Evaluating the BED capture enzyme immunoassay to estimate HIV incidence among adults in three countries in sub-Saharan Africa.
Serological assays for estimating HIV-1 incidence are prone to misclassification, limiting the accuracy of the incidence estimate. Adjustment factors have been developed and recommended for estimating assay-based HIV-1 incidence in cross-sectional settings. We evaluated the performance of the recommended adjustment factors for estimating incidence in national HIV surveys in three countries in sub-Saharan Africa. The BED-capture enzyme immunoassay was applied to stored blood specimens from (1) pregnant women aged 15-49 years attending antenatal clinics in Côte d'Ivoire (1998-2004), (2) adults aged 15-49 years participating in a demographic health survey in Kenya (2003), and (3) adults aged 15-49 years participating in a national household serosurvey in South Africa (2005). Assay-derived incidence estimates were corrected for misclassification using recommended adjustment factors and, where possible, were compared to mathematically modeled incidence in the same populations. Trends in HIV prevalence were compared to trends in assay-derived incidence to assess plausibility in the assay-derived trends. Unadjusted incidence was 3.8% [95% confidence interval (CI) 3.3-4.5] in Côte d'Ivoire, 3.5% (2.7-4.3) in Kenya, and 4.4% (CI 2.3-6.5]) in South Africa. Adjusted incidence was 2.9% (CI 2.1-3.7) in Côte d'Ivoire, 2.6% (CI 2.0-3.2) in Kenya, and 2.4% (CI 1.7-3.1) in South Africa. After adjustment, peak incidence shifted from older to younger age groups in Côte d'Ivoire and South Africa. Modeled HIV incidence was 1.0% (CI 1.02-1.08) in Kenya and 2.0% (CI 1.7-2.4) in South Africa. After applying the recommended adjustments factors, adjusted assay-derived estimates remained implausibly high in two of three populations evaluated. For more accurate measures of assay-derived population incidence, adjustment factors must be locally derived and validated. Until improved assays are available, caution should be applied in the use and interpretation of data from incidence assays.
Kim
Andrea A
AA
Global AIDS Program, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia 30333, USA. aakim@cdc.gov
McDougal
John S
JS
Hargrove
John
J
Rehle
Thomas
T
Pillay-Van Wyk
Victoria
V
Puren
Adrian
A
Ekra
Alexandre
A
Borget-Alloue
Marie-Yolande
MY
Adje-Toure
Christiane
C
Abdullahi
Ahmed Sheikh
AS
Odawo
Linus
L
Marum
Lawrence
L
Parekh
Bharat S
BS
D015492:AIDS Serodiagnosis; D000293:Adolescent; D000328:Adult; D007560:Cote d'Ivoire / Q000453:epidemiology; D003430:Cross-Sectional Studies; D005260:Female; D015658:HIV Infections / Q000453:epidemiology*; D015528:HIV Seroprevalence / Q000639:trends*; D006801:Humans; D007124:Immunoenzyme Techniques; D007630:Kenya / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D011159:Population Surveillance; D011247:Pregnancy; D011251:Pregnancy Complications, Infectious / Q000453:epidemiology* / Q000821:virology; D015995:Prevalence; D013019:South Africa / Q000453:epidemiology; D055815:Young Adult