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Modelling the Impact of Antiretroviral Use in Resource-Poor Settings

BACKGROUND: The anticipated scale-up of antiretroviral therapy (ART) in high-prevalence, resource-constrained settings requires operational research to guide policy on the design of treatment programmes. Mathematical models can explore the potential impacts of various treatment strategies, including...

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Autores principales: Baggaley, Rebecca F, Garnett, Geoff P, Ferguson, Neil M
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1395349/
https://www.ncbi.nlm.nih.gov/pubmed/16519553
http://dx.doi.org/10.1371/journal.pmed.0030124
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author Baggaley, Rebecca F
Garnett, Geoff P
Ferguson, Neil M
author_facet Baggaley, Rebecca F
Garnett, Geoff P
Ferguson, Neil M
author_sort Baggaley, Rebecca F
collection PubMed
description BACKGROUND: The anticipated scale-up of antiretroviral therapy (ART) in high-prevalence, resource-constrained settings requires operational research to guide policy on the design of treatment programmes. Mathematical models can explore the potential impacts of various treatment strategies, including timing of treatment initiation and provision of laboratory monitoring facilities, to complement evidence from pilot programmes. METHODS AND FINDINGS: A deterministic model of HIV transmission incorporating ART and stratifying infection progression into stages was constructed. The impact of ART was evaluated for various scenarios and treatment strategies, with different levels of coverage, patient eligibility, and other parameter values. These strategies included the provision of laboratory facilities that perform CD4 counts and viral load testing, and the timing of the stage of infection at which treatment is initiated. In our analysis, unlimited ART provision initiated at late-stage infection (AIDS) increased prevalence of HIV infection. The effect of additionally treating pre-AIDS patients depended on the behaviour change of treated patients. Different coverage levels for ART do not affect benefits such as life-years gained per person-year of treatment and have minimal effect on infections averted when treating AIDS patients only. Scaling up treatment of pre-AIDS patients resulted in more infections being averted per person-year of treatment, but the absolute number of infections averted remained small. As coverage increased in the models, the emergence and risk of spread of drug resistance increased. Withdrawal of failing treatment (clinical resurgence of symptoms), immunologic (CD4 count decline), or virologic failure (viral rebound) increased the number of infected individuals who could benefit from ART, but effectiveness per person is compromised. Only withdrawal at a very early stage of treatment failure, soon after viral rebound, would have a substantial impact on emergence of drug resistance. CONCLUSIONS: Our analysis found that ART cannot be seen as a direct transmission prevention measure, regardless of the degree of coverage. Counselling of patients to promote safe sexual practices is essential and must aim to effect long-term change. The chief aims of an ART programme, such as maximised number of patients treated or optimised treatment per patient, will determine which treatment strategy is most effective.
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spelling pubmed-13953492006-05-08 Modelling the Impact of Antiretroviral Use in Resource-Poor Settings Baggaley, Rebecca F Garnett, Geoff P Ferguson, Neil M PLoS Med Research Article BACKGROUND: The anticipated scale-up of antiretroviral therapy (ART) in high-prevalence, resource-constrained settings requires operational research to guide policy on the design of treatment programmes. Mathematical models can explore the potential impacts of various treatment strategies, including timing of treatment initiation and provision of laboratory monitoring facilities, to complement evidence from pilot programmes. METHODS AND FINDINGS: A deterministic model of HIV transmission incorporating ART and stratifying infection progression into stages was constructed. The impact of ART was evaluated for various scenarios and treatment strategies, with different levels of coverage, patient eligibility, and other parameter values. These strategies included the provision of laboratory facilities that perform CD4 counts and viral load testing, and the timing of the stage of infection at which treatment is initiated. In our analysis, unlimited ART provision initiated at late-stage infection (AIDS) increased prevalence of HIV infection. The effect of additionally treating pre-AIDS patients depended on the behaviour change of treated patients. Different coverage levels for ART do not affect benefits such as life-years gained per person-year of treatment and have minimal effect on infections averted when treating AIDS patients only. Scaling up treatment of pre-AIDS patients resulted in more infections being averted per person-year of treatment, but the absolute number of infections averted remained small. As coverage increased in the models, the emergence and risk of spread of drug resistance increased. Withdrawal of failing treatment (clinical resurgence of symptoms), immunologic (CD4 count decline), or virologic failure (viral rebound) increased the number of infected individuals who could benefit from ART, but effectiveness per person is compromised. Only withdrawal at a very early stage of treatment failure, soon after viral rebound, would have a substantial impact on emergence of drug resistance. CONCLUSIONS: Our analysis found that ART cannot be seen as a direct transmission prevention measure, regardless of the degree of coverage. Counselling of patients to promote safe sexual practices is essential and must aim to effect long-term change. The chief aims of an ART programme, such as maximised number of patients treated or optimised treatment per patient, will determine which treatment strategy is most effective. Public Library of Science 2006-04 2006-03-14 /pmc/articles/PMC1395349/ /pubmed/16519553 http://dx.doi.org/10.1371/journal.pmed.0030124 Text en Copyright: © 2006 Baggaley et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Baggaley, Rebecca F
Garnett, Geoff P
Ferguson, Neil M
Modelling the Impact of Antiretroviral Use in Resource-Poor Settings
title Modelling the Impact of Antiretroviral Use in Resource-Poor Settings
title_full Modelling the Impact of Antiretroviral Use in Resource-Poor Settings
title_fullStr Modelling the Impact of Antiretroviral Use in Resource-Poor Settings
title_full_unstemmed Modelling the Impact of Antiretroviral Use in Resource-Poor Settings
title_short Modelling the Impact of Antiretroviral Use in Resource-Poor Settings
title_sort modelling the impact of antiretroviral use in resource-poor settings
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1395349/
https://www.ncbi.nlm.nih.gov/pubmed/16519553
http://dx.doi.org/10.1371/journal.pmed.0030124
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