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Mapping trends in insecticide resistance phenotypes in African malaria vectors
Mitigating the threat of insecticide resistance in African malaria vector populations requires comprehensive information about where resistance occurs, to what degree, and how this has changed over time. Estimating these trends is complicated by the sparse, heterogeneous distribution of observations...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7316233/ https://www.ncbi.nlm.nih.gov/pubmed/32584814 http://dx.doi.org/10.1371/journal.pbio.3000633 |
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author | Hancock, Penelope A. Hendriks, Chantal J. M. Tangena, Julie-Anne Gibson, Harry Hemingway, Janet Coleman, Michael Gething, Peter W. Cameron, Ewan Bhatt, Samir Moyes, Catherine L. |
author_facet | Hancock, Penelope A. Hendriks, Chantal J. M. Tangena, Julie-Anne Gibson, Harry Hemingway, Janet Coleman, Michael Gething, Peter W. Cameron, Ewan Bhatt, Samir Moyes, Catherine L. |
author_sort | Hancock, Penelope A. |
collection | PubMed |
description | Mitigating the threat of insecticide resistance in African malaria vector populations requires comprehensive information about where resistance occurs, to what degree, and how this has changed over time. Estimating these trends is complicated by the sparse, heterogeneous distribution of observations of resistance phenotypes in field populations. We use 6,423 observations of the prevalence of resistance to the most important vector control insecticides to inform a Bayesian geostatistical ensemble modelling approach, generating fine-scale predictive maps of resistance phenotypes in mosquitoes from the Anopheles gambiae complex across Africa. Our models are informed by a suite of 111 predictor variables describing potential drivers of selection for resistance. Our maps show alarming increases in the prevalence of resistance to pyrethroids and DDT across sub-Saharan Africa from 2005 to 2017, with mean mortality following insecticide exposure declining from almost 100% to less than 30% in some areas, as well as substantial spatial variation in resistance trends. |
format | Online Article Text |
id | pubmed-7316233 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-73162332020-06-29 Mapping trends in insecticide resistance phenotypes in African malaria vectors Hancock, Penelope A. Hendriks, Chantal J. M. Tangena, Julie-Anne Gibson, Harry Hemingway, Janet Coleman, Michael Gething, Peter W. Cameron, Ewan Bhatt, Samir Moyes, Catherine L. PLoS Biol Research Article Mitigating the threat of insecticide resistance in African malaria vector populations requires comprehensive information about where resistance occurs, to what degree, and how this has changed over time. Estimating these trends is complicated by the sparse, heterogeneous distribution of observations of resistance phenotypes in field populations. We use 6,423 observations of the prevalence of resistance to the most important vector control insecticides to inform a Bayesian geostatistical ensemble modelling approach, generating fine-scale predictive maps of resistance phenotypes in mosquitoes from the Anopheles gambiae complex across Africa. Our models are informed by a suite of 111 predictor variables describing potential drivers of selection for resistance. Our maps show alarming increases in the prevalence of resistance to pyrethroids and DDT across sub-Saharan Africa from 2005 to 2017, with mean mortality following insecticide exposure declining from almost 100% to less than 30% in some areas, as well as substantial spatial variation in resistance trends. Public Library of Science 2020-06-25 /pmc/articles/PMC7316233/ /pubmed/32584814 http://dx.doi.org/10.1371/journal.pbio.3000633 Text en © 2020 Hancock et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Hancock, Penelope A. Hendriks, Chantal J. M. Tangena, Julie-Anne Gibson, Harry Hemingway, Janet Coleman, Michael Gething, Peter W. Cameron, Ewan Bhatt, Samir Moyes, Catherine L. Mapping trends in insecticide resistance phenotypes in African malaria vectors |
title | Mapping trends in insecticide resistance phenotypes in African malaria vectors |
title_full | Mapping trends in insecticide resistance phenotypes in African malaria vectors |
title_fullStr | Mapping trends in insecticide resistance phenotypes in African malaria vectors |
title_full_unstemmed | Mapping trends in insecticide resistance phenotypes in African malaria vectors |
title_short | Mapping trends in insecticide resistance phenotypes in African malaria vectors |
title_sort | mapping trends in insecticide resistance phenotypes in african malaria vectors |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7316233/ https://www.ncbi.nlm.nih.gov/pubmed/32584814 http://dx.doi.org/10.1371/journal.pbio.3000633 |
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