Skip to main content

Advertisement

Log in

Global dynamics of delayed CHIKV infection model with multitarget cells

  • Original Research
  • Published:
Journal of Applied Mathematics and Computing Aims and scope Submit manuscript

Abstract

We propose a latent chikungunya viral infection model with multitarget cells and saturated incidence rate. The model is an \((3n+2)\)-dimensional system of nonlinear delay differential equations (DDEs) that describes the population dynamics of CHIKV, n categories of uninfected target cells, n categories of infected cells and antibodies. The model is incorporated by intracellular discrete or distributed time delays. The qualitative behavior of the model is studied. We investigate the global stability of the equilibria of the models by using direct Lyapunov method. The effect of the time delay on the stability of the equilibria has also been illustrated by numerical simulations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Nowak, M.A., May, R.M.: Virus Dynamics: Mathematical Principles of Immunology and Virology. Oxford University, Oxford (2000)

    MATH  Google Scholar 

  2. Shu, H., Wang, L., Watmough, J.: Global stability of a nonlinear viral infection model with infinitely distributed intracellular delays and CTL imune responses. SIAM J. Appl. Math. 73(3), 1280–1302 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  3. Huang, G., Takeuchi, Y., Ma, W.: Lyapunov functionals for delay differential equations model of viral infections. SIAM J. Appl. Math. 70(7), 2693–2708 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  4. Elaiw, A.M., AlShamrani, N.H., Alofi, A.S.: Stability of CTL immunity pathogen dynamics model with capsids and distributed delay. AIP Adv. (2017). https://doi.org/10.1063/1.5006961

    Google Scholar 

  5. Elaiw, A.M., AlShamrani, N.H., Hattaf, K.: Dynamical behaviors of a general humoral immunity viral infection model with distributed invasion and production. Int. J. Biomath. (2017). https://doi.org/10.1142/S1793524517500358

    MathSciNet  MATH  Google Scholar 

  6. Elaiw, A.M., Raezah, A.A., Hattaf, K.: Stability of HIV-1 infection with saturated virus-target and infected-target incidences and CTL immune response. Int. J. Biomath. (2017). https://doi.org/10.1142/S179352451750070X

    MathSciNet  MATH  Google Scholar 

  7. Connell McCluskey, C., Yang, Y.: Global stability of a diffusive virus dynamics model with general incidence function and time delay. Nonlinear Anal. Real World Appl. 25, 64–78 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  8. Liu, S., Wang, L.: Global stability of an HIV-1 model with distributed intracellular delays and a combination therapy. Math. Biosci. Eng. 7(3), 675–685 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  9. Li, X., Fu, S.: Global stability of a virus dynamics model with intracellular delay and CTL immune response. Math. Methods Appl. Sci. 38, 420–430 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  10. Hattaf, K., Yousfi, N., Tridane, A.: Mathematical analysis of a virus dynamics model with general incidence rate and cure rate. Nonlinear Anal. Real World Appl. 13(4), 1866–1872 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  11. Elaiw, A.M., Hassanien, I.A., Azoz, S.A.: Global stability of HIV infection models with intracellular delays. J. Korean Math. Soc. 49(4), 779–794 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  12. Elaiw, A.M., Azoz, S.A.: Global properties of a class of HIV infection models with Beddington–DeAngelis functional response. Math. Methods Appl. Sci. 36, 383–394 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  13. Elaiw, A.M., Elnahary, E.K., Raezah, A.A.: Effect of cellular reservoirs and delays on the global dynamics of HIV. Adv. Differ. Equ. 18, 85 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  14. Elaiw, A.M., Raezah, A.A., Alofi, B.S.: Dynamics of delayed pathogen infection models with pathogenic and cellular infections and immune impairment. AIP Adv. (2018). https://doi.org/10.1063/1.5023752

    Google Scholar 

  15. Elaiw, A.M.: Global properties of a class of HIV models. Nonlinear Anal. Real World Appl. 11, 2253–2263 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  16. Elaiw, A.M.: Global properties of a class of virus infection models with multitarget cells. Nonlinear Dyn. 69(1–2), 423–435 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  17. Elaiw, A.M., Almuallem, N.A.: Global dynamics of delay-distributed HIV infection models with differential drug efficacy in cocirculating target cells. Math. Methods Appl. Sci. 39, 4–31 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  18. Elaiw, A.M., Raezah, A., Alofi, A.S.: Effect of humoral immunity on HIV-1 dynamics with virus-to-target and infected-to-target infections. AIP Adv. (2016). https://doi.org/10.1063/1.4960987

    Google Scholar 

  19. Elaiw, A.M., Raezah, A., Alofi, A.: Stability of a general delayed virus dynamics model with humoral immunity and cellular infection. AIP Adv. (2017). https://doi.org/10.1063/1.4989569

    Google Scholar 

  20. Elaiw, A.M., Raezah, A.A.: Stability of general virus dynamics models with both cellular and viral infections and delays. Math. Methods Appl. Sci. 40(16), 5863–5880 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  21. Li, B., Chen, Y., Lu, X., Liu, S.: A delayed HIV-1 model with virus waning term. Math. Biosci. Eng. 13, 135–157 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  22. Huang, D., Zhang, X., Guo, Y., Wang, H.: Analysis of an HIV infection model with treatments and delayed immune response. Appl. Math. Model. 40(4), 3081–3089 (2016)

    Article  MathSciNet  Google Scholar 

  23. Wang, K., Fan, A., Torres, A.: Global properties of an improved hepatitis B virus model. Nonlinear Anal. Real World Appl. 11, 3131–3138 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  24. Elaiw, A.M., AlShamrani, N.H.: Global properties of nonlinear humoral immunity viral infection models. Int. J. Biomath. (2015). https://doi.org/10.1142/S1793524515500588

    MathSciNet  MATH  Google Scholar 

  25. Monica, C., Pitchaimani, M.: Analysis of stability and Hopf bifurcation for HIV-1 dynamics with PI and three intracellular delays. Nonlinear Anal. Real World Appl. 27, 55–69 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  26. Neumann, A.U., Lam, N.P., Dahari, H., Gretch, D.R., Wiley, T.E., Layden, T.J., Perelson, A.S.: Hepatitis C viral dynamics in vivo and the antiviral efficacy of interferon-alpha therapy. Science 282, 103–107 (1998)

    Article  Google Scholar 

  27. Wang, L., Li, M.Y., Kirschner, D.: Mathematical analysis of the global dynamics of a model for HTLV-I infection and ATL progression. Math. Biosci. 179, 207–217 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  28. Shi, X., Zhou, X., Son, X.: Dynamical behavior of a delay virus dynamics model with CTL immune response. Nonlinear Anal. Real World Appl. 11, 1795–1809 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  29. Wang, J., Lang, J., Zou, X.: Analysis of an age structured HIV infection model with virus-to-cell infection and cell-to-cell transmission. Nonlinear Anal. Real World Appl. 34, 75–96 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  30. Elaiw, A.M., AlShamrani, N.H.: Global stability of humoral immunity virus dynamics models with nonlinear infection rate and removal. Nonlinear Anal. Real World Appl. 26, 161–190 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  31. Elaiw, A.M., AlShamrani, N.H.: Stability of a general delay-distributed virus dynamics model with multi-staged infected progression and immune response. Math. Methods Appl. Sci. 40(3), 699–719 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  32. Wang, Y., Liu, X.: Stability and Hopf bifurcation of a within-host chikungunya virus infection model with two delays. Math. Comput. Simul. 138, 31–48 (2017)

    Article  MathSciNet  Google Scholar 

  33. Dumont, Y., Chiroleu, F.: Vector control for the chikungunya disease. Math. Biosci. Eng. 7, 313–345 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  34. Dumont, Y., Tchuenche, J.M.: Mathematical studies on the sterile insect technique for the chikungunya disease and aedes albopictus. J. Math. Biol. 65(5), 809–854 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  35. Dumont, Y., Chiroleu, F., Domerg, C.: On a temporal model for the chikungunya disease: modeling, theory and numerics. Math. Biosci. 213, 80–91 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  36. Moulay, D., Aziz-Alaoui, M., Cadivel, M.: The chikungunya disease: modeling, vector and transmission global dynamics. Math. Biosci. 229, 50–63 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  37. Moulay, D., Aziz-Alaoui, M., Kwon, H.D.: Optimal control of chikungunya disease: larvae reduction, treatment and prevention. Math. Biosci. Eng. 9, 369–392 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  38. Manore, C.A., Hickmann, K.S., Xu, S., Wearing, H.J., Hyman, J.M.: Comparing dengue and chikungunya emergence and endemic transmission in A. aegypti and A. albopictus. J. Theor. Biol. 356, 174–191 (2014)

    Article  MathSciNet  Google Scholar 

  39. Yakob, L., Clements, A.C.: A mathematical model of chikungunya dynamics and control: the major epidemic on Reunion Island. PLoS ONE 8, e57448 (2013)

    Article  Google Scholar 

  40. Liu, X., Stechlinski, P.: Application of control strategies to a seasonal model of chikungunya disease. Appl. Math. Model. 39, 3194–3220 (2015)

    Article  MathSciNet  Google Scholar 

  41. Elaiw, A.M., Alade, T.O., Alsulami, S.M.: Stability of a within-host Chikungunya virus dynamics model with latency. J. Comput. Anal. Appl. 26(5), 777–790 (2019)

    Google Scholar 

  42. Elaiw, A.M., Alade, T.O., Alsulami, S.M.: Analysis of within-host CHIKV dynamics models with general incidence rate. Int. J. Biomath. (2018). https://doi.org/10.1142/S1793524518500626

    MathSciNet  MATH  Google Scholar 

  43. Elaiw, A.M., Alade, T.O., Alsulami, S.M.: Analysis of latent CHIKV dynamics models with general incidence rate and time delays. J. Biol. Dyn. 12(1), 700–730 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  44. Couderc, T., Chretien, F., Schilte, C., Disson, O., Brigitte, M., Guivel-Benhassine, F., et al.: A mouse model for Chikungunya: young age and inefficient type-I interferon signaling are risk factors for severe disease. PLoS Pathog. 4(2), e29 (2008)

    Article  Google Scholar 

  45. Lum, F.M., Ng, L.F.P.: Cellular and molecular mechanisms of chikungunya pathogenesis. Antivir. Res. 120, 165–174 (2015)

    Article  Google Scholar 

  46. Ozden, S., Huerre, M., Riviere, J.P., Coffey, L.L., Afonso, P.V., Mouly, V.: Human muscle satellite cells as targets of chikungunya virus infection. PLoS ONE 2(6), e527 (2007)

    Article  Google Scholar 

  47. Her, Z.: Active infection of human blood monocytes by chikungunya virus triggers an innate immune response. J. Immunol. 184, 5903–5913 (2010)

    Article  Google Scholar 

  48. Hale, J.K., Verduyn Lunel, S.M.: Introduction to Functional Differential Equations. Springer, New York (1993)

    Book  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ahmed M. Elaiw.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Elaiw, A.M., Alade, T.O. & Alsulami, S.M. Global dynamics of delayed CHIKV infection model with multitarget cells. J. Appl. Math. Comput. 60, 303–325 (2019). https://doi.org/10.1007/s12190-018-1215-7

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12190-018-1215-7

Keywords

Mathematics Subject Classification

Navigation