Antipathogen genes and the replacement of disease‐vectoring mosquito populations: a model‐based evaluation
Year: 2014
Type: article
Abstract: Recently, genetic strategies aimed at controlling populations of disease-vectoring mosquitoes have received considerable attention as alternatives to traditional measures. Theoretical studies have shown that female-killing (FK), antipathogen (AP), and reduce and replace (R&R) strategies can each decrease the number competent vectors. In this study, we utilize a mathematical model to evaluate impacts on competent Aedes aegypti populations of FK, AP, and R&R releases as well as hybrid strategies that result from combinations of these three approaches. We show that while the ordering of efficacy of these strategies depends upon population life history parameters, sex ratio of releases, and switch time in combination strategies, AP-only and R&R/AP releases typically lead to the greatest long-term reduction in competent vectors. R&R-only releases are often less effective at long-term reduction of competent vectors than AP-only releases or R&R/AP releases. Furthermore, the reduction in competent vectors caused by AP-only releases is easier to maintain than that caused by FK-only or R&R-only releases even when the AP gene confers a fitness cost. We discuss the roles that density dependence and inclusion of females play in the order of efficacy of the strategies. We anticipate that our results will provide added impetus to continue developing AP strategies.
Source: Evolutionary Applications
DOI: 10.1111/eva.12219
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $4,320
Funders: Foundation for the National Institutes of Health, U.S. Department of Homeland Security, Bill and Melinda Gates Foundation, W. M. Keck Foundation, University of California, North Carolina State University, Isaac Newton Institute for Mathematical Sciences, University of Pretoria, National Institutes of Health, National Institute of General Medical Sciences, National Institute of Allergy and Infectious Diseases, Fogarty International Center, Division of Mathematical Sciences
OpenAlex ID: W2061586504