OPTIMAL CONTROL OF AN HIV INFECTION MODEL WITH
THE CTL RESPONSE AND TWO SATURATED RATES
Bouchra Lahmidani1, Othmane Baiz2,
Youssef Tabit3, Driss El Moutawakil4 1 Univ. Sultan Moulay Slimane, Equipe de recherche MATIC
FPK, MOROCCO 2 Univ. Ibn Zohr, FP of Ouarzazate, MOROCCO 3 Univ. Hassan II, ENCG Casablanca, MOROCCO 4 Univ. Sultan Moulay Slimane, Equipe de recherche MATIC
FPK, MOROCCO
In this paper, we study a mathematical model that describes the Human Immunodeficiency Virus (HIV) pathogenesis with Cytotoxic T Lymphocytes (CTL) response. This model includes the cure of infected cells, two saturated rates describing viral infection, CTL proliferation and two treatments. These latter represent the efficiency of drug treatment in inhibiting viral production and preventing new infections. First, we derive the positivity and boundedness of solutions for nonnegative initial data, which is consistent with the biological studies. Furthermore, we prove the existence of the optimal control pair, and its characterization is obtained by using the Pontryagin's maximum principle. Finally, the optimality system is derived and illustrated by a numerical example. The obtained results show that the optimal treatment strategies reduce the viral load and then increase the uninfected CD4^{+}T cells as well as cytotoxic T-lymphocyte immune response, this improves the patient life quality.
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References
[1] R.A. Weiss, How does HIV cause AIDS?, Science, 260 (1993), 1273-1279.
[2] W. Blanttner, R.C. Gallo, H.M. Temin, HIV causes aids, Science, 241
(1988), 515-516.
[3] C.J. Silva, D.F.M. Torres, A TB/AIDS coinfection model and optimal
control treatment, Discrete and continuous dynamical systems, 35, No 9
(2015), 4639-4663.
[4] Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines
for the use of antiretroviral agents in HIV-1-infected adults and adolescents,
Department of Health and Human Services (2011), 1-166.
[5] M.A. Nowak, R.M. May, Mathematical biology of HIV infection: antigenic
variation and diversity threshold, Math. Biosci, 106, No 1 (1991), 1-21.
[6] M.A. Nowak, C.R.M. Bangham, Population dynamics of immune responses
to persitent viruses, Science, 272 (1996), 7479.
[7] A. Perelson, A. Neumann, M. Markowitz, J. Leonard, D. Ho, HIV-1 dynamics in vivo: Virion clearance rate, infected cell life-span, and viral
generation time, Science, 271 (1996), 582-1586.
[8] W. Liu, Nonlinear oscillation in models of immune response to persistent
viruses, Theor. Popul. Biol., 52 (1997), 224230.
[9] A.S. Perelson, P. W. Nelson, Mathematical analysis of HIV-1 dynamics in
vivo, SIAM Rev., 41, No 1 (1999), 3-44.
[10] M.A. Nowak, R. M. May, Viral Dynamics, Oxford University Press, Oxford
(2000).
[11] S.M. Ciupe, B. Bivort, D. Bortz, P. Nelson, Estimates of kinetic parameters
from HIV patient data during primary infection through the eyes of three
different models, Math. Biosci., 200 (2006), 1-27.
[12] K. Hattaf and N. Yousfi, Dynamics of HIV infection model with therapy
and cure rate, Inter. J. of Tomography and Statistics, 16 (2011), 74-80.
[13] B. El Boukari, K. Hattaf, N. Yousfi, Modeling the therapy of HIV infection
with CTL response and cure rate, Int. J. Ecol. Econ. Stat., 28 (2013), 117.
[14] Y. Tabit, K. Hattaf, N. Yousfi, Dynamics of an HIV pathogenesis model
with CTL immune response and two saturated rates, World J. of Modelling
and Simulation, 10, No 3 (2014), 215223.
[15] Q. Sun, L. Min, Dynamics Analysis and Simulation of a Modified HIV Infection Model with a Saturated Infection Rate, Computational and Mathematical Methods in Medicine, 2014 (2014), 145-162.
[16] Y. Tabit, A. Meskaf, K. Allali, Mathematical analysis of HIV model with
two saturated rates, CTL and antibody responses, World J. of Modelling
and Simulation, 12, No 2 (2016), 137-146.
[17] K. Allali, Y. Tabit and S. Harroudi, On HIV model with adaptive immune response, two saturated rates and therapy, Mathematical Modelling
of Natural Phenomena, 12, No 5 (2017), 1-14.
[18] X. Zhou, X. Song, X. Shi, A differential equation model of HIV infection
of CD4+ T-cells with cure rate, J. Math. Anal. Appl., 342, No 2 (2008),
1342-1355.
[19] X. Liu, H. Wang, W. Ma, Global stability of an HIV pathogenesis model
with cure rate, Nonlinear Anal. RWA, 12, No 6 (2011), 2947-2961.
[20] X. Song, A. Neumann, Global stability and periodic solution of the viral
dynamics, J. Math. Anal. Appl., 329, No 1 (2007), 281-297.
[21] S. Iwami, T. Miura, S. Nakaoka, Y. Takeuchi, Immune impairment in
HIV infection: Existence of risky and immunodeficiency thresholds, J. of
Theoretical Biology, 260, No 4 (2009), 490-501.
[22] K. Hattaf, N. Yousfi, Two optimal treatment of HIV infection medel, World
J. of Modelling and Simualtion, 8, No 1 (2012), 27-35.
[23] D. Rocha, C.J. Silva, D.F.M. Torres, Stability and optimal control of a
delayed HIV model, Mathematical Methods in Appl. Sci. (2016).
[24] A. Meskaf, K. Allali, Y. Tabit, Optimal control of a delayed hepatitis B
viral infection model with cytotoxic T-lymphocyte and antibody responses,
Intern. J. of Dynamics and Control, 5 (2017), 893-902.
[25] S. Harroudi, D. Bentaleb, Y. Tabit, S. Amine, K. Allali, Optimal control of
an HIV infection model with the adaptive immune response and two saturated rates, International Journal of Mathematics and Computer Science,
14 (2019), 787807.
[26] H.R. Thieme, Mathematics in Population Biology, Princeton University
Press, Princeton (2003).
[28] D. L. Lukes, Differential Equations: Classical to Controlled, Vol. 162 of
Mathematics in Science and Engineering, Academic Press (1982).
[29] L.S. Pontryagin, V.G. Boltyanskii, R.V. Gamkrelidze, E.F. Mishchenko,
The Mathematical Theory of Optimal Processes, Wiley (1962).
[30] S. Bonhoeffer, M. Rembiszewski, G.M. Ortiz and D.F. Nixon, Risks and
benefits of structured antiretroviral drug therapy interruptions in HIV-1
infection, AIDS, 14 (2000), 2313-2322.
[31] K. Hattaf and N. Yousfi, A delay differential equation model of HIV with
therapy and cure rate, Intern. J. of Nonlin. Sci., 12 (2011), 503512.
[32] H. Zhu and X. Zou, Dynamics of a HIV-1 infection model with cellmediated immune response and intracellular delay, Discrete and Continuous Dynam. Systems Ser. B, 12, No 2 (2009), 511-524.