Geospatial mapping of mosquito larval habitats in peri-urban areas of Kwara State, Nigeria

Background: Peri-urban environments are increasingly recognized as important settings for mosquito proliferation due to rapid land-use change, heterogeneous aquatic habitats, and expanding human settlements. Understanding the spatial distribu-tion of mosquito larval habitats and their environmental determinants is essential for evidence-based vector control planning. Methods: A cross-sectional, spatially explicit entomological study was conducted in peri-urban communities. A total of 65 georeferenced sampling locations were surveyed for mosquito larvae across natural and artificial aquatic habitats. Larval abundance was recorded at each site, and specimens were identified morphologically. Satellite-derived environmental varia-bles were processed and integrated within QGIS. Differences in larval density across aggregated habitat categories were assessed using the Kruskal–Wallis test, followed by Dunn post hoc tests with a Bonferroni correction. Environmental drivers of larval abundance were examined using Negative Binomial regression (NBR) (p<0.05). Results: Of the 1,056 larvae collected, Culex species predominated (686/1,056), while Anopheles species comprised 35.04%. Larval density differed significantly across habitat categories (H=13.44, p=0.0038). Post hoc analysis showed that used tires and drum-type containers supported significantly higher larval densities than open-water habitats (adjusted p < 0.0083). NBR indicated that open-water habitats were associated with significantly lower larval abundance than drum habi-tats (β = -0.76, p = 0.044). Surface moisture was positively associated with larval abundance, whereas built-up intensity was negatively associated. Predictive mapping revealed pronounced spatial heterogeneity in larval suitability across the study area. Conclusion: This study demonstrates that mosquito larval abundance in peri-urban Ilorin East is strongly influenced by habitat type and environmental conditions. The integration of entomological surveillance with GIS and remote sensing pro-vides a robust framework for identifying high-risk areas. Targeted management of artificial containers and incorporation of spatial risk mapping into routine surveillance are recommended to improve vector control efficiency in peri-urban settings.