{"id":"https://openalex.org/W3106175490","doi":"https://doi.org/10.1080/19475683.2020.1841828","title":"Geographic pattern of human mobility and COVID-19 before and after Hubei lockdown","display_name":"Geographic pattern of human mobility and COVID-19 before and after Hubei lockdown","publication_year":2020,"publication_date":"2020-11-11","ids":{"openalex":"https://openalex.org/W3106175490","doi":"https://doi.org/10.1080/19475683.2020.1841828","mag":"3106175490"},"language":"en","primary_location":{"id":"doi:10.1080/19475683.2020.1841828","is_oa":true,"landing_page_url":"https://doi.org/10.1080/19475683.2020.1841828","pdf_url":null,"source":{"id":"https://openalex.org/S4210199948","display_name":"Annals of GIS","issn_l":"1947-5683","issn":["1947-5683","1947-5691"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annals of GIS","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1080/19475683.2020.1841828","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002836475","display_name":"T. Edwin Chow","orcid":"https://orcid.org/0000-0002-0386-5902"},"institutions":[{"id":"https://openalex.org/I13511017","display_name":"Texas State University","ror":"https://ror.org/05h9q1g27","country_code":"US","type":"education","lineage":["https://openalex.org/I13511017"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"T. Edwin Chow","raw_affiliation_strings":["Department of Geography, Texas State University, TX, USA"],"raw_orcid":"https://orcid.org/0000-0002-0386-5902","affiliations":[{"raw_affiliation_string":"Department of Geography, Texas State University, TX, USA","institution_ids":["https://openalex.org/I13511017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006220972","display_name":"Yusik Choi","orcid":"https://orcid.org/0000-0001-8021-2756"},"institutions":[{"id":"https://openalex.org/I13511017","display_name":"Texas State University","ror":"https://ror.org/05h9q1g27","country_code":"US","type":"education","lineage":["https://openalex.org/I13511017"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yusik Choi","raw_affiliation_strings":["Department of Geography, Texas State University, TX, USA"],"raw_orcid":"https://orcid.org/0000-0001-8021-2756","affiliations":[{"raw_affiliation_string":"Department of Geography, Texas State University, TX, USA","institution_ids":["https://openalex.org/I13511017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100438302","display_name":"Mei Yang","orcid":"https://orcid.org/0000-0002-6168-0084"},"institutions":[{"id":"https://openalex.org/I13511017","display_name":"Texas State University","ror":"https://ror.org/05h9q1g27","country_code":"US","type":"education","lineage":["https://openalex.org/I13511017"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mei Yang","raw_affiliation_strings":["Department of Geography, Texas State University, TX, USA"],"raw_orcid":"https://orcid.org/0000-0002-6168-0084","affiliations":[{"raw_affiliation_string":"Department of Geography, Texas State University, TX, USA","institution_ids":["https://openalex.org/I13511017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073857984","display_name":"David L. Mills","orcid":"https://orcid.org/0000-0002-2494-9187"},"institutions":[{"id":"https://openalex.org/I13511017","display_name":"Texas State University","ror":"https://ror.org/05h9q1g27","country_code":"US","type":"education","lineage":["https://openalex.org/I13511017"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Mills","raw_affiliation_strings":["Department of Geography, Texas State University, TX, USA"],"raw_orcid":"https://orcid.org/0000-0002-2494-9187","affiliations":[{"raw_affiliation_string":"Department of Geography, Texas State University, TX, USA","institution_ids":["https://openalex.org/I13511017"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082657727","display_name":"Ricci P. H. Yue","orcid":"https://orcid.org/0000-0002-8564-8556"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]},{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ricci Yue","raw_affiliation_strings":["Department of Geography and Resource Management, Chinese University of Hong Kong, HK SAR, China","Department of Public Policy, City University of Hong Kong, Hong Kong SAR, China"],"raw_orcid":"https://orcid.org/0000-0002-8564-8556","affiliations":[{"raw_affiliation_string":"Department of Geography and Resource Management, Chinese University of Hong Kong, HK SAR, China","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"Department of Public Policy, City University of Hong Kong, Hong Kong SAR, China","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5002836475"],"corresponding_institution_ids":["https://openalex.org/I13511017"],"apc_list":{"value":1500,"currency":"USD","value_usd":1500},"apc_paid":{"value":1500,"currency":"USD","value_usd":1500},"fwci":0.42,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.70544696,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"27","issue":"2","first_page":"127","last_page":"138"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10298","display_name":"Urban Transport and Accessibility","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11711","display_name":"COVID-19 Pandemic Impacts","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.6439201235771179},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.5964418649673462},{"id":"https://openalex.org/keywords/demography","display_name":"Demography","score":0.5815927386283875},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.49759748578071594},{"id":"https://openalex.org/keywords/megacity","display_name":"Megacity","score":0.4619719088077545},{"id":"https://openalex.org/keywords/spatiotemporal-pattern","display_name":"Spatiotemporal pattern","score":0.42633792757987976},{"id":"https://openalex.org/keywords/severe-acute-respiratory-syndrome-coronavirus-2","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","score":0.41591623425483704},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.20789721608161926},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1980440318584442},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.13083621859550476},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.11467218399047852},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.08804088830947876},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.07460400462150574}],"concepts":[{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.6439201235771179},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.5964418649673462},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.5815927386283875},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.49759748578071594},{"id":"https://openalex.org/C127040729","wikidata":"https://www.wikidata.org/wiki/Q174844","display_name":"Megacity","level":2,"score":0.4619719088077545},{"id":"https://openalex.org/C2779108282","wikidata":"https://www.wikidata.org/wiki/Q22908968","display_name":"Spatiotemporal pattern","level":2,"score":0.42633792757987976},{"id":"https://openalex.org/C3007834351","wikidata":"https://www.wikidata.org/wiki/Q82069695","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","level":5,"score":0.41591623425483704},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.20789721608161926},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1980440318584442},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.13083621859550476},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.11467218399047852},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.08804088830947876},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.07460400462150574},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/19475683.2020.1841828","is_oa":true,"landing_page_url":"https://doi.org/10.1080/19475683.2020.1841828","pdf_url":null,"source":{"id":"https://openalex.org/S4210199948","display_name":"Annals of GIS","issn_l":"1947-5683","issn":["1947-5683","1947-5691"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annals of GIS","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/aba8bc51-5866-47c8-8096-250ae71053e1","is_oa":true,"landing_page_url":"https://hdl.handle.net/2031/aba8bc51-5866-47c8-8096-250ae71053e1","pdf_url":"https://scholars.cityu.edu.hk/files/87670137/60969376.pdf","source":{"id":"https://openalex.org/S7407055387","display_name":"CityU Scholars","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Chow, T E, Choi, Y, Yang, M, Mills, D & Yue, R 2021, 'Geographic pattern of human mobility and COVID-19 before and after Hubei lockdown', Annals of GIS, vol. 27, no. 2, pp. 127-138. https://doi.org/10.1080/19475683.2020.1841828","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1080/19475683.2020.1841828","is_oa":true,"landing_page_url":"https://doi.org/10.1080/19475683.2020.1841828","pdf_url":null,"source":{"id":"https://openalex.org/S4210199948","display_name":"Annals of GIS","issn_l":"1947-5683","issn":["1947-5683","1947-5691"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annals of GIS","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6600000262260437,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310830","display_name":"Texas State University","ror":"https://ror.org/009ey6w22"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1966531757","https://openalex.org/W2004439190","https://openalex.org/W2156349196","https://openalex.org/W2167620733","https://openalex.org/W2913338880","https://openalex.org/W3003668884","https://openalex.org/W3008443627","https://openalex.org/W3010131837","https://openalex.org/W3010233963","https://openalex.org/W3011945457","https://openalex.org/W3012284084","https://openalex.org/W3012320055","https://openalex.org/W3013188135","https://openalex.org/W3013376481","https://openalex.org/W3013594674","https://openalex.org/W3014433460","https://openalex.org/W3014672040","https://openalex.org/W3014712943","https://openalex.org/W3015157127","https://openalex.org/W3015792206","https://openalex.org/W3019197760","https://openalex.org/W3020001547","https://openalex.org/W4285703489"],"related_works":["https://openalex.org/W4205317059","https://openalex.org/W4206669628","https://openalex.org/W3081785542","https://openalex.org/W3176864053","https://openalex.org/W3198183218","https://openalex.org/W4205810683","https://openalex.org/W4224279380","https://openalex.org/W4206548596","https://openalex.org/W4206651655","https://openalex.org/W4292098121"],"abstract_inverted_index":{"This":[0],"research":[1],"investigates":[2],"how":[3],"travel":[4],"restrictions":[5],"affect":[6],"the":[7,32,53,64,109,122,147,154,192,200,207,212,227,239,247],"spatiotemporal":[8],"pattern":[9,34,98,209,221],"of":[10,35,48,56,68,89,96,112,125,143,149,197,215,229],"human":[11,36,117],"mobility":[12,23,37,118],"and":[13,21,26,78,101,156,242],"COVID-19":[14,69,113,150],"confirmed":[15,110,226],"cases.":[16],"Based":[17],"on":[18],"recorded":[19],"movement":[20],"Baidu":[22],"index,":[24],"in-":[25],"out-migration":[27],"were":[28,168,191,203,233],"estimated":[29],"to":[30,52,170,183,188,206],"examine":[31],"geographic":[33,220],"across":[38],"many":[39],"Chinese":[40],"cities":[41],"from":[42,186,223],"Jan":[43,73],"1":[44],"\u2013":[45],"Feb":[46,79],"11":[47],"2020.":[49],"In":[50],"addition":[51],"baseline":[54,155],"model":[55,138],"city":[57],"lockdown":[58,100,123],",":[59],"this":[60,224],"study":[61,225],"also":[62,105],"explored":[63],"time":[65],"lag":[66],"effect":[67],"incubation":[70,141,177],"period":[71,142],"before/after":[72],"28":[74],"(i.e.":[75,81],"5":[76,144],"days)":[77],"6":[80],"2":[82],"weeks)":[83],"as":[84,114],"well.":[85,115],"Full":[86],"factorial":[87],"Analysis":[88],"Variance":[90],"(ANOVA)":[91],"tests":[92],"reviewed":[93],"significant":[94],"differences":[95,148],"migration":[97,171,208],"by":[99],"origin/destination,":[102],"which":[103],"are":[104],"significantly":[106,132],"associated":[107],"with":[108],"cases":[111,151],"Specifically,":[116],"dropped":[119],"proportionally":[120],"after":[121],"regardless":[124],"origin":[126],"location,":[127],"but":[128],"Hubei":[129,216],"destination":[130],"was":[131],"lower":[133],"than":[134,153],"non-Hubei":[135],"destination.":[136],"The":[137,179,219],"assuming":[139,173],"an":[140],"days":[145,158,176],"differentiated":[146],"better":[152],"14":[157],"model.":[159],"Spatiotemporal":[160],"cluster":[161],"analysis":[162],"identified":[163],"multiple":[164],"space-time":[165],"windows":[166],"that":[167,232],"related":[169,205],"trajectory":[172],"a":[174],"5\u201314":[175],"period.":[178],"pre-lockdown":[180],"clusters":[181,202],"due":[182],"traveler\u2019s":[184],"outflow":[185],"Wuhan":[187],"those":[189],"megacities":[190],"pathways":[193],"for":[194,235],"international":[195],"transmission":[196],"COVID-19,":[198],"whereas":[199],"post-lockdown":[201],"partially":[204],"especially":[210],"within":[211],"eastern":[213],"part":[214],"around":[217],"Wuhan.":[218],"revealed":[222],"presence":[228],"super":[230],"spreaders":[231],"responsible":[234],"regional":[236],"spreading":[237],"at":[238],"early":[240],"stage":[241],"caused":[243],"local":[244],"outbreaks":[245],"in":[246],"latter":[248],"stage.":[249]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4}],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2025-10-10T00:00:00"}