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phat 24(1):

Research Article

Optimal control in models of virus propagation

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  • @ARTICLE{10.4108/eetpht.10.6041,
        author={Xiuxiu Liu and Elena Gubar},
        title={Optimal control in models of virus propagation},
        journal={EAI Endorsed Transactions on Pervasive Health and Technology},
        volume={10},
        number={1},
        publisher={EAI},
        journal_a={PHAT},
        year={2024},
        month={12},
        keywords={Optimal control, virus propagation, epidemic model, basic reproduction number, preemptive vaccine},
        doi={10.4108/eetpht.10.6041}
    }
    
  • Xiuxiu Liu
    Elena Gubar
    Year: 2024
    Optimal control in models of virus propagation
    PHAT
    EAI
    DOI: 10.4108/eetpht.10.6041
Xiuxiu Liu1,*, Elena Gubar1,*
  • 1: St Petersburg University
*Contact email: st091520@student.spbu.ru, st091520@student.spbu.ru

Abstract

Based on the SEIRD model, we consider that when multiple viruses of different virulence coexist, the more virulent virus will reinfect nodes already infected by the less virulent virus, which we call here Superexposed. Based on the state transitions, the corresponding differential equations and cost functions are established, then building the corresponding optimal control problem, where the vaccine efficiency and drug efficiency are controlled variables. This nonlinear optimal control problem is solved by Pontryagin’s maximum principle to finding the structure of the optimal control strategies. Based on the definition of the basic regeneration number, yielding the R0 value for the model, then discussed the final epidemic size. In the numerical analysis section, we validate the accuracy of the structure, fitting the behavior of each state and the effect of different parameter values.

Keywords
Optimal control, virus propagation, epidemic model, basic reproduction number, preemptive vaccine
Received
2024-12-04
Accepted
2024-12-04
Published
2024-12-04
Publisher
EAI
http://dx.doi.org/10.4108/eetpht.10.6041

Copyright © 2024 Liu et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NCSA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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