Abstract
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 km2 grids 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.
Highlights
We use data on human mobility derived through mobile applications to explore the activity patterns in the neighbourhoods of Greater London as they emerged from the first wave of national lockdown measures in summer 2020
The broader theme of this study is to demonstrate the potentialities of novel sources of data, such as the location data captured by smartphone apps, during public health crises
This article offers an early example of utilising location data captured through mobile applications to study short-term changes in population activity dynamics during the COVID-19 lockdown
Summary
We use data on human mobility derived through mobile applications to explore the activity patterns in the neighbourhoods of Greater London as they emerged from the first wave of national lockdown measures in summer 2020. The spatial and temporal granularity and the timeliness of the activity data enable detailed exploration of the mobility characteristics of a range of geodemographic groups and retail environments. The use of smartphone data in public health crises. Digital data sources that provide timely information about human behaviour, especially on mobility and the physical co-presence of people (Oliver et al, 2020), are of particular value in public health crises as official data and reliable forecasts are often scarce (Ienca and Vayena, 2020). The spatial granularity of the mobile data allows an in-depth understanding of the spatial disparities in human activity patterns during crises
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