Population mobility models of urban disease outbreak

城市疾病爆发的人口流动模型

• 批准号: 6766307
• 负责人: STEPHEN G EUBANK
• 金额: $ 44.33万
• 依托单位: UNIVERSITY OF CALIF-LOS ALAMOS NAT LAB
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-05-01 至 2005-01-05
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6766307
• 关键词: behavioral /social science research tag; bioinformatics; bioterrorism /chemical warfare; communicable disease transmission; computational biology; computer program /software; cooperative study; disasters; disease /disorder proneness /risk; disease outbreaks; epidemiology; health; health behavior; health care service utilization; host organism interaction; human population study; information systems; model design /development; patient care management; social mobility; urban area

DESCRIPTION (provided by applicant): This project will design, build, and validate models of disease epidemiology and response systems based on individuals' roles in a social network. It will focus on mathematical and computational methods for modelling exposure to pathogens and their products as well as the effectiveness and consequences of different intervention strategies. In particular, it will explore the effects of human contact patterns in urban areas on disease transmission dynamics and the consequences of proposed early and mid-term responses to intentional or natural releases of pathogens. The project will produce a simulation system tracking the transmission of multiple co-circulating and interacting diseases in a synthetic population. Flexible user-specified scenarios will include such parameterized elements as: host-pathogen interactions; disease transmission dynamics; initial health state of the population; the mode of a pathogen's introduction into the population; and choice and scheduling of response strategies, which might be demographically and/or geographically targeted. The simulation will rely on existing estimates of contact patterns in a synthetic urban population of 1.5 million individuals. Research topics will include how these patterns might change in the presence of an outbreak. In addition, the project will undertake a mathematical, structural analysis of the estimated contact patterns at the heart of the simulation. The goals of this analysis are: to determine the features of social networks that best characterize their response to epidemics and mitigation strategies; to develop efficient algorithms for evaluating these features in very large networks; to estimate variability in these features among different urban areas and different size populations; and to provide the capability for generating stochastic but realistic instances of social networks. All results will be communicated in a timely fashion to the MIDAS Informatics Group. The project intends to provide software (both the simulation itself and analysis tools for social networks) and also epidemiological data arising from simulation of a set of standard scenarios

描述（由申请人提供）：该项目将根据个人在社交网络中的角色来设计、构建和验证疾病流行病学和响应系统模型。 它将重点关注对病原体及其产物的暴露进行建模的数学和计算方法，以及不同干预策略的有效性和后果。 特别是，它将探讨城市地区人类接触模式对疾病传播动态的影响，以及针对有意或自然释放病原体所提出的早期和中期应对措施的后果。 该项目将制作一个模拟系统，跟踪合成人群中多种共同循环和相互作用的疾病的传播。 灵活的用户指定场景将包括以下参数化元素：宿主-病原体相互作用；疾病传播动态；人口的初始健康状况；病原体引入人群的方式；应对策略的选择和安排，可能是针对人口和/或地理的。 该模拟将依赖于对 150 万综合城市人口中接触模式的现有估计。 研究主题将包括这些模式在爆发时可能如何变化。 此外，该项目还将对模拟核心的估计接触模式进行数学结构分析。 该分析的目标是：确定最能体现其对流行病反应和缓解策略的社交网络的特征；开发有效的算法来评估大型网络中的这些特征；估计不同城市地区和不同规模人口中这些特征的变异性；并提供生成随机但现实的社交网络实例的能力。 所有结果将及时传达给 MIDAS 信息学小组。 该项目旨在提供软件（模拟本身和社交网络分析工具）以及模拟一组标准场景所产生的流行病学数据