Excess death estimates from multiverse analysis in 2009-2021

doi:10.1007/s10654-023-00998-2

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	Excess death estimates from multiverse analysis in 2009-2021
	Levitt, Michael 1; Zonta, Francesco2 ; Ioannidis, John P. A.3
	2023-04-01
发表期刊	EUROPEAN JOURNAL OF EPIDEMIOLOGY (IF:7.7[JCR-2023],9.7[5-Year])
ISSN	0393-2990
EISSN	1573-7284
发表状态	已发表
DOI	10.1007/s10654-023-00998-2
摘要	Excess death estimates have great value in public health, but they can be sensitive to analytical choices. Here we propose a multiverse analysis approach that considers all possible different time periods for defining the reference baseline and a range of 1 to 4 years for the projected time period for which excess deaths are calculated. We used data from the Human Mortality Database on 33 countries with detailed age-stratified death information on an annual basis during the period 2009-2021. The use of different time periods for reference baseline led to large variability in the absolute magnitude of the exact excess death estimates. However, the relative ranking of different countries compared to others for specific years remained largely unaltered. The relative ranking of different years for the specific country was also largely independent of baseline. Averaging across all possible analyses, distinct time patterns were discerned across different countries. Countries had declines between 2009 and 2019, but the steepness of the decline varied markedly. There were also large differences across countries on whether the COVID-19 pandemic years 2020-2021 resulted in an increase of excess deaths and by how much. Consideration of longer projected time windows resulted in substantial shrinking of the excess deaths in many, but not all countries. Multiverse analysis of excess deaths over long periods of interest can offer an approach that better accounts for the uncertainty in estimating expected mortality patterns, comparative mortality trends across different countries, and the nature of observed mortality peaks.
关键词	COVID-19 Mortality Excess mortality Modeling Epidemiology
URL	查看原文
收录类别	SCI
语种	英语
资助项目	NIH[R35 GM122543]
WOS研究方向	Public, Environmental & Occupational Health
WOS类目	Public, Environmental & Occupational Health
WOS记录号	WOS:001008053500001
出版者	SPRINGER
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/316410
专题	免疫化学研究所免疫化学研究所_特聘教授组_Michael Levitt组
通讯作者	Ioannidis, John P. A.
作者单位	1.Stanford Univ, Dept Struct Biol, Stanford, CA 94305 USA 2.ShanghaiTech Univ, Shanghai Inst Adv Immunochem Studies, Shanghai 201210, Peoples R China 3.Stanford Univ, Meta Res Innovat Ctr Stanford METR, Dept Med Epidemiol & Populat Hlth Biomed Data Sci, Stanford, CA 94305 USA
推荐引用方式 GB/T 7714	Levitt, Michael,Zonta, Francesco,Ioannidis, John P. A.. Excess death estimates from multiverse analysis in 2009-2021[J]. EUROPEAN JOURNAL OF EPIDEMIOLOGY,2023.
APA	Levitt, Michael,Zonta, Francesco,&Ioannidis, John P. A..(2023).Excess death estimates from multiverse analysis in 2009-2021.EUROPEAN JOURNAL OF EPIDEMIOLOGY.
MLA	Levitt, Michael,et al."Excess death estimates from multiverse analysis in 2009-2021".EUROPEAN JOURNAL OF EPIDEMIOLOGY (2023).