Evidence map›Paper›PMID 30845998›Full record

ArticleMalaria journal2019

Investigating the upsurge of malaria prevalence in Zambia between 2010 and 2015: a decomposition of determinants.

Mukumbuta Nawa, Peter Hangoma, Andrew P Morse, Charles Michelo

Open access · goldAbstract read
In one paragraph

Article in Malaria journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

13 citing papers in PubMed, 35 citations in OpenAlex.

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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

4 authors at 2 institutions in 2 countries.

Mukumbuta NawaSchool of Public Health, University of Zambia, Ridgeway Campus, Lusaka, Zambia. mktnawa@gmail.com.ORCID http://orcid.org/0000-0003-2360-2752
Peter HangomaSchool of Public Health, University of Zambia, Ridgeway Campus, Lusaka, Zambia.
Andrew P MorseDepartment of Geography and Planning, University of Liverpool, Liverpool, UK.
Charles MicheloSchool of Public Health, University of Zambia, Ridgeway Campus, Lusaka, Zambia.
University of Zambia · ZMUniversity of Liverpool · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMalaria is among the top causes of mortality and morbidity in Zambia. Efforts to control, prevent, and eliminate it have been intensified in the past two decades which has contributed to reductions in malaria prevalence and under-five mortality. However, there was a 21% upsurge in malaria prevalence between 2010 and 2015. Zambia is one of the only 13 countries to record an increase in malaria among 91 countries monitored by the World Health Organization in 2015. This study investigated the upsurge by decomposition of drivers of malaria.

methodsThe study used secondary data from three waves of nationally representative cross-sectional surveys on key malaria indicators conducted in 2010, 2012 and 2015. Using multivariable logistic regression, determinants of malaria prevalence were identified and then marginal effects of each determinant were derived. The marginal effects were then combined with changes in coverage rates of determinants between 2010 and 2015 to obtain the magnitude of how much each variable contributed to the change in the malaria prevalence.

resultsThe odds ratio of malaria for those who slept under an insecticide-treated net (ITN) was 0.90 (95% CI 0.77-0.97), indoor residual spraying (IRS) was 0.66 (95% CI 0.49-0.89), urban residence was 0.23 (95% CI 0.15-0.37), standard house was 0.40 (95% CI 0.35-0.71) and age group 12-59 Months against those below 12 months was 4.04 (95% CI 2.80-5.81). Decomposition of prevalence changes by determinants showed that IRS reduced malaria prevalence by - 0.3% and ITNs by - 0.2% however, these reductions were overridden by increases in prevalence due to increases in the proportion of more at-risk children aged 12-59 months by + 2.3% and rural residents by + 2.2%.

conclusionThe increases in interventions, such as ITNs and IRS, were shown to have contributed to malaria reduction in 2015; however, changes in demographics such as increases in the proportion of more at risk groups among under-five children and rural residents may have overridden the impact of these interventions and resulted in an overall increase. The upsurge in malaria in 2015 compared to 2010 may not have been due to weaknesses in programme interventions but due to increases in more at-risk children and rural residents compared to 2010. The apparent increase in rural residents in the sample population may not have been a true reflection of the population structure but due to oversampling in rural areas which was not fully adjusted for. The increase in malaria prevalence may therefore have been overestimated.

Indexed as

AdolescentAdultAgedAged, 80 and overChildChild, PreschoolCross-Sectional StudiesDemographyFemaleHumansInfantInfant, NewbornMalariaMaleMiddle AgedPrevalenceIndoor residual sprayingInsecticide treated netsMalaria prevalenceStandard housingUpsurge

Identifiers

PMID30845998
PMCPMC6407176
OpenAlexW2925992113

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.