Selected article for: "cc NC International license and Incubation period"
Author: Tapiwa Ganyani; Cecile Kremer; Dongxuan Chen; Andrea Torneri; Christel Faes; Jacco Wallinga; Niel Hens
Title: Estimating the generation interval for COVID-19 based on symptom onset data
  • Document date: 2020_3_8
    • ID: cq6mivr9_44
    Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.05.20031815 doi: medRxiv preprint 3 Results Table 1 shows parameter estimates of the generation and serial interval distributions for each dataset, assuming an incubation period with mean 5.2 and SD 2.8 days. The mean generation time is estimated to be 5.2 days (95%CI, 3.78 -6.78) for the Singapore data, and 3.95 days (95%CI, 3.01 -4.91) .....
    Document: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.05.20031815 doi: medRxiv preprint 3 Results Table 1 shows parameter estimates of the generation and serial interval distributions for each dataset, assuming an incubation period with mean 5.2 and SD 2.8 days. The mean generation time is estimated to be 5.2 days (95%CI, 3.78 -6.78) for the Singapore data, and 3.95 days (95%CI, 3.01 -4.91) for the Tianjin data. As expected, the estimated means of the generation interval and serial interval distributions are approximately equal but the latter has a larger variance. . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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