Castro Marcia C, Gurzenda Susie, Turra Cassio M, Kim Sun, Andrasfay Theresa, Goldman Noreen
Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Demography Department, Cedeplar, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
Demography. 2023 Apr 1;60(2):343-349. doi: 10.1215/00703370-10575276.
The COVID-19 pandemic has had overwhelming global impacts with deleterious social, economic, and health consequences. To assess the COVID-19 death toll, researchers have estimated declines in 2020 life expectancy at birth (e0). When data are available only for COVID-19 deaths, but not for deaths from other causes, the risks of dying from COVID-19 are typically assumed to be independent of those from other causes. In this research note, we explore the soundness of this assumption using data from the United States and Brazil, the countries with the largest number of reported COVID-19 deaths. We use three methods: one estimates the difference between 2019 and 2020 life tables and therefore does not require the assumption of independence, and the other two assume independence to simulate scenarios in which COVID-19 mortality is added to 2019 death rates or is eliminated from 2020 rates. Our results reveal that COVID-19 is not independent of other causes of death. The assumption of independence can lead to either an overestimate (Brazil) or an underestimate (United States) of the decline in e0, depending on how the number of other reported causes of death changed in 2020.
新冠疫情对全球产生了巨大影响，带来了有害的社会、经济和健康后果。为评估新冠死亡人数，研究人员估算了2020年出生时预期寿命（e0）的下降情况。当只有新冠死亡数据，而没有其他死因的数据时，通常假定死于新冠的风险与其他死因的风险相互独立。在本研究报告中，我们利用美国和巴西（报告新冠死亡人数最多的两个国家）的数据，探讨了这一假设的合理性。我们采用了三种方法：一种方法是估算2019年和2020年生命表之间的差异，因此不需要独立性假设；另外两种方法假定独立性，以模拟将新冠死亡率加到2019年死亡率或从2020年死亡率中剔除的情景。我们的结果显示，新冠与其他死因并非相互独立。独立性假设可能导致对e0下降的高估（巴西）或低估（美国），这取决于2020年其他报告死因的数量变化情况。
