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spazio aperto

No. 103 (2022)

Covid-19’s spatiotemporal patterns within cities: a global comparative study

  • Emanuele Sciuva
DOI
https://doi.org/10.3280/TR2022-103024OA
Submitted
dicembre 4, 2023
Published
2023-12-19

Abstract

The first confirmed cases of Covid-19 were discovered around the end of 2019 in Wuhan, Hubei Province, China, and the world as we knew it changed from then on. Whereas most of the research has focused on the meso-urban scale, there is only a limited number of studies focusing on the distribution of cases at a spatially granular scale within cities, throughout time. This work aims at filling this gap, by drawing different cities across the globe into a comparative project, where the spread of the pandemic is analysed throughout three distinct ‘waves’ of the pandemic. This study sheds light on the current debate about the variability of results across time and space, and how insights need to be reframed by accounting for the spatiotemporal dynamicity of Covid-19.

References

  1. Almagro M., Orane-Hutchinson A., 2022, «JUE Insight: The determinants of the differential exposure to Covid-19 in New York city and their evolution over time». Journal of Urban Economics, 127: 103293. Doi: 10.1016/j.jue.2020.103293.
  2. de Andrade C.L.T., Pereira C.C.D.A., Martins M., Lima S.M.L., Portela M.C., 2020, «Covid-19 hospitalizations in Brazil’s Unified Health System (SUS)». PLoS One, 15, 12: e0243126. Doi: 10.1371/journal.pone.0243126.
  3. Casti E., 2020, «Geografia a ‘vele spiegate’. Analisi territoriale e mapping riflessivo sul Covid-19 in Italia». Documenti Geografici, 1: 61-83. Doi: 10.19246/DOCUGEO2281-7549/202001_03.
  4. Cliff A.D., Haggett P., 1984, «Island epidemics». Scientific American, 250, 5: 138-147. Doi: 10.1038/scientificamerican0584-138.
  5. Cliff A.D., Haggett P., 2006, «A swash-backwash model of the single epidemic wave». Journal of geographical systems, 8: 227-252. Doi: 10.1007/s10109-006-0027-8.
  6. Cliff A.D., Haggett P., Smallman-Raynor M., 2004, World atlas of epidemic diseases. London: Arnold.
  7. ESRI, 2021, Data classification methods. https://pro.arcgis.com/en/pro-app/latest/help/mapping/layer-properties/data-classification-methods.htm (accessed: 2022.06.06).
  8. Giorgi Rossi P., Marino M., Formisano D., Venturelli F., Vicentini M., Grilli R., Reggio Emilia Covid-19 Working Group, 2020, «Characteristics and outcomes of a cohort of Covid-19 patients in the Province of Reggio Emilia, Italy». PloS one, 15, 8: e0238281. Doi: 10.1371/journal.pone.0238281.
  9. Goldstein P., Levy Yeyati E., Sartorio L., 2021, Lockdown fatigue: The diminishing effects of quarantines on the spread of Covid-19. Cambridge, MA: Center for International Development at Harvard University.
  10. Gould P.R., 1969, «Spatial Diffusion». Association of American Geographers. Washington, dc: Association of American Geographers. Haggett P., 1976, «Hybridizing alternative models of an epidemic diffusion process». Economic Geography, 52, 2: 136-146. Doi: 10.2307/143360.
  11. Haggett P., 2001, Geography: a global synthesis. Harlow: Pearson Education. Haggett P., Cliff A.D., 2003, «The geography of disease distributions». In: Johnston R.J., Williams M. (eds.), A Century of British Geography. Oxford: Oxford University Press, 521-543.
  12. Hagerstrand T., 1967). Innovation diffusion as a spatial process. Chicago, IL: The University of Chicago Press.
  13. Hu M., Roberts J.D., Azevedo G.P., Milner D., 2021, «The role of built and social environmental factors in Covid-19 transmission: A look at America’s capital city». Sustainable Cities and Society, 65: 102580. Doi: 10.1016/j.scs.2020.102580.
  14. Jassat W., Mudara C., Ozougwu L., Tempia S., Blumberg L., Davies M.A., Pillay Y., Carter T., Morewane R., Wolmarans M., von Gottberg A., 2021, «Difference in mortality among individuals admitted to hospital with Covid-19 during the first and second waves in South Africa: A cohort study». The Lancet Global Health, 9, 9: e1216-e1225. Doi: 10.11604/pamj.2023.45.5.39222.
  15. Kim S.J., Bostwick W., 2020, «Social vulnerability and racial inequality in Covid-19 deaths in Chicago». Health Education & Behavior, 47, 4: 509-513. Doi: 10.1177/1090198120929677.
  16. Li B., Peng Y., He H., Wang M., Feng T., 2021, «Built environment and early infection of Covid-19 in urban districts: A case study of Huangzhou». Sustainable Cities and Society, 66: 102685. Doi: 10.1016/j.scs.2020.102685.
  17. Li S.L., Pereira R.H., Prete Jr. C.A., Zarebski A.E., Emanuel L., Alves P.J., Peixoto P.S., Braga C.K., de Souza Santos A.A., de Souza W.M., Barbosa R.J., 2021, «Higher risk of death from Covid-19 in low-income and non-white populations of São Paulo, Brazil». Bmj Global Health, 6,4: e004959. Doi: 10.1136/bmjgh-2021-004959.
  18. Mansour S., Al Kindi A., Al-Said Alkattab, Al-Said Adham, Atkinson P., 2021, «Sociodemographic determinants of Covid-19 incidence rates in Oman: Geospatial modelling using multiscale geographically weighted regression (mgwr)». Sustainable cities and society, 65: 102627. Doi: 10.1016/j. scs.2020.102627.
  19. Maroko A.R., Nash D., Pavilonis B.T., 2020, «Covid-19 and inequity: a comparative spatial analysis of New York City and Chicago hot spots». Journal of Urban Health, 97, 4: 461-470. Doi: 10.1007/s11524-020-00468-0.
  20. McCann E., Ward K., 2011, eds., Mobile urbanism: cities and policymaking in the global age. Minneapolis, mn, University of Minnesota Press.
  21. McFarlane C., 2010, «The comparative city: Knowledge, learning, urbanism». International Journal of Urban and Regional Research, 34, 4: 725- 742. Doi: 10.1111/j.1468-2427.2010.00917.x.
  22. McFarlane C., Robinson J., 2012, «Introduction-experiments in comparative urbanism». Urban Geography, 33, 6: 765-773. Doi: 10.2747/0272-3638.33.6.765.
  23. Morrill R.L., 1970, «The shape of diffusion in space and time». Economic Geography, 46: 259-268. Doi: 10.2307/143143.
  24. Patel J.A., Nielsen F.B.H., Badiani A.A., Assi S., Unadkat V.A., Patel B., Ravindrane R., Wardle H., 2020, «Poverty, inequality and Covid-19: The forgotten vulnerable». Public Health, 183: 110. Doi: 10.1016/j.puhe.2020.05.006.
  25. Rajput A.A., Li Q., Gao X., Mostafavi A., 2022, «Revealing critical characteristics of mobility patterns in New York City during the onset of Covid-19 pandemic». Frontiers in Built Environment, 7: 180. Doi: 10.3389/fbuil.2021.654409.
  26. Ribeiro K.B., Ribeiro A.F., Veras M.A.D.S.M., de Castro M.C., 2021, «Social inequalities and Covid-19 mortality in the city of São Paulo, Brazil». International Journal of Epidemiology, 50, 3: 732-742. Doi: 10.1093/ije/dyab022.
  27. Robinson J., 2002, «Global and world cities: a view from off the map». International Journal of Urban and Regional Research 26, 3: 531-54. Doi: 10.1111/1468-2427.00397.
  28. Robinson J., 2006, Ordinary cities: Between modernity and development. London: Routledge.
  29. Robinson J., 2011, «Cities in a world of cities: The comparative gesture». International Journal of Urban and Regional Research, 35, 1: 1-23. Doi: 10.1111/j.1468-2427.2010.00982.x.
  30. Robinson J., 2016, «Thinking cities through elsewhere: Comparative tactics for a more global urban studies». Progress in Human Geography, 40, 1: 3-29. Doi: 10.1177/0309132515598025.
  31. Roy A., Ong A., 2011, eds., Worlding cities: Asian experiments and the art of being global. Hoboken, nj: John Wiley & Sons.
  32. Ward K., 2008, «Toward a comparative (re)turn in urban studies? Some reflections». Urban Geography, 29, 5: 405-410. Doi: 10.2747/0272-3638.29.5.405.
  33. Wong D.W., 2004, «The modifiable areal unit problem (MUAP)». In: Janelle D.G., Warf B. Hansen K. (eds.), WorldMinds: Geographical perspectives on 100 problems. Dordrecht: Springer, 571-575.
  34. Yin R.K., 2018, Case study research and applications. Thousand Oaks, CA: Sage.
  35. Zhonghua L., Xing B., Xue Z.Z., 2020, «The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (Covid-19) in China». National Center for Biotechnology Information, 41, 2: 145-151. Doi: 10.3760/cma.j.issn.0254-6450.2020.02.003.

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