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Description
Malaria is a major challenge in the drylands of Nigeria, where transmission is strongly conditioned by climatic instability, environmental fragility and socio-demographic pressures. This study conducted a multi-temporal geo-epidemiological analysis of malaria incidence across Yobe State, aiming to identify climatic–environmental drivers of malaria heterogeneity and delineate spatial hotspots and cool-spots for targeted intervention. The study employed unsupervised machine-learning classification across the three micro-climatic zones – the SaSZ, TZ and SuSZ. Temporal analysis revealed distinct ecological contrasts with the SaSZ displayed weakly increasing but highly erratic incidence patterns (R² = 0.06), with intermittent peaks in 2016 and 2020. The TZ showed moderate fluctuations (R² = 0.04) with declines between 2014–2017 followed by resurgence from 2019–2023; while the SuSZ demonstrated a strong rising trend (R² = 0.77) and the highest burden, with annual incidence ranging from 300–420 cases per 1,000. Seasonal decomposition showed transmission peaks between August and September, following the rainfall-driven breeding cycle. Spatial modelling identified intense hotspots in the SuSZ (indices 0.61–1.0) particularly in Fika, Gadaka and Garin Gambo, while cold-spots (indices <0.10) were concentrated in the SaSZ around Dagona and Azam Kura. NDVI–malaria coupling revealed strong co-variation in wetter zones, with greenness indices consistently aligning with incidence maxima. Population density also correlated positively with malaria intensity, especially in peri-urban and irrigated communities. Generally, the study demonstrated that malaria risk in Yobe State is climate-sensitive, spatially heterogeneous and ecologically stratified. These findings provided an empirical foundation for climate-informed, zone-specific malaria interventions in Nigeria’s dryland environments.
| Title | GEO-EPIDEMIOLOGICAL ANALYSIS OF MALARIA SPOTS IN THE SAHELIAN DRYLANDS OF NIGERIA |
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