ArticlePloS one2024
Estimation of standardized real-time fatality rate for ongoing epidemics.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- A Bayesian estimator of the real-time case fatality rate in emerging pandemic to inform public health policy-making.BMC infectious diseases · 2026Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
methodsTo 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.
findingsThe 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.
conclusionsAs many countries have chosen to coexist with the coronavirus, frequent examination of the fatality rate is of paramount importance.
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