INTEGRATING GEOSPATIAL HOTSPOT ANALYSIS AND CLINICAL SEVERITY PROFILING FOR PRECISION MALARIA CONTROL IN BAYELSA STATE, NIGERIA

Abstract

Malaria remains a persistent public health challenge in Nigeria, with transmission intensity and clinical outcomes varying substantially across geographic and population subgroups. Precision public health approaches that integrate spatial analytics with clinical severity assessment offer opportunities to improve the efficiency of malaria control interventions. This study mapped malaria transmission intensity and clinical severity in Bayelsa State, Nigeria, using routine surveillance data to identify geographic hotspots and severity patterns relevant for targeted intervention planning. A retrospective analysis of 3,000 confirmed malaria cases recorded between 2022 and 2025 across eight Local Government Areas (LGAs) was conducted. Descriptive statistics, geospatial mapping, density estimation, and severity stratification were applied to examine spatial clustering, demographic distributions, and clinical indicators. Results revealed marked spatial heterogeneity in malaria transmission, with Ogbia, Brass, and Nembe LGAs exhibiting the highest transmission intensity. Although low-severity cases predominated, distinct clusters of moderate and severe malaria were identified, particularly in LGAs with riverine and hard-to-reach communities. Body temperature demonstrated a strong positive association with clinical severity, while gender and rainfall showed limited direct influence on severity outcomes. The study demonstrates the utility of integrating transmission intensity mapping and severity analytics to inform precision public health strategies, optimize resource allocation, and strengthen malaria control programs in Bayelsa State.