Understanding COVID-lockdowns through urban management systems: a novel application of administrative data

References

• Aktay, A., Bavadekar, S., Cossoul, G., Davis, J., Desfontaines, D., Fabrikant, A.,Gabrilovich, E., Gadepalli, K., Gipson, B., Guevara, M., Kamath, C., Kansal, M., Lange, A., Mandayam, C., Oplinger, A., Pluntke, C., Roessler, T., Schlosberg, A., Shekel, T., Vispute, S., Vu, M., Wellenius, G. A., Williams, B. and Wilson, R. J. (2020). Google COVID-19 community mobility reports: anonymization process description (version 1.0). ArXiv, abs/2004.04145.
   Google Scholar
• Aloi, A., Alonso, B., Benavente, J., Cordera, R., Echániz, E., González, F., Ladisa, C. … Lezama-Romanelli, R., López-Parra, Á., Mazzei, V., Perrucci, L., Prieto-Quintana, D., Rodríguez, A, E, S. R. (2020). Affects of the COVID-19 lockdown on urban mobility: Empirical evidence from the city of Santander (Spain). Sustainability: Science, Practice and Policy, 12(9), 3870. https://doi.org/10.3390/su12093870
   Google Scholar
• Arellana, J., Márquez, L., & Cantillo, V. (2020). COVID-19 outbreak in Colombia: An analysis of its impacts on transport systems. Journal of Advanced Transportation, 2020, 8867316. https://doi.org/10.1155/2020/8867316
   Web of Science ®Google Scholar
• Arimura, M., Ha, T. V., Okumura, K., & Asada, T. (2020). Changes in urban mobility in Sapporo city, Japan due to the Covid-19 emergency declarations. Transportation Research Interdisciplinary Perspectives, 7, 100212. https://doi.org/10.1016/j.trip.2020.100212
   PubMedGoogle Scholar
• Askarizad, R., Jinliao, H., & Jafari, S. (2021). The influence of COVID-19 on the societal mobility of urban spaces. Cities, 119, 103388. https://doi.org/10.1016/j.cities.2021.103388
   PubMed Web of Science ®Google Scholar
• BBC News. (2020). Coronavirus: Outbreak investigated at Motherwell contact tracing centre. https://www.bbc.co.uk/news/uk-scotland-glasgow-west-53465160 Retrieved August 30, 2022.
   Google Scholar
• Bereitschaft, B., & Scheller, D. (2020). How might the COVID-19 pandemic affect 21st century urban design, planning, and development? Urban Science, 4(4), 56. Retrieved from, https://www.mdpi.com/2413-8851/4/4/56
   Google Scholar
• Binns, R., Lyngs, U., & Van Kleek, M. (2018 May). Third party tracking in the mobile ecosystem. Proceedings of the 10th ACM conference on web science, Amsterdam, The Netherlands, 22–24.
   Google Scholar
• Bland, A. (2020 11 July). Leicester factory put lives at risk during lockdown, claims garment worker. The Guardian, (https://www.theguardian.com/uk-news/2020/jul/11/leicester-factory-put-lives-at-risk-during-coronavirus-lockdown-claims-garment-worker), Retrieved August 8, 2022.
   Google Scholar
• Bovaird, T., Van Ryzin, G. G., Loeffler, E., & Parrado, S. (2015). Activating citizens to participate in collective co-production of public services. Journal of Social Policy, 44(1), 1–23. https://doi.org/10.1017/S0047279414000567
   Web of Science ®Google Scholar
• Bowyer, R. C. E., Varsavsky, T., Thompson, E. J., Sudre, C. H., Murray, B. A. K., Freidin, M. B., Yarand, D., Ganesh, S., Capdevila, J., Bakker, E., Cardoso, M. J., Davies, R., Wolf, J., Spector, T. D., Ourselin, S., Steves, C. J. , and Menni, C. (2021). Geo-social gradients in predicted COVID-19 prevalence in Great Britain: Results from 1 960 242 users of the COVID-19 Symptoms Study app. Thorax, 76(7), 723–725. https://doi.org/10.1136/thoraxjnl-2020-215119
   PubMed Web of Science ®Google Scholar
• Chapman, C., & Bomford, K. (2020). Litter in lockdown: A study of litter in the time of coronavirus: CPRE https://www.cpre.org.uk/wp-content/uploads/2020/12/Litter-in-lockdown-full-report-December-2020.pdf Retrieved September 23, 2022.
   Google Scholar
• Criado Perez, C. (2020). Invisible Women. Vintage.
   Google Scholar
• Degirmenci, K. (2020). Mobile users’ information privacy concerns and the role of app permission requests. International Journal of Information Management, 50, 261–272. https://doi.org/10.1016/j.ijinfomgt.2019.05.010
   Web of Science ®Google Scholar
• Department for Transport. (2020). Transport use during the coronavirus (COVID-19) pandemic. https://www.gov.uk/government/statistics/transport-use-during-the-coronavirus-covid-19-pandemic: Retrieved October 18, 2021
   Google Scholar
• Derges, J., Lynch, R., Clow, A., Petticrew, M., & Draper, A. (2012). Complaints about dog faeces as a symbolic representation of incivility in London, UK: A qualitative study. Critical Public Health, 22(4), 419–425. https://doi.org/10.1080/09581596.2012.710738
   PubMed Web of Science ®Google Scholar
• Dingel, J. I., & Neiman, B. (2020). How many jobs can be done at home? National Bureau of Economic Research Working Paper 26948.
   Google Scholar
• Douglas, M., Higgins, M., Austin, H., Armour, G., Jepson, R., Thomson, H., & Hurley, F. (2018). Health and transport: A guide. Scottish Health and Inequalities Impact Assessment Network.
   Google Scholar
• Enoch, M., Monsuur, F., Palaiologou, G., Quddus, M. A., Ellis-Chadwick, F., Morton, C., & Rayner, R. (2022). When COVID-19 came to town: Measuring the impact of the coronavirus pandemic on footfall on six high streets in England. Environment and Planning B: Urban Analytics and City Science, 49(3), 1091–1111. https://doi.org/10.1177/23998083211048497
   PubMedGoogle Scholar
• Fancourt, D., Bu, F., Mak, H. W., & Steptoe, A. (2020a). Covid-19 social study: Results release 11. UCL.
   Google Scholar
• Fancourt, D., Bu, F., Mak, H. W., & Steptoe, A. (2020b). Covid-19 social study: Results release 6. UCL.
   Google Scholar
• Fancourt, D., Steptoe, A., & Wright, L. (2020). The Cummings effect: Politics, trust, and behaviours during the COVID-19 pandemic. The Lancet, 396(10249), 464–465. https://doi.org/10.1016/S0140-6736(20)31690-1
   PubMed Web of Science ®Google Scholar
• Fatmi, M. R. (2020). COVID-19 impact on urban mobility. Journal of Urban Management, 9(3), 270–275. https://doi.org/10.1016/j.jum.2020.08.002
   Web of Science ®Google Scholar
• Findlay, A., & Sparks, L. (2012). Far from the ‘Magic of the Mall’: Retail (Change) in ‘Other Places’. Scottish Geographical Journal, 128(1), 24–41. https://doi.org/10.1080/14702541.2012.677058
   Web of Science ®Google Scholar
• Google Inc. (2020). COVID-19 Covid Mobility Reports. https://www.google.com/covid19/mobility/: Retrieved October 11, 2022.
   Google Scholar
• Hastings, A., Matthews, P., & Wang, Y. (2021). 'Unequal and Gendered: Assessing the Impacts of Austerity Cuts on Public Service Users'. Social Policy and Society, 1–21. https://doi.org/10.1017/S1474746421000543
   Web of Science ®Google Scholar
• Jay, J., Bor, J., Nsoesie, E. O., Lipson, S. K., Jones, D. K., Galea, S., & Raifman, J. (2020). Neighbourhood income and physical distancing during the COVID-19 pandemic in the United States. Nature Human Behaviour, 4(12), 1294–1302. https://doi.org/10.1038/s41562-020-00998-2
   PubMed Web of Science ®Google Scholar
• Jones, C., & Livingstone, N. (2018). The ‘online high street’ or the high street online? The implications for the urban retail hierarchy. The International Review of Retail, Distribution and Consumer Research, 28(1), 47–63. https://doi.org/10.1080/09593969.2017.1393441
   Web of Science ®Google Scholar
• King, S., & Cotterill, S. (2007). Transformational Government? The role of information technology in delivering citizen-centric local public services. Local Government Studies, 33(3), 333–354. https://doi.org/10.1080/03003930701289430
   Web of Science ®Google Scholar
• Kitchin, R. (2014). The real-time city? Big data and smart urbanism. GeoJournal, 79(1), 1–14. https://doi.org/10.1007/s10708-013-9516-8
   Google Scholar
• Kitchin, R., Lauriault, T. P., & McArdle, G. (2015). Knowing and governing cities through urban indicators, city benchmarking and real-time dashboards. Regional Studies, Regional Science, 2(1), 6–28. https://doi.org/10.1080/21681376.2014.983149
   Web of Science ®Google Scholar
• Lee, C., & Moudon, A. V. (2004). Physical activity and environment research in the health field: Implications for urban and transportation planning practice and research. Journal of Planning Literature, 19(2), 147–181. https://doi.org/10.1177/0885412204267680
   Web of Science ®Google Scholar
• Levine, J. R., & Gershenson, C. (2014). From political to material inequality: Race, immigration, and requests for public goods. Sociological Forum, 29(3), 607–627. https://doi.org/10.1111/socf.12106
   Web of Science ®Google Scholar
• Li, R., & Huang, Y. (2022). COVID-19 pandemic and minority health disparities in New York City: A spatial and temporal perspective. Environment and Planning B: Urban Analytics and City Science, 0(0), 23998083221126525. https://doi.org/10.1177/23998083221126525
   Google Scholar
• Matthews, P., Rae, A., Nyanzu, E., & Parsons, A. (2022). Accepted for publication). Dog fouling and pot-holes: Understanding the role of coproducing “citizen sensors” in local governance. Local Government Studies.
   Google Scholar
• McCool, M. (2021). Glasgow: The city that has been locked down for nine months. BBC News Online, https://www.bbc.co.uk/news/uk-scotland-glasgow-west-57272876 (Retrieved August 30, 2020).
   Google Scholar
• Minkoff, S. L. (2015). NYC 311: A tract-level analysis of citizen-government contacting in New York City. Urban Affairs Review, 52(2), 211–246. https://doi.org/10.1177/1078087415577796
   Web of Science ®Google Scholar
• Molloy, J., Schatzmann, T., Schoeman, B., Tchervenkov, C., Hintermann, B., & Axhausen, K. W. (2021). Observed impacts of the Covid-19 first wave on travel behaviour in Switzerland based on a large GPS panel. Transport Policy, 104, 43–51. https://doi.org/10.1016/j.tranpol.2021.01.009
   PubMed Web of Science ®Google Scholar
• Mongey, S., & Weinberg, A. (2020). Characteristics of workers in low work-from-home and high personal-proximity occupations. White Paper, Becker Friedman Institute. https://bfi.uchicago.edu/wp-content/uploads/BFI_White-Paper_Mongey_3.2020.pdf Retrieved February 22, 2023.
   Google Scholar
• Noble, M., Wright, G., Smith, G., & Dibben, C. (2006). Measuring multiple deprivation at the small-area level. Environment & planning A, 38(1), 169–185.
   Web of Science ®Google Scholar
• NOMIS. 2021. Labour market proFILE - North Lanarkshire. Retrieved September 23, 2022 https://www.nomisweb.co.uk/reports/lmp/la/1946157426/report.aspx
   Google Scholar
• O’Brien, D. T., Offenhuber, D., Baldwin-Philippi, J., Sands, M., & Gordon, E. (2017). Uncharted territoriality in coproduction: The motivations for 311 reporting. Journal of Public Administration Research and Theory, 27(2), 320–335. https://doi.org/10.1093/jopart/muw046
   Web of Science ®Google Scholar
• OECD. (2021). OECD employment outlook 2021: Navigating the COVID-19 crisis and recovery. https://www.oecd-ilibrary.org/sites/5a700c4b-en/1/2/1/index.html?itemId=/content/publication/5a700c4b-en&_csp_=d31326a7706c58707d6aad05ad9dc5ab&itemIGO=oecd&itemContentType=book#section-d1e1951: Retrieved September 23, 2022.
   Google Scholar
• Ofcom. (2021). Online Nation 2021 Report https://www.ofcom.org.uk/__data/assets/pdf_file/0013/220414/online-nation-2021-report.pdf: 18 October. 2021.
   Google Scholar
• Offenhuber, D. (2015). Infrastructure legibility—a comparative analysis of open311-based citizen feedback systems. Cambridge Journal of Regions, Economy and Society, 8(1), 93–112. https://doi.org/10.1093/cjres/rsu001
   Web of Science ®Google Scholar
• Office for National Statistics. (2020a). Coronavirus and travel to work: June. 2020. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/articles/coronavirusandtraveltowork/june2020: Accessed 18 October 2021
   Google Scholar
• Office for National Statistics. (2020b). Coronavirus and the social impacts on Great. Britain:May. 13 November. 2020. https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/healthandwellbeing/bulletins/coronavirusandthesocialimpactsongreatbritain/13november2020: Accessed 18 October 2020.
   Google Scholar
• Pepe, E., Bajardi, P., Gauvin, L., Privitera, F., Lake, B., Cattuto, C., & Tizzoni, M. (2020). COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown. Scientific Data, 7(1), 230. https://doi.org/10.1038/s41597-020-00575-2
   PubMed Web of Science ®Google Scholar
• Phillips, J., Walford, N., Hockey, A., & Sparks, L. (2021). Older people, town centres and the revival of the ‘high street’. Planning Theory & Practice, 22(1), 11–26. https://doi.org/10.1080/14649357.2021.1875030
   Web of Science ®Google Scholar
• Platt, L. (2021). COVID-19 and ethnic inequalities in England. LSE Public Policy Review, 1(4). https://doi.org/10.31389/lseppr.33
   PubMedGoogle Scholar
• Porter, L. (2020). The places we liVE, June 2020. Planning Theory & Practice, 21(4), 593–630. https://doi.org/10.1080/14649357.2020.1802922
   Web of Science ®Google Scholar
• Raento, M., Oulasvirta, A., & Eagle, N. (2009). Smartphones: An emerging tool for social scientists. Sociological Methods & Research, 37(3), 426–454. https://doi.org/10.1177/0049124108330005
   Web of Science ®Google Scholar
• Rogers, D., Herbert, M., Whitzman, C., McCann, E., Maginn, P. J., Watts, B., Alam, A., Pill, M., Keil, R., Dreher, T., Novacevski, M., Byrne, J., Osborne, N., Büdenbender, M., Alizadeh, T., Murray, K., Dombroski, K., Prasad, D., Connolly, C., Kass, A., Dale, E., Murray, C. and Caldis, S. (2020). The city under COVID-19: Podcasting as digital methodology. Tijdschrift Voor Economische En Sociale Geografie, 111(3), 434–450. https://doi.org/10.1111/tesg.12426
   PubMed Web of Science ®Google Scholar
• Scottish Government. (2020). Localised restrictions extended to Lanarkshire https://www.gov.scot/news/localised-restrictions-extended-to-lanarkshire/(Retrieved August 30, 2022.
   Google Scholar
• Sinclair, M., Maadi, S., Zhao, Q., Hong, J., & Bailey, N. (2022). Understanding the socio-demographic representation of Tamoco mobile phone app data in Glasgow City Region. 30th Annual Geographical Information Science Research UK (GISRUK), 5-8 April 2022, Liverpool, United Kingdom, https://doi.org/10.5281/zenodo.6411683.
   Google Scholar
• Song, H., McKenna, R. M., Chen, A. T., David, G., & Smith McLalle, A. (2021). The impact of the non-essential business closure policy on covid-19 infection rates. NBER Working Paper No 28374.
   Google Scholar
• SPICE. (n.d.). Timeline of Coronavirus (COVID-19) in Scotland. https://spice-spotlight.scot/2021/10/08/timeline-of-coronavirus-covid-19-in-scotland/: Retrieved October 20, 2021.
   Google Scholar
• Thompson, S., & Warzel, C. (201919 December). Twelve million phones, one dataset, zero privacy. New York Times (https://www.nytimes.com/interactive/2019/12/19/opinion/location-tracking-cell-phone.html), Retrieved August 23, 2022.
   Google Scholar
• Trasberg, T., & Cheshire, J. (2021). Spatial and social disparities in the decline of activities during the COVID-19 lockdown in Greater London. Urban Studies, 0(0), 00420980211040409. https://doi.org/10.1177/00420980211040409
   Google Scholar
• Tumminelli O’Brien, D., Sampson, R. J., & Winship, C. (2015). Ecometrics in the Age of Big Data. Sociological Methodology, 45(1), 101–147. https://doi.org/10.1177/0081175015576601
   Google Scholar
• White, A., & Trump, K. -S. (2018). The promises and pitfalls of 311 data. Urban Affairs Review, 54(4), 794–823. https://doi.org/10.1177/1078087416673202
   Web of Science ®Google Scholar
• Wright, L., Steptoe, A., & Fancourt, D. (2020a). Are we all in this together? Longitudinal assessment of cumulative adversities by socioeconomic position in the first 3 weeks of lockdown in the UK. Journal of Epidemiology and Community Health, 74(9), 683. https://doi.org/10.1136/jech-2020-214475
   PubMed Web of Science ®Google Scholar
• Wright, L., Steptoe, A., & Fancourt, D. (2020b). Are we all in this together? Longitudinal assessment of cumulative adversities by socioeconomic position in the first 3 weeks of lockdown in the UK. Journal of Epidemiology and Community Health, 74(9), 683–688. https://doi.org/10.1136/jech-2020/214475
   PubMed Web of Science ®Google Scholar
• Wrigley, N., & Dolega, L. (2011). Resilience, fragility, and adaptation: New evidence on the performance of UK high streets during global economic crisis and its policy implications. Environment and Planning A: Economy and Space, 43(10), 2337–2363. https://doi.org/10.1068/a44270
   Web of Science ®Google Scholar
• Wu, W. -N. (2020). Determinants of citizen-generated data in a smart city: Analysis of 311 system user behavior. Sustainable Cities and Society, 59, 102167. https://doi.org/10.1016/j.scs.2020.102167
   Web of Science ®Google Scholar
• Xu, C. K., & Tang, T. (2020). Closing the gap or widening the divide: The impacts of technology-enabled coproduction on equity in public service delivery. Public Administration Review, 80(6), 962–975. https://doi.org/10.1111/puar.13222
   Web of Science ®Google Scholar
• Yin, R. (2003). Case study research: Design and methods (3rd ed.). Sage.
   Google Scholar
• Zhou, Y., Xu, R., Hu, D., Yue, Y., Li, Q., & Xia, J. (2020). Effects of human mobility restrictions on the spread of COVID-19 in Shenzhen, China: A modelling study using mobile phone data. Lancet Digital Health, 2(8), e417–424. https://doi.org/10.1016/S2589-7500(20)30165-5
   PubMedGoogle Scholar