Research article

Markovian switching for near-optimal control of a stochastic SIV epidemic model

  • Received: 23 November 2018 Accepted: 21 January 2019 Published: 20 February 2019
  • As it is known that environmental perturbation is a key component of epidemic models, and Markov process reveals how the noise affects epidemic systems. The paper introduces Markov chain into a stochastic susceptible-infected-vaccination(SIV) epidemic model composed of vaccination and saturated treatment to analyze the near-optimal control. Based on Pontryagin stochastic maximum principle, the paper gives adequate and all necessary conditions for near-optimal control. Numerical simulations are presented to display the theoretical results and verify the effect of treatment control on epidemic diseases.

    Citation: ZongWang, Qimin Zhang, Xining Li. Markovian switching for near-optimal control of a stochastic SIV epidemic model[J]. Mathematical Biosciences and Engineering, 2019, 16(3): 1348-1375. doi: 10.3934/mbe.2019066

    Related Papers:

  • As it is known that environmental perturbation is a key component of epidemic models, and Markov process reveals how the noise affects epidemic systems. The paper introduces Markov chain into a stochastic susceptible-infected-vaccination(SIV) epidemic model composed of vaccination and saturated treatment to analyze the near-optimal control. Based on Pontryagin stochastic maximum principle, the paper gives adequate and all necessary conditions for near-optimal control. Numerical simulations are presented to display the theoretical results and verify the effect of treatment control on epidemic diseases.
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    © 2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
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