LEAPS-MPS: Development of Novel Multistage Models for Wolbachia-Based Strategies to Control Mosquito-Borne diseases

Mosquitoes are one of the deadliest creatures in the world because of the mosquito-borne diseases they can transmit, such as dengue fever, malaria, chikungunya, and Zika. Wolbachia-based intervention is a novel alternative mitigation strategy to control the spread of mosquito-borne diseases, as some Wolbachia-infected mosquitoes are less capable of transmitting diseases. This project proposes new and innovative mathematical models for the spread of Wolbachia infection in mosquitoes as a disease control which helps public health workers better understand the disease dynamics and optimize mitigation efforts. Besides the complex transmission dynamics, the models will also account for spatial and temporal heterogeneity that affects the transmission process. With these practical considerations, the proposed models can provide a comprehensive and solid understanding of Wolbachia-based interventions, and the results can better support public health workers to identify effective and sustainable approaches for reducing mosquito-borne diseases. The project will be based at a Hispanic-/minority-serving institution, where 67% of the students are minorities. The research efforts will be fully integrated with engaging students from various academic backgrounds in modeling infectious diseases and encouraging the participation of students from underrepresented groups. Leveraging the diverse student populations and their close connections to minority organizations, the research results will be disseminated through campus, professional, and media venues to achieve further impact on these groups and the general public audience. The proposed models will be built on solid epidemiological and mathematical foundations and will account for both the Wolbachia-induced biological effects and the heterogeneity from seasonality and mosquitoes' spatial dispersions. The project will derive models with different levels of biological resolutions to balance the model's predictability and analytical challenge, and it includes three specific aims: (1) analysis of small-scale models to gain a basic qualitative understanding of the Wolbachia establishment, in particular, the characterization of critical threshold condition for Wolbachia spreading and spatial infection wave propagation; this provides important insights into (2) the design of full-scale models that capture details of the biological effects. The numerical study of the full-scale models will inform practical scenarios that concern the field releases and identify efficient practices for establishing Wolbachia in the field. (3) The PI will also conduct detailed model parametrizations and quantify model uncertainty at different stages of the project. The local and global sensitivity analysis approaches will be employed to quantify the uncertainty in the models and determine their relative importance to the model predictions so that they can be more useful and interpretable by the public health community. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.