What’s the best way to estimate and track COVID-19 mortality?

When used correctly, the symptomatic case fatality ratio (sCFR) and the infection fatality ratio (IFR) are better measures by which to monitor COVID-19 epidemics than the commonly reported case fatality ratio (CFR), according to a new study published this week in PLOS Medicine by Anthony Hauser of the University of Bern, Switzerland, and colleagues. 

Reliable estimates of the mortality from SARS-CoV-2 infection are essential to understand the COVID-19 epidemic and develop public health interventions. However, the commonly used CFR—the number of reported deaths divided by the number of reported cases—can be a misleading measure of mortality associated with COVID-19. In the new study, researchers developed a computational model of the dynamics of transmission of SARS-CoV-2 along with COVID-19 associated mortality. The model took into account the delay between infection and death, the increased diagnosis of disease in people with severe symptoms, and stratified data by age. 

The researchers applied the model to Hubei province (China), Austria, Bavaria (Germany), Baden- Württemberg (Germany), Lombardy (Italy), Spain and Switzerland. In Hubei, the calculated IFR was 2.9% (95% credible interval [CrI] 2.4-3.5) while the CFR was 2.4%. In Europe, estimates of the IFR ranged from 0.5 (95% CrI 0.4-0.6) to 1.4% (95% CrI: 1.1-1.6) while the CFR ranged from 3.9% to 17.8%. Overall, estimates of sCFR and IFR were similar to each other and varied less geographically than the CFR. 

“The CFR is not a good predictor of overall mortality from SARS-CoV-2 and should not be used for evaluation of policy or comparison across settings,” the authors say. “The sCFR and IFR, adjusted for [the right biases], are measures that can be used to improve and monitor clinical and public health strategies to reduce the deaths from SARS-CoV-2 infection.”

Funding: JR is funded by the Swiss National Science Foundation (grant 174281). MJC is funded by the Swiss National Science Foundation (grant 176233). This project has received funding from the European Union’s Horizon 2020 research and innovation programme – project EpiPose (No 101003688). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. 

Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: NL is a member of the editorial board of PLOS Medicine. 

Citation: Hauser A, Counotte MJ, Margossian CC, Konstantinoudis G, Low N, Althaus CL, et al. (2020) Estimation of SARS-CoV-2 mortality during the early stages of an epidemic: A modeling study in Hubei, China, and six regions in Europe. PLoS Med 17(7): e1003189. https://doi.org/10.1371/journal.pmed.1003189

Author Affiliations: Anthony Hauser: Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland 

Michel J. Counotte: Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland 

Charles C. Margossian: Department of Statistics, Columbia University, New York, New York, United States of America 

Garyfallos Konstantinoudis: MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom 

Nicola Low: Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland 

Christian L. Althaus: Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland

Julien Riou: Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland, Division of infectious diseases, Federal Office of Public Health, Bern, Switzerland

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