Inverse Coefficient Problem for Epidemiological Mean-Field Formulation

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.

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Publication Details

Journal
Mathematics
Published
2024-11-15
DOI
https://doi.org/10.3390/math12223581
Citations
4
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
1.58

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article

Inverse Coefficient Problem for Epidemiological Mean-Field Formulation

Viktoriya Petrakova
4 citations
Mathematics
COVID-19 epidemiological studies
1.58
article

Inverse Coefficient Problem for Epidemiological Mean-Field Formulation

Viktoriya Petrakova
article en
4 citations

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.

MathematicsVol. 12(22)
Sobolev Institute of Mathematics (RU), Siberian Branch of the Russian Academy of Sciences (RU), Institute of Computational Modeling (RU)
Ministry of Science and Higher Education of the Russian Federation
Good health and well-being
Openalex Percentile: Top 18%
COVID-19 epidemiological studies
1.58
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