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COVID-19 in Toronto: A Spatial Exploratory Analysis

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  • Eric Vaz

    (Department of Geography and Environmental Studies, Ryerson University, Toronto, ON M5B 2K3, Canada)

Abstract

COVID-19 has had a significant impact on a global scale. Evident signs of spatial-explicit characteristics have been noted. Nevertheless, publicly available data are scarce, impeding a complete picture of the locational impacts of COVID-19. This paper aimed to assess, confirm, and validate several geographical attributes of the geography of the pandemic. A spatial modeling framework defined whether there was a clear spatial profile to COVID-19 and the key socio-economic characteristics of the distribution in Toronto. A stepwise backward regression model was generated within a geographical information systems framework to establish the key variables influencing the spread of COVID-19 in Toronto. Further to this analysis, spatial autocorrelation was performed at the global and local levels, followed by an error and lag spatial regression to understand which explanatory framework best explained disease spread. The findings support that COVID-19 is strongly spatially explicit and that geography matters in preventing spread. Social injustice, infrastructure, and neighborhood cohesion are evident characteristics of the increasing spread and incidence of COVID-19. Mitigation of incidents can be carried out by intertwining local policies with spatial monitoring strategies at the neighborhood level throughout large cities, ensuring open data and adequacy of information management within the knowledge chain.

Suggested Citation

  • Eric Vaz, 2021. "COVID-19 in Toronto: A Spatial Exploratory Analysis," Sustainability, MDPI, vol. 13(2), pages 1-15, January.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:2:p:498-:d:476043
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    References listed on IDEAS

    as
    1. Kathryn Barber & Duncan MacLellan, 2019. "Examining Open Data at the Urban Level: An Exploration of “Wellbeing Toronto”," Journal of Urban Technology, Taylor & Francis Journals, vol. 26(1), pages 107-121, January.
    2. Vaz, Eric & Tehranchi, Sina & Cusimano, Michael, 2017. "Spatial Assessment of Road Traffic Injuries in the Greater Toronto Area (GTA): Spatial Analysis Framework," Journal of Tourism, Sustainability and Well-being, Cinturs - Research Centre for Tourism, Sustainability and Well-being, University of Algarve, vol. 5(1), pages 37-55.
    3. Andrew Atkeson, 2020. "What Will be the Economic Impact of COVID-19 in the US? Rough Estimates of Disease Scenarios," Staff Report 595, Federal Reserve Bank of Minneapolis.
    4. Vaz, Eric, 2013. "The Spatial Business Landscape of India," Journal of Tourism, Sustainability and Well-being, Cinturs - Research Centre for Tourism, Sustainability and Well-being, University of Algarve, vol. 1(4), pages 241-253.
    5. repec:ris:cieodp:2013_020 is not listed on IDEAS
    6. Michael Batty, 2020. "The Coronavirus crisis: What will the post-pandemic city look like?," Environment and Planning B, , vol. 47(4), pages 547-552, June.
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    Cited by:

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    2. Hassan Adamu & Syaheerah Lebai Lutfi & Nurul Hashimah Ahamed Hassain Malim & Rohail Hassan & Assunta Di Vaio & Ahmad Sufril Azlan Mohamed, 2021. "Framing Twitter Public Sentiment on Nigerian Government COVID-19 Palliatives Distribution Using Machine Learning," Sustainability, MDPI, vol. 13(6), pages 1-21, March.

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