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Evaluating insecticide resistance across African districts to aid malaria control decisions.


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.

SUBMITTER: Moyes CL 

PROVIDER: S-EPMC7486715 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Evaluating insecticide resistance across African districts to aid malaria control decisions.

Moyes Catherine L CL   Athinya Duncan K DK   Seethaler Tara T   Battle Katherine E KE   Sinka Marianne M   Hadi Melinda P MP   Hemingway Janet J   Coleman Michael M   Hancock Penelope A PA  

Proceedings of the National Academy of Sciences of the United States of America 20200825 36


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 predicti  ...[more]

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