Our mobility patterns are built upon the spatio-temporal dimensions linked to routines and commuting habits. The Covid-19 pandemic changed these habits more deeply than we think, and some effect is still present. The ascension of new working, studying and shopping modes continue reshaping and changing our behaviour and, consequently, the urban dynamics. This project aims to provide a new understanding of the mechanisms behind the changes in human mobility during the COVID-19 pandemic decoupling our mobility into its space and time components.
To measure spatial mobility, we employ the Radius of Gyration metric, which measures how far people are moving regarding their homes. The further someone travel (i.e. to go shopping, to work, or school), the greater their radius of gyration.
The map on the right shows the average radius of gyration of the UK's local
authorities for 2020 compared to the baseline year of 2019. We can see a
drastic reduction in the spatial mobility levels across all regions in
March 2020 when the first lockdown started.
Our analyses suggest that rural and low-income areas substantially reduced their spatial mobility compared to urban and high-income locations.
For the temporal dimension of mobility, we are interested in synchronised behaviour linked to commuting habits, such as leaving their homes simultaneously to go to work. The proposed mobility synchronisation metrics give a value close to 1 when the population presents a high degree of synchronous mobility patterns. A value close to 0 is returned otherwise. In the examples below, the pulsing indicates the time an event was registered (e.g. someone left their hour to go to work).
The maps illustrate the synchronisation patterns before and during the
pandemic. Note how the pattern during the pandemic is more asynchronous (i.e.
more lights pulsing at different times) than before it started. This result is
linked to a disturbance in our daily habits.
Contrary to the spatial dimension, the temporal one was considerably more decreased in urban and high-income locations than in rural and low-income areas.
Studying how people move around and the timing of their movements helps us identify the impact of mobility restrictions policies depending on where you live and your social and economic levels. These policies can lead to unique movement patterns for each group as people adapt to restrictions and develop new habits such as working and studying from home.
Aggregated mobility data is provided by Spectus, a location intelligence platform. Data is collected from anonymized users who have opted-in to provide access to their location data anonymously, through a CCPA and GDPR-compliant framework. In addition to anonymizing all Device IDs, Spectus obfuscates home locations to Geohash 6 tiles to further preserve privacy. Through its Social Impact program, Spectus provides mobility insights for academic research and humanitarian initiatives. The Spectus responsible data sharing framework enables research partners to query anonymized and privacy-enhanced data, by providing access to an auditable, on-premise Data Cleanroom environment. All final outputs provided to partners are aggregated in order to preserve privacy.