Accelerating the adoption of novel mosquito control interventions by combining entomological, epidemiological and genetic data using modelling

Background The World Mosquito Programme (WMP) has led the development of wMel Wolbachia as a novel intervention for dengue. Early releases in Indonesia have been highly successful (77% reduction in dengue) but establishing Wolbachia in mosquito populations in other areas (Rio de Janeiro) has been more challenging. Objectives Objective 1: Identify gaps in Wolbachia coverage and understand why they occur Using mosquito trapping data from seven countries and a range of freely-available environmental data we will statistically test hypotheses of why successful implementation of Wolbachia is achievable in some areas but not others including the role of heterogeneous mosquito population genetics. Objective 2: Assess the epidemiological consequences of coverage gaps We will parameterise a mechanistic mathematical model that incorporates human movement using epidemiological data from WMP to test the impact of coverage gaps on transmission and elimination probability. This will be validated by phylogenetic analyses of dengue virus isolates within and outside Wolbachia release areas. Objective 3: Predict how other forms of vector control can support the successful deployment of Wolbachia By extending the mathematical model in Objective 2 to include conventional mosquito control tools, we will simulate new combinations of conventional and novel mosquito control tools to identify how implementation of Wolbachia can be optimised. Objective 4: Map where Wolbachia can eliminate dengue Predictions from Wolbachia models will be extrapolated using geostatistical frameworks to produce high resolution maps of the probability of dengue elimination across the seven countries currently considering scale up of Wolbachia.