Evidence map›Paper›PMID 32584814›Full record

ArticlePLoS biology2020

Mapping trends in insecticide resistance phenotypes in African malaria vectors.

Penelope A Hancock, Chantal J M Hendriks, Julie-Anne Tangena, Harry Gibson, Janet Hemingway, Michael Coleman, Peter W Gething, Ewan Cameron, Samir Bhatt, Catherine L Moyes

Abstract read
In one paragraph

Article in PLoS biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 108 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
108citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

108 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  12. Modeling framework to demonstrate elimination of a vector population: Tsetse elimination in Chad.Proceedings of the National Academy of Sciences of the United States of America · 2026
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48 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Penelope A HancockBig Data Institute, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-5531-1082
Chantal J M HendriksBig Data Institute, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-6749-7232
Julie-Anne TangenaDepartment of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.ORCID 0000-0002-8188-4498
Harry GibsonBig Data Institute, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-6779-3250
Janet HemingwayDepartment of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.ORCID 0000-0002-3200-7173
Michael ColemanDepartment of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.ORCID 0000-0003-4186-3526
Peter W GethingTelethon Kids Institute, Perth Children's Hospital, Perth, Australia.
Ewan CameronBig Data Institute, University of Oxford, Oxford, United Kingdom.
Samir BhattDepartment of Infectious Disease Epidemiology, Imperial College, St Mary's Hospital, London, United Kingdom.ORCID 0000-0002-0891-4611
Catherine L MoyesBig Data Institute, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-8028-4079

Funding

Medical Research Council MR/R015600/1Wellcome TrustWellcome Trust 108440/Z/15/Z
6 · The paper itself

Abstract

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.

Indexed as

Insecticide ResistanceAfricaDDTMachine LearningMalariaMosquito VectorsNitrilesPhenotypePrevalencePyrethrinsSpatio-Temporal AnalysisDDTdecamethrinNitrilesPyrethrins

Identifiers

PMID32584814
PMCPMC7316233

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.