A QUANTITATIVE ANALYSIS OF PREVENTIVE MEASURES TO MITIGATE THE INFECTIOUS DISEASES USING SIR MODEL BY OPTIMAL CONTROL TECHNIQUE
##plugins.themes.bootstrap3.article.main##
Abstract
Optimal Control Problem with the state equations which describes the standard SIR Model is studied here. we considered the SIR Model with vaccination and without vaccination. We formulated an optimal control problem and derived necessary conditions. Existence of the state and the objective functional are also verified. We also characterized the optimal control by Pontryagin’s maximum principle which minimizes the number of infected individuals and cost of vaccination over some finite period. Whenever the vaccination is carried out for a long period of time, the simulated result effectively works for diseases with high transmission rate. Observations from the numerical simulation reveals that the infectious diseases are most successfully controlled whenever control strategies were adopted at early stages.
##plugins.themes.bootstrap3.article.details##

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
H.Gaff, E. Schaefer. Optimal control applied to vaccination and treatment strategies for various epidemiological models. Mathematical Biosciences and Engineering, 2009, 6: 469–492.
K. Fister, J. Donnelly. Immunotherapy: An optimal control theory approach. Mathematical Bio sciences and Engineering, 2005, 499–510.
K. Wang, A. Fan, A. Tores. Global properties of an improved hepatitis B virus model. Nonlinear Analysis: Real World Applications, 2009. Doi:10.1016/j.nonrwa.2009.11.008.
G. Zaman, Y. Kang, I. Jung. Stability analysis and optimal vaccination of an sir epidemic model. BioSystems, 2008, 93: 240–249.
D. Kirschner, S. Lenhart, S. SerBin. Optimal control of the chemotherapy of HIV. Journal of Mathematical Biology, 1997, 35: 775–792.
T. Zhang, Z. Teng. Global behavior and permanence of sirs epidemic model with time delay. Nonlinear Analysis: Real World Applications (2008), 9: pp. 1409–1424.
Lenhart S. and J. Workman. Optimal Control Applied to Biological Models, Boca Raton, Chapman Hall/CRC, 2007.
(MR2744727) R. M. Neilan and S. Lenhart. An Introduction to Optimal Control with an Application in Disease Modeling, DIMACS Series in Discrete Mathematics, 75 (2010), pp: 67-81.
Fleming, W. H. and R. W. Rishel. Deterministic and Stochastic Optimal Control, Springer Verlag, New York, 1975.
William E. Boyce and Richard C. DiPrima. Elementary Differential Equations and Boundary Value Problems, John Wiley and Sons, New York, 2009.
Pontryagin, L. S. V. G. Boltyanskii, R. V. Gamkrelize, and E. F. Mishchenko. The Mathematical Theory of Optimal Processes, New York, Wiley, 1962.