COVID-19全球大流行的时空应对挑战与机遇

IF 2.7 Q1 GEOGRAPHY
Chaowei Yang, S. Bao, W. Guan, K. Howell, T. Hu, H. Lan, Yun Li, Qian Liu, Jennifer Smith, Anusha Srirenganathan Malarvizhi, Theo Trefonides, Kevin Wang, Zifu Wang
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引用次数: 0

摘要

作为百年一遇的大流行,COVID-19正在改变和重塑世界。2019冠状病毒病给人类社会带来了巨大挑战,促使我们发明新的分析工具,以研究跨学科研究的理论、方法和应用的复杂系统的时空模式(Yang et al. 2020)。美国国家科学基金会(NSF)资助时空创新中心(STC)进行时空快速反应,以应对这一全球健康危机。在不同社区的参与下,成立了一个多元化的团队,为全球COVID-19大流行提供全面的非医疗快速反应,以回答许多具有身体和社会挑战性的问题。武汉大学社会科学地理计算中心、清华大学、密歇根中国数据研究所、澳大利亚昆士兰大学、洛杉矶RMDS实验室等多家机构的专家和参与者组成了一个由美国几乎每个州和全球每个时区的专家和参与者组成的国际团队,以实现以下目标:(1)为当地COVID-19时空研究提供数据支持;从不同来源收集和综合信息的区域和全球各级;(2)运用先进的方法和技术,促进新冠肺炎空间蔓延和影响的定量研究;(3)推动在空间数据实验室和Dataverse平台上开展COVID-19时空研究的协同研究;(4)为未来的合作项目建立研究能力。除了进行研究和开发之外,还组织了一系列网络研讨会和小型虚拟研讨会,以介绍研究结果并征求社区反馈。本期特刊旨在介绍这些新进展和新发现,重点对COVID-19的影响进行时空分析。本期介绍的研究包括理论、方法、数据和应用研究,这些研究有助于了解COVID-19对卫生、人口、社会经济、环境、政治和其他领域的短期和长期空间和时间影响。第一个四篇论文研究了大流行的时空模式的影响在世界的不同地区(印度/萨勃拉曼尼亚等人这个问题,中国/裴等人这个问题,美国/出差费等人这个问题,10和12个二级城市发展中国家在非洲,亚洲和南美洲/ Laituri等人这个问题),不仅研究病毒感染病例(裴等人这个问题),但也多余的其他疾病的死亡(出差费等人这个问题),以及大流行的社会、经济和环境影响(Laituri等本期)。最近四篇论文探索了社交媒体或人类流动性数据(Shen等人,本期),以寻找它们与COVID-19传播(Zhang等人,本期)、非传染性疾病(Mu等人,本期)和城市大都市空气质量(Li等人,2022)的时空关系。在快速反应项目和特刊编辑过程结束时,我们组织了一次约有35人参加的小型讲习班,从时空角度讨论应对大流行病的相关机遇和挑战。本文从物理和社会挑战、数据收集、基础设施运营、计算研究、研究复制和社区参与等方面总结了2019冠状病毒病快速应对工作的成果、挑战和机遇。社会结构和脆弱性以及趋同科学也是COVID-19快速应对的关键组成部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges and opportunities of the spatiotemporal responses to the global pandemic of COVID-19
As a once-in-100-years pandemic, COVID-19 is changing and reshaping the world. COVID-19 poses grand challenges to human society and drives us to invent new analytical tools to examine the spatiotemporal patterns of the complex system for theories, methodologies, and applications of interdisciplinary research (Yang et al. 2020). The U.S. (US) National Science Foundation (NSF) funded the Spatiotemporal Innovation Center (STC) to conduct a spatiotemporal rapid response to address this global health crisis. Engaging various communities, a diverse team was formed to provide a comprehensive non-medical rapid response to the global COVID-19 pandemic for answering many physically and socially challenging questions. The international team formed by experts and participants from almost every US state and worldwide every time zone including the GeoComputation Center for Social Sciences at Wuhan University, Tsinghua University, the China Data Institute at Michigan, the University of Queensland in Australia, RMDS Lab at Los Angles, and many other institutions to achieve the objectives of (1) providing data support for the spatiotemporal study of COVID-19 at local, regional and global levels with information collected and integrated from different sources; (2) facilitating quantitative research on spatial spreading and impacts of COVID-19 with advanced methodology and technology; (3) promoting collaborative research on the spatiotemporal study of COVID-19 on the Spatial Data Lab and Dataverse platforms; and (4) building research capacity for future collaborative projects. In addition to research and development conducted, a series of webinars and a mini virtual workshop were organized to introduce findings and solicit community feedback. This Special Issue is organized to capture such new developments and findings with a focus on the spatiotemporal analysis of the impact of COVID-19. Research presented in this issue includes studies on theories, methodologies, data and applications, which together help understand the short-term and long-term impacts of COVID-19 on health, demographics, socioeconomics, environment, politics and other fields over space and time. The first four papers studied the space-time patterns of the pandemic’s impacts in different regions of the world (India/Subramanian et al. this issue, China/Pei et al. this issue, United States/Batta et al. this issue, and 12 secondary cities in 10 developing countries across Africa, Asia and South America/Laituri et al. this issue), examining not only the virus infected cases (Pei et al. this issue) but also the excess death of other diseases (Batta et al. this issue), as well as the pandemic’s social, economic and environmental impacts (Laituri et al. this issue). The last four papers explored social media or human mobility data (Shen et al. this issue) in search for their spatiotemporal relationships with COVID-19 transmission (Zhang et al. this issue), non-infectious diseases (Mu et al. this issue), and air quality in an urban metropolis (Li et al. 2022). At the end of the rapid response project and special issue editing process, we organized a mini workshop with approximately 35 participants to discuss the relevant opportunities and challenges of the pandemic response from a spatiotemporal perspective. This editorial ummarizes the findings, challenges, and opportunities from the perspectives of physical and social challenges, data collection, infrastructure operation, computing research, research replication, and community engagement in the COVID-19 rapid response. Social structure and vulnerability as well as convergence science are also practiced as critical components of the COVID-19 rapid response.
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来源期刊
Annals of GIS
Annals of GIS Multiple-
CiteScore
8.30
自引率
2.00%
发文量
31
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