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

Abstract

The COVID-19 pandemic led to unprecedented ‘lockdowns’ and stay-at-home orders to prevent the spread of infection. Social scientists have analysed mobility during these lockdowns to understand compliance at a population-level, and whether there were systematic barriers to compliance for certain population groups. Much of this analysis has used mobility data from private companies, gathered via smartphones. In this paper, we consider an unexplored source of such data – urban management administrative data – and demonstrate its usefulness for understanding mobility, and what these patterns might reveal about socio-spatial inequality and local economic activity and suggest greater imagination when analysing such data.

Rights

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

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Identifiers

DOI

https://doi.org/10.1080/21650020.2023.2203217

Repository URI

https://eprints.gla.ac.uk/297885/