Back to Search
Start Over
Estimation of incubation period distribution of COVID-19 using disease onset forward time: A novel cross-sectional and forward follow-up study.
- Source :
-
Science advances [Sci Adv] 2020 Aug 14; Vol. 6 (33), pp. eabc1202. Date of Electronic Publication: 2020 Aug 14 (Print Publication: 2020). - Publication Year :
- 2020
-
Abstract
- We have proposed a novel, accurate low-cost method to estimate the incubation-period distribution of COVID-19 by conducting a cross-sectional and forward follow-up study. We identified those presymptomatic individuals at their time of departure from Wuhan and followed them until the development of symptoms. The renewal process was adopted by considering the incubation period as a renewal and the duration between departure and symptoms onset as a forward time. Such a method enhances the accuracy of estimation by reducing recall bias and using the readily available data. The estimated median incubation period was 7.76 days [95% confidence interval (CI): 7.02 to 8.53], and the 90th percentile was 14.28 days (95% CI: 13.64 to 14.90). By including the possibility that a small portion of patients may contract the disease on their way out of Wuhan, the estimated probability that the incubation period is longer than 14 days was between 5 and 10%.<br /> (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).)
- Subjects :
- Adolescent
Adult
Aged
Aged, 80 and over
COVID-19
Child
Child, Preschool
China epidemiology
Coronavirus Infections virology
Cross-Sectional Studies
Female
Follow-Up Studies
Humans
Infant
Infant, Newborn
Male
Middle Aged
Pandemics
Pneumonia, Viral virology
SARS-CoV-2
Young Adult
Betacoronavirus
Coronavirus Infections epidemiology
Coronavirus Infections transmission
Infectious Disease Incubation Period
Models, Statistical
Pneumonia, Viral epidemiology
Pneumonia, Viral transmission
Subjects
Details
- Language :
- English
- ISSN :
- 2375-2548
- Volume :
- 6
- Issue :
- 33
- Database :
- MEDLINE
- Journal :
- Science advances
- Publication Type :
- Academic Journal
- Accession number :
- 32851189
- Full Text :
- https://doi.org/10.1126/sciadv.abc1202