Collaborative Research: Simulation-Based Policy Analysis for Reducing Ebola Transmission Risk in Air Travel

合作研究：基于模拟的政策分析，降低航空旅行中的埃博拉传播风险

• 批准号: 1525012
• 负责人: Matthew Scotch
• 金额: $ 10万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1525012&HistoricalAwards=false
• 关键词: Collaborative; Research; Simulation; Based; Policy

The researchers on this project will build fine-scale simulation models for infection spread during air travel in order to identify the causes of infection spread, as well as procedures and policies that will limit its spread without major disruption to air travel. The researchers propose to create a super-computing based application that will provide useful insight to decision makers - such as medical responders, policy makers etc. dealing with Ebola. The models can be applied at the level of individual flights; thus not only can the spread of Ebola be understood for a particular flight, but also procedures can be developed that will limit the infection risk for that flight.An air-transport model, which operates at the level of individual flights, will be integrated with a phylogeographic model (that captures the historical processes responsible for the existing geographic distributions of individuals) in order to analyze the spread of infection between geographic regions when potentially infected populations are being transported into, out of and across regions, by air travel. The result of this work will help identify policy as well as operational solutions to reduce the risk of a pandemic, and also set up scalable software capabilities on a readily available infrastructure that can be used to address the current Ebola pandemic, as well as respond quickly to new emergencies. This proposal integrates the PIs? combined expertise in modeling human movement in planes, modeling the spread of infections, building a software infrastructure for decision support, and large-scale parallel computing. The models will be integrated using the Complex Systems framework (CSF, developed by a member of the proposing team) that provides a comprehensive decision support environment for analysis. Through this project, and in addition, CSF?s scalability will be enhanced to petascale machines, and methods will be developed to reduce the large computational cost of these simulations. Results of this work will provide valuable insight to policy makers. In particular, fine grain questions regarding plane travel can be asked and answered, such as: (a) the risk air travel has on disease spread to neighboring regions (b) can a change to another type of a plane lead to reduced risk of transmission? (c) Do certain seating arrangement or changes to boarding and disembarkation processes reduce the likelihood of transmission?

该项目的研究人员将在空中旅行期间建立精细的模拟模型，以确定感染蔓延的原因，以及将限制其扩散而不会严重破坏航空旅行的程序和政策。研究人员建议创建一个基于超级计算的应用程序，该应用程序将为决策者（例如医疗响应者，政策制定者等）提供有用的见解。这些模型可以应用于单个航班级别；因此，不仅可以理解特定飞行的埃博拉病毒的传播，而且还可以制定程序，这些程序将限制该飞行的感染风险。在单个飞行水平上运行的航空运输模型将与植物地理模型集成到植物学模型（该模型中，该模型捕获了跨越历史过程，以捕获了跨越现有的范围内的范围，从而分析了外在的范围，从而分析了范围的外在，分析了范围的外在范围，分析了范围的外在，分析了地理位置的范围。地区，航空旅行。这项工作的结果将有助于确定政策和运营解决方案，以降低大流行风险，并在随时可用的基础设施上建立可扩展的软件功能，可用于解决当前的埃博拉病毒大流行，并迅速对新的紧急情况做出反应。该提案整合了PI？合并的专业知识在建模平面运动，建模感染的传播，建立一个软件基础架构以进行决策支持以及大规模并行计算。这些模型将使用复杂的系统框架（CSF，由建议团队成员开发）进行集成，该框架为分析提供了全面的决策支持环境。通过这个项目，此外，CSF的可伸缩性将增强到Petascale机器上，并将开发方法来降低这些仿真的大量计算成本。这项工作的结果将为决策者提供宝贵的见识。特别是，可以问和回答有关飞机旅行的细谷物问题，例如：（a）空中旅行对疾病的风险传播到邻近地区（b）是否可以改变到另一种类型的飞机，导致传播风险降低？ （c）某些座位安排或登机和下船过程的更改会减少传播的可能性吗？