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Estimation of COVID-19 Transmission and Advice on Public Health Interventions

Author

Listed:
  • Qingqing Ji

    (University of Chinese Academy of Sciences, Beijing 100049, China
    Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China)

  • Xu Zhao

    (Faculty of Science, Beijing University of Technology, Beijing 100124, China)

  • Hanlin Ma

    (Faculty of Science, Beijing University of Technology, Beijing 100124, China)

  • Qing Liu

    (Faculty of Science, Beijing University of Technology, Beijing 100124, China)

  • Yiwen Liu

    (University of Chinese Academy of Sciences, Beijing 100049, China
    Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China)

  • Qiyue Guan

    (Party School of the Central Committee of C.P.C (National Academy of Governance), Beijing 100091, China)

Abstract

At the end of 2019, an outbreak of the novel coronavirus (COVID-19) made a profound impact on the country’s production and people’s daily lives. Up until now, COVID-19 has not been fully controlled all over the world. Based on the clinical research progress of infectious diseases, combined with epidemiological theories and possible disease control measures, this paper establishes a Susceptible Infected Recovered (SIR) model that meets the characteristics of the transmission of the new coronavirus, using the least square estimation (LSE) method to estimate the model parameters. The simulation results show that quarantine and containment measures as well as vaccine and drug development measures can control the spread of the epidemic effectively. As can be seen from the prediction results of the model, the simulation results of the epidemic development of the whole country and Nanjing are in agreement with the real situation of the epidemic, and the number of confirmed cases is close to the real value. At the same time, the model’s prediction of the prevention effect and control measures have shed new light on epidemic prevention and control.

Suggested Citation

  • Qingqing Ji & Xu Zhao & Hanlin Ma & Qing Liu & Yiwen Liu & Qiyue Guan, 2021. "Estimation of COVID-19 Transmission and Advice on Public Health Interventions," Mathematics, MDPI, vol. 9(22), pages 1-18, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:22:p:2849-:d:676016
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    References listed on IDEAS

    as
    1. Phenyo E. Lekone & Bärbel F. Finkenstädt, 2006. "Statistical Inference in a Stochastic Epidemic SEIR Model with Control Intervention: Ebola as a Case Study," Biometrics, The International Biometric Society, vol. 62(4), pages 1170-1177, December.
    2. Sepehr Rafieenasab & Amir-Pouyan Zahiri & Ehsan Roohi, 2020. "Prediction of peak and termination of novel coronavirus COVID-19 epidemic in Iran," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 31(11), pages 1-17, November.
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