Beeton NJ, Wilkins A, Ickowicz A, Hayes KR, Hosack GR. Spatial modelling for population replacement of mosquito vectors at continental scale.
PLoS Comput Biol 2022;
18:e1009526. [PMID:
35648783 PMCID:
PMC9191746 DOI:
10.1371/journal.pcbi.1009526]
[Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 06/13/2022] [Accepted: 04/22/2022] [Indexed: 11/24/2022] Open
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.
Conventional control methods have dramatically reduced malaria, but it still kills over 300,000 children in Africa each year, and this number could increase as their effectiveness wanes. Novel control methods using gene drives rapidly reduce or modify malaria vector populations in laboratory settings, and hence are now being considered for field applications. We use modelling to assess how a gene drive might spread and persist in the malaria-carrying subspecies Anopheles gambiae sensu stricto (s.s.) and Anopheles coluzzii. These two subspecies interbreed and compete, so we model how these interactions affect the spread of the drive at a continental scale. In scenarios that allow mosquitoes to travel on prevailing wind currents, we find that a gene drive can potentially spread across national borders—and jump from offshore islands to the African mainland—but spread is eventually arrested when the drive allele is ousted by a resistant allele. As we learn more about the population dynamics of both genetically modified and wild mosquitoes, and as gene drive systems are further developed to allow local containment and evade resistance, our model will be able to answer more detailed questions about how they can be applied in the field effectively and safely.
Collapse