Universität zu Köln

Dimpfl, Thomas ORCID: 0000-0003-3415-7412, Soenksen, Jantje, Bechmann, Ingo and Grammig, Joachim (2022). Estimating the SARS-CoV-2 infection fatality rate by data combination: The case of Germany's first wave*. Econom. J., 25 (2). S. 515 - 531. OXFORD: OXFORD UNIV PRESS. ISSN 1368-423X

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Abstract

Assessing the infection fatality rate (IFR) of SARS-CoV-2 in a population is a controversial issue. Due to asymptomatic courses of COVID-19, many infections remain undetected. Reported case fatality rates are therefore poor estimates of the IFR. We propose a strategy to estimate the IFR that combines official data on cases and fatalities with data from seroepidemiological studies in infection hotspots. The application of the method yields an estimate of the IFR of wild-type SARS-CoV-2 in Germany during the first wave of the pandemic of 0.83% (95% CI: [0.69%; 0.98%]), notably higher than the estimate reported in the prominent study by Streeck et al. () (0.36% [0.17%; 0.77%]) and closer to that obtained from a world-wide meta analysis (0.68% [0.53%; 0.82%]), where the difference can be explained by Germany's disadvantageous age structure. Provided that suitable data are available, the proposed method can be applied to estimate the IFR of virus variants and other regions.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Dimpfl, Thomas UNSPECIFIED orcid.org/0000-0003-3415-7412 UNSPECIFIED Soenksen, Jantje UNSPECIFIED UNSPECIFIED UNSPECIFIED Bechmann, Ingo UNSPECIFIED UNSPECIFIED UNSPECIFIED Grammig, Joachim UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-679025
DOI:	10.1093/ectj/utac004
Journal or Publication Title:	Econom. J.
Volume:	25
Number:	2
Page Range:	S. 515 - 531
Date:	2022
Publisher:	OXFORD UNIV PRESS
Place of Publication:	OXFORD
ISSN:	1368-423X
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language PREVALENCE; TESTS; RISK Multiple languages Economics; Mathematics, Interdisciplinary Applications; Social Sciences, Mathematical Methods; Statistics & Probability Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/67902