Modelling the COVID-19 Epidemic Process of Shenzhen and the Effect of Social Intervention Based on SEIR Model

Wenjie Zhang and Wai Kin Victor Chan ()
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Wenjie Zhang: Tsinghua University
Wai Kin Victor Chan: Tsinghua University

A chapter in AI and Analytics for Public Health, 2022, pp 393-403 from Springer

Abstract: Abstract The outbreak of coronavirus disease 2019 (COVID-19) in China has seriously affected the health and daily life of Chinese people. To contain the epidemic, the government made emergency policies quickly, including large-scale social intervention. But the impact of social intervention is still unclear. As the epidemic is affecting other countries all over the world, it is necessary to assess this action. In this work, the COVID-19 outbreak process of Shenzhen and the effect of social intervention is analyzed based on a modified Susceptible-Exposed-Infectious-Removed (SEIR) model. This model takes the asymptomatic characteristic of COVID-19 into consideration. Also, the virus carriers who are in exposed stage having infectivity are taken into account. The transmission rate was estimated from Wuhan data at the early virus spreading stage and was used to simulate the virus spreading process in Shenzhen without any health intervention. The recovery rate is simulated as a function of time. This work gives a numerical simulation of the real epidemic process in Shenzhen and measure the effect of social intervention by reduction of contact rate. It concludes that social intervention has great impact on epidemic control. Reducing offline contact will shorten the duration of this pandemic, lower the peak value and dramatically lower the total infective cases.

Keywords: COVID-19; SEIR; Social intervention; Epidemic (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-75166-1_29

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DOI: 10.1007/978-3-030-75166-1_29

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