Ascertainment rate of novel coronavirus disease (COVID-19) in Japan
Ryosuke Omori, Kenji Mizumoto, Hiroshi Nishiura
Abstract
OBJECTIVE: To estimate the ascertainment rate of novel coronavirus disease (COVID-19). METHODS: The epidemiological dataset of confirmed cases with COVID-19 in Japan as of February 28, 2020 was analyzed. A statistical model was constructed to describe the heterogeneity of the reporting rate by age and severity. We estimated the number of severe and non-severe cases, accounting for under-ascertainment. RESULTS: The ascertainment rate of non-severe cases was estimated at 0.44 (95% confidence interval 0.37-0.50), indicating that the unbiased number of non-severe cases would be more than twice the reported count. CONCLUSIONS: Severe cases are twice as likely to be diagnosed and reported when compared to other cases. Considering that reported cases are usually dominated by non-severe cases, the adjusted total number of cases is also approximately double the observed count. This finding is critical in interpreting the reported data, and it is advised that the mild case data for COVID-19 should always be interpreted as under-ascertained [Au?1].