Departments of Medicine, of Epidemiology and Population Health, of Biomedical Data Science, and of Statistics, and Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, USA.
Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China.
Eur J Clin Invest. 2023 Aug;53(8):e14008. doi: 10.1111/eci.14008. Epub 2023 Apr 24.
Several teams have been publishing global estimates of excess deaths during the COVID-19 pandemic. Here, we examine potential flaws and underappreciated sources of uncertainty in global excess death calculations. Adjusting for changing population age structure is essential. Otherwise, excess deaths are markedly overestimated in countries with increasingly aging populations. Adjusting for changes in other high-risk indicators, such as residence in long-term facilities, may also make a difference. Death registration is highly incomplete in most countries; completeness corrections should allow for substantial uncertainty and consider that completeness may have changed during pandemic years. Excess death estimates have high sensitivity to modelling choice. Therefore different options should be considered and the full range of results should be shown for different choices of pre-pandemic reference periods and imposed models. Any post-modelling corrections in specific countries should be guided by pre-specified rules. Modelling of all-cause mortality (ACM) in countries that have ACM data and extrapolating these models to other countries is precarious; models may lack transportability. Existing global excess death estimates underestimate the overall uncertainty that is multiplicative across diverse sources of uncertainty. Informative excess death estimates require risk stratification, including age groups and ethnic/racial strata. Data to-date suggest a death deficit among children during the pandemic and marked socioeconomic differences in deaths, widening inequalities. Finally, causal explanations require great caution in disentangling SARS-CoV-2 deaths, indirect pandemic effects and effects from measures taken. We conclude that excess deaths have many uncertainties, but globally deaths from SARS-CoV-2 may be the minority of calculated excess deaths.
有几个团队一直在发布 COVID-19 大流行期间全球超额死亡人数的估计值。在这里，我们研究了全球超额死亡计算中潜在的缺陷和被低估的不确定性来源。调整人口年龄结构是至关重要的。否则，人口老龄化日益严重的国家的超额死亡人数将被显著高估。调整其他高风险指标（如长期护理机构的居住情况）的变化也可能有所不同。大多数国家的死亡登记都极不完整；完整性校正应考虑到大量的不确定性，并考虑到完整性可能在大流行期间发生了变化。超额死亡估计对建模选择非常敏感。因此，应该考虑不同的选择，并为不同的大流行前参考期和强制模型选择展示结果的全部范围。任何在特定国家的后建模校正都应该遵循预先规定的规则。在有 ACM 数据的国家进行所有原因死亡率（ACM）建模，并将这些模型外推到其他国家是不稳定的；模型可能缺乏可转移性。现有的全球超额死亡估计值低估了各种不确定性来源相乘的总体不确定性。信息丰富的超额死亡估计值需要风险分层，包括年龄组和族裔/种族阶层。迄今为止的数据表明，大流行期间儿童的死亡人数不足，死亡人数存在明显的社会经济差异，不平等现象扩大。最后，在厘清 SARS-CoV-2 死亡、间接大流行影响以及采取措施的影响时，因果解释需要非常谨慎。我们的结论是，超额死亡存在许多不确定性，但全球范围内 SARS-CoV-2 导致的死亡可能是计算出的超额死亡人数中的少数。
