Skip to main content

Advertisement

Log in

Dynamics of a delayed integro-differential HIV infection model with multiple target cells and nonlocal dispersal

  • Regular Article
  • Published:
The European Physical Journal Plus Aims and scope Submit manuscript

Abstract

In this paper, we formulate an age-space-structured HIV infection model that incorporating infection age, multiple target cells, and nonlocal dispersal. Applying the characteristic line method, we reduce the infection-age model to a delayed integro-differential system. The global well-posedness and boundedness of the semiflow for the system are established. The principal eigenvalue of the nonlocal dispersal problem is formulated, and it plays the same role as the basic reproduction number \(R_0\) (the spectral radius of the next generation operator), which determines the global behavior of the steady states of the system. More precisely, the infection-free steady state is globally asymptotically stable (g.a.s) when \(R_0<1\), the virus is always present and the infected steady state is g.a.s when \(R_0>1\). Numerical simulations are carried out reinforcing these analytical results. In particular, three different kernel functions are given out to study the impact of dispersal form on the HIV infection within the host. Finally, our simulation works show that (i) increasing the dispersal rate and decreasing the intracellular delay will be increasing the final viral loads; (ii) the dispersal kernel function affects the value of \(R_0\) and the final viral loads, and it is revealed that the dispersal form plays a crucial role in the process of HIV infection within the host.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. A.T. Haase, Targeting early infection to prevent HIV-1 mucosal transmission. Nature 464, 217–223 (2010)

    Article  ADS  Google Scholar 

  2. J.A. Levy, HIV and the Pathogenesis of AIDS, 3rd edn. (ASM Press, Washington, DC, 2007)

    Book  Google Scholar 

  3. X. Wang, X. Song, S. Tang, L. Rong, Analysis of HIV models with multiple target cell populations and general nonlinear rates of viral infection and cell death. Math. Comput. Simul. 124, 87–103 (2016)

    Article  MathSciNet  Google Scholar 

  4. E.C. Manda, F. Chirove, Modelling coupled within host and population dynamics of R5 and X4 HIV infection. J. Math. Biol. 76, 1123–1158 (2018)

    Article  MathSciNet  Google Scholar 

  5. X. Wang, Y. Lou, X. Song, Age-structured within-host HIV dynamics with multiple target cells. Studies in Appl. Math. 138, 43–76 (2016)

    Article  MathSciNet  Google Scholar 

  6. C. Angel, A. Eric, Global properties of an age-structured virus model with saturated antibody immune response, multi-target cells and general incidence rate. arXiv preprint arXiv:1712.05064 (2017)

  7. C. Cheng, Y. Dong, Y. Takeuchi, An age-structured virus model with two routes of infection in heterogeneous environments. Nonlinear Anal. RWA 39, 464–491 (2018)

    Article  MathSciNet  Google Scholar 

  8. X. Ren, Y. Tian, L. Liu, X. Liu, A reaction-diffusion within-host HIV model with cell-to-cell transmission. J. Math. Biol. 76, 1831–1872 (2018)

    Article  MathSciNet  Google Scholar 

  9. A.D. Agha, A.M. Elaiw, Stability of a general reaction-diffusion HIV-1 dynamics model with humoral immunity. Eur. Phys. J. Plus 134, 390–408 (2019)

    Article  Google Scholar 

  10. Y. Gao, J. Wang, Threshold dynamics of a delayed nonlocal reaction-diffusion HIV infection model with both cell-free and cell-to-cell transmissions. J. Math. Anal. Appl. 488, 124047 (2020)

    Article  MathSciNet  Google Scholar 

  11. W. Wang, X. Wang, Z. Feng, Time periodic reaction-diffusion equations for modeling 2-LTR dynamics in HIV-infected patients. Nonlinear Anal. RWA 57, 103184 (2021)

    Article  MathSciNet  Google Scholar 

  12. H. Sun, J. Wang, Dynamics of a diffusive virus model with general incidence function, cell-to-cell transmission and time delay. Comput. Math. Appl. 77, 284–301 (2019)

    Article  MathSciNet  Google Scholar 

  13. W. Wang, W. Ma, Z. Feng, Complex dynamics of a time periodic nonlocal and time-delayed model of reaction-diffusion equations for modeling CD4\(^+\) T cells decline. J. Comput. Appl. Math. 367, 112430 (2020)

    Article  MathSciNet  Google Scholar 

  14. G. Zhang, W. Li, Y. Sun, Asymptotic behavior for nonlocal dispersal equations. Nonlinear Anal. 72, 4466–4474 (2010)

    Article  MathSciNet  Google Scholar 

  15. L. Liu, P. Weng, A nonlocal diffusion model of a single species with age structure. J. Math. Anal. Appl. 432, 38–52 (2015)

    Article  MathSciNet  Google Scholar 

  16. P. Weng, L. Liu, Globally asymptotic stability of a delayed integro-differential equation with nonlocal diffusion. Can. Math. Bull. 60, 4436–448 (2017)

    Article  MathSciNet  Google Scholar 

  17. P. Magal, X.-Q. Zhao, Global attractors and steady states for uniformly persistent dynamical systems. SIAM J. Math. Anal. 37(1), 251–275 (2005)

    Article  MathSciNet  Google Scholar 

  18. F. Yang, W. Li, Dynamics of a nonlocal dispersal SIS epidemic model, J. Dyn. Differ. Equ., Revised

  19. T. Kuniya, J. Wang, Global dynamics of an SIR epidemic model with nonlocal diffusion. Nonlinear Anal. RWA 43, 262–282 (2018)

    Article  MathSciNet  Google Scholar 

  20. F. Yang, W. Li, S. Ruan, Dynamics of a nonlocal dispersal SIS epidemic model with Neumann boundary conditions. J. Differ. Equ. 267, 2011–2051 (2019)

    Article  MathSciNet  Google Scholar 

  21. G. Zhao, S. Ruan, Spatial and temporal dynamics of a nonlocal viral infection model. SIAM J. Appl. Math. 78(4), 1954–1980 (2018)

    Article  MathSciNet  Google Scholar 

  22. X. Wang, Y. Chen, J. Yang, Spatial and temporal dynamics of a viral infection model with two nonlocal effects. Complexity (2019). https://doi.org/10.1155/2019/5842942

    Article  MATH  Google Scholar 

  23. L. Liu, R. Xu, Z. Jin, Global dynamics of a spatial heterogeneous viral infection model with intracellular delay and nonlocal diffusion. Appl. Math. Model. 82(5), 150–167 (2020)

    Article  MathSciNet  Google Scholar 

  24. X. Lai, X. Zou, Dynamics of evolutionary competition between budding and lytic viral releases strategies. Math. Biol. Eng. 11(5), 1091–1113 (2014)

    MathSciNet  MATH  Google Scholar 

  25. P. Wu, H. Zhao, Dynamics of an HIV infection model with two infection routes and evolutionary competition between two viral strains. Appl. Math. Model. 84, 240–264 (2020)

    Article  MathSciNet  Google Scholar 

  26. A. Pazy, Semigroups of Linear Operators and Applications to Partial Differential Equations (Springer, New York, 1983)

    Book  Google Scholar 

  27. A. Pazy, Semigroups of Linear Operators and Applications to Partial Differential Equations (Springer, New York, NY, USA, 1983)

    Book  Google Scholar 

  28. G. Webb, Theory of Nonlinear Age-Dependent Population Dynamics (CRC Press, Boca Raton, 1985)

    MATH  Google Scholar 

  29. X.-Q. Zhao, Dynamical Systems in Population Biology (Springer-Verlag, New York, 2017)

    Book  Google Scholar 

  30. G.M. Jorge, D.R. Julio, On the principle eigenvalue of some nonlocal diffusion problems. J. Differ. Equ. 246(5), 21–38 (2009)

    MATH  Google Scholar 

  31. W. Wang, X.-Q. Zhao, Basic reproduction number for reaction-diffusion epidemic models. SIAM J. Appl. Dyn. Syt. 11, 1652–1673 (2012)

    Article  MathSciNet  Google Scholar 

  32. P. Bates, G. Zhao, Existence, uniqueness and stability of the stationary solution to a nonlocal evolution equation arising in population dispersal. J. Math. Aanl. Appl. 332(1), 428–440 (2007)

    Article  MathSciNet  Google Scholar 

  33. H.L. Smith, X.-Q. Zhao, Robust persistence for semidynamical systems. Nonlinear Anal. Theory Methods Appl. 47(9), 6169–6179 (2001)

    Article  MathSciNet  Google Scholar 

  34. D.E. Kirschner, G.F. Webb, A model for treatment strategy in the chemotherapy of AIDS. Bull. Math. Biol. 58, 367–390 (1996)

    Article  Google Scholar 

  35. M. Markowitz, M. Louie, A. Hurley et al., A novel antiviral intervention results in more accurate assessment of human immunodeficiency virus type 1 replication dynamics and T cell decay in vivo. J. Virol. 77(2–3), 5037–5038 (2003)

    Article  Google Scholar 

  36. C.Y. Kao, Y. Lou, W. Shen, Random dispersal vs non-local dispersal. Discrete Contin. Dyn. Syst. 26, 551–596 (2010)

    Article  MathSciNet  Google Scholar 

  37. E.C. Manda, F. Chirove, Modelling coupled within host and population dynamics of \(R_5\) and \(X_4\) HIV infection. J. Math. Biol. 76, 1123–1158 (2018)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

The author is very grateful to Dr. Aaron Sun for his linguistic assistance. Also, the author would like to thank Editor and the anonymous referees for their helpful comments and suggestions which led to an improvement of the original manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Peng Wu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, P. Dynamics of a delayed integro-differential HIV infection model with multiple target cells and nonlocal dispersal. Eur. Phys. J. Plus 136, 117 (2021). https://doi.org/10.1140/epjp/s13360-020-01049-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1140/epjp/s13360-020-01049-5

Keywords

Navigation