Spatial modelling for population replacement of mosquito vectors at continental scale

PLoS Comput Biol. 2022 Jun 1;18(6):e1009526. doi: 10.1371/journal.pcbi.1009526. eCollection 2022 Jun.

Abstract

Malaria is one of the deadliest vector-borne diseases in the world. Researchers are developing new genetic and conventional vector control strategies to attempt to limit its burden. Novel control strategies require detailed safety assessment to ensure responsible and successful deployments. Anopheles gambiae sensu stricto (s.s.) and Anopheles coluzzii, two closely related subspecies within the species complex Anopheles gambiae sensu lato (s.l.), are among the dominant malaria vectors in sub-Saharan Africa. These two subspecies readily hybridise and compete in the wild and are also known to have distinct niches, each with spatially and temporally varying carrying capacities driven by precipitation and land use factors. We model the spread and persistence of a population-modifying gene drive system in these subspecies across sub-Saharan Africa by simulating introductions of genetically modified mosquitoes across the African mainland and its offshore islands. We explore transmission of the gene drive between the two subspecies that arise from different hybridisation mechanisms, the effects of both local dispersal and potential wind-aided migration to the spread, and the development of resistance to the gene drive. Given the best current available knowledge on the subspecies' life histories, we find that an introduced gene drive system with typical characteristics can plausibly spread from even distant offshore islands to the African mainland with the aid of wind-driven migration, with resistance beginning to take over within a decade. Our model accounts for regional to continental scale mechanisms, and demonstrates a range of realistic dynamics including the effect of prevailing wind on spread and spatio-temporally varying carrying capacities for subspecies. As a result, it is well-placed to answer future questions relating to mosquito gene drives as important life history parameters become better understood.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Africa South of the Sahara
  • Animals
  • Anopheles* / genetics
  • Malaria*
  • Mosquito Control
  • Mosquito Vectors / genetics
  • Population Dynamics

Grants and funding

NJB, GRH, AI and KRH contribution to this study was funded by CSIRO Data61 and CSIRO Health and Biosecurity. AW contribution was funded by CSIRO Health and Biosecurity and CSIRO Mineral Resources. The CSIRO funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.