SCC-IRG JST: PanCommunity: Leveraging Data and Models for Understanding and Improving Community Response in Pandemics

SCC-IRG JST：泛社区：利用数据和模型来理解和改善流行病中的社区响应

• 批准号: 2125246
• 负责人: Kasim Candan
• 金额: $ 72万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2125246&HistoricalAwards=false
• 关键词: SCC; IRG; JST; PanCommunity; Leveraging

The goal of this integrative research effort is to enhance the understanding of the complex relationships characterizing pandemics and interventions under crisis. The global-scale response to the COVID-19 pandemic triggered drastic measures including economic shutdowns, travel bans, stay-home orders, and even complete lockdowns of entire cities, regions, and countries. The need to effectively produce and deliver PPE, testing and vaccines has affected different communities of stakeholders in different ways, requiring coordination at family/business units, counties/states to federal level entities. This project, therefore, considers communities at local, federal, and international (US and Japan) scales and investigate impact of testing, preventative measures and vaccines, when used in combination, to improve community and inter-agency response at the different scales. The impacts of this research includes technologies to help save lives, restore basic services and community functionality, and establish a platform that supports core capabilities including planning, public information, and warning. The project organizes an interdisciplinary community, bringing together (a) computer/data scientists, (b) domain and social scientists and policy experts, (c) federal, state, local governments, (d) industry and nonprofits, and (e) educators, to serve as a nexus for major research collaborations that will: overcome key research barriers and explore and catalyze new paradigms and practices in cross-community response to pandemics; enable development and sharing of sustainable and reusable technologies, coupled with extensive broader dissemination activities; act as a resource for public policy guidance on relevant strategies and regulations; and provide education, broadening participation, and workforce development at all levels (K12 to postgraduate) for the next generation of scientists, engineers, and practitioners. The project involves a close collaboration between Arizona State University in the United States, and Kyoto University in Japan. The project involves interfaces with community partners in Tempe, Arizona and Kyoto, as well as national-level civic organizations in both the U.S. and Japan. This effort aims to answer several fundamental research challenges across computing and community health: (a) epidemic, testing, vaccination and behavior model/data integration and alignment, (b) multi-model and multi-scale simulation ensemble creation and decision support, and (c) multi-scale social impact of decision making across communities. To tackle these challenges, the project develops new data and model informed methods, brought together in PanCommunity, to develop testing and vaccination policies, considering coordination, collaboration, and competition across communities at multiple scales. This project will develop a novel model description, assessment, and composition framework that supports seamless integration of independently developed, reusable scientific model and analysis components within the same framework as the data for understanding and improving community response in pandemics. This project also develops novel coupled simulation and optimization frameworks that account not only for economical but also social costs in supporting decision making.This project is a joint collaboration between the National Science Foundation and the Japan Science and Technology Agency.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.

这一综合研究工作的目标是加强对危机下流行病和干预措施之间复杂关系的理解。 全球范围内对COVID-19疫情的应对引发了严厉的措施，包括经济关闭、旅行禁令、居家令，甚至整个城市、地区和国家的全面封锁。有效生产和提供个人防护设备、检测和疫苗的需求以不同的方式影响了不同的利益相关者群体，需要在家庭/企业单位、县/州到联邦一级实体之间进行协调。因此，本项目考虑地方、联邦和国际（美国和日本）规模的社区，并调查检测、预防措施和疫苗结合使用时的影响，以改善不同规模的社区和机构间反应。这项研究的影响包括帮助拯救生命、恢复基本服务和社区功能的技术，以及建立一个支持规划、公共信息和预警等核心能力的平台。 该项目组织了一个跨学科社区，汇集了（a）计算机/数据科学家，（B）领域和社会科学家及政策专家，（c）联邦、州、地方政府，（d）工业和非营利组织，以及（e）教育工作者，作为重大研究合作的纽带，将：克服关键的研究障碍，探索和促进跨社区应对流行病的新范例和做法;促进可持续和可重复使用技术的开发和共享，同时开展广泛的传播活动;作为有关战略和法规的公共政策指导资源;为下一代科学家、工程师和从业人员提供各级教育、扩大参与和劳动力发展（从K12到研究生）。该项目涉及美国亚利桑那州立大学和日本京都大学之间的密切合作。 该项目涉及与亚利桑那州滕佩和京都的社区合作伙伴以及美国和日本的国家级民间组织的接口。这项工作的目的是回答几个基础研究的挑战，在计算和社区健康：（a）流行病，测试，疫苗接种和行为模型/数据集成和对齐，（B）多模型和多尺度模拟集成创建和决策支持，（c）跨社区决策的多尺度社会影响。为了应对这些挑战，该项目开发了新的数据和模型知情的方法，汇集在泛社区，以制定测试和疫苗接种政策，考虑多个规模的社区之间的协调，合作和竞争。该项目将开发一种新的模型描述、评估和组合框架，支持将独立开发的、可重复使用的科学模型和分析组件无缝集成在同一框架内，作为理解和改善社区对流行病反应的数据。该项目是由美国国家科学基金会和日本科学技术厅共同合作的项目。该奖项反映了NSF的法定使命，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。