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Domestic and international mobility trends in the United Kingdom during the COVID-19 pandemic: An analysis of Facebook data (preprint)
medrxiv; 2021.
Preprint
in English
| medRxiv | ID: ppzbmed-10.1101.2021.08.03.21261545
ABSTRACT
Since early March 2020, the COVID-19 epidemic across the United Kingdom has led to a range of social distancing policies, which resulted in changes to mobility across different regions. An understanding of how these policies impacted travel patterns over time and at different spatial scales is important for designing effective strategies, future pandemic planning and in providing broader insights on the population geography of the country. Crowd level data on mobile phone usage can be used as a proxy for population mobility patterns and provide a way of quantifying in near-real time the impact of social distancing measures on changes in mobility. Here we explore patterns of change in densities, domestic and international flows and co-location of Facebook users in the UK from March 2020 to March 2021. We find substantial heterogeneities across time and region, with large changes observed compared to pre-pandemic patterns. The impacts of periods of lockdown on distances travelled and flow volumes are evident, with each showing variations, but some significant reductions in co-location rates. Clear differences in multiple metrics of mobility are seen in central London compared to the rest of the UK, with each of Scotland, Wales and Northern Ireland showing significant deviations from England at times. Moreover, the impacts of rapid changes in rules on international travel to and from the UK are seen in substantial fluctuations in traveller volumes by destination. While questions remain about the representativeness of the Facebook data, previous studies have shown strong correspondence with census-based data and alternative mobility measures, suggesting that findings here are valuable for guiding strategies.
Full text:
Available
Collection:
Preprints
Database:
medRxiv
Main subject:
COVID-19
Language:
English
Year:
2021
Document Type:
Preprint
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