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Estimation of global case fatality rate of coronavirus disease 2019 (COVID-19) using meta-analyses: Comparison between calendar date and days since the outbreak of the first confirmed case

journal contribution
posted on 2023-08-30, 17:36 authored by Ramy A. Ghayda, Keum Hwa Lee, Young Joo Han, Seohyun Ryu, Sung Hwi Hong, Sojung Yoon, Jeong Gwang, Jinhee Lee, Jun Young Lee, Jae Won Yang, Maria Effenberger, Michael Eisenhut, Andreas Kronbichler, Marco Solmi, Han Li, Louis Jacob, Ai Koyanagi, Joaquim Radua, Jae Il Shin, Lee Smith
Objective: Since the outbreak of the coronavirus disease 2019 (COVID-19) in December of 2019 in China, the estimation of the pandemic’s case fatality rate (CFR) has been the focus and interest of many stakeholders. In this manuscript, we prove that the method of using the cumulative CFR is static and does not reflect the trend according to the daily change per unit of time. Methods: A proportion meta-analysis was carried out on CFR in every country reporting COVID-19 cases. Based on the results, we performed a meta-analysis for global COVID-19 CFR. Each analysis was performed on two different calculations of CFR: according to calendar date and according to days since the outbreak of the first confirmed case. We thus explored an innovative and original calculation of CFR concurrently based on the date of the first confirmed case as well as on a daily basis. Results: For the first time, we showed that using meta-analyses, according to calendar date and days since the outbreak of the first confirmed case were different. Conclusion: We propose that CFR according to days since the outbreak of the first confirmed case might be a better predictor of the current CFR of COVID-19 and its kinetics.

History

Refereed

  • Yes

Volume

100

Page range

302-308

Publication title

International Journal of Infectious Diseases

ISSN

1201-9712

Publisher

Elsevier

File version

  • Accepted version

Language

  • eng

Legacy posted date

2020-09-01

Legacy creation date

2020-09-01

Legacy Faculty/School/Department

COVID-19 Research Collection

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