TY - JOUR T1 - A Stochastic Model of Latently Infected Cell Reactivation and Viral Blip Generation in Treated HIV Patients A1 - Conway, Jessica M. A1 - Coombs, Daniel Y1 - 2011/04/28 N2 - Author Summary While on successful drug treatment, routine testing does not usually detect virus in the blood of an HIV patient. However, more sensitive techniques can detect extremely low levels of virus. Occasionally, routine blood tests show “viral blips”: short periods of elevated, detectable viral load. We explore the hypothesis that residual low-level viral load can be largely explained by re-activation of cells that were infected before the initiation of treatment, and that viral blips can be viewed as occasional statistical events. To do this, we propose a mathematical model of latently-infected cells, activated cells, and virus. The model captures random fluctuations of the system as well as the mean behaviour. We estimate the time it takes for all the latently-infected cells to be eradicated. Eradication of these cells is considered a major hurdle in eliminating infection. We predict a wide range of eradication times, highlighting the importance of studying latently-infected cells. We also estimate the frequency and duration of viral blips, and find qualitative agreement with clinical studies. By refining our models, we hope to find guidelines that can be used in practise to distinguish between clinically insignificant statistical blips, and instances of drug failure. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 7 IS - 4 UR - https://doi.org/10.1371/journal.pcbi.1002033 SP - e1002033 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1002033 ER -