新型冠状病毒肺炎的流行病学参数与模型

Translated title of the contribution: Epidemiological parameters and models of coronavirus disease 2019

Ying Ke Li, Shi Zhao, Yi Jun Lou, Dao Zhou Gao, Lin Yang, Dai Hai He

Research output: Journal article publicationReview articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

The coronavirus disease 2019 (COVID-19) has become a major public health concern internationally. To capture the epidemic growing patterns and quantify the transmissibility, some key epidemiological parameters and dynamic models are of significance for helping us to understand the features of COVID-19 and thus informing the strategic decision-making in combating the outbreak. In this study, we review and summarize the recently released research results about the reproduction numbers, incubation period and serial interval of COVID-19. We summarize the estimates as well as estimation approaches adopted to calculate these epidemiological parameters in the existing literature. These studies found that the basic reproduction number is estimated at 2.6, the mean incubation period at about 5.0 days, and the mean serial interval at about 5.5 days. The COVID-19 infections can increase rapidly if it is not controlled. The control measures including the isolation, quarantine, contact tracing, improvement of public awareness, and adoption of self-protection measures can effectively mitigate the COVID-19 outbreak.

Translated title of the contributionEpidemiological parameters and models of coronavirus disease 2019
Original languageChinese
Article number090202
JournalWuli Xuebao/Acta Physica Sinica
Volume69
Issue number9
DOIs
Publication statusPublished - 5 May 2020

Keywords

  • Basic reproduction number
  • Coronavirus disease 2019
  • Dynamic model
  • Incubation period
  • Serial interval

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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