Urban form and COVID-19 cases and deaths in Greater London: an urban morphometric approach

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
17 Downloads (Pure)


The COVID-19 pandemic generated a considerable debate in relation to urban density. This is an old debate, originated in mid 19th century’s England with the emergence of public health and urban planning disciplines. While popularly linked, evidence suggests that such relationship cannot be generally assumed. Furthermore, urban density has been investigated in a spatially coarse manner (predominantly at city level) and never contextualised with other descriptors of urban form. In this work, we explore COVID-19 and urban form in Greater London, relating a comprehensive set of morphometric descriptors (including built-up density) to COVID-19 deaths and cases, while controlling for socioeconomic, ethnicity, age and co-morbidity. We describe urban form at individual building level and then aggregate information for official neighbourhoods, allowing for a detailed intra-urban representation. Results show that: (i.) control variables significantly explain more variance of both COVID-19 cases and deaths than the morphometric descriptors; (ii.) of what the latter can explain, built-up density is indeed the most associated, though inversely. The typical London neighbourhood with high levels of COVID-19 infections and deaths resembles a suburb, featuring a low-density urban fabric dotted by larger free-standing buildings and framed by a poorly inter-connected street network.
Original languageEnglish
Pages (from-to)1228-1243
Number of pages16
JournalEnvironment and Planning B: Urban Analytics and City Science
Issue number5
Early online date14 Oct 2022
Publication statusE-pub ahead of print - 14 Oct 2022


  • urban form
  • urban morphometrics
  • COVID-19
  • density
  • Greater London


Dive into the research topics of 'Urban form and COVID-19 cases and deaths in Greater London: an urban morphometric approach'. Together they form a unique fingerprint.

Cite this