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Improved HIV-1 incidence estimates using the BED capture enzyme immunoassay

Hargrove, John Wa,f; Humphrey, Jean Ha,c; Mutasa, Kudaa; Parekh, Bharat Sd; McDougal, J Steved; Ntozini, Roberta; Chidawanyika, Henrya; Moulton, Lawrence Hc; Ward, Briane; Nathoo, Kusumb; Iliff, Peter Ja; Kopp, Ekkehardf

doi: 10.1097/QAD.0b013e3282f2a960
Epidemiology and Social

Objective: To validate the BED capture enzyme immunoassay for HIV-1 subtype C and to derive adjustments facilitating estimation of HIV-1 incidence from cross-sectional surveys.

Design: Laboratory analysis of archived plasma samples collected in Zimbabwe.

Methods: Serial plasma samples from 85 women who seroconverted to HIV-1 during the postpartum year were assayed by BED and used to estimate the window period between seroconversion and the attainment of a specified BED absorbance. HIV-1 incidences for the year prior to recruitment and for the postpartum year were calculated by applying the BED technique to HIV-1-positive samples collected at baseline and at 12 months.

Results: The mean window for an absorbance cut-off of 0.8 was 187 days. Among women who were HIV-1 positive at baseline and retested at 12 months, a proportion (&epsiv;) 5.2% (142/2749) had a BED absorbance < 0.8 at 12 months and were falsely identified as recent seroconverters. Consequently, the estimated BED annual incidence at 12 months postpartum (7.6%) was 2.2 times the contemporary prospective estimate. BED incidence adjusted for &epsiv; was 3.5% [95% confidence interval (CI), 2.6–4.5], close to the 3.4% estimated prospectively. Adjusted BED incidence at baseline was 6.0% (95% CI, 5.2–6.9) and, like the prospective estimates, declined with maternal age. Unadjusted BED incidence estimates were largely independent of age; the pooled estimate was 58% higher than adjusted incidence.

Conclusion: The BED method can be used in an African setting, but further estimates of &epsiv; and of the window period are required, using large samples in a variety of circumstances, before its general utility can be gauged.

From the aZVITAMBO Project

bUniversity of Zimbabwe Faculties of Medicine and Science, Harare, Zimbabwe

cJohns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA

dCenters for Disease Control and Prevention, Atlanta, Georgia, USA

eResearch Institute of the Montreal General Hospital, Montreal, Quebec, Canada

fDST/NRF Centre of Excellence in Epidemiological Modelling and Analysis, SACEMA, Stellenbosch, South Africa.

Received 2 March, 2007

Revised 12 July, 2007

Accepted 18 July, 2007

Correspondence to Dr J. Humphrey, ZVITAMBO, 1 Borrowdale Road, Borrowdale, Harare, Zimbabwe. E-mail:

© 2008 Lippincott Williams & Wilkins, Inc.