ESTIMATION OF CURRENT HUMAN-IMMUNODEFICIENCY-VIRUS INCIDENCE RATES FROM A CROSS-SECTIONAL SURVEY USING EARLY DIAGNOSTIC-TESTS

ESTIMATION OF CURRENT HUMAN-IMMUNODEFICIENCY-VIRUS INCIDENCE RATES FROM A CROSS-SECTIONAL SURVEY USING EARLY DIAGNOSTIC-TESTS
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DOI:
10.1093/oxfordjournals.aje.a117404
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发表时间:
1995-01-15
影响因子:
5
通讯作者:
QUINN, TC
QUINN, TC
中科院分区:
医学2区
文献类型:
--
作者:
BROOKMEYER, R;QUINN, TC

文献摘要

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与获得性免疫缺陷综合症发病率和人类免疫缺陷病毒(HIV)血清流行率有关的大量全球流行病学数据形成鲜明对比的是,有关当前艾滋病毒发病率水平的信息相对较少。作者提出了一种基于单一横断面调查和流行病学模型来估计当前 HIV 发病率的新方法,该方法基于 HIV p24 抗原的诊断测试,以识别处于抗体前或窗口期(暴露于 HIV 和出现可检测到的 HIV 抗体之间的时间)的个体。 抗体前期相对较短,作者报告了 HIV 血清转化前 p24 抗原血症持续时间的数据。该持续时间与从横断面调查中获得的 p24 抗原血症的流行率一起用于流行病学模型中,以估计当前的发病率。这种估计发病率的方法可能对发展中国家和高危人群尤其有用,因为在这些国家和高危人群中,很难跟踪队列来识别血清转化者,并且在设计疫苗效力研究时,其中当前的发病率对于计算样本量至关重要。
In sharp contrast to the considerable worldwide epidemiologic data available on acquired immunodeficiency syndrome incidence and human immunodeficiency virus (HIV) seroprevalence, there is relatively little information about current levels of HIV incidence rates. The authors suggest a novel approach for estimating current HIV incidence rates based on a single cross-sectional survey and on an epidemiologic model, The approach is based on diagnostic tests for HIV p24 antigen to identify individuals in the preantibody or window period (time between exposure to HIV and appearance of detectable HIV antibodies), Individuals in the preantibody period are likely to have been infected very recently because the duration of the preantibody period is relatively short, The authors report data on the duration of p24 antigenemia prior to HIV seroconversion. This duration together with the prevalence of p24 antigenemia obtained from a cross-sectional survey are used in an epidemiologic model to estimate current incidence rates, This approach of estimating incidence rates may be especially useful in developing countries and high-risk populations in which it is difficult to follow cohorts to identify seroconverters, and in the design of vaccine efficacy studies in which current incidence rates are crucial for calculating sample sizes.