Corona and Coffee on your commute: A spatial analysis of COVID-19 mortality and commuting flows in England in 2020

Research output: Contribution to journalArticlepeer-review

Abstract

Background
The COVID-19 pandemic forced governments to implement lockdown policies to curb the spread of the disease. These policies explicitly encouraged homeworking, hence reducing the number of commuters with the implicit assumption that restricting peoples’ movement reduces risk of infection for travellers and other people in their areas of residence and work. Yet, the spatial interrelation of different areas has been rarely addressed both in the public discourse and in early accounts of the various consequences of COVID-19.

Methods
Our study proposes a spatial analysis of the association between commuting flows and COVID-19 mortality in England between March and June 2020, using a range of publicly available area-level data. To account for spatial correlation, we used a structural mobility gravity model to analyse commuting flows between Local Authority Districts. By accounting for these spatial dependencies, we temper concerns of bias and inefficiency affecting simple linear estimates. Additionally, we disentangle the direct and indirect (from other areas) influence of commuting on COVID-19 mortality.

Results
The results of our spatial regression models suggest that higher commuting flows – in general and particularly by public transport - are associated with higher COVID-19 mortality. Our results are consistent with a reduction in COVID-related mortality after the introduction of a national lockdown in March. The spatial-lag term is statistically significant, highlighting the importance of accounting for spatial dependencies.

Conclusion
We suggest that considering spatial interactions through commuting or travel motivations may offer interesting perspectives on the trade-off between health and economic activity during lockdowns.

Bibliographical metadata

Original languageEnglish
Pages (from-to)901–907
JournalEuropean journal of public health
Volume31
Issue number4
Early online date19 Apr 2021
DOIs
Publication statusPublished - 10 May 2021