Global Stability of General Pathogen Models With CTL Impairment and Distributed Delays

Main Article Content

B. S. Alofi

Abstract

This paper presents a pathogen dynamics models with impaired of cytotoxic T lymphocytes (CTLs) function. The models includes both pathogen-to-cell and cell-to-cell modes of transmission which are represented by general nonlinear functions. The basic reproduction number R0 is determined and two equilibrium points are calculated. Nonnegativity and boundedness of the solution are proved. Lyapunov function and LaSalle’s invariance principle are used to prove the global stability of each equilibria. Simulations are used to illustrate the theoretical results. A study is conducted on the effect of impaired CTL-cell functions and time delays on pathogen dynamics. Finally, we have observed that increasing of time delay will suppress the pathogen replication.

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References

  1. M.A. Nowak, R.M.May, Virus Dynamics: Mathematical Principles of Immunology and Virology, Oxford University, Oxford, (2000).
  2. P.K. Roy, A.N. Chatterjee, D. Greenhalgh, Q.J.A. Khan, Long Term Dynamics in a Mathematical Model of Hiv-1 Infection With Delay in Different Variants of the Basic Drug Therapy Model, Nonlinear Anal.: Real World Appl. 14 (2013), 1621–1633. https://doi.org/10.1016/j.nonrwa.2012.10.021.
  3. J. Wang, J. Pang, T. Kuniya, A Note on Global Stability for Malaria Infections Model With Latencies, Math. Biosci. Eng. 11 (2014), 995–1001. https://doi.org/10.3934/mbe.2014.11.995.
  4. D. Callaway, HIV-1 Infection and Low Steady State Viral Loads, Bull. Math. Biol. 64 (2002), 29–64. https://doi.org/10.1006/bulm.2001.0266.
  5. A.M. Elaiw, S.A. Azoz, Global Properties of a Class of HIV Infection Models with Beddington-DeAngelis Functional Response, Math. Methods Appl. Sci. 36 (2012), 383–394. https://doi.org/10.1002/mma.2596.
  6. A.M. Elaiw, Global Properties of a Class of HIV Models, Nonlinear Anal.: Real World Appl. 11 (2010), 2253–2263. https://doi.org/10.1016/j.nonrwa.2009.07.001.
  7. M.Y. Li, L. Wang, Backward Bifurcation in a Mathematical Model for HIV Infection in Vivo With Anti-Retroviral Treatment, Nonlinear Anal.: Real World Appl. 17 (2014), 147–160. https://doi.org/10.1016/j.nonrwa.2013.11.002.
  8. K. Wang, A. Fan, A. Torres, Global Properties of an Improved Hepatitis B Virus Model, Nonlinear Anal.: Real World Appl. 11 (2010), 3131–3138. https://doi.org/10.1016/j.nonrwa.2009.11.008.
  9. F. Zhang, J. Li, C. Zheng, L. Wang, Dynamics of an HBV/HCV Infection Model With Intracellular Delay and Cell Proliferation, Comm. Nonlinear Sci. Numer. Simul. 42 (2017), 464–476. https://doi.org/10.1016/j.cnsns.2016.06.009.
  10. A.U. Neumann, N.P. Lam, H. Dahari, D.R. Gretch, T.E. Wiley, T.J. Layden, A.S. Perelson, Hepatitis C Viral Dynamics in Vivo and the Antiviral Efficacy of Interferon-α Therapy, Science, 282 (1998), 103–107. https://doi.org/10.1126/science.282.5386.103.
  11. A.M. Elaiw, N.A. Almuallem, Global Dynamics of Delay-distributed Hiv Infection Models With Differential Drug Efficacy in Cocirculating Target Cells, Math. Methods Appl. Sci. 39 (2015), 4–31. https://doi.org/10.1002/mma.3453.
  12. A.M. Elaiw, R.M. Abukwaik, 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. 07 (2014), 1450055. https://doi.org/10.1142/s1793524514500557.
  13. S. Zhang, X. Xu, Dynamic Analysis and Optimal Control for a Model of Hepatitis C With Treatment, Comm. Nonlinear Sci. Numer. Simul. 46 (2017), 14–25. https://doi.org/10.1016/j.cnsns.2016.10.017.
  14. L. Wang, M.Y. Li, D. Kirschner, Mathematical Analysis of the Global Dynamics of a Model for HTLV-I Infection and ATL Progression, Math. Biosci. 179 (2002), 207–217. https://doi.org/10.1016/s0025-5564(02)00103-7.
  15. A.M. Elaiw, Global Dynamics of an HIV Infection Model with Two Classes of Target Cells and Distributed Delays, Discr. Dyn. Nat. Soc. 2012 (2012), 253703. https://doi.org/10.1155/2012/253703.
  16. A. Elaiw, I. Hassanien, S. Azoz, Global Stability of Hiv Infection Models With Intracellular Delays, J. Korean Math. Soc. 49 (2012), 779–794. https://doi.org/10.4134/JKMS.2012.49.4.779.
  17. A.M. Ełaiw, A.A. Raezah, K. Hattaf, Stability of HIV-1 Infection With Saturated Virus-Target and Infected-Target Incidences and CTL Immune Response, Int. J. Biomath. 10 (2017), 1750070. https://doi.org/10.1142/s179352451750070x.
  18. S.A. Azoz, A.M. Ibrahim, Effect of Cytotoxic T Lymphocytes on HIV-1 Dynamics, J. Comput. Anal. Appl. 25 (2018), 111–125.
  19. M. Aidoo, V. Udhayakumar, Field Studies of Cytotoxic T Lymphocytes in Malaria Infections: Implications for Malaria Vaccine Development, Parasitol. Today, 16 (2000), 50–56. https://doi.org/10.1016/s0169-4758(99)01592-6.
  20. M.A. Nowak, C.R.M. Bangham, Population Dynamics of Immune Responses to Persistent Viruses, Science, 272 (1996), 74–79. https://doi.org/10.1126/science.272.5258.74.
  21. M.Y. Li, H. Shu, Global Dynamics of a Mathematical Model for HTLV-I Infection of CD4+ T Cells With Delayed CTL Response, Nonlinear Anal.: Real World Appl. 13 (2012), 1080–1092. https://doi.org/10.1016/j.nonrwa.2011.02.026.
  22. C. Lv, L. Huang, 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.
  23. E. Ibarguen-Mondragon, L. Esteva, On CTL Response Against Mycobacterium Tuberculosis, Appl. Math. Sci. 8 (2014), 2383–2389. https://doi.org/10.12988/ams.2014.43150.
  24. H. Shu, L. Wang, J. Watmough, Global Stability of a Nonlinear Viral Infection Model with Infinitely Distributed Intracellular Delays and CTL Immune Responses, SIAM J. Appl. Math. 73 (2013), 1280–1302. https://doi.org/10.1137/120896463.
  25. X. Wang, A. Elaiw, X. Song, Global Properties of a Delayed HIV Infection Model With CTL Immune Response, Appl. Math. Comput. 218 (2012), 9405–9414. https://doi.org/10.1016/j.amc.2012.03.024.
  26. X. Li, S. Fu, Global Stability of a Virus Dynamics Model With Intracellular Delay and CTL Immune Response, Math. Methods Appl. Sci. 38 (2014), 420–430. https://doi.org/10.1002/mma.3078.
  27. D. Huang, X. Zhang, Y. Guo, H. Wang, Analysis of an HIV Infection Model With Treatments and Delayed Immune Response, Appl. Math. Model. 40 (2016), 3081–3089. https://doi.org/10.1016/j.apm.2015.10.003.
  28. J. Pang, J. Cui, J. Hui, The Importance of Immune Responses in a Model of Hepatitis B Virus, Nonlinear Dyn. 67 (2011), 723–734. https://doi.org/10.1007/s11071-011-0022-6.
  29. J. Pang, J.A. Cui, Analysis of a Hepatitis B Viral Infection Model With Immune Response Delay, Int. J. Biomath. 10 (2017), 1750020. https://doi.org/10.1142/s1793524517500206.
  30. Y. Zhao, Z. Xu, Global Dynamics for a Delayed Hepatitis C Virus Infection Model, Elec. J. Differ. Equ. 2014 (2014), 1–18.
  31. R.A. Arnaout, N. Martin A., D. Wodarz, HIV-1 Dynamics Revisited: Biphasic Decay by Cytotoxic T Lymphocyte Killing?, Proc. R. Soc. Lond. B. 267 (2000), 1347–1354. https://doi.org/10.1098/rspb.2000.1149.
  32. K. Wang, W. Wang, X. Liu, Global Stability in a Viral Infection Model With Lytic and Nonlytic Immune Responses, Comp. Math. Appl. 51 (2006), 1593–1610. https://doi.org/10.1016/j.camwa.2005.07.020.
  33. R.R. Regoes, D. Wodarz, M.A. Nowak, Virus Dynamics: the Effect of Target Cell Limitation and Immune Responses on Virus Evolution, J. Theor. Biol. 191 (1998), 451–462. https://doi.org/10.1006/jtbi.1997.0617.
  34. J. Wang, M. Guo, X. Liu, Z. Zhao, Threshold Dynamics of Hiv-1 Virus Model With Cell-to-Cell Transmission, Cell-Mediated Immune Responses and Distributed Delay, Appl. Math. Comp. 291 (2016), 149–161. https://doi.org/10.1016/j.amc.2016.06.032.
  35. S. Wang, X. Song, Z. Ge, Dynamics Analysis of a Delayed Viral Infection Model With Immune Impairment, Appl. Math. Model. 35 (2011), 4877–4885. https://doi.org/10.1016/j.apm.2011.03.043.
  36. P. Krishnapriya, M. Pitchaimani, Analysis of Time Delay in Viral Infection Model With Immune Impairment, J. Appl. Math. Comput. 55 (2016), 421–453. https://doi.org/10.1007/s12190-016-1044-5.
  37. Z. Hu, J. Zhang, H. Wang, W. Ma, F. Liao, Dynamics Analysis of a Delayed Viral Infection Model With Logistic Growth and Immune Impairment, Appl. Math. Model. 38 (2014), 524–534. https://doi.org/10.1016/j.apm.2013.06.041.
  38. J. Jia, X. Shi, Analysis of a viral infection model with immune impairment and cure rate, J. Nonlinear Sci. Appl. 9 (2016), 3287–3298.
  39. E. Avila-Vales, N. Chan-Chí, G. García-Almeida, Analysis of a Viral Infection Model With Immune Impairment, Intracellular Delay and General Non-Linear Incidence Rate, Chaos Solitons Fractals. 69 (2014), 1–9. https://doi.org/10.1016/j.chaos.2014.08.009.
  40. R.V. Culshaw, S. Ruan, G. Webb, A Mathematical Model of Cell-to-Cell Spread of HIV-1 That Includes a Time Delay, J. Math. Biol. 46 (2003), 425–444. https://doi.org/10.1007/s00285-002-0191-5.
  41. H. Pourbashash, S.S. Pilyugin, P. De Leenheer, C. McCluskey, Global Analysis of Within Host Virus Models With Cell-to-Cell Viral Transmission, Discr. Contin. Dyn. Syst. - B. 19 (2014), 3341–3357. https://doi.org/10.3934/dcdsb.2014.19.3341.
  42. J. Wang, J. Lang, X. Zou, Analysis of an Age Structured Hiv Infection Model With Virus-to-Cell Infection and Cell-to-Cell Transmission, Nonlinear Anal.: Real World Appl. 34 (2017), 75–96. https://doi.org/10.1016/j.nonrwa.2016.08.001.
  43. S.S. Chen, C.Y. Cheng, Y. Takeuchi, Stability Analysis in Delayed Within-Host Viral Dynamics With Both Viral and Cellular Infections, J. Math. Anal. Appl. 442 (2016), 642–672. https://doi.org/10.1016/j.jmaa.2016.05.003.
  44. X. Lai, X. Zou, Modeling Cell-to-Cell Spread of HIV-1 With Logistic Target Cell Growth, J. Math. Anal. Appl. 426 (2015), 563–584. https://doi.org/10.1016/j.jmaa.2014.10.086.
  45. X. Lai, X. Zou, Modeling HIV-1 Virus Dynamics with Both Virus-to-Cell Infection and Cell-to-Cell Transmission, SIAM J. Appl. Math. 74 (2014), 898–917. https://doi.org/10.1137/130930145.
  46. Y. Yang, L. Zou, S. Ruan, Global Dynamics of a Delayed Within-Host Viral Infection Model With Both Virus-to-Cell and Cell-to-Cell Transmissions, Math. Biosci. 270 (2015), 183–191. https://doi.org/10.1016/j.mbs.2015.05.001.
  47. B. Buonomo, C. Vargas-De-León, Global Stability for an Hiv-1 Infection Model Including an Eclipse Stage of Infected Cells, J. Math. Anal. Appl. 385 (2012), 709–720. https://doi.org/10.1016/j.jmaa.2011.07.006.
  48. A.M. Elaiw, A.A. Raezah, B.S. Alofi, Stability of Pathogen Dynamics Models With Viral and Cellular Infections and Immune Impairment, J. Nonlinear Sci. Appl. 11 (2018), 456–468. https://doi.org/10.22436/jnsa.011.04.02.
  49. A.M. Elaiw, A.A. Raezah, B.S. Alofi, Dynamics of Delayed Pathogen Infection Models With Pathogenic and Cellular Infections and Immune Impairment, AIP Adv. 8 (2018), 025323. https://doi.org/10.1063/1.5023752.
  50. B. S. Alofi, S. A. Azoz, Stability of General Pathogen Dynamic Models With Two Types of Infectious Transmission With Immune Impairment, AIMS Math. 6 (2021), 114–140. https://doi.org/10.3934/math.2021009.
  51. A.M. Elaiw, B.S. Alofi, Stability Analysis of Immune Impairment Pathogen Dynamics Model With Two Routes of Infection and Holling Type-II Function, Appl. Math. Sci. 12 (2018), 1419–1432. https://doi.org/10.12988/ams.2018.810151.