Contact patterns among high school students.
Contact patterns among high school students.
复制标题
高中生之间的接触模式。
DOI：
10.1371/journal.pone.0107878
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Barrat A
中科院分区：
文献类型：
--
作者：
Fournet J;Barrat A
人与人之间面对面的接触有助于形成社会网络，并在确定传染病如何在人群中传播方面发挥重要作用。因此，获得在各种日常生活环境中发生的人类接触模式的准确和可靠的描述是很重要的。最近的技术进步和可穿戴传感器的发展，能够感知接近模式，使得收集数据成为可能，从而可以访问特定环境中个人的时变接触网络。在这里，我们提出并分析了两个这样的数据集描述与高时间分辨率的接触模式的学生在一所高中。我们定义了描述不同班级学生之间接触模式的接触矩阵，并展示了班级结构的重要性。我们利用这两个数据集是在连续两年的几天内在同一环境中收集的这一事实，在两个非常不同的时间尺度上进行纵向分析。我们发现接触模式在不同时期和不同年份具有高度的稳定性：接触次数和持续时间的统计分布在不同时期是相同的，我们观察到不同日期或不同年份测量的接触矩阵具有非常高的相似性。在不同的年份，每个人一天到第二天的接触率变化也是相似的。我们讨论了当前分析和数据集对各个领域的兴趣，包括社会科学，以便更好地理解和模拟不同背景下的人类行为和相互作用，以及流行病学，以便为描述传染病传播的模型提供信息并设计有针对性的遏制策略。
Face-to-face contacts between individuals contribute to shape social networks and play an important role in determining how infectious diseases can spread within a population. It is thus important to obtain accurate and reliable descriptions of human contact patterns occurring in various day-to-day life contexts. Recent technological advances and the development of wearable sensors able to sense proximity patterns have made it possible to gather data giving access to time-varying contact networks of individuals in specific environments. Here we present and analyze two such data sets describing with high temporal resolution the contact patterns of students in a high school. We define contact matrices describing the contact patterns between students of different classes and show the importance of the class structure. We take advantage of the fact that the two data sets were collected in the same setting during several days in two successive years to perform a longitudinal analysis on two very different timescales. We show the high stability of the contact patterns across days and across years: the statistical distributions of numbers and durations of contacts are the same in different periods, and we observe a very high similarity of the contact matrices measured in different days or different years. The rate of change of the contacts of each individual from one day to the next is also similar in different years. We discuss the interest of the present analysis and data sets for various fields, including in social sciences in order to better understand and model human behavior and interactions in different contexts, and in epidemiology in order to inform models describing the spread of infectious diseases and design targeted containment strategies.
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DOI：
10.1098/rspb.2013.1037
发表时间：
2013-08-22
期刊：
Proceedings. Biological sciences
影响因子：
--
作者：
Danon L;Read JM;House TA;Vernon MC;Keeling MJ
通讯作者：
Keeling MJ
影响因子：
4.3
作者：
Iozzi F;Trusiano F;Chinazzi M;Billari FC;Zagheni E;Merler S;Ajelli M;Del Fava E;Manfredi P
通讯作者：
Manfredi P
影响因子：
3.8
作者：
Melegaro, Alessia;Jit, Mark;Edmunds, W. John
通讯作者：
Edmunds, W. John
DOI：
10.1098/rspb.1997.0131
发表时间：
1997-07-22
影响因子：
4.7
作者：
Edmunds, WJ;OCallaghan, CJ;Nokes, DJ
通讯作者：
Nokes, DJ
影响因子：
6.4
作者：
Hornbeck, Thomas;Naylor, David;Polgreen, Philip M.
通讯作者：
Polgreen, Philip M.