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Article: Identification of superspreading environment under COVID-19 through human mobility data

TitleIdentification of superspreading environment under COVID-19 through human mobility data
Authors
Issue Date2021
PublisherNature Research: Fully open access journals. The Journal's web site is located at http://www.nature.com/srep/index.html
Citation
Scientific Reports, 2021, v. 11, p. article no. 4699 How to Cite?
AbstractCOVID-19 reaffirms the vital role of superspreaders in a pandemic. We propose to broaden the research on superspreaders through integrating human mobility data and geographical factors to identify superspreading environment. Six types of popular public facilities were selected: bars, shopping centres, karaoke/cinemas, mega shopping malls, public libraries, and sports centres. A historical dataset on mobility was used to calculate the generalized activity space and space–time prism of individuals during a pre-pandemic period. Analysis of geographic interconnections of public facilities yielded locations by different classes of potential spatial risk. These risk surfaces were weighed and integrated into a “risk map of superspreading environment” (SE-risk map) at the city level. Overall, the proposed method can estimate empirical hot spots of superspreading environment with statistical accuracy. The SE-risk map of Hong Kong can pre-identify areas that overlap with the actual disease clusters of bar-related transmission. Our study presents first-of-its-kind research that combines data on facility location and human mobility to identify superspreading environment. The resultant SE-risk map steers the investigation away from pure human focus to include geographic environment, thereby enabling more differentiated non-pharmaceutical interventions and exit strategies to target some places more than others when complete city lockdown is not practicable.
Persistent Identifierhttp://hdl.handle.net/10722/297248
ISSN
2023 Impact Factor: 3.8
2023 SCImago Journal Rankings: 0.900
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLoo, BPY-
dc.contributor.authorTsoi, KH-
dc.contributor.authorWong, PPY-
dc.contributor.authorLai, PC-
dc.date.accessioned2021-03-08T07:16:16Z-
dc.date.available2021-03-08T07:16:16Z-
dc.date.issued2021-
dc.identifier.citationScientific Reports, 2021, v. 11, p. article no. 4699-
dc.identifier.issn2045-2322-
dc.identifier.urihttp://hdl.handle.net/10722/297248-
dc.description.abstractCOVID-19 reaffirms the vital role of superspreaders in a pandemic. We propose to broaden the research on superspreaders through integrating human mobility data and geographical factors to identify superspreading environment. Six types of popular public facilities were selected: bars, shopping centres, karaoke/cinemas, mega shopping malls, public libraries, and sports centres. A historical dataset on mobility was used to calculate the generalized activity space and space–time prism of individuals during a pre-pandemic period. Analysis of geographic interconnections of public facilities yielded locations by different classes of potential spatial risk. These risk surfaces were weighed and integrated into a “risk map of superspreading environment” (SE-risk map) at the city level. Overall, the proposed method can estimate empirical hot spots of superspreading environment with statistical accuracy. The SE-risk map of Hong Kong can pre-identify areas that overlap with the actual disease clusters of bar-related transmission. Our study presents first-of-its-kind research that combines data on facility location and human mobility to identify superspreading environment. The resultant SE-risk map steers the investigation away from pure human focus to include geographic environment, thereby enabling more differentiated non-pharmaceutical interventions and exit strategies to target some places more than others when complete city lockdown is not practicable.-
dc.languageeng-
dc.publisherNature Research: Fully open access journals. The Journal's web site is located at http://www.nature.com/srep/index.html-
dc.relation.ispartofScientific Reports-
dc.rightsScientific Reports. Copyright © Nature Research: Fully open access journals.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleIdentification of superspreading environment under COVID-19 through human mobility data-
dc.typeArticle-
dc.identifier.emailLoo, BPY: bpyloo@hku.hk-
dc.identifier.emailTsoi, KH: kahotsoi@hku.hk-
dc.identifier.emailLai, PC: pclai@hku.hk-
dc.identifier.authorityLoo, BPY=rp00608-
dc.identifier.authorityLai, PC=rp00565-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1038/s41598-021-84089-w-
dc.identifier.pmid33633273-
dc.identifier.pmcidPMC7907097-
dc.identifier.scopuseid_2-s2.0-85101772932-
dc.identifier.hkuros321661-
dc.identifier.volume11-
dc.identifier.spagearticle no. 4699-
dc.identifier.epagearticle no. 4699-
dc.identifier.isiWOS:000626621800059-
dc.publisher.placeUnited Kingdom-

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