Selected article for: "estimate incubation period and incubation period"

Author: Du, Z C; Gu, J; Li, J H; Lin, X; Wang, Y; Chen, L; Hao, Y T
Title: [Estimating the distribution of COVID-19 incubation period by interval-censored data estimation method].
  • Cord-id: g22sm02v
  • Document date: 2020_7_10
  • ID: g22sm02v
    Snippet: Objectives: The COVID-19 has been the public health issues of global concern, but the incubation period was still under discussion. This study aimed to estimate the incubation period distribution of COVID-19. Methods: The exposure and onset information of COVID-19 cases were collected from the official information platform of provincial or municipal health commissions. The distribution of COVID-19 incubation period was estimated based on the Log- normal, Gamma and Weibull distribution by interva
    Document: Objectives: The COVID-19 has been the public health issues of global concern, but the incubation period was still under discussion. This study aimed to estimate the incubation period distribution of COVID-19. Methods: The exposure and onset information of COVID-19 cases were collected from the official information platform of provincial or municipal health commissions. The distribution of COVID-19 incubation period was estimated based on the Log- normal, Gamma and Weibull distribution by interval-censored data estimation method. Results: A total of 109 confirmed cases were collected, with an average age of 39.825 years. The median COVID-19 incubation period based on Log-normal, Gamma, and Weibull distribution were 4.958 (P(25)-P(75): 3.472-7.318) days, 5.083 (P(25)-P(75): 3.511-7.314) days, and 5.695 (P(25)-P(75): 3.675-7.674) days, respectively. Gamma distribution had the largest log-likelihood result. Conclusions: The distribution of COVID-19 incubation period followed the Gamma distribution, and the interval-censored data estimation method can be used to estimate the incubation period distribution.

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