Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020-21

被引:1186
作者
Wang, Haidong [1 ]
Paulson, Katherine R. [1 ]
Pease, Spencer A. [1 ]
Watson, Stefanie [1 ]
Comfort, Haley [1 ]
Zheng, Peng [1 ]
Aravkin, Aleksandr Y. [1 ,2 ]
Bisignano, Catherine [1 ]
Barber, Ryan M. [1 ]
Alam, Tahiya [1 ]
Fuller, John E. [1 ]
May, Erin A. [1 ]
Jones, Darwin Phan [1 ]
Frisch, Meghan E. [1 ]
Abbafati, Cristiana [8 ]
Adolph, Christopher [3 ,4 ]
Allorant, Adrien [1 ]
Amlag, Joanne O. [1 ]
Bang-Jensen, Bree [1 ]
Bertolacci, Gregory J. [1 ]
Bloom, Sabina S. [1 ]
Carter, Austin [1 ]
Castro, Emma [1 ]
Chakrabarti, Suman [1 ,5 ]
Chattopadhyay, Jhilik [1 ]
Cogen, Rebecca M. [1 ]
Collins, James K. [1 ]
Cooperrider, Kimberly [1 ]
Dai, Xiaochen [1 ]
Dangel, William James [1 ]
Daoud, Farah [1 ]
Dapper, Carolyn [1 ]
Deen, Amanda [1 ]
Duncan, Bruce B. [9 ]
Erickson, Megan [1 ]
Ewald, Samuel B. [1 ]
Fedosseeva, Tatiana [1 ]
Ferrari, Alize J. [1 ,10 ]
Frostad, Joseph Jon [1 ]
Fullman, Nancy [1 ]
Gallagher, John [1 ]
Gamkrelidze, Amiran [12 ]
Guo, Gaorui [1 ]
He, Jiawei [1 ]
Helak, Monika [1 ]
Henry, Nathaniel J. [13 ]
Hulland, Erin N. [1 ,5 ]
Huntley, Bethany M. [1 ]
Kereselidze, Maia [12 ]
Lazzar-Atwood, Alice [1 ]
机构
[1] Univ Washington, Inst Hlth Metr & Evaluat, Seattle, WA 98195 USA
[2] Univ Washington, Dept Appl Math, Seattle, WA 98195 USA
[3] Univ Washington, Dept Polit Sci, Seattle, WA 98195 USA
[4] Univ Washington, Ctr Stat & Social Sci, Seattle, WA 98195 USA
[5] Univ Washington, Dept Global Hlth, Seattle, WA 98195 USA
[6] Univ Washington, Henry M Jackson Sch Int Studies, Seattle, WA 98195 USA
[7] Univ Washington, Evans Sch Publ Policy & Governance, Seattle, WA 98195 USA
[8] Univ Roma La Sapienza, Dept Jurid & Econ Studies, Rome, Italy
[9] Univ Fed Rio Grande do Sul, Postgrad Program Epidemiol, Porto Alegre, RS, Brazil
[10] Univ Queensland, Sch Publ Hlth, Brisbane, Qld, Australia
[11] Natl Ctr Dis Control & Publ Hlth, Med Stat Dept, Tbilisi, Georgia
[12] Natl Ctr Dis Control & Publ Hlth, Tbilisi, Georgia
[13] Univ Oxford, Nuffield Dept Clin Med, Oxford, England
[14] Queensland Ctr Mental Hlth Res, Sch Publ Hlth, Wacol, Qld, Australia
[15] Queensland Ctr Mental Hlth Res, West Moreton Hosp Hlth Serv, Wacol, Qld, Australia
[16] Queensland Ctr Mental Hlth Res, Policy & Epidemiol Grp, Wacol, Qld, Australia
[17] Univ Sao Paulo, Dept Med, Sao Paulo, Brazil
[18] Univ Toronto, Munk Sch Global Affairs & Publ Policy, Toronto, ON, Canada
[19] Univ Fed Minas Gerais, Dept Maternal & Child Nursing & Publ & Hlth, Belo Horizonte, MG, Brazil
[20] Univ Fed Minas Gerais, Dept Publ Hlth, Belo Horizonte, MG, Brazil
[21] Univ Fed Minas Gerais, Dept Internal Med, Belo Horizonte, MG, Brazil
[22] Univ Fed Minas Gerais, Ctr Telehlth, Belo Horizonte, MG, Brazil
[23] Vital Strategies, Dept Publ Hlth, Sao Paulo, Brazil
[24] Ethiopian Publ Hlth Inst, Natl Data Management Ctr Hlth, Addis Ababa, Ethiopia
[25] Univ Bergen, Ctr Int Hlth, Bergen, Norway
[26] Burlo Garofolo Inst Maternal & Child Hlth, Clin Epidemiol & Publ Hlth Res Unit, Trieste, Italy
[27] Keio Univ, Dept Hlth Policy & Management, Tokyo, Japan
[28] Univ Tokyo, Dept Global Hlth Policy, Tokyo, Japan
[29] Addis Ababa Univ, Sch Elect & Comp Engn, Addis Ababa, Ethiopia
[30] Univ Georgia, Sch Hlth Sci, Tbilisi, Georgia
[31] Yale Univ, Dept Social & Behav Sci, New Haven, CT USA
[32] Jagiellonian Univ Med Coll, Inst Publ Hlth, Krakow, Poland
[33] Agcy Hlth Technol Assessment & Tariff Syst, Warsaw, Poland
[34] South African Med Res Council, Cochrane South Africa, Cape Town, South Africa
[35] Univ Cape Town, Sch Publ Hlth & Family Med, Cape Town, South Africa
基金
美国国家科学基金会; 英国医学研究理事会; 比尔及梅琳达.盖茨基金会;
关键词
D O I
10.1016/S0140-6736(21)02796-3
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background Mortality statistics are fundamental to public health decision making. Mortality varies by time and location, and its measurement is affected by well known biases that have been exacerbated during the COVID-19 pandemic. This paper aims to estimate excess mortality from the COVID-19 pandemic in 191 countries and territories, and 252 subnational units for selected countries, from Jan 1, 2020, to Dec 31, 2021. Methods All-cause mortality reports were collected for 74 countries and territories and 266 subnational locations (including 31 locations in low-income and middle-income countries) that had reported either weekly or monthly deaths from all causes during the pandemic in 2020 and 2021, and for up to 11 year previously. In addition, we obtained excess mortality data for 12 states in India. Excess mortality over time was calculated as observed mortality, after excluding data from periods affected by late registration and anomalies such as heat waves, minus expected mortality. Six models were used to estimate expected mortality; final estimates of expected mortality were based on an ensemble of these models. Ensemble weights were based on root mean squared errors derived from an out-of-sample predictive validity test. As mortality records are incomplete worldwide, we built a statistical model that predicted the excess mortality rate for locations and periods where all-cause mortality data were not available. We used least absolute shrinkage and selection operator (LASSO) regression as a variable selection mechanism and selected 15 covariates, including both covariates pertaining to the COVID-19 pandemic, such as seroprevalence, and to background population health metrics, such as the Healthcare Access and Quality Index, with direction of effects on excess mortality concordant with a meta-analysis by the US Centers for Disease Control and Prevention. With the selected best model, we ran a prediction process using 100 draws for each covariate and 100 draws of estimated coefficients and residuals, estimated from the regressions run at the draw level using draw-level input data on both excess mortality and covariates. Mean values and 95% uncertainty intervals were then generated at national, regional, and global levels. Out-of-sample predictive validity testing was done on the basis of our final model specification. Findings Although reported COVID-19 deaths between Jan 1, 2020, and Dec 31, 2021, totalled 5 center dot 94 million worldwide, we estimate that 18 center dot 2 million (95% uncertainty interval 17 center dot 1-19 center dot 6) people died worldwide because of the COVID-19 pandemic (as measured by excess mortality) over that period. The global all-age rate of excess mortality due to the COVID-19 pandemic was 120 center dot 3 deaths (113 center dot 1-129 center dot 3) per 100 000 of the population, and excess mortality rate exceeded 300 deaths per 100 000 of the population in 21 countries. The number of excess deaths due to COVID-19 was largest in the regions of south Asia, north Africa and the Middle East, and eastern Europe. At the country level, the highest numbers of cumulative excess deaths due to COVID-19 were estimated in India (4 center dot 07 million [3 center dot 71-4 center dot 36]), the USA (1 center dot 13 million [1 center dot 08-1 center dot 18]), Russia (1 center dot 07 million [1 center dot 06-1 center dot 08]), Mexico (798 000 [741 000-867 000]), Brazil (792 000 [730 000-847 000]), Indonesia (736 000 [594 000-955 000]), and Pakistan (664 000 [498 000-847 000]). Among these countries, the excess mortality rate was highest in Russia (374 center dot 6 deaths [369 center dot 7-378 center dot 4] per 100 000) and Mexico (325 center dot 1 [301 center dot 6-353 center dot 3] per 100 000), and was similar in Brazil (186 center dot 9 [172 center dot 2-199 center dot 8] per 100 000) and the USA (179 center dot 3 [170 center dot 7-187 center dot 5] per 100 000). Interpretation The full impact of the pandemic has been much greater than what is indicated by reported deaths due to COVID-19 alone. Strengthening death registration systems around the world, long understood to be crucial to global public health strategy, is necessary for improved monitoring of this pandemic and future pandemics. In addition, further research is warranted to help distinguish the proportion of excess mortality that was directly caused by SARS-CoV-2 infection and the changes in causes of death as an indirect consequence of the pandemic. Funding Bill & Melinda Gates Foundation, J Stanton, T Gillespie, and J and E Nordstrom Copyright (c) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
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收藏
页码:1513 / 1536
页数:24
相关论文
共 40 条
[1]  
Baumgartner J.C., 2021, The Spike in Drug Overdose Deaths During the COVID-19 Pandemic and Policy Options to Move Forward
[2]   Underreporting COVID-19: the curious case of the Indian subcontinent [J].
Biswas, Raaj Kishore ;
Afiaz, Awan ;
Huq, Samin .
EPIDEMIOLOGY AND INFECTION, 2020, 148
[3]  
Bourzac K., 2020, COVID 19 LOCKDOWNS H
[4]  
Burkart KG, 2021, LANCET, V398, P685, DOI 10.1016/S0140-6736(21)01700-1
[5]   Estimating global and regional disruptions to routine childhood vaccine coverage during the COVID-19 pandemic in 2020: a modelling study [J].
Causey, Kate ;
Fullman, Nancy ;
Sorensen, Reed J. D. ;
Galles, Natalie C. ;
Zheng, Peng ;
Aravkin, Aleksandr ;
Danovaro-Holliday, M. Carolina ;
Martinez-Piedra, Ramon ;
Sodha, Samir, V ;
Velandia-Gonzalez, Martha Patricia ;
Gacic-Dobo, Marta ;
Castro, Emma ;
He, Jiawei ;
Schipp, Megan ;
Deen, Amanda ;
Hay, Simon, I ;
Lim, Stephen S. ;
Mosser, Jonathan F. .
LANCET, 2021, 398 (10299) :522-534
[6]  
Centers for Disease Control and Prevention, purported urban subculture that emerged from marginalized economic conditions
[7]  
Centers for Disease Control and Prevention Health Alert Network, 2020, INCR FAT DRUG OV US
[8]   Trends in Drug Overdose Mortality in Ohio During the First 7 Months of the COVID-19 Pandemic [J].
Currie, Janet M. ;
Schnell, Molly K. ;
Schwandt, Hannes ;
Zhang, Jonathan .
JAMA NETWORK OPEN, 2021, 4 (04)
[9]   Fewer cancer diagnoses during the COVID-19 epidemic in the Netherlands Comment [J].
Dinmohamed, Avinash G. ;
Visser, Otto ;
Verhoeven, Rob H. A. ;
Louwman, Marieke W. J. ;
van Nederveen, Francien H. ;
Willems, Stefan M. ;
Merkx, Matthias A. W. ;
Lemmens, Valery E. P. P. ;
Nagtegaal, Iris D. ;
Siesling, Sabine .
LANCET ONCOLOGY, 2020, 21 (06) :750-751
[10]   Impact of COVID-19 lockdown measures on institutional delivery, neonatal admissions and prematurity: a reflection from Lagos, Nigeria [J].
Ezenwa, Beatrice Nkolika ;
Fajolu, Iretiola B. ;
Nabwera, Helen ;
Wang, Duolao ;
Ezeaka, Chinyere, V ;
Allen, Stephen .
BMJ PAEDIATRICS OPEN, 2021, 5 (01)