Bulletin of Mathematical Biology

, Volume 69, Issue 2, pp 563–584 | Cite as

Estimation and Prediction With HIV-Treatment Interruption Data

  • B. M. Adams
  • H. T. Banks
  • M. Davidian
  • E. S. Rosenberg
Original Article


We consider longitudinal clinical data for HIV patients undergoing treatment interruptions. We use a nonlinear dynamical mathematical model in attempts to fit individual patient data. A statistically-based censored data method is combined with inverse problem techniques to estimate dynamic parameters. The predictive capabilities of this approach are demonstrated by comparing simulations based on estimation of parameters using only half of the longitudinal observations to the full longitudinal data sets.


HIV models Treatment interruptions Censored data Parameter estimation Prediction 


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Copyright information

© Society for Mathematical Biology 2006

Authors and Affiliations

  • B. M. Adams
    • 1
  • H. T. Banks
    • 1
  • M. Davidian
    • 1
  • E. S. Rosenberg
    • 2
  1. 1.Center for Research in Scientific ComputationNorth Carolina State UniversityRaleighUSA
  2. 2.I.D. Unit—Gray 5Massachusetts General Hospital and Harvard Medical SchoolBostonUSA

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