Comparative assessment of gene drive release patterns and spread with a hex-based model for large-scale simulations

Abstract

Spatial population genetic and ecological modeling is often necessary to predict outcomes accurately. One example is gene drive, a rapid process involving spread of gene drive alleles through a population, usually to suppress pests or reduce transmission of vector-borne disease. Several existing models have been used to assess gene drive and other spatial processes. However, each of these has limitations, such as high computational cost and limited scalability, difficulty in incorporating environmental factors and complex lifecycles, or potentially simplified spatial structure. To overcome these challenges, we propose a hexagon-based computational framework that is designed to mimic continuous space for rapid genetic wave advances. This allows us to accurately simulate a larger spatial domain with lower computational investment. We implemented this model and compared the wave speeds of different gene drives with those obtained from other models. The results showed good agreement when hexagon width and dispersal were properly calibrated. We then determined optimal circular and linear (along roads) release patterns for a variety of gene drives and Wolbachia bacteria. To demonstrate the application of our framework to a hypothetical scenario, we constructed a model Culex quinquefasciatus mosquitoes on Hainan Island. We then evaluated the outcome of different gene drive release strategies, showing the transgenic insect release level necessary to achieve high gene drive coverage and how this could be further optimized based on mosquito and human distribution. Overall, our hex-based population genetic framework provides a flexible platform for realistic and large-scale models for gene drive and related applications.