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Stochastic Optimal Control Analysis For The Covid-19 Epidemic Model Under Real Statistics

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  • PEIJIANG LIU

    (School of Statistics and Mathematics, Guangdong University of Finance and Economics, Big Data and Educational Statistics Application Laboratory, Guangzhou 510320, P. R. China2School of Statistics and Mathematics, Guangdong University of Finance and Economics, Guangzhou 510320, P. R. China)

  • ABDULLAHI YUSUF

    (Department of Computer Engineering, Biruni University, Istanbul, Turkey4Department of Mathematics, Federal University Dutse, Jigawa, Nigeria)

  • TING CUI

    (School of Economics, Guangdong University of Finance and Economics, Guangzhou 510320, P. R. China)

  • ANWARUD DIN

    (Department of Mathematics, Sun Yat-sen University, Guangzhou 510275, P. R. China)

Abstract

The COVID-19 pandemic started, a global effort to develop vaccines and make them available to the public, has prompted a turning point in the history of vaccine development. In this study, we formulate a stochastic COVID-19 epidemic mathematical model with a vaccination effect. First, we present the model equilibria and basic reproduction number. To indicate that our stochastic model is well-posed, we prove the existence and uniqueness of a positive solution at the beginning. The sufficient conditions of the extinction and the existence of a stationary probability measure for the disease are established. For controlling the transmission of the disease by the application of external sources, the theory of stochastic optimality is established. The nonlinear least-squares procedure is utilized to parametrize the model from actual cases reported in Pakistan. The numerical simulations are carried out to demonstrate the analytical results.

Suggested Citation

  • Peijiang Liu & Abdullahi Yusuf & Ting Cui & Anwarud Din, 2022. "Stochastic Optimal Control Analysis For The Covid-19 Epidemic Model Under Real Statistics," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 30(08), pages 1-24, December.
    • Handle: RePEc:wsi:fracta:v:30:y:2022:i:08:n:s0218348x22402204
    DOI: 10.1142/S0218348X22402204
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    Cited by:

    1. Khatun, Mst Sebi & Mahato, Kiriti Bhusan & Das, Pritha, 2024. "Dynamics of an SuSaV IR epidemic model with stochastic optimal control and awareness programs," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).
    2. Olivares, Alberto & Staffetti, Ernesto, 2023. "A statistical moment-based spectral approach to the chance-constrained stochastic optimal control of epidemic models," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).

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