Modelling the Wolbachia incompatible insect technique: strategies for effective mosquito population elimination
BackgroundThe Wolbachia incompatible insect technique (IIT) shows promise as a method for eliminating populations of invasive mosquitoes such as Aedes aegypti (Linnaeus) (Diptera: Culicidae) and reducing the incidence of vector-borne diseases such as dengue, chikungunya and Zika. Successful implemen...
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Veröffentlicht in: | BMC biology 2020-11, Vol.18 (1), p.161-161, Article 161 |
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Sprache: | eng |
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Zusammenfassung: | BackgroundThe Wolbachia incompatible insect technique (IIT) shows promise as a method for eliminating populations of invasive mosquitoes such as Aedes aegypti (Linnaeus) (Diptera: Culicidae) and reducing the incidence of vector-borne diseases such as dengue, chikungunya and Zika. Successful implementation of this biological control strategy relies on high-fidelity separation of male from female insects in mass production systems for inundative release into landscapes. Processes for sex-separating mosquitoes are typically error-prone and laborious, and IIT programmes run the risk of releasing Wolbachia-infected females and replacing wild mosquito populations.ResultsWe introduce a simple Markov population process model for studying mosquito populations subjected to a Wolbachia-IIT programme which exhibit an unstable equilibrium threshold. The model is used to study, in silico, scenarios that are likely to yield a successful elimination result. Our results suggest that elimination is best achieved by releasing males at rates that adapt to the ever-decreasing wild population, thus reducing the risk of releasing Wolbachia-infected females while reducing costs.ConclusionsWhile very high-fidelity sex separation is required to avoid establishment, release programmes tend to be robust to the release of a small number of Wolbachia-infected females. These findings will inform and enhance the next generation of Wolbachia-IIT population control strategies that are already showing great promise in field trials. |
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ISSN: | 1741-7007 1741-7007 |
DOI: | 10.1186/s12915-020-00887-0 |