Department of Genetics, University of Cambridge, Cambridge, UK.
Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.
Nature. 2021 Feb;590(7844):140-145. doi: 10.1038/s41586-020-2918-0. Epub 2020 Nov 2.
Estimating the size of the coronavirus disease 2019 (COVID-19) pandemic and the infection severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is made challenging by inconsistencies in the available data. The number of deaths associated with COVID-19 is often used as a key indicator for the size of the epidemic, but the observed number of deaths represents only a minority of all infections. In addition, the heterogeneous burdens in nursing homes and the variable reporting of deaths of older individuals can hinder direct comparisons of mortality rates and the underlying levels of transmission across countries. Here we use age-specific COVID-19-associated death data from 45 countries and the results of 22 seroprevalence studies to investigate the consistency of infection and fatality patterns across multiple countries. We find that the age distribution of deaths in younger age groups (less than 65 years of age) is very consistent across different settings and demonstrate how these data can provide robust estimates of the share of the population that has been infected. We estimate that the infection fatality ratio is lowest among 5-9-year-old children, with a log-linear increase by age among individuals older than 30 years. Population age structures and heterogeneous burdens in nursing homes explain some but not all of the heterogeneity between countries in infection fatality ratios. Among the 45 countries included in our analysis, we estimate that approximately 5% of these populations had been infected by 1 September 2020, and that much higher transmission rates have probably occurred in a number of Latin American countries. This simple modelling framework can help countries to assess the progression of the pandemic and can be applied in any scenario for which reliable age-specific death data are available.
估算 2019 年冠状病毒病(COVID-19)大流行的规模和严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)的感染严重程度,受到可用数据不一致的影响。COVID-19 相关死亡人数通常被用作疫情规模的关键指标,但观察到的死亡人数仅代表所有感染人数的一小部分。此外,养老院的负担不均和老年人死亡报告的差异,可能会阻碍各国之间死亡率和潜在传播水平的直接比较。在这里,我们使用来自 45 个国家的特定年龄 COVID-19 相关死亡数据和 22 项血清流行率研究的结果,调查多个国家感染和病死率模式的一致性。我们发现,在不同环境下,年轻年龄组(<65 岁)的死亡年龄分布非常一致,并展示了这些数据如何提供关于感染人群比例的可靠估计。我们估计,感染病死率在 5-9 岁儿童中最低,30 岁以上人群的病死率呈对数线性增加。人口年龄结构和养老院的负担不均解释了感染病死率在国家之间存在差异的部分原因,但并非全部原因。在我们分析的 45 个国家中,我们估计截至 2020 年 9 月 1 日,这些人群中约有 5%已经感染,而在一些拉丁美洲国家,可能发生了更高的传播率。这个简单的建模框架可以帮助各国评估大流行的进展情况,并且可以在任何有可靠的特定年龄死亡数据的情况下应用。