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: 1525061
• 负责人: Ashok Srinivasan
• 金额: $ 5万
• 依托单位: Florida 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=1525061&HistoricalAwards=false
• 关键词: Collaborative; Research; Simulation; Based; Policy

When Ebola has spread widely, it is known that much of the spread is through infected passengers that travel by air, to then spread Ebola far afield from the site of their infection. Understanding how Ebola spreads during air travel is critical in effectively dealing with this type of spreading. To help gain this understanding, 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 super-computing based applications that researchers propose to create will provide useful insight to decision makers - such as medical responders, policy makers etc. dealing with Ebola spread during air travel. The models are intended to be applied at the level of individual flights, so that the spread of Ebola can be understood for a particular flight while it is in the air, and procedures developed that will limit the infection risk for everyone on 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?

当埃博拉病毒广泛传播时，众所周知，大部分传播是通过乘空中行驶的受感染乘客，然后从感染部位传播埃博拉病毒。了解埃博拉在航空旅行期间如何传播在有效地处理这种类型的传播方面至关重要。为了帮助获得这种理解，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重大破坏航空旅行的程序和政策。研究人员建议创建的基于超级计算的应用程序将为决策者提供有用的见解，例如医疗响应者，政策制定者等，在航空旅行期间处理埃博拉病毒差异。这些模型旨在在单个飞行级别上应用，以便在空气中的特定飞行中可以理解埃博拉的传播，并且开发的程序将限制该飞行中每个人的感染风险，该模型将在空中飞行模型中运行，该模型将在单个飞行中运行，以捕获个人的传播范围，以捕获现有的历史过程（该模型的传播）（该模型的传播）（该模型的传播）（该模型的传播）（该模型）（该模型都将历史过程中的传播分配）（通过空中旅行，地理区域可能被运输到潜在的感染人群中，外出和跨区域。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。该建议将PIS整合在对飞机中的人体运动建模，建模感染的传播，建立软件基础架构以进行决策支持以及大规模并行计算的过程中，整合了PIS的组合知识。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？