Anonymised and aggregated crowd level mobility data from mobile phones suggests that initial compliance with COVID-19 social distancing interventions was high and geographically consistent across the UK

Abstract

Background: Since early March 2020, the COVID-19 epidemic across the United Kingdom has led to a range of social distancing policies, which have resulted in reduced mobility across different regions. Crowd level data on mobile phone usage can be used as a proxy for actual population mobility patterns and provide a way of quantifying the impact of social distancing measures on changes in mobility. Methods: Here, we use two mobile phone-based datasets (anonymised and aggregated crowd level data from O2 and from the Facebook app on mobile phones) to assess changes in average mobility, both overall and broken down into high and low population density areas, and changes in the distribution of journey lengths. Results: We show that there was a substantial overall reduction in mobility, with the most rapid decline on the 24th March 2020, the day after the Prime Minister's announcement of an enforced lockdown. The reduction in mobility was highly synchronized across the UK. Although mobility has remained low since 26th March 2020, we detect a gradual increase since that time. We also show that the two different datasets produce similar trends, albeit with some location-specific differences. We see slightly larger reductions in average mobility in high-density areas than in low-density areas, with greater variation in mobility in the high-density areas: some high-density areas eliminated almost all mobility. Conclusions: These analyses form a baseline from which to observe changes in behaviour in the UK as social distancing is eased and inform policy towards the future control of SARS-CoV-2 in the UK.

Keywords: Covid-19; Mobile Phone; Mobility; SARS-CoV-2; United Kingdom.

Figure 1.

Rapid reduction in mobility in the UK from the 18th March 2020 ( A) through to the 26th March ( I). Colour shows percentage change in daily number of journeys compared to the mean in the week 10th-16th March 2020 inclusive, by origin tiles that consistently reported data each day. Sufficient data were not available for tiles in the grey area. Note that (C) and (D) are weekend days and there was an increase in overall mobility on the 23rd March (see also Figure 2).

Figure 2.. Consistent changes in mobility observed between Facebook data and mobile phone data.

Change in movement over time as a percentage of baseline movement for the four home countries within the UK and their largest city for Facebook data (blue) and mobile phone data (red). Baseline movement defined as the mean number of journeys starting within a small unit within each city from 10th-16th March 2020 inclusive. The dashed vertical line at 23rd March indicates when the most stringent lockdown measures were imposed.

Figure 3.. Fit of the segmented-linear model with 5 breakpoints to the percentage relative to baseline of number of trips against time (top panel).

Weekdays (blue), Saturdays (red), Sundays (orange) and bank holidays (purple). Bottom panel shows univariate 95% confidence regions for each breakpoint.

Figure 4.. We ranked each UK local authority district by population density and determined the corresponding quartile for each local authority district, with lower population density in quartile 1 and higher population density in quartile 4.

The shaded region is the range of percentage differences in journeys made at each time point for both lower quantile (low population density) and upper quantile (high population density) using the mobile data. Solid lines are the median difference from baseline within each quartile. The dashed line on 23rd March is when the most stringent lockdown measures were imposed.

Figure 5.. Distribution of mean journey lengths per LAD on each Wednesday in the Facebook data for areas of increasing population density.

( A– D) Journey length distributions for each quartile of population density from lowest ( A) to highest ( D). The y axis is on a log10 scale and the median and interquartile range for each distribution is shown by the horizontal lines. A Gaussian kernel is used to define the shape of the distributions which are truncated at the minimum and maximum point in the data.