Modelling COVID-19 outbreak on the Diamond Princess ship using the public surveillance data

Shi Zhao, Peihua Cao, Daozhou Gao, Zian Zhuang, Weiming Wang, Jinjun Ran, Kai Wang, Lin Yang, Mohammad R. Einollahi, Yijun Lou, Daihai He, Maggie H. Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)

Abstract

The novel coronavirus disease 2019 (COVID-19) outbreak on the Diamond Princess (DP) ship has caused over 634 cases as of February 20, 2020. We model the transmission process on DP ship as a stochastic branching process, and estimate the reproduction number at the innitial phase of 2.9 (95%CrI: 1.7–7.7). The epidemic doubling time is 3.4 days, and thus timely actions on COVID-19 control were crucial. We estimate the COVID-19 transmissibility reduced 34% after the quarantine program on the DP ship which was implemented on February 5. According to the model simulation, relocating the population at risk may sustainably decrease the epidemic size, postpone the timing of epidemic peak, and thus relieve the tensive demands in the healthcare. The lesson learnt on the ship should be considered in other similar settings.

Original languageEnglish
Pages (from-to)189-195
Number of pages7
JournalInfectious Disease Modelling
Volume7
Issue number2
DOIs
Publication statusPublished - Jun 2022

Keywords

  • COVID-19
  • Diamond princess ship
  • Reproduction number
  • Transmission

ASJC Scopus subject areas

  • Health Policy
  • Infectious Diseases
  • Applied Mathematics

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