Department of Epidemiology, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, Guangdong, 510632, China.
Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, 511430, China.
BMC Public Health. 2024 Feb 2;24(1):350. doi: 10.1186/s12889-024-17803-8.
The COVID-19 pandemic has resulted in significant excess mortality globally. However, the differences in excess mortality between the Omicron and non-Omicron waves, as well as the contribution of local epidemiological characteristics, population immunity, and social factors to excess mortality, remain poorly understood. This study aims to solve the above problems.
Weekly all-cause death data and covariates from 29 countries for the period 2015-2022 were collected and used. The Bayesian Structured Time Series Model predicted expected weekly deaths, stratified by gender and age groups for the period 2020-2022. The quantile-based g-computation approach accounted for the effects of factors on the excess all-cause mortality rate. Sensitivity analyses were conducted using alternative Omicron proportion thresholds.
From the first week of 2021 to the 30th week of 2022, the estimated cumulative number of excess deaths due to COVID-19 globally was nearly 1.39 million. The estimated weekly excess all-cause mortality rate in the 29 countries was approximately 2.17 per 100,000 (95% CI: 1.47 to 2.86). Weekly all-cause excess mortality rates were significantly higher in both male and female groups and all age groups during the non-Omicron wave, except for those younger than 15 years (P < 0.001). Sensitivity analysis confirmed the stability of the results. Positive associations with all-cause excess mortality were found for the constituent ratio of non-Omicron in all variants, new cases per million, positive rate, cardiovascular death rate, people fully vaccinated per hundred, extreme poverty, hospital patients per million humans, people vaccinated per hundred, and stringency index. Conversely, other factors demonstrated negative associations with all-cause excess mortality from the first week of 2021 to the 30th week of 2022.
Our findings indicate that the COVID-19 Omicron wave was associated with lower excess mortality compared to the non-Omicron wave. This study's analysis of the factors influencing excess deaths suggests that effective strategies to mitigate all-cause mortality include improving economic conditions, promoting widespread vaccination, and enhancing overall population health. Implementing these measures could significantly reduce the burden of COVID-19, facilitate coexistence with the virus, and potentially contribute to its elimination.
全球范围内,COVID-19 大流行导致了大量超额死亡。然而,Omicron 变体波与非 Omicron 变体波之间的超额死亡率差异,以及当地流行病学特征、人口免疫力和社会因素对超额死亡率的影响,仍知之甚少。本研究旨在解决上述问题。
收集了 2015 年至 2022 年期间来自 29 个国家的每周全因死亡数据和协变量,并使用贝叶斯结构时间序列模型按性别和年龄组对 2020 年至 2022 年期间的每周预期死亡人数进行了分层预测。基于分位数的 g 计算方法考虑了各种因素对全因超额死亡率的影响。使用替代的 Omicron 比例阈值进行了敏感性分析。
从 2021 年第一周到 2022 年第 30 周,全球 COVID-19 导致的估计累积超额死亡人数接近 139 万。在 29 个国家中,每周全因超额死亡率约为每 10 万人 2.17 例(95%CI:1.47 至 2.86)。在非 Omicron 波期间,男性和女性以及所有年龄组的每周全因超额死亡率均显著高于 Omicron 波,除 15 岁以下人群外(P<0.001)。敏感性分析证实了结果的稳定性。在所有变体中,非 Omicron 构成比、每百万例新发病例、阳性率、心血管病死亡率、每百万人接种人数、赤贫、每百万人住院患者、每百万人接种人数和严格指数与全因超额死亡率呈正相关。相反,从 2021 年第一周到 2022 年第 30 周,其他因素与全因超额死亡率呈负相关。
我们的研究结果表明,与非 Omicron 波相比,COVID-19 的 Omicron 波与较低的超额死亡率相关。本研究对影响超额死亡的因素进行分析后表明,减轻全因死亡率的有效策略包括改善经济条件、促进广泛接种疫苗以及提高整体人口健康水平。实施这些措施可以显著降低 COVID-19 的负担,促进与病毒共存,并有可能有助于消灭该病毒。