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Collaborative:Elements:Cyberinfrastructure for Pedestrian Dynamics-Based Analysis of Infection Propagation Through Air Travel

Collaborative:Elements:Cyberinfrastructure for Pedestrian Dynamics-Based Analysis of Infection Propagation Through Air Travel
协作:元素:基于行人动力学的航空旅行感染传播分析的网络基础设施
批准号:
1931560
负责人:
Matthew Scotch
金额:
$9.95万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-11-01 至 2023-10-31

项目摘要

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中文摘要
翻译
当人们聚集在一起时,例如,在娱乐活动中,在人群中,在飞机上,他们彼此密切接触,可以传播传染病。2016年迪士尼乐园爆发的麻疹就是一个突出的例子。特别是航空旅行,是传染病传播的一个主要因素,在航空旅行期间已经爆发了几次严重疾病的传播,如SARS、H1N1流感和肺结核。如果这些政策是基于科学的,那么人群管理、登机等方面的公共卫生政策和程序可以帮助减轻疾病的传播。直接传播疾病的传播受人的移动模式控制,因为移动可以使受感染的人接近其他人。“行人动力学”科学提供了可以精确模拟人群中个人运动的数学模型。这些模型使科学家能够了解不同的政策(如飞机登机程序)如何预防或使感染传播变得更糟。该项目旨在开发一种新颖的软件,该软件将提供各种行人动力学模型、感染传播模型以及数据,以便科学家可以分析不同机制对拥挤地区直接传播疾病传播的影响。这个项目最初的重点是航空旅行。然而,该软件可以扩展到更广泛的运动分析和流行病学应用范围,例如在主题公园和体育场馆。该项目团队正与机场、公共卫生机构和航空业的决策者密切合作。这种合作将导致这门科学的实际应用,从而改善公众健康。该项目和软件将教育范围广泛的科学家和学生,特别是来自代表性不足群体的学生,以及在公共卫生领域工作的专业人员。该项目旨在开发一种新颖的软件,该软件将提供各种行人动力学模型、感染传播模型以及数据,以便科学家可以分析不同机制对拥挤地区直接传播疾病传播的影响。这个项目最初的重点是航空旅行。然而,该软件可以扩展到更广泛的运动分析和流行病学应用范围,例如在主题公园和体育场馆。拟议软件的开发将涉及几项创新。它将包括一个新的系统地理学模型,该模型将精细的人类运动数据与病毒遗传信息联系起来,以更准确地模拟病毒的地理扩散。行人运动的新模型将使复杂的人类运动模式建模成为可能。行人动态模型选择的推荐系统和政策和人类行为输入的领域特定语言将提高不同领域研究人员的可用性。社区建设倡议将促进跨学科研究,通过大量贡献者和用户确保项目的长期可持续性。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
When people congregate - for example, at entertainment events, in crowds, and airplanes - they come into close contact with each other and can spread infectious diseases. The Disney World measles outbreak in 2016 is a prominent example. Air travel, in particular, is a leading factor in the spread of infections, and there have been several outbreaks of serious diseases that spread during air travel, such as SARS, H1N1 influenza, and tuberculosis. Public health policies and procedures for crowd management, boarding airplanes, etc. can help in mitigating the spread of disease, if these policies are science-based. The spread of directly transmitted diseases is governed by the movement patterns of people because the movement can bring an infected person close to others. The science of "pedestrian dynamics" provides mathematical models that can accurately simulate the movement of individuals in a crowd. These models allow scientists to understand how different policies, such as boarding procedures on planes, can prevent, or make worse, the transmission of infections. This project seeks to develop a novel software that will provide a variety of pedestrian dynamics models, infection spread models, as well as data so that scientists can analyze the effect of different mechanisms on the spread of directly transmitted diseases in crowded areas. The initial focus of this project is on air travel. However, the software can be extended to a broader scope of applications in movement analysis and epidemiology, such as in theme parks and sports venues. The project team is working closely with decision makers in airports, public health agencies, and the airline industry. This collaboration will lead to practical applications of this science that will improve public health. This project and the software will educate a wide range of scientists as well as students, in particular, students from under-represented groups, as well as professionals working in the public health fields.This project seeks to develop a novel software that will provide a variety of pedestrian dynamics models, infection spread models, as well as data so that scientists can analyze the effect of different mechanisms on the spread of directly transmitted diseases in crowded areas. The initial focus of this project is on air travel. However, the software can be extended to a broader scope of applications in movement analysis and epidemiology, such as in theme parks and sports venues. Development of the proposed software will involve several innovations. It will include a novel phylogeography model that links fine-scale human movement data with virus genetic information to more accurately model geographic diffusion of viruses. New models for pedestrian movement will enable modeling of complex human movement patterns. A recommendation system for the choice of pedestrian dynamics models and a domain specific language for the input of policies and human behaviors will enhance usability by researchers in diverse fields. Community building initiatives will catalyze inter-disciplinary research to ensures the long-term sustainability of the project through a critical mass of contributors and users.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Collaborative Research: NSF-CSIRO: HCC: Small: Understanding Bias in AI Models for the Prediction of Infectious Disease Spread
  • 批准号:
    2302969
  • 项目类别:
    Standard Grant
  • 资助金额:
    $9.72万
  • 财政年份:
    2023
  • 负责人:
    Matthew Scotch
  • 依托单位:
Collaborative:RAPID: Leveraging New Data Sources to Analyze the Risk of COVID-19 in Crowded Locations
  • 批准号:
    2027529
  • 项目类别:
    Standard Grant
  • 资助金额:
    $4.97万
  • 财政年份:
    2020
  • 负责人:
    Matthew Scotch
  • 依托单位:
Collaborative Research: Petascale Simulation of Viral Infection Propagation Through Air Travel
  • 批准号:
    1640911
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.55万
  • 财政年份:
    2016
  • 负责人:
    Matthew Scotch
  • 依托单位:
Collaborative Research: Simulation-Based Policy Analysis for Reducing Ebola Transmission Risk in Air Travel
  • 批准号:
    1525012
  • 项目类别:
    Standard Grant
  • 资助金额:
    $10.0万
  • 财政年份:
    2015
  • 负责人:
    Matthew Scotch
  • 依托单位:
海外基金