Guclu Hasan, Read Jonathan, Vukotich Charles J, Galloway David D, Gao Hongjiang, Rainey Jeanette J, Uzicanin Amra, Zimmer Shanta M, Cummings Derek A T
Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
Public Health Dynamics Laboratory, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
PLoS One. 2016 Mar 15;11(3):e0151139. doi: 10.1371/journal.pone.0151139. eCollection 2016.
Students attending schools play an important role in the transmission of influenza. In this study, we present a social network analysis of contacts among 1,828 students in eight different schools in urban and suburban areas in and near Pittsburgh, Pennsylvania, United States of America, including elementary, elementary-middle, middle, and high schools. We collected social contact information of students who wore wireless sensor devices that regularly recorded other devices if they are within a distance of 3 meters. We analyzed these networks to identify patterns of proximal student interactions in different classes and grades, to describe community structure within the schools, and to assess the impact of the physical environment of schools on proximal contacts. In the elementary and middle schools, we observed a high number of intra-grade and intra-classroom contacts and a relatively low number of inter-grade contacts. However, in high schools, contact networks were well connected and mixed across grades. High modularity of lower grades suggests that assumptions of homogeneous mixing in epidemic models may be inappropriate; whereas lower modularity in high schools suggests that homogenous mixing assumptions may be more acceptable in these settings. The results suggest that interventions targeting subsets of classrooms may work better in elementary schools than high schools. Our work presents quantitative measures of age-specific, school-based contacts that can be used as the basis for constructing models of the transmission of infections in schools.
在校学生在流感传播中起着重要作用。在本研究中,我们对美国宾夕法尼亚州匹兹堡市及其附近城市和郊区八所不同学校的1828名学生之间的接触情况进行了社会网络分析,这些学校包括小学、初 - 中连读学校、初中和高中。我们收集了佩戴无线传感器设备的学生的社交接触信息,这些设备会在距离3米内时定期记录其他设备。我们分析了这些网络,以确定不同班级和年级中近距离学生互动的模式,描述学校内部的社区结构,并评估学校物理环境对近距离接触的影响。在小学和初中,我们观察到同年级和教室内的接触数量较多,而跨年级的接触数量相对较少。然而,在高中,接触网络连接良好且各年级之间相互混合。低年级的高模块性表明,流行病模型中均匀混合的假设可能不合适;而高中的低模块性表明,在这些环境中均匀混合假设可能更可接受。结果表明,针对部分教室的干预措施在小学可能比在高中更有效。我们的工作提供了按年龄划分的、基于学校的接触的定量测量方法,可作为构建学校感染传播模型的基础。