A stochastic model of latently infected cell reactivation and viral blip generation in treated HIV patients

Jessica M. Conway, Daniel Coombs

Research output: Contribution to journalArticle

47 Citations (Scopus)

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.

Original languageEnglish (US)
Article numbere1002033
JournalPLoS computational biology
Volume7
Issue number4
DOIs
StatePublished - Apr 1 2011

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Stochastic models
human immunodeficiency virus
Viral Load
reactivation
Stochastic Model
HIV
Probability distributions
viral load
Cell
probability distribution
Probability Distribution
Viremia
Direct numerical simulation
Multitype Branching Process
cells
Extinction Time
HIV Infection
Load Distribution
Probability generating function
HIV Infections

All Science Journal Classification (ASJC) codes

  • Cellular and Molecular Neuroscience
  • Ecology
  • Molecular Biology
  • Genetics
  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Computational Theory and Mathematics

Cite this

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A stochastic model of latently infected cell reactivation and viral blip generation in treated HIV patients. / Conway, Jessica M.; Coombs, Daniel.

In: PLoS computational biology, Vol. 7, No. 4, e1002033, 01.04.2011.

Research output: Contribution to journalArticle

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