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Estimation of the incubation period of COVID-19 using viral load data.
Ejima, Keisuke; Kim, Kwang Su; Ludema, Christina; Bento, Ana I; Iwanami, Shoya; Fujita, Yasuhisa; Ohashi, Hirofumi; Koizumi, Yoshiki; Watashi, Koichi; Aihara, Kazuyuki; Nishiura, Hiroshi; Iwami, Shingo.
  • Ejima K; Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, IN, USA. Electronic address: kejima@iu.edu.
  • Kim KS; Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan.
  • Ludema C; Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, IN, USA.
  • Bento AI; Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, IN, USA.
  • Iwanami S; Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan.
  • Fujita Y; Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan.
  • Ohashi H; Department of Virology II, National Institute of Infectious Diseases, Tokyo, Japan; Department of Applied Biological Science, Tokyo University of Science, Noda, Japan.
  • Koizumi Y; National Center for Global Health and Medicine, Tokyo, Japan.
  • Watashi K; Department of Virology II, National Institute of Infectious Diseases, Tokyo, Japan; Department of Applied Biological Science, Tokyo University of Science, Noda, Japan; MIRAI, JST, Saitama, Japan; Institute for Frontier Life and Medical Sciences, Kyoto University, Kyoto, Japan.
  • Aihara K; International Research Center for Neurointelligence, The University of Tokyo, Tokyo, Japan.
  • Nishiura H; Graduate School of Medicine, Hokkaido University, Hokkaido, Japan.
  • Iwami S; Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan; MIRAI, JST, Saitama, Japan; Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Kyoto, Japan; NEXT-Ganken Program, Japanese Foundation for Cancer Research (JFCR), Tokyo, Japan; Science Groove Inc.
Epidemics ; 35: 100454, 2021 06.
Article in English | MEDLINE | ID: covidwho-1135321
Preprint
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ABSTRACT
The incubation period, or the time from infection to symptom onset, of COVID-19 has usually been estimated by using data collected through interviews with cases and their contacts. However, this estimation is influenced by uncertainty in the cases' recall of exposure time. We propose a novel method that uses viral load data collected over time since hospitalization, hindcasting the timing of infection with a mathematical model for viral dynamics. As an example, we used reported data on viral load for 30 hospitalized patients from multiple countries (Singapore, China, Germany, and Korea) and estimated the incubation period. The median, 2.5, and 97.5 percentiles of the incubation period were 5.85 days (95 % CI 5.05, 6.77), 2.65 days (2.04, 3.41), and 12.99 days (9.98, 16.79), respectively, which are comparable to the values estimated in previous studies. Using viral load to estimate the incubation period might be a useful approach, especially when it is impractical to directly observe the infection event.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Viral Load / Infectious Disease Incubation Period / COVID-19 Limits: Adult / Humans / Male Country/Region as subject: Asia Language: English Journal: Epidemics Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Viral Load / Infectious Disease Incubation Period / COVID-19 Limits: Adult / Humans / Male Country/Region as subject: Asia Language: English Journal: Epidemics Year: 2021 Document Type: Article