Schistosomiasis remains a significant public health concern in tropical and subtropical regions, especially in low-and-middle-income countries. In Brazil, control measures have reduced the disease's prevalence, creating low-endemic areas. However, environmental and climate dynamics, coupled with inadequate urbanization, pose risks of re-emergence. The middle Paranapanema basin, S & atilde;o Paulo state, exemplifies such a region. Here, the presence of Biomphalaria snail species (B. glabrata, B. straminea, and B. tenagophila), inadequate sanitation, and environmental changes signal potential schistosomiasis resurgence. This study aimed to develop a methodological framework to better understand schistosomiasis transmission mechanisms in low-endemic areas. It integrated demographic, environmental, malacological, and climatic data to identify transmission risk areas. The framework comprised a spatial hydrological model to assess fecal-contaminated water bodies, an exploratory spatial model for transmission hotspots, and snail dispersal analysis within drainage networks, incorporating climate projections. The methodology used geoprocessing tools to analyze hydrological, demographic, malacological, and climatic datasets. A spatial hydrological model combined sewage treatment and population density data with digital elevation models to identify potential transmission foci. Snail occurrence and schistosomiasis cases were spatially analyzed, with climate indices (1951-2022) providing rainfall trend projections. Land use datasets facilitated host habitat assessments, and outputs correlated potential foci with disease incidence. Results revealed that streams near urban areas with high concentrations of blackwater were associated with schistosomiasis cases. Streams hosting B. glabrata upstream had the strongest association with disease, while mixed-species habitats underscored hydrological connectivity's role. Urban and agricultural land-use areas overlapped with snail habitats, identifying high-risk zones. Climate projections indicated increasing extreme rainfall events, enhancing flooding and erosion, which may facilitate snail dispersal and extend schistosomiasis foci downstream. Effluent from municipalities like Ourinhos could intensify contamination, impacting neighboring areas like Salto Grande. The findings emphasize integrating hydrological, climatic, and ecological perspectives into schistosomiasis control strategies. Simple hydrological models assessing fecal-contaminated water bodies provide valuable insights for sanitation policies, and climate-related snail dispersal scenarios highlight emerging risks in connected areas. Addressing these challenges is crucial for eliminating schistosomiasis, particularly in low-endemic regions. This study's novel integrated hydrological-spatial models, based on freely available data, offer reproducible methods for identifying schistosomiasis transmission risks and guiding surveillance and control efforts in similar settings across Brazil.

Understanding the occurrence of urban floods and their conditioning factors is essential for effective management of urban watersheds. However, few studies have explored the spatial variability of these factors in detail. This study investigates the spatial relationships between conditioning factors and flood occurrences in the Tamanduate & iacute; River Basin, S & atilde;o Paulo, Brazil. Multi-source geospatial data were integrated to analyze spatial patterns using kernel density estimation, spatial autocorrelation, and geographically weighted regression at multiple scales. The results reveal strong spatial dependence and highlight the combined influence of environmental factors on flood susceptibility. Flatter, highly urbanized areas exhibited the greatest concentration of flood hotspots, confirming the importance of local topographic control. These findings contribute to a better understanding of spatial heterogeneity in urban flood dynamics and provide a replicable methodological framework for identifying high-risk areas, supporting more precise and spatially informed mitigation and adaptation strategies in rapidly urbanizing regions.

Este estudo teve como objetivo regionalizar a represa de Várzea das Flores, em Minas Gerais, por meio de sensoriamento remoto e métodos estatísticos de análise de dados geoespaciais, de 2017 a 2024. Inaugurada em 1972 para atender à crescente demanda hídrica da Região Metropolitana de Belo Horizonte, a represa enfrenta problemas de qualidade da água, associados à ocupação e ao uso do solo em sua bacia hidrográfica. Para isso, foram aplicadas as técnicas de regionalização SKATER e K-Medoids para agrupar o espelho d’água em zonas homogêneas. A análise baseou-se em dados de batimetria, turbidez e temperatura de superfície da água. A temperatura de superfície foi obtida a partir das bandas no infravermelho termal dos sensores a bordo dos satélites da série Landsat. A batimetria foi obtida do banco de dados Global lakes bathymetry dataset (GLOBathy) e a turbidez foi estimada por meio de modelos semianalíticos, combinando imagens do satélite Sentinel-2 e amostras de campo. O método K-Medoids apresentou maior eficiência para o agrupamento de zonas homogêneas, sendo selecionado o número de três grupos, fundamentado nos critérios do método Elbow e do índice Silhouette Score. A análise multivariada de variância indicou diferenças sazonais significativas entre as zonas. Esses resultados contribuem para subsidiar ações de gestão e conservação da represa.

Since the 20th century, cities in the Amazon have played a strategic role as logistical bases for territorial occupation and development, supporting the expansion of pioneer fronts expressed physically through land use and land cover change. Understanding nature's transformation in the contemporary Amazonian urban context requires a spatial delimitation of what constitutes the urban and how it extends across a diverse and often overlooked territory. This study adopts a theoretical-methodological approach that uses the urban weft as an analytical reference to represent this extensive, frequently invisibilized urban fabric and to investigate how industrial-capitalist rationality has reshaped human-nature relationships. The analysis is based on historical and recent forest loss indicators, calculated using annual deforestation data, with the urban weft of the state of Par & aacute; as the spatial focus. The results indicate that deforestation dynamics also extend into urban and peri-urban areas, revealing continuous pressures on these spaces and highlighting the importance of urbanization as a key element in the development and strengthening of regional planning and development agendas that are integrated with the biome and committed to nature conservation.

A economia agrária, com seus agentes sociais e sistemas técnicos, mobiliza os elementos que geram as transformações nas paisagens social e florestal na Amazônia brasileira. As escolhas para o desenvolvimento regional levam à sustentabilidade ou insustentabilidade do ecossistema florestal e de sua paisagem social. A saúde é negligenciada nesse debate. Argumentamos que uma estrutura analítica para abordagens integradas, saúde-ambiente-economia, necessita de uma representação territorial para as paisagens associadas aos modos de viver e produzir no agrário amazônico, as unidades de paisagem de produção (PLU, acrônimo em inglês). Neste artigo, exploramos técnicas de aprendizado de máquina, no campo da classificação supervisionada, com métodos baseados em árvores de decisão, para identificar e mapear as PLU. Um estudo de caso foi desenvolvido para os municípios de Mocajuba e Cametá, na região do Baixo Tocantins, no Estado do Pará, para o ano de 2021. Descrevemos como identificar e mapear as PLU em uma unidade espacial de referência intramunicipal e como associá-las aos tipos de trajetórias tecnoprodutivas rurais ou trajetórias tecnológicas (TTs) presentes na economia agrária regional, bem como promovemos uma discussão inicial do uso das PLU na estruturação de abordagens integradas em saúde. Este artigo contribui para alinhar debates sobre estratégias para o desenvolvimento econômico à promoção da saúde na Amazônia brasileira.

In the Amazon, the land market is imposed by the conversion of the forest into land for economic purposes. Part of this land is the result of illicit actions, using different levels of violence and producing changes in the forest landscape. We argue that conflicts over land are signs in the territories of the action of mechanisms to generate land as a commodity in the region. Based on the situations of land conflicts mapped by the Pastoral Land Commission in the period from 2012 to 2021 and the analytical categories of the agrarian economy (technological trajectories, TTs) for 2006 and 2017, an analysis was built at the municipal level based on two periods. From 2012 to 2017, we sought to identify and characterize the territories where these mechanisms were present, observed in conjunction with the state transitions of the TTs from 2006 to 2017. From 2018 to 2021, we sought to identify processes and trends for the most recent period. Municipalities that converged to economies based on livestock and grain farming systems concentrated more than 60% of the conflicts that occurred in the decade. The results show the persistence of conflicts in historical areas, such as in the southeast of Pará, and in new borders, such as in municipalities on the Amazonas, Rondônia and Acre borders. There is also the internalization of violence towards the western Amazon, in municipalities with economies based on the biome in different arrangements, revealing new fronts of interest for the land resource. The results contribute to the debate on violence in the Amazon, based on the choices for the agrarian development model, which can result in illnesses of individuals and communities trapped in disputes, to control the ways of living and producing.

This study analyzes the establishment of Local Agri-Food Systems (LAFSs) in the triple-border region between the states of Minas Gerais, Rio de Janeiro, and São Paulo, by identifying and mapping potential areas of primary peasant agri-food production. An integrated analysis of data sources was treated, processed, and integrated into a common spatial support. Land use and land cover data were used from demographic and agricultural censuses, from the Rural Environmental Registry, agrarian reform settlement projects and conservation units. Our study revealed that 23.73% of the regional area has potential for peasant production, identifying four regions that stand out in terms of this potential. The area presented livestock and animal husbandry as the main agri-food chain, with potential for processing within the territory itself, in addition to extractive activities in the Atlantic Forest biome. The results indicate that there are possibilities for the establishment of LAFSs as a local development strategy associated with social inclusion and environmental responsibility, although there is a need to expand and strengthen the transportation and marketing channels for products from these short chains. The cartographies produced aim to contribute as auxiliary instruments to land use planning and management, seeking to strengthen LAFSs at different scales of governance.

The Amazon Biome, the most biodiverse region on Earth, plays a crucial role in providing ecosystem services, notably global climate regulation. Despite its significance, the Amazon rainforest has experienced extensive loss and degradation over the past five decades. This study introduces the Forest Landscape Disturbance Index (FLDI) and the Forest Landscape Structural Integrity Index (FLSII), composite indices designed to quantify the degree of forest disturbance and structural integrity across landscapes in the state of Para in the Brazilian Amazon. Landscape metrics on primary forest, secondary forest, deforestation, and forest degradation were extracted from the Brazilian Biomes Monitoring Program (BiomasBR) data using a regular grid. Each cell in the grid represents a landscape unit for which the FLDI and FLSII were computed. A sensitivity analysis was conducted to assess indices' performance. Results indicate that 32 % of landscape units experienced high forest disturbance, while 55 % retained high structural integrity. To assess these indices, five regions of Para were selected for comparison with field-based observations. Field observations explored links between forest condition, local occupation history, and agrarian productive systems. These indices rely on simple, publicly available data and are easy to interpret, enhancing their utility for researchers, policymakers, and land managers. Their application at regional scales enables the identification of forest conditions across gradients of human impact. Although further validation with additional field data is recommended, the FLDI and FLSII show strong potential as tools for monitoring forest conditions and guiding strategic decision-making in forest conservation, management, and restoration across the Brazilian Amazon.

The agrarian economy, with its social agents and technical systems, mobilizes the elements that generate transformations in the social and natural landscapes in the Brazilian Amazon. Choices for regional development lead to sustainability or unsustainability of the forest ecosystem and its social landscape, while not including health in this debate. We argue that an analytical framework for integrated health-environment-economy approaches needs a territorial representation for the landscapes associated with the ways of living and producing in Amazonian agriculture: the production landscape units (PLU). In this article, we explore machine learning techniques, in the field of supervised classification, with methods based on decision trees, to identify and map the PLU. A case study is developed for the municipalities of Mocajuba and Cametá, in the Baixo Tocantins region, in the State of Pará, for 2021. We describe how to identify and map the PLU in an intra-municipal spatial unit of reference and how to associate them with the types of rural techno-productive trajectories or technological trajectories (TTs) found in the regional agrarian economy. We promote an initial discussion on the use of PLU in the structuring of integrated approaches in health. This article contributes to align debates on strategies for economic development with health promotion in the Brazilian Amazon.

Na Amazônia, o mercado de terras se impõe pela conversão da floresta em terras para o mercado. Parte dessas terras é fruto do ilícito, com uso de diferentes níveis de violência, e produzem alterações na paisagem florestal. Argumentamos que os conflitos por terra são sinalizadores nos territórios de ação dos mecanismos geradores de terra, como mercadoria, que operam na região. Partindo das situações de conflitos por terra mapeadas pela Comissão Pastoral da Terra no período de 2012 a 2021 e as categorias analíticas da economia agrária (trajetórias tecnológicas, TT), para 2006 e 2017, construímos uma análise em nível municipal baseada em dois períodos. De 2012 a 2017, buscamos identificar e caracterizar os territórios onde esses mecanismos estiveram presentes, observando-os em conjunto às transições de estado das TTs de 2006 para 2017. De 2018 a 2021, buscou-se identificar processos e tendências para o período mais recente. Municípios que convergiram para economias baseadas em sistemas patronais de pecuária e de agricultura de grãos concentraram mais de 60% dos conflitos ocorridos na década. Os resultados mostram a persistência dos conflitos em áreas históricas, como no sudeste paraense, e em novas fronteiras, como em municípios da fronteira Amazonas, Rondônia e Acre. Há, também, a interiorização das violências em direção à Amazônia ocidental, em municípios de economias baseadas no bioma em arranjos diversos, revelando novas frentes de interesse do recurso terra. Os resultados contribuem para o debate das violências na Amazônia, a partir das escolhas pelo modelo de desenvolvimento agrário, que pode resultar no adoecimento de indivíduos e comunidades aprisionados em disputas para o controle dos modos de viver e produzir.

Background Schistosomiasis, a chronic parasitic disease, remains a public health issue in tropical and subtropical regions, especially in low and moderate-income countries lacking assured access to safe water and proper sanitation. A national prevalence survey carried out by the Brazilian Ministry of Health from 2011 to 2015 found a decrease in human infection rates to 1%, with 19 out of 26 states still classified as endemic areas. There is a risk of schistosomiasis reemerging as a public health concern in low-endemic regions. This study proposes an integrated landscape-based approach to aid surveillance and control strategies for schistosomiasis in low-endemic areas. Methodology/Principal findings In the Middle Paranapanema river basin, specific landscapes linked to schistosomiasis were identified using a comprehensive methodology. This approach merged remote sensing, environmental, socioeconomic, epidemiological, and malacological data. A team of experts identified ten distinct landscape categories associated with varying levels of schistosomiasis transmission potential. These categories were used to train a supervised classification machine learning algorithm, resulting in a 92.5% overall accuracy and a 6.5% classification error. Evaluation revealed that 74.6% of collected snails from water collections in five key municipalities within the basin belonged to landscape types with higher potential for S. mansoni infection. Landscape connectivity metrics were also analysed. Conclusions/Significance This study highlights the role of integrated landscape-based analyses in informing strategies for eliminating schistosomiasis. The methodology has produced new schistosomiasis risk maps covering the entire basin. The region’s low endemicity can be partly explained by the limited connectivity among grouped landscape-units more prone to triggering schistosomiasis transmission. Nevertheless, changes in social, economic, and environmental landscapes, especially those linked to the rising pace of incomplete urbanization processes in the region, have the potential to increase risk of schistosomiasis transmission. This study will help target interventions to bring the region closer to schistosomiasis elimination.

The geographical range of schistosomiasis is affected by the ecology of schistosome parasites and their obligate host snails, including their response to temperature. Previous models predicted schistosomiasis' thermal optimum at 21.7 °C, which is not compatible with the temperature in sub-Saharan Africa (SSA) regions where schistosomiasis is hyperendemic. We performed an extensive literature search for empirical data on the effect of temperature on physiological and epidemiological parameters regulating the free-living stages of S. mansoni and S. haematobium and their obligate host snails, i.e., Biomphalaria spp. and Bulinus spp., respectively. We derived nonlinear thermal responses fitted on these data to parameterize a mechanistic, process-based model of schistosomiasis. We then re-cast the basic reproduction number and the prevalence of schistosome infection as functions of temperature. We found that the thermal optima for transmission of S. mansoni and S. haematobium range between 23.1-27.3 °C and 23.6-27.9 °C (95 % CI) respectively. We also found that the thermal optimum shifts toward higher temperatures as the human water contact rate increases with temperature. Our findings align with an extensive dataset of schistosomiasis prevalence in SSA. The refined nonlinear thermal-response model developed here suggests a more suitable current climate and a greater risk of increased transmission with future warming for more than half of the schistosomiasis suitable regions with mean annual temperature below the thermal optimum.

ABSTRACTSchistosomiasis is a neglected tropical disease caused bySchistosomaparasites.Schistosomaare obligate parasites of freshwaterBiomphalariasnails, so controlling snail populations is critical to reducing transmission risk. As snails are sensitive to environmental conditions, we expect their distribution is significantly impacted by global change. Here, we leveraged machine learning, remote sensing, and 30 years of snail occurrence records to map the historical and current distribution of competentBiomphalariathroughout Brazil. We identified key features influencing the distribution of suitable habitat and determined howBiomphalariahabitat has changed with climate and urbanization over the last three decades. Our models show that climate change has driven broad shifts in snail host range, whereas expansion of urban and peri-urban areas has driven localized increases in habitat suitability. Elucidating change inBiomphalariadistribution – while accounting for non-linearities that are difficult to detect from local case studies – can help inform schistosomiasis control strategies.