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

该RAPID奖项支持开发和部署基于web的实时COVID-19数据中心，由数据科学、地理信息学、流行病学和地理领域的跨学科专家团队管理。该小组将收集、分析和传播有关COVID-19大流行在北极的时空动态的数据。将向包括北极居民、研究人员和政策制定者在内的利益攸关方提供分区域一级的数据集和时空趋势分析。通过收集北极社区COVID-19经历的第一人称叙述，将大流行数据纳入背景。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。方法：研究小组将利用他们在收集和分析与2019冠状病毒病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的数据库中收集；变量将包括基本的人口统计数据、检测率、发病率和死亡率。关于大流行应对、隔离措施、缓解努力和官方公告的定性数据将被标记和编目，以供基于主题和位置的搜索。将以虚拟方式收集关于北极社区COVID-19经历的多语言叙述，并在知情同意的情况下，在该项目的数据中心提供。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。

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.