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

时空创新IUCRC开发了新的时空分析工具，使具有国家和全球意义的应用成为可能。作为对新冠肺炎危机的回应，哈佛大学和乔治梅森大学是该国际预防和控制中心内的两所大学，他们提出了这个合作项目，以近实时地收集和共享与冠状病毒相关的数据，进行时空分析，并挖掘社会经济和环境知识，以促进决策支持系统应对这一流行病。该项目将建立一个独特的基于云的平台，包括用于收集全球高质量新冠肺炎相关数据的数据收集子系统；用于分析疾病演变和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所收集的数据以及访问开发的时空分析和建模工具的能力。这种能力将有助于快速产生数据驱动的决策支持系统，以便社区做好准备。该项目已获得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爆发，如何影响地球环境，以及如何根据亚洲和欧洲的经验在美国平衡经济重新开放和控制疾病传播。超过200名本科生志愿者，包括许多来自代表性不足的群体，已经通过哈佛的冠状病毒可视化团队的努力参与了这个项目。该项目积累的数据、信息和知识已经并将继续长期保存在一个综合门户(covid-19.stcenter.net)中。这些数据包括确诊病例的时空分布，来自不同来源的相关社会、经济和自然信息，如权威报告、新闻稿、地球观测和社交媒体。开发的软件和工具发布在GitHub上，供开放访问。持续的在线合作正在进行中，以产生可复制的研究，使用时空分析来挖掘新冠肺炎与社会和自然因素之间的模式和关系，以便社区做出反应和准备。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智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.