Comparison of HIV type 1 incidence observed during longitudinal follow-up with incidence estimated by cross-sectional analysis using the BED capture enzyme immunoassay

AIDS Res Hum Retroviruses. 2006 Oct;22(10):945-52. doi: 10.1089/aid.2006.22.945.


The BED capture enzyme immunoassay (BED CEIA) for recent infection was developed for the estimation of HIV-1 incidence in a population from a single cross-sectional survey. To evaluate performance, we applied the assay to specimen sets obtained from a longitudinal cohort study, the AIDSVAX B/B vaccine trial, in which there was an independent and conventional measure of observed incidence. The BED CEIA was performed on specimens obtained during follow-up for seroconversion conducted every 6 months for 3 years. There was excellent agreement between the observed and BED-estimated incidence for all the intervals. The cumulative, annualized incidence observed in the cohort was 3.10 new infections per 100 person-years (95% CI, 2.57-3.63). The corresponding BED-estimated incidence was 2.91 (2.30-3.53). We also estimated the effect of varied prevalence on a fixed incidence. Because some specimens from persons with longer-term infection are classified as recent by the assay, this can inflate the incidence estimate. We quantify this effect and discuss potential mitigation by excluding certain specimens on clinical grounds, by relying on trend differences rather than absolute incidence estimates, by secondary confirmatory testing, or by analytic adjustments for misclassification. Cross-sectional HIV incidence estimation circumvents many of the drawbacks associated with longitudinal cohort studies, but there are test-specific limitations that should be considered in the design of population surveys.

Publication types

  • Comparative Study
  • Evaluation Study

MeSH terms

  • Algorithms
  • Clinical Trials, Phase III as Topic
  • Cohort Studies
  • Cross-Sectional Studies
  • Female
  • HIV Infections / epidemiology*
  • HIV Seropositivity / epidemiology
  • HIV-1 / genetics*
  • Humans
  • Immunoenzyme Techniques
  • Immunoglobulin G / analysis
  • Incidence
  • Male


  • Immunoglobulin G