Journal of Preventive Medicine and Public Health

  • 제53권6호
  • /
  • Pages.405-408
  • /
  • 2020
  • /
  • 1975-8375(pISSN)
  • /
  • 2233-4521(eISSN)
대한예방의학회 (The Korean Society for Preventive Medicine)
권호 표지
DOI QR코드

DOI QR Code

Interpretation of the Basic and Effective Reproduction Number

  • Lim, Jun-Sik (College of Veterinary Medicine and Institute of Veterinary Science, Kangwon National University) ;
  • Cho, Sung-il (Department of Public Health Science, Graduate School of Public Health, Seoul National University) ;
  • Ryu, Sukhyun (Department of Preventive Medicine, Konyang University College of Medicine) ;
  • Pak, Son-Il (College of Veterinary Medicine and Institute of Veterinary Science, Kangwon National University)
  • 투고 : 2020.06.19
  • 심사 : 2020.10.07
  • 발행 : 2020.11.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

In epidemiology, the basic reproduction number (R0) is a term that describes the expected number of infections generated by 1 case in a susceptible population. At the beginning of the coronavirus disease 2019 (COVID-19) pandemic, R0 was frequently referenced by the public health community and the wider public. However, this metric is often misused or misinterpreted. Moreover, the complexity of the process of estimating R0 has caused difficulties for a substantial number of researchers. In this article, in order to increase the accessibility of this concept, we address several misconceptions related to the threshold characteristics of R0 and the effective reproduction number (Rt). Moreover, the appropriate interpretation of the metrics is discussed. R0 should be considered as a population-averaged value that pools the contact structure according to a stochastic transmission process. Furthermore, it is necessary to understand the unavoidable time lag for Rt due to the incubation period of the disease.

키워드

참고문헌

  1. Ryu S, Chun BC; Korean Society of Epidemiology 2019-nCoV Task Force Team. An interim review of the epidemiological characteristics of 2019 novel coronavirus. Epidemiol Health 2020;42:e2020006. https://doi.org/10.4178/epih.e2020006
  2. Ryu S, Ali ST, Lim JS, Chun BC. Estimation of the excess COVID-19 cases in Seoul, South Korea by the students arriving from China. Int J Environ Res Public Health 2020;17(9):3113. https://doi.org/10.3390/ijerph17093113
  3. Delamater PL, Street EJ, Leslie TF, Yang YT, Jacobsen KH. Complexity of the basic reproduction number (R0). Emerg Infect Dis 2019;25(1):1-4. https://doi.org/10.3201/eid2501.171901
  4. Keeling MJ, Rohani P. Modeling infectious diseases in humans and animals. Princeton: Princeton University Press; 2011, p. 62.
  5. Lloyd-Smith JO, Schreiber SJ, Kopp PE, Getz WM. Superspreading and the effect of individual variation on disease emergence. Nature 2005;438(7066):355-359. https://doi.org/10.1038/nature04153
  6. Cauchemez S, Boëlle PY, Thomas G, Valleron AJ. Estimating in real time the efficacy of measures to control emerging communicable diseases. Am J Epidemiol 2006;164(6):591-597. https://doi.org/10.1093/aje/kwj274
  7. Hwang J, Park H, Jung J, Kim SH, Kim N. Basic and effective reproduction numbers of COVID-19 cases in South Korea excluding Sincheonji cases. medRxiv 2020. doi: https://doi.org/10.1101/2020.03.19.20039347.
  8. Thompson RN, Stockwin JE, van Gaalen RD, Polonsky JA, Kamvar ZN, Demarsh PA, et al. Improved inference of time-varying reproduction numbers during infectious disease outbreaks. Epidemics 2019;29:100356. https://doi.org/10.1016/j.epidem.2019.100356

피인용 문헌

  1. Basic reproduction number of African swine fever in wild boars (Sus scrofa) and its spatiotemporal heterogeneity in South Korea vol.22, pp.5, 2020, https://doi.org/10.4142/jvs.2021.22.e71
  2. The detection of the epidemic phase of COVID-19 and the timing of social distancing policies in Korea vol.201, 2020, https://doi.org/10.1016/j.puhe.2021.10.002
  3. Transmission dynamics and control of two epidemic waves of SARS-CoV-2 in South Korea vol.21, pp.1, 2020, https://doi.org/10.1186/s12879-021-06204-6