Evidence map›Paper›PMID 29587882›Full record

SynthesisParasites & vectors2018

Comparative effectiveness of malaria prevention measures: a systematic review and network meta-analysis.

Kinley Wangdi, Luis Furuya-Kanamori, Justin Clark, Jan J Barendregt, Michelle L Gatton, Cathy Banwell, Gerard C Kelly, Suhail A R Doi, Archie C A Clements

Abstract readSystematic ReviewNetwork Meta-Analysis
In one paragraph

Synthesis in Parasites & vectors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 5 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

32 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  14. Role of cytokines in immunomodulation during malaria clearance.Annals of medicine and surgery (2012) · 2024
    Review
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  16. Updates on traditional methods for combating malaria and emergingFrontiers in cellular and infection microbiology · 2024
    Review
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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

9 authors.

Kinley WangdiResearch School of Population Health, College of Health and Medicine, The Australian National University, ACT, Canberra, Australia. kinley.wangdi@anu.edu.au.
Luis Furuya-KanamoriResearch School of Population Health, College of Health and Medicine, The Australian National University, ACT, Canberra, Australia.
Justin ClarkCentre for Research in Evidence-Based Practice (CREBP), Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia.
Jan J BarendregtSchool of Public Health, The University of Queensland, Brisbane, Queensland, Australia.
Michelle L GattonSchool of Public Health & Social Work, Queensland University of Technology, Brisbane, Queensland, Australia.
Cathy BanwellResearch School of Population Health, College of Health and Medicine, The Australian National University, ACT, Canberra, Australia.
Gerard C KellyResearch School of Population Health, College of Health and Medicine, The Australian National University, ACT, Canberra, Australia.
Suhail A R DoiResearch School of Population Health, College of Health and Medicine, The Australian National University, ACT, Canberra, Australia.
Archie C A ClementsResearch School of Population Health, College of Health and Medicine, The Australian National University, ACT, Canberra, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMalaria causes significant morbidity and mortality worldwide. There are several preventive measures that are currently employed, including insecticide-treated nets (ITNs, including long-lasting insecticidal nets and insecticidal-treated bed nets), indoor residual spraying (IRS), prophylactic drugs (PD), and untreated nets (UN). However, it is unclear which measure is the most effective for malaria prevention. We therefore undertook a network meta-analysis to compare the efficacy of different preventive measures on incidence of malaria infection.

methodsA systematic literature review was undertaken across four medical and life sciences databases (PubMed, Cochrane Central, Embase, and Web of Science) from their inception to July 2016 to compare the effectiveness of different preventive measures on malaria incidence. Data from the included studies were analysed for the effectiveness of several measures against no intervention (NI). This was carried out using an automated generalized pairwise modeling (GPM) framework for network meta-analysis to generate mixed treatment effects against a common comparator of no intervention (NI).

resultsThere were 30 studies that met the inclusion criteria from 1998-2016. The GPM framework led to a final ranking of effectiveness of measures in the following order from best to worst: PD, ITN, IRS and UN, in comparison with NI. However, only ITN (RR: 0.49, 95% CI: 0.32-0.74) showed precision while other methods [PD (RR: 0.24, 95% CI: 0.004-15.43), IRS (RR: 0.55, 95% CI: 0.20-1.56) and UN (RR: 0.73, 95% CI: 0.28-1.90)] demonstrating considerable uncertainty associated with their point estimates.

conclusionCurrent evidence is strong for the protective effect of ITN interventions in malaria prevention. Even though ITNs were found to be the only preventive measure with statistical support for their effectiveness, the role of other malaria control measures may be important adjuncts in the global drive to eliminate malaria.

Indexed as

BiostatisticsCommunicable Disease ControlDisease Transmission, InfectiousHumansIncidenceMalariaTreatment OutcomeEfficacyMalariaMeta-analysisPreventive measures

Identifiers

PMID29587882
PMCPMC5869791

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.