Determination of mean recency period for estimation of HIV type 1 Incidence with the BED-capture EIA in persons infected with diverse subtypes

AIDS Res Hum Retroviruses. 2011 Mar;27(3):265-73. doi: 10.1089/aid.2010.0159. Epub 2010 Oct 18.


The IgG capture BED enzyme immunoassay (BED-CEIA) was developed to detect recent HIV-1 infection for the estimation of HIV-1 incidence from cross-sectional specimens. The mean time interval between seroconversion and reaching a specified assay cutoff value [referred to here as the mean recency period (ω)], an important parameter for incidence estimation, is determined for some HIV-1 subtypes, but testing in more cohorts and new statistical methods suggest the need for a revised estimation of ω in different subtypes. A total of 2927 longitudinal specimens from 756 persons with incident HIV infections who had been enrolled in 17 cohort studies was tested by the BED-CEIA. The ω was determined using two statistical approaches: (1) linear mixed effects regression (ω(1)) and (2) a nonparametric survival method (ω(2)). Recency periods varied among individuals and by population. At an OD-n cutoff of 0.8, ω(1) was 176 days (95% CL 164-188 days) whereas ω(2) was 162 days (95% CL 152-172 days) when using a comparable subset of specimens (13 cohorts). When method 2 was applied to all available data (17 cohorts), ω(2) ranged from 127 days (Thai AE) to 236 days (subtypes AG, AD) with an overall ω(2) of 197 days (95% CL 173-220). About 70% of individuals reached a threshold OD-n of 0.8 by 197 days (mean ω) and 95% of people reached 0.8 OD-n by 480 days. The determination of ω with more data and new methodology suggests that ω of the BED-CEIA varies between different subtypes and/or populations. These estimates for ω may affect incidence estimates in various studies.

MeSH terms

  • AIDS Serodiagnosis / methods
  • Cohort Studies
  • HIV Antibodies*
  • HIV Infections* / classification
  • HIV Infections* / diagnosis
  • HIV Infections* / epidemiology
  • HIV Seropositivity*
  • HIV-1 / classification
  • HIV-1 / immunology*
  • Humans
  • Immunoenzyme Techniques
  • Immunoglobulin G / blood
  • Time Factors


  • HIV Antibodies
  • Immunoglobulin G