Modeling the potential distribution of Wesselsbron, Sindbis, and Middelburg viruses and their vectors in Africa under future climatic and land-use changes

BACKGROUND: Outbreaks of zoonotic arboviruses originating in Africa occur amidst complex ecological changes and are increasingly emerging as important neglected tropical diseases. Despite sporadic epizootics and human cases of Wesselsbron virus (WSLV), Sindbis virus (SINV), and Middelburg virus (MIDV) in Africa, knowledge of associated risks remains insufficient for prevention. METHODOLOGY: We developed species distribution models for the three viruses alongside five key vectors, Aedes circumluteolus and Aedes mcintoshi for WSLV; Culex univittatus and Culex pipiens for SINV; and Mansonia africana and Aedes mcintoshi for MIDV that indicate areas with ecological suitability for the arboviruses in Africa. We integrated virus and mosquito species occurrence data with climate and land-use data for current (2015) and future (2021 - 2040) scenarios under two shared socioeconomic pathways of emission and climate projections. We applied the Maxent algorithm and evaluated over 100 candidate models per species, selecting those with above-random predictive performance based on high mean Area Under the Curve ratios (Range = 1.45 - 1.88). RESULTS: Our models revealed high ecological suitability for the five mosquitoes in Equatorial and Southern Africa and predict emerging ecologically suitable hotspots for arboviral presence in Southern and Eastern regions, with potential future expansion into North and West Africa. Changing patterns in precipitation, especially precipitation in dry and warm seasons, urbanization, human population, livestock density, and climate change exacerbated the geographic expansion of vectors and ecological risk for arbovirus presence. While the ecological risk to arbovirus presence was currently higher in rural areas, our projections indicated a potential future shift towards urban areas. CONCLUSION: Our study describes how ecological changes are shaping current and future ecological risk of neglected arboviral diseases in Africa and provides spatial maps to aid intersectoral targeted surveillance and vector control as part of early-warning systems.