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Discrete Dynamics in Nature and Society
Volume 2011, Article ID 673843, 13 pages
http://dx.doi.org/10.1155/2011/673843
Research Article

Global Dynamics of a Delayed HIV-1 Infection Model with CTL Immune Response

Institute of Applied Mathematics, Shijiazhuang Mechanical Engineering College, Shijiazhuang 050003, China

Received 16 April 2011; Accepted 14 June 2011

Academic Editor: Jinde Cao

Copyright © 2011 Yunfei Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A delayed HIV-1 infection model with CTL immune response is investigated. By using suitable Lyapunov functionals, it is proved that the infection-free equilibrium is globally asymptotically stable if the basic reproduction ratio for viral infection is less than or equal to unity; if the basic reproduction ratio for CTL immune response is less than or equal to unity and the basic reproduction ratio for viral infection is greater than unity, the CTL-inactivated infection equilibrium is globally asymptotically stable; if the basic reproduction ratio for CTL immune response is greater than unity, the CTL-activated infection equilibrium is globally asymptotically stable.

1. Introduction

Recently, many mathematical models have been developed to describe the infection with HIV-1 (human immunodeficiency virus 1). By investigating these models, researchers have gained much important knowledge about the HIV-1 pathogenesis and have enhanced progress in the understanding of HIV-1 infection (see, e.g., [14]). It is pointed out by the work of [5] that immune response is universal and necessary to eliminate or control the disease during viral infections. In particular, as a part of innate response, cytotoxic T lymphocytes (CTLs) play a particularly important role in antiviral defense by attacking infected cells. Thus, many authors have studied the mathematical modelling of viral dynamics with CTL immune response (see, e.g., [59]). In [7], Nowak and Bangham considered an HIV-1 infection model with CTL immune response which is described by the following differential equations: where , , , and represent the densities of uninfected target cells, infected cells, virions, and CTL cells at time , respectively. Uninfected cells are produced at rate , die at rate , and become infected cells at rate . Infected cells are produced from uninfected cells at rate and die at rate . The parameter accounts for the strength of the lytic component. Free virions are produced from uninfected cells at rate and are removed at rate . The parameter is the death rate for CTLs, and describes the rate of CTL immune response activated by the infected cells.

Moreover, infection rate plays an important role in the modelling of epidemic dynamics. Holling type-II functional response seems more reasonable than the bilinear incidence rate (see, [10]). In [11], by stability analysis, Song and Avidan obtained that the system with the bilinear incidence rate was an extreme case of the model with Holling type-II functional response term.

In [3, 4, 7], the researchers used ordinary differential equations to describe different aspects of the dynamics of the viral infections. However, in the real virus dynamics, infection processes are not instantaneous. Time delays are usually introduced for the purpose of accurate representations of this phenomena (see, e.g., [6, 1217]). As pointed out in [12], there is a time delay between initial viral entry into a cell and subsequent viral production, and the effect of saturation infection of an HIV-1 model was studied. By using the Lyapunov-LaSalle type theorem, sufficient conditions were derived for the global stability of the infection-free equilibrium and the chronic-infection equilibrium. In addition, there is also a period between virions that have created within a cell, and the new virions are released from the cell (see, e.g., [6, 13, 17]). In [13], Zhu and Zou studied an HIV-1 model with discrete delays and found that large delays can help eliminate the virus. To the best of our knowledge, there are few works on the dynamics of HIV-1 system with CTL immune response, Holling type-II functional response, and two kinds of discrete delays. Therefore, we are concerned with the effect of the above factors on system (1.1).

Motivated by the works of Nowak and Bangham [7], Song and Avidan [11], in the present paper, we consider the following delay differential equations: where the parameters have the same meanings as in system (1.1), represents the time between viral entry into a target cell and the production of new virus particles and stands for a virus production period for new virions to be produced within and released from the infected cells.

The initial conditions for system (1.2) take the form where (, the Banach space of continuous functions mapping the interval into , where , .

It is well known by the fundamental theory of functional differential equations [18] that system (1.2) has a unique solution satisfying the initial conditions (1.3). It is easy to show that all solutions of system (1.2) with initial conditions (1.3) are defined on and remain positive for all .

This paper is organized as follows. In Section 2, by analyzing the basic reproduction ratio for viral infection and CTL immune response, the existence of three equilibria is established. Moreover, the ultimate boundedness of the solutions for system (1.2) is presented. In Section 3, by means of suitable Lyapunov functionals and LaSalle's invariant principle, we discuss the global stability of the infection-free equilibrium, the CTL-inactivated infection equilibrium, and the CTL-activated infection equilibrium, respectively. In Section 4, we carry out some numerical examples to illustrate the theoretical results. Finally, a discussion is given in Section 5 to end this work.

2. Preliminary Results

In this section, we discuss the existence of three equilibria and prove that all the solutions are positive and bounded.

Clearly, system (1.2) always has an infection-free equilibrium .

Denote Here, and are called the basic reproduction ratios for viral infection and CTL immune response of system (1.2), respectively. It is easy to see that always holds. If , system (1.2) has a CTL-inactivated infection equilibrium besides the equilibrium , where

If , system (1.2) has a CTL-activated infection equilibrium besides the equilibrium and , where

Theorem 2.1. Supposing that is a solution of system (1.2) with initial conditions (1.3), then there exists , such that all the solutions satisfy , , , for sufficiently large time .

Proof. Let Since all solutions of system (1.2) are positive, simple calculation leads to Therefore, we get for sufficiently large time , where is an arbitrarily small positive constant. Finally, all the solutions of system (1.2) are ultimately bounded by some positive constant. This completes the proof.

3. Global Stability

In this section, we study the global stability of each equilibrium of system (1.2) by using suitable Lyapunov functionals which are inspired by Xu [12] and McCluskey [19] and LaSalle's invariant principle.

Define the following function: Clearly, for , has the minimum at and .

Theorem 3.1. If , the infection-free equilibrium of system (1.2) is globally asymptotically stable.

Proof. Let be any positive solution of system (1.2) with initial conditions (1.3). Define the following Lyapunov functional: Calculating the derivative of along positive solutions of system (1.2), it follows that
Noting that , we obtain . Hence, from (3.3), we have . By Theorem in [18], solutions limit to , the largest invariant subset of . Let be the solution with initial function in . Then, from the invariance of , we obtain , , and for any . Further, from the third equation of system (1.2), we obtain . Accordingly, it follows from LaSalle's invariance principal that the infection-free equilibrium is globally asymptotically stable for any positive time delays. This completes the proof.

Theorem 3.2. If , the CTL-inactivated infection equilibrium of system (1.2) is globally asymptotically stable.

Proof. Let be any positive solution of system (1.2) with initial conditions (1.3). Define the following Lyapunov functional: where
For clarity, we will calculate the derivatives of , , , , , and along positive solutions of system (1.2), respectively.
Since holds, it follows that Noting that , we get that Since holds, it follows that Calculating the derivatives of and shows that We therefore derive from (3.6)–(3.9) that
Noting that , we derive that . Hence, from (3.10), we have . Similar to Theorem 3.1, solutions limit to , the largest invariant subset of . Let be the solution with initial function in . Then, we obtain that It is readily to show that , , , and for any . Thus, it follows from LaSalle's invariance principal that the CTL-inactivated infection equilibrium is globally asymptotically stable for any positive time delays. This completes the proof.

Theorem 3.3. If , the CTL-activated infection equilibrium of system (1.2) is globally asymptotically stable.

Proof. Let be any positive solution of system (1.2) with initial conditions (1.3). We construct the following Lyapunov functional: where
Next, we will calculate the derivatives of , , , , , and along positive solutions of system (1.2), respectively.
Similar to (3.6), we derive that Noting that , it follows that Similar to (3.8), we get that Calculating the derivative of shows that Similar to (3.9), it follows that We therefore derive from (3.14)–(3.18) that
Hence, from (3.19), we get . Similar to Theorem 3.1, solutions limit to , the largest invariant subset of . Let be the solution with initial function in . Then, it holds that It is easy to show that , , and for any time . Moreover, from the second equation of system (1.2), we obtain . Therefore, it follows from LaSalle's invariance principal that the CTL-activated infection equilibrium is globally asymptotically stable for any positive time delays. This completes the proof.

4. Numerical Simulations

In the following, we give three examples to illustrate the main theoretical results above. All the parameters were obtained from [9, 16, 20].

Example 4.1. In system (1.2), we choose , , , , , , , , , , and , . It is easy to show that , and that system (1.2) has an infection-free equilibrium . By Theorem 3.1, we get that the infection-free equilibrium of system (1.2) is globally asymptotically stable. Numerical simulation illustrates this fact (see Figure 1).

fig1
Figure 1: The infection-free equilibrium of system (1.2) is globally asymptotically stable. Here , , and the initial value is .

Example 4.2. In system (1.2), we set , , , , , , , , , , and , . It is easy to show that , and that system (1.2) has a CTL-inactivated infection equilibrium . By Theorem 3.2, we obtain that the CTL-inactivated infection equilibrium of system (1.2) is globally asymptotically stable. Numerical simulation illustrates our result (see Figure 2).

fig2
Figure 2: The CTL-inactivated infection equilibrium of system (1.2) is globally asymptotically stable. Here , , and the initial value is .

Example 4.3. In system (1.2), let , , , , , , , , , , and , . It is easy to show that , and then system (1.2) has a CTL-activated infection equilibrium . By Theorem 3.3, we get that the CTL-activated infection equilibrium of system (1.2) is globally asymptotically stable. Numerical simulation illustrates this fact (see Figure 3).

fig3
Figure 3: The CTL-activated infection equilibrium of system (1.2) is globally asymptotically stable. Here , , and the initial value is .

5. Discussion

In this paper, we have studied the global dynamics of a delayed HIV-1 infection model with CTL immune response. By constructing suitable Lyapunov functionals, sufficient conditions have been derived for the global stability of three equilibria. It is easy to show that if the basic reproduction ratio for viral infection , infection-free equilibrium is globally asymptotically stable, and the virus is cleared up; if the basic reproduction ratio for CTL immune response satisfies , the equilibrium is globally asymptotically stable, and the infection becomes chronic but without CTL immune response; if , system (1.2) has a CTL-activated infection equilibrium besides and , which is globally asymptotically stable, and the infection turns to chronic with CTL immune response.

From Theorems 3.1, 3.2, and 3.3, we see that the delays and do not affect the global stability of the feasible equilibria and therefore do not induce periodic oscillations, and the possibility of Hopf bifurcations is therefore ruled out. On the other hand, if the basic reproduction ratio for CTL immune response , we can get which shows that the number of infected cells and virions of the equilibrium is greater than the number of those of the equilibrium . Hence, the CTL immune response plays an important role in the reduction of the infected cells and the free virions.

Acknowledgment

This work was supported by the National Natural Science Foundation of China (no. 11071254).

References

  1. M. Nowak, S. Bonhoeffer, G. M. Shaw, and R. M. May, “Anti-viral drug treatment: Dynamics of resistance in free virus and infected cell populations,” Journal of Theoretical Biology, vol. 184, no. 2, pp. 203–217, 1997. View at Publisher · View at Google Scholar · View at Scopus
  2. A. Perelson, A. Neumann, M. Markowitz, J. M. Leonard, and D. D. Ho, “HIV-1 dynamics in vivo: Virion clearance rate, infected cell life-span, and viral generation time,” Science, vol. 271, no. 5255, pp. 1582–1586, 1996. View at Google Scholar · View at Scopus
  3. M. Nowark and R. May, Virus Dynamics, Oxford University Press, Cambridge, UK, 2000. View at Zentralblatt MATH
  4. A. S. Perelson and P. W. Nelson, “Mathematical analysis of HIV-1 dynamics in vivo,” SIAM Review, vol. 41, no. 1, pp. 3–44, 1999. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  5. H. Zhu and X. Zou, “Dynamics of a HIV-1 infection model with cell-mediated immune response and intracellular delay,” Discrete and Continuous Dynamical Systems. Series B, vol. 12, no. 2, pp. 511–524, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  6. Y. Nakata, “Global dynamics of a cell mediated immunity in viral infection models with distributed delays,” Journal of Mathematical Analysis and Applications, vol. 375, no. 1, pp. 14–27, 2011. View at Publisher · View at Google Scholar
  7. M. Nowak and C. R. M. Bangham, “Population dynamics of immune responses to persistent viruses,” Science, vol. 272, no. 5258, pp. 74–79, 1996. View at Google Scholar · View at Scopus
  8. X. Shi, X. Zhou, and X. Song, “Dynamical behavior of a delay virus dynamics model with CTL immune response,” Nonlinear Analysis: Real World Applications, vol. 11, no. 3, pp. 1795–1809, 2010. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  9. R. V. Culshaw, S. Ruan, and R. J. Spiteri, “Optimal HIV treatment by maximising immune response,” Journal of Mathematical Biology, vol. 48, no. 5, pp. 545–562, 2004. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  10. D. Li and W. Ma, “Asymptotic properties of a HIV-1 infection model with time delay,” Journal of Mathematical Analysis and Applications, vol. 335, no. 1, pp. 683–691, 2007. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  11. X. Song and U. Avidan, “Global stability and periodic solution of the viral dynamics,” Journal of Mathematical Analysis and Applications, vol. 329, no. 1, pp. 281–297, 2007. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  12. R. Xu, “Global stability of an HIV-1 infection model with saturation infection and intracellular delay,” Journal of Mathematical Analysis and Applications, vol. 375, no. 1, pp. 75–81, 2011. View at Publisher · View at Google Scholar
  13. H. Zhu and X. Zou, “Impact of delays in cell infection and virus production on HIV-1 dynamics,” Mathematical Medicine and Biology, vol. 25, no. 2, pp. 99–112, 2008. View at Publisher · View at Google Scholar · View at Scopus
  14. R. V. Culshaw, S. Ruan, and G. Webb, “A mathematical model of cell-to-cell spread of HIV-1 that includes a time delay,” Journal of Mathematical Biology, vol. 46, no. 5, pp. 425–444, 2003. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  15. K. Wang, W. Wang, H. Pang, and X. Liu, “Complex dynamic behavior in a viral model with delayed immune response,” Physica D, vol. 226, no. 2, pp. 197–208, 2007. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  16. X. Song, X. Zhou, and X. Zhao, “Properties of stability and Hopf bifurcation for a HIV infection model with time delay,” Applied Mathematical Modelling, vol. 34, no. 6, pp. 1511–1523, 2010. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  17. P. Nelson and A. Perelson, “Mathematical analysis of delay differential equation models of HIV-1 infection,” Mathematical Biosciences, vol. 179, no. 1, pp. 73–94, 2002. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  18. J. K. Hale and S. Verduyn Lunel, Introduction to Functional Differential Equations, Applied Mathematical Sciences, Springer, New York, NY, USA, 1993.
  19. C. C. McCluskey, “Complete global stability for an SIR epidemic model with delay-distributed or discrete,” Nonlinear Analysis: Real World Applications, vol. 11, no. 1, pp. 55–59, 2010. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  20. A. Perelson, D. Kirschner, and R. De Boer, “Dynamics of HIV infection of CD4+ T cells,” Mathematical Biosciences, vol. 114, no. 1, pp. 81–125, 1993. View at Publisher · View at Google Scholar · View at Scopus