RAPID: Structure of Contact Networks and the Spread of Flu-like Infectious Diseases: Implications for Dynamics and Control

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。斯坦福大学的人类学家詹姆斯·霍兰德·琼斯博士和遗传学家马库斯·费尔德曼博士将使用无线传感器网络（WSN）技术来识别学校环境中典型日子的时间网络动态。了解自由形成的群体的结构以及它与整个社会结构的关系仍然是社会科学的一个重大挑战。本项目收集的数据将大大有助于提高这一认识。这些数据还将有助于在真实世界的接触网络上模拟疾病和流行病动态，由于缺乏适当的数据，这在以前从未做过。这样的动态模型将使测试不同的控制方案成为可能，以防止流感样疾病在学校的传播。参与者将有小型无线传感器连接到他们;这些传感器发送和接收无线电信号，并从附近的其他传感器。这项技术将使研究人员能够以无与伦比的精度收集动态接触网络数据。与此相反，传统的群体身份自我报告显示出明显的回忆偏差。基于收集的数据，研究人员将采用和扩展小群体形成和随机网络演化的经典理论。除了对社会科学理论做出贡献外，该项目还具有重要的政策意义，因为社会结构及其形成过程是传染性病原体传播和控制的基本特征。鉴于社会过程对群体形成的重要性，以及新型猪源性甲型H1N1流感的出现，迫切需要接触网络数据，以了解流感传播的社会结构。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Anthropologist Dr. James Holland Jones and geneticist Dr. Marcus Feldman, both of Stanford University, will use Wireless Sensor Network (WSN) technology to identify the temporal network dynamics during typical days in a school setting. Understanding the structure of freely-forming groups and how that relates to the overall social structure remains a major social science challenge. The data collected in this project will contribute significantly to improving this understanding. The data also will help to model disease and epidemic dynamics on real-world contact networks, which has never been done before due to the lack of appropriate data. Such dynamic modeling will make it possible to test different control scenarios to prevent the spread of flu-like diseases in schools.Participants will have small wireless sensors attached to them; these sensors send and receive radio signals to and from other sensors nearby. This technology will allow the researchers to collect dynamic contact network data with unparalleled precision. In contract, traditional self-reports of group identities show marked recall biases. Based on the collected data, the researchers will employ and extend classical theories of small group formation and stochastic network evolution. In addition to contributing to social science theory, this project has significant policy importance because social structure and the processes that underlie its formation are fundamental features of the transmission and control of infectious agents. Given the importance of social processes on group formation, and the emergence of novel swine-origin influenza A(H1N1), there is an urgent need for contact network data in order to understand the social structure through which influenza spreads.