Spatial-Temporal Risk Mapping and Epidemiological Modeling of Bovine Fascioliasis in Uganda: A One Health Surveillance Framework at the Livestock, Snail, and Water Interface (IOCVS 2026)

Background: Fascioliasis is a neglected zoonotic infection that causes significant burdens at the livestock, human, and environmental interface in sub-Saharan Africa. In Uganda, despite notable economic losses in veterinary fields, the spatiotemporal patterns, environmental factors, and epidemiological clustering of bovine fascioliasis have not been fully characterized using integrated surveillance and predictive modeling.

Methods: Passive disease surveillance records from Uganda's national livestock disease database for 2023 to 2024 were georeferenced across three major lake basins. These records were combined with high-resolution bioclimatic (WorldClim 2.1), hydrological, topographic, soil (ISRIC SoilGrids), and vegetation (MODIS) datasets at a 1 km² resolution. We used multivariable logistic regression, checked for variance inflation factor, and performed receiver operating characteristic analysis to determine key environmental predictors. Spatial and space-time clustering were identified using SaTScan v9.4.4 with Bernoulli and Poisson models, evaluating significance through 999 Monte Carlo permutations.

Results: Fascioliasis showed significant spatial variation across Uganda's lake basins. The Lake Victoria basin (Jinja-Mayuge) stood out as the main high-prevalence area, with a prevalence of 18.0% and a relative risk of 4.9 (p < 0.001). This was linked to wetland ecosystems, high annual rainfall, and frequent human and livestock contact through fishing, irrigated farming, and abattoir operations. Moderate-risk clusters were found in the Albert Nile basin (Hoima: 2.1%) and temporary clusters in the Kyoga basin (Lira: 4.4%). Important environmental predictors included temperature variability, changes in precipitation, soil organic carbon levels, and the enhanced vegetation index. Projections from 1970 to 2030 showed expanding ecological suitability and transmission hotspots focused in southwestern and peri-urban areas.

Conclusions: This first combined spatiotemporal surveillance and modeling shows fascioliasis as a varied, environmentally driven zoonotic threat with specific geographic transmission areas in Uganda. Targeted interventions, including managing snail habitats, strategic livestock deworming, and community health education within a one health framework that provides a replicable and scalable model for regional disease control.