Modeling of arbovirus emergence

Emerging and re-emerging arboviral diseases are an increasing threat to global health, particularly in Africa, where rapid ecological and socio-economic changes are reshaping transmission patterns. Despite growing recognition of these drivers, gaps remain in understanding how ecology, evolution, and existing policy responses interact to influence arboviral emergence. This dissertation aims to address these gaps using an integrated, multi-scale modeling framework to investigate the ecological, evolutionary, and decision-making dimensions of emerging neglected arboviruses in Africa, with a focus on Wesselsbron virus (WSLV), Sindbis virus (SINV), and Middelburg virus (MIDV). In the first study, the current and future distribution of these viruses and their key vectors, Aedes circumluteolus and Aedes mcintoshi for WSLV; Culex univittatus and Culex pipiens for SINV; and Mansonia africana and Aedes mcintoshi is characterized using ecological niche modeling. The results indicate high ecological suitability across Equatorial and Southern Africa, with projected expansions into North and West Africa and a potential shift of risk from rural to increasingly urban areas. Precipitation patterns, urbanization, human population density, and livestock distribution emerged as key drivers of vector suitability and arboviral risk. In the second study, a Bayesian continuous phylogeographic analysis used SINV genomes sampled across Africa between 1952 and 2022 to reconstruct the long-term dispersal dynamics of SINV from eastern and central Africa around 1890 to the rest of Africa. The evolutionary rate was estimated at 4.33 × 10⁻⁴ substitutions/site/year at a mean dispersal velocity of 99 km/year. The findings reveal that viral dispersal is strongly influenced by landuse change, human mobility, ecological conditions, and socio-economic development. Together, these results demonstrate that arboviral emergence is shaped by both environmental and anthropogenic drivers. In the third study, participatory structured decision analysis integrating expert knowledge was applied to evaluate policy interventions for reducing arboviral disease risk in Uganda. Results highlighted that a One Health in All Policies approach—integrating biodiversity conservation, vector control, surveillance, inter-disciplinary actions, and public health measures—provides a more effective pathway to reducing arboviral disease risk in Uganda rather than single-sector interventions. The dissertation conceptualizes arboviral emergence as a socio-ecological system in which environmental change, viral evolution, and human decision-making are interconnected. The results highlight the limitations of fragmented, reactive surveillance systems and underscore the need for proactive, integrated approaches that incorporate ecological risk mapping, vector and genomic surveillance, and cross-sectoral decision-making. Key policy implications include strengthening vector- and ecology-inclusive early warning systems, integrating human, animal, environmental, and socioeconomic surveillance data, and operationalizing One Health through coordinated governance and evidence-based prioritization of interventions. Overall, this work advances understanding of neglected arboviruses in Africa by linking spatial risk, transmission dynamics, and policy responses within a unified analytical framework. It provides a foundation for developing anticipatory, multi-sectoral strategies to improve surveillance, guide targeted interventions, and enhance preparedness for arboviral disease emergence in a rapidly changing socio-ecological landscape.