Abstract
COVID-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.
Highlights
COVID-19 reaffirms the vital role of superspreaders in a pandemic
There is evidence to support both H1 and H2 for two types of public facilities: bars and small-medium shopping centers. These public facilities were associated with users with higher activity space (AS) and space–time prism (STP), especially when they existed in high facility agglomerations and in urban areas (Class 1 potential spatial risk (PSR) in Group A, Table 1)
Our results show that this second group of public facilities was associated with users of higher AS and STP but in areas with lower facility agglomeration (Class 1 PSR in Group B, Table 1), perhaps suggesting a lack of similar types of provision in the wider communities
Summary
COVID-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. Analysis of geographic interconnections of public facilities yielded locations by different classes of potential spatial risk. Two scenarios of spatial spread could result, assuming that 80% of all infected cases was caused by superspreaders[1], and the transmission rates of super versus non-super spreaders were modelled at ten and two respectively; where these values may be adjusted according to updated and realistic estimates gathered from field data. We argue that a community/district with mobile population must possess certain amenities or services to turn it into a superspreading environment This is analogous to Losch modified Christaller’s central place t heory[9], which suggests the locations of retail in urban areas attract people/consumers to purchase goods and services they need (see Supplemental Methods S1.1). The combined characteristics of higher spatial agglomeration of retail activities and expanse transportation can serve as a proxy for superspreading environment
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
