Evidence map›Paper›PMID 41361835›Full record

ArticlePopulation health metrics2025

Assessing the impact of COVID-19 pandemic on all-cause mortality and child mortality in a population cohort of Iganga Mayuge HDSS in Eastern Uganda (2015-2021).

Dan Kajungu, Betty Nabukeera, Jean Bashingwa, Chodziwadziwa Kabudula, Beth T Barr, Donald Ndyomugyenyi, Akello Mercy Consolate, Collins Gyezaho, Elizeus Rutebemberwa

Abstract read
In one paragraph

Article in Population health metrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Dan KajunguMakerere University Centre for Health and Population Research (MUCHAP), Iganga Mayuge Health and Demographic Surveillance Site (IMHDSS), Kampala, Uganda. dan.kajungu@gmail.com.ORCID 0000-0002-3363-7062
Betty NabukeeraMakerere University Centre for Health and Population Research (MUCHAP), Iganga Mayuge Health and Demographic Surveillance Site (IMHDSS), Kampala, Uganda.
Jean BashingwaSAMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), Faculty of Health Sciences, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa.
Chodziwadziwa KabudulaSAMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), Faculty of Health Sciences, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa.
Beth T BarrNyanja Health Research Institute, Lilongwe, Malawi.
Donald NdyomugyenyiMakerere University Centre for Health and Population Research (MUCHAP), Iganga Mayuge Health and Demographic Surveillance Site (IMHDSS), Kampala, Uganda.
Akello Mercy ConsolateMakerere University Centre for Health and Population Research (MUCHAP), Iganga Mayuge Health and Demographic Surveillance Site (IMHDSS), Kampala, Uganda.
Collins GyezahoMakerere University Centre for Health and Population Research (MUCHAP), Iganga Mayuge Health and Demographic Surveillance Site (IMHDSS), Kampala, Uganda.
Elizeus RutebemberwaDepartment of Health Policy, Planning and Management, Makerere University School of Public Health, Kampala, Uganda.

Funding

Bill and Melinda Gates Foundation INV-050361Gates Foundation INV-030309
6 · The paper itself

Abstract

backgroundEfforts to track the mortality and public health impact of the coronavirus disease (COVID-19) in Uganda have been hampered by weak Civil registration and vital statistics (CRVS) system and suboptimal health seeking behaviors or patterns. Evaluating unexplained increases in all-cause mortality provides a complete picture of the impact of COVID-19 pandemic and guide public health policies and resource allocation to protect the most vulnerable populations.

methodsThe longitudinal population cohort data on demographic events and socioeconomic status collected from 2015 to 2021 within the Iganga Mayuge Health and Demographic Surveillance System (IMHDSS) was used. Number of deaths and person years at risk were counted for each quarter of the year from January 2015 to December 2021 and classified as "pre-pandemic" (before January 2020), and "during pandemic" (January 2020 to December 2021). Crude mortality rates were computed comparing the two periods. Time series model was used to estimate excess mortality and to locate the exact time when excess deaths occurred. Cox Proportional Hazard model was used to estimate the Hazard ratio associated with death.

resultsA total of 132,367 individuals were followed up from 2015 to 2021 and 3,424 deaths were registered. Slightly more than a half of all deaths (53%, n = 1,827) were male, and 65.4% (n = 2,238) were rural residents. Children under five years had a significantly higher CMR during COVID-19 period of 18.9, (95% CI 17.2-20.8) per 1000 person compared to 12.5 (95% CI 11.6-13.4) per 1000 person years before COVID-19. The risk of dying among children under 5 years compared to those aged between 5 and 14 years was higher during the COVID-19 pandemic period (aHR = 18.0, 95% CI 13.6-24.0) than pre-pandemic (aHR = 10.4, 95% CI 8.8-12.3).

conclusionThe COVID-19 pandemic increased all-cause mortality in the Iganga Mayuge HDSS population cohort in Eastern Uganda, particularly among children under five, likely due to restricted healthcare access and economic disruptions. Pandemic response measures should prioritize vulnerable populations at higher risk of malnutrition and preventable diseases to mitigate future negative impacts.

Indexed as

Child MortalityCOVID-19MortalityAdolescentAdultCause of DeathChildChild, PreschoolFemaleHumansInfantInfant, NewbornLongitudinal StudiesMaleMiddle AgedPandemicsCOVID-19Excess mortalityHealth and demographic surveillance system (HDSS)UgandaUnder-five mortality

Identifiers

PMID41361835
PMCPMC12687486

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LicenceCC BY
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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.