Evidence map›Paper›PMID 39435517›Full record

ArticleJournal of Korean medical science2024

Estimating Excess Mortality During the COVID-19 Pandemic Between 2020-2022 in Korea.

Minjeong Jang, Soyoung Kim, Sunhwa Choi, Boyeong Ryu, So Young Choi, Siwon Choi, Misuk An, Seong-Sun Kim

Abstract read
In one paragraph

Article in Journal of Korean medical science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Reassessing Early COVID-19 Strategies in East Asia: Insights From Japan and Korea.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2026
    Review
  4. Article
  5. Article
  6. Observational
  7. 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

8 authors.

Minjeong Jang *Data Analysis Team, Central Disease Control Headquarters for COVID-19, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0009-0000-3273-6379
Soyoung Kim *Innovation Center for Industrial Mathematics, National Institute for Mathematical Sciences, Seongnam, Korea.ORCID https://orcid.org/0000-0003-4918-1087
Sunhwa ChoiInnovation Center for Industrial Mathematics, National Institute for Mathematical Sciences, Seongnam, Korea.ORCID https://orcid.org/0000-0002-6608-6981
Boyeong RyuData Analysis Team, Central Disease Control Headquarters for COVID-19, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0001-9336-8098
So Young ChoiData Analysis Team, Central Disease Control Headquarters for COVID-19, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0001-6817-2114
Siwon ChoiDivision of Public Health Emergency Response Research, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0003-1279-3661
Misuk AnData Analysis Team, Central Disease Control Headquarters for COVID-19, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0009-0007-7505-5398
Seong-Sun KimData Analysis Team, Central Disease Control Headquarters for COVID-19, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0001-5277-492X

Funding

National Institute for Mathematical Sciences B24810000
6 · The paper itself

Abstract

backgroundThe persistent coronavirus disease 2019 (COVID-19) pandemic has had direct and indirect effects on mortality, making it essential to analyze excess mortality to fully understand the impact of the pandemic. In this study, we constructed a mathematical model using number of deaths from Statistics Korea and analyzed excess mortality between 2020 and 2022 according to age, sex, and dominant severe acute respiratory syndrome coronavirus 2 variant period.

methodsNumber of all-cause deaths between 2010 and 2022 were obtained from the annual cause-of-death statistics provided by Statistics Korea. COVID-19 mortality data were acquired from the Korea Disease Control and Prevention Agency. A multivariate linear regression model with seasonal effect, stratified by sex and age, was used to estimate the number of deaths in the absence of COVID-19. The estimated excess mortality rate was calculated.

resultsExcess mortality was not significant between January 2020 and October 2021. However, it started to increase monthly from November 2021 and reached its highest point during the omicron-dominant period. Specifically, in March and April 2022, during the omicron BA.1/BA.2-dominant period, the estimated median values for excess mortality were the highest at 17,634 and 11,379, respectively. Both COVID-19-related deaths and excess mortality increased with age. A notable increase in excess mortality was observed in individuals aged ≥ 65 years. In the context of excess mortality per 100,000 population based on the estimated median values in March 2022, the highest numbers were found among males and females aged ≥ 85 years at 1,048 and 910, respectively.

conclusionThis study revealed that the prolonged COVID-19 pandemic coupled with its high transmissibility not only increased COVID-19-related deaths but also had a significant impact on overall mortality rates, especially in the elderly. Therefore, it is crucial to concentrate healthcare resources and services on the elderly and ensure continued access to healthcare services during pandemics. Establishing an excess mortality monitoring system in the early stages of a pandemic is necessary to understand the impact of infectious diseases on mortality and effectively evaluate pandemic response policies.

Indexed as

COVID-19SARS-CoV-2AdolescentAdultAgedAged, 80 and overAge FactorsChildChild, PreschoolFemaleHumansInfantInfant, NewbornMaleMiddle AgedModels, TheoreticalCOVID-19Excess MortalitySouth Korea

Identifiers

PMID39435517
PMCPMC11496562

What OpenQuestion holds

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LicenceCC BY-NC
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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.