摘要翻译：
目前检测传染病爆发的方法充其量只能提供关于流行病进程的同期信息。平均而言，处于社交网络中心的个人可能比处于边缘的人更早被感染。然而，绘制整个网络以确定要监视的中心个人通常是非常困难的。我们提出了一种不需要确定全局网络结构的替代策略，即监控随机选择的个体的朋友。众所周知，这样的人更集中。为了评估这样一个朋友小组是否真的能提供早期检测，我们研究了2009年末哈佛大学爆发的一次流感。我们跟踪了744名学生，分为随机组和朋友组。根据临床诊断，朋友组的疫情进展比随机选择的组（即整体人群）提前14.7天(95%C.I.11.7-17.6)。朋友组在疫情的第16天也显示出显著的提前时间(P<0.05)，比整体人群的日发病率高峰提前了整整46天。这种传感器方法可以提供大量额外的时间来对监测下的小规模或大规模人群中的流行病做出反应。此外，该方法原则上可以推广到在网络中传播的其他生物、心理、信息或行为传染病。
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英文标题：
《Social Network Sensors for Early Detection of Contagious Outbreaks》
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作者：
Nicholas A. Christakis, James H. Fowler
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最新提交年份：
2010
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分类信息：

一级分类：Physics        物理学
二级分类：Physics and Society        物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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一级分类：Quantitative Biology        数量生物学
二级分类：Other Quantitative Biology        其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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英文摘要：
  Current methods for the detection of contagious outbreaks give contemporaneous information about the course of an epidemic at best. Individuals at the center of a social network are likely to be infected sooner, on average, than those at the periphery. However, mapping a whole network to identify central individuals whom to monitor is typically very difficult. We propose an alternative strategy that does not require ascertainment of global network structure, namely, monitoring the friends of randomly selected individuals. Such individuals are known to be more central. To evaluate whether such a friend group could indeed provide early detection, we studied a flu outbreak at Harvard College in late 2009. We followed 744 students divided between a random group and a friend group. Based on clinical diagnoses, the progression of the epidemic in the friend group occurred 14.7 days (95% C.I. 11.7-17.6) in advance of the randomly chosen group (i.e., the population as a whole). The friend group also showed a significant lead time (p<0.05) on day 16 of the epidemic, a full 46 days before the peak in daily incidence in the population as a whole. This sensor method could provide significant additional time to react to epidemics in small or large populations under surveillance. Moreover, the method could in principle be generalized to other biological, psychological, informational, or behavioral contagions that spread in networks.
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PDF链接：
https://arxiv.org/pdf/1004.4792