Evidence map›Paper›PMID 38902661›Full record

SynthesisBMC public health2024

Excess mortality during the COVID-19 pandemic in low-and lower-middle-income countries: a systematic review and meta-analysis.

Jonathan Mawutor Gmanyami, Wilm Quentin, Oscar Lambert, Andrzej Jarynowski, Vitaly Belik, John Humphrey Amuasi

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–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

12 citing papers in PubMed.

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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

6 authors.

Jonathan Mawutor GmanyamiSchool of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. jgmanyami@gmail.com.
Wilm QuentinGerman West-African Centre for Global Health and Pandemic Prevention, Berlin, Germany.
Oscar LambertSchool of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Andrzej JarynowskiDepartment of Veterinary Medicine, Freie Universität Berlin, Berlin, Germany.
Vitaly BelikDepartment of Veterinary Medicine, Freie Universität Berlin, Berlin, Germany.
John Humphrey AmuasiSchool of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough the COVID-19 pandemic claimed a great deal of lives, it is still unclear how it affected mortality in low- and lower-middle-income countries (LLMICs). This review summarized the available literature on excess mortality during the COVID-19 pandemic in LLMICs, including methods, sources of data, and potential contributing factors that might have influenced excess mortality.

methodsWe conducted a systematic review and meta-analysis on excess mortality during the COVID-19 pandemic in LLMICs in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020 guidelines We searched PubMed, Embase, Web of Science, Cochrane Library, Google Scholar, and Scopus. We included studies published from 2019 onwards with a non-COVID-19 period of at least one year as a comparator. The meta-analysis included studies reporting data on population size, as well as observed and expected deaths. We used the Mantel-Haenszel method to estimate the pooled risk ratio with 95% confidence intervals. The protocol was registered in PROSPERO (ID: CRD42022378267).

resultsThe review covered 29 countries, with 10 countries included in the meta-analysis. The pooled meta-analysis included 1,405,128,717 individuals, for which 2,152,474 deaths were expected, and 3,555,880 deaths were reported. Calculated excess mortality was 100.3 deaths per 100,000 population per year, with an excess risk of death of 1.65 (95% CI: 1.649, 1.655, p < 0.001). The data sources used in the studies included civil registration systems, surveys, public cemeteries, funeral counts, obituary notifications, burial site imaging, and demographic surveillance systems. The primary techniques used to estimate excess mortality were statistical forecast modelling and geospatial analysis. One out of the 24 studies found higher excess mortality in urban settings.

conclusionOur findings demonstrate that excess mortality in LLMICs during the pandemic was substantial. However, estimates of excess mortality are uncertain due to relatively poor data. Understanding the drivers of excess mortality, will require more research using various techniques and data sources.

Indexed as

COVID-19Developing CountriesHumansMortalityPandemicsSARS-CoV-219 pandemicExcess mortality, COVIDLow- and lower-middle-income countries

Identifiers

PMID38902661
PMCPMC11188207

What OpenQuestion holds

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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.