Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/219224
Authors: 
Gubar, Elena
Taynitskiy, Vladislav
Zhu, Quanyan
Year of Publication: 
2018
Citation: 
[Journal:] Games [ISSN:] 2073-4336 [Volume:] 9 [Year:] 2018 [Issue:] 4 [Pages:] 1-18
Abstract: 
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.
Subjects: 
epidemic process
SIR model
optimal control
evolutionary games
virus mutation
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article
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