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Article

Optimal Control of Heterogeneous Mutating Viruses

by 1,†, 1,*,† and 2,†
1
Faculty of Applied Mathematics and Control Processes, St. Petersburg State University, Universitetskii Prospekt 35, Petergof, Saint-Petersburg 198504, Russia
2
Department of Electrical and Computer Engineering, Tandon School of Engineering, New York University, Brooklyn, NY 11201, USA
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Games 2018, 9(4), 103; https://doi.org/10.3390/g9040103
Received: 25 August 2018 / Revised: 25 November 2018 / Accepted: 7 December 2018 / Published: 13 December 2018
(This article belongs to the Special Issue Game Models for Cyber-Physical Infrastructures)
Different strains of influenza viruses spread in human populations during every epidemic season. As the size of an infected population increases, the virus can mutate itself and grow in strength. The traditional epidemic SIR model does not capture virus mutations and, hence, the model is not sufficient to study epidemics where the virus mutates at the same time as it spreads. In this work, we establish a novel framework to study the epidemic process with mutations of influenza viruses, which couples the SIR model with replicator dynamics used for describing virus mutations. We formulated an optimal control problem to study the optimal strategies for medical treatment and quarantine decisions. We obtained structural results for the optimal strategies and used numerical examples to corroborate our results. View Full-Text
Keywords: epidemic process; SIR model; optimal control; evolutionary games; virus mutation epidemic process; SIR model; optimal control; evolutionary games; virus mutation
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MDPI and ACS Style

Gubar, E.; Taynitskiy, V.; Zhu, Q. Optimal Control of Heterogeneous Mutating Viruses. Games 2018, 9, 103. https://doi.org/10.3390/g9040103

AMA Style

Gubar E, Taynitskiy V, Zhu Q. Optimal Control of Heterogeneous Mutating Viruses. Games. 2018; 9(4):103. https://doi.org/10.3390/g9040103

Chicago/Turabian Style

Gubar, Elena, Vladislav Taynitskiy, and Quanyan Zhu. 2018. "Optimal Control of Heterogeneous Mutating Viruses" Games 9, no. 4: 103. https://doi.org/10.3390/g9040103

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