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不同的艾滋病潜伏期及其对重建人类免疫缺陷病毒流行情况和预测艾滋病发病率的影响。

Different AIDS incubation periods and their impacts on reconstructing human immunodeficiency virus epidemics and projecting AIDS incidence.

作者信息

Bacchetti P, Segal M R, Hessol N A, Jewell N P

机构信息

Department of Epidemiology and Biostatistics, University of California, San Francisco 94143-1347.

出版信息

Proc Natl Acad Sci U S A. 1993 Mar 15;90(6):2194-6. doi: 10.1073/pnas.90.6.2194.

Abstract

The objective of this study was to investigate heterogeneity in incubation distributions in different cohorts and to assess the sensitivity of back-calculated infection rates to different assumptions about incubation times from human immunodeficiency virus (HIV) infection to AIDS diagnosis. Incubation distributions were estimated by using data from three different cohort studies. These and one other published incubation model were used as inputs for a back-calculation procedure that reconstructed smooth HIV-infection rates from AIDS incidence among adults in the United States, allowing for changes over time in incubation. Incubation estimates from the different cohorts differed substantially. The cumulative HIV incidence estimates that result from using the different incubations are very different, but the back-calculated models all produce good fits to the observed diagnosis counts. We conclude that systematic differences in incubation times of different groups add substantially to the uncertainty inherent in using the back-calculation method to reconstruct HIV epidemics and project future numbers of AIDS cases.

摘要

本研究的目的是调查不同队列中潜伏期分布的异质性,并评估反向推算的感染率对从人类免疫缺陷病毒(HIV)感染到艾滋病诊断的不同潜伏期假设的敏感性。通过使用来自三项不同队列研究的数据来估计潜伏期分布。这些数据以及另一个已发表的潜伏期模型被用作反向推算程序的输入,该程序根据美国成年人中的艾滋病发病率重建平滑的HIV感染率,同时考虑潜伏期随时间的变化。不同队列的潜伏期估计值存在很大差异。使用不同潜伏期得出的累积HIV发病率估计值非常不同,但反向推算模型对观察到的诊断计数都有很好的拟合度。我们得出结论,不同群体潜伏期的系统差异极大地增加了使用反向推算方法重建HIV流行情况和预测未来艾滋病病例数时固有的不确定性。

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Uncertainty of AIDS incubation time and its effects on back-calculation estimates.艾滋病潜伏期的不确定性及其对回溯推算估计值的影响。
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Using AIDS mortality data to reconstruct HIV/AIDS epidemics.利用艾滋病死亡率数据重建艾滋病毒/艾滋病疫情。
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