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A Multistage Time-Delay Control Model for COVID-19 Transmission

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Listed:
  • Zhuang Wu

    (School of Management Engineering, Capital University of Economics and Business, 121 Zhangjia Road, Huaxiang, Fengtai District, Beijing 100070, China)

  • Yuanyuan Wang

    (School of Management Engineering, Capital University of Economics and Business, 121 Zhangjia Road, Huaxiang, Fengtai District, Beijing 100070, China)

  • Jing Gao

    (School of Management Engineering, Capital University of Economics and Business, 121 Zhangjia Road, Huaxiang, Fengtai District, Beijing 100070, China)

  • Jiayang Song

    (School of Management Engineering, Capital University of Economics and Business, 121 Zhangjia Road, Huaxiang, Fengtai District, Beijing 100070, China)

  • Yi Zhang

    (School of Management Engineering, Capital University of Economics and Business, 121 Zhangjia Road, Huaxiang, Fengtai District, Beijing 100070, China)

Abstract

With the transmission of the COVID-19 epidemic at home and abroad, this paper considers the spread process in China, improves the classic epidemic SEIR model, and establishes a multistage time-delay control model (MTCM) for COVID-19 transmission. The MTCM divides the spread of COVID-19 into three periods: the outbreak period, the control period and the steady period. The classical SEIR model, the improved SEQIR model and the SEQIR Ⅱ model correspond to the three periods. The classical SEIR model was adopted for the outbreak period and yielded results that were consistent with the observed early propagation of COVID-19 transmission. In the control period, adding isolation measures and a time delay to the MTCM and adjusting the rates yielded a better simulation effect. In the steady period, the focus of consideration is the number of new patients, population movement (in-migration and out-migration of the population) and patient classification (symptomatic and asymptomatic patients). The MCTM was used for simulation, and the comparison results revealed that the simulated data of the MCTM (improved SEQIR model) and the actual data are similar in the control period. The control policy of isolation measures is effective. New infections, population flow and patients with symptomatic or asymptomatic symptoms are more consistent with the steady period characteristics. The multi-stage time-delay control model for COVID-19 transmission provides theoretical methods and good prevention and control measures for future epidemic policy formulation.

Suggested Citation

  • Zhuang Wu & Yuanyuan Wang & Jing Gao & Jiayang Song & Yi Zhang, 2022. "A Multistage Time-Delay Control Model for COVID-19 Transmission," Sustainability, MDPI, vol. 14(21), pages 1-23, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14657-:d:965996
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    References listed on IDEAS

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    2. He, Shaobo & Banerjee, Santo, 2018. "Epidemic outbreaks and its control using a fractional order model with seasonality and stochastic infection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 408-417.
    3. Fanelli, Duccio & Piazza, Francesco, 2020. "Analysis and forecast of COVID-19 spreading in China, Italy and France," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
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