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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.
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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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.
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Malária Falciparum , Malária Vivax , População Rural , Brasil/epidemiologia , Humanos , Feminino , Masculino , Adolescente , Adulto , População Rural/estatística & dados numéricos , Pessoa de Meia-Idade , Adulto Jovem , Criança , Pré-Escolar , Malária Vivax/epidemiologia , Malária Vivax/parasitologia , Malária Falciparum/epidemiologia , Malária Falciparum/parasitologia , Prevalência , Lactente , Idoso , Incidência , Idoso de 80 Anos ou mais , Plasmodium vivax , Malária/epidemiologia , Malária/transmissãoRESUMO
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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Doenças Endêmicas , Hanseníase , Humanos , Brasil/epidemiologia , Estudos Transversais , Masculino , Feminino , Doenças Endêmicas/estatística & dados numéricos , Adulto , Hanseníase/epidemiologia , Hanseníase/diagnóstico , Pessoa de Meia-Idade , Adulto Jovem , Adolescente , Estudos de Coortes , Idoso , Diagnóstico Precoce , Programas de RastreamentoRESUMO
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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Vacinas contra COVID-19 , COVID-19 , SARS-CoV-2 , Cobertura Vacinal , Humanos , COVID-19/prevenção & controle , COVID-19/epidemiologia , COVID-19/mortalidade , Brasil/epidemiologia , Cobertura Vacinal/estatística & dados numéricos , Incidência , Vacinas contra COVID-19/administração & dosagem , Pandemias/prevenção & controle , Análise Espaço-Temporal , Vacinação/estatística & dados numéricosRESUMO
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 Fuzzy , Leishmaniose Cutânea , Fatores Socioeconômicos , Análise Espacial , Brasil/epidemiologia , Humanos , Leishmaniose Cutânea/epidemiologia , Fatores de RiscoRESUMO
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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Leishmaniose Cutânea , Análise Espaço-Temporal , Brasil/epidemiologia , Humanos , Incidência , Leishmaniose Cutânea/epidemiologia , Cidades/epidemiologiaRESUMO
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.