Assessing schistosomiasis transmission risk based on integrated hydrological and environmental modeling

Abstract 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, São 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.