Dengue, Chikungunya, Zika and other mosquito-borne diseases continue to pose a major global health burden through much of the world, despite the widespread distribution of insecticide-based tools and antimalarial drugs. Consequently, there is interest in novel strategies to control these diseases, including the release of genetically sterile male mosquitoes, mosquitoes transfected with Wolbachia, and mosquitoes engineered with gene drive systems. The safety and effectiveness of these strategies and considerations regarding trial design and implementation are critically dependent upon a detailed understanding of mosquito movement at both fine and broad spatial scales, yet there are major gaps in our understanding of these movement patterns. The declining cost of genome sequencing and novel methods for analyzing geocoded genomic data provide opportunities to address these knowledge gaps. In this project, we propose to devise a robust approach for inferring fine-scale mosquito dispersal patterns and their impact on innovative vector control strategies. We propose to use in silico simulations of mosquito ecology and preliminary geocoded mosquito genomic data collected from Fresno, California to determine sampling routines capable of quantifying dispersal patterns, population sizes and mating patterns using genetic kinship analyses (Aim 1). Results from these analyses will iteratively inform sampling schemes for two rounds of subsequent collections of Aedes aegypti, the mosquito vector of dengue, Chikungunya and Zika viruses, in Yishun, Singapore (Aim 2). Genome sequencing and kinship analyses will be used to quantify Ae. aegypti movement patterns, population sizes and mating behaviors at this location, and to parameterize spatially-structured 3D models of Ae. aegypti population dynamics. The resulting models will be used to explore biosafety, trial design and implementation considerations for novel vector control strategies including: i) population suppression systems such as Wolbachia-infected males and genetically sterile males, and ii) population replacement systems such as population transfection with Wolbachia, localized systems such as chromosomal translocations, and non- localized systems such as homing-based gene drive (Aim 3). We expect the proposed research to lead to the development of greatly enhanced surveillance strategies to infer fine-scale mosquito movement patterns and other demographic parameters, and to help inform the safe application of several novel and highly promising strategies for the control of dengue, Chikungunya and Zika viruses and other devastating mosquito-borne diseases.
Dengue, Chikungunya, Zika and other mosquito-borne diseases continue to pose a major global health burden through much of the world, despite the widespread distribution of insecticides and other interventions. Novel strategies have been proposed to control these diseases, including the release of mosquitoes transfected with Wolbachia and engineered with gene drive systems, the safety and efficacy of which critically depends on a detailed understanding of mosquito movement. In this project, we will use genetic data to quantify the fine- scale movement patterns of Aedes aegypti mosquito vectors and explore implications for novel intervention strategies.
