Estimation of standardized real-time fatality rate for ongoing epidemics

Yuanke Qu and Chun Yin Lee

PLOS ONE, 2024, vol. 19, issue 5, 1-17

Abstract: Background: The fatality rate is a crucial metric for guiding public health policies during an ongoing epidemic. For COVID-19, the age structure of the confirmed cases changes over time, bringing a substantial impact on the real-time estimation of fatality. A ‘spurious decrease’ in fatality rate can be caused by a shift in confirmed cases towards younger ages even if the fatalities remain unchanged across different ages. Methods: To address this issue, we propose a standardized real-time fatality rate estimator. A simulation study is conducted to evaluate the performance of the estimator. The proposed method is applied for real-time fatality rate estimation of COVID-19 in Germany from March 2020 to May 2022. Findings: The simulation results suggest that the proposed estimator can provide an accurate trend of disease fatality in all cases, while the existing estimator may convey a misleading signal of the actual situation when the changes in temporal age distribution take place. The application to Germany data shows that there was an increment in the fatality rate at the implementation of the ‘live with COVID’ strategy. Conclusions: As many countries have chosen to coexist with the coronavirus, frequent examination of the fatality rate is of paramount importance.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0303861

DOI: 10.1371/journal.pone.0303861

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