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Development of Methods for Cross-Sectional HIV Incidence Estimation in a Large, Community Randomized Trial

BACKGROUND: Accurate methods of HIV incidence determination are critically needed to monitor the epidemic and determine the population level impact of prevention trials. One such trial, Project Accept, a Phase III, community-randomized trial, evaluated the impact of enhanced, community-based volunta...

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Autores principales: Laeyendecker, Oliver, Kulich, Michal, Donnell, Deborah, Komárek, Arnošt, Omelka, Marek, Mullis, Caroline E., Szekeres, Greg, Piwowar-Manning, Estelle, Fiamma, Agnes, Gray, Ronald H., Lutalo, Tom, Morrison, Charles S., Salata, Robert A., Chipato, Tsungai, Celum, Connie, Kahle, Erin M., Taha, Taha E., Kumwenda, Newton I., Karim, Quarraisha Abdool, Naranbhai, Vivek, Lingappa, Jairam R., Sweat, Michael D., Coates, Thomas, Eshleman, Susan H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3827276/
https://www.ncbi.nlm.nih.gov/pubmed/24236054
http://dx.doi.org/10.1371/journal.pone.0078818
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author Laeyendecker, Oliver
Kulich, Michal
Donnell, Deborah
Komárek, Arnošt
Omelka, Marek
Mullis, Caroline E.
Szekeres, Greg
Piwowar-Manning, Estelle
Fiamma, Agnes
Gray, Ronald H.
Lutalo, Tom
Morrison, Charles S.
Salata, Robert A.
Chipato, Tsungai
Celum, Connie
Kahle, Erin M.
Taha, Taha E.
Kumwenda, Newton I.
Karim, Quarraisha Abdool
Naranbhai, Vivek
Lingappa, Jairam R.
Sweat, Michael D.
Coates, Thomas
Eshleman, Susan H.
author_facet Laeyendecker, Oliver
Kulich, Michal
Donnell, Deborah
Komárek, Arnošt
Omelka, Marek
Mullis, Caroline E.
Szekeres, Greg
Piwowar-Manning, Estelle
Fiamma, Agnes
Gray, Ronald H.
Lutalo, Tom
Morrison, Charles S.
Salata, Robert A.
Chipato, Tsungai
Celum, Connie
Kahle, Erin M.
Taha, Taha E.
Kumwenda, Newton I.
Karim, Quarraisha Abdool
Naranbhai, Vivek
Lingappa, Jairam R.
Sweat, Michael D.
Coates, Thomas
Eshleman, Susan H.
author_sort Laeyendecker, Oliver
collection PubMed
description BACKGROUND: Accurate methods of HIV incidence determination are critically needed to monitor the epidemic and determine the population level impact of prevention trials. One such trial, Project Accept, a Phase III, community-randomized trial, evaluated the impact of enhanced, community-based voluntary counseling and testing on population-level HIV incidence. The primary endpoint of the trial was based on a single, cross-sectional, post-intervention HIV incidence assessment. METHODS AND FINDINGS: Test performance of HIV incidence determination was evaluated for 403 multi-assay algorithms [MAAs] that included the BED capture immunoassay [BED-CEIA] alone, an avidity assay alone, and combinations of these assays at different cutoff values with and without CD4 and viral load testing on samples from seven African cohorts (5,325 samples from 3,436 individuals with known duration of HIV infection [1 month to >10 years]). The mean window period (average time individuals appear positive for a given algorithm) and performance in estimating an incidence estimate (in terms of bias and variance) of these MAAs were evaluated in three simulated epidemic scenarios (stable, emerging and waning). The power of different test methods to detect a 35% reduction in incidence in the matched communities of Project Accept was also assessed. A MAA was identified that included BED-CEIA, the avidity assay, CD4 cell count, and viral load that had a window period of 259 days, accurately estimated HIV incidence in all three epidemic settings and provided sufficient power to detect an intervention effect in Project Accept. CONCLUSIONS: In a Southern African setting, HIV incidence estimates and intervention effects can be accurately estimated from cross-sectional surveys using a MAA. The improved accuracy in cross-sectional incidence testing that a MAA provides is a powerful tool for HIV surveillance and program evaluation.
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spelling pubmed-38272762013-11-14 Development of Methods for Cross-Sectional HIV Incidence Estimation in a Large, Community Randomized Trial Laeyendecker, Oliver Kulich, Michal Donnell, Deborah Komárek, Arnošt Omelka, Marek Mullis, Caroline E. Szekeres, Greg Piwowar-Manning, Estelle Fiamma, Agnes Gray, Ronald H. Lutalo, Tom Morrison, Charles S. Salata, Robert A. Chipato, Tsungai Celum, Connie Kahle, Erin M. Taha, Taha E. Kumwenda, Newton I. Karim, Quarraisha Abdool Naranbhai, Vivek Lingappa, Jairam R. Sweat, Michael D. Coates, Thomas Eshleman, Susan H. PLoS One Research Article BACKGROUND: Accurate methods of HIV incidence determination are critically needed to monitor the epidemic and determine the population level impact of prevention trials. One such trial, Project Accept, a Phase III, community-randomized trial, evaluated the impact of enhanced, community-based voluntary counseling and testing on population-level HIV incidence. The primary endpoint of the trial was based on a single, cross-sectional, post-intervention HIV incidence assessment. METHODS AND FINDINGS: Test performance of HIV incidence determination was evaluated for 403 multi-assay algorithms [MAAs] that included the BED capture immunoassay [BED-CEIA] alone, an avidity assay alone, and combinations of these assays at different cutoff values with and without CD4 and viral load testing on samples from seven African cohorts (5,325 samples from 3,436 individuals with known duration of HIV infection [1 month to >10 years]). The mean window period (average time individuals appear positive for a given algorithm) and performance in estimating an incidence estimate (in terms of bias and variance) of these MAAs were evaluated in three simulated epidemic scenarios (stable, emerging and waning). The power of different test methods to detect a 35% reduction in incidence in the matched communities of Project Accept was also assessed. A MAA was identified that included BED-CEIA, the avidity assay, CD4 cell count, and viral load that had a window period of 259 days, accurately estimated HIV incidence in all three epidemic settings and provided sufficient power to detect an intervention effect in Project Accept. CONCLUSIONS: In a Southern African setting, HIV incidence estimates and intervention effects can be accurately estimated from cross-sectional surveys using a MAA. The improved accuracy in cross-sectional incidence testing that a MAA provides is a powerful tool for HIV surveillance and program evaluation. Public Library of Science 2013-11-13 /pmc/articles/PMC3827276/ /pubmed/24236054 http://dx.doi.org/10.1371/journal.pone.0078818 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
spellingShingle Research Article
Laeyendecker, Oliver
Kulich, Michal
Donnell, Deborah
Komárek, Arnošt
Omelka, Marek
Mullis, Caroline E.
Szekeres, Greg
Piwowar-Manning, Estelle
Fiamma, Agnes
Gray, Ronald H.
Lutalo, Tom
Morrison, Charles S.
Salata, Robert A.
Chipato, Tsungai
Celum, Connie
Kahle, Erin M.
Taha, Taha E.
Kumwenda, Newton I.
Karim, Quarraisha Abdool
Naranbhai, Vivek
Lingappa, Jairam R.
Sweat, Michael D.
Coates, Thomas
Eshleman, Susan H.
Development of Methods for Cross-Sectional HIV Incidence Estimation in a Large, Community Randomized Trial
title Development of Methods for Cross-Sectional HIV Incidence Estimation in a Large, Community Randomized Trial
title_full Development of Methods for Cross-Sectional HIV Incidence Estimation in a Large, Community Randomized Trial
title_fullStr Development of Methods for Cross-Sectional HIV Incidence Estimation in a Large, Community Randomized Trial
title_full_unstemmed Development of Methods for Cross-Sectional HIV Incidence Estimation in a Large, Community Randomized Trial
title_short Development of Methods for Cross-Sectional HIV Incidence Estimation in a Large, Community Randomized Trial
title_sort development of methods for cross-sectional hiv incidence estimation in a large, community randomized trial
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3827276/
https://www.ncbi.nlm.nih.gov/pubmed/24236054
http://dx.doi.org/10.1371/journal.pone.0078818
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