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.

该快速奖项支持由数据科学，地理信息学，流行病学和地理专家跨学科的团队管理的基于Web的COVID-19数据中心的开发和部署。该团队将收集，分析和传播有关北极期间COVID-19的空间和临时动态的数据。北极居民，研究人员和决策者在内的利益相关者都将对次区域级别的空间时间趋势进行数据集和分析。大流行数据将通过收集北极社区的Covid-19经验的第一人称叙述来进行上下文。该团队还将开发地理化工具并分析数据集，以解决与Covid-19在北极地区传播和地理有关的紧急问题，评估遏制和缓解政策，并评估病例死亡率是否受环境，社会经济和/或/或地理变量的影响。北极Covid-19的长期策划数据和数据产品将确保将来的分析，历史研究和政策考虑。方法：研究团队将基于他们在收集和分析潜水员，多语言数据集的专业知识的基础上，与Covid-19在北极地区的事件和传播有关。从北美，斯堪的纳维亚半岛和俄罗斯的地理参考的定量数据将从公开可用的数据库中收集；变量将包括基本的人口统计数据以及测试率，发病率和死亡率。有关大流行响应，隔离措施，缓解工作和官方公告的定性数据将被挖掘和分类，以进行主题和基于位置的搜索。几乎可以收集有关Covid-19在北极社区中经验的多语言叙事记载，并在知情同意书中获得该项目数据枢纽的知识同意。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准来通过评估来诚实地认为通过评估。

项目成果

Lessons on COVID-19 from Indigenous and remote communities of the Arctic

• DOI: 10.1038/s41591-021-01473-9
• 发表时间: 2021-08-23
• 期刊: NATURE MEDICINE
• 影响因子: 82.9
• 作者: Petrov, Andrey N.;Welford, Mark;Savelyev, Alexander
• 通讯作者: Savelyev, Alexander