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Efficient production of male Wolbachia-infected Aedes aegypti mosquitoes enables large-scale suppression of wild populations.

Jacob E CrawfordDavid W ClarkeVictor CriswellMark DesnoyerDevon CornelBrittany DeeganKyle GongKaycie C HopkinsPaul HowellJustin S HydeJosh LivniCharlie BehlingRenzo BenzaWilla ChenKaren L DobsonCraig EldershawDaniel GreeleyYi HanBridgette HughesEvdoxia KakaniJoe KarbowskiAngus KitchellErika LeeTeresa LinJianyi LiuMartin LozanoWarren MacDonaldJames W MainsMatty MetlitzSara N MitchellDavid MooreJohanna R OhmKathleen ParkesAlexandra PorshnikoffChris RobuckMartin SheridanRobert SobeckiPeter SmithJessica StevensonJordan SullivanBrian WassonAllison M WeakleyMark WilhelmJoshua WonAri YasunagaWilliam C ChanJodi HolemanNigel SnoadLinus UpsonTiantian ZhaStephen L DobsonF Steven MulliganPeter MassaroBradley J White
Published in: Nature biotechnology (2020)
The range of the mosquito Aedes aegypti continues to expand, putting more than two billion people at risk of arboviral infection. The sterile insect technique (SIT) has been used to successfully combat agricultural pests at large scale, but not mosquitoes, mainly because of challenges with consistent production and distribution of high-quality male mosquitoes. We describe automated processes to rear and release millions of competitive, sterile male Wolbachia-infected mosquitoes, and use of these males in a large-scale suppression trial in Fresno County, California. In 2018, we released 14.4 million males across three replicate neighborhoods encompassing 293 hectares. At peak mosquito season, the number of female mosquitoes was 95.5% lower (95% CI, 93.6-96.9) in release areas compared to non-release areas, with the most geographically isolated neighborhood reaching a 99% reduction. This work demonstrates the high efficacy of mosquito SIT in an area ninefold larger than in previous similar trials, supporting the potential of this approach in public health and nuisance-mosquito eradication programs.
Keyphrases
  • aedes aegypti
  • zika virus
  • public health
  • dengue virus
  • machine learning
  • risk assessment
  • clinical trial
  • heavy metals
  • randomized controlled trial
  • study protocol
  • open label
  • phase ii