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HIV models for treatment interruption: adaptation and comparison

Hillmann, Andreas orcid logoORCID: 0000-0002-6517-1615, Crane, Martin orcid logoORCID: 0000-0001-7598-3126 and Ruskin, Heather J. orcid logoORCID: 0000-0001-7101-2242 (2017) HIV models for treatment interruption: adaptation and comparison. Physica A Statistical Mechanics and its Applications, 483 . pp. 44-56. ISSN 0378-4371

Abstract
In recent years, Antiretroviral Therapy (ART) has become commonplace for treating HIV infections, although a cure remains elusive, given reservoirs of replicating latently-infected cells, which are resistant to normal treatment regimes. Treatment interruptions, whether ad hoc or structured, are known to cause a rapid increase in viral production to detectable levels, but numerous clinical trials remain inconclusive on the dangers inherent in this resurgence. In consequence, interest in examining interruption strategies has recently been rekindled. This overview considers modelling approaches, which have been used to explore the issue of treatment interruption. We highlight their purpose and the formalisms employed and examine ways in which clinical data have been used. Implementation of selected models is demonstrated, illustrative examples provided and model performance compared for these cases. Possible extensions to bottom-up modelling techniques for treatment interruptions are briefly discussed.
Metadata
Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:Compartmental Models; Structured Treatment Interruption; Dynamic models; HIV; Cellular automata; Antiretroviral treatment
Subjects:Biological Sciences > Bioinformatics
Mathematics > Differential equations
Mathematics > Numerical analysis
Medical Sciences > Epidemiology
Medical Sciences > Diseases
Mathematics > Statistics
Biological Sciences > Immunology
Computer Science > Computer simulation
DCU Faculties and Centres:Research Initiatives and Centres > Scientific Computing and Complex Systems Modelling (Sci-Sym)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Publisher:Elsevier
Official URL:https://doi.org/10.1016/j.physa.2017.05.005
Copyright Information:© 2017 Elsevier
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:21791
Deposited On:11 May 2017 15:24 by Martin Crane . Last Modified 04 Aug 2022 14:12
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