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STABILITY OF DELAY-DISTRIBUTED HIV INFECTION MODELS WITH MULTIPLE VIRAL PRODUCER CELLS

  • ELAIW, A.M. (DEPARTMENT OF MATHEMATICS, FACULTY OF SCIENCE, KING ABDULAZIZ UNIVERSITY) ;
  • ELNAHARY, E.KH. (DEPARTMENT OF MATHEMATICS, FACULTY OF SCIENCE SOHAG UNIVERSITY) ;
  • SHEHATA, A.M. (DEPARTMENT OF MATHEMATICS, FACULTY OF SCIENCE AL-AZHAR UNIVERSITY) ;
  • ABUL-EZ, M. (DEPARTMENT OF MATHEMATICS, FACULTY OF SCIENCE SOHAG UNIVERSITY)
  • Received : 2017.12.16
  • Accepted : 2018.02.26
  • Published : 2018.03.25

Abstract

We investigate a class of HIV infection models with two kinds of target cells: $CD4^+$ T cells and macrophages. We incorporate three distributed time delays into the models. Moreover, we consider the effect of humoral immunity on the dynamical behavior of the HIV. The viruses are produced from four types of infected cells: short-lived infected $CD4^+$T cells, long-lived chronically infected $CD4^+$T cells, short-lived infected macrophages and long-lived chronically infected macrophages. The drug efficacy is assumed to be different for the two types of target cells. The HIV-target incidence rate is given by bilinear and saturation functional response while, for the third model, both HIV-target incidence rate and neutralization rate of viruses are given by nonlinear general functions. We show that the solutions of the proposed models are nonnegative and ultimately bounded. We derive two threshold parameters which fully determine the positivity and stability of the three steady states of the models. Using Lyapunov functionals, we established the global stability of the steady states of the models. The theoretical results are confirmed by numerical simulations.

Keywords

References

  1. M. A. Nowak and R. M. May, Virus dynamics: Mathematical Principles of Immunology and Virology, Oxford Uni., Springer Verlag, Oxford, 2000.
  2. A.S. Perelson and P.W. Nelson, Mathematical analysis of HIV-1 dynamics in vivo, SIAM Rev., 41 (1999), 3-44. https://doi.org/10.1137/S0036144598335107
  3. D. S. Callaway and A. S. Perelson, HIV-1 infection and low steady state viral loads, Bull. Math. Biol., 64 (2002), 29-64. https://doi.org/10.1006/bulm.2001.0266
  4. V. Herz, S. Bonhoeffer, R. Anderson, R. M. May and M. A. Nowak, Viral dynamics in vivo: Limitations on estimations on intracellular delay and virus delay, Proc. Natl. Acad. Sci. USA, 93 (1996), 7247-7251. https://doi.org/10.1073/pnas.93.14.7247
  5. J. Wang, J. Lang and F. Li, Constructing Lyapunov functionals for a delayed viral infection model with multitarget cells, J. NonlinearSci. Appl., 9 (2) (2016), 524-536. https://doi.org/10.22436/jnsa.009.02.18
  6. N. M. Dixit and A.S. Perelson, Complex patterns of viral load decay under antiretroviral therapy: influence of pharmacokinetics and intracellular delay, J. Theoret. Biol., 226 (2004), 95-109. https://doi.org/10.1016/j.jtbi.2003.09.002
  7. C. Connell McCluskey and Y. Yang, Global stability of a diffusive virus dynamics model with general incidence function and time delay, Nonlinear Anal. Real World Appl., 25 (2015), 64-78. https://doi.org/10.1016/j.nonrwa.2015.03.002
  8. Z. Yuan and X. Zou, Global threshold dynamics in an HIV virus model with nonlinear infection rate and distributed invasion and production delays, Math. Biosc. Eng., 10 (2) (2013), 483-498. https://doi.org/10.3934/mbe.2013.10.483
  9. S. Liu and L.Wang, Global stability of an HIV-1 model with distributed intracellular delays and a combination therapy, Math. Biosc. Eng., 7(3) (2010), 675-685. https://doi.org/10.3934/mbe.2010.7.675
  10. A. M. Elaiw and N. H. AlShameani, Global analysis for a delay-distributed viral infection model with antibodies and general nonlinear incidence rate, J. Korean Soc. Ind. Appl. Math., 18(4) (2014), 317-335.
  11. A. M. Elaiw, Global threshold dynamics in humoral immunity viral infection models including an eclipse stage of infected cells, J. Korean Soc. Ind. Appl. Math., 19:2 (2015), 137-170.
  12. A. M. Elaiw, I. A. Hassanien and S. A. Azoz, Global stability of HIV infection models with intracellular delays, J. Korean Math. Soc., 49(4) (2012), 779-794. https://doi.org/10.4134/JKMS.2012.49.4.779
  13. A.M. Elaiw and S.A. Azoz, Global properties of a class of HIV infection models with Beddington-DeAngelis functional response, Math. Methods Appl. Sci., 36 (2013), 383-394. https://doi.org/10.1002/mma.2596
  14. A.M. Elaiw, Global properties of a class of HIV models, Nonlinear Anal. RealWorld Appl., 11 (2010), 2253-2263. https://doi.org/10.1016/j.nonrwa.2009.07.001
  15. A. M. Elaiw and N. A. Almuallem, Global properties of delayed-HIV dynamics models with differential drug efficacy in co-circulating target cells, Appl. Math. Comput., 265 (2015), 1067-1089.
  16. A. M. Elaiw and X. Xia, HIV dynamics: Analysis and robust multirate MPC-based treatment schedules, J. Math. Anal. Appl., 356 (2009), 285-301.
  17. B. Buonomo and C. Vargas-De-Le, Global stability for an HIV-1 infection model in cluding an eclipse stage of infected cells, J. Math. Anal. Appl., 385 (2012), 709-720. https://doi.org/10.1016/j.jmaa.2011.07.006
  18. A. M. Elaiw, R. M. Abukwaik and E. O. Alzahrani, Global properties of a cell mediated immunity in HIV infection model with two classes of target cells and distributed delays, Int. J. Biomath., 77(5) (2014), 25 Pages.
  19. B. Li, Y. Chen, X. Lu and S. Liu, A delayed HIV-1 model with virus waning term, Math. Biosci. Eng., 13 (2016), 135-157.
  20. C. Monica and M. Pitchaimani, Analysis of stability and Hopf bifurcation for HIV-1 dynamics with PI and three intracellular delays, Nonlinear Anal. Real World Appl., 27 (2016), 55-69. https://doi.org/10.1016/j.nonrwa.2015.07.014
  21. C. Lv, L. Huang and Z. Yuan, Global stability for an HIV-1 infection model with Beddington-DeAngelis incidence rate and CTL immune response, Commun. Nonlinear Sci. Numer. Simul., 19 (2014), 121-127. https://doi.org/10.1016/j.cnsns.2013.06.025
  22. R. Xu, Global stability of an HIV-1 infection model with saturation infection and in tracellular delay, J.Math. Anal. Appl., 375 (2011), 75-81. https://doi.org/10.1016/j.jmaa.2010.08.055
  23. J. A. Deans and S. Cohen, Immunology of malaria, Ann. Rev. Microbiol, 37 (1983), 25-49. https://doi.org/10.1146/annurev.mi.37.100183.000325
  24. T. Wang, Z. Hu and F. Liao, Stability and Hopf bifurcation for a virus infection model with delayed humoral immunity response, J. Math. Anal. Appl., 411 (2014), 63-74. https://doi.org/10.1016/j.jmaa.2013.09.035
  25. A. M. Elaiw and A. Alhejelan, Global dynamics of virus infection model with humoral immune response and distributed delays, J. Comput. Anal. Appl.,17 (2014), 515-523.
  26. A.M. Elaiw and N. H. AlShamrani, Global stability of a delayed humoral immunity virus dynamics model with nonlinear incidence and infected cells removal rates, Int. J. of Dynam. Control, (2015), DOI: 10.1007/s40435-015-0200-3.
  27. A.M. Elaiw and N. H. AlShamrani, Dynamics of viral infection models with antibodies and general nonlinear incidence and neutralize rates, Int. J. of Dynam. Control, (2015), DOI: 10.1007/s40435-015-0181-2.
  28. A. M. Elaiw and N. H. AlShameani, Global stability of humoral immunity virus dynamics models with nonlinear infection rate and removal, Nonlinear Anal. Real World Appl., 26 (2015), 161-190. https://doi.org/10.1016/j.nonrwa.2015.05.007
  29. T. Wang, Z. Hu, F. Liao and W. Ma, Global stability analysis for delayed virus infection model with general incidence rate and humoral immunity, Math. Comput. Simulation, 89 (2013), 13-22. https://doi.org/10.1016/j.matcom.2013.03.004
  30. A. M. Shehata, A. M. Elaiw, E. Kh. Elnahary and M. Abul-Ez, Stability analysis of humoral immunity HIV infection models with RTI and discrete delays, Int. J. of Dynam. Control, (2016), DOI 10.1007/s40435-016-0235-0.
  31. R. Larson and B. H. Edwards, Calculus of a single variable, Cengage Learning, Inc., USA, 2010.
  32. J. K. Hale and S. M. V. Lunel, Introduction to functional differential equations, Springer Science & Business Media 99, 2013.
  33. X. Yang, L. Chen, and J. Chen, Permanence and positive periodic solution for the single-species nonautonomous delay diffusive models, Computers & Mathematics with Applications, 32 (4) (1996), 109-116. https://doi.org/10.1016/0898-1221(96)00129-0