We use data on human mobility obtained from mobile applications to explore the activity
patterns in the neighbourhoods of Greater London as they emerged from the first wave of
COVID-19 lockdown restrictions during summer 2020 and analyse how the lockdown guidelines
have exposed the socio-spatial fragmentation between urban communities. The location data
are spatially aggregated to 1 km2grids and cross-checked against publicly
available mobility metrics (e.g. Google COVID-19 Community Report, Apple Mobility Trends
Report). They are then linked to geodemographic classifications to compare the average
decline of activities in the areas with different sociodemographic characteristics. We
found that the activities in the deprived areas dominated by minority groups declined less
compared to the Greater London average, leaving those communities more exposed to the
virus. Meanwhile, the activity levels declined more in affluent areas dominated by
white-collar jobs. Furthermore, due to the closure of non-essential stores, activities
declined more in premium shopping destinations and less in suburban high streets.