Factors such as varied definitions of mortality, uncertainty in disease prevalence, and biased sampling complicate the quantification of fatality during an epidemic. Regardless of the employed fatality measure, the infected population and the number of infection-caused deaths need to be consistently estimated for comparing mortality across regions. We combine historical and current mortality data, a statistical testing model, and an SIR epidemic model, to improve estimation of mortality. We find that the average excess death across the entire US from January 2020 until February 2021 is 9\(\%\) higher than the number of reported COVID-19 deaths. In some areas, such as New York City, the number of weekly deaths is about eight times higher than in previous years. Other countries such as Peru, Ecuador, Mexico, and Spain exhibit excess deaths significantly higher than their reported COVID-19 deaths. Conversely, we find statistically insignificant or even negative excess deaths for at least most of 2020 in places such as Germany, Denmark, and Norway.

死亡率定义的不同、疾病流行的不确定性以及抽样偏差等因素使流行病期间死亡率的量化变得复杂。无论采用何种死亡率衡量标准，都需要对感染人口和感染导致的死亡人数进行一致估计，以比较不同地区的死亡率。我们结合历史和当前死亡率数据、统计测试模型和 SIR 流行病模型来改进死亡率估计。我们发现，从 2020 年 1 月到 2021 年 2 月，整个美国的平均超额死亡人数比报告的 COVID-19 死亡人数高出 9 \(\%\) 。在纽约市等一些地区，每周的死亡人数比前几年高出约八倍。秘鲁、厄瓜多尔、墨西哥和西班牙等其他国家的超额死亡人数明显高于其报告的 COVID-19 死亡人数。相反，我们发现，在德国、丹麦和挪威等地，至少在 2020 年的大部分时间里，超额死亡人数在统计上并不显着，甚至为负值。