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Dynamics analysis and optimal control of SIVR epidemic model with incomplete immunity

Yiming Liu, Shuang Jian, Jianguo Gao

2022Advances in Continuous and Discrete Models13 citationsDOIOpen Access PDF

Abstract

Abstract In this paper, we establish an SIVR model with diffusion, spatially heterogeneous, latent infection, and incomplete immunity in the Neumann boundary condition. Firstly, the threshold dynamic behavior of the model is proved by using the operator semigroup method, the well-posedness of the solution and the basic reproduction number $\Re _{0}$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>ℜ</mml:mi> <mml:mn>0</mml:mn> </mml:msub> </mml:math> are given. When $\Re _{0}&lt;1$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>ℜ</mml:mi> <mml:mn>0</mml:mn> </mml:msub> <mml:mo>&lt;</mml:mo> <mml:mn>1</mml:mn> </mml:math> , the disease-free equilibrium is globally asymptotically stable, the disease will be extinct; when $\Re _{0}&gt;1$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>ℜ</mml:mi> <mml:mn>0</mml:mn> </mml:msub> <mml:mo>&gt;</mml:mo> <mml:mn>1</mml:mn> </mml:math> , the epidemic equilibrium is globally asymptotically stable, the disease will persist with probability one. Then, we introduce the patient’s treatment into the system as the control parameter, and the optimal control of the system is discussed by applying the Hamiltonian function and the adjoint equation. Finally, the theoretical results are verified by numerical simulation.

Topics & Concepts

ImmunityDynamics (music)Epidemic controlComputer scienceBiologyMedicinePsychologyCoronavirus disease 2019 (COVID-19)ImmunologyImmune systemInfectious disease (medical specialty)PathologyPedagogyDiseaseMathematical and Theoretical Epidemiology and Ecology ModelsCOVID-19 epidemiological studiesEvolution and Genetic Dynamics
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