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Development of Methods for Cross-Sectional HIV Incidence Estimation in a Large, Community Randomized Trial
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Details:
  • Pubmed ID:
    24236054
  • Pubmed Central ID:
    PMC3827276
  • Funding:
    5D43TW00010/TW/FIC NIH HHS/United States
    K08 AI0744248/AI/NIAID NIH HHS/United States
    K22 AI092150-01/AI/NIAID NIH HHS/United States
    N01-HD-0-3310/HD/NICHD NIH HHS/United States
    P30 A127757/PHS HHS/United States
    R01 A134265/PHS HHS/United States
    R01 A134826/PHS HHS/United States
    R01 AI095068/AI/NIAID NIH HHS/United States
    R01 HD 050180/HD/NICHD NIH HHS/United States
    R01-AI095068/AI/NIAID NIH HHS/United States
    U01 AI46749/AI/NIAID NIH HHS/United States
    U01 AI52054/AI/NIAID NIH HHS/United States
    U01AI068613/UM1AI068613/AI/NIAID NIH HHS/United States
    U01AI068617/UM1AI068617/AI/NIAID NIH HHS/United States
    U01AI068619/UM1AI068619/AI/NIAID NIH HHS/United States
    U01MH066687/MH/NIMH NIH HHS/United States
    U01MH066688/MH/NIMH NIH HHS/United States
    U01MH066701/MH/NIMH NIH HHS/United States
    U01MH066702/MH/NIMH NIH HHS/United States
    U50 PS022061-05/PS/NCHHSTP CDC HHS/United States
    U50/CC0222061/CC/ODCDC CDC HHS/United States
  • Document Type:
  • Collection(s):
  • 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.