Spatial relationships between mosquito breeding sites and malaria cases in rural Uganda: Implications for larval source management

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ID: 329686
2026
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Abstract
Abstract Background Larval source management (LSM) has been a core strategy of malaria control but is difficult to implement in holoendemic regions of rural sub-Saharan Africa. More targeted approaches that reduce the burden of effort, but maintain impact are needed. Methods The prospective cohort study examined the spatial relationship between mosquito breeding sites and malaria cases to guide targeted LSM. After enrolling households across three villages, we recorded malaria cases from neighboring health facilities and conducted larval and adult mosquito surveillance. Breeding site density was assessed within different search radii from malaria cases using GIS. Households were grouped by environmental similarity using Factor Analysis of Mixed Data (FAMD) and k-means clustering, and clusters were compared in terms of malaria incidence and mosquito abundance. Results We identified and surveyed 69 breeding sites (March–May 2023, 90% larva-positive) in the study area and documented 56 clinical malaria cases among 366 households (April–June 2023). Malaria incidence was higher within 200 m of breeding sites than in households without (0.20 vs 0.09 cases per household; p = 0.005). When searching outward from cases, the number of covered breeding sites increased rapidly, reaching 60% within 200 m and 75% within 300 m, before plateauing. Malaria risk and mosquito abundance varied across clusters, particularly near the hydroelectric station spillway and in areas with different house construction. Conclusions The findings support the potential of reactive LSM by targeting breeding sites near malaria cases. Further research is needed to assess its effectiveness and its added value in malaria control programs.
Reference Key
openalex_W7214231434 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors
Journal The Journal of infectious diseases
Year 2026
DOI
10.1093/infdis/jiag481
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