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• W3080712139 abstract "Significance Malaria control in Africa largely relies on the use of insecticides to prevent mosquitoes from transmitting the malaria parasite to humans; however, these mosquitoes have evolved resistance to these insecticides. To manage this threat to malaria control, it is vital that we map locations where the prevalence of resistance exceeds thresholds defined by insecticide resistance management plans. A geospatial model and data from Africa are used to predict locations where thresholds of resistance linked to specific recommended actions are exceeded. This model is shown to provide more accurate next-year predictions than two simpler approaches. The model is used to generate maps that aid insecticide resistance management planning and that allow targeted deployment of interventions that counter specific mechanisms of resistance." @default.
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• W3080712139 date "2020-08-25" @default.
• W3080712139 modified "2023-10-16" @default.
• W3080712139 title "Evaluating insecticide resistance across African districts to aid malaria control decisions" @default.
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• W3080712139 doi "https://doi.org/10.1073/pnas.2006781117" @default.
• W3080712139 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7486715" @default.
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