Twenty-first-century demographic and social inequalities of heat-related deaths in Brazilian urban areas.

Population exposure to heat waves (HWs) is increasing worldwide due to climate change, significantly affecting society, including public health. Despite its significant vulnerabilities and limited adaptation resources to rising temperatures, South America, particularly Brazil, lacks research on the health impacts of temperature extremes, especially on the role played by socioeconomic factors in the risk of heat-related illness. Here, we present a comprehensive analysis of the effects of HWs on mortality rates in the 14 most populous urban areas, comprising approximately 35% of the country's population. Excess mortality during HWs was estimated through the observed-to-expected ratio (O/E) for total deaths during the events identified. Moreover, the interplay of intersectionality and vulnerability to heat considering demographics and socioeconomic heterogeneities, using gender, age, race, and educational level as proxies, as well as the leading causes of heat-related excess death, were assessed. A significant increase in the frequency was observed from the 1970s (0-3 HWs year-1) to the 2010s (3-11 HWs year-1), with higher tendencies in the northern, northeastern, and central-western regions. Over the 2000-2018 period, 48,075 (40,448-55,279) excessive deaths were attributed to the growing number of HWs (>20 times the number of landslides-related deaths for the same period). Nevertheless, our event-based surveillance analysis did not detect the HW-mortality nexus, reinforcing that extreme heat events are a neglected disaster in Brazil. Among the leading causes of death, diseases of the circulatory and respiratory systems and neoplasms were the most frequent. Critical regional differences were observed, which can be linked to the sharp North-South inequalities in terms of socioeconomic and health indicators, such as life expectancy. Higher heat-related excess mortality was observed for low-educational level people, blacks and browns, older adults, and females. Such findings highlight that the strengthening of primary health care combined with reducing socioeconomic, racial, and gender inequalities represents a crucial step to reducing heat-related deaths.

Involvement of political and socio-economic factors in the spatial and temporal dynamics of COVID-19 outcomes in Brazil: A population-based study.

Background: 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. Methods: 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. Findings: 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. Interpretation: 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. Funding: International joint laboratories of Institute de Recherche pour le Développement, a partnership between the University of Brasília and the Oswaldo Cruz Foundation (LMI-Sentinela - UnB - Fiocruz - IRD), Coordination for the Improvement of Higher Education Personnel (CAPES), National Council for Scientific and Technological Development (CNPq).

Improving Dengue Forecasts by Using Geospatial Big Data Analysis in Google Earth Engine and the Historical Dengue Information-Aided Long Short Term Memory Modeling.

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.

Urban Land Expansion from Scratch to Urban Agglomeration in the Federal District of Brazil in the Past 60 Years.

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.

Migração e saúde: inter-relações, legislação e acesso / Migration and health: interrelations, legislation and access / Migración y salud: interrelaciones, legislación y acceso

A mobilidade humana se constitui em um dos principais desafios para a saúde global na atualidade. Com uma população mundial de migrantes, voluntários e forçados, estimada de 258 milhões em 2017, o acesso aos serviços de saúde afeta tanto a saúde do migrante quanto a sociedade na qual se insere, sendo um dos temas centrais em fóruns multilaterais como a Organização Mundial de Saúde e em debates sobre acesso universal à saúde. Buscando contribuir para esse debate, a formulação de políticas públicas e a futuros estudos, o presente artigo faz uma revisão narrativa de literatura sobre as inter-relações entre migração e saúde, seu aspecto legal no âmbito internacional e nacional e sobre o que vem a ser acesso nesse contexto de super diversidade. Identificamos que o processo migratório por acentuar vulnerabilidades e a exposição a riscos impacta negativamente a saúde física e mental do migrante. No Brasil, mesmo com o recuo governamental em relação ao Pacto Global para a Migração, o acesso aos serviços de saúde é assegurado por vários dispositivos legais como a Constituição Federal de 1988, a Lei do SUS e a Lei de Migração. No entanto, recomenda-se estudos que avaliem a efetividade dessas leis na saúde dos imigrantes. Por fim, revisitamos diversas abordagens sobre o conceito de acesso e reconhecemos que para avaliar o acesso e formular políticas direcionadas ou inclusivas devem partir da conceitualização de acesso capazes de abranger as especificidades das populações migrantes e refugiadas. (AU)

Nowadays, human mobility is one of the major challenges for global health. In 2017, voluntary and forced migrants were estimated 258 million. Access to health care affects both the migrant's health and the host society, being a central issue on universal access in multilateral forums such as the World Health Organization. Aiming to contribute to the debate, the formulation of public policies and future studies, this article makes a narrative review of the literature on the interrelationships between migration and health, its legal aspect in the international and national scope and what means access in this context of super-diversity. We identified that the migratory process negatively impacts the physical and mental health of the migrant by accentuating vulnerabilities and increasing the exposure to risks. In Brazil, even with the government's withdrawal from the Global Compact for Migration, we conclude that access to health care is granted by various legal provisions such as the Federal Constitution of 1988, the Unified Health System Law and the Migration Law. However, studies evaluating the effectiveness of the law are recommended. Finally, we revisit several approaches on the concept of access and recognize that in order to evaluate access, formulate targeted or inclusive policies and for future research, the concept or approach of access should encompass the specificities of migrant and refugee populations. (AU)

La movilidad humana se constituye en uno de los principales desafíos para la salud global en la actualidad. Con una población de migrantes, voluntarios y forzados, estimada de 258 millones en 2017, el acceso a los servicios de salud afecta tanto a la salud del migrante como a la sociedad en la que se inserta. Siendo uno de los temas centrales en foros multilaterales como la Organización Mundial de Salud y en debates sobre acceso universal a la salud. En el presente artículo se hace una revisión narrativa de literatura sobre las interrelaciones entre migración y salud, su aspecto legal en el ámbito internacional y nacional y sobre lo que viene a ser acceso en ese contexto de super diversidad. Identificamos que el proceso migratorio por acentuar vulnerabilidades y la exposición a riesgos impacta negativamente en la salud física y mental del migrante. En Brasil, incluso con el retroceso gubernamental con relación al Pacto Global para la Migración, el acceso a los servicios de salud está asegurado por varios dispositivos legales como la Constitución Federal de 1988, la Ley del SUS y la Ley de Migración. Sin embargo, se recomiendan estudios que evalúen la efectividad de la ley. Por último, revisamos diversos enfoques sobre el concepto de acceso y reconocemos que para evaluar el acceso y formular políticas dirigidas o inclusivas deben partir de la conceptualización de acceso capaces de abarcar las especificidades de los migrantes y refugiados. (AU)

Semi-Supervised Text Classification Framework: An Overview of Dengue Landscape Factors and Satellite Earth Observation.

In recent years there has been an increasing use of satellite Earth observation (EO) data in dengue research, in particular the identification of landscape factors affecting dengue transmission. Summarizing landscape factors and satellite EO data sources, and making the information public are helpful for guiding future research and improving health decision-making. In this case, a review of the literature would appear to be an appropriate tool. However, this is not an easy-to-use tool. The review process mainly includes defining the topic, searching, screening at both title/abstract and full-text levels and data extraction that needs consistent knowledge from experts and is time-consuming and labor intensive. In this context, this study integrates the review process, text scoring, active learning (AL) mechanism, and bidirectional long short-term memory (BiLSTM) networks, and proposes a semi-supervised text classification framework that enables the efficient and accurate selection of the relevant articles. Specifically, text scoring and BiLSTM-based active learning were used to replace the title/abstract screening and full-text screening, respectively, which greatly reduces the human workload. In this study, 101 relevant articles were selected from 4 bibliographic databases, and a catalogue of essential dengue landscape factors was identified and divided into four categories: land use (LU), land cover (LC), topography and continuous land surface features. Moreover, various satellite EO sensors and products used for identifying landscape factors were tabulated. Finally, possible future directions of applying satellite EO data in dengue research in terms of landscape patterns, satellite sensors and deep learning were proposed. The proposed semi-supervised text classification framework was successfully applied in research evidence synthesis that could be easily applied to other topics, particularly in an interdisciplinary context.

Dengue spatiotemporal dynamics in the Federal District, Brazil: occurrence and permanence of epidemics. / Dinâmica espaço-temporal da dengue no Distrito Federal, Brasil: ocorrência e permanência de epidemias.

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.

Dengue Surveillance System in Brazil: A Qualitative Study in the Federal District.

Dengue's increasing trends raise concerns over global health and pose a challenge to the Brazilian health system, highlighting the necessity of a strong surveillance system to reduce morbidity, mortality, and the economic burden of this disease. Although the Brazilian surveillance system reports more dengue cases than any other country, recent studies suggest that non-reported cases are the majority. The aim of the study is to explore the strengths and weaknesses of the Brazilian surveillance system, particularly looking at the functioning of data collection and reporting. This was done through qualitative semi-structured interviews with 17 experts in dengue surveillance, supported by quantitative data from the official notification system. To select the interviewees, purposive and theoretical sampling were used. Data were analyzed through thematic analysis. The research highlighted that a lack of human and technological resources in healthcare units and surveillance departments slows down the notification process and data analysis. Due to a lack of integration in the private sector, the surveillance system fails to detect the socioeconomic profile of the patients. Investments in public healthcare, human and technological resources for surveillance and better integration in the private healthcare system, and vector surveillance may improve dengue surveillance.

Dinâmica espaço-temporal da dengue no Distrito Federal, Brasil: ocorrência e permanência de epidemias / Dengue spatiotemporal dynamics in the Federal District, Brazil: occurrence and permanence of epidemics

Resumo O Distrito Federal (DF) apresenta características particulares que favorecem a introdução, reprodução, disseminação e permanência do vetor e dos vírus da dengue. O objetivo deste trabalho foi analisar os padrões espaço-temporais das epidemias de dengue nas Regiões Administrativas (RAs) do DF no período de janeiro de 2007 a dezembro de 2017. Utilizando o modelo da série parcial de Fourier, obteve-se uma assinatura sazonal da série temporal, o que permitiu calcular indicadores de permanência (número de anos epidêmicos, número de meses epidêmicos por ano, proporção de meses epidêmicos do período) e tempo/momento das epidemias (mês do pico epidêmico). Contabilizou-se um total de 82 epidemias nesse período. As RAs com maior número de anos epidêmicos foram Varjão (5 epidemias), Gama, Lago Sul e Sobradinho (4 epidemias). Essas últimas três RAs também tiveram as maiores proporções de meses epidêmicos de todo o período de estudo (nove). Verificou-se que as RAs com função de centralidade urbana possuem pico epidêmico mais cedo que as demais, nos meses de fevereiro e março. As epidemias apresentaram altos valores de permanência em RAs com diferentes tipos de ocupação, ressaltando-se a necessidade de considerar os processos de organização social do espaço nos estudos da distribuição da dengue.

Abstract 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.

Wetlands and Malaria in the Amazon: Guidelines for the Use of Synthetic Aperture Radar Remote-Sensing.

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.

Land cover, land use and malaria in the Amazon: a systematic literature review of studies using remotely sensed data.

The nine countries sharing the Amazon forest accounted for 89% of all malaria cases reported in the Americas in 2008. Remote sensing can help identify the environmental determinants of malaria transmission and their temporo-spatial evolution. Seventeen studies characterizing land cover or land use features, and relating them to malaria in the Amazon subregion, were identified. These were reviewed in order to improve the understanding of the land cover/use class roles in malaria transmission. The indicators affecting the transmission risk were summarized in terms of temporal components, landscape fragmentation and anthropic pressure. This review helps to define a framework for future studies aiming to characterize and monitor malaria.

An ecoregional classification for the state of Roraima, Brazil: the importance of landscape in malaria biology.

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.

An ecoregional classification for the state of Roraima, Brazil: the importance of landscape in malaria biology

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.

Distribution summaries of malaria vectors in the northern Brazilian Amazon.

Knowledge of vector distribution is important for the design of effective local malaria control programs. Here we apply ecological niche modeling to analyze and predict the distributions of malaria vectors based on entomological collection points in the State of Roraima in the northern Brazilian Amazon Basin. Anopheline collections were conducted from 1999 to 2003 at 76 localities, all with active malaria transmission. A total of 13 anopheline species was identified from 17,074 adult females collected: Anopheles darlingi, An. albitarsis s.l., An. nuneztovari, An. triannulatus s.l., An. braziliensis, An. peryassui, An. oswaldoi s.l., An. mattogrossensis, An. strodei, An. evansae, An. squamifemur, An. mediopunctatus s.l, An. intermedius. Anopheles darlingi, and An. albitarsis were the most frequently found species. An. squamifemur was found for the first time in Roraima. A distributional prediction model (genetic algorithm for rule-set prediction-GARP) and environmental variables were used to predicted potential distribution range for six anopheline species that occurred at > or = 19 collection points. The method allows for the application of moderate sample sizes to produce distribution maps of vector species that could be used to maximize efficiency of surveys and optimize use of economic resources in epidemiology and control.