Development of methods for cross-sectional HIV incidence estimation in a large, community randomized trial.
<h4>Background</h4>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, comm...
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2013
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oai:doaj.org-article:6c641db5cff34cad825b14fb1cc40c122021-11-18T08:46:53ZDevelopment of methods for cross-sectional HIV incidence estimation in a large, community randomized trial.1932-620310.1371/journal.pone.0078818https://doaj.org/article/6c641db5cff34cad825b14fb1cc40c122013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24236054/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>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.<h4>Methods and findings</h4>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.<h4>Conclusions</h4>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.Oliver LaeyendeckerMichal KulichDeborah DonnellArnošt KomárekMarek OmelkaCaroline E MullisGreg SzekeresEstelle Piwowar-ManningAgnes FiammaRonald H GrayTom LutaloCharles S MorrisonRobert A SalataTsungai ChipatoConnie CelumErin M KahleTaha E TahaNewton I KumwendaQuarraisha Abdool KarimVivek NaranbhaiJairam R LingappaMichael D SweatThomas CoatesSusan H EshlemanPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 11, p e78818 (2013) |
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Medicine R Science Q |
| spellingShingle |
Medicine R Science Q Oliver Laeyendecker Michal Kulich Deborah Donnell Arnošt Komárek Marek Omelka Caroline E Mullis Greg Szekeres Estelle Piwowar-Manning Agnes Fiamma Ronald H Gray Tom Lutalo Charles S Morrison Robert A Salata Tsungai Chipato Connie Celum Erin M Kahle Taha E Taha Newton I Kumwenda Quarraisha Abdool Karim Vivek Naranbhai Jairam R Lingappa Michael D Sweat Thomas Coates Susan H Eshleman Development of methods for cross-sectional HIV incidence estimation in a large, community randomized trial. |
| description |
<h4>Background</h4>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.<h4>Methods and findings</h4>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.<h4>Conclusions</h4>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. |
| format |
article |
| author |
Oliver Laeyendecker Michal Kulich Deborah Donnell Arnošt Komárek Marek Omelka Caroline E Mullis Greg Szekeres Estelle Piwowar-Manning Agnes Fiamma Ronald H Gray Tom Lutalo Charles S Morrison Robert A Salata Tsungai Chipato Connie Celum Erin M Kahle Taha E Taha Newton I Kumwenda Quarraisha Abdool Karim Vivek Naranbhai Jairam R Lingappa Michael D Sweat Thomas Coates Susan H Eshleman |
| author_facet |
Oliver Laeyendecker Michal Kulich Deborah Donnell Arnošt Komárek Marek Omelka Caroline E Mullis Greg Szekeres Estelle Piwowar-Manning Agnes Fiamma Ronald H Gray Tom Lutalo Charles S Morrison Robert A Salata Tsungai Chipato Connie Celum Erin M Kahle Taha E Taha Newton I Kumwenda Quarraisha Abdool Karim Vivek Naranbhai Jairam R Lingappa Michael D Sweat Thomas Coates Susan H Eshleman |
| author_sort |
Oliver Laeyendecker |
| title |
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_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_sort |
development of methods for cross-sectional hiv incidence estimation in a large, community randomized trial. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2013 |
| url |
https://doaj.org/article/6c641db5cff34cad825b14fb1cc40c12 |
| work_keys_str_mv |
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