Federal Institute for Population Research (BiB), Friedrich-Ebert-Allee 4, 65185, Wiesbaden, Germany.
J Epidemiol Glob Health. 2023 Dec;13(4):664-675. doi: 10.1007/s44197-023-00141-0. Epub 2023 Aug 4.
Evaluating mortality effects of the COVID-19 pandemic using all-cause mortality data for national populations is inevitably associated with the risk of masking important subnational differentials and hampering targeted health policies. This study aims at assessing simultaneously cause-specific, spatial and seasonal mortality effects attributable to the pandemic in Germany in 2020.
Our analyses rely on official cause-of-death statistics consisting of 5.65 million individual death records reported for the German population during 2015-2020. We conduct differential mortality analyses by age, sex, cause, month and district (N = 400), using decomposition and standardisation methods, comparing each strata of the mortality level observed in 2020 with its expected value, as well as spatial regression to explore the association of excess mortality with pre-pandemic indicators.
The spatial analyses of excess mortality reveal a very heterogenous pattern, even within federal states. The coastal areas in the north were least affected, while the south of eastern Germany experienced the highest levels. Excess mortality in the most affected districts, with standardised mortality ratios reaching up to 20%, is driven widely by older ages and deaths reported in December, particularly from COVID-19 but also from cardiovascular and mental/nervous diseases.
Our results suggest that increased psychosocial stress influenced the outcome of excess mortality in the most affected areas during the second lockdown, thus hinting at possible adverse effects of strict policy measures. It is essential to accelerate the collection of detailed mortality data to provide policymakers earlier with relevant information in times of crisis.
利用全因死亡率数据评估国家人群的 COVID-19 大流行的死亡率效应,不可避免地会掩盖重要的亚国家差异,并阻碍有针对性的卫生政策。本研究旨在同时评估 2020 年德国大流行归因于特定原因、空间和季节性的死亡率效应。
我们的分析依赖于官方死因统计数据,这些数据由 2015-2020 年期间报告的德国人口的 565 万个人死亡记录组成。我们通过年龄、性别、死因、月份和地区(N=400)进行差异死亡率分析,使用分解和标准化方法,将 2020 年观察到的死亡率水平的每个层次与预期值进行比较,以及空间回归来探索超额死亡率与大流行前指标的关联。
超额死亡率的空间分析显示出非常不均匀的模式,即使在联邦州内部也是如此。北部沿海地区受影响最小,而德国东部的南部地区受影响最大。受影响最严重的地区的超额死亡率(标准化死亡率比高达 20%)主要由年龄较大和 12 月报告的死亡驱动,特别是 COVID-19,但也有心血管和精神/神经疾病。
我们的结果表明,在第二次封锁期间,增加的心理社会压力影响了受影响最严重地区的超额死亡率的结果,这暗示了严格政策措施可能产生的不利影响。在危机时期,必须加快收集详细的死亡率数据,以便为政策制定者提供更早的相关信息。