Epidemiological measures for assessing the dynamics of the SARS-CoV-2-outbreak: Simulation study about bias by incomplete case-detection.

During the SARS-CoV-2 outbreak, several epidemiological measures, such as cumulative case-counts (CCC), incidence rates, effective reproduction numbers (Reff) and doubling times, have been used to inform the general public and to justify interventions such as lockdown. It has been very likely that not all infectious people have been identified during the course of the epidemic, which lead to incomplete case-detection. We compare CCC, incidence rates, Reff and doubling times in the presence of incomplete case-detection. For this, an infection-age-structured SIR model is used to simulate a SARS-CoV-2 outbreak followed by a lockdown in a hypothetical population. Different scenarios about temporal variations in case-detection are applied to the four measures during outbreak and lockdown. The biases resulting from incomplete case-detection on the four measures are compared in terms of relative errors. CCC is most prone to bias by incomplete case-detection in all of our settings. Reff is the least biased measure. The possibly biased CCC may lead to erroneous conclusions in cross-country comparisons. With a view to future reporting about this or other epidemics, we recommend including and placing an emphasis on Reff in those epidemiological measures used for informing the general public and policy makers.

Déclaration de conflit d'intérêts

The authors have read the journal’s policy and have declared the following competing interests: TK received research grants from the Gemeinsamer Bundesausschuss (G-BA – Federal Joint Committee, Germany), the Bundesministerium für Gesundheit (BMG – Federal Ministry of Health, Germany) outside of the submitted work. He further has received personal compensation from Eli Lilly & Company, Teva Pharmaceuticals, Total Energies S.E., the BMJ, and Frontiers outside of the submitted work. This does not alter our adherence to PLOS ONE policies on sharing data and materials.