Dr. Jane Heffernan

Department of Mathematics and Statistics

York University

* Title: *"Models of HIV Infection: Natural Variability and Drug Therapy "

* Abstract:*

Understanding how the human immunodeficiency virus (HIV) infects and eventually weakens the immune

system is one of the most important medical problems of the 21st century. Mathematical models of

HIV infection describing virus and immune system dynamics have contributed significantly to the

understanding of HIV pathogenesis within a single individual, "in-host". However, the majority of

these models are deterministic, ignoring the stochastic nature of HIV dynamics. Thus, the expected

variability of clinically relevant measures cannot be estimated. We have developed a Monte Carlo

model of in-host HIV dynamics. The simulation proceeds at the level of individual cells and HIV

virions, thus capturing the inherent stochasticity in viral replication and T-cell infection. Simple

modifications permit the incorporation of pharmacokinetic models of drug therapy and prediction of

the clearance probability of an initial inoculum of virus. The simulation is used to determine the

sensitivity in important model parameters, such as the basic reproductive ratio (R0), the initial

growth rate and the infected equilibrium, to the underlying T-cell and HIV virion lifetime distributions.