a stochastic model of latently infected cell reactivation and viral blip generation in treated hiv patients随机模型的潜伏性感染细胞活化和病毒通货代治疗艾滋病患者.pdfVIP

A Stochastic Model of Latently Infected Cell Reactivation and Viral Blip Generation in Treated HIV Patients Jessica M. Conway, Daniel Coombs* Department of Mathematics and Institute of Applied Mathematics, University of British Columbia, Vancouver, British Columbia, Canada Abstract Motivated by viral persistence in HIV+ patients on long-term anti-retroviral treatment (ART), we present a stochastic model of HIV viral dynamics in the blood stream. We consider the hypothesis that the residual viremia in patients on ART can be explained principally by the activation of cells latently infected by HIV before the initiation of ART and that viral blips (clinically-observed short periods of detectable viral load) represent large deviations from the mean. We model the system as a continuous-time, multi-type branching process. Deriving equations for the probability generating function we use a novel numerical approach to extract the probability distributions for latent reservoir sizes and viral loads. We find that latent reservoir extinction-time distributions underscore the importance of considering reservoir dynamics beyond simply the half- life. We calculate blip amplitudes and frequencies by computing complete viral load probability distributions, and study the duration of viral blips via direct numerical simulation. We find that our model qualitatively reproduces short small-amplitude blips detected in clinical studies of treated HIV infection. Stochastic models of this type provide insight into treatment- outcome variability that cannot be found from deterministic models. Citation: Conway JM, Coombs D (2011) A Stochastic Model of Latently Infected Cell Reactivation and Viral Blip Generation in Treated HIV Patients. PLoS Comput Biol 7(4): e1002033. doi:10.1371/journal.pcbi.1002033 Editor: Christophe Fraser, Imperial College London, United Kingdom