Joint effects of mitosis and intracellular delay on viral dynamics: two-parameter bifurcation analysis

To understand joint effects of logistic growth in target cells and intracellular delay on viral dynamics in vivo, we carry out two-parameter bifurcation analysis of an in-host model that describes infections of many viruses including HIV-I, HBV and HTLV-I. The bifurcation parameters are the mitosis rate r of the target cells and an intracellular delay τ in the incidence of viral infection. We describe the stability region of the chronic-infection equilibrium E* in the two-dimensional (r, τ) parameter space, as well as the global Hopf bifurcation curves as each of τ and r varies. Our analysis shows that, while both τ and r can destabilize E* and cause Hopf bifurcations, they do behave differently. The intracellular delay τ can cause Hopf bifurcations only when r is positive and sufficiently large, while r can cause Hopf bifurcations even when τ = 0. Intracellular delay τ can cause stability switches in E* while r does not.

[1]  Liancheng Wang,et al.  HIV infection and CD4+ T cell dynamics , 2006 .

[2]  Yan Wang,et al.  Oscillatory viral dynamics in a delayed HIV pathogenesis model. , 2009, Mathematical biosciences.

[3]  S. Ruan,et al.  A delay-differential equation model of HIV infection of CD4(+) T-cells. , 2000, Mathematical biosciences.

[4]  Alan S. Perelson,et al.  Dynamics of HIV Infection , 2003 .

[5]  M A Nowak,et al.  Viral dynamics in vivo: limitations on estimates of intracellular delay and virus decay. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[6]  To Oluyo,et al.  Mathematical analysis of the global dynamics of a model for HIV infection of CD4 + T cells , 2008 .

[7]  Michael Y. Li,et al.  Multiple Stable Periodic Oscillations in a Mathematical Model of CTL Response to HTLV-I Infection , 2011, Bulletin of mathematical biology.

[8]  A. Perelson,et al.  A model of HIV-1 pathogenesis that includes an intracellular delay. , 2000, Mathematical biosciences.

[9]  A. Korobeinikov Global properties of basic virus dynamics models , 2004, Bulletin of mathematical biology.

[10]  Denise Kirschner,et al.  Mathematical analysis of the global dynamics of a model for HTLV-I infection and ATL progression. , 2002, Mathematical biosciences.

[11]  Henry C Tuckwell,et al.  On the behavior of solutions in viral dynamical models. , 2004, Bio Systems.

[12]  Hal L. Smith,et al.  Virus Dynamics: A Global Analysis , 2003, SIAM J. Appl. Math..

[13]  M. Nowak,et al.  Population Dynamics of Immune Responses to Persistent Viruses , 1996, Science.

[14]  Alan S. Perelson,et al.  Mathematical Analysis of HIV-1 Dynamics in Vivo , 1999, SIAM Rev..

[15]  Yang Kuang,et al.  Geometric Stability Switch Criteria in Delay Differential Systems with Delay Dependent Parameters , 2002, SIAM J. Math. Anal..

[16]  M A Nowak,et al.  Viral dynamics in hepatitis B virus infection. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[17]  Michael Y. Li,et al.  Global Dynamics of an In-host Viral Model with Intracellular Delay , 2010, Bulletin of mathematical biology.

[18]  Patrick W Nelson,et al.  Mathematical analysis of delay differential equation models of HIV-1 infection. , 2002, Mathematical biosciences.

[19]  A. Perelson,et al.  HIV-1 Dynamics in Vivo: Virion Clearance Rate, Infected Cell Life-Span, and Viral Generation Time , 1996, Science.

[20]  K. Kim CD4+T Cells , 1993 .

[21]  Michael Y. Li,et al.  Impact of Intracellular Delays and Target-Cell Dynamics on In Vivo Viral Infections , 2010, SIAM J. Appl. Math..

[22]  Libin Rong,et al.  Modeling HIV persistence, the latent reservoir, and viral blips. , 2009, Journal of theoretical biology.