Using excess deaths and testing statistics to determine COVID-19 mortalities

被引:26
作者
Bottcher, Lucas [1 ,2 ]
D'Orsogna, Maria R. [1 ,3 ]
Chou, Tom [1 ,4 ]
机构
[1] UCLA, Dept Computat Med, Los Angeles, CA 90095 USA
[2] Frankfurt Sch Finance & Management, Computat Social Sci, D-60322 Frankfurt, Germany
[3] Calif State Univ Northridge, Dept Math, Los Angeles, CA 91330 USA
[4] Univ Calif Los Angeles, Dept Math, Los Angeles, CA 90095 USA
基金
美国国家科学基金会; 瑞士国家科学基金会;
关键词
COVID-19; Excess deaths; Mortality; Test statistics;
D O I
10.1007/s10654-021-00748-2
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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.
引用
收藏
页码:545 / 558
页数:14
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