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Factors such as viral adaptation, variations in mosquitoes across different sites and species, the availability of sylvan mammalian hosts, the range and distribution of other vertebrate hosts, and patterns in human availability, population density, and travel contribute to determining the future course of both OROV and MAYV. The escalating risk of OROV, MAYV, and other emerging arbovirus epidemics results from factors such as an expanding susceptible population, increased population density and mobility, growing incursions of vulnerable tourists and workers into forested areas, urban encroachment, and potential colonisation of habitats by anthropophilic insect species [5]. Environmental changes, such as deforestation in the Amazon and the subsequent expansion of cocoa plantations, have created an ideal environment for vector reproduction in cocoa shells.

Dengue fever, a mosquito-borne viral disease, poses a significant public health challenge whose transmission dynamics are highly sensitive to climatic conditions. However, the effects of extreme weather events like heatwaves remain poorly understood. This study investigated the influence of climatic factors and heatwaves on dengue incidence in two key Brazilian hotspots: the subtropical megacity of São Paulo (Sao Paulo State) and the tropical coastal city of Natal (Rio Grande do Norte State). We analyzed weekly confirmed dengue cases and meteorological data (temperature, precipitation, heatwaves) from 2014 to 2023. Distributed lag non-linear models and negative binomial regression were used to assess the complex, delayed associations between meteorological variables and dengue infections. Over the study period, 149,468 dengue cases were reported in São Paulo and 80,999 in Natal. Transmission patterns differed significantly, with Natal exhibiting more regular epidemic cycles. Our models revealed that higher minimum temperatures were associated with increased dengue risk in both cities. Conversely, and perhaps counter-intuitively, higher maximum temperatures and total precipitation showed negative associations with dengue cases. The impact of heatwaves was strikingly different between the locations. In São Paulo, the occurrence of a heatwave was associated with a 70% reduction in dengue risk in subsequent weeks (Relative Risk [RR]: 0.30, 95% Confidence Interval [CI]: 0.18–0.49). In contrast, no statistically significant association between heatwaves and dengue was observed in Natal. Our findings demonstrate that the relationship between extreme heat and dengue transmission is not uniform and can be inhibitory, challenging the assumption that warming consistently favors vector proliferation. These location-specific insights are critical for developing more accurate, tailored public health early-warning systems and caution against one-size-fits-all climate adaptation strategies for vector-borne diseases.

Changes in the geographic distribution and territorial expansion of Aedes aegypti, the main dengue vector in the Americas, coupled with the concurrent circulation of multiple DENV serotypes, have driven the overall rise in dengue incidence in Brazil. Here, we investigate the spatiotemporal distribution of dengue virus serotypes across Brazil, focusing on dengue epidemiology over the last decade (2014–2025). We examine the temporal dynamics of these serotypes and discuss the main strategies to mitigate the public health impact of their co-circulation.

Oropouche virus (OROV) is an arthropod-borne virus responsible for outbreaks of Oropouche fever (ORO) in Central and South America since the 1950s. Herein, we investigated the climatic and socioenvironmental factors contributing to the reemergence of ORO in Brazil in 2024, culminating in the largest epidemic in the country’s history. Accordingly, we conducted a modeling study to identify areas with the highest incidence of OROV in Brazil based on confirmed human cases between the 2020 and 2024 outbreaks and socioenvironmental variables. Our analysis utilized Maxent software, a machine learning algorithm for species distribution modeling, along with SatScan software to identify high- and low-risk spatial clusters. A total of 8,258 ORO cases were serologically confirmed in Brazil in 2024 and 108 in 2020/2021. The distribution of OROV differed markedly in 2020 and 2024: in 2020, cases were primarily confined to the Amazon region, while in 2024, cases expanded across nearly the entire country. High-risk areas showed higher temperatures and precipitation, and land-cover and land-use change (LCLUC) appeared to be key factors in ORO distribution. Upon comparing deforestation rates between 2020 and 2023, we noted a sharper increase in the expansion of pasture cover and soybean plantations in high-risk regions. Moreover, municipalities in high-risk clusters tended to face greater socioeconomic challenges, including poverty and restricted access to healthcare. Our study identified areas vulnerable to OROV circulation, providing valuable insights to support the establishment of robust public health policies that must be prioritized and strengthened in the context of climate change.

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. 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. 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. 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.

Seasonal fluctuations in weather are recognized as factors that affect both Aedes (Ae.) aegypti mosquitoes and the diseases they carry, such as dengue fever. The El Niño-Southern Oscillation (ENSO) is widely regarded as one of the most impactful atmospheric phenomena on Earth, characterized by the interplay of shifting ocean temperatures, trade wind intensity, and atmospheric pressure, resulting in extensive alterations in climate conditions. In this study, we investigate the influence of ENSO and local weather conditions on the spatio-temporal variability of Ae. aegypti infestation index. We collected seasonal entomological survey data of immature forms of Ae. aegypti mosquitoes (Breteau index), as well as data on temperature, rainfall and the Oceanic Niño Index (ONI) for the period 2008-2018 over the 645 municipalities of the subtropical State of São Paulo (Brazil). We grounded our analytical approach on a Bayesian framework and we used a hierarchical spatio-temporal model to study the relationship between ENSO tracked by ONI, seasonal weather fluctuations and the larval index, while adjusting for population density and wealth inequalities. Our results showed a relevant positive effect for El Niño on the Ae. aegypti larval index. In particular, we found that the number of positive containers would be expected to increase by 1.30-unit (95% Credible Intervals (CI): 1.23 to 1.37) with El Niño events (i.e., ≥ 1°C, moderate to strong) respect to neutral (and weak) events. We also found that seasonal rainfall exceeding 153.12 mm appears to have a notable impact on vector index, leading potentially to the accumulation of ample water in outdoor discarded receptacles, supporting the aquatic phase of mosquito development. Additionally, seasonal temperature above 23.30°C was found positively associated to the larval index. Although the State of São Paulo as a whole has characteristics favourable to proliferation of the vector, there were specific areas with a greater tendency for mosquito infestation, since the most vulnerable areas are predominantly situated in the central and northern regions of the state, with hot spots of abundance in the south, especially during El Niño events. Our findings also indicate that social disparities present in the municipalities contributes to Ae. aegypti proliferation. Considering the anticipated rise in both the frequency and intensity of El Niño events in the forthcoming decades as a consequence of climate change, the urgency to enhance our ability to track and diminish arbovirus outbreaks is crucial.

Identifying Aedes aegypti breeding hotspots in urban areas is crucial for the design of effective vector control strategies. Remote sensing techniques offer valuable tools for mapping habitat suitability. In this study, we evaluated the association between urban landscape, thermal features, and mosquito infestations. Entomological surveys were conducted between 2016 and 2019 in Vila Toninho, a neighborhood of São José do Rio Preto, São Paulo, Brazil, in which the numbers of adult female Ae. aegypti were recorded monthly and grouped by season for three years. We used data from 2016 to 2018 to build the model and data from summer of 2019 to validate it. WorldView-3 satellite images were used to extract land cover classes, and land surface temperature data were obtained using the Landsat-8 Thermal Infrared Sensor (TIRS). A multilevel negative binomial model was fitted to the data, which showed that the winter season has the greatest influence on decreases in mosquito abundance. Green areas and pavements were negatively associated, and a higher cover of asbestos roofs and exposed soil was positively associated with the presence of adult females. These features are related to socio-economic factors but also provide favorable breeding conditions for mosquitos. The application of remote sensing technologies has significant potential for optimizing vector control strategies, future mosquito suppression, and outbreak prediction.

Scorpion envenomation is a significant public health concern in São Paulo, Brazil, and its incidence and mortality have increased in recent decades. The present study analyzed documented scorpion envenomation notifications from 2008 to 2018 throughout the 645 municipalities of São Paulo. Annual incidence and mortality rates were calculated and stratified according to sex and age. The local empirical Bayesian method and Getis-Ord Gi* statistic were used to represent standardized incidence rates in the municipalities and to identify high- and low-risk agglomerates. The incidence rate of scorpion envenomation quintupled between 2008 and 2018. Overall, the risk was higher for man, and increased with age. Deaths due to envenomation, however, were concentrated almost entirely in children 0–9 years of age. Incidence maps showed that the risk of envenomation increased in almost all regions and municipalities of São Paulo throughout the study period. The highest incidence rates were found in the western, northwestern and northern regions of the state, in contrast to the São Paulo metropolitan area and southern and coastal regions. Hot spots were identified in the Presidente Prudente, Barretos, São José do Rio Preto, and Araçatuba regional health districts, which over time formed a single high-risk cluster. In spatial terms, however, deaths were randomly distributed. In this study, we identified areas and populations at risk of scorpion envenomation and associated–fatalities, which can be used to support decision-making by health services to reduce human contact with these arachnids and avoid fatalities, especially in children.

Oropouche virus (OROV) is mainly transmitted to humans by Culicoides paraensis , a biting midge widely distributed across the Americas. In this study, we modeled the potential distribution of C. paraensis in Brazil using environmental variables and found that temperature-related factors, particularly minimum temperature and annual temperature range, were the strongest predictors of its occurrence. Comparison of the predicted distribution with confirmed autochthonous OROV cases revealed several areas of mismatch, suggesting either underreporting of C. paraensis or the involvement of additional vector species in transmission. These findings highlight the need to integrate C. paraensis into Brazil’s arbovirus surveillance systems and to strengthen entomological monitoring with the support of remote sensing, climate data, and ecological research to better anticipate and mitigate future transmission risks. Graphical Abstract

Brazil is a tropical country that is largely covered by rainforests and other natural ecosystems, which provide ideal conditions for the existence of many arboviruses. However, few analyses have examined the associations between environmental factors and arboviral diseases. Thus, based on the hypothesis of correlation between environment and epidemiology, the proposals of this study were (1) to obtain the probability of occurrence of Oropouche, Mayaro, Saint Louis and Rocio fevers in Brazil based on environmental conditions corresponding to the periods of occurrence of the outbreaks; (2) to describe the macroclimatic scenario in Brazil in the last 50 years, evaluating if there was any detectable tendency to increase temperatures and (3) to model future expansion of those arboviruses in Brazil based on future temperature projections. Our model assessed seven environmental factors (annual rainfall, annual temperature, elevation, seasonality of temperature, seasonality of precipitation, thermal amplitude, and daytime temperature variation) for their association with the occurrence of outbreaks in the last 50 years. Our results suggest that various environmental factors distinctly influence the distribution of each arbovirus, with temperature being the central determinant of disease distribution in all high-risk areas. These areas are subject to change, since the average temperature of some areas has increased significantly over the time. This is the first spatio-temporal study of the Oropouche, Mayaro, Saint Louis, and Rocio arboviruses, and our results indicate that they may become increasingly important public health problems in Brazil. Thus, next studies and control programs should include these diseases and also take into consideration key environmental elements.