期刊
JOURNAL OF INFECTIOUS DISEASES
卷 214, 期 3, 页码 344-352出版社
OXFORD UNIV PRESS INC
DOI: 10.1093/infdis/jiw005
关键词
HCV; HIV; surveillance; recent infection; antibody response; incidence testing; people who inject drugs
资金
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health (NIH)
- NIH [T32DA007292, U19 AI088791, R01AI108403, R01AI077757, R01DA12568, R37DA013806, U01DA036297, UM1-AI068613]
Background. Sensitive methods are needed to estimate the population-level incidence of hepatitis C virus (HCV) infection. Methods. We developed an HCV immunoglobulin G (IgG) antibody avidity assay by modifying the Ortho 3.0 HCV enzyme-linked immunoassay and tested 997 serum or plasma samples from 568 people who inject drugs enrolled in prospective cohort studies. Avidity-based testing algorithms were evaluated by their (1) mean duration of recent infection (MDRI), defined as the average time an individual is identified as having been recently infected, according to a given algorithm; (2) false-recent rate, defined as the proportion of samples collected >2 years after HCV seroconversion that were misclassified as recent; (3) sample sizes needed to estimate incidence; and (4) power to detect a reduction in incidence between serial cross-sectional surveys. Results. A multiassay algorithm (defined as an avidity index of <30%, followed by HCV viremia detection) had an MDRI of 147 days (95% confidence interval [CI], 125-195 days), and the false-recent rates were 0.7% (95% CI,.2%-1.8%) and 7.6% (95% CI, 4.2%-12.3%) among human immunodeficiency virus (HIV)-negative and HIV-positive persons, respectively. In various simulated high-risk populations, this algorithm required <1000 individuals to estimate incidence (relative standard error, 30%) and had >80% power to detect a 50% reduction in incidence. Conclusions. Avidity-based algorithms have the capacity to accurately estimate HCV infection incidence and rapidly assess the impact of public health efforts among high-risk populations. Efforts to optimize this method should be prioritized.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据