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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.

The present study focused on the scenario of confirmed cases of SARS-CoV-2 infection in the state of Minas Gerais (MG), Brazil, from March 2020 to March 2021. We evaluated the evolution of COVID-19 prevalence and death in one municipality from each of the 14 health macro-regions of MG state. Socio-demographic characteristics and variables related to the municipalities were analyzed. The raw dataset used in this study was freely sourced from the website Brasil.io. From the raw dataset, two time series were extracted: the cumulative confirmed cases of COVID-19 and cumulative death counts, and they were compared to the state data using a nowcasting approach. In order to make time series comparisons possible, all data was normalized per 100,000 inhabitants. When analyzing in light of colored wave code interventions initiated in August 2020 in MG, for the majority of the municipalities, there was an absence of clear influence on prevalence and deaths. The national holidays in the first semester of 2020 had a small impact on the COVID-19 prevalence of the municipalities, but the holidays in the second semester of 2020 and beginning of 2021 caused important impacts on COVID-19 prevalence. The low number of ICU beds in some municipalities contributed to the higher number of deaths. The analysis showed here is expected to contribute to the improvement of decision making of the MG government, as it opened a huge possibility to have the total macro-regions and state data analyzed.

Objective: to analyze the spatial distribution of elder abuse in Ribeirão Preto-SP, according to victims' place of residence and event., Method: an ecological study that analyzed 1,153 elder abuse police reports (2009 to 2013). Local gross and empirical Bayesian rates and Local Moran's I were calculated., Results: there was a heterogeneous distribution of concentration of sectors with a high incidence rate surrounded by neighbors with also high rates, considering place of residence. In contrast, analysis by place of occurrence showed a greater concentration in the central areas of the municipality. More than 80% of cases of violence occurred at their own homes and with spatial dependence on distribution by occurrence up to a 5,000 m distance from their places of residence., Conclusion: data reinforce that violence is a complex phenomenon, affecting several social strata, including in central urban areas and in elderly people families' own context.

Background: Currently, Brazil is experiencing one of the fastest increasing coronavirus disease (COVID-19) mortality rates worldwide, with a minimum of 158,000 confirmed deaths presently. The city of São Paulo is particularly vulnerable because it is the most populated city in Brazil. Thus, this study aimed to analyse COVID-19 mortality in a spatiotemporal context in São Paulo, with respect to socio-economic levels., Method: We modelled the deaths using spatiotemporal architectures and Poisson probability distributions using a latent Gaussian Bayesian model approach., Results: Both total deaths and confirmed deaths showed similar spatial patterns. Mortality was higher in men and increased with age. The most critical period regarding mortality occurred between the 20th and 23rd epidemiological weeks, followed by an apparent stabilisation of the epidemiological trend. The risk of death was greater in areas with the worst social conditions during the study period. However, this pattern was not uniform over time, since we identified a shift of high risk from the areas with the best socio-economic conditions to those with the worst conditions., Conclusions: Our study corroborated the relationship between COVID-19 mortality and socio-economic conditions, revealing the importance of geographic screening in the integration of better actions to face the pandemic., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Objective: To verify the spatial pattern of mortality from breast and cervical cancer in areas of primary health care, considering socioeconomic conditions., Methods: This is an ecological study, from January 2000 to December 2016. The study area is the municipality of São Paulo, Brazil, and its 456 coverage areas of primary health units. Information on deaths of women aged 20 years or over were geocoded according to residence address. We calculated mortality rates, standardized by age, and smoothed by the local empirical Bayesian method, and grouped into three or two years to reduce the random fluctuation of the data. In addition, bivariate global and local Moran indexes were calculated to verify the existence of spatial agglomeration of standardized mortality rates with a domain of socioeconomic condition, elaborated based on the Índice Paulista de Vulnerabilidade Social (IPVS - São Paulo Index of Social Vulnerability)., Results: The success rate of geocoding was 98.9%. Mortality from breast cancer, without stratification by time, showed a pattern with higher rates located in central regions with better socioeconomic conditions. It showed a decrease at the end of the period and a change in spatial pattern, with increased mortality in peripheral regions. On the other hand, mortality from cervical cancer remained with the highest rates in peripheral regions with worse socioeconomic conditions, despite being reduced over time., Conclusion: The spatial pattern of mortality from the studied cancers, over time, suggests association with the best socioeconomic conditions of the municipality, either as protection (cervical) or risk (breast). This knowledge may direct resources to prevent and promote health in the territories.

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.

Traffic-related air pollution is being associated with hematologic cancer in young individuals. This study performed a spatial analysis of the hematologic cancer incidence and mortality among younger people, using a Bayesian approach, to associate with traffic density in the city of São Paulo, Brazil. Two databases were employed: incidence (2002-2011) and mortality (2002-2013). The relationships between the cases of hematologic cancer and the covariates - traffic density, the Municipal Human Development Index (MHDI), and population density - were evaluated using a Besag-York-Mollié ecological model with relative risks (RRs) estimates. Per 1-unit standard-deviation increase in traffic density, in the MHDI, and in population density, the RR for the incidence was 1.06 (95% CI: 0.97-1.14), 1.28 (95% CI: 1.16-1.42), and 1.01 (95% CI: 0.94-1.08), respectively. For mortality, no covariates were considered risk factors. Our findings suggest significant association between living in regions with better socioeconomic conditions, where traffic density is usually higher, and risk of hematologic cancer in younger people.

Background: Reducing TB mortality is a great challenge in Brazil due to its territorial extension, cultural variations and economic and political crises, which impact the health system. This study aimed to estimate in space and time the risk of TB mortality and test its relationship with social inequities., Methods: This was an ecological study that included deaths from TB between 2006 and 2016 in Cuiabá, Brazilian Legal Amazon. Bayesian models based on the integrated nested Laplace approximation approach were used to estimate spatio-temporal RRs. RRs for TB mortality were obtained according to the covariables representative of social inequities., Results: The risk of TB mortality was stable between 2006 and 2016 and high-risk areas were identified throughout the municipality studied. Regarding social inequities, income was an important factor associated with TB mortality risk, as an increase of 1 SD in income resulted in a 35.4% (RR 0.646; CI 95% 0.476 to 0.837) decrease in risk., Conclusions: The results provided evidence of areas with higher TB mortality risks that have persisted over time and are related to social inequities. Advancing social policies and protections in these areas will contribute to achieving the WHO's End TB strategy., (© The Author(s) 2020. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Visceral leishmaniasis is an emerging and neglected disease that is currently expanding to urban areas. The incidence of human disease is related to canine infection. Araçatuba and Birigui are municipalities (counties) in the state of São Paulo, Brazil, with 8-10% seroprevalence of canine infection and that employ control strategies targeting the canine reservoir, based on serological survey and culling of seropositive dogs. Using data from these control programs to parameterize mathematical models, this study assessed the efficacy of these activities. We estimated that current control is capable of reducing the incidence of canine visceral leishmaniasis (CVL) by approximately 20%. Assuming continuous control and three times the current serological survey activities in Araçatuba and Birigui, culling dogs with a positive CVL diagnosis would be effective for the control of canine infection. Although theoretically possible, in practice the control of CVL with the currently recommended strategies is insufficient, since it would require overcoming the difficulties in these activities, such as lack of material, human, and financial resources, besides associated ethical and legal issues.

Background: Tuberculosis (TB) is the infectious disease that kills the most people worldwide. The use of geoepidemiological techniques to demonstrate the dynamics of the disease in vulnerable communities is essential for its control. Thus, this study aimed to identify risk clusters for TB deaths and their variation over time., Methods: This ecological study considered cases of TB deaths in residents of Londrina, Brazil between 2008 and 2015. We used standard, isotonic scan statistics for the detection of spatial risk clusters. The Poisson discrete model was adopted with the high and low rates option used for 10, 30 and 50% of the population at risk, with circular format windows and 999 replications considered the maximum cluster size. Getis-Ord Gi* (Gi*) statistics were used to diagnose hotspot areas for TB mortality. Kernel density was used to identify whether the clusters changed over time., Results: For the standard version, spatial risk clusters for 10, 30 and 50% of the exposed population were 4.9 (95% CI 2.6-9.4), 3.2 (95% CI: 2.1-5.7) and 3.2 (95% CI: 2.1-5.7), respectively. For the isotonic spatial statistics, the risk clusters for 10, 30 and 50% of the exposed population were 2.8 (95% CI: 1.5-5.1), 2.7 (95% CI: 1.6-4.4), 2.2 (95% CI: 1.4-3.9), respectively. All risk clusters were located in the eastern and northern regions of the municipality. Additionally, through Gi*, hotspot areas were identified in the eastern and western regions., Conclusions: There were important risk areas for tuberculosis mortality in the eastern and northern regions of the municipality. Risk clusters for tuberculosis deaths were observed in areas where TB mortality was supposedly a non-problem. The isotonic and Gi* statistics were more sensitive for the detection of clusters in areas with a low number of cases; however, their applicability in public health is still restricted.

Background: There is evidence that exposure to traffic-related air pollution is related to the incidence of and mortality associated with lung cancer. The aim of this study was to perform a spatial analysis, with a Bayesian approach, to test the hypothesis that high traffic density is associated with increased respiratory tract cancer incidence and mortality risk among individuals over 20 years of age residing in the city of São Paulo, Brazil., Methods: We employed data from two different databases: the São Paulo Municipal Population-Based Cancer Registry (2002-2011 cancer incidence data); and the Mortality Database of the São Paulo Municipal Health Department (2002-2013 cancer mortality data). The relationships between the number of cases of respiratory tract cancer in each area analyzed and the standardized covariates-traffic density and the Municipal Human Development Index (MHDI)-were evaluated with a Besag-York-Mollié ecological model with relative risks (RRs) estimates., Results: Per 1-unit standard-deviation increase in traffic density and in the MHDI, the RR for respiratory tract cancer incidence was 1.07 (95% CI: 1.02-1.13) and 1.25 (95% CI: 1.18-1.32), respectively, whereas the RR for mortality was 1.04 (95% CI: 0.99-1.09) and 1.23 (95% CI: 1.16-1.30), respectively., Conclusion: Our findings support the hypothesis that residing in areas with high traffic density is associated with increased respiratory tract cancer incidence and mortality risk in the city of São Paulo., (Copyright © 2018 Elsevier Ltd. All rights reserved.)