STATISTICAL APPROACHES FOR ASSESSING EXCESS MORTALITY DURING THE COVID-19 PANDEMIC: A SCOPING REVIEW

Q3 Social Sciences
Ekaterina A Krieger, Vitaly A. Postoev, Andrej М Grjibovski
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Abstract

Excess mortality is a measure of the increase in the number of deaths in a population during a certain time period compared to the expected values. This phenomenon can be triggered by a variety of natural or man-made disasters. Throughout the global COVID-19 pandemic, all countries experienced a rise in mortality rates, although not all deaths were directly caused by the coronavirus infection. Estimation of excess mortality during a pandemic, particularly stratified by the leading causes of death, is an important public health issue. The outcomes of these calculations, however, can vary significantly depending on the methodological approaches employed to estimate excess mortality. The aim of this study was to provide a systematic review of the analytical methods used by the international research community to quantify excess mortality during the COVID-19 pandemic. Full-text publications in both Russian and English, published between 2020 and 2022, that focused on assessing excess mortality during the COVID-19 were reviewed. The search for English-language publications was conducted in the MEDLINE database (www.pubmed.gov), while Russian-language publications were sourced from the Scientific Electronic Library database (www.elibrary.ru). Out of the 725 publications initially identified, we included 73 original studies in this review. Among the various statistical methods employed to estimate excess mortality, the most commonly utilized approaches were Poisson regression with correction for overdispersion and a range of adaptive models based on autoregression and integrated moving average. The selection of a specific model depended on factors such as the duration of the existing time series, its characteristics, and the forecasting interval. This review may serve as a resource for Russian-speaking researchers and analysts seeking guidance on selecting an appropriate analytical approach when examining excess deaths during the COVID-19 pandemic in Russia.
评估COVID-19大流行期间超额死亡率的统计方法:范围审查
超额死亡率是衡量某一时期内人口中死亡人数比预期数值增加的一种指标。这种现象可由各种自然或人为灾害引发。在全球COVID-19大流行期间,所有国家的死亡率都有所上升,尽管并非所有死亡都是由冠状病毒感染直接引起的。估计大流行期间的超额死亡率,特别是按主要死亡原因分层,是一个重要的公共卫生问题。然而,这些计算的结果可能因估计超额死亡率所采用的方法方法而有很大差异。本研究的目的是对国际研究界用于量化COVID-19大流行期间超额死亡率的分析方法进行系统回顾。回顾了2020年至2022年期间发表的俄文和英文全文出版物,重点评估了2019冠状病毒病期间的超额死亡率。英文出版物的搜索在MEDLINE数据库(www.pubmed.gov)中进行,而俄语出版物则来自科学电子图书馆数据库(www.elibrary.ru)。在最初确定的725篇出版物中,我们在本综述中纳入了73篇原始研究。在估算超额死亡率的各种统计方法中,最常用的方法是校正过分散的泊松回归和基于自回归和综合移动平均的一系列自适应模型。具体模型的选择取决于现有时间序列的持续时间、其特征和预测间隔等因素。本综述可作为俄语研究人员和分析人员在审查俄罗斯COVID-19大流行期间的超额死亡人数时寻求适当分析方法指导的资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Ekologiya Cheloveka (Human Ecology)
Ekologiya Cheloveka (Human Ecology) Medicine-Medicine (all)
CiteScore
1.00
自引率
0.00%
发文量
62
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