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A New Method for Estimating the Number of Undiagnosed HIV Infected Based on HIV Testing History, with an Application to Men Who Have Sex with Men in Seattle/King County, WA
We develop a new approach for estimating the undiagnosed fraction of HIV cases, the first step in the HIV Care Cascade. The goal is to address a critical blindspot in HIV prevention and treatment planning, with an approach that simplifies data requirements and can be implemented with open-source sof...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4510124/ https://www.ncbi.nlm.nih.gov/pubmed/26196132 http://dx.doi.org/10.1371/journal.pone.0129551 |
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author | Fellows, Ian E. Morris, Martina Birnbaum, Jeanette K. Dombrowski, Julia C. Buskin, Susan Bennett, Amy Golden, Matthew R. |
author_facet | Fellows, Ian E. Morris, Martina Birnbaum, Jeanette K. Dombrowski, Julia C. Buskin, Susan Bennett, Amy Golden, Matthew R. |
author_sort | Fellows, Ian E. |
collection | PubMed |
description | We develop a new approach for estimating the undiagnosed fraction of HIV cases, the first step in the HIV Care Cascade. The goal is to address a critical blindspot in HIV prevention and treatment planning, with an approach that simplifies data requirements and can be implemented with open-source software. The primary data required is HIV testing history information on newly diagnosed cases. Two methods are presented and compared. The first is a general methodology based on simplified back-calculation that can be used to assess changes in the undiagnosed fraction over time. The second makes an assumption of constant incidence, allowing the estimate to be expressed as a simple closed formula calculation. We demonstrate the methods with an application to HIV diagnoses among men who have sex with men (MSM) from Seattle/King County. The estimates suggest that 6% of HIV-infected MSM in King County are undiagnosed, about one-third of the comparable national estimate. A sensitivity analysis on the key distributional assumption gives an upper bound of 11%. The undiagnosed fraction varies by race/ethnicity, with estimates of 4.9% among white, 8.6% of African American, and 9.3% of Hispanic HIV-infected MSM being undiagnosed. |
format | Online Article Text |
id | pubmed-4510124 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-45101242015-07-24 A New Method for Estimating the Number of Undiagnosed HIV Infected Based on HIV Testing History, with an Application to Men Who Have Sex with Men in Seattle/King County, WA Fellows, Ian E. Morris, Martina Birnbaum, Jeanette K. Dombrowski, Julia C. Buskin, Susan Bennett, Amy Golden, Matthew R. PLoS One Research Article We develop a new approach for estimating the undiagnosed fraction of HIV cases, the first step in the HIV Care Cascade. The goal is to address a critical blindspot in HIV prevention and treatment planning, with an approach that simplifies data requirements and can be implemented with open-source software. The primary data required is HIV testing history information on newly diagnosed cases. Two methods are presented and compared. The first is a general methodology based on simplified back-calculation that can be used to assess changes in the undiagnosed fraction over time. The second makes an assumption of constant incidence, allowing the estimate to be expressed as a simple closed formula calculation. We demonstrate the methods with an application to HIV diagnoses among men who have sex with men (MSM) from Seattle/King County. The estimates suggest that 6% of HIV-infected MSM in King County are undiagnosed, about one-third of the comparable national estimate. A sensitivity analysis on the key distributional assumption gives an upper bound of 11%. The undiagnosed fraction varies by race/ethnicity, with estimates of 4.9% among white, 8.6% of African American, and 9.3% of Hispanic HIV-infected MSM being undiagnosed. Public Library of Science 2015-07-21 /pmc/articles/PMC4510124/ /pubmed/26196132 http://dx.doi.org/10.1371/journal.pone.0129551 Text en © 2015 Fellows 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 Fellows, Ian E. Morris, Martina Birnbaum, Jeanette K. Dombrowski, Julia C. Buskin, Susan Bennett, Amy Golden, Matthew R. A New Method for Estimating the Number of Undiagnosed HIV Infected Based on HIV Testing History, with an Application to Men Who Have Sex with Men in Seattle/King County, WA |
title | A New Method for Estimating the Number of Undiagnosed HIV Infected Based on HIV Testing History, with an Application to Men Who Have Sex with Men in Seattle/King County, WA |
title_full | A New Method for Estimating the Number of Undiagnosed HIV Infected Based on HIV Testing History, with an Application to Men Who Have Sex with Men in Seattle/King County, WA |
title_fullStr | A New Method for Estimating the Number of Undiagnosed HIV Infected Based on HIV Testing History, with an Application to Men Who Have Sex with Men in Seattle/King County, WA |
title_full_unstemmed | A New Method for Estimating the Number of Undiagnosed HIV Infected Based on HIV Testing History, with an Application to Men Who Have Sex with Men in Seattle/King County, WA |
title_short | A New Method for Estimating the Number of Undiagnosed HIV Infected Based on HIV Testing History, with an Application to Men Who Have Sex with Men in Seattle/King County, WA |
title_sort | new method for estimating the number of undiagnosed hiv infected based on hiv testing history, with an application to men who have sex with men in seattle/king county, wa |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4510124/ https://www.ncbi.nlm.nih.gov/pubmed/26196132 http://dx.doi.org/10.1371/journal.pone.0129551 |
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