Magnitude, global variation, and temporal development of the COVID-19 infection fatality burden

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Bohk-Ewald , C , Acosta , E , Riffe , T , Dudel , C & Myrskylä , M 2021 ' Magnitude, global variation, and temporal development of the COVID-19 infection fatality burden ' MPIDR Working Paper , no. WP-2021-024 , Max Planck Institute for Demographic Research , Rostock , pp. 21 . https://doi.org/10.4054/MPIDR-WP-2021-024

Title: Magnitude, global variation, and temporal development of the COVID-19 infection fatality burden
Author: Bohk-Ewald, Christina; Acosta, Enrique; Riffe, Tim; Dudel, Christian; Myrskylä, Mikko
Contributor organization: Doctoral Programme in Social Sciences
Population Research Unit (PRU)
Faculty Common Matters
Centre for Social Data Science, CSDS
Center for Population, Health and Society
Publisher: Max Planck Institute for Demographic Research
Date: 2021
Language: eng
Belongs to series:
Belongs to series: MPIDR Working Paper
DOI: https://doi.org/10.4054/MPIDR-WP-2021-024
URI: http://hdl.handle.net/10138/340383
Abstract: How deadly is an infection with SARS-CoV-2 worldwide over time? This information is critical for developing and assessing public health responses on the country and global levels. However, imperfect data have been the most limiting factor for estimating the COVID-19 infection fatality burden during the first year of the pandemic. Here we leverage recently emerged compelling data sources and broadly applicable modeling strategies to estimate the crude infection fatality rate (cIFR) in 77 countries from 28 March 2020 to 31 March 2021, using 2.4 million reported deaths and estimated 435 million infections by age, sex, country, and date. The global average of all cIFR estimates is 1.2% (10th to 90th percentile: 0.2% to 2.4%). The cIFR varies strongly across countries, but little within countries over time, and it is often lower for women than men. Cross-country differences in cIFR are largely driven by the age structures of both the general and the truly infected population. While the broad trends and patterns of the cIFR estimates are more robust, we show that their levels are uncertain and sensitive to input data and modeling choices. In consequence, increased efforts at collecting high-quality data are essential for accurately estimating the cIFR, which is a key indicator for better understanding the health and mortality consequences of this pandemic.
Subject: 5141 Sociology
Usage restriction: openAccess
Self-archived version: publishedVersion


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