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Human mobility data in the COVID-19 pandemic:characteristics,applications,and challenges

International Journal of Digital Earth 2021年第9期14卷 1126-1147页

作者： Tao Hu Siqin Wang Bing She Mengxi Zhang Xiao Huang Yunhe Cui Jacob Khuri Yaxin Hu Xiaokang Fu Xiaoyue Wang Peixiao Wang Xinyan Zhu Shuming Bao Wendy Guan Zhenlong Li Department of Geography Oklahoma State UniversityStillwaterOKUSA Center for Geographic Analysis Harvard UniversityCambridgeMAUSA School of Earth and Environmental Sciences The University of QueenslandSt LuciaAustralia Institute for Social Research University of MichiganAnn ArborMIUSA School of Health Ball State UniversityMuncieINUSA Department of Geosciences University of ArkansasFayettevilleARUSA Department of Geography University of ConnecticutStorrsCTUSA Lake Erie College of Osteopathic Medicine Seton Hill UniversityGreensburgPAUSA School of Resource and Environmental Sciences Wuhan UniversityWuhanPeople’s Republic of China State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanPeople’s Republic of China China Data Institute Ann ArborMIUSA Geoinformation and Big Data Research Laboratory Department of GeographyUniversity of South CarolinaColumbiaSCUSA

The COVID-19 pandemic poses unprecedented challenges around the world.Many studies have applied mobility data to explore spatiotemporal trends over time,investigate associations with other variables,and predict or simulate the spread of COVID-19.Our objective was to provide a comprehensive overview of human mobility open data to guide researchers and policymakers in conducting data-driven evaluations and decision-making for the COVID-19 pandemic and other infectious disease outbreaks.We summarized the mobility data usage in COVID-19 studies by reviewing recent publications on COVID-19 and human mobility from a data-oriented perspective.We identified three major sources of mobility data:public transit systems,mobile operators,and mobile phone applications.Four approaches have been commonly used to estimate human mobility:public transit-based flow,social activity patterns,index-based mobility data,and social media-derived mobility data.We compared mobility datasets’characteristics by assessing data privacy,quality,space–time coverage,high-performance data storage and processing,and accessibility.We also present challenges and future directions of using mobility data.This review makes a pivotal contribution to understanding the use of and access to human mobility data in the COVID-19 pandemic and future disease outbreaks.

关键词： COVID-19 public health human mobility open data mobile phone mobility index

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Taking the pulse of COVID-19:a spatiotemporal perspective

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International Journal of Digital Earth 2020年第10期13卷 1186-1211页

作者： Chaowei Yang Dexuan Sha Qian Liu Yun Li Hai Lan Weihe Wendy Guan Tao Hu Zhenlong Li Zhiran Zhang John Hoot Thompson Zifu Wang David Wong Shiyang Ruan Manzhu Yu Douglas Richardson Luyao Zhang Ruizhi Hou You Zhoua Cheng Zhong Yifei Tian Fayez Beaini Kyla Carte Colin Flynn Wei Liu Dieter Pfoser Shuming Bao Mei Li Haoyuan Zhang Chunbo Liu Jie Jiang Shihong Du Liang Zhao Mingyue Lu Lin Li Huan Zhou Andrew Ding NSF Spatiotemporal Innovation Center George Mason Univ.FairfaxVAUSA Department of Geography and GeoInformation Science George Mason Univ.FairfaxVAUSA Department of Geographical Sciences University of MarylandCollege ParkMDUSA Center for Geographic Analysis Harvard UniversityCambridgeMAUSA Geoinformation and Big Data Research Lab Department of GeographyUniversity of South CarolinaColumbiaSCUSA Chinese Academy of Surveying and Mapping BeijingPeople’s Republic of China School of Resource and Environmental Sciences Wuhan UniversityWuhanPeople’s Republic of China Cloud Computeand Storage OperationsInformation Technology ServicesGeorge Mason UniversityFairfaxVAUSA Department of Geography Pennsylvania State UniversityState CollegePAUSA School of Business Management East China Normal UniversityShanghaiPeople’s Republic of China School of Mathematical Sciences East China Normal UniversityShanghaiPeople’s Republic of China Department of Psychology George Mason UniversityFairfaxVAUSA mDepartment of Computer Science George Mason UniversityFairfaxVAUSA Department of Information Technology George Mason UniversityFairfaxVAUSA Department of Biology George Mason UniversityFairfaxVAUSA College of Land Science and Technology China Agricultural UniversityBeijingPeople’s Republic of China China Data Institute Ann ArborMIUSA Institute of Remote Sensing and GIS Peking UniversityBeijingPeople’s Republic of China Aerospace Information Research Institute Chinese Academy of SciencesBeijingPeople’s Republic of China School of Geomatics and Urban Spatial Informatics Beijing University of Civil Engineering and ArchitectureBeijingPeople’s Republic of China School of Geographical Sciences Nanjing University of Information Science&TechnologyNanjingPeople’s Republic of China School of Geodesy and Geomatics Wuhan UniversityWuhanPeople’s Republic of China wFaculty of Environment University of WaterlooWaterlooCanada

The sudden outbreak of the Coronavirus disease(COVID-19)swept across the world in early 2020,triggering the lockdowns of several billion people across many countries,including China,Spain,India,the U.K.,Italy,France,Germany,Brazil,Russia,and the U.S.The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S.,India,Russia,and Brazil.In response to this national and global emergency,the NSF Spatiotemporal Innovation Center brought together a taskforce of international researchers and assembled implementation strategies to rapidly respond to this crisis,for supporting research,saving lives,and protecting the health of global citizens.This perspective paper presents our collective view on the global health emergency and our effort in collecting,analyzing,and sharing relevant data on global policy and government responses,human mobility,environmental impact,socioeconomical impact;in developing research capabilities and mitigation measures with global scientists,promoting collaborative research on outbreak dynamics,and reflecting on the dynamic responses from human societies.

关键词： Big Data Earth system emergency geospatial sciences epidemics applications

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