Long term dynamics in a mathematical model of HIV-1 infection with delay in different variants of the basic drug therapy model
Roy, Priti Kumar and Chatterjee, Amar Nath and Greenhalgh, David and Khan, Qamar J A (2013) Long term dynamics in a mathematical model of HIV-1 infection with delay in different variants of the basic drug therapy model. Nonlinear Analysis: Real World Applications, 14 (3). pp. 1621-1633. ISSN 1468-1218 (https://doi.org/10.1016/j.nonrwa.2012.10.021)
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Abstract
Infection with HIV-1, degrading the human immune system and recent advances of drug therapy to arrest HIV-1 infection, has generated considerable research interest in the area. Sebastian Bonhoeffer et al. [2], introduced a population model representing long term dynamics of HIV infection in response to available drug therapies. We consider a similar type of approximate model incorporating time delay in the process of infection on the healthy T cells which, in turn, implies inclusion of a similar delay in the process of viral replication. The model is studied both analytically and numerically. We also include a similar delay in the killing rate of infected CD4+ T cells by Cytotoxic TLymphocyte (CTL) and in the stimulation of CTL and analyze two resulting models numerically. The models with no time delay present have two equilibria: one where there is no infection and a non-trivial equilibrium where the infection can persist. If there is no time delay then the non-trivial equilibrium is locally asymptotically stable. Both our analytical results (for the first model) and our numerical results (for all three models) indicate that introduction of a time delay can destabilize the non-trivial equilibrium. The numerical results indicate that such destabilization occurs at realistic time delays and that there is a threshold time delay beneath which the equilibrium with infection present is locally asymptotically stable and above which this equilibrium is unstable and exhibits oscillatory solutions of increasing amplitude.
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Item type: Article ID code: 49774 Dates: DateEventJune 2013Published31 October 2012AcceptedSubjects: Science > Mathematics > Probabilities. Mathematical statistics Department: Faculty of Science > Mathematics and Statistics Depositing user: Pure Administrator Date deposited: 14 Oct 2014 08:30 Last modified: 25 Mar 2024 02:28 URI: https://strathprints.strath.ac.uk/id/eprint/49774