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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Exposure to non-optimal temperatures remains the single most deathful direct climate change impact to health. The risk varies based on the adaptation capacity of the exposed population which can be driven by climatic and/or non-climatic factors subject to fluctuations over time. We investigated temporal changes in the exposure-response relationship between daily mean temperature and mortality by cause of death, sex, age, and ethnicity in the megacity of São Paulo, Brazil (2000-2018). We fitted a quasi-Poisson regression model with time-varying distributed-lag non-linear model (tv-DLNM) to obtain annual estimates. We used two indicators of adaptation: trends in the annual minimum mortality temperature (MMT), i.e., temperature at which the mortality rate is the lowest, and in the cumulative relative risk (cRR) associated with extreme cold and heat. Finally, we evaluated their association with annual mean temperature and annual extreme cold and heat, respectively to assess the role of climatic and non-climatic drivers. In total, we investigated 4,471,000 deaths from non-external causes. We found significant temporal trends for both the MMT and cRR indicators. The former was decoupled from changes in AMT, whereas the latter showed some degree of alignment with extreme heat and cold, suggesting the role of both climatic and non-climatic adaptation drivers. Finally, changes in MMT and cRR varied substantially by sex, age, and ethnicity, exposing disparities in the adaptation capacity of these population groups. Our findings support the need for group-specific interventions and regular monitoring of the health risk to non-optimal temperatures to inform urban public health policies.
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.
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).
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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: 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.
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.
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.
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.
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.
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.
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.
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.
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.
