PDF(Pubmed)
Abstract：
BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
摘要：
背景：使用全国人群的全因死亡率数据评估COVID-19大流行的死亡率影响不可避免地与掩盖重要的国家以下差异和阻碍有针对性的卫生政策的风险有关。这项研究旨在同时评估特定原因，2020年德国大流行对空间和季节性死亡率的影响。
方法：我们的分析依赖于官方的死亡原因统计数据，包括2015-2020年德国人口报告的565万份个人死亡记录。我们按年龄进行死亡率差异分析，性别,cause,月份和地区(N=400)，使用分解和标准化方法，将2020年观察到的每一层死亡率水平与其预期值进行比较，以及空间回归来探索超额死亡率与大流行前指标的关系。
结果：超额死亡率的空间分析揭示了一种非常异质的模式，甚至在联邦州内。北部沿海地区受影响最小,而德国东部南部经历了最高的水平。受影响最严重地区的死亡率过高，标准化死亡率高达20%，是由12月份报告的老年人和死亡造成的，特别是来自COVID-19，但也来自心血管和精神/神经疾病。
结论：我们的结果表明，在第二次封锁期间，心理社会压力的增加影响了受影响最严重地区的超额死亡率。从而暗示严格政策措施可能产生的不利影响。必须加快收集详细的死亡率数据，以便在危机时期尽早向决策者提供相关信息。
方法：我们的分析依赖于官方的死亡原因统计数据，包括2015-2020年德国人口报告的565万份个人死亡记录。我们按年龄进行死亡率差异分析，性别,cause,月份和地区(N=400)，使用分解和标准化方法，将2020年观察到的每一层死亡率水平与其预期值进行比较，以及空间回归来探索超额死亡率与大流行前指标的关系。
结果：超额死亡率的空间分析揭示了一种非常异质的模式，甚至在联邦州内。北部沿海地区受影响最小,而德国东部南部经历了最高的水平。受影响最严重地区的死亡率过高，标准化死亡率高达20%，是由12月份报告的老年人和死亡造成的，特别是来自COVID-19，但也来自心血管和精神/神经疾病。
结论：我们的结果表明，在第二次封锁期间，心理社会压力的增加影响了受影响最严重地区的超额死亡率。从而暗示严格政策措施可能产生的不利影响。必须加快收集详细的死亡率数据，以便在危机时期尽早向决策者提供相关信息。
