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  • 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.
  • 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. (en)
Title
  • Development of Methods for Cross-Sectional HIV Incidence Estimation in a Large, Community Randomized Trial
  • Development of Methods for Cross-Sectional HIV Incidence Estimation in a Large, Community Randomized Trial (en)
skos:prefLabel
  • Development of Methods for Cross-Sectional HIV Incidence Estimation in a Large, Community Randomized Trial
  • Development of Methods for Cross-Sectional HIV Incidence Estimation in a Large, Community Randomized Trial (en)
skos:notation
  • RIV/00216208:11320/13:10172646!RIV14-MSM-11320___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • N
http://linked.open...iv/cisloPeriodika
  • 11
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 69157
http://linked.open...ai/riv/idVysledku
  • RIV/00216208:11320/13:10172646
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Estimation; Cross-sectional study; Incidence; HIV (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • US - Spojené státy americké
http://linked.open...ontrolniKodProRIV
  • [9DD6A18276DD]
http://linked.open...i/riv/nazevZdroje
  • PLoS ONE
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 8
http://linked.open...iv/tvurceVysledku
  • Kulich, Michal
  • Komárek, Arnošt
  • Omelka, Marek
  • Sweat, Michael
  • Donnell, Deborah
  • Fiamma, Agnes
  • Laeyendecker, Oliver
  • Piwowar-Manning, Estelle
  • Szekeres, Greg
  • Abdool Karim, Quarraisha
  • Celum, Connie
  • Chipato, Tsungai
  • Coates, Thomas
  • Eshleman, Susan
  • Gray, Ronald
  • Kahle, Erin
  • Kumwenda, Newton
  • Lingappa, Jairam
  • Lutalo, Tom
  • Morrison, Charles
  • Mullis, Caroline
  • Naranbhai, Vivek
  • Salata, Robert
  • Taha, Taha
http://linked.open...ain/vavai/riv/wos
  • 000327254700051
issn
  • 1932-6203
number of pages
http://bibframe.org/vocab/doi
  • 10.1371/journal.pone.0078818
http://localhost/t...ganizacniJednotka
  • 11320
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