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Collaborative Research: RAPID: Building a Spatiotemporal Platform for Rapid Response to COVID-19

合作研究：RAPID：构建快速响应 COVID-19 的时空平台

基本信息

批准号：
2027540
负责人：
Weihe Guan
金额：
$ 10万
依托单位：
Harvard University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-06-01 至 2021-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2027540&HistoricalAwards=false
关键词：
Collaborative Research RAPID Building Spatiotemporal

项目摘要

The Spatiotemporal Innovation IUCRC develops novel spatiotemporal analytical tools to enable applications of national and global significance. In response to the COVID-19 crisis, Harvard University and George Mason University, university sites within this IUCRC, propose this collaborative project to collect and share COVID related data in near real time, conduct spatiotemporal analytics, and mine socioeconomic and environmental knowledge to facilitate decision support systems in response to the pandemic. This project will build a unique cloud-based platform composed of a data collection subsystem for collecting global, high quality COVID-19-related data; spatiotemporal analytics tools for analyzing the disease evolution and socioeconomic patterns; and, modeling tools for assessing medical supplies and logistics. Through web access services, the platform will provide capabilities for easy access to the data collected as well as access to the developed spatiotemporal analytical and modeling tools. Such capabilities will facilitate quick production of data-driven decision support systems for community preparedness. This project has secured participation of 50+ international researchers in developing the proposed platform. These researchers will help collect and validate data, analyze how policies influence the outbreaks, how the Earth environment is impacted, and how to balance reopening of the economy and controlling the spreading of the disease in the U.S. based on experiences from Asia and Europe. Over 200 undergraduate volunteers, including many from underrepresented groups, are already involved in this project through Harvard’s Coronavirus Visualization Team efforts. Data, information, and knowledge accumulated in this project have been, and will continue to be, archived long term in a comprehensive gateway (covid-19.stcenter.net). Such data include spatiotemporal distribution of confirmed cases, relevant social, economic and natural information from different resources, such as authoritative reports, news releases, Earth observation, and social media. Software and tools developed are posted on GitHub for open access. Sustained online collaboration is being conducted to produce replicable research using spatiotemporal analyses to mine patterns and relations between COVID-19 and social and natural factors for community response and preparedness.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.

世界自然与自然保护委员会开发新的时空分析工具，以实现具有国家和全球意义的应用。为应对COVID-19危机，世界自然保护委员会下属的哈佛大学和乔治梅森大学提出了这个合作项目，以近乎实时地收集和共享COVID-19相关数据，进行时空分析，挖掘社会经济和环境知识，以促进应对大流行的决策支持系统。该项目将构建一个独特的云平台，由数据采集子系统组成，用于收集全球高质量的covid -19相关数据；疾病演变与社会经济模式的时空分析工具以及用于评估医疗用品和后勤的建模工具。通过网络访问服务，该平台将提供方便地访问收集到的数据以及访问开发的时空分析和建模工具的能力。这种能力将有助于为社区备灾快速生产数据驱动的决策支持系统。该项目已确保50多名国际研究人员参与开发拟议的平台。这些研究人员将帮助收集和验证数据，分析政策如何影响疫情，如何影响地球环境，以及如何根据亚洲和欧洲的经验平衡重新开放经济和控制疾病在美国的传播。通过哈佛大学冠状病毒可视化团队的努力，200多名本科生志愿者，包括许多来自代表性不足的群体，已经参与了这个项目。本项目积累的数据、信息和知识已经并将继续在综合网关（covid-19.stcenter.net）中长期存档。这些数据包括确诊病例的时空分布，以及来自不同资源的相关社会、经济和自然信息，如权威报告、新闻稿、对地观测和社交媒体。开发的软件和工具发布在GitHub上供开放访问。正在开展持续的在线协作，以开展可复制的研究，利用时空分析挖掘COVID-19与社区应对和准备的社会和自然因素之间的模式和关系。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。