Simplifying mosquito sampling to estimate community biting exposure and malaria indoor vector control impact

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Abstract Insecticide-treated nets (ITNs) are most effective against malaria if mosquitoes attempt to bite people when they are in bed. Collecting the biting behaviour data required to quantify a key metric - the proportion of bites taken when people are in bed - is challenging. We tested the reliability of a simplified mosquito sampling method against data from a published systematic review. Using the methodology in the remote, malaria-endemic Bijagos archipelago, Guinea-Bissau, we estimate this proportion is 0.95 (95% Credible intervals, CrI: 0.84, 1.00). Transmission modelling suggests that pyrethroid-only ITNs in a Bijagos-like setting could avert 86% of Plasmodium falciparum clinical cases in under 5-year-olds (95% CrI: 77, 89%), compared to without ITNs. Due to agricultural work, some islanders sleep without ITNs in temporary outdoor shelters, potentially reducing the predicted population-level impact of ITNs by 35%. Our methodology increases the feasibility of monitoring the impact of indoor malaria control interventions in resource-limited settings.
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Simplifying mosquito sampling to estimate community biting exposure and malaria indoor vector control impact | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Simplifying mosquito sampling to estimate community biting exposure and malaria indoor vector control impact Nilani Chandradeva, Elizabeth Pretorius, Eunice Teixeira da Silva, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7065171/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Insecticide-treated nets (ITNs) are most effective against malaria if mosquitoes attempt to bite people when they are in bed. Collecting the biting behaviour data required to quantify a key metric - the proportion of bites taken when people are in bed - is challenging. We tested the reliability of a simplified mosquito sampling method against data from a published systematic review. Using the methodology in the remote, malaria-endemic Bijagos archipelago, Guinea-Bissau, we estimate this proportion is 0.95 (95% Credible intervals, CrI: 0.84, 1.00). Transmission modelling suggests that pyrethroid-only ITNs in a Bijagos-like setting could avert 86% of Plasmodium falciparum clinical cases in under 5-year-olds (95% CrI: 77, 89%), compared to without ITNs. Due to agricultural work, some islanders sleep without ITNs in temporary outdoor shelters, potentially reducing the predicted population-level impact of ITNs by 35%. Our methodology increases the feasibility of monitoring the impact of indoor malaria control interventions in resource-limited settings. Health sciences/Medical research/Epidemiology Biological sciences/Ecology/Ecological epidemiology Biological sciences/Zoology/Entomology Health sciences/Diseases/Infectious diseases/Malaria Biological sciences/Computational biology and bioinformatics/Statistical methods Full Text Additional Declarations There is NO Competing Interest. Supplementary Files ChandradevaetalSupplementaryInformation.pdf Supplementary Information Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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