Contact among Utah School-aged Populations (CUSP)

摘要本研究的目的是描述和量化特定年龄的个体社会接触， 在一年的时间里，使用以下方法，在犹他州的社区环境中混合学龄儿童（K-12）的模式 主观和客观定量评价。收集这些数据的目的是提高精度 传染病传播模型的接触率估计和参数化的准确性， 支持制定疾病预防和控制战略。 研究产生的数据将以个人联系数据、社会联系和 混合数据，并用于接触矩阵和网络。这些将被收集，处理，比较， 评估协议，并以对传染病传播模型有用的形式提供。研究 团队包括各种传输建模技术和应用的专业知识。 研究中包括的社区环境是学校、营地、家庭、俱乐部会议， 体育实践。这些学校被选择来代表犹他州的人口和气候变化 包括农村、平均季节温度、人口密度、种族、社会经济 学校的地位和自然集水区。该研究小组包括专业知识，在合作， 学校、统计学、地理信息系统、流行病学和公共卫生。 该研究将在设计中使用季节性块收集全年的接触和混合数据。 学校设置的受访者的一个子集将被招募参加在所有四个赛季。 用于收集接触和混合数据的定量评估工具是调查，自我日记， 接近传感器使用主观调查和自我日记是标准做法，但我们将在 在更广泛的人口统计中有更大的数字。研究小组包括调查设计方面的专门知识。 接近传感器的使用对于用于收集客观接触和混合模式的领域是新的。后 传感器的最小化准备，以便快速使用，我们将继续开发传感器技术，以减少 可测量的距离。开发将保留这两种测量类型，以允许比较数据 新的测量的贯穿和有效的比较。研究团队包括无线通信领域的专业知识， 传感器网络，包括我们将使用的接近传感器的开发人员。 设计策略包括设置种群大于 我们将拥有的传感器沿着网络估计，将开发最佳网络采样策略 接触的性质和预测。研究团队包括样本设计和网络图方面的专业知识。 最后，研究还包括一项收集流感特异性RT-PCR检测结果和干预措施的计划 在流感样疾病急性爆发的情况下，研究参与者子集的信息。的 研究小组具有儿科呼吸系统疾病监测专业知识。

Abstract The objective of this study is to describe and quantify age-specific individual social contact and mixing patterns of school-aged children (K-12) in Utah across community setting over a period of a year using subjective and objective quantitative assessment. The purpose for collecting these data is to improve precision and accuracy of contact rate estimation and parameterization for infectious disease transmission models to support the development of disease prevention and control strategies. The data generated from the study will be in the form of individual contact data, social contact and mixing data, and for use in contact matrices and networks. These will be collected, processed, compared to assess agreement, and made available in forms useful for infectious disease transmission models. The study team includes expertise in various transmission modeling techniques and applications. The community settings included in the study are schools, camps, households, club meetings, and sports practices. The schools are selected to represent the demographic and climatic variability of Utah including stratification for rurality, average seasonal temperature, population density, ethnicity, socioeconomic status, and natural catchment area of the school. The study team includes expertise in collaborating with schools, statistics, GIS, epidemiology, and public health. The study will collect contact and mixing data throughout the year using seasonal blocks in the design. A subset of the school setting respondents will be recruited to participate during all four seasons. The quantitative assessment tools used to collect contact and mixing data are surveys, self-diaries, and proximity sensors. Use of subjective surveys and self-diaries is standard practice but we will deploy them in greater numbers across a broad demographic. The study team includes expertise in survey design. Use of proximity sensors is new to the field for collecting objective contact and mixing patterns. After minimal preparation of sensors for use quickly, we will continue development of sensor technology to reduce the measurable distance. The development will retain both measurement types to allow for comparable data throughout and efficient comparison of the new measurement. The study team includes expertise in wireless sensor networks, and includes the developer of the proximity sensor we will use. The design strategy includes situations where the setting population is larger than the number of sensors we will have. Optimal network sampling strategies will be developed along with estimation of network properties and prediction of contacts. The study team includes expertise in sample design and network graphs. Finally, the study includes a plan to collect influenza-specific RT-PCR test results and intervention information on a subset of the study participants in the event of an acute outbreak of influenza-like illness. The study team have expertise in pediatric respiratory disease surveillance.