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Inverse Coefficient Problem for Epidemiological Mean-Field Formulation

Author

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  • Viktoriya Petrakova

    (Institute of Computational Modeling, Siberian Branch of the Russian Academy of Sciences, Akademgorodok, 50/44, 660036 Krasnoyarsk, Russia
    Sobolev Institute of Mathematics, Siberian Branch of the Russian Academy of Sciences, Koptyuga Ave., 4, 630090 Novosibirsk, Russia)

Abstract

The paper proposes an approach to solving the inverse epidemiological problem, written in terms of the “mean-field” theory. Finding the coefficients of an epidemiological SIR mean-field model is reduced to solving an optimization problem, for the solution of which only zero-order methods can be used. An algorithm for the solution of the inverse coefficient problem is proposed. Computational experiments were carried out to compare the obtained solutions with respect to synthetic and real data. The results of computational experiments have shown the efficiency of this approach. Ways to further improve the approach have also been determined.

Suggested Citation

  • Viktoriya Petrakova, 2024. "Inverse Coefficient Problem for Epidemiological Mean-Field Formulation," Mathematics, MDPI, vol. 12(22), pages 1-19, November.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:22:p:3581-:d:1522093
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    References listed on IDEAS

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    1. La Torre, Davide & Malik, Tufail & Marsiglio, Simone, 2020. "Optimal control of prevention and treatment in a basic macroeconomic–epidemiological model," Mathematical Social Sciences, Elsevier, vol. 108(C), pages 100-108.
    2. Xiang Gao & Jianxing Yu, 2020. "Public governance mechanism in the prevention and control of the COVID-19: information, decision-making and execution," Journal of Chinese Governance, Taylor & Francis Journals, vol. 5(2), pages 178-197, April.
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