Evidence map›Paper›PMID 39333953›Full record

ArticleBMC public health2024

An assessment of excess mortality during the COVID-19 pandemic, a retrospective post-mortem surveillance in 12 districts - Zambia, 2020-2022.

Stephen Longa Chanda, Jonas Z Hines, Warren Malambo, Amos Hamukale, Nathan Kapata, Nyambe Sinyange, Muzala Kapina, Luchenga Adam Mucheleng'anga, Roma Chilengi

Abstract 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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Observational
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.

Stephen Longa ChandaSurveillance and Disease Intelligence Cluster, Zambia National Public Health Institute, Stand No. 1186 Corner of Chaholi & Addis Ababa Roads, Lusaka, Zambia. longachandadoc88@gmail.com.
Jonas Z HinesUnited States Centers for Disease Control and Prevention, Lusaka, Zambia.
Warren MalamboUnited States Centers for Disease Control and Prevention, Lusaka, Zambia.
Amos HamukaleSurveillance and Disease Intelligence Cluster, Zambia National Public Health Institute, Stand No. 1186 Corner of Chaholi & Addis Ababa Roads, Lusaka, Zambia.
Nathan KapataSurveillance and Disease Intelligence Cluster, Zambia National Public Health Institute, Stand No. 1186 Corner of Chaholi & Addis Ababa Roads, Lusaka, Zambia.
Nyambe SinyangeSurveillance and Disease Intelligence Cluster, Zambia National Public Health Institute, Stand No. 1186 Corner of Chaholi & Addis Ababa Roads, Lusaka, Zambia.
Muzala KapinaSurveillance and Disease Intelligence Cluster, Zambia National Public Health Institute, Stand No. 1186 Corner of Chaholi & Addis Ababa Roads, Lusaka, Zambia.
Luchenga Adam Mucheleng'angaOffice of the State Forensic Pathologist, Government of the Republic of Zambia, Ministry of Home Affairs and Internal Security, Lusaka, Zambia.
Roma ChilengiSurveillance and Disease Intelligence Cluster, Zambia National Public Health Institute, Stand No. 1186 Corner of Chaholi & Addis Ababa Roads, Lusaka, Zambia.

Funding

United States Centers for Disease Control and Prevention, Lusaka, Zambia CoAg ID number: GH002234
6 · The paper itself

Abstract

backgroundThe number of COVID-19 deaths reported in Zambia (N = 4069) is most likely an underestimate due to limited testing, incomplete death registration and inability to account for indirect deaths due to socioeconomic disruption during the pandemic. We sought to assess excess mortality during the COVID-19 pandemic in Zambia.

methodsWe conducted a retrospective analysis of monthly-death-counts (2017-2022) and individual-daily-deaths (2020-2022) of all reported health facility and community deaths at district referral health facility mortuaries in 12 districts in Zambia. We defined COVID-19 wave periods based on a sustained nationally reported SARS-CoV-2 test positivity of greater than 5%. Excess mortality was calculated as the difference between observed monthly death counts during the pandemic (2020-2022) and the median monthly death counts from the pre-pandemic period (2017-2019), which served as the expected number of deaths. This calculation was conducted using a Microsoft Excel-based tool. We compared median daily death counts, median age at death, and the proportion of deaths by place of death (health facility vs. community) by wave period using the Mann-Whitney-U test and chi-square test respectively in R.

resultsA total of 112,768 deaths were reported in the 12 districts between 2020 and 2022, of which 17,111 (15.2%) were excess. Wave periods had higher median daily death counts than non-wave periods (median [IQR], 107 [95-126] versus 96 [85-107], p < 0.001). The median age at death during wave periods was older than non-wave periods (44.0 [25.0-67.0] versus 41.0 [22.0-63.0] years, p < 0.001). Approximately half of all reported deaths occurred in the community, with an even greater proportion during wave periods (50.6% versus 53.1%, p < 0.001), respectively.

conclusionThere was excess mortality during the COVID-19 pandemic in Zambia, with more deaths occurring within the community during wave periods. This analysis suggests more COVID-19 deaths likely occurred in Zambia than suggested by officially reported numbers. Mortality surveillance can provide important information to monitor population health and inform public health programming during pandemics.

Indexed as

COVID-19AdolescentAdultAgedAged, 80 and overAutopsyCause of DeathChildChild, PreschoolFemaleHumansInfantMaleMiddle AgedMortalityPandemicsCOVID-19Excess mortalityMortality surveillancePandemicRetrospective studiesSARS-CoV-2Socioeconomic factorsZambia

Identifiers

PMID39333953
PMCPMC11437817

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.