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量化行为和传播集群之间相互作用的方法。

An Approach to Quantifying the Interaction between Behavioral and Transmission Clusters.

机构信息

Department of Infectious Diseases, Bern University Hospital Inselspital, University of Bern, 3010 Bern, Switzerland.

Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland.

出版信息

Viruses. 2022 Apr 10;14(4):784. doi: 10.3390/v14040784.

Abstract

We hypothesize that patterns of sexual behavior play a role in the conformation of transmission networks, i.e., the way you behave might influence whom you have sex with. If that was the case, behavioral grouping might in turn correlate with, and potentially predict transmission networking, e.g., proximity in a viral phylogeny. We rigorously present an intuitive approach to address this hypothesis by quantifying mapped interactions between groups defined by similarities in sexual behavior along a virus phylogeny while discussing power and sample size considerations. Data from the Swiss HIV Cohort Study on condom use and hepatitis C virus (HCV) sequences served as proof-of-concept. In this case, a strict inclusion criteria contrasting with low HCV prevalence hindered our possibilities to identify significant relationships. This manuscript serves as guide for studies aimed at characterizing interactions between behavioral patterns and transmission networks. Large transmission networks such as those of HIV or COVID-19 are prime candidates for applying this methodological approach.

摘要

我们假设性行为模式在传播网络的形成中发挥作用,即你的行为方式可能会影响你与谁发生性行为。如果是这样的话,行为分组可能反过来与传播网络相关,并可能预测传播网络,例如病毒系统发育中的接近程度。我们通过沿着病毒系统发育量化通过性行为相似性定义的群组之间的映射交互作用,严格地提出了一种直观的方法来解决这个假设,同时讨论了功效和样本量的考虑因素。来自瑞士艾滋病毒队列研究的数据用于检测避孕套使用和丙型肝炎病毒 (HCV) 序列,作为概念验证。在这种情况下,严格的纳入标准与 HCV 低流行率形成鲜明对比,这限制了我们识别显著关系的可能性。本文旨在为描述行为模式和传播网络之间的相互作用的研究提供指导。HIV 或 COVID-19 等大型传播网络是应用这种方法的主要候选者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1de/9032082/ea2cb334b022/viruses-14-00784-g001.jpg

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