Schistosomiasis in Sub-Saharan Africa

Using geostatistical and machine learning models, we analyzed spatio-temporal trends in schistosomiasis prevalence and heavy-intensity infections among children in SSA at sub-national scales from 2000 to 2022. Data were sourced from the Expanded Special Project to Eliminate Neglected Tropical Diseases (ESPEN) database and a systematic review of published literature, focusing on children under 18 in endemic regions. Counterfactual analyses were conducted to assess the impact of MDA, socioeconomic changes, and environmental factors on prevalence trends. Projections for 2030 were developed using deep learning models to assess the feasibility of WHO's targets and identify intervention priorities in high-risk areas.