Sensitivity analysis of HIV infection response to treatment

Samira Khalili, Antonios Armaou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


This work focuses on the analysis of HIV infection dynamics during the initial stages of infection when the viral load is low and random fluctuations may have a significant effect on the dynamics of the disease. The ability of deterministic models to accurately describe the expected behavior of such processes is limited. Stochastic simulations, which are not hampered by this limitation, are used to determine the probability of successful infection in an average patient. Specifically, a stochastic model based on Gillespie's algorithm is derived and is employed to determine the sensitivity of HIV infection to different treatment strategies and the effect of latency in treatment initiation on virus clearance probability. The model is subsequently revised to include mutation in the virus genome and the response to treatment is analyzed.

Original languageEnglish (US)
Title of host publicationProceedings of the 45th IEEE Conference on Decision and Control 2006, CDC
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
ISBN (Print)1424401712, 9781424401710
StatePublished - 2006
Event45th IEEE Conference on Decision and Control 2006, CDC - San Diego, CA, United States
Duration: Dec 13 2006Dec 15 2006

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370


Other45th IEEE Conference on Decision and Control 2006, CDC
Country/TerritoryUnited States
CitySan Diego, CA

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization


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