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Evaluating insecticide resistance across African districts to aid malaria control decisions.
Moyes, Catherine L; Athinya, Duncan K; Seethaler, Tara; Battle, Katherine E; Sinka, Marianne; Hadi, Melinda P; Hemingway, Janet; Coleman, Michael; Hancock, Penelope A.
Afiliação
  • Moyes CL; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom; catherinemoyes@gmail.com janet.hemingway@lstmed.ac.uk penny.hancock@bdi.ox.ac.uk.
  • Athinya DK; Vestergaard Frandsen (EA) Ltd, Nairobi, Kenya.
  • Seethaler T; Clinton Health Access Initiative, Boston, MA 02127.
  • Battle KE; Institute for Disease Modeling, Bellevue, WA 98005.
  • Sinka M; Department of Zoology, University of Oxford, Oxford OX1 3RB, United Kingdom.
  • Hadi MP; Vestergaard SA, CH - 1003 Lausanne, Switzerland.
  • Hemingway J; Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool L3 5QA, United Kingdom catherinemoyes@gmail.com janet.hemingway@lstmed.ac.uk penny.hancock@bdi.ox.ac.uk.
  • Coleman M; Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool L3 5QA, United Kingdom.
  • Hancock PA; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom; catherinemoyes@gmail.com janet.hemingway@lstmed.ac.uk penny.hancock@bdi.ox.ac.uk.
Proc Natl Acad Sci U S A ; 117(36): 22042-22050, 2020 09 08.
Article em En | MEDLINE | ID: mdl-32843339
ABSTRACT
Malaria vector control may be compromised by resistance to insecticides in vector populations. Actions to mitigate against resistance rely on surveillance using standard susceptibility tests, but there are large gaps in the monitoring data across Africa. Using a published geostatistical ensemble model, we have generated maps that bridge these gaps and consider the likelihood that resistance exceeds recommended thresholds. Our results show that this model provides more accurate next-year predictions than two simpler approaches. We have used the model to generate district-level maps for the probability that pyrethroid resistance in Anopheles gambiae s.l. exceeds the World Health Organization thresholds for susceptibility and confirmed resistance. In addition, we have mapped the three criteria for the deployment of piperonyl butoxide-treated nets that mitigate against the effects of metabolic resistance to pyrethroids. This includes a critical review of the evidence for presence of cytochrome P450-mediated metabolic resistance mechanisms across Africa. The maps for pyrethroid resistance are available on the IR Mapper website, where they can be viewed alongside the latest survey data.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Resistência a Inseticidas / Controle de Mosquitos / Mosquitos Vetores / Inseticidas / Malária / Anopheles Tipo de estudo: Evaluation_studies / Prognostic_studies Limite: Animals / Humans País/Região como assunto: Africa Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Resistência a Inseticidas / Controle de Mosquitos / Mosquitos Vetores / Inseticidas / Malária / Anopheles Tipo de estudo: Evaluation_studies / Prognostic_studies Limite: Animals / Humans País/Região como assunto: Africa Idioma: En Ano de publicação: 2020 Tipo de documento: Article