tetano
Editor, Senior Moderator
Int J Infect Dis. 2020 May 7. pii: S1201-9712(20)30292-7. doi: 10.1016/j.ijid.2020.04.080. [Epub ahead of print]
Ascertainment rate of novel coronavirus disease (COVID-19) in Japan.
Omori R[SUP]1[/SUP], Mizumoto K[SUP]2[/SUP], Nishiura H[SUP]3[/SUP].
Author information
Abstract
OBJECTIVE:
To estimate the ascertainment rate of novel coronavirus (COVID-19).
METHODS:
We analyzed the epidemiological dataset of confirmed cases with COVID-19 in Japan as of 28 February 2020. A statistical model was constructed to describe the heterogeneity of 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 unbiased number of non-cases would be more than twice the reported count.
CONCLUSIONS:
Severe cases are twice more likely diagnosed and reported than other cases. Considering that reported cases are usually dominated by non-severe cases, the adjusted total number of cases is also about a double of observed count. Our finding is critical in interpreting the reported data, and it is advised to interpret mild case data of COVID-19 as always under-ascertained.
Copyright ? 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.
KEYWORDS:
coronavirus; diagnosis; epidemiology; outbreak; reporting; statistical model; viruses
PMID:32389846DOI:10.1016/j.ijid.2020.04.080
Free full text
Ascertainment rate of novel coronavirus disease (COVID-19) in Japan.
Omori R[SUP]1[/SUP], Mizumoto K[SUP]2[/SUP], Nishiura H[SUP]3[/SUP].
Author information
Abstract
OBJECTIVE:
To estimate the ascertainment rate of novel coronavirus (COVID-19).
METHODS:
We analyzed the epidemiological dataset of confirmed cases with COVID-19 in Japan as of 28 February 2020. A statistical model was constructed to describe the heterogeneity of 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 unbiased number of non-cases would be more than twice the reported count.
CONCLUSIONS:
Severe cases are twice more likely diagnosed and reported than other cases. Considering that reported cases are usually dominated by non-severe cases, the adjusted total number of cases is also about a double of observed count. Our finding is critical in interpreting the reported data, and it is advised to interpret mild case data of COVID-19 as always under-ascertained.
Copyright ? 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.
KEYWORDS:
coronavirus; diagnosis; epidemiology; outbreak; reporting; statistical model; viruses
PMID:32389846DOI:10.1016/j.ijid.2020.04.080
Free full text