Modeling the progression and treatment of HIV

Current treatment of HIV patients is based on various guidelines that have changed with the advent of newer antiretroviral therapies and the emergence of resistance to them. However, there remains uncertainty over the best time to initiate HIV therapy or when to switch. Observational cohort studies or clinical trials are limited in the number of scenarios they can examine, whereas simulation modeling is well suited for considering various treatment policies. We describe a Monte Carlo simulation of a cohort of HIV positive patients that explicitly models two key components of HIV progression: adherence and the acquisition of resistance. Simulation results closely match cohort statistics such as survival time and length of time on the first three treatment regimens. We also describe sensitivity analyses and experiments such as testing the effects of starting therapy at different levels.