An Optimal Treatment Control of TB-HIV Coinfection

An optimal control on the treatment of the transmission of tuberculosis-HIV coinfection model is proposed in this paper. We use two treatments, that is, anti-TB and antiretroviral, to control the spread of TB and HIV infections, respectively. We first present an uncontrolled TB-HIV coinfection model. The model exhibits four equilibria, namely, the disease-free, the HIV-free, the TB-free, and the coinfection equilibria. We further obtain two basic reproduction ratios corresponding to TB and HIV infections. These ratios determine the existence and stability of the equilibria of the model. The optimal control theory is then derived analytically by applying the Pontryagin Maximum Principle. The optimality system is performed numerically to illustrate the effectiveness of the treatments.

[1]  Mathematical modeling of drug resistance in tuberculosis transmission and optimal control treatment , 2014 .

[2]  Agraj Tripathi,et al.  Modelling the effect of tuberculosis on the spread of HIV infection in a population with density-dependent birth and death rate , 2009, Math. Comput. Model..

[3]  J. Hyman,et al.  Determining Important Parameters in the Spread of Malaria Through the Sensitivity Analysis of a Mathematical Model , 2008, Bulletin of mathematical biology.

[4]  Fatmawati,et al.  An optimal control strategy to reduce the spread of malaria resistance. , 2015, Mathematical biosciences.

[5]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[6]  Victor M. Becerra,et al.  Optimal control , 2008, Scholarpedia.

[7]  M. L. Chambers The Mathematical Theory of Optimal Processes , 1965 .

[8]  Oluwole Daniel Makinde,et al.  Impact of optimal control on the treatment of HIV/AIDS and screening of unaware infectives , 2013 .

[9]  Sunita Gakkhar,et al.  A dynamical model for HIV-TB co-infection , 2012, Appl. Math. Comput..

[10]  Oluwole Daniel Makinde,et al.  A co-infection model of malaria and cholera diseases with optimal control. , 2014, Mathematical biosciences.

[11]  O. Diekmann,et al.  On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations , 1990, Journal of mathematical biology.

[12]  O. Makinde,et al.  Optimal control analysis of hepatitis C virus with acute and chronic stages in the presence of treatment and infected immigrants , 2014 .

[13]  Kevin Barraclough,et al.  I and i , 2001, BMJ : British Medical Journal.

[14]  A. G. Butkovskiy,et al.  Optimal control of systems , 1966 .

[15]  W. Marsden I and J , 2012 .

[16]  Carlos Castillo-Chavez,et al.  Modeling TB and HIV co-infections. , 2009, Mathematical biosciences and engineering : MBE.

[17]  Kazeem O. Okosun,et al.  Impact of Chemo-therapy on Optimal Control of Malaria Disease with Infected Immigrants , 2011, Biosyst..

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

[19]  L. S. Pontryagin,et al.  Mathematical Theory of Optimal Processes , 1962 .

[20]  O. Makinde,et al.  Mathematical Analysis of the Effects of HIV-Malaria Co-infection on Workplace Productivity , 2015, Acta biotheoretica.

[21]  Folashade B. Agusto,et al.  Optimal chemoprophylaxis and treatment control strategies of a tuberculosis transmission model , 2009 .

[22]  O. Diekmann Mathematical Epidemiology of Infectious Diseases , 1996 .

[23]  F. B. Agusto,et al.  Optimal control of a two-strain tuberculosis-HIV/AIDS co-infection model , 2014, Biosyst..

[24]  Baojun Song,et al.  Mathematical analysis of the transmission dynamics of HIV/TB coinfection in the presence of treatment. , 2008, Mathematical biosciences and engineering : MBE.

[25]  M. A. Aziz-Alaoui,et al.  Optimal intervention strategies for tuberculosis , 2013, Commun. Nonlinear Sci. Numer. Simul..