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Breast cancer (BC) is the most common neoplasm, and its global burden has become one of the most important factors jeopardizing the health of the world population, especially women. The aim of this study was to analyze mortality trends and the spatial distribution of BC in women in the capital and state of Sergipe, aiming to contribute to the implementation and improvement of strategies for the prevention and health promotion of women with BC. Trends were calculated using the Joinpoint Regression Program 5.0.2. Spatial analyses were performed using the empirical Bayesian model, thematic maps were created using QGIS 3.10.7 and Moran's I indices were calculated using TerraView 4.2.2. Between 1996 and 2022, 1384 and 3128 BC deaths were recorded in the capital and state of Sergipe, respectively. The mortality trend increased in the age groups of 45-75+ for the state of Sergipe, while in the capital, we observed stability in all age groups. The highest AAPC was 4.6213, with a 95 % confidence interval (2.16; 7.14). Univariate global Moran's I analysis indicated spatial autocorrelation during the study period. A direct relationship was found between mortality rates and the more economically developed regions.

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BACKGROUND: Dengue is a vector-borne viral infection caused by the dengue virus transmitted to humans primarily by Aedes aegypti. The year 2024 has been a historic year for dengue in Brazil, with the highest number of probable cases ever registered. Herein, we analyze the temporal trend and spatio-temporal dynamics of dengue cases in Brazil during the first nine epidemiological weeks (EW) of 2024. METHODS: This is an ecological study, including all probable cases of dengue in Brazil during the period, carried out in two steps: time series analysis to assess the temporal trend and spatial analysis to identify high-risk clusters. RESULTS: 1,345,801 probable cases of dengue were reported. The regions with the highest increasing trend were the Northeast with an average epidemiologic week percent change (AEPC) of 52.4 (95% CI: 45.5-59.7; p < 0.001) and the South with 35.9 (95% CI: 27.7-44.5; p < 0.001). There was a statistically significant increasing trend in all states, except Acre (AEPC = -4.1; 95% CI: -16.3-10; p = 0.55), Amapá (AEPC = 1.3; 95% CI: -16.2-22.3; p = 0.9) and Espírito Santo (AEPC = 8.9; 95% CI: -15.7-40.6; p = 0.5). The retrospective space-time analysis showed a cluster within the Northeast, Central-West and Southeast regions, with a radius of 515.3 km, in which 1,267 municipalities and 525,324 of the cases were concentrated (RR = 6.3; p < 0.001). Regarding the spatial variation of the temporal trend, 21 risk areas were found, all of them located in Southeast or Central-West states. The area with the highest relative risk was Minas Gerais state, where 5,748 cases were concentrated (RR = 8.1; p < 0.001). Finally, a purely spatial analysis revealed 25 clusters, the one with the highest relative risk being composed of two municipalities in Acre (RR = 6.9; p < 0.001). CONCLUSIONS: We described a detailed temporal-spatial analysis of dengue cases in the first EWs of 2024 in Brazil, which were mainly concentrated in the Southeast and Central-West regions. Overall, it is recommended that governments adopt public policies to control the the vector population in high-risk areas, as well as to prevent the spread of dengue fever to other areas of Brazil.

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Aedes , Dengue , Epidemias , Análisis Espacio-Temporal , Brasil/epidemiología , Dengue/epidemiología , Dengue/transmisión , Humanos , Epidemias/estadística & datos numéricos , Aedes/virología , Animales , Toma de Decisiones , Mosquitos Vectores/virología , Virus del Dengue

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During outbreaks of emerging infectious diseases, internationally connected cities often experience large and early outbreaks, while rural regions follow after some delay. This hierarchical structure of disease spread is influenced primarily by the multiscale structure of human mobility. However, during the COVID-19 epidemic, public health responses typically did not take into consideration the explicit spatial structure of human mobility when designing nonpharmaceutical interventions (NPIs). NPIs were applied primarily at national or regional scales. Here, we use weekly anonymized and aggregated human mobility data and spatially highly resolved data on COVID-19 cases at the municipality level in Mexico to investigate how behavioral changes in response to the pandemic have altered the spatial scales of transmission and interventions during its first wave (March-June 2020). We find that the epidemic dynamics in Mexico were initially driven by exports of COVID-19 cases from Mexico State and Mexico City, where early outbreaks occurred. The mobility network shifted after the implementation of interventions in late March 2020, and the mobility network communities became more disjointed while epidemics in these communities became increasingly synchronized. Our results provide dynamic insights into how to use network science and epidemiological modeling to inform the spatial scale at which interventions are most impactful in mitigating the spread of COVID-19 and infectious diseases in general.

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Sporotrichosis is a fungal anthropozoonosis that has become a major public health problem in tropical countries. With that in mind, this study analyzed the relationship between this disease and demographic, socioeconomic and public health issues in Belém, State of Pará, Brazil, from 2020 to 2022. This ecological and cross-sectional study used data from the Belém Zoonosis Control Center, the Brazilian Institute of Geography and Statistics and the Health Ministry. Descriptive and spatial analyses were performed employing significance statistical, kernel, buffer and Moran techniques. One hundred sporotrichosis cases in cats and 49 in humans were analyzed. The results showed that the individuals most affected were women (61.22 %), adults (87.76 %), with the cutaneous form (95.92 %), diagnosed histopathologically (38.78 %), still undergoing treatment (46.94 %) and that the form of contagion was through cat scratches or bites (73.47 %). The profile also showed quantitative significance of ignored data related to treatment (65.31 %) and cat presence at home (63.27 %). The disease had a non-homogeneous distribution with very high densities in Campina de Icoaraci, Águas Negras and Parque Guajará. Those neighborhoods presented a very low Living Conditions Index and precarious services and health centers. The spatial dependence between the environmental and socioeconomic studied variables evidenced the establishment of an active transmission circuit for sporotrichosis in peripheral areas of the city, related to health inequalities with an underlying possible epidemiological silence, suggesting the need for expanding One Health public policies, aiming the sustainable development.

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Factores Socioeconómicos , Esporotricosis , Esporotricosis/epidemiología , Brasil/epidemiología , Humanos , Estudios Transversales , Femenino , Gatos , Masculino , Animales , Adulto , Enfermedades de los Gatos/epidemiología , Enfermedades de los Gatos/microbiología , Persona de Mediana Edad , Zoonosis , Adolescente , Análisis Espacial , Adulto Joven , Niño

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Abstract This study examined the spatial distribution and social inequalities in COVID-19 vaccine coverage among children aged 5-11 in Brazil. First and second dose vaccine coverage was calculated for all Brazilian municipalities and analyzed by geographic region and deciles based on human development index (HDI-M) and expected years of schooling at 18 years of age. Multilevel models were used to determine the variance partition coefficient, and bivariate local Moran's I statistic was used to assess spatial association. Results showed significant differences in vaccine coverage rates among Brazilian municipalities, with lower coverage in the North and Midwest regions. Municipalities with lower HDI and expected years of schooling had consistently lower vaccine coverage rates. Bivariate clustering analysis identified extensive concentrations of municipalities in the Northern and Northeastern regions with low vaccine coverage and low human development, while some clusters of municipalities in the Southeast and South regions with low coverage were located in areas with high HDI-M. These findings highlight the persistent municipal-level inequalities in vaccine coverage among children in Brazil and the need for targeted interventions to improve vaccine access and coverage in underserved areas.

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Resumo O estudo analisou a distribuição espacial e as desigualdades sociais na cobertura vacinal para COVID-19 entre crianças de 5 a 11 anos no Brasil. As coberturas vacinais foram calculadas para os municípios brasileiros e analisadas por região geográfica e decis com base no Índice de Desenvolvimento Humano (IDH-M) e expectativa de escolaridade aos 18 anos. Modelos multiníveis foram usados ​​para determinar o coeficiente de partição da variância, e a estatística local bivariada de Moran I foi usada para avaliar a associação espacial. Os resultados mostraram diferenças significativas nas taxas de cobertura vacinal entre os municípios, com menor cobertura nas regiões Norte e Centro-Oeste. Municípios com menor IDH e anos de escolaridade esperados apresentaram menores taxas de cobertura vacinal. A análise de agrupamento bivariado identificou extensas concentrações de municípios nas regiões Norte e Nordeste com baixa cobertura vacinal e baixo desenvolvimento humano, enquanto alguns aglomerados de municípios nas regiões Sudeste e Sul com baixa cobertura localizavam-se em áreas com alto IDH-M. Essas descobertas destacam as desigualdades persistentes em nível municipal na cobertura vacinal entre crianças e a necessidade de intervenções para melhorar o acesso e a cobertura vacinal em áreas mais vulneráveis.

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Objectives: To examine the epidemiology of hospitalized cases of malaria in indigenous people living in the municipalities of Roraima in the northern Brazilian Amazon from 2008 to 2022. Methods: Ecological study using secondary data and spatiotemporal analyses based on thematic maps. Average rates were calculated per study period and spatiotemporal clusters were estimated from spatial statistics. Results: Of the 541 medical records, 77.08% were related to Plasmodium vivax. Higher rates were observed in municipalities in the south and center of the state. The rates increased throughout the study period. The analysis generated three clusters. Conclusions: Although Roraima has characteristics that worsen the malaria problem, no studies were found that examined the transmission of the disease in the state as a whole. This increases the importance of this study, which contributes to the discussion in the field of indigenous health.

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Introduction: According to the Instituto Brasileiro de Geografia e Estatística (Brazilian Institute of Geography and Statistics), 33% of Brazilian municipalities have faced problems with areas of contaminated soil. According to Companhia Ambiental do Estado de São Paulo (State of São Paulo Environmental Company), contaminated areas are places where there is demonstrably pollution or contamination. Objective: To identify the areas and municipalities affected by contamination at fuel service stations in the Centro de Referência em Saúde do Trabalhador (Occupational Health Reference Center) of Osasco region in 2017. Methods: Descriptive ecological study, carried out in the Occupational Health Reference Center of Osasco region. Data on contaminated areas were extracted from State of São Paulo Environmental Company and digital maps from Brazilian Institute of Geography and Statistics. Spatial analysis was carried out of the contamination areas, according to their classification, as well as artesian wells and service stations, using Geographic Information System tools. Results: The highest concentrations of contaminated areas with confirmed risk are found in the municipality of Osasco and headquarters of Occupational Health Reference Center. In the analysis of the Kernel Ratio, the most compromised municipalities were Osasco, Barueri and Taboão da Serra. Conclusions: Municipalities with contaminated areas with confirmed risk also have water extraction from artesian wells, with potential risk of contamination of this water by benzene. Thus, it is necessary to improve inspection and surveillance of areas with environmental liabilities, such as service stations that do not have remediation, in addition to surveillance of exposed workers.

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Introdução: De acordo com o Instituto Brasileiro de Geografia e Estatística, 33% dos municípios brasileiros têm enfrentado problemas com áreas de solo contaminado. Segundo a Companhia Ambiental do Estado de São Paulo, as áreas contaminadas são locais onde há poluição ou contaminação por substâncias ou resíduos. Objetivo: Identificar as áreas e os municípios afetados por contaminação em postos de serviços de combustível na região do Centro de Referência em Saúde do Trabalhador de Osasco, no estado de São Paulo, em 2017. Métodos: Tratou-se de um estudo descritivo ecológico, realizado na área do Centro de Referência em Saúde do Trabalhador de Osasco. Os dados de áreas contaminadas foram extraídos da Companhia Ambiental do Estado de São Paulo, e os mapas digitais, do Instituto Brasileiro de Geografia e Estatística. Foi realizada análise espacial das áreas de contaminação segundo a sua classificação, bem como de poços artesianos e postos de combustível, utilizando ferramentas de Sistemas de Informações Geográficas. Resultados: As maiores concentrações de áreas contaminadas com risco confirmado se encontram no município de Osasco, sede do Centro de Referência em Saúde do Trabalhador. Na análise da razão de Kernel, os municípios mais comprometidos foram Osasco, Barueri e Taboão da Serra. Conclusões: Os municípios com áreas contaminadas com risco confirmado possuem extração de água de poços artesianos, com potencial risco de contaminação dessa água por benzeno. Assim, é necessário melhorar a fiscalização e a vigilância das áreas com passivo ambiental, como postos de gasolina.

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BACKGROUND: More than 95% of malaria transmission in Brazil occurs in the Legal Amazon Region, which in 2010 recorded around 333,429 cases reported in the Epidemiological Surveillance Information System-Malaria (Sivep_malaria), presenting an annual parasitic incidence (IPA) of 13.1 cases/1000 inhabitants. METHODS: This was a descriptive study that measured the community prevalence of Plasmodium infection and its relationship with land use in Três Fronteiras District, Colniza Municipality, Mato Grosso State. Data were collected during household visits in July 2011, with blood collection from finger pricks for the preparation of thick smear slides, and completion of a standardized case notification form. A georeferenced database was analysed, with land use evaluated as categorical variables. A kernel density map was built to show the density of cases and their location. RESULTS: Of the 621 respondents, 68(11%) had Plasmodium infection: 39 (57.4%) with Plasmodium vivax, 27(39.7%) with Plasmodium falciparum and two (2.9%) with mixed infections. Among infected individuals, 49 (72.1%) were men. Cases of malaria were distributed over the district, with greater occurrence of cases per household in open areas close to the mining company and artisanal mining sites. The was a greater density of cases located in the gold mining region. CONCLUSION: Transmission of malaria in Três Fronteiras District has a heterogeneous distribution. Individuals residing in mining and timber extraction sites have increased occurrence of Plasmodium infection.

Asunto(s)

Malaria Falciparum , Malaria Vivax , Población Rural , Brasil/epidemiología , Humanos , Femenino , Masculino , Adolescente , Adulto , Población Rural/estadística & datos numéricos , Persona de Mediana Edad , Adulto Joven , Niño , Preescolar , Malaria Vivax/epidemiología , Malaria Vivax/parasitología , Malaria Falciparum/epidemiología , Malaria Falciparum/parasitología , Prevalencia , Lactante , Anciano , Incidencia , Anciano de 80 o más Años , Plasmodium vivax , Malaria/epidemiología , Malaria/transmisión

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Epidemiological studies to better understand wheat blast (WB) spatial and temporal patterns were conducted in three field environments in Bolivia between 2019 and 2020. The temporal dynamics of wheat leaf blast (WLB) and spike blast (WSB) were best described by the logistic model compared with the Gompertz and exponential models. The nonlinear logistic infection rates were higher under defined inoculation in experiments two and three than under undefined inoculation in experiment one, and they were also higher for WSB than for WLB. The onset of WLB began with a spatial clustering pattern according to autocorrelation analysis and Moran's index values, with higher severity and earlier onset for defined than for undefined inoculation until the last sampling time. The WSB onset did not start with a spatial clustering pattern; instead, it was detected later until the last sampling date across experiments, with higher severity and earlier onset for defined than for undefined inoculation. Maximum severity (Kmax) was 1.0 for WSB and less than 1.0 for WLB. Aggregation of WLB and WSB was higher for defined than for undefined inoculation. The directionality of hotspot development was similar for both WLB and WSB, mainly occurring concentrically for defined inoculation. Our results show no evidence of synchronized development but suggest a temporal and spatial progression of disease symptoms on wheat leaves and spikes. Thus, we recommend that monitoring and management of WB should be considered during early growth stages of wheat planted in areas of high risk.

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Enfermedades de las Plantas , Triticum , Triticum/microbiología , Triticum/crecimiento & desarrollo , Enfermedades de las Plantas/microbiología , Enfermedades de las Plantas/estadística & datos numéricos , Bolivia , Hojas de la Planta/microbiología , Análisis Espacio-Temporal

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OBJECTIVE: To assess the evolution of the COVID-19 pandemic in Brazil and its macro-regions, considering disease incidence and mortality rates, as well as identifying territories with still rising disease indices and evaluating vaccine coverage and population adherence to COVID-19 immunization. METHODS: An ecological study conducted in Brazil with COVID-19 cases and deaths reported between February 2020 and April 2024, obtained through the Coronavirus Panel. Historical series were constructed from incidence and mortality rates to assess the pandemic's evolution, and temporal trends were estimated using the Seasonal Trend Decomposition using Loess (STL) method. The Spatial Variation in Temporal Trends (SVTT) technique was employed to identify clusters with significant variations in temporal trends. Vaccination was analyzed considering the percentage of vaccinated and unvaccinated population in each municipality of the country. RESULTS: Brazil recorded a total of 38,795,966 cases and 712,038 deaths from COVID-19 during the study period. Incidence and mortality rates showed three waves of the disease, with a fourth wave of smaller amplitude. Four clusters with significant case growth and two with increased deaths were identified. Vaccine coverage varied among municipalities, with some regions showing low vaccination rates and others with high immunization adherence. CONCLUSION: The study provided a comprehensive overview of coronavirus behavior in Brazil, and its results highlight the ongoing importance of vaccination and the need to direct efforts and resources to areas of higher risk.

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Vacunas contra la COVID-19 , COVID-19 , SARS-CoV-2 , Cobertura de Vacunación , Humanos , COVID-19/prevención & control , COVID-19/epidemiología , COVID-19/mortalidad , Brasil/epidemiología , Cobertura de Vacunación/estadística & datos numéricos , Incidencia , Vacunas contra la COVID-19/administración & dosificación , Pandemias/prevención & control , Análisis Espacio-Temporal , Vacunación/estadística & datos numéricos

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To assess the temporal and spatial dynamics of chikungunya incidence and its association with social vulnerability indicators in Brazil, an ecological and population-based study was conducted herein, with confirmed cases of chikungunya and based on clinical and clinical-epidemiological criteria from 2017 to 2023. Data were obtained from the Notifiable Diseases Information System and social vulnerability indicators were extracted from the official platform of the United Nations Development Program and the Social Vulnerability Atlas. Temporal, spatial, and global spatial regression models were employed. The temporal trend showed that in 2017, the incidence increased by 1.9%, and this trend decreased from 2020 to 2021 (-0.93%). The spatial distribution showed heterogeneity and positive spatial autocorrelation (I: 0.71; p < 0.001) in chikungunya cases in Brazil. Also, the high-risk areas for the disease were concentrated in the northeast and north regions. The social vulnerability indicators associated with the outcome were those related to income, education, and housing conditions. Our analyses demonstrate that chikungunya continues to be a serious health concern in Brazil, but specially in the northeast and north regions. Lastly, mapping risk areas can provide evidence for the development of public health strategies and disease control in endemic regions.

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INTRODUCTION: This study sought to analyze the relationships between cutaneous leishmaniasis and its epidemiological, environmental and socioeconomic conditions, in the 22 microregions of Pará state, Brazil, for the period from 2017 to 2022. METHODOLOGY: In this ecological and exploratory study, the microregions were used as spatial units because they are formed by contiguous municipalities with similar characteristics. The epidemiological, environmental, socioeconomic, and public health policy data employed were obtained from the official information systems at the Ministry of Health, National Institute for Space Research, and Brazilian Institute of Geography and Statistics. A fuzzy system was developed to identify risk factors for the disease, using Python programming language. The results were analyzed with the bivariate Global Moran spatial analysis technique. RESULTS: It was observed that the Altamira microregion had the highest risk percentage for the disease, while Breves had the lowest, with significant differences in the relevance of its conditioning factors, mainly related to land use and cover patterns, in addition to demography and living conditions index, education and public health policies. CONCLUSIONS: The fuzzy system associated with the geostatistical technique was satisfactory for identifying areas with health vulnerability gradients related to deforestation, pasture, poverty, illiteracy, and health services coverage, as its conditioning variables. Thus, it was demonstrated that deforestation was the main risk factor for the disease. The system can also be used in environmental and epidemiological surveillance.

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Lógica Difusa , Leishmaniasis Cutánea , Factores Socioeconómicos , Análisis Espacial , Brasil/epidemiología , Humanos , Leishmaniasis Cutánea/epidemiología , Factores de Riesgo

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BACKGROUND: Leprosy, a neglected tropical disease, is reported in over 120 countries, with upwards of 200,000 new cases annually. This Cross-Sectional Cohort Study aimed to delineate the epidemiological profile of leprosy in a low-endemic area in southern Brazil, both before and after implementing an active search strategy. METHODS: The study examined two surveillance periods in Caçador, Santa Catarina, Brazil. The active search strategy was carried out through the application of the LSQ by the community health workers as a screening and detection tool for new cases of leprosy and this was compared with passive case detection. The first spanned from 2014 to 2020, and the second from January 2021 to August 2023. FINDINGS: 48 leprosy cases were reported throughout the study, 83.3 % of which were diagnosed as multibacillary. The first period had an average detection rate of 0.38 cases per 10,000 inhabitants, increasing to 1.19 cases per 10,000 inhabitants in the second period. Notably, there was a substantial shift in the degree of physical disability (GD), with more Grade 0 and Grade 1 disabilities observed post-active search. MAIN CONCLUSIONS: The study underscores the efficacy of active search strategies in early diagnosis, highlighting a 300 % increase in the annual average of diagnosed cases. This large number of detected cases demonstrates the high sensitivity of the LSQ. This approach significantly aids in uncovering hidden cases of leprosy, enhancing disease management and control in low-endemic areas indicating that the Ministry of Health should intensify leprosy control activities in these regions.

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Enfermedades Endémicas , Lepra , Humanos , Brasil/epidemiología , Estudios Transversales , Masculino , Femenino , Enfermedades Endémicas/estadística & datos numéricos , Adulto , Lepra/epidemiología , Lepra/diagnóstico , Persona de Mediana Edad , Adulto Joven , Adolescente , Estudios de Cohortes , Anciano , Diagnóstico Precoz , Tamizaje Masivo

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Background: COVID-19 has led to significant global mortality, with Peru being among the countries most affected. While pre-existing comorbidities have been linked to most cases, the exact distribution of fatalities within the country remains unclear. We aimed to assess deaths attributed to cardiovascular diseases (CVD) before and during the COVID-19 pandemic across various regions and provinces in Peru. Methods: An observational georeferencing study was designed. Peru faced four waves of COVID-19 over three years, with variable impacts across its three regions (Coast, Highlands, and Jungle). Deaths related to cardiovascular diseases, such as heart failure (HF), arrhythmia, acute myocardial infarction (AMI), strokes, and acute coronary syndrome, were examined as primary variables. The study period spanned pre-pandemic years (2017-2019) and pandemic years (2020-2021), utilizing death data from the National Death Information System (SINADEF). The georeferencing analysis was conducted using ArcGIS v10.3. Results: A total of 28,197 deaths were recorded during the study period, with significant increases during the pandemic (2020-2021). Cardiovascular deaths were disproportionately higher during the pandemic, totaling 19,376 compared to 8,821 in the pre-pandemic period (p < 0.001). AMI and HF were the leading causes of mortality, showing significant increases from the pre-pandemic (5,573 and 2,584 deaths) to the pandemic period (12,579 and 5,628 deaths), respectively. Deaths due to CVD predominantly affected individuals aged over 60, with significant increases between the two study periods (7,245 vs. 16,497 deaths, p = 0.002). Geospatial analysis revealed regional disparities in CVD mortality, highlighting provinces like Lima and Callao as COVID-19 critical areas. The substantial increase in cardiovascular deaths during the COVID-19 pandemic in Peru showed distinctive patterns across regions and provinces. Conclusions: Geospatial analysis identified higher-risk areas and can guide specific interventions to mitigate the impact of future health crises. Understanding the dynamic relationship between pandemics and cardiovascular health is crucial for effective public health strategies.

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OBJECTIVES: The aim of this study was to analyse the spatial patterns and factors associated with the incidence of tuberculosis-diabetes (TB-DM) in Brazil, from 2001 to 2019. STUDY DESIGN: Ecological study. METHODS: Brazilian municipalities were used as the units of analysis. The local empirical Bayesian rate and the spatial autocorrelation test were calculated. Moran and Getis-Ord Gi∗ were used to identify spatial clusters, and spatially weighted regression was conducted. RESULTS: In total, 75,021 new cases of TB associated with DM were reported in Brazil during the study period. Most Brazilian municipalities had an average TB-DM incidence of 1.0-2.0/100,000 inhabitants. The regression showed that the Gini index (ß = 0.85) and family health strategy coverage (ß = -0.26) were the two indicators that had the most influence on TB-DM incidence in Brazil. CONCLUSIONS: This study identified spatial clusters of TB-DM in Brazil. The results also indicated that social inequalities played a key role in the incidence of TB.

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Diabetes Mellitus , Análisis Espacial , Tuberculosis , Humanos , Brasil/epidemiología , Incidencia , Tuberculosis/epidemiología , Diabetes Mellitus/epidemiología , Factores Socioeconómicos , Teorema de Bayes , Factores de Riesgo , Masculino , Femenino

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Understanding the distribution of tegumentary leishmaniasis (TL) in different periods enables the adequate conduction of actions at the public health level. The present study analyzes the spatiotemporal evolution of TL incidence rates in the municipalities of Brazil and identifies priority areas from 2001 to 2020. Notifications of new cases were analyzed employing space-time scan statistics and Local Indicators of Spatial Association. As TL incidence rates presented a downward trend in most Brazilian municipalities, spatiotemporal clusters of high relative risks (RR) were more frequent in the first decade of the series. There was a concentration of those clusters in the North and Northeast regions, mainly in the Legal Amazon area. More recent high-RR areas were identified in municipalities of different regions. The number of priority municipalities showed a stable trend in Brazil. There was a great concentration of such municipalities in the states of Acre, Mato Grosso, Rondônia, Pará, and Amapá, as well as large areas in Roraima, Amazonas, Maranhão, and Tocantins, and smaller areas in the states of Goiás, Ceará, Bahia, Minas Gerais, São Paulo, and Paraná. The present study contributes to the understanding of the historical evolution of TL in Brazil and subsidizes actions to combat the disease.

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Leishmaniasis Cutánea , Análisis Espacio-Temporal , Brasil/epidemiología , Humanos , Incidencia , Leishmaniasis Cutánea/epidemiología , Ciudades/epidemiología

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Drought is considered the most severe water-related disaster in the Cauto river basin, which is the longest river and the main agricultural producer in Cuba. Better understanding of drought characteristics is crucial to drought management. Given the sparsity of ground-based precipitation observations in the Cauto, this study aims at using gridded global precipitation to analyze the spatio-temporal variations of drought in this river basin. Firstly, the monthly Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) was calibrated with the gauged precipitation using the Thiessen polygon-based method and linear least squares regression equations. Then, the gridded standardized precipitation index (SPI) with time scales of 3, 6, 9 months and drought characteristics, namely, drought frequency, duration and intensity were calculated using the calibrated CHIRPS. Finally, the spatio-temporal analysis was performed to investigate the variations of drought in the Cauto river basin in time and space. The obtained results show that the calibrated CHIRPS is highly consistent with the gauged observations and is capable of determining the magnitude, time, and spatial extent of drought events in the Cauto river basin. The trend analysis by the Mann-Kendall test reveals that although the trend is not statistically significant, the SPI tends to decrease with time in the dry season, which indicates the more severe drought. The spatial analysis indicates that the lower altitude area of the Cauto river basin is suffered from longer drought duration and higher drought intensity than the upper one. This study expresses the importance of open global precipitation data sources in monitoring and quantifying drought characteristics in data-scarce regions.

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Data on the temporal and spatial evolution of SARS-CoV-2 and local control measures and their effects on morbidity and mortality patterns in rural Brazil are scarce. We analyzed the data from case notification systems, epidemiological investigation reports, and municipal decrees in Itapajé, a small municipality in Ceará State in northeast Brazil. For spatial and spatio-temporal analyses, cases and deaths were mapped. There were a total of 3020 cases of COVID-19, recorded between April 2020 and December 2021; 135 (4.5%) died. The cumulative incidence and mortality rates were 5650.3 cases and 252.6 deaths per 100,000 people, respectively. The index case of SARS-CoV-2 in Itapajé was diagnosed in March 2020. The first peak of cases and deaths occurred in May 2020. The second wave peaked in May 2021, with the highest number of deaths in March 2021. According to the spatial analysis, the highest density of cases and deaths occurred in the central urban areas. In these areas, there were also the clusters of highest risk according to the spatio-temporal analyses. The municipal government issued 69 decrees on restriction measures, surveillance, and the maintenance of social isolation as a response to the pandemic. The spread of the SARS-CoV-2 pandemic in Itapajé mirrored the dynamics in large metropolitan regions, going from central neighborhoods of low socio-economic status to the wealthier peripheries.

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Brazil reported 18,282 suspected congenital Zika syndrome (CZS) cases up to 2018 and accounts for 61.4% of the total reported Zika cases in the Americas in the period. To detect high-risk areas for children with CZS in the city of Rio de Janeiro, we used cluster detection and thematic maps. We analyzed data using a Poisson model in Satscan 10.1.3 software. We also analyzed the records of children with CZS from 2015 to 2016 to describe the clinical and epidemiological maternal and child profile, as well as live births in 2016 and the social development index (SDI) by neighborhood. In 2015 and 2016, the incidence rates of CZS were 8.84 and 46.96 per 100,000 live births in the city, respectively. Severe congenital findings such as microcephaly and brain damage, osteoarticular impairment, ocular abnormalities, and hearing loss were observed in 47 children. The spatial distribution of CZS was concentrated in the north and west zones in heterogeneous neighborhoods. The neighborhoods with the highest occurrence of CZS cases were found to have the worst SDIs. Stascan detected three spatial clusters in the north zone, where the SDI is lower. The clusters presented high relative risks for CZS (7.86, 1.46, and 2.08), although they were not statistically significant. Our findings highlight a higher occurrence of CZS in areas with less favorable socioeconomic conditions.

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Visceral leishmaniasis is a zoonotic disease that affects humans and dogs. The infection is endemic in the municipality of Araçatuba, São Paulo, Brazil. Given the role of dogs in the epidemiology of leishmaniasis, strategies to enhance surveillance and reduce transmission are focused on dogs. In this study, we retrospectively analyzed records of canine visceral leishmaniasis from 2013 to 2022. According to this database, the prevalence of dogs testing positive for leishmaniasis fluctuated, with an average of 65.04% (6590/10,133). Cases were clustered in 10 statistically significant areas. Environmental analyses identified a significant geographical association between animals testing positive and higher vegetation density rates compared with animals testing negative. The period from sample collection to diagnosis and euthanasia, as recommended by the Brazilian Ministry, correlated with disease prevalence and decreased over time. These findings serve to implement different action plans against leishmaniasis for each geographic region and to understand the impact and efforts of strategies in an endemic area.