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Incorporating incidence information within the UNAIDS Estimation and Projection Package framework: a study based on simulated incidence assay data

OBJECTIVES: The objective of this study is to extend the UNAIDS incidence estimation model, the UNAIDS Estimation and Projection Package (EPP), so that it can incorporate data from incidence assays. METHODS: We propose combining the likelihood of the incidence assay data with the likelihood of other...

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Autores principales: Bao, Le, Ye, Jingyi, Hallett, Timothy B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4247275/
https://www.ncbi.nlm.nih.gov/pubmed/25406754
http://dx.doi.org/10.1097/QAD.0000000000000434
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author Bao, Le
Ye, Jingyi
Hallett, Timothy B.
author_facet Bao, Le
Ye, Jingyi
Hallett, Timothy B.
author_sort Bao, Le
collection PubMed
description OBJECTIVES: The objective of this study is to extend the UNAIDS incidence estimation model, the UNAIDS Estimation and Projection Package (EPP), so that it can incorporate data from incidence assays. METHODS: We propose combining the likelihood of the incidence assay data with the likelihood of other data, in a manner that is consistent with the biomarker-based incidence estimator using incidence assay data. Two calibrating parameters specify the performance of the incidence assays: the false recent rate and the mean duration of recent infection. We then use synthetic data, based on prevalence data obtained from antenatal clinic surveillances, and in some cases household surveys, from 24 countries, to examine the impact of including incidence assay data, under circumstances wherein the incidence assay data imply the same or a different incidence rate as that inferred from the prevalence data alone, and wherein incorrect calibrating parameters for the incidence assay data are used. RESULTS: Using incidence assay data, in addition to prevalence data, can improve estimate by narrowing uncertainty intervals in derived HIV incidence estimates, and by providing information on levels or trends in incidence that were not apparent in the prevalence data alone. However, the effect is relatively modest if the sample size of the incidence assay survey is small and results can be biased if the calibrating parameters for the incidence assay data are not known accurately. CONCLUSION: Incorporating information from incidence assays in the manner proposed has the potential to improve estimates. Further work will examine in more detail the circumstances under which the contribution of incidence assay data would be most valuable.
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spelling pubmed-42472752014-12-01 Incorporating incidence information within the UNAIDS Estimation and Projection Package framework: a study based on simulated incidence assay data Bao, Le Ye, Jingyi Hallett, Timothy B. AIDS The 2013/14 UNAIDS Estimates Methods: Extending The Scope and Granularity of HIV Estimates OBJECTIVES: The objective of this study is to extend the UNAIDS incidence estimation model, the UNAIDS Estimation and Projection Package (EPP), so that it can incorporate data from incidence assays. METHODS: We propose combining the likelihood of the incidence assay data with the likelihood of other data, in a manner that is consistent with the biomarker-based incidence estimator using incidence assay data. Two calibrating parameters specify the performance of the incidence assays: the false recent rate and the mean duration of recent infection. We then use synthetic data, based on prevalence data obtained from antenatal clinic surveillances, and in some cases household surveys, from 24 countries, to examine the impact of including incidence assay data, under circumstances wherein the incidence assay data imply the same or a different incidence rate as that inferred from the prevalence data alone, and wherein incorrect calibrating parameters for the incidence assay data are used. RESULTS: Using incidence assay data, in addition to prevalence data, can improve estimate by narrowing uncertainty intervals in derived HIV incidence estimates, and by providing information on levels or trends in incidence that were not apparent in the prevalence data alone. However, the effect is relatively modest if the sample size of the incidence assay survey is small and results can be biased if the calibrating parameters for the incidence assay data are not known accurately. CONCLUSION: Incorporating information from incidence assays in the manner proposed has the potential to improve estimates. Further work will examine in more detail the circumstances under which the contribution of incidence assay data would be most valuable. Lippincott Williams & Wilkins 2014-11 2014-11-20 /pmc/articles/PMC4247275/ /pubmed/25406754 http://dx.doi.org/10.1097/QAD.0000000000000434 Text en © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License, where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially. http://creativecommons.org/licenses/by-nc-nd/4.0
spellingShingle The 2013/14 UNAIDS Estimates Methods: Extending The Scope and Granularity of HIV Estimates
Bao, Le
Ye, Jingyi
Hallett, Timothy B.
Incorporating incidence information within the UNAIDS Estimation and Projection Package framework: a study based on simulated incidence assay data
title Incorporating incidence information within the UNAIDS Estimation and Projection Package framework: a study based on simulated incidence assay data
title_full Incorporating incidence information within the UNAIDS Estimation and Projection Package framework: a study based on simulated incidence assay data
title_fullStr Incorporating incidence information within the UNAIDS Estimation and Projection Package framework: a study based on simulated incidence assay data
title_full_unstemmed Incorporating incidence information within the UNAIDS Estimation and Projection Package framework: a study based on simulated incidence assay data
title_short Incorporating incidence information within the UNAIDS Estimation and Projection Package framework: a study based on simulated incidence assay data
title_sort incorporating incidence information within the unaids estimation and projection package framework: a study based on simulated incidence assay data
topic The 2013/14 UNAIDS Estimates Methods: Extending The Scope and Granularity of HIV Estimates
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4247275/
https://www.ncbi.nlm.nih.gov/pubmed/25406754
http://dx.doi.org/10.1097/QAD.0000000000000434
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