HIV-1: Optimizing treatment protocols when diagnostics are costly
- Date:
- April 30, 2015
- Source:
- PLOS
- Summary:
- HIV-1 continues to spread globally. While neither a cure, nor an effective vaccine are available, recent focus has been put on 'treatment-for-prevention', which is a method by which treatment is used to reduce the contagiousness of an infected person. A new study challenges current treatment paradigms in the context of 'treatment for prevention' against HIV-1.
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HIV-1 continues to spread globally. While neither a cure, nor an effective vaccine are available, recent focus has been put on 'treatment-for-prevention', which is a method by which treatment is used to reduce the contagiousness of an infected person. A study published this week in PLOS Computational Biology challenges current treatment paradigms in the context of 'treatment for prevention' against HIV-1.
Sulav Duwal, Max von Kleist and their collaborators develop and employ optimal control theory to compute and assess diagnostic-guided vs. pro-active treatment strategies in terms of their expected costs, treatment benefit and reduction of onwards transmission.
In the study published this week in PLOS Computational Biology, the authors provide a mathematical platform that can be used to compute optimal diagnostic-guided vs. pro-active treatment strategies under consideration of available resources. They apply this framework to a stochastic model of viral intra-host dynamics and drug resistance development. When applied to resource-constrained settings, they show that pro-active strategies may be worthwhile.
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Journal Reference:
- Sulav Duwal, Stefanie Winkelmann, Christof Schütte, Max von Kleist. Optimal Treatment Strategies in the Context of ‘Treatment for Prevention’ against HIV-1 in Resource-Poor Settings. PLOS Computational Biology, 2015; 11 (4): e1004200 DOI: 10.1371/journal.pcbi.1004200
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