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Contact among Utah School-aged Populations (CUSP)

Contact among Utah School-aged Populations (CUSP)
犹他州学龄人口之间的接触 (CUSP)
批准号:
8238950
负责人:
MATTHEW H SAMORE
金额:
$70.0万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-08-31 至 2013-08-30

项目摘要

项目成果

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中文摘要
翻译
描述(由申请人提供):本研究的目的是使用主观和客观定量评估,描述和量化犹他州社区环境中学龄儿童(K-12)在一年内的特定年龄个体社会接触和混合模式。收集这些数据的目的是提高接触率估计和传染病传播模型参数化的精度和准确性,以支持疾病预防和控制策略的制定。 研究产生的数据将以个人接触数据、社会接触和混合数据的形式出现,并用于接触矩阵和网络。这些信息将被收集、处理、比较以评估一致性,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、俱乐部会议和体育活动。选择这些学校是为了代表犹他州的人口和气候变化,包括农村分层,平均季节温度,人口密度,种族,社会经济地位和学校的自然集水区。该研究小组包括与学校,统计,地理信息系统,流行病学和公共卫生合作的专业知识。 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、自我日记和接近传感器。使用主观调查和自我日记是标准做法,但我们将在更广泛的人群中部署更多的调查。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。在为快速使用传感器做好最少的准备之后,我们将继续开发传感器技术,以减少可测量的距离。开发将保留两种测量类型,以便在整个过程中提供可比数据,并对新测量进行有效比较。该研究团队包括无线传感器网络方面的专业知识,并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数量的情况。最佳的网络抽样策略将沿着网络属性的估计和接触的预测。研究团队包括样本设计和网络图方面的专业知识。 最后,该研究包括一项计划,在流感样疾病急性爆发的情况下,收集流感特异性RT-PCR检测结果和研究参与者子集的干预信息。研究团队具有儿科呼吸系统疾病监测方面的专业知识。
英文摘要
DESCRIPTION (provided by applicant): 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.
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Modeling and Simulation to Support Epidemiological Decision-Making in Healthcare Settings
  • 批准号:
    10800785
  • 项目类别:
  • 资助金额:
    $60.0万
  • 财政年份:
    2020
  • 负责人:
    MATTHEW H SAMORE
  • 依托单位:
Modeling and Simulation to Support Epidemiological Decision-Making in Healthcare Settings
  • 批准号:
    10462461
  • 项目类别:
  • 资助金额:
    $60.0万
  • 财政年份:
    2020
  • 负责人:
    MATTHEW H SAMORE
  • 依托单位:
Modeling and Simulation to Support Epidemiological Decision-Making in Healthcare Settings
  • 批准号:
    10220770
  • 项目类别:
  • 资助金额:
    $120.0万
  • 财政年份:
    2020
  • 负责人:
    MATTHEW H SAMORE
  • 依托单位:
Modeling and Simulation to Support Antibiotic Stewardship and Epidemiological Decision-Making in Healthcare Settings
  • 批准号:
    9420334
  • 项目类别:
  • 资助金额:
    $65.0万
  • 财政年份:
    2017
  • 负责人:
    MATTHEW H SAMORE
  • 依托单位:
海外基金