MGDrivE 2: A simulation framework for gene drive systems incorporating seasonality and epidemiological dynamics

• DOI: 10.1371/journal.pcbi.1009030
• Publication Date: 2021-05-21T17:37:59Z
• Authors: Sean L. Wu; Jared B. Bennett; Héctor M. Sánchez C.; Andrew J. Dolgert; Tomás M. León; John M. Marshall
• Keywords: Gene drive

Interest in gene drive technology has continued to grow as promising new systems have been developed the lab and discussions are moving towards implementing field trials. The prospect of trials requires models that incorporate a significant degree ecological detail, including parameters change over time response environmental data such temperature rainfall, leading seasonal patterns mosquito population density. Epidemiological outcomes also growing importance, as: i) suitability construct for release will depend on its expected impact disease transmission, ii) initial measured entomological outcome modeled epidemiological outcome. We present MGDrivE 2 (Mosquito Gene Drive Explorer 2): development from 1 simulation framework investigates dynamics variety architectures their spread through spatially-explicit populations. Key strengths fundamental improvements are: ability vary with induce dynamics, an module accommodating reciprocal pathogen transmission between humans mosquitoes, iii) implementation based stochastic Petri nets enables efficient model formulation flexible implementation. Example simulations presented demonstrate application CRISPR-based split system intended disease-refractory into confinable reversible manner, incorporating time-varying rainfall data. evaluate human incidence prevalence. Further documentation use examples provided vignettes at project’s CRAN repository. is freely available open-source R package ( https://CRAN.R-project.org/package=MGDrivE2 ). intend provide tool capable modeling constructs they move closer infer transmission.