title: Investigating the utility of the HIV-1 BED capture enzyme immunoassay using cross-sectional and longitudinal seroconverter specimens from Africa.
abstract: BACKGROUND
  The identification of populations at risk of HIV infection is a priority for trials of preventive technologies, including HIV vaccines. To quantify incidence traditionally requires laborious and expensive prospective studies.
  
  
  METHODS
  The BED IgG-Capture enzyme immunoassay (EIA) was developed to estimate HIV-1 incidence using cross-sectional data by measuring increasing levels of HIV-specific IgG as a proportion of total IgG. To evaluate this assay, we tested 189 seroconversion samples taken at 3-monthly intervals from 15 Rwandan and 26 Zambian volunteers with known time of infection and cross-sectional specimens from 617 Kenyan and Ugandan volunteers with prevalent infection.
  
  
  RESULTS
  The BED-EIA-estimated incidence in Uganda was unexpectedly high, at 6.1%/year [95% confidence interval (CI) 4.2-8.0] in Masaka and 6.0%/year (95% CI 4.3-7.7) in Kakira. Prospective incidence data in Masaka from the same population was 1.7%/year before and 1.4%/year after the study. Kenyan estimates were 3.5%/year in Kilifi (95% CI 2.1-4.9) and 3.4%/year in Nairobi (95% CI 1.5-5.3). From the Rwandan and Zambian data, the sensitivity of the assay was 81.2% and the specificity was 67.8%. After approximately one year, subjects misclassified as recently infected tended to have lower plasma viral loads compared with those not misclassified as recent (median copies/ml 14 773 versus 93 560; P = 0.02). Clinical presentation, sex and HIV subtype were not significantly associated with BED-EIA misclassification in seroconverter samples.
  
  
  CONCLUSIONS
  These data suggest that this assay does not perform reliably in all populations. Further research is warranted before using this assay to estimate incidence from prevalent HIV samples.
authors.affiliation: Projet San Francisco, Kigali, Rwanda.
authors.forename: Etienne
authors.initials: E
authors.lastname: Karita
authors.forename: Matt
authors.initials: M
authors.lastname: Price
authors.forename: Eric
authors.initials: E
authors.lastname: Hunter
authors.forename: Elwyn
authors.initials: E
authors.lastname: Chomba
authors.forename: Susan
authors.initials: S
authors.lastname: Allen
authors.forename: Lin
authors.initials: L
authors.lastname: Fei
authors.forename: Anatoli
authors.initials: A
authors.lastname: Kamali
authors.forename: Eduard J
authors.initials: EJ
authors.lastname: Sanders
authors.forename: Omu
authors.initials: O
authors.lastname: Anzala
authors.forename: Michael
authors.initials: M
authors.lastname: Katende
authors.forename: Nzeera
authors.initials: N
authors.lastname: Ketter
mesh_terms: D000293:Adolescent; D000328:Adult; D004812:Epidemiologic Methods; D015483:HIV Antibodies / Q000097:blood; D015658:HIV Infections / Q000175:diagnosis / Q000453:epidemiology*; D006679:HIV Seropositivity; D015497:HIV-1 / Q000276:immunology; D006801:Humans; D007124:Immunoenzyme Techniques / Q000379:methods; D007074:Immunoglobulin G / Q000097:blood; D008875:Middle Aged; D012432:Rwanda / Q000453:epidemiology; D019562:Viral Load; D015024:Zambia / Q000453:epidemiology
chemical_list: D015483:HIV Antibodies; D007074:Immunoglobulin G