Finding Missing Children: A Ward-Level Geospatial Framework for Targeting Malaria Chemoprevention and Child Survival Interventions in Sokoto State, Nigeria

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Malaria interventions depend critically on accurate estimates of the target population, yet discrepancies between household enumeration and modeled population products may result in eligible children being missed by prevention programs. This study developed a ward-level geospatial framework to identify children at risk of exclusion from malaria interventions and prioritize locations for chemoprevention investments in Sokoto State, Nigeria. Household microcensus data from 35,204 settlements, GRID3 settlement records, WorldPop 2025 population estimates, malaria surveillance indicators, malaria transmission metrics, healthcare accessibility variables, and monthly under-five malaria mortality records (2014–2024) were integrated via spatial analysis and multicriteria modeling. Household enumeration identified 762,317 under-five children, whereas WorldPop estimated 911,358 children, representing an excess of 149,041 children (19.6%). Denominator uncertainty was spatially heterogeneous, with a median absolute percentage difference of 41.6% between household-enumerated and WorldPop-derived under-five population estimates. The chemoprevention priority index (CPI), which integrates malaria burden, treatment and healthcare access deficits, child vulnerability, denominator uncertainty, and settlement complexity, identified high-priority wards concentrated in Gada, Wamakko, Tambuwal, Isa, and Kware LGAs. Dukamaje (Gada LGA) recorded the highest CPI score (100), followed by Gilbadi (97.7) and Kaura (92.8). These findings demonstrate that integrating operational microcensus data with geospatial population models can support geographically targeted investments in seasonal malaria chemoprevention, perennial malaria chemoprevention, malaria vaccination, and broader child survival programs.