Socioeconomic factors increase the risk of teenage pregnancy: spatial and temporal analysis in a Brazilian municipality.

OBJECTIVE: To evaluate the distribution of the proportion of teenage mothers (PTM) in time and space and its relationship with socioeconomic indicators and social vulnerability. METHODS: An ecological study was carried out with teenage mothers living in 322 census tracts in Foz do Iguaçu (state of Paraná, Brazil) between 2013 and 2019. Spatial clusters of teenage mothers were identified by spatial scanning and grouped into strata with different prevalence. The association between these strata and the individual social vulnerability of the mothers was evaluated using the Pearson's Chi-square test. Linear regression models were adjusted to evaluate the association between PTM and socioeconomic factors by census tract and temporal trend in PTM in different strata. RESULTS: We identified five high prevalence clusters in peripheral regions and six with low prevalence in the central region of the municipality. Proportionally, there were more teenage mothers with a worse vulnerability index in the high prevalence stratum than in the low prevalence stratum. Places with worse socioeconomic conditions present higher PTM, a profile that did not change over time. For the increase of one unit in the Brazilian Deprivation Index and proportion of women responsible for the household, the PTM increased, respectively, by 3.8 (95%CI 3.1-4.4) and 0.086% (95%CI 0.03-0.14). There was a reduction in the global PTM in part of the period, which occurred later in the higher prevalence strata, but the proportions were stable again in the last years of study. CONCLUSION: Teenage pregnancy is concentrated in regions with worse socioeconomic conditions and greater maternal vulnerability and its behavior over time occurred differently in these areas.

Automatic mapping of high-risk urban areas for Aedes aegypti infestation based on building facade image analysis.

BACKGROUND: Dengue, Zika, and chikungunya, whose viruses are transmitted mainly by Aedes aegypti, significantly impact human health worldwide. Despite the recent development of promising vaccines against the dengue virus, controlling these arbovirus diseases still depends on mosquito surveillance and control. Nonetheless, several studies have shown that these measures are not sufficiently effective or ineffective. Identifying higher-risk areas in a municipality and directing control efforts towards them could improve it. One tool for this is the premise condition index (PCI); however, its measure requires visiting all buildings. We propose a novel approach capable of predicting the PCI based on facade street-level images, which we call PCINet. METHODOLOGY: Our study was conducted in Campinas, a one million-inhabitant city in São Paulo, Brazil. We surveyed 200 blocks, visited their buildings, and measured the three traditional PCI components (building and backyard conditions and shading), the facade conditions (taking pictures of them), and other characteristics. We trained a deep neural network with the pictures taken, creating a computational model that can predict buildings' conditions based on the view of their facades. We evaluated PCINet in a scenario emulating a real large-scale situation, where the model could be deployed to automatically monitor four regions of Campinas to identify risk areas. PRINCIPAL FINDINGS: PCINet produced reasonable results in differentiating the facade condition into three levels, and it is a scalable strategy to triage large areas. The entire process can be automated through data collection from facade data sources and inferences through PCINet. The facade conditions correlated highly with the building and backyard conditions and reasonably well with shading and backyard conditions. The use of street-level images and PCINet could help to optimize Ae. aegypti surveillance and control, reducing the number of in-person visits necessary to identify buildings, blocks, and neighborhoods at higher risk from mosquito and arbovirus diseases.

Spatiotemporal Bayesian modeling of the risk of congenital syphilis in São Paulo, SP, Brazil.

The aim of this study is to analyze the spatiotemporal risk of congenital syphilis (CS) in high-prevalence areas in the city of São Paulo, SP, Brazil, and to evaluate its relationship with socioeconomic, demographic, and environmental variables. An ecological study was conducted based on secondary CS data with spatiotemporal components collected from 310 areas between 2010 and 2016. The data were modeled in a Bayesian context using the integrated nested Laplace approximation (INLA) method. Risk maps showed an increasing CS trend over time and highlighted the areas that presented the highest and lowest risk in each year. The model showed that the factors positively associated with a higher risk of CS were the Gini index and the proportion of women aged 18-24 years without education or with incomplete primary education, while the factors negatively associated were the proportion of women of childbearing age and the mean per capita income.

Human movement and environmental barriers shape the emergence of dengue.

Understanding how emerging infectious diseases spread within and between countries is essential to contain future pandemics. Spread to new areas requires connectivity between one or more sources and a suitable local environment, but how these two factors interact at different stages of disease emergence remains largely unknown. Further, no analytical framework exists to examine their roles. Here we develop a dynamic modelling approach for infectious diseases that explicitly models both connectivity via human movement and environmental suitability interactions. We apply it to better understand recently observed (1995-2019) patterns as well as predict past unobserved (1983-2000) and future (2020-2039) spread of dengue in Mexico and Brazil. We find that these models can accurately reconstruct long-term spread pathways, determine historical origins, and identify specific routes of invasion. We find early dengue invasion is more heavily influenced by environmental factors, resulting in patchy non-contiguous spread, while short and long-distance connectivity becomes more important in later stages. Our results have immediate practical applications for forecasting and containing the spread of dengue and emergence of new serotypes. Given current and future trends in human mobility, climate, and zoonotic spillover, understanding the interplay between connectivity and environmental suitability will be increasingly necessary to contain emerging and re-emerging pathogens.

Socioeconomic factors increase the risk of teenage pregnancy: spatial and temporal analysis in a Brazilian municipality / Fatores socioeconômicos aumentam o risco de gravidez na adolescência: análise espacial e temporal em um município brasileiro

ABSTRACT Objective: To evaluate the distribution of the proportion of teenage mothers (PTM) in time and space and its relationship with socioeconomic indicators and social vulnerability. Methods: An ecological study was carried out with teenage mothers living in 322 census tracts in Foz do Iguaçu (state of Paraná, Brazil) between 2013 and 2019. Spatial clusters of teenage mothers were identified by spatial scanning and grouped into strata with different prevalence. The association between these strata and the individual social vulnerability of the mothers was evaluated using the Pearson's Chi-square test. Linear regression models were adjusted to evaluate the association between PTM and socioeconomic factors by census tract and temporal trend in PTM in different strata. Results: We identified five high prevalence clusters in peripheral regions and six with low prevalence in the central region of the municipality. Proportionally, there were more teenage mothers with a worse vulnerability index in the high prevalence stratum than in the low prevalence stratum. Places with worse socioeconomic conditions present higher PTM, a profile that did not change over time. For the increase of one unit in the Brazilian Deprivation Index and proportion of women responsible for the household, the PTM increased, respectively, by 3.8 (95%CI 3.1-4.4) and 0.086% (95%CI 0.03-0.14). There was a reduction in the global PTM in part of the period, which occurred later in the higher prevalence strata, but the proportions were stable again in the last years of study. Conclusion: Teenage pregnancy is concentrated in regions with worse socioeconomic conditions and greater maternal vulnerability and its behavior over time occurred differently in these areas.

RESUMO Objetivo: Avaliar a distribuição da proporção de mães adolescentes (PMA) no tempo e espaço e sua relação com indicadores socioeconômicos e vulnerabilidade social. Métodos: Realizou-se estudo ecológico com mães adolescentes residentes em 322 setores censitários de Foz do Iguaçu (PR) entre 2013 e 2019. Aglomerados espaciais de mães adolescentes foram identificados por varredura espacial e agrupados em estratos com diferentes prevalências. Avaliou-se a associação entre esses estratos e a vulnerabilidade social individual das mães pelo teste qui-quadrado de Pearson. Ajustaram-se modelos de regressão linear para avaliar associação entre a PMA e fatores socioeconômicos por setor censitário e tendência temporal da PMA nos diferentes estratos. Resultados: Identificaram-se cinco aglomerados de alta prevalência nas regiões periféricas e seis de baixa na região central do município. Proporcionalmente houve mais mães adolescentes com pior índice de vulnerabilidade no estrato de alta prevalência do que no de baixa. Locais com piores condições socioeconômicas apresentaram maior PMA, perfil que não mudou ao longo do tempo. Para o aumento de uma unidade do Índice Brasileiro de Privação e da proporção de mulheres responsáveis por domicílio, a PMA aumentou respectivamente 3,8 (IC95% 3,1-4,4) e 0,086% (IC95% 0,03-0,14). Houve uma redução na PMA global em parte do período, que ocorreu mais tardiamente nos estratos de maior prevalência, mas as proporções voltaram a ficar estáveis nos últimos anos de estudo. Conclusão: A gravidez na adolescência se concentra em regiões de pior condição socioeconômica e com maior vulnerabilidade materna e seu comportamento no tempo ocorreu, nessas áreas, de modo distinto.

Zika, chikungunya and co-occurrence in Brazil: space-time clusters and associated environmental-socioeconomic factors.

Chikungunya and Zika have been neglected as emerging diseases. This study aimed to analyze the space-time patterns of their occurrence and co-occurrence and their associated environmental and socioeconomic factors. Univariate (individually) and multivariate (co-occurrence) scans were analyzed for 608,388 and 162,992 cases of chikungunya and Zika, respectively. These occurred more frequently in the summer and autumn. The clusters with the highest risk were initially located in the northeast, dispersed to the central-west and coastal areas of São Paulo and Rio de Janeiro (2018-2021), and then increased in the northeast (2019-2021). Chikungunya and Zika demonstrated decreasing trends of 13% and 40%, respectively, whereas clusters showed an increasing trend of 85% and 57%, respectively. Clusters with a high co-occurrence risk have been identified in some regions of Brazil. High temperatures are associated with areas at a greater risk of these diseases. Chikungunya was associated with low precipitation levels, more urbanized environments, and places with greater social inequalities, whereas Zika was associated with high precipitation levels and low sewage network coverage. In conclusion, to optimize the surveillance and control of chikungunya and Zika, this study's results revealed high-risk areas with increasing trends and priority months and the role of socioeconomic and environmental factors.

Spatial Clusters of Cancer Mortality in Brazil: A Machine Learning Modeling Approach.

Objectives: Our aim was to test if machine learning algorithms can predict cancer mortality (CM) at an ecological level and use these results to identify statistically significant spatial clusters of excess cancer mortality (eCM). Methods: Age-standardized CM was extracted from the official databases of Brazil. Predictive features included sociodemographic and health coverage variables. Machine learning algorithms were selected and trained with 70% of the data, and the performance was tested with the remaining 30%. Clusters of eCM were identified using SatScan. Additionally, separate analyses were performed for the 10 most frequent cancer types. Results: The gradient boosting trees algorithm presented the highest coefficient of determination (R 2 = 0.66). For total cancer, all algorithms overlapped in the region of Bagé (27% eCM). For esophageal cancer, all algorithms overlapped in west Rio Grande do Sul (48%-96% eCM). The most significant cluster for stomach cancer was in Macapá (82% eCM). The most important variables were the percentage of the white population and residents with computers. Conclusion: We found consistent and well-defined geographic regions in Brazil with significantly higher than expected cancer mortality.

Physical Attributes of Tree Holes in the Atlantic Forest Edges: Evaluating Their Association with the Presence and Abundance of Immature Haemagogus leucocelaenus.

Sylvatic yellow fever (SYF) was recently a health issue in Brazil (2016-2019) because transmission was facilitated by a high density of vectors, amplifying hosts, and low vaccine coverage of the human population, especially in urban forests in the Southeast Region of Brazil. Moreover, urban forest edges are more likely to have contact between human and sylvatic vector mosquito populations. Here, we show the association between abiotic and biotic features of tree holes as Haemagogus leucocelaenus rearing sites in Cantareira State Park in Atlantic Forest edges. The analyzed physical features of the tree holes were diameter at breast height, tree hole opening diameter, depth, trunk diameter, tree hole volume, collected volume, height (varying from 0.02 to 4.2 m above ground), and the presence of Culicidae species other than Hg. leucocelaenus. We analyzed 105 positive and 68 negative water samples for larval presence and found no differences between them, suggesting the lack of specific physical characteristics in these categories. Hg. leucocelaenus larval abundance was correlated with the collected volume and opening diameter of tree holes. The tree species that most represented negative breeding sites were Euplassa cantareirae, Guarea macrophylla, Psychotria suterella, and Tibouchina pulchra. Four significant clusters as areas with a high risk of SYV were identified by Get-Ordis spatial analysis. Although Hg. leucocelaenus larvae were found in tree holes with high water levels, their occurrence was regulated by that of other mosquito species. Our findings contribute to clarifying immature vector ecology in tree holes related to human exposure to SYF in urban forest edges.

Spatiotemporal bayesian modelling of scorpionism and its risk factors in the state of São Paulo, Brazil.

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.

Covid-19 hospital mortality using spatial hierarchical models: cohort design with 74,994 registers.

OBJECTIVE: To investigate the relationship between covid-19 hospital mortality and risk factors, innovating by considering contextual and individual factors and spatial dependency and using data from the city of São Paulo, Brazil. METHODS: The study was performed with a spatial hierarchical retrospective cohort design using secondary data (individuals and contextual data) from hospitalized patients and their geographic unit residences. The study period corresponded to the first year of the pandemic, from February 25, 2020 to February 24, 2021. Mortality was modeled with the Bayesian context, Bernoulli probability distribution, and the integrated nested Laplace approximations. The demographic, distal, medial, and proximal covariates were considered. RESULTS: We found that per capita income, a contextual covariate, was a protective factor (odds ratio: 0.76 [95% credible interval: 0.74-0.78]). After adjusting for income, the other adjustments revealed no differences in spatial dependence. Without income inequality in São Paulo, the spatial risk of death would be close to one in the city. Other factors associated with high covid-19 hospital mortality were male sex, advanced age, comorbidities, ventilation, treatment in public healthcare settings, and experiencing the first covid-19 symptoms between January 24 and February 24, 2021. CONCLUSIONS: Other than sex and age differences, geographic income inequality was the main factor responsible for the spatial differences in the risk of covid-19 hospital mortality. Investing in public policies to reduce socioeconomic inequities, infection prevention, and other intersectoral measures should focus on lower per capita income, to control covid-19 hospital mortality.

Covid-19 hospital mortality using spatial hierarchical models: cohort design with 74, 994 registers

ABSTRACT OBJECTIVE To investigate the relationship between covid-19 hospital mortality and risk factors, innovating by considering contextual and individual factors and spatial dependency and using data from the city of São Paulo, Brazil. METHODS The study was performed with a spatial hierarchical retrospective cohort design using secondary data (individuals and contextual data) from hospitalized patients and their geographic unit residences. The study period corresponded to the first year of the pandemic, from February 25, 2020 to February 24, 2021. Mortality was modeled with the Bayesian context, Bernoulli probability distribution, and the integrated nested Laplace approximations. The demographic, distal, medial, and proximal covariates were considered. RESULTS We found that per capita income, a contextual covariate, was a protective factor (odds ratio: 0.76 [95% credible interval: 0.74-0.78]). After adjusting for income, the other adjustments revealed no differences in spatial dependence. Without income inequality in São Paulo, the spatial risk of death would be close to one in the city. Other factors associated with high covid-19 hospital mortality were male sex, advanced age, comorbidities, ventilation, treatment in public healthcare settings, and experiencing the first covid-19 symptoms between January 24 and February 24, 2021. CONCLUSIONS Other than sex and age differences, geographic income inequality was the main factor responsible for the spatial differences in the risk of covid-19 hospital mortality. Investing in public policies to reduce socioeconomic inequities, infection prevention, and other intersectoral measures should focus on lower per capita income, to control covid-19 hospital mortality.

Spatiotemporal bayesian modelling of scorpionism and its risk factors in the state of São Paulo, Brazil

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.

Impact of climate change on West Nile virus distribution in South America.

BACKGROUND: West Nile virus (WNV) is a vector-borne pathogen of global relevance and is currently the most widely distributed flavivirus causing encephalitis worldwide. Climate conditions have direct and indirect impacts on vector abundance and virus dynamics within the mosquito. The significance of environmental variables as drivers in WNV epidemiology is increasing under the current climate change scenario. In this study we used a machine learning algorithm to model WNV distributions in South America. METHODS: Our model evaluated eight environmental variables for their contribution to the occurrence of WNV since its introduction in South America in 2004. RESULTS: Our results showed that environmental variables can directly alter the occurrence of WNV, with lower precipitation and higher temperatures associated with increased virus incidence. High-risk areas may be modified in the coming years, becoming more evident with high greenhouse gas emission levels. Countries such as Bolivia, Paraguay and several Brazilian areas, mainly in the northeast and midwest regions and the Pantanal biome, will be greatly affected, drastically changing the current WNV distribution. CONCLUSIONS: Understanding the linkages between climatological and ecological change as determinants of disease emergence and redistribution will help optimize preventive strategies. Increased virus surveillance, integrated modelling and the use of geographically based data systems will provide more anticipatory measures by the scientific community.

Scorpion envenomation in the state of São Paulo, Brazil: Spatiotemporal analysis of a growing public health concern.

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.

Spatio-temporal dynamics of dengue-related deaths and associated factors.

Since the reintroduction of dengue viruses in 1987, Sao Paulo State (SP), Brazil, has experienced recurrent epidemics in a growing number of municipalities, each time with more cases and deaths. In the present study, we investigated the spatio-temporal dynamics of dengue-related deaths and associated factors in SP. This was an ecological study with spatial and temporal components, based on notified dengue-related deaths in the municipalities of SP between 2007 and 2017. A latent Gaussian Bayesian model with Poisson probability distribution was used to estimate the standardized mortality ratios (SMR) for dengue and relative risks (RR) for the socioeconomic, demographic, healthcare-related, and epidemiological factors considered. Epidemiological factors included the annual information on the number of circulating serotypes. A total of 1,019 dengue-related deaths (0.22 per 100,000 inhabitant-years) between 2007 and 2017 were confirmed in SP by laboratory testing. Mortality increased with age, peaking at 70 years or older (1.41 deaths per 100,000 inhabitant-years). Mortality was highest in 2015, and the highest SMR values were found in the North, Northwest, West, and coastal regions of SP. An increase of one circulating serotype, one standard deviation in the number of years with cases, and one standard deviation in the degree of urbanization were associated with increases of 75, 35, and 45% in the risk of death from dengue, respectively. The risk of death from dengue increased with age, and the distribution of deaths was heterogeneous in space and time. The positive relationship found between the number of dengue serotypes circulating and years with cases at the municipality/micro-region level indicates that this information can be used to identify risk areas, intensify surveillance and control measures, and organize healthcare to better respond to this disease.

Association between densities of adult and immature stages of Aedes aegypti mosquitoes in space and time: implications for vector surveillance.

BACKGROUND: Mosquito control is currently the main tool available to contain the spread of several arboviruses in Brazil. We have evaluated the association between entomological surveys of female adult Aedes aegypti and the Breteau index (BI) in space and time in a hyperendemic area, and compared the human resources costs required to measure each of these indicators. METHODS: Entomological surveys were conducted between 2016 and 2019 in Vila Toninho, a neighborhood in the city of São José do Rio Preto, Brazil. Monthly records of collected mosquito specimens were made and then grouped by season. RESULTS: Our findings showed that adult and immature mosquitoes are more related in time than in space, possibly due to differences in their habitats or in climate variables. Bayesian temporal modeling revealed that an increase in 1 standard deviation in the BI was associated with a 27% increase in the number of adult female mosquitoes when adjusted for climatic conditions. The cost of entomological surveys of adult mosquitoes was found to be 83% lower than the cost of determining the BI when covering the same geographic area. CONCLUSIONS: For fine-scale assessments, a simple measure of adult Ae. aegypti abundance may be more realistic than aquatic indicators, but the adult indices are not necessarily the only reliable measure. Surveying adult female mosquitoes has significant potential for optimizing vector control strategies because, unlike the BI, this tool provides an effective indicator for micro-areas within an urban region. It should be noted that the results of the present study may be due to specific features of of the study area, and future studies should analyze whether the patterns found in the study neighborhood are also found in other regions.

Temporal trends in leptospirosis incidence and association with climatic and environmental factors in the state of Santa Catarina, Brazil. / Tendência temporal da leptospirose e sua associação com variáveis climáticas e ambientais em Santa Catarina, Brasil.

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.

A leptospirose é uma zoonose que apresenta potencial epidêmico, principalmente após fortes chuvas que acarretam inundações, alagamentos e enxurradas. Algumas características da região costeira de Santa Catarina, localizada no Sul do Brasil, influenciam nesses processos. Portanto, a partir do estudo da leptospirose nos seis municípios do estado com as maiores incidências e picos epidêmicos de 2000 a 2015, buscou-se conhecer a tendência dessa doença e as variáveis climáticas e ambientais associadas à sua ocorrência, ajustando dois modelos com resposta binomial negativa. As maiores incidências foram encontradas em 2008 e 2011, com picos no mesmo mês ou no posterior aos eventos de desastres. A incidência apresentou forte comportamento sazonal, sendo maior nos meses do verão. Observou-se tendência de queda na incidência dos municípios estudados, estimada em 3,21% ao ano. Os fatores climáticos e ambientais mais fortemente associados foram o número de dias de chuva, a temperatura máxima e a presença de enxurrada e de inundação, com diferentes impactos entre os municípios. Houve interações significativas, indicando que o efeito de inundações na incidência não é o mesmo em todos os municípios e que as diferenças nas incidências entre os municípios dependem da ocorrência ou não de inundações.

Detection of areas vulnerable to scorpionism and its association with environmental factors in São Paulo, Brazil.

Accidents caused by scorpions are considered a neglected condition and represent a major health problem in most tropical countries, especially for children and elderly people. In Brazil, scorpionism is recurrent in the southeast region, mainly in the state of São Paulo, due to the progressive increase in scorpions found in urban habitats. Thus, our study aimed to provide better insights into the geographic and epidemiological characteristics of scorpion envenomation in São Paulo state and identify the environmental factors that are associated with these accidents. This is an ecological and retrospective study with secondary data on scorpion accidents in the state of São Paulo from 2008 to 2018 obtained from the Notifiable Disease Information System. The SatScan software was used to identify the higher- and lower-risk spatiotemporal clusters. A total of 145,464 scorpion sting cases were recorded in the state of São Paulo, between 2008 and 2018; there was a four-fold increase in the incidence rate. Accidents occurred more frequently in the spring season, wherein higher-risk clusters were in the north and northwest regions of the state. High temperatures, low precipitation, and poor natural vegetation are associated with higher risk areas. Our study mapped vulnerable areas for scorpion accidents that can aid in the design of efficient public health policies, which should be intensified during the spring season.

Tendência temporal da leptospirose e sua associação com variáveis climáticas e ambientais em Santa Catarina, Brasil / Temporal trends in leptospirosis incidence and association with climatic and environmental factors in the state of Santa Catarina, Brazil

Resumo A leptospirose é uma zoonose que apresenta potencial epidêmico, principalmente após fortes chuvas que acarretam inundações, alagamentos e enxurradas. Algumas características da região costeira de Santa Catarina, localizada no Sul do Brasil, influenciam nesses processos. Portanto, a partir do estudo da leptospirose nos seis municípios do estado com as maiores incidências e picos epidêmicos de 2000 a 2015, buscou-se conhecer a tendência dessa doença e as variáveis climáticas e ambientais associadas à sua ocorrência, ajustando dois modelos com resposta binomial negativa. As maiores incidências foram encontradas em 2008 e 2011, com picos no mesmo mês ou no posterior aos eventos de desastres. A incidência apresentou forte comportamento sazonal, sendo maior nos meses do verão. Observou-se tendência de queda na incidência dos municípios estudados, estimada em 3,21% ao ano. Os fatores climáticos e ambientais mais fortemente associados foram o número de dias de chuva, a temperatura máxima e a presença de enxurrada e de inundação, com diferentes impactos entre os municípios. Houve interações significativas, indicando que o efeito de inundações na incidência não é o mesmo em todos os municípios e que as diferenças nas incidências entre os municípios dependem da ocorrência ou não de inundações.

Abstract 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.