IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i21p14657-d965996.html
   My bibliography  Save this article

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

Author

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/21/14657/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/21/14657/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fanelli, Duccio & Piazza, Francesco, 2020. "Analysis and forecast of COVID-19 spreading in China, Italy and France," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
    2. Balvinder Singh Gill & Vivek Jason Jayaraj & Sarbhan Singh & Sumarni Mohd Ghazali & Yoon Ling Cheong & Nuur Hafizah Md Iderus & Bala Murali Sundram & Tahir Bin Aris & Hishamshah Mohd Ibrahim & Boon Ha, 2020. "Modelling the Effectiveness of Epidemic Control Measures in Preventing the Transmission of COVID-19 in Malaysia," IJERPH, MDPI, vol. 17(15), pages 1-13, July.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. František Božek & Irena Tušer, 2021. "Measures for Ensuring Sustainability during the Current Spreading of Coronaviruses in the Czech Republic," Sustainability, MDPI, vol. 13(12), pages 1-22, June.
    2. Singhal, Amit & Singh, Pushpendra & Lall, Brejesh & Joshi, Shiv Dutt, 2020. "Modeling and prediction of COVID-19 pandemic using Gaussian mixture model," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    3. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "Dynamic tracking with model-based forecasting for the spread of the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    4. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "A SIR model assumption for the spread of COVID-19 in different communities," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    5. Song, Jialu & Xie, Hujin & Gao, Bingbing & Zhong, Yongmin & Gu, Chengfan & Choi, Kup-Sze, 2021. "Maximum likelihood-based extended Kalman filter for COVID-19 prediction," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    6. Huang, Yubo & Wu, Yan & Zhang, Weidong, 2020. "Comprehensive identification and isolation policies have effectively suppressed the spread of COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    7. Chakraborty, Tanujit & Ghosh, Indrajit, 2020. "Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
    8. Gaetano Perone, 2020. "An ARIMA model to forecast the spread and the final size of COVID-2019 epidemic in Italy," Health, Econometrics and Data Group (HEDG) Working Papers 20/07, HEDG, c/o Department of Economics, University of York.
    9. Luca Bonacini & Giovanni Gallo & Fabrizio Patriarca, 2021. "Identifying policy challenges of COVID-19 in hardly reliable data and judging the success of lockdown measures," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(1), pages 275-301, January.
    10. Memon, Zaibunnisa & Qureshi, Sania & Memon, Bisharat Rasool, 2021. "Assessing the role of quarantine and isolation as control strategies for COVID-19 outbreak: A case study," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    11. Jahanshahi, Hadi & Munoz-Pacheco, Jesus M. & Bekiros, Stelios & Alotaibi, Naif D., 2021. "A fractional-order SIRD model with time-dependent memory indexes for encompassing the multi-fractional characteristics of the COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    12. Salgotra, Rohit & Gandomi, Mostafa & Gandomi, Amir H., 2020. "Evolutionary modelling of the COVID-19 pandemic in fifteen most affected countries," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    13. Bimal Kumar Mishra, 2022. "Stochastic models on the transmission of novel COVID-19," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(2), pages 599-603, April.
    14. Swapnarekha, H. & Behera, Himansu Sekhar & Nayak, Janmenjoy & Naik, Bighnaraj, 2020. "Role of intelligent computing in COVID-19 prognosis: A state-of-the-art review," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    15. Satoh, Daisuke & Uchida, Masato, 2021. "Riccati equation as topology-based model of computer worms and discrete SIR model with constant infectious period," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    16. Aguilar-Canto, Fernando Javier & de León, Ugo Avila-Ponce & Avila-Vales, Eric, 2022. "Sensitivity theorems of a model of multiple imperfect vaccines for COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    17. Han, Zhimin & Wang, Yi & Cao, Jinde, 2023. "Impact of contact heterogeneity on initial growth behavior of an epidemic: Complex network-based approach," Applied Mathematics and Computation, Elsevier, vol. 451(C).
    18. Goyal, Manish & Baskonus, Haci Mehmet & Prakash, Amit, 2020. "Regarding new positive, bounded and convergent numerical solution of nonlinear time fractional HIV/AIDS transmission model," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    19. Ashwin Muniyappan & Balamuralitharan Sundarappan & Poongodi Manoharan & Mounir Hamdi & Kaamran Raahemifar & Sami Bourouis & Vijayakumar Varadarajan, 2022. "Stability and Numerical Solutions of Second Wave Mathematical Modeling on COVID-19 and Omicron Outbreak Strategy of Pandemic: Analytical and Error Analysis of Approximate Series Solutions by Using HPM," Mathematics, MDPI, vol. 10(3), pages 1-27, January.
    20. Reis, Ruy Freitas & de Melo Quintela, Bárbara & de Oliveira Campos, Joventino & Gomes, Johnny Moreira & Rocha, Bernardo Martins & Lobosco, Marcelo & Weber dos Santos, Rodrigo, 2020. "Characterization of the COVID-19 pandemic and the impact of uncertainties, mitigation strategies, and underreporting of cases in South Korea, Italy, and Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14657-:d:965996. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.