Improved time-varying reproduction numbers using the generation interval for COVID-19

Tobhin Kim, Hyojung Lee, Sungchan Kim, Changhoon Kim, Hyunjin Son, Sunmi Lee

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Estimating key epidemiological parameters, such as incubation period, serial interval (SI), generation interval (GI) and latent period, is essential to quantify the transmissibility and effects of various interventions of COVID-19. These key parameters play a critical role in quantifying the basic reproduction number. With the hard work of epidemiological investigators in South Korea, estimating these key parameters has become possible based on infector-infectee surveillance data of COVID-19 between February 2020 and April 2021. Herein, the mean incubation period was estimated to be 4.9 days (95% CI: 4.2, 5.7) and the mean generation interval was estimated to be 4.3 days (95% CI: 4.2, 4.4). The mean serial interval was estimated to be 4.3, with a standard deviation of 4.2. It is also revealed that the proportion of presymptomatic transmission was ~57%, which indicates the potential risk of transmission before the disease onset. We compared the time-varying reproduction number based on GI and SI and found that the time-varying reproduction number based on GI may result in a larger estimation of (Formula presented.), which refers to the COVID-19 transmission potential around the rapid increase of cases. This highlights the importance of considering presymptomatic transmission and generation intervals when estimating the time-varying reproduction number.

Original languageEnglish
Article number1185854
JournalFrontiers in Public Health
Volume11
DOIs
StatePublished - 2023

Keywords

  • COVID-19
  • generation interval
  • incubation period
  • latent period
  • presymptomatic transmission
  • serial interval

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