Optimal control problem of an SIR reaction-diffusion model with inequality constraints

Abstract This paper studies an optimal control problem of a susceptible–infected–recovered (SIR) reaction–diffusion model to derive an efficient vaccination strategy for influenza outbreaks. The control problem reflects realistic restrictions associated with limited total vaccination coverage and the maximum daily vaccine administration using state variable inequality constraints. We prove the existence of the optimal control solution and also investigate an optimality system by introducing a penalty function to deal with the constrained optimal control problem. A gradient-based algorithm is discussed to solve the optimality system. The spatial SIR model is solved by using the finite difference method (FDM) in time and the finite element method (FEM) in space. The results of numerical simulations show that the optimal vaccine strategy varies regionally according to the spreading rate of the disease.

[1]  Julien Arino,et al.  A model for influenza with vaccination and antiviral treatment. , 2008, Journal of theoretical biology.

[2]  Jinde Cao,et al.  Effect of time delay on pattern dynamics in a spatial epidemic model , 2014, Physica A: Statistical Mechanics and its Applications.

[3]  A. Hatzakis,et al.  Use of an inactivated vaccine in mitigating pandemic influenza A(H1N1) spread: a modelling study to assess the impact of vaccination timing and prioritisation strategies. , 2009, Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin.

[4]  E. Lyons,et al.  Pandemic Potential of a Strain of Influenza A (H1N1): Early Findings , 2009, Science.

[5]  David G. Luenberger,et al.  Linear and nonlinear programming , 1984 .

[6]  Gerardo Chowell,et al.  Exploring optimal control strategies in seasonally varying flu-like epidemics. , 2017, Journal of theoretical biology.

[7]  Wan-Tong Li,et al.  A reaction–diffusion SIS epidemic model in an almost periodic environment , 2015 .

[8]  Herbert W. Hethcote,et al.  The Mathematics of Infectious Diseases , 2000, SIAM Rev..

[9]  A. Settati,et al.  Dynamics and optimal control of a non-linear epidemic model with relapse and cure , 2018 .

[10]  Tianhu Yu,et al.  Epidemic model with group mixing: Stability and optimal control based on limited vaccination resources , 2018, Commun. Nonlinear Sci. Numer. Simul..

[11]  Zhen Jin,et al.  Pattern transitions in spatial epidemics: Mechanisms and emergent properties , 2016, Physics of Life Reviews.

[12]  J. Robins,et al.  Transmission Dynamics and Control of Severe Acute Respiratory Syndrome , 2003, Science.

[13]  Chao-hua,et al.  An Optimal Control Problem of a Coupled Nonlinear Parabolic Population System , 2007 .

[14]  N. Apreutesei,et al.  An optimal control problem for a pest, predator, and plant system , 2012 .

[15]  Suzanne Lenhart,et al.  Optimal control of treatments in a two-strain tuberculosis model , 2002 .

[16]  H. Kwon,et al.  Optimal control of an influenza model with seasonal forcing and age-dependent transmission rates. , 2013, Journal of theoretical biology.

[17]  Yuan Lou,et al.  Asymptotic profiles of the steady states for an SIS epidemic reaction-diffusion model , 2008 .

[18]  Marcus R. Garvie,et al.  Optimal Control of a Nutrient-Phytoplankton-Zooplankton-Fish System , 2007, SIAM J. Control. Optim..

[19]  V. Barbu Mathematical Methods in Optimization of Differential Systems , 1994 .

[20]  Max Gunzburger,et al.  Perspectives in flow control and optimization , 1987 .

[21]  Zhongjun Ma,et al.  Dynamic stability of an SIQS epidemic network and its optimal control , 2019, Commun. Nonlinear Sci. Numer. Simul..

[22]  Narcisa C. Apreutesei Necessary optimality conditions for three species reaction-diffusion system , 2011, Appl. Math. Lett..

[23]  B. Adams,et al.  HIV dynamics: Modeling, data analysis, and optimal treatment protocols , 2005 .

[24]  John T. Workman,et al.  Optimal Control Applied to Biological Models , 2007 .

[25]  Fred Brauer,et al.  Some simple epidemic models. , 2005, Mathematical biosciences and engineering : MBE.

[26]  Settapat Chinviriyasit,et al.  Numerical modelling of an SIR epidemic model with diffusion , 2010, Appl. Math. Comput..

[27]  Jeehyun Lee,et al.  Constrained optimal control applied to vaccination for influenza , 2016, Computers & Mathematics with Applications.

[28]  Xiao-Qiang Zhao,et al.  A reaction–diffusion malaria model with incubation period in the vector population , 2011, Journal of mathematical biology.

[29]  G. Chowell,et al.  Modeling Optimal Age-Specific Vaccination Strategies Against Pandemic Influenza , 2011, Bulletin of Mathematical Biology.

[30]  Yanzhao Cao,et al.  Optimal control of vector-borne diseases: Treatment and prevention , 2009 .

[31]  Dexing Feng,et al.  s10255-007-0378-z , 2007 .