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. 2020 May 5;172(9):577-582.
doi: 10.7326/M20-0504. Epub 2020 Mar 10.

The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application

Free PMC article

The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application

Stephen A Lauer et al. Ann Intern Med. .
Free PMC article


Background: A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in China in December 2019. There is limited support for many of its key epidemiologic features, including the incubation period for clinical disease (coronavirus disease 2019 [COVID-19]), which has important implications for surveillance and control activities.

Objective: To estimate the length of the incubation period of COVID-19 and describe its public health implications.

Design: Pooled analysis of confirmed COVID-19 cases reported between 4 January 2020 and 24 February 2020.

Setting: News reports and press releases from 50 provinces, regions, and countries outside Wuhan, Hubei province, China.

Participants: Persons with confirmed SARS-CoV-2 infection outside Hubei province, China.

Measurements: Patient demographic characteristics and dates and times of possible exposure, symptom onset, fever onset, and hospitalization.

Results: There were 181 confirmed cases with identifiable exposure and symptom onset windows to estimate the incubation period of COVID-19. The median incubation period was estimated to be 5.1 days (95% CI, 4.5 to 5.8 days), and 97.5% of those who develop symptoms will do so within 11.5 days (CI, 8.2 to 15.6 days) of infection. These estimates imply that, under conservative assumptions, 101 out of every 10 000 cases (99th percentile, 482) will develop symptoms after 14 days of active monitoring or quarantine.

Limitation: Publicly reported cases may overrepresent severe cases, the incubation period for which may differ from that of mild cases.

Conclusion: This work provides additional evidence for a median incubation period for COVID-19 of approximately 5 days, similar to SARS. Our results support current proposals for the length of quarantine or active monitoring of persons potentially exposed to SARS-CoV-2, although longer monitoring periods might be justified in extreme cases.

Primary funding source: U.S. Centers for Disease Control and Prevention, National Institute of Allergy and Infectious Diseases, National Institute of General Medical Sciences, and Alexander von Humboldt Foundation.


Visual Abstract.
Visual Abstract.
The Incubation Period of COVID-19 From Publicly Reported Confirmed Cases Using news reports and press releases from provinces, regions, and countries outside Wuhan, Hubei province, China, this analysis estimates the length of the incubation period of coronavirus disease 2019 (COVID-19) and its public health implications.
Figure 1.
Figure 1.
SARS-CoV-2 exposure (blue), symptom onset (red), and case detection (green) times for 181 confirmed cases. Shaded regions represent the full possible time intervals for exposure, symptom onset, and case detection; points represent the midpoints of these intervals. SARS-CoV-2 = severe acute respiratory syndrome coronavirus 2.
Figure 2.
Figure 2.
Cumulative distribution function of the COVID-19 incubation period estimate from the log-normal model. The estimated median incubation period of COVID-19 was 5.1 days (CI, 4.5 to 5.8 days). We estimated that fewer than 2.5% of infected persons will display symptoms within 2.2 days (CI, 1.8 to 2.9 days) of exposure, whereas symptom onset will occur within 11.5 days (CI, 8.2 to 15.6 days) for 97.5% of infected persons. Horizontal bars represent the 95% CIs of the 2.5th, 50th, and 97.5th percentiles of the incubation period distribution. The estimate of the dispersion parameter is 1.52 (CI, 1.32 to 1.72). COVID-19 = coronavirus disease 2019.
Figure 3.
Figure 3.
Proportion of known symptomatic SARS-CoV-2 infections that have yet to develop symptoms, by number of days since infection, using bootstrapped estimates from a log-normal accelerated failure time model.

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