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从横截面病毒负荷分布估计流行病学动态
作者:小柯机器人 发布时间:2021/6/6 15:39:31

美国哈佛 T.H.陈公共卫生学院Michael J. Mina、Lee Kennedy-Shaffer和James A. Hay研究组合作取得最新进展。他们从横断面对流行病学动态病毒负荷分布进行估计。2021年6月3日出版的《科学》杂志发表了这一研究成果。

他们表明,在随机或基于症状的监测下观察到的病毒负荷群体分布,以从逆转录定量聚合酶链反应测试中获得的循环阈值 (Ct)的形式,在流行期间发生变化。因此,即使是有限数量的随机样本的 Ct 值也可以提供提高的流行病轨迹估计。组合来自多个此类样本的数据可提高此类估计的精度和稳健性。他们将他们的方法应用于 SARS-CoV-2 大流行期间在各种环境中进行的监测的 Ct 值,并提供替代方法来实时估计流行轨迹以进行爆发管理和响应。

据了解,估计流行病的轨迹对于制定对传染病的公共卫生反应至关重要,但用于此类估计的病例数据会受到可变测试实践的混淆。

附:英文原文

Title: Estimating epidemiologic dynamics from cross-sectional viral load distributions

Author: James A. Hay, Lee Kennedy-Shaffer, Sanjat Kanjilal, Niall J. Lennon, Stacey B. Gabriel, Marc Lipsitch, Michael J. Mina

Issue&Volume: 2021/06/03

Abstract: Estimating an epidemic’s trajectory is crucial for developing public health responses to infectious diseases, but case data used for such estimation are confounded by variable testing practices. We show that the population distribution of viral loads observed under random or symptom-based surveillance, in the form of cycle threshold (Ct) values obtained from reverse-transcription quantitative polymerase chain reaction testing, changes during an epidemic. Thus, Ct values from even limited numbers of random samples can provide improved estimates of an epidemic’s trajectory. Combining data from multiple such samples improves the precision and robustness of such estimation. We apply our methods to Ct values from surveillance conducted during the SARS-CoV-2 pandemic in a variety of settings and offer alternative approaches for real-time estimates of epidemic trajectories for outbreak management and response.

DOI: 10.1126/science.abh0635

Source: https://science.sciencemag.org/content/early/2021/06/02/science.abh0635

期刊信息
Science:《科学》,创刊于1880年。隶属于美国科学促进会,最新IF:41.037