Estimation of the serial interval and basic reproduction number of COVID-19 in Qom, Iran, and three other countries: A data-driven analysis in the early phase of the outbreak

Transbound Emerg Dis. 2020 Nov;67(6):2860-2868. doi: 10.1111/tbed.13656. Epub 2020 Jun 16.


The outbreak of COVID-19 was first reported from China, and on 19 February 2020, the first case was confirmed in Qom, Iran. The basic reproduction number (R0 ) of infection is variable in different populations and periods. This study aimed to estimate the R0 of COVID-19 in Qom, Iran, and compare it with that in other countries. For estimation of the serial interval, we used data of the 51 confirmed cases of COVID-19 and their 318 close contacts in Qom, Iran. The number of confirmed cases daily in the early phase of the outbreak and estimated serial interval were used for R0 estimation. We used the time-varying method as a method with the least bias to estimate R0 in Qom, Iran, and in China, Italy and South Korea. The serial interval was estimated with a gamma distribution, a mean of 4.55 days and a standard deviation of 3.30 days for the COVID-19 epidemic based on Qom data. The R0 in this study was estimated to be between 2 and 3 in Qom. Of the four countries studied, the lowest R0 was estimated in South Korea (1.5-2) and the highest in Iran (4-5). Sensitivity analyses demonstrated that R0 is sensitive to the applied mean generation time. To the best of the authors' knowledge, this study is the first to estimate R0 in Qom. To control the epidemic, the reproduction number should be reduced by decreasing the contact rate, decreasing the transmission probability and decreasing the duration of the infectious period.

Keywords: COVID-19; Coronavirus Infections; basic reproduction number; disease outbreaks; pandemics.

MeSH terms

  • Basic Reproduction Number*
  • COVID-19 / epidemiology*
  • COVID-19 / transmission*
  • China / epidemiology
  • Contact Tracing*
  • Disease Outbreaks*
  • Iran / epidemiology
  • Italy / epidemiology
  • Republic of Korea / epidemiology
  • SARS-CoV-2 / physiology*