Evidence map›Paper›PMID 38443885›Full record

ArticleBMC public health2024

Population mortality before and during the COVID-19 epidemic in two Sudanese settings: a key informant study.

Rahaf AbuKoura, Francesco Checchi, Omama Abdalla, Omnia Ibrahim, Ahmed Tom Hemeadan, Ahmed Ali Ahmed Eldirdiri, Direeg Ismail Mohamed, Aljaile Ahmed, Abd Elhameed Ahmed, Nada Abdelmagid and 2 more

Open access · goldAbstract read
In one paragraph

Article 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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.2field-weighted citation impact, top 27% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

12 authors at 2 institutions in 2 countries.

Rahaf AbuKouraLondon School of Hygiene and Tropical Medicine, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London, UK. rahaf.Abu-koura@lshtm.ac.uk.ORCID 0000-0002-1956-2551
Francesco ChecchiLondon School of Hygiene and Tropical Medicine, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London, UK.ORCID 0000-0001-9030-5382
Omama AbdallaY-Peer, Khartoum, Sudan.
Omnia IbrahimY-Peer, Khartoum, Sudan.
Ahmed Tom HemeadanY-Peer, Khartoum, Sudan.
Ahmed Ali Ahmed EldirdiriY-Peer, Khartoum, Sudan.
Direeg Ismail MohamedY-Peer, Khartoum, Sudan.
Aljaile AhmedY-Peer, Khartoum, Sudan.
Abd Elhameed AhmedY-Peer, Khartoum, Sudan.
Nada AbdelmagidLondon School of Hygiene and Tropical Medicine, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London, UK.ORCID 0000-0003-4296-7378
Pasquale PepeOcular Technology Group - International, London, UK.
Maysoon DahabLondon School of Hygiene and Tropical Medicine, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London, UK.ORCID 0000-0002-4271-9705
London School of Hygiene & Tropical Medicine · GBSudan Academy of Sciences · SD

Funding

CGH CDC HHS U01 GH002319
6 · The paper itself

Abstract

backgroundPopulation mortality is an important metric that sums information from different public health risk factors into a single indicator of health. However, the impact of COVID-19 on population mortality in low-income and crisis-affected countries like Sudan remains difficult to measure. Using a community-led approach, we estimated excess mortality during the COVID-19 epidemic in two Sudanese communities.

methodsThree sets of key informants in two study locations, identified by community-based research teams, were administered a standardised questionnaire to list all known decedents from January 2017 to February 2021. Based on key variables, we linked the records before analysing the data using a capture-recapture statistical technique that models the overlap among lists to estimate the true number of deaths.

resultsWe estimated that deaths per day were 5.5 times higher between March 2020 and February 2021 compared to the pre-pandemic period in East Gezira, while in El Obeid City, the rate was 1.6 times higher.

conclusionThis study suggests that using a community-led capture-recapture methodology to measure excess mortality is a feasible approach in Sudan and similar settings. Deploying similar community-led estimation methodologies should be considered wherever crises and weak health infrastructure prevent an accurate and timely real-time understanding of epidemics' mortality impact in real-time.

Indexed as

COVID-19Black PeopleHumansPandemicsPovertyPublic HealthCapture-recaptureCommunityCo-productionCOVID-19HumanitarianKey informantMortalityMultiple systems estimationSARS-CoV-2Sudan

Identifiers

PMID38443885
PMCPMC10916139
OpenAlexW4392472635

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.