Speaker
Description
Despite decades of efforts to control mosquito-borne diseases, the global burden of these diseases remains high due to their complex biological and immunological dynamics. While extensive research has focused on vector-host or between-host transmissions, the within-vector mechanisms remain poorly understood. This gap is critical to fill because mosquitoes have relatively short lifespans, and their midgut acts as the primary bottleneck for viral progression. Following an infectious blood meal, viruses must first infect midgut epithelial cells before reaching the salivary glands and becoming transmissible to the next host. Understanding midgut infection is therefore central to designing more targeted interventions, which could complement traditional vector control strategies and help address the current lack of effective prophylactic drugs and vaccines.
In this study, we establish an iterative cycle between modelling and experiments. We develop a 3D stochastic model of midgut infection dynamics and show that, with parameters informed by experimental assays, the model can reproduce the clustered infection patterns observed in dengue-infected midguts of Aedes aegypti mosquitoes. This framework provides a quantitative tool to investigate the pivotal role of the mosquito midgut in shaping infection dynamics, and offers a basis for designing targeted vector control strategies. It can also be extended to study other mosquito-borne viruses.
