Statistical Methods for Network Epidemiology

网络流行病学统计方法

• 批准号: 8462284
• 负责人: Wanda Martina MORRIS
• 金额: $ 58.95万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-05-01 至 2016-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8462284
• 关键词: AIDS prevention; Behavior Therapy; Code; Collaborations; Communication Tools; Computer software; Computers; Development; Disease; Drops; Educational workshop; Ensure; Epidemic; Epidemiology; Family; Goals; Graph; HIV; HIV/STD; Herd Immunity; High Prevalence; Imagery; Individual; Internet; Intervention; Manuals; Methodology; Methods; Modeling; Pathway Analysis; Pattern; Population; Population Sizes; Prevalence; Prevention Research; Public Health; Publishing; Research; Research Design; Research Personnel; Resources; Risk; Sampling; Science; Simulate; Social Network; Statistical Methods; Structure; Time; Training; United States; United States National Institutes of Health; Vaccinated; Vaccines; Work; base; computer program; design; experience; innovation; network models; open source; outreach; programs; public health relevance; reproductive; simulation; theories; tool; transmission process

DESCRIPTION (provided by applicant): Social network analysis has become increasingly central to the study of HIV/STI transmission dynamics and disparities. For this approach to reach its full potential, the theory and methodology must be empirically grounded. This requires a comprehensive analytic strategy that starts with a feasible plan for sampling networks, and uses a statistical framework to leverage the sample information for understanding of population level network structure and dynamics. In this project, our team seeks to build on an innovative research agenda that has developed the statistical theory, methods and programs needed to establish a principled approach to network epidemiology. We seek to extend the current methodology to support comprehensive modeling for dynamic networks. Our specific aims are to: 1. develop the statistical theory and methodology for modeling network dynamics a. Refine and extend the current ERGM approach to modeling partnership dynamics. b. Develop extensions of ERGM to handle changing population size and composition. c. Create new network visualization tools designed specifically for epidemiological applications. 2. Integrate the new methods into the stat net software for network analysis and simulation a. Develop robust code for implementing the new methods b. Develop comprehensive help functions, manuals, and tutorials c. Ensure public access by publishing the code on CRAN and exploiting internet-based tools. 3. Develop training resources for researchers from different field's a. Develop a 5 day workshop in network theory, study design, analysis, simulation and visualization. b. Develop a 2 day training workshop on using stat net for network analysis. c. Develop 1 day training workshops for interdisciplinary outreach. Our project team comprises an interdisciplinary group of individuals with a long track record of working together, deep expertise in the application of network methods to STI research and prevention, experience in capacity building, and a commitment to the development of publicly accessible software. Our goal is to advance the science of network analysis, provide innovative research tools for research in epidemiology and public health, and lower the barriers to accessing these new tools.

描述(申请人提供)：社会网络分析已成为艾滋病毒/性传播感染传播动态和差异研究的越来越重要的中心。为了使这一方法充分发挥其潜力，理论和方法必须有经验基础。这需要一个全面的分析战略，从抽样网络的可行计划开始，并使用一个统计框架来利用样本信息来了解人口水平的网络结构和动态。在这个项目中，我们的团队寻求建立在创新研究议程的基础上，该议程开发了建立网络流行病学原则性方法所需的统计理论、方法和程序。我们寻求扩展当前的方法以支持动态网络的全面建模。我们的具体目标是：1.发展用于网络动力学建模的统计理论和方法。a.改进和扩展现有的伙伴关系动力学建模的ERGM方法。B.开发ERGM的扩展部分，以应对不断变化的人口规模和构成。C.创建专门为流行病学应用设计的新网络可视化工具。2.将新方法集成到STAT Net软件中进行网络分析和模拟a.开发用于实施新方法的健壮代码；b.开发全面的帮助功能、手册和教程；c.通过在cran上发布代码和开发基于互联网的工具来确保公众可访问。3.为不同领域的研究人员开发培训资源。a.开发为期5天的网络理论、研究设计、分析、模拟和可视化研讨会。开发一个为期两天的关于使用STAT网络进行网络分析的培训研讨会。C.为跨学科外展开发为期一天的培训讲习班。我们的项目团队由一个跨学科的个人小组组成，他们有着长期的合作记录，在将网络方法应用于STI研究和预防方面拥有深厚的专业知识，在能力建设方面有经验，并致力于开发可公开访问的软件。我们的目标是推进网络分析科学，为流行病学和公共卫生研究提供创新的研究工具，并降低获得这些新工具的门槛。