Predictive Risk Mapping for Schistosomiasis in Parts of Borgu Local Government Area (LGA) of Niger State, Nigeria

Background. This study constructed predictive risk mapping of schistosomiasis infection and transmission using environmental and proximity risk factors. Methods. Environmental risk factors were derived from satellite imageries. Proximity risk factors and parasitological results were derived from fieldwork. The geographic coordinates of the settlement layer were used to extract the underlying cell values of the rasterized data layers using spatial collocation method. Results. The results suggest all the risk factors are likely to increase the odds of schistosomiasis infection, with the LST (Exp(beta) = 39.760) and NDVI (Exp(beta) = 1.030E+068) as the most important predictors. Conclusion. This study suggests an urgent need to conduct parasitological tests in other communities in high-risk zone in order to develop an inclusive and comprehensive treatment campaigns to reach the unreached and leave no community behind in schistosomiasis containment.