https://doi.org/10.4081/gh.2022.1022
The impact of geographic mobility on the spread of COVID-19 in Hong Kong
Submitted: 22 May 2021
Accepted: 3 December 2021
Published: 14 February 2022
Accepted: 3 December 2021
Abstract Views: 2624
PDF: 344
HTML: 106
HTML: 106
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
The modern highly globalised economy is jeopardising human health as the increased mobility and interconnectedness has the potential to rapidly transmit pathogens across the globe. This was recently confirmed by the coronavirus disease 2019 outbreak, which quickly led to localised outbreaks in virtually every country. As the existing health systems were unprepared, the world has witnessed a critical shortage of life-supporting and health-sustaining resources. In the absence of effective non-pharmaceutical interventions to suppress the virus transmission, many governments imposed total or partial lockdowns, with devastating economic consequences. The case of Hong Kong in quickly suppressing the virus from spreading can thus be a lesson for all. In this study, open data sources of infected individuals are employed to compile maps of disease incidents at various geographic scales with the aim of better understanding the transmission dynamics and discern spatial variability. Our findings show that tracking human mobility patterns can improve awareness of spatiotemporal factors driving the risks of human exposure to viruses. Moreover, we have demonstrated that spatial tools can be successfully employed to explore connections between individuals and wider communities with the aim of informing adaptation of policies at different spatial scales and for different time periods. As was shown in the case of Hong Kong, disease control encompasses the interrelated tasks of reducing social interactions and encouraging adoption of protective behaviours.
Alvarez FE, Argente D, Lippi F, 2020. A simple planning problem for covid-19 lockdown (No. w26981). National Bureau of Economic Research Working Paper No. 26981. Available from: https://www.nber.org/papers/w26981.pdf Accessed: 10 May 2020.
DOI: https://doi.org/10.3386/w26981
Carlos HA, Shi X, Sargent J, Tanski S, Berke EM, 2010. Density estimation and adaptive bandwidths: a primer for public health practitioners. Int J Health Geograph 9:39.
DOI: https://doi.org/10.1186/1476-072X-9-39
Citymapper, 2020. Citymapper Mobility Index, March 2020 - September 2021. Available from: https://citymapper.com/cmi/hongkong Accessed: 10 May 2020.
ESRI, 2020. ESRI China (Hong Kong) homepage. Available from: https://www.esrichina.hk/en-hk/home Accessed: 10 May 2020.
Haklay M, Singleton A, Parker C, 2008. Web mapping 2.0: The neogeography of the GeoWeb. Geography Compass 2:2011-39.
DOI: https://doi.org/10.1111/j.1749-8198.2008.00167.x
He X, Lau EH, Wu P, Deng X, Wang J, Hao X, Mo X, 2020. Temporal dynamics in viral shedding and transmissibility of COVID-19. Nature Med 1-4.
DOI: https://doi.org/10.1101/2020.03.15.20036707
HKSAR Government, 2020. Latest situation of coronavirus disease (COVID-19) in Hong Kong. Available from: https://chp-dashboard.geodata.gov.hk/covid-19/en.html Accessed: 30 April 2020.
Holmes EA, O’Connor RC, Perry VH, Tracey I, Wessely S, Arseneault L, Ford T, 2020. Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science. Lancet Psychiatr [Epub ahead of print].
DOI: https://doi.org/10.1016/S2215-0366(20)30168-1
Hung LS, 2003. The SARS epidemic in Hong Kong: what lessons have we learned? J R Soc Med 96:374-8.
DOI: https://doi.org/10.1258/jrsm.96.8.374
Ienca M, Vayena E, 2020. On the responsible use of digital data to tackle the COVID-19 pandemic. Nature Med 26:463-4.
DOI: https://doi.org/10.1038/s41591-020-0832-5
Johns Hopkins, 2020. COVID-19 Dashboard. Available from: https://coronavirus.jhu.edu/map.html Accessed: 30 April 2020.
Kraak MJ, 2004. The role of the map in a Web-GIS environment. J Geograph Syst 6:83-93.
DOI: https://doi.org/10.1007/s10109-004-0127-2
Kwan MP, 2000. Interactive geovisualisation of activity-travel patterns using three-dimensional geographical information systems: a methodological exploration with a large data set. Transport Res Part C Emerg Technol 8:185-203.
DOI: https://doi.org/10.1016/S0968-090X(00)00017-6
Lai PC, So FM, Chan KW, 2008. Spatial epidemiological approaches in disease mapping and analysis. CRC Press, Boca Raton, FL, USA.
DOI: https://doi.org/10.1201/9781420045536
Lai PC, Wong CM, Hedley AJ, Lo SV, Leung PY, Kong J, Leung GM, 2004. Understanding the spatial clustering of severe acute respiratory syndrome (SARS) in Hong Kong. Environ Health Perspect 112:1550-6.
DOI: https://doi.org/10.1289/ehp.7117
Lau H, Khosrawipour V, Kocbach P, Mikolajczyk A, Schubert J, Bania J, Khosrawipour T, 2020. The positive impact of lockdown in Wuhan on containing the COVID-19 outbreak in China. J Travel Med 27:taaa037.
DOI: https://doi.org/10.1093/jtm/taaa037
Lau JT, Yang X, Leung PC, Chan Lo, Wong E, Fong C, Tsui HY, 2004. SARS in three categories of hospital workers, Hong Kong. Emerg Infect Dis 10:1399.
DOI: https://doi.org/10.3201/eid1008.040041
Li X, Zhou L, Jia T, Peng R, Fu X, Zou Y, 2020. Associating COVID-19 severity with urban factors: a case study of Wuhan. Int J Environ Res Public Health 17:6712.
DOI: https://doi.org/10.3390/ijerph17186712
MacEachren AM, 2004. How maps work: representation, visualization, and design. Guilford Press, New York, NY, USA.
McCloskey B, Heymann DL, 2020. SARS to novel coronavirus-old lessons and new lessons. Epidemiol Infection 148.
DOI: https://doi.org/10.1017/S0950268820000254
McMichael AJ, Beaglehole R, 2000. The changing global context of public health. Lancet 356:495-9.
DOI: https://doi.org/10.1016/S0140-6736(00)02564-2
Ostrom E, 2010. Polycentric systems for coping with collective action and global environmental change. Global Environ Change 20:550-7.
DOI: https://doi.org/10.1016/j.gloenvcha.2010.07.004
Robinson AC, Demšar U, Moore AB, Buckley A, Jiang B, Field K, Sluter CR, 2017. Geospatial big data and cartography: research challenges and opportunities for making maps that matter. Int J Cartograph 3:32-60.
DOI: https://doi.org/10.1080/23729333.2016.1278151
Romanillos G, GarcÃa-Palomares JC, Moya-Gómez B, Gutiérrez J, Torres J, López M, Herranz R, 2021. The city turned off: Urban dynamics during the COVID-19 pandemic based on mobile phone data. Appl Geograph 134:102524.
DOI: https://doi.org/10.1016/j.apgeog.2021.102524
School of Public Health, The University of Hong Kong (2020). Coronavirus disease (COVID-19). Available from: https://covid19.sph.hku.hk/dashboard Accessed: 30 May 2021.
Scott LM, Janikas MV, 2010. Spatial statistics in ArcGIS. In M.M. Fischer and A. Getis (Eds.), Handbook of applied spatial analysis. Springer, Berlin, Heidelberg, Germany, pp. 27-41.
DOI: https://doi.org/10.1007/978-3-642-03647-7_2
Smith RD, 2006. Responding to global infectious disease outbreaks: lessons from SARS on the role of risk perception, communication and management. Social Sci Med 63:3113-23.
DOI: https://doi.org/10.1016/j.socscimed.2006.08.004
Sui DZ, 2021. The quantum turn for geospatial technologies and Society. In A. Kent (Ed.), The Routledge Handbook of Geospatial Technologies and Society. Routledge, London, UK. [In press].
Ting DSW, Carin L, Dzau V, Wong TY, 2020. Digital technology and COVID-19. Nature Med, 26:459-61.
DOI: https://doi.org/10.1038/s41591-020-0824-5
Vannoni M, McKee M, Semenza JC, Bonell C, Stuckler D, 2020. Using volunteered geographic information to assess mobility in the early phases of the COVID-19 pandemic: a cross-city time series analysis of 41 cities in 22 countries from March 2nd to 26th 2020. Global Health 16:85.
DOI: https://doi.org/10.1186/s12992-020-00598-9
Wong SY, Kwong RS, Wu TC, Chan JWM, Chu MY, Lee SY, Lung DC, 2020. Risk of nosocomial transmission of coronavirus disease 2019: an experience in a general ward setting in Hong Kong. J Hosp Infect 105:119-27.
DOI: https://doi.org/10.1016/j.jhin.2020.03.036
Wood J, Dykes J, Slingsby A, 2010. Visualisation of origins, destinations and flows with OD maps. Cartograph J 47:117-29.
DOI: https://doi.org/10.1179/000870410X12658023467367
How to Cite
Wong, P. P. Y., Low, C.-T., & Lai, P.-C. (2022). The impact of geographic mobility on the spread of COVID-19 in Hong Kong. Geospatial Health, 17(s1). https://doi.org/10.4081/gh.2022.1022
Copyright (c) 2022 the Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
Similar Articles
- Olga De Cos, Valentín Castillo-Salcines, David Cantarero-Prieto, A geographical information system model to define COVID-19 problem areas with an analysis in the socio-economic context at the regional scale in the North of Spain , Geospatial Health: Vol. 17 No. s1 (2022): Special issue on COVID-19
- Chunhui Liu, Xiaodi Su, Zhaoxuan Dong, Xingyu Liu, Chunxia Qiu, Understanding COVID-19: comparison of spatio-temporal analysis methods used to study epidemic spread patterns in the United States , Geospatial Health: Vol. 18 No. 1 (2023)
- Ahmad Raeesi, Behzad Kiani, Azam Hesami, Ladan Goshayeshi, Neda Firouraghi, Shahab MohammadEbrahimi, Soheil Hashtarkhani, Access to the COVID-19 services during the pandemic - a scoping review , Geospatial Health: Vol. 17 No. s1 (2022): Special issue on COVID-19
- I Gede Nyoman Mindra Jaya, Yudhie Andriyana, Bertho Tantular, Post-pandemic COVID-19 estimated and forecasted hotspots in the Association of Southeast Asian Nations (ASEAN) countries in connection to vaccination rate , Geospatial Health: Vol. 17 No. s1 (2022): Special issue on COVID-19
- Peter M. Macharia, Kerry L.M. Wong, Lenka Beňová, Jia Wang, Prestige Tatenda Makanga, Nicolas Ray, Aduragbemi Banke-Thomas, Measuring geographic access to emergency obstetric care: a comparison of travel time estimates modelled using Google Maps Directions API and AccessMod in three Nigerian conurbations , Geospatial Health: Vol. 19 No. 1 (2024)
- Behzad Kiani, Colleen Lau, Robert Bergquist, From Snow’s map of cholera transmission to dynamic catchment boundary delineation: current front lines in spatial analysis , Geospatial Health: Vol. 18 No. 2 (2023)
You may also start an advanced similarity search for this article.
