Search

Estima-se que cerca de 2% a 5% dos nascidos vivos no mundo apresentam algum tipo de malformação detectada no nascimento. As maiores prevalências de malformação congênita no Brasil estão na Bahia, Distrito Federal, Alagoas, Pernambuco, Ceará, Tocantins e Sergipe. Malformações congênitas podem ser decorrentes de diversos fatores, inclusive ambientais. Para uma compreensão mais adequada da distribuição deste evento no país, deve-se considerar a complexidade e a heterogeneidade de manifestações socioeconômicas observadas na extensão do território. Neste contexto, este estudo tem como objetivo caracterizar a distribuição das taxas de malformações congênitas segundo as tipologias de espaços rurais e urbanos no Brasil, definidas pelo Instituto Brasileiro de Geografia e Estatística (IBGE). Para tanto, utilizou-se dados secundários de malformações congênitas e o número de nascidos vivos por município de residência da mãe de 2012 a 2017 disponibilizados pelo Ministério da Saúde (MS). Verificou-se a concentração de altas prevalências de malformações congênitas em municípios rurais sugere a necessidade de estudos que identifiquem fatores que tenham de alguma forma contribuído para as malformações congênitas, bem como que caracterizem o acesso dessas populações aos serviços de saúde, para melhor adequar as políticas públicas vigentes às necessidades de saúde dessas populações.

Climate Change has increased population exposure to more frequent, more intense, and longer heat waves (HWs) worldwide. South America and particularly Brazil is highly vulnerable to rising temperatures, with limited adaptation resources and a growing and aging urban population. However still lacks research on the direct and indirect impacts of extreme heat on health in these regions, in particular on the role of social and demographic factors, as well as regional disparities in heat-related mortality. This work presents a comprehensive analysis of the occurrence of HW in the 14 most populous metropolitan regions (MRs) in Brazil, comprising circa 35% of the country's population, based on the Excess Heat Factor index. The impact of HWs on mortality was accessed employing the ratio between observed and expected deaths (O/E), which reveals a burden of 48,075 excess heat-related excess deaths over the 2000–2018 period, in line with the recent and significant increase observed in the annual number of days under extreme heat. Diseases of the circulatory and respiratory systems and neoplasms are the dominant causes of death (COD), although other COD little explored in the literature have also presented large O/E values in some MRs, such as diseases of the skin, nervous and genitourinary system, and mental and behavioral disorders. In addition, the vulnerability population profile was investigated considering the splits in terms of gender, age, race, and educational level subgroups. Overall, females, older, low-educational level, and black/brown are the most sensitive groups in most MRs, with significantly larger O/E values. Nonetheless, significant regional disparities were observed, mainly due to North-South socio-economic inequalities existing in Brazil, and differences in health indicators between these regions, such as life expectancy. Our findings are expected to guide the implementation of public mitigation and adaptation strategies in some of the most populated regions of South America.This work was supported by FIOCRUZ [grant VPPCB-003-FIO-19] and FAPERJ [grant E26/202.714/2019]. D.M.S. was supported by FIOCRUZ [grant VPPCB-003-FIO-19].

Brazil has been severely impacted by COVID-19 pandemics that is aggravated by the absence of a scientifically-driven coordinated informative campaign and the interference in public health management, which ultimately affected health measures to avoid SARS-CoV2 spread. The decentralization and resultant conflicts in disease control activities produced different protection behaviours and local government measures. In the present study, we investigated how political partisanship and socio-economic factors determined the outcome of COVID-19 at the local level in Brazil.A retrospective study of COVID-19 deaths was carried out using mortality databases between Feb 2020, and Jun 2021 for the 5570 Brazilian municipalities. Socio-economic parameters including city categories, income and inequality indexes, health service quality and partisanship, assessed by the result of the second round of the 2018 Brazilian presidential elections, were included. Regression tree analysis was carried out to identify the statistical significance and conditioning relationships of variables.Municipalities that supported then-candidate Jair Bolsonaro in the 2018 elections were those that had the worst COVID-19 mortality rates, mainly during the second epidemic wave of 2021. This pattern was observed even considering structural inequalities among cities.In general, the first phase of the pandemic hit large and central cities hardest, while the second wave mostly impacted Bolsonarian municipalities, where scientific denialism among the population was stronger. Negative effects of partisanship towards the right-wing on COVID-19 outcomes counterbalances favourable socioeconomic indexes in affluent Brazilian cities. Our results underscore the fragility of public health policies which were undermined by the scientific denialism of right-wing supporters in Brazil.International joint laboratories of

The research aims to describe the temporal-spatial dynamics of deaths from esophageal cancer in the southern region of Brazil, from sex and age group, during the years 2007 to 2017, according to municipalities of residence. The research is a descriptive study, with a quantitative methodological approach. The annual temporal distribution of cases is continuous and the spatial distribution of mortality rates is concentrated in the mesoregions of the Northwest Rio-Grandense, Metropolitan Region of Porto Alegre and Centro Oriental Rio-Grandense for both sexes. Due to the higher male mortality, following the world and Brazilian trend, the mesoregions of the Northeast Rio-Grandense, Southwest Paranaense, North Central Paranaense and Western Catarinense present concentrations for this sex. Female deaths are concentrated in the 75-79 year age group and in the male deaths in the 60-64 year age group in Rio Grande do Sul. In Paraná and Santa Catarina, the peak of women's deaths is in the 65-69 age group and the of men is at 60-64 years old. This research updates the epidemiological profile of the region, which, when mentioned, did not go beyond the regional analysis, so it also deepens it. A pesquisa tem por objetivo descrever a dinâmica espaço-temporal dos óbitos por câncer de esôfago na região Sul do Brasil, a partir de sexo e faixa etária, durante os anos de 2007 a 2017, e segundo municípios de residência. A pesquisa trata-se de um estudo descritivo, de abordagem metodológica quantitativa. A distribuição temporal anual de casos é contínua e a distribuição espacial de taxas de mortalidade é concentrada nas mesorregiões do Noroeste Rio-Grandense, Região Metropolitana de Porto Alegre e Centro Oriental Rio-Grandense para ambos os sexos. A maior mortalidade é masculina, seguindo a tendência mundial e brasileira. Se concentram na faixa etária dos 75-79 anos os óbitos femininos e aos 60-64 anos os masculinos no Rio Grande do Sul. No Paraná e em Santa Catarina, o ápice de óbitos de mulheres é na faixa dos 65-69 anos e o dos homens é aos 60-64 anos. Esta pesquisa atualiza o perfil epidemiológico da região.

Contexto: a geografia da saúde é uma área de pesquisa que se torna cada dia mais importante, especialmente no Brasil onde a presença de um sistema único de saúde é tema de muitas pesquisas. De modo a conhecer a abrangência do ensino de Geografia e Saúde nos cursos de geografia, foi realizado um estudo para avaliar a disponibilidade de disciplinas sobre essa temática nas universidades públicas brasileiras. Para tal, foi elaborado e enviado aos coordenadores dos cursos de geografia um questionário online e foi realizada entrevistas abertas com professores da área da saúde sobre a utilização da geografia em suas aulas. Resultados: apenas cerca de um terço dos cursos possuem uma disciplina na temática de geografia da saúde, e elas tendem a ser de caráter optativo e não possuir oferta frequente. Além disso, professores da área de saúde afirmaram que utilizam técnicas e saberes de geografia da saúde, mas não conheciam essa temática de pesquisa, pelo menos não por esse nome. Conclusões: apensar do aumento de estudos nessa temática ainda há uma importante lacuna no ensino da geografia da saúde no Brasil, provavelmente devido abaixa institucionalização e divulgação dessa temática. Portanto, recomenda-se um esforço na divulgação e institucionalização dessa temática a partir da oferta de disciplinas e ações de interação da geográfica com cursos da área da saúde.

A Poliomielite foi eliminada no Brasil, desde a década de 90, atribuído ao sucesso das campanhas de vacinação no país, tendo o último caso registrado em 1989. Porém uma baixa cobertura vacinal é um dos fatores de alerta, para a volta da circulação do vírus selvagem no país e das sequelas permanentes provocadas pelo vírus, exigindo assim um monitoramento contínuo no território. Este trabalho teve como objetivo analisar a distribuição espacial da cobertura vacinal (CV) da poliomielite na região Nordeste do Brasil em 2020 quanto a meta de CV ≥ 95%. Os dados públicos do indicador da Taxa de CV foram obtidos do Sistema de Informação do Programa Nacional de Imunizações no site do DATASUS. Os resultados até o momento da extração mostram a Região Nordeste com cobertura de 71,8% inferior à meta, sendo a menor taxa de CV registrada, no estado do Maranhão (60,1%) e a maior, no Ceará (86,9%). O Estado do Maranhão, também apresentou um maior número de municípios em situação crítica (23,5%),) com cobertura vacinal ≤ 50%. Os dados espaciais mostram uma tendencia de agrupamento de municípios com alta cobertura vacinal em alguns estados da região, porém não altera a conclusão de que em 2020 a população menor de um ano esteve em situação de vulnerabilidade quanto a reintrodução do vírus selvagem na maior parte dos municípios dos estados dessa região e nos demais estados brasileiros.

No Brasil em 2015, foi constatada uma disseminação do vírus Zika, acompanhado do aumento de relatos de casos de recém-nascidos com microcefalia e outros distúrbios neurológicos causadas pelo vírus, levantando o debate sobre as dificuldades de acesso aos cuidados de crianças acometidas por infecções intrauterinas, denominadas Síndrome Congênita da Zika e STORCH. As repercussões na saúde infantil se espalharam por todas as regiões brasileiras, sendo as regiões Nordeste e Sudeste do Brasil as mais atingidas, desafiando-nos a compreender o acesso aos cuidados em saúde dessas crianças. O objetivo deste artigo é caracterizar o acesso e a mobilidade aos serviços de saúde e às atividades de estimulação precoce por crianças com Síndrome Congênita por Zika e STORCH, no Distrito Federal – Brasil. A metodologia consistiu no mapeamento dos casos de Síndrome Congênita por Zika e STORCH e das unidades de reabilitação e estimulação precoce, no período entre 2015 e 2017. Como resultado, verificou-se que as crianças com Síndrome Congênita, usuárias do serviço público de saúde, necessitam percorrer longas distâncias para ter acesso às unidades de reabilitação e estimulação precoce em unidades de saúde, enquanto para as unidades de educação, o deslocamento realizado é menor. No geral, nossos resultados evidenciam a dificuldade de execução de políticas de saúde para a estimulação precoce e o importante papel desempenhado pela educação nas atividades de educação precoce no Distrito Federal – Brasil.

Timely and accurate forecasts of dengue cases are of great importance for guiding disease prevention strategies, but still face challenges from (1) time-effectiveness due to time-consuming satellite data downloading and processing, (2) weak spatial representation capability due to data dependence on administrative unit-based statistics or weather station-based observations, and (3) stagnant accuracy without the application of historical case information. Geospatial big data, cloud computing platforms (e.g., Google Earth Engine, GEE), and emerging deep learning algorithms (e.g., long short term memory, LSTM) provide new opportunities for advancing these efforts. Here, we focused on the dengue epidemics in the urban agglomeration of the Federal District of Brazil (FDB) during 2007–2019. A new framework was proposed using geospatial big data analysis in the Google Earth Engine (GEE) platform and long short term memory (LSTM) modeling for dengue case forecasts over an epidemiological week basis. We first defined a buffer zone around an impervious area as the main area of dengue transmission by considering the impervious area as a human-dominated area and used the maximum distance of the flight range of Aedes aegypti and Aedes albopictus as a buffer distance. Those zones were used as units for further attribution analyses of dengue epidemics by aggregating the pixel values into the zones. The near weekly composite of potential driving factors was generated in GEE using the epidemiological weeks during 2007–2019, from the relevant geospatial data with daily or sub-daily temporal resolution. A multi-step-ahead LSTM model was used, and the time-differenced natural log-transformed dengue cases were used as outcomes. Two modeling scenarios (with and without historical dengue cases) were set to examine the potential of historical information on dengue forecasts. The results indicate that the performance was better when historical dengue cases were used and the 5-weeks-ahead forecast had the best performance, and the peak of a large outbreak in 2019 was accurately forecasted. The proposed framework in this study suggests the potential of the GEE platform, the LSTM algorithm, as well as historical information for dengue risk forecasting, which can easily be extensively applied to other regions or globally for timely and practical dengue forecasts.

Empirical studies of urban expansion have increased rapidly in recent decades worldwide. Previous studies mainly focused on cities in China, the United States or African countries, with Brazilian cities receiving less attention. Moreover, such studies are rare in purpose-built cities. Taking the urban expansion from scratch (1960) to urban agglomeration (2015) in the Federal District of Brazil (FDB) as an example, this study aims to quantify the magnitude, patterns, modes, types and efficiency of urban land expansion and attempts to reveal some implications within sustainable urban expansion thinking. Annual expansion, landscape metrics, local Moran’s I index, area weighted mean expansion index, and land-use efficiency were computed. The suitability of diffusion–coalescence theory and the impact of population growth and urban development policies on urban expansion were discussed. Urban land continuously expanded and became more fragmented during 1960–2015, which mainly occurred in SSW and WSW directions. Urban land evolved in a polycentric way. Edge expansion was identified as the stable contributor, and the importance of infilling and spontaneous growth alternated. Urban expansion in this region supported the diffusion–coalescence theory. Population growth promoted urban expansion, and the creation of peripheral urban nuclei and their development were associated with the urban expansion and the changes in urban land structure. This study adds new empirical evidence of urban expansion to Brazil urbanization, and compact urbanization, population control, and efficient urban land use should be considered in the future.

The specific characteristics of the Federal District (DF) favor the introduction, reproduction, dissemination, and permanence of dengue vector and viruses. Here, we aimed to analyze the spatiotemporal patterns of dengue epidemics in the Administrative Regions (RAs) of the DF from January 2007 to December 2017. We used Fourier partial series model to obtain a seasonal signature of the time series, which allowed calculating indicators of permanence (number of epidemic years, number of epidemic months per year, the proportion of epidemic months for the period) and time/moment of epidemics (month of epidemic peak). A total of 82 epidemics were recorded in this period. The RAs with the largest number of epidemic years were Varjão (5 epidemics), Gama, Lago Sul, and Sobradinho (4 epidemics). These last three RAs also had the highest proportions of epidemic months of the entire study period (9 epidemic months). The RAs with urban centrality function had an earlier epidemic peak than the others, in February and March. Epidemics showed high permanence values in RAs with different types of occupations, emphasizing the need to consider the social organization of space processes in dengue distribution studies.

A distribuição dos mosquitos vetores da malária é controlada por vários fatores, como clima, tipos de cobertura do solo ou uso da terra, ou atividades humanas. Na região amazônica, persistem focos endêmicos de malária, particularmente na fronteira entre a Guiana Francesa e o Estado do Amapá no Brasil. Esta área, com mais de 300 km de extensão, apresenta muitas dificuldades na coleta de informações necessárias para a gestão da saúde das populações presentes. Neste tipo de contexto geográfico com poucos dados isolados e transfronteiriços, uma metodologia baseada na exploração de imagens de sensoriamento remoto é particularmente apropriada. Dados de sensoriamento remoto têm ampla cobertura espacial e uma grande variedade de resoluções espaciais. Aqui nós apresentamos uma abordagem combinando alta resolução e alta resolução espacial e dados de satélite óptico e RADAR. Nosso método possibilita mapear os diferentes tipos de cobertura do solo no contexto das fronteiras tropicais da Guiana Francesa - Brasil, caracterizado por um forte aproveitamento. Os resultados mostram que a complementaridade dos sensores ópticos e RADAR possibilita resolver, em grande parte, a questão da persistente nebulosidade. As classificações dos vários cobertura do solo obtidos permitem construir indicadores espacializados em relação aos espaços favoráveis à existência de criadouros e áreas de descanso do vetor da malária. Através de uma discussão sobre a aplicação de classificações da cobertura do solo compostas para a avaliação do risco de exposição à malária em várias escalas, este estudo de caso ilustra o interesse das abordagens de sensoriamento remoto por satélite para caracterizar os elementos da paisagem e a cobertura da terra, o que pode explicar a distribuição das populações de vetores em conexão com a transmissão de arbovírus. The distribution of mosquito vectors of malaria is controlled by various factors such as climate, land cover and land use, or human activities. In the Amazon region, endemic foci of malaria persist, particularly on the border between French Guiana and Amapa State in Brazil. This area, long by 300 km, presents many difficulties in collecting informations necessary for the health management of the local populations. In this type of geographical context, with few, isolated and cross-border data, a methodology based on the exploitation of remote sensing images is particularly appropriate. Remote sensing data have wide spatial coverage, and a large range of spatial resolutions. Here we present an approach combining high resolution and very high spatial resolution optical and SAR satellite data. Our method makes it possible to map the different types of land cover in the tropical border context French Guiana - Brazil, characterized by a persistent cloud cover. The results show that the complementarity of optical and RADAR sensors allows the production of multi-scale mapping of land use/land cover (LULC) independently from cloud cover. In particular, we produced LULC classifications to generate spatialized indicators and characterize the relationship between suitable habitats for malaria vectors and environmental factors. Through a discussion on the application of composite LULC classifications for the assessment of malaria exposure risk at various scales, this case study illustrates the interest of satellite remote sensing approaches to characterize landscape elements and land cover, which can account for the distribution of vector populations in connection with arboviruses transmission. La distribution des moustiques vecteurs du paludisme est contrôlée par divers facteurs comme le climat, les types d’occupation du sol, ou les activités humaines. Dans la région amazonienne, des foyers endémiques de paludisme subsistent, notamment à la frontière entre la Guyane française et l’état d’Amapa au Brésil. Cette zone, longue de plus de 300 km, présente de nombreuses difficultés dans la collecte des informations nécessaires à la gestion sanitaire des populations présentes. Dans ce type de contexte géographique bénéficiant de peu de données, isolé et transfrontalier, une méthodologie fondée sur l’exploitation d’images de télédétection est particulièrement adaptée. Les données de télédétection présentent une large couverture spatiale, et une gamme importante de résolutions spatiales. Nous présentons ici une approche combinant des données satellite optiques et RADAR à haute et très haute résolution spatiale. Notre méthode permet de cartographier les différents types d’occupation du sol dans le contexte tropical frontalier Guyane française – Brésil, caractérisé par un fort ennuagement. Les résultats montrent que la complémentarité des capteurs optiques et RADAR permet de résoudre en grande partie la question de l’ennuagement persistant. En particulier, les classifications des différentes occupations du sol obtenues permettent de construire des indicateurs spatialisés en lien avec les espaces favorables à l’existence de gîtes larvaires et de zones de repos du vecteur du paludisme. A travers une discussion sur l’application de ces classifications composites à l’estimation du risque d’exposition vectoriel considéré à différentes échelles, ce cas d’étude illustre l'intérêt d’approches de télédétection satellite pour caractériser des éléments du paysage et l’occupation des sols, susceptibles de rendre compte de la distribution des populations vectorielles en lien avec la transmission d’arbovirus.

The prevention and control of mosquito-borne diseases, such as malaria, are important health issues in tropical areas. Malaria transmission is a multi-scale process strongly controlled by environmental factors, and the use of remote-sensing data is suitable for the characterization of its spatial and temporal dynamics. Synthetic aperture radar (SAR) is well-adapted to tropical areas, since it is capable of imaging independent of light and weather conditions. In this study, we highlight the contribution of SAR sensors in the assessment of the relationship between vectors, malaria and the environment in the Amazon region. More specifically, we focus on the SAR-based characterization of potential breeding sites of mosquito larvae, such as man-made water collections and natural wetlands, providing guidelines for the use of SAR capabilities and techniques in order to optimize vector control and malaria surveillance. In light of these guidelines, we propose a framework for the production of spatialized indicators and malaria risk maps based on the combination of SAR, entomological and epidemiological data to support malaria risk prevention and control actions in the field.

International audience; Cet article présente l'intérêt et la méthodologie de construction d'un site sentinelle sur la zone transfrontalière entre la Guyane française et l'Amapá (Brésil), pour la caractérisation et le suivi de l'impact des processus environnementaux, climatiques et socio-démographiques sur le paludisme. Nous présentons et discutons les concepts de site sentinelle et d'observatoire et nous décrivons les principaux dispositifs existants. Nous détaillons et justifions les choix nécessaires à la construction d'un tel site sentinelle, et décrivons les résultats préliminaires, à savoir les premières cartes sur la situation épidémiologique dans la zone transfrontalière, la première caractérisation du risque entomologique du côté brésilien, et la mise en oeuvre d'un portail internet dédié à la diffusion des données de base et des indicateurs de risque.Mots-clés : Changement climatique, paludisme, frontières internationales, systèmes d'informations. Este artigo apresenta o interesse ea metodologia de construção de um sítio sentinela na fronteira Guiana Francesa-Amapá (Brasil), para a caracterização e o monitoramento do impacto dos processos ambientais, climáticos e sócio-demográficas sobre a malária. Apresentamos e discutimos os conceitos " de sítio sentinela " e observatório e descrevemos as principais dispositivos existentes. Nós mostramos as escolhas necessárias para construir um " sitio sentinela " , e descrevemos os resultados preliminares, as primeiras mapas sobre a situação epidemiológica na fronteira, a primeira caracterização de risco entomológico no lado brasileiro, e a implementação de um portal na internet dedicado à divulgação de dados e indicadores de risco.Palavras-chave : Mudanças climáticas, malária, fronteiras internacionais, sistemas de informação.This paper presents the interest and methodology of building a sentinel site within the trans-border area between French Guiana and Amapá (Brazil), for the characterization and monitoring of the impacts of environmental, climatic and socio-demographic processes on malaria. We present and discuss the “sentinel site” and “observatory” concepts and we describe the main existing web portals related to these concepts. We detail and justify the choices required to build such a sentinelsite, and describe the preliminary results, i.e. the first maps of the epidemiological situation within the border area, the first characterization of entomological risk on the Brazilian side, and the implementation of a web portal dedicated to thedissemination of raw data and risk indicators.Keywords : climate change, malaria, international borders, information systems

Understanding the different background landscapes in which malaria transmission occurs is fundamental to understanding malaria epidemiology and to designing effective local malaria control programs. Geology, geomorphology, vegetation, climate, land use, and anopheline distribution were used as a basis for an ecological classification of the state of Roraima, Brazil, in the northern Amazon Basin, focused on the natural history of malaria and transmission. We used unsupervised maximum likelihood classification, principal components analysis, and weighted overlay with equal contribution analyses to fine-scale thematic maps that resulted in clustered regions. We used ecological niche modeling techniques to develop a fine-scale picture of malaria vector distributions in the state. Eight ecoregions were identified and malaria-related aspects are discussed based on this classification, including 5 types of dense tropical rain forest and 3 types of savannah. Ecoregions formed by dense tropical rain forest were named as montane (ecoregion I), submontane (II), plateau (III), lowland (IV), and alluvial ( V). Ecoregions formed by savannah were divided into steppe ( VI, campos de Roraima), savannah (VII, cerrado), and wetland (VIII, campinarana). Such ecoregional mappings are important tools in integrated malaria control programs that aim to identify specific characteristics of malaria transmission, classify transmission risk, and define priority areas and appropriate interventions. For some areas, extension of these approaches to still-finer resolutions will provide an improved picture of malaria transmission patterns.