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Serial interval of novel coronavirus (COVID-19) infections

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Title: Serial interval of novel coronavirus (COVID-19) infections
Authors: Nishiura, Hiroshi Browse this author →KAKEN DB
Linton, Natalie M. Browse this author
Akhmetzhanov, Andrei R. Browse this author
Keywords: Coronavirus
Illness onset
Generation time
Statistical model
Issue Date: Apr-2020
Publisher: Elsevier
Journal Title: International journal of infectious diseases
Volume: 93
Start Page: 284
End Page: 286
Publisher DOI: 10.1016/j.ijid.2020.02.060
Abstract: Objective: To estimate the serial interval of novel coronavirus (COVID-19) from information on 28 infector-infectee pairs. Methods: We collected dates of illness onset for primary cases (infectors) and secondary cases (infectees) from published research articles and case investigation reports. We subjectively ranked the credibility of the data and performed analyses on both the full dataset (n = 28) and a subset of pairs with highest certainty in reporting (n = 18). In addition, we adjust for right truncation of the data as the epidemic is still in its growth phase. Results: Accounting for right truncation and analyzing all pairs, we estimated the median serial interval at 4.0 days (95% credible interval [CrI]: 3.1, 4.9). Limiting our data to only the most certain pairs, the median serial interval was estimated at 4.6 days (95% CrI: 3.5, 5.9). Conclusions: The serial interval of COVID-19 is close to or shorter than its median incubation period. This suggests that a substantial proportion of secondary transmission may occur prior to illness onset. The COVID-19 serial interval is also shorter than the serial interval of severe acute respiratory syndrome (SARS), indicating that calculations made using the SARS serial interval may introduce bias. (C) 2020 The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases.
Type: article
Appears in Collections:医学院・医学研究院 (Graduate School of Medicine / Faculty of Medicine) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

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