Imitation dynamics in the mitigation of the novel coronavirus disease (COVID-19) outbreak in Wuhan, China from 2019 to 2020

Shi Zhao, Lewi Stone, Daozhou Gao, Salihu Sabiu Musa, Marc K.C. Chong, Daihai He, Maggie H. Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Background: The coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China on December 2019 in patients presenting with atypical pneumonia. Although ‘city-lockdown’ policy reduced the spatial spreading of the COVID-19, the city-level outbreaks within each city remain a major concern to be addressed. The local or regional level disease control mainly depends on individuals self-administered infection prevention actions. The contradiction between choice of taking infection prevention actions or not makes the elimination difficult under a voluntary acting scheme, and represents a clash between the optimal choice of action for the individual interest and group interests.

Methods: We develop a compartmental epidemic model based on the classic susceptible-exposed-infectious-recovered model and use this to fit the data. Behavioral imitation through a game theoretical decision-making process is incorporated to study and project the dynamics of the COVID-19 outbreak in Wuhan, China. By varying the key model parameters, we explore the probable course of the outbreak in terms of size and timing under several public interventions in improving public awareness and sensitivity to the infection risk as well as their potential impact.

Results: We estimate the basic reproduction number, R0, to be 2.5 (95% CI: 2.4−2.7). Under the current most realistic setting, we estimate the peak size at 0.28 (95% CI: 0.24−0.32) infections per 1,000 population. In Wuhan, the final size of the outbreak is likely to infect 1.35% (95% CI: 1.00−2.12%) of the population. The outbreak will be most likely to peak in the first half of February and drop to daily incidences lower than 10 in June 2020. Increasing sensitivity to take infection prevention actions and the effectiveness of infection prevention measures are likely to mitigate the COVID-19 outbreak in Wuhan.

Conclusions: Through an imitating social learning process, individual-level behavioral change on taking infection prevention actions have the potentials to significantly reduce the COVID-19 outbreak in terms of size and timing at city-level. Timely and substantially resources and supports for improving the willingness-to-act and conducts of self-administered infection prevention actions are recommended to reduce to the COVID-19 associated risks.
Original languageEnglish
Pages (from-to)1-14
Number of pages14
JournalAnnals of Translational Medicine
Volume8
Issue number7
DOIs
Publication statusPublished - Apr 2020

Keywords

  • Coronavirus disease 2019 (COVID-19)
  • mathematical modelling
  • imitation game
  • final epidemic size
  • reproduction number

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