Vegetation density, land use, and childhood malaria in Uganda, 2015–2023: An ecological study

Introduction: Malaria remains a major public health challenge in Uganda, particularly among children under five years of age. Environmental factors such as vegetation density and land use/land cover (LULC) may influence malaria transmission by affecting mosquito breeding habitats and vector survival. This study assessed the association between environmental factors, particularly the Normalized Difference Vegetation Index (NDVI) and LULC, and Malaria cases among children under five years across four ecologically diverse regions of Uganda: West Nile, Karamoja, Central, and Western Uganda. Methods: Retrospective ecological analysis (2015–2023) with district-month as the analytical unit, involving 13 high-burden districts across four regions: West Nile [3], Karamoja [3], Western [3], and Central [4]. Malaria case data were obtained from DHIS2 and aggregated into monthly district-level totals. Environmental variables (NDVI, LULC, rainfall, temperature) were measured within 5-km buffers around eight high-burden health facilities selected as sentinel environmental sites across four regions. Facility-level environmental exposures were aggregated to the district-month level. Fixed-effects negative binomial regression estimated associations. Results: Higher district-level NDVI (vegetation density) was significantly associated with increased Malaria cases: IRR = 1.47 per 0.5-unit increase (95% CI: 1.40–1.54; p < 0.001). Rural districts with dense vegetation (NDVI > 0.6) exhibited a 47% higher monthly incidence compared to urbanized districts (NDVI < 0.3). Urbanization was protective (IRR=0.92 per 10% urban increase; 95% CI: 0.87–0.97). Temperature and rainfall also significantly predicted incidence. Conclusion: At the district-month level, vegetation density and LULC were significantly associated with childhood malaria. Environmental surveillance may complement district-level malaria prediction. Future studies should develop facility-level outcome surveillance to enable targeted interventions.