Kim Andrea A, McDougal John S, Hargrove John, Rehle Thomas, Pillay-Van Wyk Victoria, Puren Adrian, Ekra Alexandre, Borget-Alloue Marie-Yolande, Adje-Toure Christiane, Abdullahi Ahmed Sheikh, Odawo Linus, Marum Lawrence, Parekh Bharat S
Global AIDS Program, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia 30333, USA.
AIDS Res Hum Retroviruses. 2010 Oct;26(10):1051-61. doi: 10.1089/aid.2009.0218. Epub 2010 Sep 19.
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.
用于估计HIV-1发病率的血清学检测容易出现错误分类，从而限制了发病率估计的准确性。已开发并推荐了调整因子，用于在横断面研究中估计基于检测的HIV-1发病率。我们评估了推荐的调整因子在撒哈拉以南非洲三个国家的全国性HIV调查中估计发病率的性能。将BED捕获酶免疫测定法应用于来自以下人群的储存血液标本：（1）1998 - 2004年在科特迪瓦产前诊所就诊的15 - 49岁孕妇；（2）2003年参与肯尼亚人口健康调查的15 - 49岁成年人；（3）2005年参与南非全国家庭血清学调查的15 - 49岁成年人。使用推荐的调整因子对检测得出的发病率估计值进行错误分类校正，并在可能的情况下，将其与相同人群中数学建模得出的发病率进行比较。将HIV流行趋势与检测得出的发病率趋势进行比较，以评估检测得出的趋势的合理性。未调整的发病率在科特迪瓦为3.8% [95%置信区间（CI）3.3 - 4.5] 在肯尼亚为3.5%（2.7 - 4.3），在南非为4.4%（CI 2.3 - 6.5]）。调整后的发病率在科特迪瓦为2.9%（CI 2.1 - 3.7），在肯尼亚为2.6%（CI 2.0 - 3.2），在南非为2.4%（CI 1.7 - 3.1）。调整后，科特迪瓦和南非的发病率高峰从年龄较大的人群转移到了年龄较小的人群。在肯尼亚，建模得出的HIV发病率为1.0%（CI 1.02 - 1.08），在南非为2.0%（CI 1.7 - 2.4）。在应用推荐的调整因子后，在评估的三个人群中，有两个群体经调整的检测得出的估计值仍然高得不合理。为了更准确地测量检测得出的人群发病率，调整因子必须在当地得出并进行验证。在有改进的检测方法之前，在使用和解释发病率检测数据时应谨慎。
