Abstract: The paper discusses the problems of using optimal control models with constraints in the form of systems of ordinary differential equations to predict the development of an epidemic. The issue discussed here is related to the evaluation of the model functional that determines the behavior of a population under an epidemic process. For the model to forecast adequately, its functional should describe the processes that actually occur in the population during the simulated period of time (for example, the population’s attitude to isolation measures or vaccination). At the same time, without knowledge of the socio-economic characteristics of the region, it is quite difficult to perform an adequate evaluation of the population’s behavior. The formulation of the inverse problem proposed in the paper is about representing the control functional as a linear combination of other functionals, each of which describes one of the processes that determines the behavior of the population. The coefficients in such a linear combination can be restored by solving the inverse coefficient problem based on real data. The problems associated with this formulation are discussed in this article. The paper also proposes an optimal control model where control is used to adjust the virus contagiousness parameter. Its advantage is shown on real data on COVID-19 incidence over the SIR-type model with the same population structure. It is obtained the estimate of the relationship between the weighting coefficients included in the functional components for such a model, which can be used for computational realization of the model.

Cite: Petrakova V. , Krivorot’ko O.
Study of the Formulation of the Inverse Epidemiological Optimal Control Problem
Differential Equations and Dynamical Systems. 2025. DOI: 10.1007/s12591-025-00749-7 OpenAlex

Dates:

Submitted:	Mar 21, 2025
Accepted:	Dec 1, 2025
Published online:	Dec 29, 2025

Identifiers:

OpenAlex:

W7117484596

Citing: Пока нет цитирований

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