Data Analysis Team, Central Disease Control Headquarters for COVID-19, Korea Disease Control and Prevention Agency, Cheongju, Korea.
Innovation Center for Industrial Mathematics, National Institute for Mathematical Sciences, Seongnam, Korea.
J Korean Med Sci. 2024 Oct 21;39(40):e267. doi: 10.3346/jkms.2024.39.e267.
The 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.
Number 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.
Excess 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.
This 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.
持续的 2019 年冠状病毒病（COVID-19）大流行对死亡率产生了直接和间接的影响，因此分析超额死亡率对于全面了解大流行的影响至关重要。在这项研究中，我们使用韩国统计局提供的死亡人数构建了一个数学模型，并根据年龄、性别和主要严重急性呼吸综合征冠状病毒 2 变异期分析了 2020 年至 2022 年的超额死亡率。
从韩国统计局提供的年度死因统计数据中获取 2010 年至 2022 年所有原因的死亡人数。从韩国疾病控制和预防机构获取 COVID-19 死亡人数。使用具有季节性效应的多变量线性回归模型，按性别和年龄分层，估计不存在 COVID-19 情况下的死亡人数。计算估计的超额死亡率。
2020 年 1 月至 2021 年 10 月期间，超额死亡率不显著。然而，从 2021 年 11 月开始，每月开始增加，并在 omicron 主导期间达到最高点。具体而言，在 2022 年 3 月和 4 月，在 omicron BA.1/BA.2 主导期间，超额死亡率的估计中位数分别高达 17634 和 11379。COVID-19 相关死亡人数和超额死亡率均随年龄增长而增加。在≥65 岁的人群中，观察到超额死亡率显著增加。在基于 2022 年 3 月估计中位数的每 10 万人中超额死亡率的背景下，最高的数字出现在≥85 岁的男性和女性中，分别为 1048 和 910。
本研究表明，COVID-19 大流行的持续时间及其高传染性不仅增加了 COVID-19 相关死亡人数，而且对总死亡率产生了重大影响，特别是在老年人中。因此，集中医疗资源和服务于老年人，并确保在大流行期间持续获得医疗服务至关重要。在大流行的早期阶段建立超额死亡率监测系统对于了解传染病对死亡率的影响并有效评估大流行应对政策至关重要。
