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Construction and Simulation Analysis of Epidemic Propagation Model Based on COVID-19 Characteristics

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  • Sheng Bin

    (College of Computer Science & Technology, Qingdao University, Qingdao 266071, China)

Abstract

This paper proposes the epidemic propagation model SEAIHR to elucidate the propagation mechanism of the Corona Virus Disease of 2019 (COVID-19). Based on the analysis of the propagation characteristics of COVID-19, the hospitalization isolation state and recessive healing state are introduced. The home morbidity state is introduced to consider the self-healing of asymptomatic infected populations, the early isolation of close contractors, and the impact of epidemic prevention and control measures. In this paper, by using the real epidemic data combined with the changes in parameters in different epidemic stages, multiple model simulation comparative tests were conducted. The experimental results showed that the fitting and prediction accuracy of the SEAIHR model was significantly better than the classical epidemic propagation model, and the fitting error was 34.4–72.8% lower than that of the classical model in the early and middle stages of the epidemic.

Suggested Citation

  • Sheng Bin, 2022. "Construction and Simulation Analysis of Epidemic Propagation Model Based on COVID-19 Characteristics," IJERPH, MDPI, vol. 20(1), pages 1-16, December.
    • Handle: RePEc:gam:jijerp:v:20:y:2022:i:1:p:132-:d:1011321
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    References listed on IDEAS

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    1. Asamoah, Joshua Kiddy K. & Jin, Zhen & Sun, Gui-Quan & Seidu, Baba & Yankson, Ernest & Abidemi, Afeez & Oduro, F.T. & Moore, Stephen E. & Okyere, Eric, 2021. "Sensitivity assessment and optimal economic evaluation of a new COVID-19 compartmental epidemic model with control interventions," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    2. Annas, Suwardi & Isbar Pratama, Muh. & Rifandi, Muh. & Sanusi, Wahidah & Side, Syafruddin, 2020. "Stability analysis and numerical simulation of SEIR model for pandemic COVID-19 spread in Indonesia," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    3. Korolev, Ivan, 2021. "Identification and estimation of the SEIRD epidemic model for COVID-19," Journal of Econometrics, Elsevier, vol. 220(1), pages 63-85.
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