MGDrivE 3: A decoupled vector-human framework for epidemiological simulation of mosquito genetic control tools and their surveillance.

Vector-borne diseases such as malaria cause massive morbidity and mortality throughout much of the world. Currently-available control measures, such as insecticide-based tools and antimalarial drugs, have limited impact and are waning in effectiveness, hence there is a need for novel tools to complement existing ones.Mosquito genetic control tools, such as gene drive systems and genetic versions of the sterile insect technique, offer a range of promising options, the development of which has greatly expanded since the advent of CRISPR-based gene-editing. Recently, we proposed MGDrivE 2 (Mosquito Gene Drive Explorer 2), which incorporates epidemiology into simulations of the dynamics of these systems in spatially-structured mosquito populations; however, that framework relied on simple model representations of vector-borne diseases. Here, we present MGDrivE 3, which decouples the vector portion of the model from the human portion, allowing the mosquito genetic control framework to be paired with more-detailed epidemiological frameworks. As an example, we implement the human transmission dynamics of the Imperial College London malaria model. We also incorporate a network of mosquito traps for surveillance. As genetic control technology edges closer towards field implementation, more detailed predictions of its epidemiological and biosafety implications are needed. We propose MGDrivE 3 to fulfill this role.