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特定年龄组艾滋病毒发病率的反向推算模型。

Backcalculation models of age-specific HIV incidence rates.

作者信息

Rosenberg P S

机构信息

National Cancer Institute, Epidemiologic Methods Section, Rockville, Maryland 20892.

出版信息

Stat Med. 1994;13(19-20):1975-90. doi: 10.1002/sim.4780131909.

Abstract

This paper extends the use of backcalculation to estimate past incidence of HIV infection in different age groups from age-specific counts of AIDS incidence. The approach is flexible and allows the distribution of age at HIV infection to change over time. In this new approach, the incubation distributions used to backcalculate HIV infection rates depend on the age at HIV infection, because younger age is associated with slower progression. The effect of age on progression is estimated from a joint analysis of natural history data from several cohort studies of gay and bisexual men. As in previous applications, the incubation distributions also change over time to accommodate treatment effects and the 1987 revision of the surveillance definition. The method is applied to AIDS incidence data for the United States population. Estimated infection incidence for the entire population declined from peak levels seen in the mid-1980s. However, persons under age 25 years have accounted for an increasing proportion of new HIV infections as the epidemic has progressed. Quantitative estimates were sensitive to the assumed incubation distribution, but the trend toward younger age at HIV infection was apparent using several models of the incubation distribution. Although the models are computationally intensive, they provide useful information about seroincidence trends in different age groups.

摘要

本文扩展了反向推算的应用,以便根据特定年龄组的艾滋病发病率计数来估计不同年龄组过去的艾滋病毒感染发病率。该方法具有灵活性,允许艾滋病毒感染时的年龄分布随时间变化。在这种新方法中,用于反向推算艾滋病毒感染率的潜伏期分布取决于艾滋病毒感染时的年龄,因为年龄较小与病情进展较慢相关。年龄对病情进展的影响是通过对来自几项男同性恋和双性恋男性队列研究的自然史数据进行联合分析来估计的。与之前的应用一样,潜伏期分布也会随时间变化,以适应治疗效果和1987年监测定义的修订。该方法应用于美国人群的艾滋病发病率数据。整个人口的估计感染发病率从20世纪80年代中期的峰值水平下降。然而,随着疫情的发展,25岁以下人群在新感染艾滋病毒者中所占比例不断增加。定量估计对假定的潜伏期分布很敏感,但使用几种潜伏期分布模型时,艾滋病毒感染年龄趋于年轻化的趋势很明显。尽管这些模型计算量很大,但它们提供了有关不同年龄组血清发病率趋势的有用信息。

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