscape and regional). These additional variables were not explored here, and should be considered in future studies.
BACKGROUND: The burden of gastrointestinal infections related to hot ambient temperature remains largely unexplored in low-to-middle income countries which have most of the cases globally and are experiencing the greatest impact from climate change. The situation is particularly true in Brazil. OBJECTIVES: Using medical records covering over 78 % of population, we quantify the association between high temperature and risk of hospitalization for gastrointestinal infection in Brazil between 2000 and 2015. METHODS: Data on hospitalization for gastrointestinal infection and weather conditions were collected from 1814 Brazilian cities during the 2000-2015 hot seasons. A time-stratified case-crossover design was used to estimate the association. Stratified analyses were performed by region, sex, age-group, type of infection and early/late study period. RESULTS: For every 5 °C increase in mean daily temperature, the cumulative odds ratio (OR) of hospitalization over 0-9 days was 1.22 [95 % confidence interval (CI): 1.21, 1.23] at the national level, reaching its maximum in the south and its minimum in the north. The strength of association tended to decline across successive age-groups, with infants < 1 year most susceptible. The effect estimates were similar for men and women. Waterborne and foodborne infections were more associated with high temperature than the 'others' and 'idiopathic' groups. There was no substantial change in the association over the 16-year study period. DISCUSSION: Our findings indicate that exposure to high temperature is associated with increased risk of hospitalization for gastrointestinal infection in the hot season, with the strength varying by region, population subgroup and infection type. There was no evidence to indicate adaptation to heat over the study duration.
We evaluated species richness, abundance, alpha diversity, and true diversity of Phlebotominae sand flies temporal changes in domiciles within the northern Argentina city of Corrientes. A total of 16 sampling nights were conducted seasonally throughout the years 2012-2014 through light traps supplemented with CO2. Meteorological and remote sensing environmental factors were used to assessed for vectors implications in disease transmission through Generalized Mixt Models. Lutzomyia longipalpis was the most abundant and common species, followed by Nyssomyia neivai and Migonemyia migonei. Lutzomyia longipalpis was more abundant in urban areas, Ny. neivai was associated with vegetation in periurban areas, both were found all sampling years with higher abundance during the rainy season. Positive association of Lu. longipalpis with precipitation and relative humidity and negative association with temperature were observed. Models showed humidity and vegetation as making effects on Lu. longipalpis abundance. Precipitation was significant for Mg. migonei models, with higher abundance in periurban and periurban-rural environments. For Ny. neivai models, relative humidity was the most important variable, followed by precipitation frequency. Our findings led to identify high risk areas and develop predictive models. These are useful for public health stakeholders giving tolls to optimized resources aim to prevent leshmaniasis transmission on the area.
The Atlantic Forest is home to several arboviruses potentially pathogenic to humans. Therefore, it is crucial to assess the effects of seasonality on mosquito populations circulating in this domain. We evaluated the influence of seasonal variation on the oviposition activity of epidemiologically important mosquito populations in an Environmental Protection Area in Rio de Janeiro, Brazil. Mosquito eggs were collected using ovitraps for 1 year. During the sampling period, 1,086 eggs were collected. Of these, 39 (3.6%) did not hatch, and 1,047 (96.4%) reached the adult stage. Aedes albopictus (44.8%), Ae. terrens (6.4%), and Haemagogus leucocelaenus (48.8%) eggs and adults were identified. The changes in this community over the seasons were also analyzed. Season influence on the collections was significant. The highest numbers of collected eggs were collected in the summer and autumn, with Hg. leucocelaenus dominant in the summer and Ae. albopictus in the autumn. These two seasons were more similar to each other in terms of the composition of the collected mosquito community, forming a separate cluster from winter and spring groups. Summer, autumn, and winter presented values of Dominance (D), Shannon Diversity (H), and Evenness (J) closer to each other than spring. Climatic factors recorded throughout the collection period were not associated with egg abundance, except for temperature, which was positively correlated with Ae. albopictus presence. Finally, seasonality seemed to influence the oviposition activity of the three species recorded. Summer and autumn were the most critical seasons due to Ae. albopictus and Hg. leucocelaenus circulation. These findings should be considered in prophylaxis and implementation of entomological control strategies in the study area.
According to the World Health Organization, more than 80% of the world’s population lives in areas at risk of vector-borne diseases transmission. The Aedes aegypti mosquito is through its bite the responsible vector for transmitting many diseases, such as dengue, Zika, and chikungunya fever, with 50-100 million estimated cases of dengue fever yearly worldwide. The vector control is the recommended action to mitigate the transmission, but public health organizations face limitations on budget, mainly in emerging countries. In that sense, the efficiency in vector control with fewer costs becomes reasonably desirable. The present work aims to develop an optimization procedure on a new rainfall dependent nonlinear dynamic population model, which is adjusted by the data obtained from females captured in traps. Thus, we can find solutions that contribute to reduce the vector infestation and minimize both the social and economic costs involved. The problem is approached over two different strategies: simultaneous step size control (SSC) and simultaneous descending control (SDC). Control strategies may vary according to the type of control, the time, and the application period throughout the year. Numerical simulations consider the case for the city of Lavras, Minas Gerais State, Brazil, during the spring and summer. The Real-Biased Genetic Algorithm was used in a mono-objective optimization problem to find optimal intervention solutions. The findings indicate policy solutions with a low total cost and a high efficiency, reflecting the decline in vector populations according to the weather. (c) 2020 Elsevier Inc. All rights reserved.
Dengue virus remains a significant public health challenge in Brazil, and seasonal preparation efforts are hindered by variable intra- and interseasonal dynamics. Here, we present a framework for characterizing weekly dengue activity at the Brazilian mesoregion level from 2010-2016 as time series properties that are relevant to forecasting efforts, focusing on outbreak shape, seasonal timing, and pairwise correlations in magnitude and onset. In addition, we use a combination of 18 satellite remote sensing imagery, weather, clinical, mobility, and census data streams and regression methods to identify a parsimonious set of covariates that explain each time series property. The models explained 54% of the variation in outbreak shape, 38% of seasonal onset, 34% of pairwise correlation in outbreak timing, and 11% of pairwise correlation in outbreak magnitude. Regions that have experienced longer periods of drought sensitivity, as captured by the “normalized burn ratio,” experienced less intense outbreaks, while regions with regular fluctuations in relative humidity had less regular seasonal outbreaks. Both the pairwise correlations in outbreak timing and outbreak trend between mesoresgions were best predicted by distance. Our analysis also revealed the presence of distinct geographic clusters where dengue properties tend to be spatially correlated. Forecasting models aimed at predicting the dynamics of dengue activity need to identify the most salient variables capable of contributing to accurate predictions. Our findings show that successful models may need to leverage distinct variables in different locations and be catered to a specific task, such as predicting outbreak magnitude or timing characteristics, to be useful. This advocates in favor of “adaptive models” rather than “one-size-fits-all” models. The results of this study can be applied to improving spatial hierarchical or target-focused forecasting models of dengue activity across Brazil.
BACKGROUND: Phlebotomines are a group of insects which include vectors of the Leishmania parasites that cause visceral leishmaniasis (VL) and cutaneous leishmaniasis (CL), diseases primarily affecting populations of low socioeconomic status. VL in Brazil is caused by Leishmania infantum, with transmission mainly attributed to Lutzomyia longipalpis, a species complex of sand fly, and is concentrated mainly in the northeastern part of the country. CL is distributed worldwide and occurs in five regions of Brazil, at a higher incidence in the north and northeast regions, with etiological agents, vectors, reservoirs and epidemiological patterns that differ from VL. The aim of this study was to determine the composition, distribution and ecological relationships of phlebotomine species in an Atlantic Forest conservation unit and nearby residential area in northeastern Brazil. METHODS: Centers for Disease Control and Shannon traps were used for collections, the former at six points inside the forest and in the peridomestic environment of surrounding residences, three times per month for 36 months, and the latter in a forest area, once a month for 3 months. The phlebotomines identified were compared with climate data using simple linear correlation, Pearson’s correlation coefficient and cross-correlation. The estimate of ecological parameters was calculated according to the Shannon-Wiener diversity index, standardized index of species abundance and the dominance index. RESULTS: A total of 75,499 phlebotomines belonging to 11 species were captured in the CDC traps, the most abundant being Evandromyia walkeri, Psychodopygus wellcomei and Lu. longipalpis. Evandromyia walkeri abundance was most influenced by temperature at collection time and during the months preceding collection and rainfall during the months preceding collection. Psychodopygus wellcomei abundance was most affected by rainfall and relative humidity during the collection month and the month immediately preceding collection time. Lutzomyia longipalpis abundance showed a correlation with temperature and the rainfall during the months preceding collection time. The Shannon trap contained a total of 3914 phlebotomines from these different species. Psychodopygus wellcomei, accounting for 91.93% of the total, was anthropophilic and active mainly at night. CONCLUSIONS: Most of the species collected in the traps were seasonal and exhibited changes in their composition and population dynamics associated with local adaptions. The presence of vectors Ps. wellcomei and Lu. longipalpis underscore the epidemiological importance of these phlebotomines in the conservation unit and surrounding anthropized areas. Neighboring residential areas should be permanently monitored to prevent VL or CL transmission and outbreaks.
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.
Este reporte corresponde al capítulo de la guía de la CMNUCC bajo el título: Programas que comprenden medidas para facilitar la adecuada adaptación al cambio climático.
La Convención Marco de Naciones Unidas sobre el Cambio Climático (CMNUCC) establece que los países firmantes, deben informar periódicamente a la Conferencia de las Partes (CP) sobre tres puntos básicos por medio de las Comunicaciones Nacionales (CN):
Fuentes de emisión y absorción de gases de efecto invernadero
Información relevante para el logro del objetivo de la Convención
Programas nacionales sobre mitigación y que faciliten la adecuada adaptación al cambio.
Con el fin de facilitar el reporte de la información en una forma transparente, comparable y flexible, la secretaría de la CMNUCC ha preparado instrumentos que guían la elaboración de las CN (UNFCC, 2004). Estas guías han servido de marco para adecuar la información de vulnerabilidad y adaptación de sectores relevantes para la economía y la sociedad costarricense, con el fin de que sirvan como plataforma de conocimiento para que el país inicie el camino de la adaptación ante el cambio climático con un sentido de desarrollo y aprovechamiento de oportunidades.
El Sistema de Alerta Temprana en Incendios Forestales (SATIF) permite evaluar los distintos elementos que afectan la probable ocurrencia y el potencial comportamiento del fuego; así mismo es de importancia para planificar la prevención y el control de incendios, ayudando a una mejor asignación de los recursos.
El SATIF, se basa únicamente en el cálculo de las siguientes variables meteorológicas: Temperatura (ºC),
Humedad Relativa (%), Velocidad del Viento (km/h), Lluvia (mm).
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.
Mosquitoes are the most crucial insects in public health due to their vector capacity and competence to transmit pathogens, including arboviruses, bacterias and parasites. Re-emerging and emerging arboviral diseases, such as yellow fever virus (YFV), dengue virus (DENV), zika virus (ZIKV), and chikungunya virus (CHIKV), constitute one of the most critical health public concerns in Latin America. These diseases present a significant incidence within the human settlements increasing morbidity and mortality events. Likewise, among the different genus of mosquito vectors of arboviruses, those of the most significant medical importance corresponds to Aedes and Culex. In Latin America, the mosquito vector species of YFV, DENV, ZIKV, and CHIKV are mainly Aedes aegypti and Ae. Albopictus. Ae. aegypti is recognized as the primary vector in urban environments, whereas Ae. albopictus, recently introduced in the Americas, is more prone to rural settings. This minireview focuses on what is known about the epidemiological impact of mosquito-borne diseases in Latin American countries, with particular emphasis on YFV, DENV, ZIKV and CHIKV, vector mosquitoes, geographic distribution, and vector-arbovirus interactions. Besides, it was analyzed how climate change and social factors have influenced the spread of arboviruses and the control strategies developed against mosquitoes in this continent.
Climatic change will have an impact on production and release of pollen, with consequences for the duration and magnitude of aeroallergen seasonal exposure and allergic diseases. Evaluations of pollen aerobiology in the southern hemisphere have been limited by resourcing and the density of monitoring sites. This review emphasizes inconsistencies in pollen monitoring methods and metrics used globally. Research should consider unique southern hemisphere biodiversity, climate, plant distributions, standardization of pollen aerobiology, automation, and environmental integration. For both hemispheres, there is a clear need for better understanding of likely influences of climate change and comprehending their impact on pollen-related health outcomes.
This paper highlights the important leadership role of the public health sector, working with other governmental sectors and nongovernmental entities, to advance environmental public health in Latin America and the Caribbean toward the achievement of 2030 Sustainable Development Goal 3: Health and Well-Being. The most pressing current and future environmental public health threats are discussed, followed by a brief review of major historical and current international and regional efforts to address these concerns. The paper concludes with a discussion of three major components of a regional environmental public health agenda that responsible parties can undertake to make significant progress toward ensuring the health and well-being of all people throughout Latin America and the Caribbean.
Almost half of the Brazilian population has no access to sewage collection and treatment. Untreated effluents discharged in waters of reservoirs for human supply favor the flowering of cyanobacteria – and these microorganisms produce toxins, such as saxitoxin, which is a very potent neurotoxin present in reservoirs in the Northeast region. A recent study confirmed that chronic ingestion of neurotoxin-infected water associated with Zika virus infection could lead to a microcephaly-like outcome in pregnant mice. Cyanobacteria benefit from hot weather and organic matter in water, a condition that has been intensified by climate change, according to our previous studies. Considering the new findings, we emphasize that zika arbovirus is widespread and worsened when associated with climate change, especially in middle- or low-income countries with low levels of sanitation coverage.
Degradation of rainforest, extreme weather events, and climate change affect the spread of mosquito borne diseases like dengue, chikungunya, and Zika, write Rachel Lowe and colleagues. Urgent action is needed
INTRODUCTION: Yellow fever (YF) is primarily transmitted by Haemagogus species of mosquitoes. Under climate change, mosquitoes and the pathogens that they carry are expected to develop faster, potentially impacting the case count and duration of YF outbreaks. The aim of this study was to determine how YF virus outbreaks in Brazil may change under future climate, using ensemble simulations from regional climate models under RCP4.5 and RCP8.5 scenarios for three time periods: 2011-2040 (short-term), 2041-2070 (mid-term), and 2071-2100 (long-term). METHODS: A compartmental model was developed to fit the 2017/18 YF outbreak data in Brazil using least squares optimization. To explore the impact of climate change, temperature-sensitive mosquito parameters were set to change over projected time periods using polynomial equations fitted to their relationship with temperature according to the average temperature for years 2011-2040, 2041-2070, and 2071-2100 for climate change scenarios using RCP4.5 and RCP8.5, where RCP4.5/RCP8.5 corresponds to intermediate/high radiative forcing values and to moderate/higher warming trends. A sensitivity analysis was conducted to determine how the temperature-sensitive parameters impacted model results, and to determine how vaccination could play a role in reducing YF in Brazil. RESULTS: Yellow fever case projections for Brazil from the models varied when climate change scenarios were applied, including the peak clinical case incidence, cumulative clinical case incidence, time to peak incidence, and the outbreak duration. Overall, a decrease in YF cases and outbreak duration was observed. Comparing the observed incidence in 2017/18 to the projected incidence in 2070-2100, for RCP4.5, the cumulative case incidence decreased from 184 to 161, and the outbreak duration decreased from 21 to 20 weeks. For RCP8.5, the peak case incidence decreased from 184 to 147, and the outbreak duration decreased from 21 to 17 weeks. The observed decrease was primarily due to temperature increasing beyond that suitable for Haemagogus mosquito survival. CONCLUSIONS: Climate change is anticipated to have an impact on mosquito-borne diseases. We found outbreaks of YF may reduce in intensity as temperatures increase in Brazil; however, temperature is not the only factor involved with disease transmission. Other factors must be explored to determine the attributable impact of climate change on mosquito-borne diseases.
BACKGROUND: Both the World Health Organization and the Intergovernmental Panel on Climate Change project that malnutrition will be the greatest contributor to climate change-associated morbidity and mortality. Although there have been several studies that have examined the potential effects of climate change on human health broadly, the effects on malnutrition are still not well understood. We conducted a systematic review investigating the role of three climate change proxies (droughts, floods, and climate variability) on malnutrition in children and adults. METHODS AND FINDINGS: We identified 22 studies examining the effects of droughts, floods, and climate variability on at least one malnutrition metric. We found that 17 out of 22 studies reported a significant relationship between climate change proxies and at least one malnutrition metric. In meta-analysis, drought conditions were significantly associated with both wasting (Odds Ratio [OR] 1.46, 95% Confidence Interval [CI] 1.05-2.04) and underweight prevalence (OR 1.46, 95% CI 1.01-2.11). CONCLUSIONS: Given the long-term consequences of malnutrition on individuals and society, adoption of climate change adaptation strategies such as sustainable agriculture and water irrigation practices, as well as improving nutritional interventions aimed at children aged 1-2 years and older adults, should be prioritised on global policy agendas in the coming years.
Environmental variables related to vegetation and weather are some of the most influential factors that impacting Aedes (Stegomya) aegypti, a mosquito vector of dengue, chikungunya and Zika viruses. In this paper, we aim to develop temporal predictive models for Ae. aegypti oviposition activity utilizing vegetation and meteorological variables as predictors in Córdoba city (Argentina). Eggs were collected using ovitraps placed throughout the city from 2009 to 2012 that were replaced weekly. Temporal generalized linear mixed models were developed with negative binomial distributions of errors that model average number of eggs collected weekly as a function of vegetation and meteorological variables with time lags. The best model included a vegetation index, vapor pressure of water, precipitation and photoperiod. With each unit of increment in vegetation index per week the average number of eggs increased by 1.71 in the third week. Furthermore, each millimeter increase of accumulated rain during 4 weeks was associated with a decrease of 0.668 in the average number of eggs found in the following week. This negative effect of precipitation could occur during abundant rainfalls that fill containers completely, thereby depriving females of oviposition sites and leading them to search for other suitable breeding sites. Furthermore, the average number of eggs increased with the photoperiod at low values of mean vapor pressure; however the average number of eggs decreased at high values of mean vapor pressure, and the positive relationship between the response variable and mean vapor pressure was stronger at low values of photoperiod. Additionally, minimum temperature was associated positively with oviposition activity and that low minimum temperatures could be a limiting factor in Ae. aegypti oviposition activity. Our results emphasize the important role that climatic variables such as temperature, precipitation, and vapor pressure play in Ae. aegypti oviposition activity and how these variables along with vegetation indices can be used to inform predictive temporal models of Ae. aegypti population dynamics that can be used for informing mosquito population control and arbovirus mitigation strategies.
Experiments and models suggest that climate affects mosquito-borne disease transmission. However, disease transmission involves complex nonlinear interactions between climate and population dynamics, which makes detecting climate drivers at the population level challenging. By analysing incidence data, estimated susceptible population size, and climate data with methods based on nonlinear time series analysis (collectively referred to as empirical dynamic modelling), we identified drivers and their interactive effects on dengue dynamics in San Juan, Puerto Rico. Climatic forcing arose only when susceptible availability was high: temperature and rainfall had net positive and negative effects respectively. By capturing mechanistic, nonlinear and context-dependent effects of population susceptibility, temperature and rainfall on dengue transmission empirically, our model improves forecast skill over recent, state-of-the-art models for dengue incidence. Together, these results provide empirical evidence that the interdependence of host population susceptibility and climate drives dengue dynamics in a nonlinear and complex, yet predictable way.
Aedes albopictus (Diptera: Culicidae) distribution is bounded to a subtropical area in Argentina, while Aedes aegypti (Diptera: Culicidae) covers both temperate and subtropical regions. We assessed thermal and photoperiod conditions on dormancy status, development time and mortality for these species from subtropical Argentina. Short days (8 light : 16 dark) significantly increased larval development time for both species, an effect previously linked to diapause incidence. Aedes albopictus showed higher mortality than Ae. aegypti at 16?°C under long day treatments (16 light : 8 dark), which could indicate a lower tolerance to a sudden temperature decrease during the summer season. Aedes albopictus showed a slightly higher percentage of dormant eggs from females exposed to a short day, relative to previous research in Brazilian populations. Since we employed more hours of darkness, this could suggest a relationship between day-length and dormancy intensity. Interestingly, local Ae. aegypti presented dormancy similar to Ae. albopictus, in accordance with temperate populations. The minimum dormancy in Ae. albopictus would not be sufficient to extend its bounded distribution. We believe that these findings represent a novel contribution to current knowledge about the ecophysiology of Ae. albopictus and Ae. aegypti, two species with great epidemiological relevance in this subtropical region.
Brazil is the country with the highest social inequality in South America. This socioeconomic disparity reflects not only on the families’ income but also on their spatial localization in the city, as well as on the urban design. These urban environments can alter the urban microclimate, and consequently, interfere in dwellers’ thermal comfort. This research investigated the relationship between socio-spatial inequalities and thermal comfort in two different Local Climate Zones (LCZ) using a combination of measurement and modeling. Air temperature (Tair) was obtained by on-site measurements in compact high-rise (LCZ1) and compact low-rise buildings (LCZ3) and Mean radiant temperature (Tmrt) was simulated using SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG). The results indicated that in LCZ1 seafront-localized buildings, in which residents have a higher income, the temperature remains in a range classified as comfortable, mainly due to shading and sea breeze. On the other hand, LCZ3, located in the periphery of the city, in which the low-income population is concentrated and is marked by a precariousness urban environment, presented a higher air temperature and Tmrt values, exposing the dwellers to heat stress throughout the year, especially during the summer season. These observations suggested that public and private actions tend to promote better urban designs in areas with a higher concentration of income. Public reforms aimed at improving the urban environment and promoting thermal comfort should be a priority for the warmest LCZ, where the poorest residents live. Public agents should rethink the distribution of environmental resources to promote equitable urban spaces.
Desert dust transported from the Saharan-Sahel region to the Caribbean Sea is responsible for peak exposures of particulate matter (PM). This study explored the potential added value of satellite aerosol optical thickness (AOT) measurements, compared to the PM concentration at ground level, to retrospectively assess exposure during pregnancy. MAIAC MODIS AOT retrievals in blue band (AOT(470)) were extracted for the French Guadeloupe archipelago. AOT(470) values and PM(10) concentrations were averaged over pregnancy for 906 women (2005-2008). Regression modeling was used to examine the AOT(470)-PM(10) relationship during pregnancy and test the association between dust exposure estimates and preterm birth. Moderate agreement was shown between mean AOT(470) retrievals and PM(10) ground-based measurements during pregnancy (R(2)?=?0.289). The magnitude of the association between desert dust exposure and preterm birth tended to be lower using the satellite method compared to the monitor method. The latter remains an acceptable trade-off between epidemiological relevance and exposure misclassification, in areas with few monitoring stations and complex topographical/meteorological conditions, such as tropical islands.
Amazonian populations are increasingly exposed to climatic shocks, yet knowledge of related health impacts is limited. Understanding how health risks are coproduced by local climatic variability, place and social inequities is vital for improving decision-making, particularly in decentralized contexts. We assess the impacts of rainfall variability and multiscale vulnerabilities on birth weight, which has lifelong health consequences. We focus on highly river-dependent areas in Amazonia, using urban and rural birth registrations during 2006-2017. We find a strong but spatially differentiated relationship between local rainfall and subsequent river-level anomalies. Using Bayesian models, we disentangle the impacts of rainfall shocks of different magnitudes, municipal characteristics, social inequities and seasonality. Prenatal exposure to extremely intense rainfall is associated with preterm birth, restricted intra-uterine growth and lower mean birth weight (<=-183 g). Adverse birth outcomes also follow non-extreme intense rainfall (40% higher odds of low birth weight), drier conditions than seasonal averages (-39 g mean birth weight) and conception in the rising-water season (-13 g mean birth weight). Babies experience penalties totalling 646 g when born to adolescent, Amerindian, unmarried mothers that received no formal education or antenatal or obstetric health care. Rainfall variability confers intergenerational disadvantage, especially for socially marginalized Amazonians in forgotten places. Structural changes are required to reduce inequities, foster citizen empowerment and improve the social accountability of public institutions. Amazonians are subject to climate shocks, but the associated health outcomes are still unclear. This study finds that rainfall variability is associated with adverse birth outcomes, especially for those most isolated and marginalized.
In Colombia, little is known on the distribution of the Asian mosquito Aedes albopictus, main vector of dengue, chikungunya, and Zika in Asia and Oceania. Therefore, this work sought to estimate its current and future potential geographic distribution under the Representative Concentration Paths (RCP) 2.6 and 8.5 emission scenarios by 2050 and 2070, using ecological niche models. For this, predictions were made in MaxEnt, employing occurrences of A. albopictus from their native area and South America and bioclimatic variables of these places. We found that, from their invasion of Colombia to the most recent years, A. albopictus is present in 47% of the country, in peri-urban (20%), rural (23%), and urban (57%) areas between 0 and 1800 m, with Antioquia and Valle del Cauca being the departments with most of the records. Our ecological niche modelling for the currently suggests that A. albopictus is distributed in 96% of the Colombian continental surface up to 3000 m (p < 0.001) putting at risk at least 48 million of people that could be infected by the arboviruses that this species transmits. Additionally, by 2050 and 2070, under RCP 2.6 scenario, its distribution could cover to nearly 90% of continental extension up to 3100 m (?55 million of people at risk), while under RCP 8.5 scenario, it could decrease below 60% of continental extension, but expand upward to 3200 m (< 38 million of people at risk). These results suggest that, currently in Colombia, A. albopictus is found throughout the country and climate change could diminish eventually its area of distribution, but increase its altitudinal range. In Colombia, surveillance and vector control programs must focus their attention on this vector to avoid complications in the national public health setting.
Climate change has direct effects on the availability and quality of water for human consumption. In order to propose actions aimed at reducing vulnerability caused by water shortages and risk management required due to extreme events, real knowledge of the community`s perception is vital. This study developed in the department of Caldas, in the Colombian Andean region, analysed the perception of the incidence of climate change particularly related to water resources. To achieve this, a survey was used with various actors based on the first National Survey of Public Perception of Climate Change. The results show that the respondents perceive that the availability and quality of water are indeed highly threatened by climate change. As actions for adaptation, they suggested the promotion of the protection of hydrographic basins and a greater control of dumping liquids into surface water sources. Finally, they requested increased opportunities to improve water governance and participation in decision-making bodies regarding climate change, which they see as a fundamental aspect to achieve a real climate empowerment that can lead to action and adaptation in the territories in emerging countries.
Mosquitoes propagate many human diseases, some widespread and with no vaccines. The Ae. aegypti mosquito vector transmits Zika, Chikungunya, and Dengue viruses. Effective public health interventions to control the spread of these diseases and protect the population require models that explain the core environmental drivers of the vector population. Field campaigns are expensive, and data from meteorological sites that feed models with the required environmental data often lack detail. As a consequence, we explore temporal modeling of the population of Ae. aegypti mosquito vector species and environmental conditions- temperature, moisture, precipitation, and vegetation- have been shown to have significant effects. We use earth observation (EO) data as our source for estimating these biotic and abiotic environmental variables based on proxy features, namely: Normalized difference vegetation index, Normalized difference water index, Precipitation, and Land surface temperature. We obtained our response variable from field-collected mosquito population measured weekly using 791 mosquito traps in Vila Velha city, Brazil, for 36 weeks in 2017, and 40 weeks in 2018. Recent similar studies have used machine learning (ML) techniques for this task. However, these techniques are neither intuitive nor explainable from an operational point of view. As a result, we use a Generalized Linear Model (GLM) to model this relationship due to its fitness for count response variable modeling, its interpretability, and the ability to visualize the confidence intervals for all inferences. Also, to improve our model, we use the Akaike Information Criterion to select the most informative environmental features. Finally, we show how to improve the quality of the model by weighting our GLM. Our resulting weighted GLM compares well in quality with ML techniques: Random Forest and Support Vector Machines. These results provide an advancement with regards to qualitative and explainable epidemiological risk modeling in urban environments.
The Middle Paranapanema region in the state of São Paulo, Brazil, is an area with high diversity for Biomphalaria species, with municipalities historically marked by cases of schistosomiasis transmission. The objectives of the study were to evaluate the current distribuition and predict the future distribution of habitats of Biomphalaria species at a high spatial resolution along 114 freshwater sites in the Middle Paranapanema watershed. The modelling encompassed 55 municipalities of the Middle Paranapanema region, which were analyzed through the maximum entropy algorithm. All geographic coordinates of the Biomphalaria species collected from 2015-2018 and environmental data were obtained through WorldClim, HydroSHEDS, TOPODATA and Secretaria do Meio Ambiente for the 1970-2017 period. For the 2041-2060 period we used the HadGEM2-ES climate model. Due to climate change, MaxEnt showed that there was a high probability for the maintenance of B. glabrata habitats near Ourinhos and Assis, an expansion of scattered spots, and a 50% probability that the species will spread throughout new suitable areas. The results showed that the geographical range of B. straminea will most likely expand in the future along the Middle Paranapanema hydrographic basin, especially in the municipalities near Ourinhos. For B. glabrata and B. straminea, the geographic expansion was related to the predicted increase in the annual temperature range. The habitats suitable for B. tenagophila and B. peregrina seemed to slightly expand around the west border of the Middle Paranapanema region. Biomphalaria occidentalis may have a small reduction in its distribution due to climate change. The variables that contributed the most to the future modelling for these three species were precipitation and temperature. Identifying the sites with intermediate hosts for schistosomiasis may guide public health measures to avoid or reduce future transmissions in this region.
Over the past decade, Brazil has experienced and continues to be impacted by extreme climate events. This study aims to evaluate the association between daily average temperature and mortality from respiratory disease among Brazilian elderlies. A daily time-series study between 2000 and 2017 in 27 Brazilian cities was conducted. Data outcomes were daily counts of deaths due to respiratory diseases in the elderly aged 60 or more. The exposure variable was the daily mean temperature from Copernicus ERA5-Land reanalysis. The association was estimated from a two-stage time series analysis method. We also calculated deaths attributable to heat and cold. The pooled exposure-response curve presented a J-shaped format. The exposure to extreme heat increased the risk of mortality by 27% (95% CI: 15-39%), while the exposure to extreme cold increased the risk of mortality by 16% (95% CI: 8-24%). The heterogeneity between cities was explained by city-specific mean temperature and temperature range. The fractions of deaths attributable to cold and heat were 4.7% (95% CI: 2.94-6.17%) and 2.8% (95% CI: 1.45-3.95%), respectively. Our results show a significant impact of non-optimal temperature on the respiratory health of elderlies living in Brazil. It may support proactive action implementation in cities that have critical temperature variations.
BACKGROUND: Global temperatures are projected to rise by ?2?°C by the end of the century, with expected impacts on infectious disease incidence. Establishing the historic relationship between temperature and childhood diarrhea is important to inform future vulnerability under projected climate change scenarios. METHODS: We compiled a national dataset from Peruvian government data sources, including weekly diarrhea surveillance records, annual administered doses of rotavirus vaccination, annual piped water access estimates, and daily temperature estimates. We used generalized estimating equations to quantify the association between ambient temperature and childhood (
Most of the recent epidemic outbreaks in the world have as a trigger, a strong migratory component as has been evident in the recent Covid-19 pandemic. In this work we address the problem of migration of human populations and its effect on pathogen reinfections in the case of Dengue, using a Markov-chain susceptible-infected-susceptible (SIS) metapopulation model over a network. Our model postulates a general contact rate that represents a local measure of several factors: the population size of infected hosts that arrive at a given location as a function of total population size, the current incidence at neighboring locations, and the connectivity of the network where the disease spreads. This parameter can be interpreted as an indicator of outbreak risk at a given location. This parameter is tied to the fraction of individuals that move across boundaries (migration). To illustrate our model capabilities, we estimate from epidemic Dengue data in Mexico the dynamics of migration at a regional scale incorporating climate variability represented by an index based on precipitation data.
Climate-induced relocation is expected to become an adaptive response for one sector of the society that is otherwise already in a vulnerable situation and often living in remote areas, that is, Indigenous Peoples. Several Latin American countries have referred to planned relocation or managed retreat as one of their adaptation strategies within their Nationally Determined Contributions to the United Nations Framework Convention on Climate Change. However, a gap in academic analysis exists regarding not only the potential impacts but also the consequences of climate-induced planned relocations both in the broader context of Latin America and in the specific case of Indigenous Peoples living in that region. In addition, academia has so far underexplored the adverse impacts of managed retreat on Indigenous Peoples, such as the loss of a sense of community, culture, and traditional knowledge. Against this background, this article offers an overview on two key cases of climate-induced (planned) relocation of Indigenous Peoples in Latin America and the Caribbean (the Gunayala people in the San Blás archipelago in Panama and the case of the densely Indigenous-inhabited Mexican state of Chiapas), explores whether managed retreat has been or may become a tool or a threat, and provides a list of specific policy recommendations to be taken into consideration in similar cases.
The International Agency for Research on Cancer (IARC) classifies benzene in group 1 (carcinogenic to humans). Particulate matter (PM) has recently also been classified in this category. This was an advance toward prioritizing the monitoring of particles in urban areas. The aim of the present study was to assess levels of PM(2.5) and BTEX (benzene, toluene, ethylbenzene, and xylene), the influence of meteorological variables, the planetary boundary layer (PBL), and urban variables as well as risks to human health in the city of Fortaleza, Brazil, in the wet and dry periods. BTEX compounds were sampled using the 1501 method of NIOSH and determined by GC-HS-PID/FID. PM(2.5) was monitored using an air sampling pump with a filter holder and determined by the gravimetric method. Average concentrations of BTEX ranged from 1.6 to 45.5 ?g m(-3), with higher values in the wet period, which may be explained by the fact that annual distribution is influenced by meteorological variables and the PBL. PM(2.5) levels ranged from 4.12 to 33.0 ?g m(-3) and 4.18 to 86.58 ?g m(-3) in the dry and wet periods, respectively. No seasonal pattern was found for PM(2.5), probably due to the influence of meteorological variables, the PBL, and urban variables. Cancer risk ranged from 2.46E(-04) to 4.71E(-03) and 1.72E(-04) to 2.01E(-03) for benzene and from 3.07E(-06) to 7.04E(-05) and 3.08E(-06) to 2.85E(-05) for PM(2.5) in the wet and dry periods, respectively. Cancer risk values for benzene were above the acceptable limit established by the international regulatory agency in both the dry and wet periods. The results obtained of the noncarcinogenic risks for the compounds toluene, ethylbenzene, and xylene were within the limits of acceptability. The findings also showed that the risk related to PM is always greater among smokers than nonsmokers.
The impact of heat waves and cold spells on mortality has become a major public health problem worldwide, especially among older adults living in low-to middle-income countries. This study aimed to investigate the effects of heat waves and cold spells under different definitions on cause-specific mortality among people aged ?65 years in São Paulo from 2006 to 2015. A quasi-Poisson generalized linear model with a distributed lag model was used to investigate the association between cause-specific mortality and extreme air temperature events. To evaluate the effects of the intensity under different durations, we considered twelve heat wave and nine cold spell definitions. Our results showed an increase in cause-specific deaths related to heat waves and cold spells under several definitions. The highest risk of death related to heat waves was identified mostly at higher temperature thresholds with longer events. We verified that men were more vulnerable to die from cerebrovascular diseases and ischemic stroke on cold spells and heat waves days than women, while women presented a higher risk of dying from ischemic heart diseases during cold spells and tended to have a higher risk of chronic obstructive pulmonary disease than men during heat waves. Identification of heat wave- and cold spell-related mortality is important for the development and promotion of public health measures.
Despite mitigation attempts, the trajectory of climate change remains on an accelerated path, with devastating health impacts. As a response to the United Nations Framework Convention on Climate Change call for National Adaptation Plans, Peru has developed a national and decentralized regional adaptation plans. The purpose of this article is to understand the role and priority status of health within the adaptation planning and process. Peru was used as a case study to analyse the policy process in the creation of adaptation plans, encompassing the need to address climate change impacts on health with a particular focus on marginalized people. An actor, content and context policy analyses were conducted to analyse 17 out of 25 regional adaptation plans, which are available. The national adaptation plans (2002, 2015) do not include health as a priority or health adaptation strategies. In a decentralized health care system, regional plans demonstrate an increased improvement of complexity, systematization and structure over time (2009-17). In general, health has not been identified as a priority but as another area of impact. There is no cohesiveness between plans in format, content, planning and execution and only a limited consideration for marginalized populations. In conclusion, the regional departments of Peru stand on unequal footing regarding adapting the health sector to climate change. Findings in the strategies call into question how mitigation and adaption to climate change may be achieved. The lack of local research on health impacts due to climate change and a particular focus on marginalized people creates a policy vacuum. The Peruvian case study resembles global challenges to put health in the centre of national and regional adaptation plans. In-depth cross-country analysis is still missing but urgently needed to learn from other experiences.
OBJECTIVES: This study compared the prevalence of concentrated urine (urine specific gravity ?1.021), an indicator of hypohydration, across Tsimane’ hunter-forager-horticulturalists living in hot-humid lowland Bolivia and Daasanach agropastoralists living in hot-arid Northern Kenya. It tested the hypotheses that household water and food insecurity would be associated with higher odds of hypohydration. METHODS: This study collected spot urine samples and corresponding weather data along with data on household water and food insecurity, demographics, and health characteristics among 266 Tsimane’ households (N = 224 men, 235 women, 219 children) and 136 Daasanach households (N = 107 men, 120 women, 102 children). RESULTS: The prevalence of hypohydration among Tsimane’ men (50.0%) and women (54.0%) was substantially higher (P?
Climate change is increasing the frequency and intensity of extreme events. Adaptation strategies at societal and household level are crucial to reduce vulnerability. We assessed to what extent personal flood affectedness, in particular health impacts, influence adaptive behavior. We conducted a cross-sectional survey in northern Chile one year after a major flood event and assessed several dimensions of flood affectedness and adaptive behavior at the household level. After the event, a wide range of adaptation measures, including water storage and prepa-ration of emergency kits, had been implemented by 80% of the population.
This study investigates the impact of future changes in climatic variables on dengue incidence in the region of the Tucurui dam in the Amazon. Tucurui dam is the one of the largest hydroelectric power stations in the Amazon. Correlations and regression analysis through least squares fitting between dengue cases and temperature, precipitation, and humidity are obtained. Positive correlations between dengue incidence and temperature are found for lags from 4 to 5 months (higher correlation for lag 5), dengue and precipitation for lags 0 up to 1, and dengue and humidity for lag 0. The positive correlations between dengue and precipitation and between dengue and humidity are higher for the simultaneous correlation. To investigate the impact of the future changes in these climatic variables in the region, projections of RegCM4 model simulations under the RCP 8.5 scenario are obtained. The model projections indicate a warming and moisture increase in the region near the dam at the end of the twenty-first century. Regression analysis using the model projections indicates that the dengue incidence may increase substantially in future climate scenarios in this region (more than fivefold compared with the present climate). This increase is between two and three times higher than the global estimates of dengue incidence in the future. It is suggested that the incidence of dengue cases is more sensitive to changes in temperature. Vector parameters increase with temperature in the future, indicating that the temperature conditions are highly favorable for the spread of the disease in the region. The results indicate that cities in the area surrounding the Tucurui hydroelectric dam are areas of potential dengue incidence in the future. These findings may be applied to hydroelectric dams in other areas of the world. However, future studies involving additional dams are necessary. The results suggest an increase in climate-driven risk of transmission from Aedes aegypti throughout the entire Amazon, and especially the eastern and southern parts.
Leptospirosis is a disease usually acquired by humans through water contaminated with the urine of rodents that comes into direct contact with the cutaneous lesions, eyes, or mucous membranes. The disease has an important environmental component associated with climatic conditions and natural disasters, such as floods. We analyzed the relationship between rainfall and temperature and the incidence of leptospirosis in the top 30 municipalities with the highest numbers of cases of the disease in the period of 2007 to 2016. It was an ecological study of the time series of cases of leptospirosis, rainfall, and temperature with lags of 0, 1, 2, 3, and 4 weeks. A multilevel negative binomial regression model was implemented to evaluate the relationship between leptospirosis and both meteorological factors. In the 30 evaluated municipalities during the study period, a total of 5136 cases of leptospirosis were reported. According to the implemented statistical model, there was a positive association between the incidence of leptospirosis and rainfall with a lag of 1 week and a negative association with temperature with a lag of 4 weeks. Our results show the importance of short-term lags in rainfall and temperature for the occurrence of new cases of leptospirosis in Colombia.
Cumulative and synergistic impacts from environmental pressures, particularly in low-lying tropical coastal regions, present challenges for the governance of ecosystems, which provide natural resource-based livelihoods for communities. Here, we seek to understand the relationship between responses to the impacts of El Niño and La Niña events and the vulnerability of mangrove-dependent communities in the Caribbean region of Colombia. Using two case study sites, we show how communities are impacted by, and undertake reactive short-term responses to, El Niño and La Niña events, and how such responses can affect their adaptive capacity to progressive environmental deterioration. We show that certain coping measures to climate variability currently deliver maladaptive outcomes, resulting in circumstances that could contribute to system ‘lock-in’ and engender undesirable ecological states, exacerbating future livelihood vulnerabilities. We highlight the significant role of social barriers on vulnerabilities within the region, including perceptions of state abandonment, mistrust and conflicts with authorities. Opportunities to reduce vulnerability include enhancing the communities’ capacity to adopt more positive and preventative responses based on demonstrable experiential learning capacity. However, these will require close cooperation between formal and informal organisations at different levels, and the development of shared coherent adaptation strategies to manage the complexity of multiple interacting environmental and climatic pressures.
The purpose of this article is to analyze how indigenous livelihoods are challenged by the global phenomenon of climate change while paying particular attention to how historically shaped, non-climatic factors influence how climate change is experienced in the Peruvian Amazon. In this sense, we will address indigenous people’s lived experiences of climate variations using a theoretical framework based on concepts of vulnerability. Methodologically, we draw on both a recent literature review and fieldwork conducted during 2015 and 2016 with two Kukama Kukamiria communities in Loreto (low jungle) and three Ashaninka communities in Junín (high jungle). After describing our theoretical framework and qualitative methods, we discuss the economic history of the addressed areas and show how non-climatic factors, such as colonialism, influence these communities’ experiences. This context allows us to better understand indigenous people’s experience of seasonal variations, precipitations and climatic events, its effect on their livelihoods, and their adaptive strategies in response to challenges imposed by climate unpredictability and broader transformations in their territories. Our conclusions are twofold: (a) addressing climate change must incorporate multiple temporal and spatial scales and (b) non-climatic factors are integral to understanding the role of climate change vulnerability of indigenous population.
The intensifying impacts of climate change pose a serious global threat, particularly for rural populations whose livelihoods are closely tied to natural resources. Yet there is a lack of critical understanding of how asymmetric power dynamics shape the vulnerabilities of such populations under climate change. This article examines the interrelations between smallholders’ climate-related vulnerability experiences and power relations across multiple scales of climate adaptation in the Peruvian Andes, a region susceptible to increasing climatic threats. The analysis draws on a case study conducted in the Mantaro River Valley in Central Peru using qualitative methods: open-ended interviews, participant observation, and document analysis. Findings of the study show that in the context of climate change, the production of vulnerabilities has much to do with larger socio-political structures in which protection of the highland farmers is not prioritized. The impact of the uneven scalar power dynamics in climate adaptation and other overlapping fields of policy have created uneven terms of adaptation among smallholders. This has created marginalization, conflicts, and deepened smallholders’ vulnerabilities under climate change. I argue that to reach a better understanding of the multidimensionality of vulnerabilities, more detailed attention must be paid to place-based climate experiences within context-specific, socio-political processes, and to the ways these are shaped by unequal power relations across multiple scales.
Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases, such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28-85% for vectors, 44-88% for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections.
BACKGROUND: The impact of simultaneous adverse climate conditions in the risk of myocardial infarction (MI) was not tested before. The aim of the present study was to investigate the impact of the combination of climate and air pollution features in the number of admissions and mortality due to acute myocardial infarction in 39 municipalities of São Paulo from 2012 to 2015. METHODS: Data about MI admissions were obtained from the Brazilian public health system (DataSUS). Daily information on weather were accessed from the Meteorological Database for Teaching and Research. Additionally, daily information on air pollution were obtained from the Environmental Company of the State of São Paulo. A hierarchical cluster analysis was applied for temperature, rainfall patterns, relative air humidity, nitrogen dioxide, particulate matter 2.5 and particulate matter 10. MI admissions and in-hospital mortality were compared among the clusters. RESULTS: Data analysis produced 3 clusters: High temperature variation-Low humidity-high pollution (n=218 days); Intermediate temperature variation/high humidity/intermediate pollution (n=751 days) and low temperature variation/intermediate humidity-low pollution (n=123 days). All environmental variables were significantly different among clusters. The combination of high temperature variation, dry weather and high pollution resulted in a significant 9% increase in hospital admissions for MI [30.5 (IQR 25.0-36.0)]; patients/day; P<0.01). The differences in weather and pollution did not have impact on in-hospital mortality (P=0.88). CONCLUSION: The combination of atmospheric conditions with high temperature variation, lower temperature, dryer weather and increased inhalable particles was associated with a marked increase of hospital admissions due to MI.
Climate change has been linked to poor childhood growth and development through maternal stress, nutritional insults related to lean harvests, and exposure to infectious diseases. Vulnerable populations are often most susceptible to these stressors. This study tested whether susceptibility to linear growth faltering is higher among Peruvian children from indigenous, rural, low-education, and low-income households. High-resolution weather and household survey data from Demographic and Health Survey 1996-2012 were used to explore height-for-age z-scores (HAZ) at each year of life from 0 to 5. Rural, indigenous children at age 0-1 experience a HAZ reduction of 0.35 units associated with prenatal excess rainfall which is also observed at age 4-5. Urban, non-indigenous children at age 4-5 experience a HAZ increase of 0.07 units associated with postnatal excess rainfall, but this advantage is not seen among rural, indigenous children. These findings highlight the need to consider developmental stage and social predictors as key components in public health interventions targeting increased climate change resilience.
Arboviral diseases are a theme of high interest in the field of public and collective health worldwide. Dengue, Zika, and Chikungunya, in particular, have shown significant expansion in terms of morbidity and mortality in different portions of the ecumene. These diseases are of great interest in geographic studies due to the characteristics of their vector (Aedes aegypti), adapted to the environmental and unequal context of the urbanization process. Given this background, this study assesses the relationship between global climate change and the risk of arboviral diseases for the state of Rio de Janeiro. To this end, the characteristics of future climate susceptibility to vector proliferation in the scenarios RCP 4.5 and 8.5 (2011-2040 and 2041-2070) were assessed using two models: Eta HadGEM2-ES and Eta MIROC5, as well as the vulnerability conditions that favor the spread of arboviruses. The results indicate that the tendency of thermal and hygrometric elevation, in association with vulnerability, may have repercussions on the intensification and spatial expansion of the risk of arboviral diseases in the state of Rio de Janeiro, since there is a spatial and temporal expansion of the optimal environmental conditions for the development of the vector.
Around 27% of South Americans live in central and southern Brazil. Of 19,400 human malaria cases in Brazil in 2018, some were from the southern and southeastern states. High abundance of malaria vectors is generally positively associated with malaria incidence. Expanding geographic distributions of Anopheles vector mosquito species (e.g. A. cruzii) in the face of climate change processes would increase risk of such malaria transmission; such risk is of particular concern in regions that hold human population concentrations near present limits of vector species’ geographic distributions. We modeled effects of likely climate changes on the distribution of A. cruzii, evaluating two scenarios of future greenhouse gas emissions for 2050, as simulated in 21 general circulation models and two greenhouse gas scenarios (RCP 4.5 and RCP 8.5) for 2050. We tested 1305 candidate models, and chose among them based on statistical significance, predictive performance, and complexity. The models closely approximated the known geographic distribution of the species under current conditions. Under scenarios of future climate change, we noted increases in suitable area for the mosquito vector species in São Paulo and Rio de Janeiro states, including areas close to 30 densely populated cities. Under RCP 8.5, our models anticipate areal increases of >75% for this important malaria vector in the vicinity of 20 large Brazilian cities. We developed models that anticipate increased suitability for the mosquito species; around 50% of Brazilians reside in these areas, and ?89% of foreign tourists visit coastal areas in this region. Under climate change thereefore, the risk and vulnerability of human populations to malaria transmission appears bound to increase.
Both global climate change and urbanization trends will demand adaptation measures in cities. Large agglomerations and impacts on landscape and natural environments due to city growth will require guided densification schemes in urban areas, particularly in developing countries. Human biometeorological indices such as the Universal Thermal Climate Index (UTCI) could guide this process, as they provide a clear account of expected effects on thermal sensation from a given change in outdoor settings. However, an earlier step should optimally include an adequacy test of suggested comfort and thermal stress ranges with calibration procedures based on surveys with the target population. This paper compares obtained thermal comfort ranges for three different locations in Brazil: Belo Horizonte, 20° S, Aw climate type; Curitiba, 25.5° S, Cfb subtropical climate, both locations in elevation (above 900 m a.s.l.); and Pelotas, at sea level, latitude 32° S, with a Cfa climate type. In each city, a set of outdoor comfort field campaigns has been carried out according to similar procedures, covering a wide range of climatic conditions over different seasons of the year. Obtained results indicate a variation of neutral temperatures up to 3 °C (UTCI units) as a possible latitude and local climate effect between the southern locations relative to the northernmost location. Low UTCI values were found in the two subtropical locations for the lower threshold of the thermal comfort band as compared with the original threshold. A possible explanation for that is a longer exposure to cold conditions as buildings are seldom provided with heating systems.
Spermatogenesis is a temperature-dependent process, and high summer temperatures have been linked to lower sperm concentration and count. However, reports describing the association between other meteorological variables and semen quality are scarce. This study evaluated the association between semen quality and temperature, humidity, pressure, apparent temperature (AT), temperature-humidity index (THI), simplified wet-bulb global temperature (sWBGT), and sunshine duration. Semen samples were obtained at the Laboratorio de Andrología y Reproducción (LAR, Argentina), from men undergoing routine andrology examination (n=11657) and computer-assisted sperm analysis (n=4705) following WHO 2010 criteria. Meteorological variables readings were obtained from the Sistema Meteorológico Nacional. Sperm quality parameters were negatively affected in summer when compared to winter. Additionally, there was a significant decrease in sperm kinematics between winter and spring. Branch and bound variable selection followed by multiple regression analysis revealed a significant association between semen quality and meteorological variables. Specifically, changes in sunshine duration and humidity reinforced the prognosis of semen quality. Highest/lowest sunshine duration and humidity quantiles resulted in decreased sperm concentration, count, motility, vitality and membrane competence, nuclear maturity, and sperm kinematics associated to highest sunshine duration and lowest humidity. Findings from this report highlight the relevance of environmental studies for predicting alterations in male reproductive health associated to variations in meteorological variables, especially considering the current climate changes around the planet due to global warming and its consequences for human health.
In the Northeast Brazil (NEB), the impacts of climate extreme events such as severe droughts are aggravated by poverty and poor socioeconomic conditions. In this region, such events usually result in the spread of endemic diseases, problems in water distribution, and agricultural losses, often leading to an increase in the population’s vulnerability. Thus, this study aims to evaluate the microregions of the Rio Grande do Norte (RN) state, in the NEB, according to the Epidemiological Index for Drought Vulnerability (EIDV). We mapped and classified the microregions according to three dimensions of vulnerability: risk, susceptibility, and adaptive capacity. We also verified potential associations between drought risk and epidemiological vulnerability. The EIDV was calculated by considering the three dimensions of vulnerability as mutually exclusive events and applying the third axiom of probability. Then we carried out a cluster analysis in order to classify the microregions according to similarities in the EIDV. Odds ratio were also calculated in order to evaluate the odds of microregions having a high susceptibility to diseases and high vulnerability given the drought risk. Results showed that the Pau dos Ferros, Seridó Ocidental, Seridó Oriental, and Umarizal microregions were the most vulnerable, while Natal and Litoral Sul were the least vulnerable. Regarding the dimensions of vulnerability, we observed that almost the entire RN state exhibited high drought risk. Pau dos Ferros and Umarizal had the highest susceptibility and Litoral Nordeste presented the worst adaptive capacity to the effects of drought on health. The EIDV revealed that the population of the RN state needs improvements in living conditions and health, since socioeconomic status is one of the factors that most influence the vulnerability of microregions, which in turn is aggravated by drought risk.
The indoor human thermal comfort (HTC) was investigated in residences located in the Pelotas City, southern Brazil, by the effective temperature index (ETI). In this study, temperature and relative humidity were measured inside 429 houses, located in different regions of Pelotas city, from January 11 to August 27, 2019. Samples were obtained using HOBO data loggers, indoor sensors, installed in different regions of the municipality, in the context of a cohort study of children between 2 and 4 years old and their respective mothers, led by Epidemiological Research Center of the Federal University of Pelotas (UFPEL). In general, all regions had average hourly values of effective temperature index above the comfort zone in summer and below the comfort zone in the winter. In terms of spatial variability, the indoor HTC was dependent on environmental factors such as lake breeze and indoor behavior factors, such as the use of air conditioning system in the downtown buildings.
With the rising trends in elderly populations around the world, there is a growing interest in understanding how climate variability is related to the health of this population group. Therefore, we analyzed the associations between mortality in the elderly due to cardiovascular (CVD) and respiratory diseases (RD) and meteorological variables, for three cities in the State of Sao Paulo, Brazil: Campos do Jordao, Ribeirao Preto, and Santos, all in different subtropical regions, from 1996 to 2017. The main objective was to verify how these distinct subtropical climates impact elderly mortality differently. We applied the autoregressive model integrated with moving average (ARIMA) and the principal component analysis (PCA), in order to evaluate statistical associations. Results showed CVD as a major cause of mortality, particularly in the cold period, when a high mortality rate is also observed due to RD. The mortality rate was higher in Campos do Jordao and lower in Santos. In Campos do Jordao, results indicate an increased probability of mortality from CVD and RD due to lower temperatures. In Ribeirao Preto, the lower relative humidity may be related to the increase in CVD and RD deaths. This study emphasizes that, even among subtropical climates, there are significant differences on how climate impacts human health, which can assist decision-makers in the implementation of mitigating and adaptive measures.
Health determinants might play an important role in shaping the impacts related to long-term disasters such as droughts. Understanding their distribution in populated dry regions may help to map vulnerabilities and set coping strategies for current and future threats to human health. The aim of the study was to identify the most vulnerable municipalities of the Brazilian semiarid region when it comes to the relationship between drought, health, and their determinants using a multidimensional index. From a place-based framework, epidemiological, socio-economic, rural, and health infrastructure data were obtained for 1135 municipalities in the Brazilian semiarid region. An exploratory factor analysis was used to reduce 32 variables to four independent factors and compute a Health Vulnerability Index. The health vulnerability was modulated by social determinants, rural characteristics, and access to water in this semiarid region. There was a clear distinction between municipalities with the highest human welfare and economic development and those municipalities with the worst living conditions and health status. Spatial patterns showed a cluster of the most vulnerable municipalities in the western, eastern, and northeastern portions of the semiarid region. The spatial visualization of the associated vulnerabilities supports decision making on health promotion policies that should focus on reducing social inequality. In addition, policymakers are presented with a simple tool to identify populations or areas with the worst socioeconomic and health conditions, which can facilitate the targeting of actions and resources on a more equitable basis. Further, the results contribute to the understanding of social determinants that may be related to medium- and long-term health outcomes in the region.
BACKGROUND: Zika virus (ZIKV) emerged in the Pacific Ocean and subsequently caused a dramatic Pan-American epidemic after its first appearance in the Northeast region of Brazil in 2015. The virus is transmitted by Aedes mosquitoes. We evaluated the role of temperature and infectious doses of ZIKV in vector competence of Brazilian populations of Ae. aegypti and Ae. albopictus. METHODOLOGY/PRINCIPAL FINDINGS: Two Ae. aegypti (Rio de Janeiro and Natal) and two Ae. albopictus (Rio de Janeiro and Manaus) populations were orally challenged with five viral doses (102 to 106 PFU / ml) of a ZIKV strain (Asian genotype) isolated in Northeastern Brazil, and incubated for 14 and 21 days in temperatures mimicking the spring-summer (28°C) and winter-autumn (22°C) mean values in Brazil. Detection of viral particles in the body, head and saliva samples was done by plaque assays in cell culture for determining the infection, dissemination and transmission rates, respectively. Compared with 28°C, at 22°C, transmission rates were significantly lower for both Ae. aegypti populations, and Ae. albopictus were not able to transmit the virus. Ae. albopictus showed low transmission rates even when challenged with the highest viral dose, while both Ae. aegypti populations presented higher of infection, dissemination and transmission rates than Ae. albopictus. Ae. aegypti showed higher transmission efficiency when taking virus doses of 105 and 106 PFU/mL following incubation at 28°C; both Ae. aegypti and Ae. albopictus were unable to transmit ZIKV with virus doses of 102 and 103 PFU/mL, regardless the incubation temperature. CONCLUSIONS/SIGNIFICANCE: The ingested viral dose and incubation temperature were significant predictors of the proportion of mosquito’s biting becoming infectious. Ae. aegypti and Ae. albopictus have the ability to transmit ZIKV when incubated at 28°C. However Brazilian populations of Ae. aegypti exhibit a much higher transmission potential for ZIKV than Ae. albopictus regardless the combination of infection dose and incubation temperature.
As global temperatures continue to rise it is imperative to understand the adverse effects this will pose to workers laboring outdoors. The purpose of this study was to investigate the relationship between increases in wet bulb globe temperature (WBGT) and risk of occupational injury or dehydration among agricultural workers. We used data collected by an agribusiness in Southwest Guatemala over the course of four harvest seasons and Poisson generalized linear modelling for this analysis. Our analyses suggest a 3% increase in recorded injury risk with each degree increase in daily average WBGT above 30 °C (95% CI: -6%, 14%). Additionally, these data suggest that the relationship between WBGT and injury risk is non-linear with an additional 4% acceleration in risk for every degree increase in WBGT above 30 °C (95% CI: 0%, 8%). No relationship was found between daily average WBGT and risk of dehydration. Our results indicate that agricultural workers are at an increased risk of occupational injury in humid and hot environments and that businesses need to plan and adapt to increasing global temperatures by implementing and evaluating effective occupational safety and health programs to protect the health, safety, and well-being of their workers.
It is well known that sudden variations of air temperature have the potential to cause severe impacts on human health. Therefore, it becomes necessary to provide information capable of quantifying the severity of the problem, considering that the continuous increase of temperature due to global warming and urban development will cause more intense effects in heavily populated areas. Due to its geographical location and local characteristics, Ecuador, a country located on the western coast of South America, is characterized by a high vulnerability to climatic extremes. The present research develops an evaluation of urban climate change effects through the analysis of extreme temperature indices using four meteorological stations situated in the city of Guayaquil (southwest Ecuador). Since the available data are not adequate for extreme temperature indices criteria, it was necessary to employ an infilling method for times series in an innovative way that can be applicable at the small scale. Thus, a cross-correlation-enhanced inverse distance weighting (CC-IDW) method was proposed. The method entails a spatial interpolation based on data of urban stations situated outside of Guayaquil by taking into account cross-correlation among times series at precise lags that leads to an improvement in the way of estimating the missing values. Subsequently, a homogeneity test, data quality control and the calculation of extreme temperature indices chosen from those proposed by the World Meteorological Organization (WMO) were implemented. The results show that there is a general tendency of warming with quite homogenous temperatures for all considered stations. However, it should be recognized that the climate pattern of this region is strongly modulated by the El Nino Southern Oscillation (ENSO) cycle. Only for two extreme indices: the highest maximum temperature (TXx) and the warm days (TX90p), are the resulting trend co-efficients statistically significant. The study suggests a deteriorated climatic condition due to heat stress that warrants further study using the available database for the city of Guayaquil.
Malaria is a vector-borne disease of significant public health concern. Despite widespread success of many elimination initiatives, elimination efforts in some regions of the world have stalled. Barriers to malaria elimination include climate and land use changes, such as warming temperatures and urbanization, which can alter mosquito habitats. Socioeconomic factors, such as political instability and regional migration, also threaten elimination goals. This is particularly relevant in areas where local elimination has been achieved and consequently surveillance and control efforts are dwindling and are no longer a priority. Understanding how environmental change, impacts malaria elimination has important practical implications for vector control and disease surveillance strategies. It is important to consider climate change when monitoring the threat of malaria resurgence due to socioeconomic influences. However, there is limited assessment of how the combination of climate variation, interventions and socioeconomic pressures influence long-term trends in malaria transmission and elimination efforts. In this study, we used Bayesian hierarchical mixed models and malaria case data for a 29-year period to disentangle the impacts of climate variation and malaria control efforts on malaria risk in the Ecuadorian province of El Oro, which achieved local elimination in 2011. We found shifting patterns of malaria between rural and urban areas, with a relative increase ofPlasmodium vivaxin urbanized areas. Minimum temperature was an important driver of malaria seasonality and the association between warmer minimum temperatures and malaria incidence was greater forPlasmodium falciparumcompared toP. vivaxmalaria. There was considerable heterogeneity in the impact of three chemical vector control measures on bothP. falciparumandP. vivaxmalaria. We found statistically significant associations between two of the three measures [indoor residual spraying (IRS) and space spraying] and a reduction in malaria incidence, which varied between malaria type. We also found environmental suitability for malaria transmission is increasing in El Oro, which could limit future elimination efforts if malaria is allowed to re-establish. Our findings have important implications for understanding environmental obstacles to malaria elimination and highlights the importance of designing and sustaining elimination efforts in areas that remain vulnerable to resurgence.
Fuel poverty has increasingly been associated with thermal discomfort, health related issues and winter deaths in the Global North because it can force families to choose between food and a warmer environment. Juxtaposing the concept of fuel poverty in rural tropical areas of the Global South, it is likely that a similar pattern between fuel poverty and heat related illnesses can be found. A recent study shows that between 1.8 and 4.1 billion people, especially in India, Southeast Asia and Sub-Saharan Africa will need indoor cooling to avoid heat related health issues. This paper aims to address a blind spot in the literature on the links between fuel poverty, thermal comfort and cooling strategies in the Brazilian Amazon. This study draws from current definitions and indicators of fuel poverty in the Global North and juxtaposes it in the context of tropical areas to understand how fuel poverty affects human health, livelihood strategies and social justice in rural communities that live in hot climates. To do so, this paper uses qualitative methods and a conceptual framework to guide the analysis. I call the intersection between vernacular architecture and sustainable cooling practices ‘energy relief.
Limited research exists on the influence of climatic conditions on the risk of hospital admission for asthma in Minas Gerais, Brazil. The objectives of this article are: a) to evaluate the influence of climatic conditions on hospital admissions for asthma and lower respiratory tract infections (LRTIs) among children and adolescents living in Belo Horizonte during the period 2002 to 2012 and identify epidemic peaks of admissions for asthma; b) to compare local seasonal patterns of admissions for asthma and LRTIs. Using hospital admission data stratified by aged group, regression analysis was performed to determine the relationship between the variables. Epidemic peaks were identified using an ARIMA model. There was an increase in admissions for asthma with an increase in relative humidity after rainy periods; admissions for bronchiolitis were associated with low levels of maximum temperature and rainfall. Rainy periods can lead to an increase in indoor and outdoor humidity, facilitating fungal proliferation, while cold periods can lead to an increase in the spread of viruses.
In recent decades, the nutritional transition has been encroaching on remote rural areas of developing countries where feeding patterns are shifting from unprocessed foods to industrialized processed goods. Such changes in the Amazon region have been detected, for instance, by comparing the natural carbon (C-13:C-12) and nitrogen (N-15:N-14) isotopic ratios of people living in riverine communities with urban dwellers their putative diet. In this study, we considered how landscape variables impacted food consumption by comparing fingernail isotopic ratios of individuals in the rural settlement of Costa do Caldeirao located in the floodplain (varzea) of the Solimoes River, and in the rural settlement of Paquequer located in a non-flooded area (terra-firme) near the Madeira River banks. A total of 70 fingernails were sampled for carbon and nitrogen isotopic analysis during the low water period and again during the high water period from the same residents of the varzea and terra-firme. The consumption of C-4-like resources (e.g., frozen chicken and canned meat) increased in both rural settlements during the high water period when C-3-like resources (fish, cassava, rice, beans) are less available due to the flooding of lowland areas, but this difference was more pronounced in the terra-firme. The higher consumption of C-4-like resources in the varzea compared to the terra-firme shows how seasonal flooding is a key factor influencing food security and health, due to stark variations in river water levels. While fish and farinha are still important staple foods, differences within rural settlements suggest that, besides seasonal variation and changes in water levels, other factors such as age, origin, and income may be crucial to understanding individual dietary behavior change in line with the nutritional transition model.
Recent literature provides evidence that income shocks early in life can have long-run consequences on adult welfare. Rural Brazil frequently suffers from rainfall variations that negatively impact vulnerable households, who often lack the means for coping with these events. This paper evaluates how early-life rainfall shocks influence adult health and socioeconomic outcomes in Brazil. We find evidence that several critical periods can produce long-run consequences. Using rainfall deviations, our two most robust results are that greater rainfall in utero negatively impacts adult incomes (finding that a one standard deviation increase in rainfall causes adult incomes to fall by 7-10 percent) and that greater rainfall in the second and third years of life improve adult health (increasing body mass index by 0.16). However, our results depend crucially on our choices regarding two features. First, our results differ across two common measures of critical periods, which are used to define shocks relative to the timing of one’s birth. Second, the way rainfall variation is measured also matters, with use of an extreme weather indicator suggesting heterogeneous effects by gender, with extreme weather negatively impacting women’s health (both before and after birth) but positively affecting several men’s outcomes (both before and after birth). We find some evidence that mortality selection may drive some of these results. This paper provides further evidence that early-life shocks (from in utero through the third year of life) can cause long-run consequences, but also suggests that more attention should be paid to the specific measurement and timing of rainfall shocks.
The northeast (NE) region of Brazil commonly goes through drought periods, which favor cyanobacterial blooms, capable of producing neurotoxins with implications for human and animal health. The most severe dry spell in the history of Brazil occurred between 2012 and 2016. Coincidently, the highest incidence of microcephaly associated with the Zika virus (ZIKV) outbreak took place in the NE region of Brazil during the same years. In this work, we tested the hypothesis that saxitoxin (STX), a neurotoxin produced in South America by the freshwater cyanobacteria Raphidiopsis raciborskii, could have contributed to the most severe Congenital Zika Syndrome (CZS) profile described worldwide. Quality surveillance showed higher cyanobacteria amounts and STX occurrence in human drinking water supplies of NE compared to other regions of Brazil. Experimentally, we described that STX doubled the quantity of ZIKV-induced neural cell death in progenitor areas of human brain organoids, while the chronic ingestion of water contaminated with STX before and during gestation caused brain abnormalities in offspring of ZIKV-infected immunocompetent C57BL/6J mice. Our data indicate that saxitoxin-producing cyanobacteria is overspread in water reservoirs of the NE and might have acted as a co-insult to ZIKV infection in Brazil. These results raise a public health concern regarding the consequences of arbovirus outbreaks happening in areas with droughts and/or frequent freshwater cyanobacterial blooms.
During the 2012-2016 drought in La Guajira, Colombia, child mortality rates rose to 23.4 out of 1000. Most of these children belonged to the Wayuu indigenous community, the largest and one of the most vulnerable in Colombia. At the municipal level, this study found a significant positive correlation between the average child mortality rate and households with a monthly income of less than USD 100, the number of people without access to health insurance, being part of the indigenous population, being illiterate, lacking sewage systems, living in rural areas, and large households with members younger than 5 years old and older than 65 years old. No correlation was found with households without access to a water source. The stepwise regression analysis showed that households with a monthly income of less than USD 100, no members older than 65 years old, but several children younger than 5 years old, account for 90.4% of the child mortality rate. This study concludes that, if inhabitants had had better incomes or assets, as well as an adequate infrastructure, they could have faced the drought without the observed increase in child mortality.
Air temperature, both cold and hot, has impacts on mortality and morbidities, which are exacerbated by poor health service and protection responses, particularly in under-developed countries. This study was designed to analyze the effects of air temperature on the risk of deaths for all and specific causes in two regions of Brazil (Florianopolis and Recife), between 2005 and 2014. The association between temperature and mortality was performed through the fitting of a quasi-Poisson non-linear lag distributed model. The association between air temperature and mortality was identified for both regions. The results showed that temperature exerted influence on both general mortality indicators and specific causes, with hot and cold temperatures bringing different impacts to the studied regions. Cerebrovascular and cardiovascular deaths were more sensitive to cold temperatures for Florianopolis and Recife, respectively. Based on the application of the very-well documented state-of-the-art methodology, it was possible to conclude that there was evidence that extreme air temperature influenced general and specific deaths. These results highlighted the importance of consolidating evidence and research in tropical countries such as Brazil as a way of understanding climate change and its impacts on health indicators.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), universally recognized as COVID-19, is currently is a global issue. Our study uses multivariate regression for determining the relationship between the ambient environment and COVID-19 cases in Lima. We also forecast the pattern trajectory of COVID-19 cases with variables using an Auto-Regressive Integrated Moving Average Model (ARIMA). There is a significant association between ambient temperature and PM10 and COVID-19 cases, while no significant correlation has been seen for PM2.5. All variables in the multivariate regression model have R-2 = 0.788, which describes a significant exposure to COVID-19 cases in Lima. ARIMA (1,1,1), during observation time of PM2.5, PM10, and average temperature, is found to be suitable for forecasting COVID-19 cases in Lima. This result indicates that the expected high particle concentration and low ambient temperature in the coming season will further facilitate the transmission of the coronavirus if there is no other policy intervention. A suggested sustainable policy related to ambient environment and the lessons learned from different countries to prevent future outbreaks are also discussed in this study.
Urban heat islands (UHIs) can present significant risks to human health. Santiago, Chile has around 7 million residents, concentrated in an average density of 480 people/km(2). During the last few summer seasons, the highest extreme maximum temperatures in over 100 years have been recorded. Given the projections in temperature increase for this metropolitan region over the next 50 years, the Santiago UHI could have an important impact on the health and stress of the general population. We studied the presence and spatial variability of UHIs in Santiago during the summer seasons from 2005 to 2017 using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery and data from nine meteorological stations. Simple regression models, geographic weighted regression (GWR) models and geostatistical interpolations were used to find nocturnal thermal differences in UHIs of up to 9 degrees C, as well as increases in the magnitude and extension of the daytime heat island from summer 2014 to 2017. Understanding the behavior of the UHI of Santiago, Chile, is important for urban planners and local decision makers. Additionally, understanding the spatial pattern of the UHI could improve knowledge about how urban areas experience and could mitigate climate change.
We have evaluated the spread of SARS-CoV-2 through Latin America and the Caribbean (LAC) region by means of a correlation between climate and air pollution indicators, namely, average temperature, minimum temperature, maximum temperature, rainfall, average relative humidity, wind speed, and air pollution indicators PM(10), PM(2.5), and NO(2) with the COVID-19 daily new cases and deaths. The study focuses in the following LAC cities: Mexico City (Mexico), Santo Domingo (Dominican Republic), San Juan (Puerto Rico), Bogotá (Colombia), Guayaquil (Ecuador), Manaus (Brazil), Lima (Perú), Santiago (Chile), São Paulo (Brazil) and Buenos Aires (Argentina). The results show that average temperature, minimum temperature, and air quality were significantly associated with the spread of COVID-19 in LAC. Additionally, humidity, wind speed and rainfall showed a significant relationship with daily cases, total cases and mortality for various cities. Income inequality and poverty levels were also considered as a variable for qualitative analysis. Our findings suggest that and income inequality and poverty levels in the cities analyzed were related to the spread of COVID-19 positive and negative, respectively. These results might help decision-makers to design future strategies to tackle the spread of COVID-19 in LAC and around the world.
BACKGROUND: Exposure to temperature variability has been associated with increased risk of mortality and morbidity. We aimed to evaluate whether the association between short-term temperature variability and hospitalisation was affected by local socioeconomic level in Brazil. METHODS: In this time-series study, we collected city-level socioeconomic data, and daily hospitalisation and weather data from 1814 Brazilian cities between Jan 1, 2000, and Dec 31, 2015. All-cause and cause-specific hospitalisation data was from the Hospital Information System of the Unified Health System in Brazil. City-specific daily minimum and maximum temperatures came from a 0·25°?×?0·25° Brazilian meteorological dataset. We represented city-specific socioeconomic level using literacy rate, urbanisation rate, average monthly household income per capita (using the 2000 and 2010 Brazilian census), and GDP per capita (using statistics from the Brazilian Institute of Geography and Statistics for 2000-15), and cities were categorised according to the 2015 World Bank standard. We used quasi-Poisson regression to do time-series analyses and obtain city-specific associations between temperature variability and hospitalisation. We pooled city-specific estimates according to different socioeconomic quartiles or levels using random-effect meta-analyses. Meta-regressions adjusting for demographic and climatic characteristics were used to evaluate the modification effect of city-level socioeconomic indicators on the association between temperature variability and hospitalisation. FINDINGS: We included a total of 147?959?243 hospitalisations (59·0% female) during the study period. Overall, we estimated that the hospitalisation risk due to every 1°C increase in the temperature variability in the current and previous day (TV(0-1)) increased by 0·52% (95% CI 0·50-0·55). For lower-middle-income cities, this risk was 0·63% (95% CI 0·58-0·69), for upper-middle-income cities it was 0·50% (0·47-0·53), and for high-income cities it was 0·39% (0·33-0·46). The socioeconomic inequality in vulnerability to TV(0-1) was especially evident for people aged 0-19 years (effect estimate 1·21% [1·11-1·31] for lower-middle income vs 0·52% [0·41-0·63] for high income) and people aged 60 years or older (0·60% [0·50-0·70] vs 0·43% [0·31-0·56]), and for hospitalisation due to infectious diseases (1·62% [1·46-1·78] vs 0·56% [0·30-0·82]), respiratory diseases (1·32% [1·20-1·44] vs 0·55% [0·37-0·74]), and endocrine diseases (1·21% [0·99-1·43] vs 0·32% [0·02-0·62]). INTERPRETATION: People living in less developed cities in Brazil were more vulnerable to hospitalisation related to temperature variability. This disparity could exacerbate existing health and socioeconomic inequalities in Brazil, and it suggests that more attention should be paid to less developed areas to mitigate the adverse health effects of short-term temperature fluctuations. FUNDING: None.
INTRODUCTION: Leptospirosis is an endemic disease in Brazil that can become an epidemic during the rainy season resulting from floods in areas susceptible to natural disasters. These areas are widespread in Santa Catarina, particularly in the coastal region. Therefore, the objective of this study was to identify environmental, climatic, and demographic factors associated with the incidence of leptospirosis in the municipalities of Santa Catarina from 2001 to 2015, taking into account possible spatial dependence. METHODS: This was an ecological study aggregated by municipality. To evaluate the association between the incidence of leptospirosis and the factors under study (temperature, altitude, occurrence of natural disasters, etc.) while taking into account spatial dependence, linear regression models and models with global spatial error were used. RESULTS: Lower altitudes, higher temperatures, and areas of natural disaster risk in the municipality contributed the most to explaining the variability in the incidence rate. After taking spatial dependence into account, only the minimum altitude variable remained significant. The regions of lower altitude, where the highest rates of leptospirosis were recorded, corresponded to the eastern portion of the state near the coastal region, where floods, urban floods, and overflows are common occurrences. No associations were found concerning demographic factors. CONCLUSIONS: The incidence of leptospirosis in Santa Catarina was associated with environmental factors, particularly low altitude, even when considering the spatial dependence structure present in the data. The spatial error model allowed for adequate modeling of spatial autocorrelation.
BACKGROUND: Heat exposure, which will increase with global warming, has been linked to increased risk of a range of types of cause-specific hospitalizations. However, little is known about socioeconomic disparities in vulnerability to heat. We aimed to evaluate whether there were socioeconomic disparities in vulnerability to heat-related all-cause and cause-specific hospitalization among Brazilian cities. METHODS AND FINDINGS: We collected daily hospitalization and weather data in the hot season (city-specific 4 adjacent hottest months each year) during 2000-2015 from 1,814 Brazilian cities covering 78.4% of the Brazilian population. A time-stratified case-crossover design modeled by quasi-Poisson regression and a distributed lag model was used to estimate city-specific heat-hospitalization association. Then meta-analysis was used to synthesize city-specific estimates according to different socioeconomic quartiles or levels. We included 49 million hospitalizations (58.5% female; median [interquartile range] age: 33.3 [19.8-55.7] years). For cities of lower middle income (LMI), upper middle income (UMI), and high income (HI) according to the World Bank’s classification, every 5°C increase in daily mean temperature during the hot season was associated with a 5.1% (95% CI 4.4%-5.7%, P < 0.001), 3.7% (3.3%-4.0%, P < 0.001), and 2.6% (1.7%-3.4%, P < 0.001) increase in all-cause hospitalization, respectively. The inter-city socioeconomic disparities in the association were strongest for children and adolescents (0-19 years) (increased all-cause hospitalization risk with every 5°C increase [95% CI]: 9.9% [8.7%-11.1%], P < 0.001, in LMI cities versus 5.2% [4.1%-6.3%], P < 0.001, in HI cities). The disparities were particularly evident for hospitalization due to certain diseases, including ischemic heart disease (increase in cause-specific hospitalization risk with every 5°C increase [95% CI]: 5.6% [-0.2% to 11.8%], P = 0.060, in LMI cities versus 0.5% [-2.1% to 3.1%], P = 0.717, in HI cities), asthma (3.7% [0.3%-7.1%], P = 0.031, versus -6.4% [-12.1% to -0.3%], P = 0.041), pneumonia (8.0% [5.6%-10.4%], P < 0.001, versus 3.8% [1.1%-6.5%], P = 0.005), renal diseases (9.6% [6.2%-13.1%], P < 0.001, versus 4.9% [1.8%-8.0%], P = 0.002), mental health conditions (17.2% [8.4%-26.8%], P < 0.001, versus 5.5% [-1.4% to 13.0%], P = 0.121), and neoplasms (3.1% [0.7%-5.5%], P = 0.011, versus -0.1% [-2.1% to 2.0%], P = 0.939). The disparities were similar when stratifying the cities by other socioeconomic indicators (urbanization rate, literacy rate, and household income). The main limitations were lack of data on personal exposure to temperature, and that our city-level analysis did not assess intra-city or individual-level socioeconomic disparities and could not exclude confounding effects of some unmeasured variables. CONCLUSIONS: Less developed cities displayed stronger associations between heat exposure and all-cause hospitalizations and certain types of cause-specific hospitalizations in Brazil. This may exacerbate the existing geographical health and socioeconomic inequalities under a changing climate.
Optimise control strategies of infectious diseases, identify factors that favour the circulation of pathogens, and propose risk maps are crucial challenges for global health. Ecological niche modelling, once relying on an adequate framework and environmental descriptors can be a helpful tool for such purposes. Despite the existence of a vaccine, yellow fever (YF) is still a public health issue. Brazil faced massive sylvatic YF outbreaks from the end of 2016 up to mid-2018, but cases in human and non-human primates have been recorded until the beginning of 2020. Here we used both human and monkey confirmed YF cases from two epidemic periods (2016/2017 and 2017/2018) to describe the spatial distribution of the cases and explore how biotic and abiotic factors drive their occurrence. The distribution of YF cases largely overlaps for humans and monkeys, and a contraction of the spatial extent associated with a southward displacement is observed during the second period of the epidemics. More contributive variables to the spatiotemporal heterogeneity of cases were related to biotic factors (mammal richness), abiotic factors (temperature and precipitation), and some human-related variables (population density, human footprint, and human vaccination coverage). Both projections of the most favourable conditions showed similar trends with a contraction of the more at-risk areas. Once extrapolated at a large scale, the Amazon basin remains at lower risk, although surrounding forest regions and notably the North-West region, would face a higher risk. Spatial projections of infectious diseases often relied on climatic variables only; here for both models, we instead highlighted the importance of considering local biotic conditions, hosts vulnerability, social and epidemiological factors to run the spatial risk analysis correctly: all YF cases occurring later on, in 2019 and 2020, were observed in the predicted at-risk areas.
Climate change affects individual life-history characteristics and species interactions, including predator-prey interactions. While effects of warming on Aedes aegypti adults are well known, clarity the interactive effects of climate change (temperature and CO2 concentration) and predation risk on the larval stage remains unexplored. In this study, we performed a microcosm experiment simulating temperature and CO2 changes in Manaus, Amazonas, Brazil, for the year 2100. Simulated climate change scenarios (SCCS) were in accordance with the Fourth Assessment Report of Intergovernmental Panel on Climate Change (IPCC). Used SCCS were: Control (real-time current conditions in Manaus: average temperature is ~25.76°C ± 0.71°C and ~477.26 ± 9.38 parts per million by volume (ppmv) CO2); Light: increase of ~1,7°C and ~218 ppmv CO2; Intermediate: increase of ~2.4°C and ~446 ppmv CO2; and Extreme: increase of ~4.5°C and ~861 ppmv CO2, all increases were relative to a Control SCCS. Light, Intermediate and Extreme SCCS reproduced, respectively, the B1, A1B, and A2 climatic scenarios predicted by IPCC (2007). We analyzed Aedes aegypti larval survivorship and adult emergence pattern with a factorial design combining predation risk (control and predator presence-Toxorhynchites haemorrhoidalis larvae) and SCCS. Neither SCCS nor predation risk affected Aedes aegypti larval survivorship, but adult emergence pattern was affected by SCCS. Accordingly, our results did not indicate interactive effects of SCCS and predation risk on larval survivorship and emergence pattern of Aedes aegypti reared in SCCS in western Amazonia. Aedes aegypti is resistant to SCCS conditions tested, mainly due to high larval survivorship, even under Extreme SCCS, and warmer scenarios increase adult Aedes aegypti emergence. Considering that Aedes aegypti is a health problem in western Amazonia, an implication of our findings is that the use of predation cues as biocontrol strategies will not provide a viable means of controlling the accelerated adult emergence expected under the IPCC climatic scenarios.
INTRODUCTION: Malaria is an infectious disease of high transmission in the Amazon region, but its dynamics and spatial distribution may vary depending on the interaction of environmental, socio-cultural, economic, political and health services factors. OBJECTIVE: To verify the existence of malaria case patterns in consonance with the fluviometric regimes in Amazon basin. METHOD: Methods of descriptive and inferential statistics were used in malaria and water level data for 35 municipalities in the Amazonas State, in the period from 2003 to 2014. RESULTS: The existence of a tendency to modulate the seasonality of malaria cases due to distinct periods of rivers flooding has been demonstrated. Differences were observed in the annual hydrological variability accompanied by different patterns of malaria cases, showing a trend of remodeling of the epidemiological profile as a function of the flood pulse. CONCLUSION: The study suggests the implementation of regional and local strategies considering the hydrological regimes of the Amazon basin, enabling municipal actions to attenuate the malaria in the Amazonas State.
BACKGROUND: Southeast Brazil has recently experienced a Yellow Fever virus (YFV) outbreak where the mosquito Haemagogus leucocelaenus was a primary vector. Climatic factors influence the abundance of mosquito vectors and arbovirus transmission. OBJECTIVES: We aimed at describing the population dynamics of Hg. leucocelaenus in a county touched by the recent YFV outbreak. METHODS: Fortnightly egg collections with ovitraps were performed from November 2012 to February 2017 in a forest in Nova Iguaçu, Rio de Janeiro, Brazil. The effects of mean temperature and rainfall on the Hg. leucocelaenus population dynamics were explored. FINDINGS: Hg. leucocelaenus eggs were continuously collected throughout the study, with a peak in the warmer months (December-March). The climatic variables had a time-lagged effect and four weeks before sampling was the best predictor for the positivity of ovitraps and total number of eggs collected. The probability of finding > 50% positive ovitraps increased when the mean temperature was above 24ºC. The number of Hg. leucocelaenus eggs expressively increase when the mean temperature and accumulated precipitation surpassed 27ºC and 100 mm, respectively, although the effect of rainfall was less pronounced. MAIN CONCLUSIONS: Monitoring population dynamics of Hg. leucocelaenus and climatic factors in YFV risk areas, especially mean temperature, may assist in developing climate-based surveillance procedures to timely strengthening prophylaxis and control.
BACKGROUND: Extreme ambient temperatures and air quality have been directly associated with various human diseases from several studies around the world. However, few analyses involving the association of these environmental circumstances with mental and behavioral disorders (MBD) have been carried out, especially in developing countries such as Brazil. METHODS: A time series study was carried out to explore the associations between daily air pollutants (SO(2), NO(2), O(3), and PM(10)) concentrations and meteorological variables (temperature and relative humidity) on hospital admissions for mental and behavioral disorders for Curitiba, Brazil. Daily hospital admissions from 2010 to 2016 were analyzed by a semi-parametric generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM). RESULTS: Significant associations between environmental conditions (10??g/m(3) increase in air pollutants and temperature °C) and hospitalizations by MBD were found. Air temperature was the environmental variable with the highest relative risk (RR) at 0-day lag for all ages and sexes analyzed, with RR values of 1.0182 (95% CI: 1.0009-1.0357) for men, and 1.0407 (95% CI: 1.0230-1.0587) for women. Ozone exposure was a risk for all women groups, being higher for the young group, with a RR of 1.0319 (95% CI: 1.0165-1.0483). Elderly from both sexes were more susceptible to temperature variability, with a RR of 1.0651 (95% CI: 1.0213-1.1117) for women, and 1.0215 (95% CI: 1.0195-1.0716) for men. CONCLUSIONS: This study suggests that temperatures above and below the thermal comfort threshold, in addition to high concentrations of air pollutants, present significant risks on hospitalizations by MBD; besides, there are physiological and age differences resulting from the effect of this exposure.
OBJECTIVE: The objective of this study was to identify frequency, severity, and risk factors associated with bronchiolitis in Puerto Rican children. METHODS: A cross-sectional was study performed at 4 emergency departments of Puerto Rico’s metropolitan area, between June 2014 and May 2015. We included children younger than 24 months, with a clinical diagnosis of bronchiolitis, who were born and living in Puerto Rico at the time of recruitment. A physician-administered questionnaire inquiring about the patient’s medical, family, and social history and a bronchiolitis severity assessment were performed. Daily weather conditions were monitored, and aeroallergens were collected with an air sample and precision weather station within the metropolitan area to evaluate environmental factors. RESULTS: We included 600 patients for 12 months. More than 50% of the recruited patients had a previous episode of bronchiolitis, of which 40% had been hospitalized. Older age (odds ratio [OR], 18.3; 95% confidence interval [CI], 9.2-36.5), male sex (OR, 1.6; 95% CI, 1.1-2.4), history of asthma (OR, 8.9; 95% CI, 3.6-22), allergic rhinitis (OR, 3.6; 95% CI, 1.8-7.4), and smoke exposure by a caretaker (OR, 2.3; 95% CI, 1.2-4.4) were predictors of bronchiolitis episodes. Bronchiolitis episodes were associated with higher severity score (P = 0.040), increased number of atopic factors (P < 0.001), and higher number of hospitalizations (P < 0.001). CONCLUSIONS: This study identifies Puerto Rican children who may present a severe clinical course of disease without traditional risk factors. Atopy-related factors are associated with frequency and severity of bronchiolitis. Puerto Rican children present risk factors related to atopy earlier in life, some of which may be modified to prevent the subsequent development of asthma.
This study aimed to evaluate the relationship between weather factors (temperature, humidity, solar radiation, wind speed, and rainfall) and COVID-19 infection in the State of Rio de Janeiro, Brazil. Solar radiation showed a strong (-0.609, p < 0.01) negative correlation with the incidence of novel coronavirus (SARS-CoV-2). Temperature (maximum and average) and wind speed showed negative correlation (p < 0.01). Therefore, in this studied tropical state, high solar radiation can be indicated as the main climatic factor that suppress the spread of COVID-19. High temperatures, and wind speed also are potential factors. Therefore, the findings of this study show the ability to improve the organizational system of strategies to combat the pandemic in the State of Rio de Janeiro, Brazil, and other tropical countries around the word.
Mosquito-borne diseases affect millions of individuals worldwide; the area of endemic transmission has been increasing due to several factors linked to globalization, urban sprawl, and climate change. The Aedes aegypti mosquito plays a central role in the dissemination of dengue, Zika, chikungunya, and urban yellow fever. Current preventive measures include mosquito control programs; however, identifying high-risk areas for mosquito infestation over a large geographic region based only on field surveys is labor-intensive and time-consuming. Thus, the objective of this study was to assess the potential of remote satellite images (WorldView) for determining land features associated with Ae. aegypti adult infestations in São José do Rio Preto/SP, Brazil. We used data from 60 adult mosquito traps distributed along four summers; the remote sensing images were classified by land cover types using a supervised classification method. We modeled the number of Ae. aegypti using a Poisson probability distribution with a geostatistical approach. The models were constructed in a Bayesian context using the Integrated nested Laplace Approximations and Stochastic Partial Differential Equation method. We showed that an infestation of Ae. aegypti adult mosquitoes was positively associated with the presence of asbestos roofing and roof slabs. This may be related to several other factors, such as socioeconomic or environmental factors. The usage of asbestos roofing may be more prevalent in socioeconomically poor areas, while roof slabs may retain rainwater and contribute to the generation of temporary mosquito breeding sites. Although preliminary, our results demonstrate the utility of satellite remote sensing in identifying landscape differences in urban environments using a geostatistical approach, and indicated directions for future research. Further analyses including other variables, such as land surface temperature, may reveal more complex relationships between urban mosquito micro-habitats and land cover features.
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.
Identifying Aedes aegypti breeding hotspots in urban areas is crucial for the design of effective vector control strategies. Remote sensing techniques offer valuable tools for mapping habitat suitability. In this study, we evaluated the association between urban landscape, thermal features, and mosquito infestations. Entomological surveys were conducted between 2016 and 2019 in Vila Toninho, a neighborhood of São José do Rio Preto, São Paulo, Brazil, in which the numbers of adult female Ae. aegypti were recorded monthly and grouped by season for three years. We used data from 2016 to 2018 to build the model and data from summer of 2019 to validate it. WorldView-3 satellite images were used to extract land cover classes, and land surface temperature data were obtained using the Landsat-8 Thermal Infrared Sensor (TIRS). A multilevel negative binomial model was fitted to the data, which showed that the winter season has the greatest influence on decreases in mosquito abundance. Green areas and pavements were negatively associated, and a higher cover of asbestos roofs and exposed soil was positively associated with the presence of adult females. These features are related to socio-economic factors but also provide favorable breeding conditions for mosquitos. The application of remote sensing technologies has significant potential for optimizing vector control strategies, future mosquito suppression, and outbreak prediction.
Over the years, Jamaica has experienced sporadic cases of dengue fever. Even though the island is vulnerable to dengue, there is paucity in the spatio-temporal analysis of the disease using Geographic Information Systems (GIS) and remote sensing tools. Further, access to time series dengue data at the community level is a major challenge on the island. This study therefore applies the Water-Associated Disease Index (WADI) framework to analyze vulnerability to dengue in Jamaica based on past, current and future climate change conditions using three scenarios: (1) WorldClim rainfall and temperature dataset from 1970 to 2000; (2) Climate Hazard Group InfraRed Precipitation with Station data (CHIRPS) rainfall and land surface temperature (LST) as proxy for air temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) for the period 2002 to 2016, and (3) maximum temperature and rainfall under the Representative Concentration Pathway (RCP) 8.5 climate change scenario for 2030 downscaled at 25 km based on the Regional Climate Model, RegCM4.3.5. Although vulnerability to dengue varies spatially and temporally, a higher vulnerability was depicted in urban areas in comparison to rural areas. The results also demonstrate the possibility for expansion in the geographical range of dengue in higher altitudes under climate change conditions based on scenario 3. This study provides an insight into the use of data with different temporal and spatial resolution in the analysis of dengue vulnerability.
Extreme floods pose multiple direct and indirect health risks. These risks include contamination of water, food, and the environment, often causing outbreaks of diarrheal disease. Evidence regarding the effects of flooding on individual diarrhea-causing pathogens is limited, but is urgently needed in order to plan and implement interventions and prioritize resources before climate-related disasters strike. This study applied a causal inference approach to data from a multisite study that deployed broadly inclusive diagnostics for numerous high-burden common enteropathogens. Relative risks (RRs) of infection with each pathogen during a flooding disaster that occurred at one of the sites-Loreto, Peru-were calculated from generalized linear models using a comparative interrupted time series framework with the other sites as a comparison group and adjusting for background seasonality. During the early period of the flood, increased risk of heat-stable enterotoxigenic E. coli (ST-ETEC) was identified (RR = 1.73 [1.10, 2.71]) along with a decreased risk of enteric adenovirus (RR = 0.36 [0.23, 0.58]). During the later period of the flood, sharp increases in the risk of rotavirus (RR = 5.30 [2.70, 10.40]) and sapovirus (RR = 2.47 [1.79, 3.41]) were observed, in addition to increases in transmission of Shigella spp. (RR = 2.86 [1.81, 4.52]) and Campylobacter spp. (RR = 1.41 (1.01, 1.07). Genotype-specific exploratory analysis reveals that the rise in rotavirus transmission during the flood was likely due to the introduction of a locally atypical, non-vaccine (G2P[4]) strain of the virus. Policy-makers should target interventions towards these pathogens-including vaccines as they become available-in settings where vulnerability to flooding is high as part of disaster preparedness strategies, while investments in radical, transformative, community-wide, and locally-tailored water and sanitation interventions are also needed.
The Phyllosoma complex is a Triatominae (Hemiptera: Reduviidae) group of medical importance involved in Trypanosoma cruzi (Kinetoplastida: Trypanosomatidae) transmission. Most of the members of this group are endemic and sympatric species with distribution in Mexico and the southern U.S.A. We employed MaxEnt to construct ecological niche models of nine species of Triatominae to test three hypothesis: (a) whether species with a broad climatic niche breadth occupy a broader geographical range than species with a narrow climatic breadth, (b) whether species with broad distribution present high degree of climatic fragmentation/isolation, which was tested through landscape metrics; and (c) whether the species share the same climatic niche space (niche conservatism) considered through an equivalence test implemented in ENMtools. Overall, our results suggest that the geographical distribution of this complex is influenced mainly by temperature seasonality where all suitable areas are places of current and potential transmission of T. cruzi. Niche breadth in the Phyllosoma complex is associated with the geographical distribution range, and the geographical range affects the climatic connectivity. We found no strong evidence of niche climatic divergence in members of this complex. We discuss the epidemiological implications of these results.
Rural, natural resource dependent communities are especially vulnerable to climate change, and their input is critical in developing solutions, but the study of risk perception within and among vulnerable communities remains underdeveloped. Our multi-disciplinary research team used a mixed-methods approach to document, analyze, and conceptualize the interacting factors that shape vulnerability and to explore community members’ perceptions of the role and relative importance of climate change compared to other factors in three rural communities in Ecuador. Economic instability, lack of access to basic services, and environmental degradation are perceived as greater threats to community well being than increasing seasonal variability and flooding. Programs and policies directed at climate change adaptation should integrate climate and non-climate related stressors. Our findings also point to a greater need for collaboration across public health, poverty alleviation, and environmental management fields through practical research targeting assistance to vulnerable populations.
Background: Toxoplasma gondii is a parasite of worldwide importance but its burden in indigenous communities remains unclear. In French Guiana, atypical strains of T. gondii originating from a complex rainforest cycle involving wild felids have been linked to severe infections in humans. These cases of Amazonian toxoplasmosis are sporadic and outbreaks are rarely described. We report on the investigation of an outbreak of acute toxoplasmosis in a remote Amerindian village. We discuss the causes and consequences of this emergence. Methods: In May 2017, during the rainy season and following an episode of flooding, four simultaneous cases of acute toxoplasmosis were serologically confirmed in two families living the village. Other non-diagnosed cases were then actively screened by a medical team along with epidemiological investigations. Inhabitants from nine households were tested for T. gondii antibodies and parasite DNA by PCR when appropriate. Samples of water, cat feces and cat rectal swabs, soil, and meat were tested for T. gondii DNA by PCR. Positive PCR samples with sufficient DNA amounts were genotyped using 15 microsatellite markers. Results: Between early May and early July 2017, out of 54 tested inhabitants, 20 cases were serologically confirmed. A fetus infected at gestational week 10 died but other cases were mild. Four patients tested positive for parasite DNA and two identical strains belonging to an atypical genotype could be isolated from unrelated patients. While domestic cats had recently appeared in the vicinity, most families drank water from unsafe sources. Parasite DNA was recovered from one water sample and nine soil samples. Three meat samples tested positive, including wild and industrial meat. Conclusions: The emergence of toxoplasmosis in such a community living in close contact with the Amazon rainforest is probably multifactorial. Sedentary settlements have been built in the last few decades without providing safe water sources, increasing the risk of parasite circulation in cases of dangerous new habits such as cat domestication. Public health actions should be implemented in these communities such as safe water supply, health recommendations, and epidemiological surveillance of acute toxoplasmosis. A “One Health” strategy of research involving medical anthropology, veterinary medicine, and public health needs to be pursued for a better understanding of the transmission routes and the emergence of this zoonosis.
The robust estimate and forecast capability of random forests (RF) has been widely recognized, however this ensemble machine learning method has not been widely used in mosquito-borne disease forecasting. In this study, two sets of RF models were developed at the national (pooled department-level data) and department level in Colombia to predict weekly dengue cases for 12-weeks ahead. A pooled national model based on artificial neural networks (ANN) was also developed and used as a comparator to the RF models. The various predictors included historic dengue cases, satellite-derived estimates for vegetation, precipitation, and air temperature, as well as population counts, income inequality, and education. Our RF model trained on the pooled national data was more accurate for department-specific weekly dengue cases estimation compared to a local model trained only on the department’s data. Additionally, the forecast errors of the national RF model were smaller to those of the national pooled ANN model and were increased with the forecast horizon increasing from one-week-ahead (mean absolute error, MAE: 9.32) to 12-weeks ahead (MAE: 24.56). There was considerable variation in the relative importance of predictors dependent on forecast horizon. The environmental and meteorological predictors were relatively important for short-term dengue forecast horizons while socio-demographic predictors were relevant for longer-term forecast horizons. This study demonstrates the potential of RF in dengue forecasting with a feasible approach of using a national pooled model to forecast at finer spatial scales. Furthermore, including sociodemographic predictors is likely to be helpful in capturing longer-term dengue trends.
OBJECTIVE: In 2011-2012, severe El Niño Southern Oscillation (ENSO) conditions (La Niña) led to massive flooding and temporarily displacement in the Peruvian Amazon. Our aims were to examine the impact of this ENSO exposure on child diets, in particular: (1) frequency of food consumption patterns, (2) the amount of food consumed (g/d), (3) dietary diversity (DD), (4) consumption of donated foods, among children aged 9-36 months living in the outskirts of City of Iquitos in the Amazonian Peru. DESIGN: This was a longitudinal study that used quantitative 24-h recall dietary data collection from children aged 9-36 months from 2010 to 2014 as part of the MAL-ED birth cohort study. SETTING: Iquitos, Loreto, Peru. PARTICIPANTS: Two hundred and fifty-two mother-child dyads. RESULTS: The frequency of grains, rice, dairy and sugar in meals reduced by 5-7 %, while the frequency of plantain in meals increased by 24 % after adjusting for covariates. ENSO exposure reduced girl’s intake of plantains and sugar. Despite seasonal fluctuations in the availability of fruits, vegetables and fish, DD remained constant across seasons and as children aged. However, DD was significantly reduced under moderate La Niña conditions by 0·32 (P < 0·05) food groups. Adaptive social strategies such as consumption of donated foods were significantly higher among households with girls. CONCLUSIONS: This is the first empirical study to show differential effect of the ENSO on the dietary patterns of children, highlighting differences by gender. Public health nutrition programmes should be climate- and gender-sensitive in their efforts to safeguard the diets of vulnerable populations.
Leptospirosis is a serious bacterial infection that occurs worldwide, with fatality rate of up to 40% in the most severe cases. The number of cases peaks during the rainy season and may reach epidemic proportions in the event of flooding. It is possible that people living in areas affected by natural disasters are at greater risk of contracting the disease. The aim of this study was to identify clusters of relatively higher risk for leptospirosis occurrence, both in space and time, in six municipalities of Santa Catarina, Brazil, which had the highest incidence of the disease between 2000 and 2016, and to evaluate if these clusters coincide with the occurrence of natural disasters. The cases were geocoded with the geographic coordinates of patients’ home addresses, and the analysis was performed using SaTScan software. The areas mapped as being at risk for hydrological and mass movements were compared with the locations of detected leptospirosis clusters. The disease was more common in men and in the age group from 15 to 69 years. In the scan statistics performed, only space-time showed significant results. Clusters were detected in all municipalities in 2008, when natural disasters preceded by heavy rainfall occurred. One of the municipalities also had clusters in 2011. In these clusters, most of the cases lived in urban areas and areas at risk for experiencing natural disasters. The interaction between time (time of disaster occurrence) and space (areas at risk of experiencing natural disasters) were the determining factors affecting cluster formation.
Kerteszia cruzii is a sylvatic mosquito and the primary vector of Plasmodium spp., which can cause malaria in humans in areas outside the Amazon River basin in Brazil. Anthropic changes in the natural environments are the major drivers of massive deforestation and local climate change, with serious impacts on the dynamics of mosquito communities and on the risk of acquiring malaria. Considering the lack of information on the dynamics of malaria transmission in areas across the Atlantic Forest biome, where Ke. cruzii is the dominant vector, and the impact of climate drivers of malaria, the present study aimed to: (i) investigate the occurrence and survival rate of Ke. cruzii based on the distinct vegetation profiles found in areas across the coastal region of the Brazilian Atlantic Forest biome; (ii) estimate the extrinsic incubation period (EIP) and survival rates of P. vivax and P. falciparum parasites in Ke. cruzii under current and future scenarios. The potential distribution of Plasmodium spp. was estimated using simulation analyses under distinct scenarios of average temperature increases from 1 °C to 3.7 °C. Our results showed that two conditions are necessary to explain the occurrence and survival of Ke. cruzii: warm temperature and presence of the Atlantic Forest biome. Moreover, both Plasmodium species showed a tendency to decrease their EIP and increase their estimated survival rates in a scenario of higher temperature. Our findings support that the high-risk malaria areas may include the southern region of the distribution range of the Atlantic Forest biome in the coming years. Despite its limitations and assumptions, the present study provides robust evidence of areas with potential to be impacted by malaria incidence in a future scenario. These areas should be monitored in the next decades regarding the occurrence of the mosquito vector and the potential for malaria persistence and increased occurrence.
The incidence of hospitalized leptospirosis patients was positively associated with increased precipitation in Salvador, Brazil. However, Leptospira infection risk among a cohort of city residents was inversely associated with rainfall. These findings indicate that, although heavy rainfall may increase severe illness, Leptospira exposures can occur year-round.
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 aim of the present study was to evaluate the relationship between cognitive performance, health and environmental comfort as a function of indoor air temperature (T-a) variation. A total of 360 undergraduate students were subjected to the variation of the T-a at 20, 24 and 30 degrees C; their thermal responses were evaluated over three consecutive days. Performance variables measured in the study were cognitive performance, blood pressure, heart rate (HR) and comfort. The environmental variables measured were T-a, globe temperature (T-g), illumination, noise, airflow velocity and air quality. The variation in HR was influenced by the variables, relative air humidity and mean radiant temperature (T-rm) during the three days of observation, where HR was higher than 100 bpm when T-g was greater than T-a. T-rm increased proportionally to the increase in T-g, thus characterising heat exchange by radiation. The number of correct answers and test response time were also positively influenced by T-rm when T-a was 20 degrees C. Teaching environments (TEs) with increased heat load due to the individual body heat of students, increased outdoor T-a and urban morphology associated with the building of the TEs result in increasing in T-rm due to the T-g being higher than the air temperature, with possible impacts on health and performance variables.
BACKGROUND: Dengue is an arbovirus that has caused serious problem in Brazil, putting the public health system under severe stress. Understanding its incidence and spatial distribution is essential for disease control and prevention. OBJECTIVE: To perform an analysis on dengue incidence and spatial distribution in a medium-sized, cool-climate and high-altitude city. DESIGN AND SETTING: Ecological study carried out in a public institution in the city of Garanhuns, Pernambuco, Brazil. METHODS: Secondary data provided by specific agencies in each area were used for spatial analysis and elaboration of kernel maps, incidence calculations, correlations and percentages of dengue occurrence. The Geocentric Reference System for the Americas (Sistema de Referência Geocêntrico para as Américas, SIRGAS), 2000, was the software of choice. RESULTS: The incidence rates were calculated per 100,000 inhabitants. Between 2010 and 2019, there were 6,504 cases and the incidence was 474.92. From 2010 to 2014, the incidence was 161.46 for a total of 1,069 cases. The highest incidence occurred in the period from 2015 to 2019: out of a total of 5,435 cases, the incidence was 748.65, representing an increase of 485.97%. Population density and the interaction between two climatic factors, i.e. atypical temperature above 31 °C and relative humidity above 31.4%, contributed to the peak incidence of dengue, although these variables were not statistically significant (P > 0.05). CONCLUSION: The dengue incidence levels and spatial distribution reflected virus and vector adjustment to the local climate. However, there was no correlation between climatic factors and occurrences of dengue in this city.
INTRODUCTION: Snakebites represent a serious global public health problem, especially in tropical countries. In Brazil, the incidence of snakebites ranges from 19 to 22 thousand cases per 100000 persons annually. The state of Rondônia, in particular, has had an increasing incidence of snakebites. METHODS: A retrospective cross-sectional study on snakebites was conducted from January 2007 to December 2018. Brazil’s Information System for Notifiable Diseases was queried for all snakebites reported in Porto Velho, Ariquemes, Cacoal, and Vilhena. Data on land surface temperatures during the day and night, precipitation, and humidity were obtained using the Google Earth Engine. A Bayesian time series model was constructed to describe the pattern of snakebites and their relationship with climate data. RESULTS: In total, 6326 snakebites were reported in Rondônia. Accidents were commonly caused by Bothrops sp. (n=2171, 81.80%). Snakebites most frequently occurred in rural areas (n=2271, 85.5%). Men, with a median age of 34 years (n=2101, 79.1%), were the most frequent bitten. Moderate clinical manifestation was the most common outcome of an accident (n=1101, 41.50%). There were clear seasonal patterns with respect to rainfall, humidity, and temperature. Rainfall and land surface temperature during the day or night did not increase the risk of snakebites in any city; however, changes in humidity increased the risk of snakebites in all cities. CONCLUSION: This study identified the population exposed to snakes and the influence of anthropic and climatic factors on the incidence of snakebites. According to climate data, changes in humidity increased the risk of snakebites.
INTRODUCTION: Asthma is a disease that has been associated with the presence of different genetic and socio-environmental factors. OBJECTIVE: To identify and evaluate the seasonality of respiratory syncytial virus (RSV) and human rhinovirus (RV) in asthmatic children and adolescents in tropical climate, as well as to assess the socioeconomic and environmental factors involved. METHODS: The study was conducted in a referral hospital, where a total of 151 children were recruited with a respiratory infection. The International Study of Asthma and Allergies in Childhood (ISAAC) protocol and a questionnaire were applied, and a skin prick test was performed. The nasal swab was collected to detect RV and RSV through molecular assay. National Meteorological Institute (INMET) database was the source of climatic information. RESULTS: The socio-environmental characterization of asthmatic children showed the family history of allergy, disturbed sleep at night, dry cough, allergic rhinitis, individuals sensitized to at least one mite. We identified RV in 75% of children with asthma and 66.7% of RSV in children with asthma. There was an association between the presence of RV and the dry season whereas the presence of the RSV was associated with the rainy season. Contributing to these results, a negative correlation was observed between the RSV and the wind speed and the maximum temperature (T. Max) and a positive correlation with precipitation. CONCLUSIONS: The results suggest a high prevalence of RV and RSV in asthmatic children and the seasonality of these viruses were present in different climatic periods. This has significant implications for understanding short- and long-term clinical complications in asthmatic patients.
Temperature record-breaking events, such as the observed more intense, longer-lasting, and more frequent heat waves, pose a new global challenge to health sectors worldwide. These threats are of particular interest in low-income regions with limited investments in public health and a growing urban population, such as Brazil. Here, we apply a comprehensive interdisciplinary climate-health approach, including meteorological data and a daily mortality record from the Brazilian Health System from 2000 to 2015, covering 21 cities over the Metropolitan Region of Rio de Janeiro. The percentage of absolute mortality increase due to summer extreme temperatures is estimated using a negative binomial regression modeling approach and maximum/minimum temperature-derived indexes as covariates. Moreover, this study assesses the vulnerability to thermal stress for different age groups and both genders and thoroughly analyzes four extremely intense heat waves during 2010 and 2012 regarding their impacts on the population. Results showed that the highest absolute mortality values during heat-related events were linked to circulatory illnesses. However, the highest excess of mortality was related to diabetes, particularly for women within the elderly age groups. Moreover, results indicate that accumulated heat stress conditions during consecutive days preferentially preceded by persistent periods of moderate-temperature, lead to higher excess mortality rather than sporadic single hot days. This work may provide directions in human health policies related to extreme climate events in large tropical metropolitan areas from developing countries, contributing to altering the historically based purely reactive response.
Diarrheal diseases remain a significant contributor to the global burden of disease. Climate change may increase their incidence by altering the epidemiology of waterborne pathogens through changes in rainfall patterns. To assess potential impacts of future changes in rainfall patterns, we analyzed 33,927 cases of diarrhea across all Ministry of Health clinical facilities in Esmeraldas Province, Ecuador, for a 24-month period from 2013 to 2014, using mixed-effects Poisson regression. We assessed the association between the incidence of diarrheal diseases and heavy rainfall events (HREs) and antecedent rainfall conditions. In rural areas, we found no significant associations between HREs and incidence. In urban areas, dry antecedent conditions were associated with higher incidence than wet conditions. In addition, HREs with dry antecedent conditions were associated with elevated incidence by up to 1.35 (incidence rate ratio, 95% CI: 1.14-1.60) times compared with similar conditions without HREs. These patterns may be driven by accumulation of fecal contamination during dry periods, followed by a flushing effect during HREs. This phenomenon is more important in dense urban environments with more impervious surfaces. These findings suggest that projected increases in rainfall variability and HREs may increase diarrhea burden in urban regions, which are rapidly expanding globally.
Currently, occupational heat exposure is usually measured using environmental variables such as the wet bulb globe temperature index. The costs of heat stress monitoring include the acquisition of specialized equipment and the recruitment of trained personnel. In rapidly changing environments, such as outdoor settings, these assessments must be conducted on a daily basis. The wet bulb globe temperature index has been criticized as a measure of heat stress for its failure to account for individual differences in susceptibility to heat stress, age, body mass index, physical fitness, clothing, illnesses and use of alcohol or drugs. The objective of this study was to assess the relationship between heart rate and body temperature in heat-exposed workers to determine whether heart rate can be used to monitor and prevent heat stress and physiological strain. This study was based on previous literature as well as physiological and environmental data collected from 10 individuals engaged in heavy physical labor. Heart rate, which has been recommended by the American Conference of Governmental Industrial Hygienists (ACGIH) as a possible measure of heat stress, follows a similar trend to body temperature with a slight temporal delay. Heart rate monitors with alarm systems could be developed to notify workers when to slow down their activities or take a break for thermal recovery, thereby contributing to the prevention of heat-related illness.
The Metropolitan Region of Sao Paulo (MRSP) is one of the main regions of Brazil that in recent years has shown an increase in the number of days with heat waves, mainly affecting the health of the most sensitive populations, such as the elderly. In this study, we identified the heat waves in the MRSP using three different definitions regarding the maximum daily temperature threshold. To analyze the impact of heat waves on elderly mortality, we used distributed lag nonlinear models (dlnm) and we quantified the heat wave-related excess mortality of elderly people from 1985 to 2005 and made projections for the near future (2030 to 2050) and the distant future (2079-2099) under the climate change scenarios RCP4.5 and RCP8.5 (RCP: Representative Concentration Paths). An important aspect of this research is that for the projections we take into account two assumptions: non-adaptation and adaptation to the future climate. Our projections show that the heat wave-related excess of elderly mortality will increase in the future, being highest when we consider no adaptation, mainly from cardiovascular diseases in women (up to 587 deaths per 100,000 inhabitants per year). This study can be used for public policies to implement preventive and adaptive measures in the MRSP.
BACKGROUND: Rodent-borne hantaviruses (genus Orthohantavirus) are the etiologic agents causing two human diseases: hemorrhagic fever with renal syndrome (HFRS) in Euroasia; and hantavirus pulmonary syndrome (HPS) in North and South America. In South America fatality rates of HPS can reach up to 35%-50%. The transmission of pathogenic hantaviruses to humans occurs mainly via inhalation of aerosolized excreta from infected rodents. Thus, the epidemiology of HPS is necessarily linked to the ecology of their rodent hosts and the contact with a human, which in turn may be influenced by climatic variability. Here we examined the relationship between climatic variables and hantavirus transmission aim to develop an early warning system of potential hantavirus outbreaks based on ecologically relevant climatic factors. METHODOLOGY AND MAIN FINDINGS: We compiled reported HPS cases in northwestern Argentina during the 1997-2017 period and divided our data into biannual, quarterly, and bimestrial time periods to allow annual and shorter time delays to be observed. To evaluate the relationship of hantavirus transmission with mean temperature and precipitation we used dynamic regression analysis. We found a significant association between HPS incidence and lagged rainfall and temperature with a delay of 2 to 6 months. For the biannual and quarterly models, hantavirus transmission was positively associated with lagged rainfall and temperature; whereas the bimestrial models indicate a direct relationship with the rainfall but inverse for temperature in the second lagged period. CONCLUSIONS/SIGNIFICANCE: This work demonstrates that climate variability plays a significant role in the transmission of hantavirus in northwestern Argentina. The model developed in this study provides a basis for the forecast of potential HPS outbreaks based on climatic parameters. Our findings are valuable for the development of public health policies and prevention strategies to mitigate possible outbreaks. Nonetheless, a surveillance program on rodent population dynamics would lead to a more accurate forecast of HPS outbreaks.
Climate change affects the dynamics of vector-borne diseases. Culex pipiens Linnaeus is the main vector of West Nile fever, a widely distributed arbovirus, it is continuously increasing its distribution. Using a species distribution model, maps of suitable habitats of Cx. pipiens were generated for Chile in the current climate and three climate change scenarios, using global and regional georeferenced vector presence records as input, plus bioclimatic variables. Since this virus has not yet arrived in Chile, the purpose of this study is to anticipate potential risk areas and to prevent the establishment and spread of the virus. Cx. pipiens is widely distributed in Chile. The suitable habitats in Chile were concentrated mostly from 32 degrees to 35 degrees S, increasing in future scenarios up to 113 % in the northern zone and moving towards the mountains. This species conserves around 90 % of its niche in the future, and shows a reduction of 11.4 % in the severe climate change scenario. It is anticipated that Chile will experience an increase in the environmental suitability for Cx. pipiens moving from the Andes to the coastal zone throughout the country, mainly in the center-south. This will raise the risk of local virus transmission if the virus is introduced to the country via diverse routes.
INTRODUCTION: Haemagogus are mosquitoes with diurnal habits that live preferentially in forest areas. In Brazil, they are considered the primary vectors of wild yellow fever. METHODS: The ecological relationships between Haemagogus spegazzinii, the environment, and some of its activities in the semiarid region of Rio Grande do Norte were analyzed by collecting eggs with ovitraps, actively searching in tree holes, capturing adults in Shannon traps, and conducting an investigation for viral infections. RESULTS: A total of 2420 eggs, 271 immature specimens (larvae and pupae), and 206 adults were collected. Egg collection depended on rainfall and relative humidity, with oviposition occurring between January and May. Larvae were found in five plant species, including Tabebuia aurea (craibeira), with 160 larvae collected. We observed shared breeding sites between Hg. spegazzinii and the following species: Aedes albopictus, Aedes terrens, Culex spp., and Toxorhynchites theobaldi. Adults exhibited greater activity between 5 pm and 6 pm, when 191 (92.7%) specimens were captured, while only 1 (0.5%) was collected between 7 pm and 8 pm. The relationship between Hg. spegazzinii and rainfall was significant, with positive correlations with accumulated rainfall 5, 10, 15, 20, and 30 days before mosquito collection. We found that the species was infected with the DENV-2 virus. CONCLUSIONS: This work contributes new information on the bioecology of Hg. spegazzinii, with data on the main reproduction periods, oviposition, breeding sites, activity times, and the relationship between the species and meteorological variables in the Caatinga of northeastern Brazil.
Climate change has caused an increased occurrence of heat waves. As a result of rising temperatures, implications for health and the environment have been more frequently reported. Outdoor labour activities deserve special attention, as is the case with agricultural and construction workers exposed to extreme weather conditions, including intense heat. This paper presents an overview of heat stress conditions in Brazil from 1961 to 2010. It also presents computer-simulated projections of heat stress conditions up to the late 21st century. The proposed climate analysis drew on historical weather data obtained from national weather stations and on reanalysis data, in addition to future projections with the ETA (regarding the model’s unique vertical coordinate) regional forecast model. The projections took into consideration two Representative Concentration Pathways (RCP)-the 4.5 and 8.5 climate scenarios, namely, moderate and high emissions scenarios, respectively. Heat stress was inferred based on the wet-bulb globe temperature (WBGT) index. The results of this climate analysis show that Brazilian outdoor workers have been exposed to an increasing level of heat stress. These results suggest that future changes in the regional climate may increase the probability of heat stress situations in the next decades, with expectations of WBGT values greater than those observed in the baseline period (1961-1990). In terms of spatial distribution, the Brazilian western and northern regions experienced more critical heat stress conditions with higher WBGT values. As a response to the increased frequency trends of hot periods in tropical areas, urgent measures should be taken to review public policies in Brazil. Such policies should include actions towards better working conditions, technological development to improve outdoor labour activities, and employment legislation reviews to mitigate heat impacts on occupational health.
Air pollution regulation requires knowing major sources on any given zone, setting specific controls, and assessing how health risks evolve in response to those controls. Receptor models (RM) can identify major sources: transport, industry, residential, etc. However, RM results are typically available for short term periods, and there is a paucity of RM results for developing countries. We propose to combine a cluster analysis (CA) of air pollution and meteorological measurements with a short-term RM analysis to estimate a long-term, hourly source apportionment of ambient PM(2.5) and PM(10). We have developed a proof of the concept for this proposed methodology in three case studies: a large metropolitan zone, a city with dominant residential wood burning (RWB) emissions, and a city in the middle of a desert region. We have found it feasible to identify the major sources in the CA results and obtain hourly time series of their contributions, effectively extending short-term RM results to the whole ambient monitoring period. This methodology adds value to existing ambient data. The hourly time series results would allow researchers to apportion health benefits associated with specific air pollution regulations, estimate source-specific trends, improve emission inventories, and conduct environmental justice studies, among several potential applications.
Human actions intensify the greenhouse effect, aggravating climate changes in the Amazon and elsewhere in the world. The Intergovernmental Panel on Climate Change (IPCC) foresees a global increase of up to 4.5 °C and 850 ppm CO(2) (above current levels) by 2100. This will impact the biology of the Aedes aegypti mosquito, vector of Dengue, Zika, urban Yellow Fever and Chikungunya. Heat shock proteins are associated with adaptations to anthropic environments and the interaction of some viruses with the vector. The transcription of the hsp26, hsp83 and hsc70 genes of an A. aegypti population, maintained for more than forty-eight generations, in the Current, Intermediate and Extreme climatic scenario predicted by the IPCC was evaluated with qPCR. In females, highest levels of hsp26, hsp83 and hsc70 expression occurred in the Intermediate scenario, while in males, levels were high only for hsp26 gene in Current and Extreme scenarios. Expression of hsp83 and hsc70 genes in males was low under all climatic scenarios, while in the Extreme scenario females had lower expression than in the Current scenario. The data suggest compensatory or adaptive processes acting on heat shock proteins, which can lead to changes in the mosquito’s biology, altering vectorial competence.
