Spatio-ecological determinants of Biomphalaria and Bulinus snail intermediate hosts and schistosome-like infections in the Lango subregion, Northern Uganda: a geostatistical approach to guide targeted disease control

Abstract

Abstract Background Freshwater snails of the genus Biomphalaria transmit Schistosoma mansoni (intestinal schistosomiasis), Bulinus species transmit S. haematobium (urogenital schistosomiasis), and Lymnaea species transmit Fasciola spp. (fascioliasis). These diseases are of major public health and veterinary concern in sub-Saharan Africa. In Uganda's Lango subregion, schistosomiasis remains endemic despite control efforts, yet comprehensive spatial and ecological analyses of snail intermediate host distributions are lacking. This study employed geostatistical approaches to identify high-density snail habitats and sites where schistosome cercarial shedding was detected (as a proxy for potential infection, without molecular confirmation) to inform further surveillance and consideration of targeted control strategies. Methods A cross-sectional study was conducted during the dry and rainy seasons of 2023 across 26 georeferenced sites in Lira and Kole districts. Freshwater snails were collected using standardized methods and identified morphologically using Brown (1994) and Mandahi-Barth (1988) keys. Cercarial shedding tests determined patent infection status but could not definitely distinguish human-infective from non-human schistosome species without molecular confirmation. Physicochemical parameters (pH, salinity, total dissolved solids, dissolved oxygen, temperature, and conductivity) and ecological variables were measured. Spatial analysis included Moran’s I for autocorrelation, Getis-Ord Gi* for hotspot detection, and inverse distance weighting for interpolation. Generalized linear mixed models with spatial random effects were used to assess predictors of snail prevalence and density, compared with non-spatial models using the Akaike Information Criterion. Dry and rainy season data were treated as separate observations from the same sites ( n = 52 site-season observations), with site included as random effect to account for repeated measures. Results A total of 4802 snails from 13 species were collected, with Biomphalaria choanomphala (25.8%, n = 1241) being most abundant. Bulinus africanus (17.7%, n = 852) and Lymnaea natalensis (10.6%, n = 510) were also abundant. Significant spatial clustering was detected for B. choanomphala (Moran’s I = 0.32, p = 0.004) and B. sudanica (Moran’s I = 0.24, p = 0.018). Three density hotspots and sites where cercarial shedding was detected (descriptive only given the small number of infected snails) were identified, primarily in rice paddies and swamps near human settlements. Overall patent infection rate (based on cercarial shedding) was 0.15% (5/3404 tested snails). Species-specific rates were B. choanomphala 0.16% (2/1,241), B. sudanica 0.13% (1/749), and B. africanus 0.23% (2/852). No schistosome-like infections were detected in Lymnaea snails or other genera. Spatial GLMMs outperformed non-spatial models (ΔAIC = 12.7–15.3), revealing significant effects of salinity (odds ratio = 0.21, p < 0.001), total dissolved solids ( β = − 0.03, p = 0.002), dissolved oxygen ( β = 0.54, p = 0.003), and anthropogenic activities. Spatial random effects accounted for 18–24% of residual variation. Conclusions This study demonstrates the added value of geostatistical methods in identifying snail intermediate host clusters and sites with detected schistosome-like infections. The integration of spatial analysis with ecological modeling provides a robust framework to guide further surveillance and consideration of targeted snail control interventions. Our findings suggest that focused surveillance in identified high-density areas, integration of spatial risk maps into district health planning, and community engagement in modifying high-risk water contact sites could be considered to help reduce schistosomiasis transmission in the Lango subregion. These suggestions require validation through longitudinal studies before implementation at scale.