Evidence map›Paper›PMID 32971006›Full record

ArticleThe Lancet. Infectious diseases2021

Indirect effects of the COVID-19 pandemic on malaria intervention coverage, morbidity, and mortality in Africa: a geospatial modelling analysis.

Daniel J Weiss, Amelia Bertozzi-Villa, Susan F Rumisha, Punam Amratia, Rohan Arambepola, Katherine E Battle, Ewan Cameron, Elisabeth Chestnutt, Harry S Gibson, Joseph Harris and 11 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Lancet. Infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 140 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
140citing papers in PubMed, 2 pooled it
6.2field-weighted citation impact, top 3% of its field
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

140 citing papers in PubMed, 2 syntheses or guidelines pooled it, 249 citations in OpenAlex.

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80 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

21 authors at 8 institutions in 5 countries.

Daniel J WeissTelethon Kids Institute, Perth Children's Hospital, Perth, WA, Australia; Curtin University, Perth, WA, Australia; Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Amelia Bertozzi-VillaOxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK; Institute for Disease Modeling, Bellevue, WA, USA.
Susan F RumishaOxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK; National Institute for Medical Research, Dar es Salaam, Tanzania.
Punam AmratiaTelethon Kids Institute, Perth Children's Hospital, Perth, WA, Australia.
Rohan ArambepolaOxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Katherine E BattleInstitute for Disease Modeling, Bellevue, WA, USA.
Ewan CameronTelethon Kids Institute, Perth Children's Hospital, Perth, WA, Australia; Curtin University, Perth, WA, Australia.
Elisabeth ChestnuttOxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Harry S GibsonOxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Joseph HarrisTelethon Kids Institute, Perth Children's Hospital, Perth, WA, Australia.
Suzanne KeddieTelethon Kids Institute, Perth Children's Hospital, Perth, WA, Australia.
Justin J MillarOxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Jennifer RozierTelethon Kids Institute, Perth Children's Hospital, Perth, WA, Australia.
Tasmin L SymonsOxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Camilo Vargas-RuizOxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Simon I HayInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
David L SmithInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Pedro L AlonsoGlobal Malaria Programme, World Health Organization, Geneva, Switzerland.
Abdisalan M NoorGlobal Malaria Programme, World Health Organization, Geneva, Switzerland.
Samir BhattDepartment of Infectious Disease Epidemiology, Imperial College London, London, UK.
Peter W GethingTelethon Kids Institute, Perth Children's Hospital, Perth, WA, Australia; Curtin University, Perth, WA, Australia. Electronic address: peter.gething@telethonkids.org.au.
University of Oxford · GBPrincess Margaret Hospital for Children · AUCurtin University · AUUniversity of Washington · USWorld Health Organization · CHBellevue Hospital Center · USImperial College London · GBThe Kids Research Institute Australia · AU

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundSubstantial progress has been made in reducing the burden of malaria in Africa since 2000, but those gains could be jeopardised if the COVID-19 pandemic affects the availability of key malaria control interventions. The aim of this study was to evaluate plausible effects on malaria incidence and mortality under different levels of disruption to malaria control.

methodsUsing an established set of spatiotemporal Bayesian geostatistical models, we generated geospatial estimates across malaria-endemic African countries of the clinical case incidence and mortality of malaria, incorporating an updated database of parasite rate surveys, insecticide-treated net (ITN) coverage, and effective treatment rates. We established a baseline estimate for the anticipated malaria burden in Africa in the absence of COVID-19-related disruptions, and repeated the analysis for nine hypothetical scenarios in which effective treatment with an antimalarial drug and distribution of ITNs (both through routine channels and mass campaigns) were reduced to varying extents.

findingsWe estimated 215·2 (95% uncertainty interval 143·7-311·6) million cases and 386·4 (307·8-497·8) thousand deaths across malaria-endemic African countries in 2020 in our baseline scenario of undisrupted intervention coverage. With greater reductions in access to effective antimalarial drug treatment, our model predicted increasing numbers of cases and deaths: 224·1 (148·7-326·8) million cases and 487·9 (385·3-634·6) thousand deaths with a 25% reduction in antimalarial drug coverage; 233·1 (153·7-342·5) million cases and 597·4 (468·0-784·4) thousand deaths with a 50% reduction; and 242·3 (158·7-358·8) million cases and 715·2 (556·4-947·9) thousand deaths with a 75% reduction. Halting planned 2020 ITN mass distribution campaigns and reducing routine ITN distributions by 25%-75% also increased malaria burden to a total of 230·5 (151·6-343·3) million cases and 411·7 (322·8-545·5) thousand deaths with a 25% reduction; 232·8 (152·3-345·9) million cases and 415·5 (324·3-549·4) thousand deaths with a 50% reduction; and 234·0 (152·9-348·4) million cases and 417·6 (325·5-553·1) thousand deaths with a 75% reduction. When ITN coverage and antimalarial drug coverage were synchronously reduced, malaria burden increased to 240·5 (156·5-358·2) million cases and 520·9 (404·1-691·9) thousand deaths with a 25% reduction; 251·0 (162·2-377·0) million cases and 640·2 (492·0-856·7) thousand deaths with a 50% reduction; and 261·6 (167·7-396·8) million cases and 768·6 (586·1-1038·7) thousand deaths with a 75% reduction.

interpretationUnder pessimistic scenarios, COVID-19-related disruption to malaria control in Africa could almost double malaria mortality in 2020, and potentially lead to even greater increases in subsequent years. To avoid a reversal of two decades of progress against malaria, averting this public health disaster must remain an integrated priority alongside the response to COVID-19.

fundingBill and Melinda Gates Foundation; Channel 7 Telethon Trust, Western Australia.

Indexed as

SARS-CoV-2AfricaAntimalarialsBayes TheoremCOVID-19HumansIncidenceInsecticide-Treated BednetsMalariaModels, StatisticalMorbidityAntimalarials

Identifiers

PMID32971006
PMCPMC7505634
OpenAlexW3087003139

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.