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.