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COVID-19 infection outbreaks in Melbourne: what is the role of the built environment? | 119.33 KB |
The COVID-19 pandemic has impacted all regions of the world affecting lives, businesses and disrupting national and regional economies. Inarguably, cities were and continue to remain the epicentre of outbreaks. The global management responses have focused on making changes in the built environment (BE) aimed at reducing crowding, interactions, and movements across cities. As a result, there have been renewed debates about the future of urban planning and BE for developing cities that can promote public health and better cope with outbreaks. To better contribute to shaping the debates, there are growing interests in urban studies about the extent to which BE attributes influence the spread of COVID-19. As cities begin reopening, new research addressing this issue is timely, but this is very limited and particularly non-existent in Australia. Such an understanding is critical for policymaking about how to interact with different aspects of our cities during the recovery phase.
This ongoing research examined the effects of the BE attributes on COVID-19 infections, using metropolitan Melbourne as a case study. Melbourne is the worst affected city in Australia, recording the most infections and COVID-related deaths, and arguably the most locked down city in the world. It recently ended its sixth lockdown which saw the easing of restrictions – including night curfew, limits on movements, shopping hours, social activities, among others – in what is seen to be the boldest step in a road map to reopening.
Understandably, the geography of recent impacts of COVID-19 has ignited research interests in how the BE influenced outbreak especially in North America and Asia. However, these studies are limited in two ways: they mostly focus on international or intercity investigations and/or involves cross-sectional studies in the early period of the pandemic. This study explores the intracity dynamics of Melbourne neighbourhoods using postcode-level data and analysis across three different outbreaks.