RAPID: Tracking the Spatiotemporal Dynamics of the COVID-19 Pandemic in the Arctic

RAPID：追踪北极地区 COVID-19 大流行的时空动态

• 批准号: 2034886
• 负责人: Andrey Petrov
• 金额: $ 20万
• 依托单位: University of Northern Iowa
• 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: 2020-06-15 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2034886&HistoricalAwards=false
• 关键词: RAPID; Tracking; Spatiotemporal; Dynamics; COVID

This RAPID award supports the development and deployment of a real-time web-based COVID-19 data hub managed by an interdisciplinary team of experts in data science, geoinformatics, epidemiology and geography. The team will collect, analyze, and disseminate data on the spatial and temporal dynamics of the COVID-19 pandemic in the Arctic. Both datasets and analyses of spatiotemporal trends at the subregional level will be made available to stakeholders including Arctic residents, researchers, and policymakers. Pandemic data will be contextualized through the collection of first-person accounts of the COVID-19 experience in Arctic communities. The team will also develop geovisualization tools and analyze datasets to address urgent questions related to the spread and geography of COVID-19 in the Arctic, assessing containment and mitigation policies and evaluating whether case fatality rates are affected by environmental, socioeconomic, and/or geographic variables. Long-term curation of Arctic COVID-19 data and data products will ensure availability for future analysis, historical study and policy consideration. Methods: The research team will build on their expertise in collection and analysis of diverse, multilingual datasets relevant to the incidence and spread of COVID-19 in the Arctic. Georeferenced quantitative data from North America, Scandinavia, and Russia will be collected from publicly available databases; variables will include basic demographic data, and rates of testing, morbidity, and mortality. Qualitative data on pandemic response, quarantine measures, mitigation efforts, and official announcements will be geotagged and catalogued for theme- and location-based searches. Multilingual narrative accounts of the experience of COVID-19 in Arctic communities will be collected virtually and, with informed consent, made available on the project’s data hub.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.

该RAPID奖项支持开发和部署基于网络的实时COVID-19数据中心，由数据科学，地理信息学，流行病学和地理学的跨学科专家团队管理。该团队将收集、分析和传播有关COVID-19在北极大流行的时空动态的数据。将向包括北极居民、研究人员和决策者在内的利益攸关方提供次区域一级的数据集和时空趋势分析。大流行数据将通过收集北极社区COVID-19经历的第一人称描述进行背景化。该团队还将开发地理可视化工具并分析数据集，以解决与COVID-19在北极的传播和地理相关的紧迫问题，评估遏制和缓解政策，并评估病死率是否受到环境，社会经济和/或地理变量的影响。北极COVID-19数据和数据产品的长期管理将确保未来分析、历史研究和政策考虑的可用性。研究方法：该研究团队将利用他们在收集和分析与COVID-19在北极的发病率和传播相关的多种多语言数据集方面的专业知识。来自北美、斯堪的纳维亚和俄罗斯的地理参考定量数据将从公开数据库中收集;变量将包括基本人口统计数据以及检测率、发病率和死亡率。将对流行病应对、隔离措施、缓解措施和官方公告的定性数据进行地理标记和编目，以便进行基于主题和位置的搜索。该奖项反映了NSF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。