The Impact of SARS-COVID-19 Outbreak on European Cities Urban Mobility

The global outbreak of the SARS-COVID-19 pandemic has changed our lives, driving an unprecedented transformation of our habits. In response, the authorities have enforced several measures, including social distancing and travel restrictions that lead to the temporary closure of activities centered around schools, companies, local businesses to those pertaining to the recreation category. As such, with a mobility reduction, the life of our cities during the outbreak changed significantly. In this paper, we aim at drawing attention to this problem and perform an analysis for multiple cities through crowdsensed information available from datasets such as Apple Maps, to shed light on the changes undergone during both the outbreak and the recovery. Specifically, we exploit data characterizing many mobility modes like driving, walking, and transit. With the use of Gaussian Processes and clustering techniques, we uncover patterns of similarity between the major European cities. Further, we perform a prediction analysis that permits forecasting the trend of the recovery process and exposes the deviation of each city from the trend of the cluster. Our results unveil that clusters are not typically formed by cities with geographical ties, but rather on the spread of the infection, lockdown measures, and citizens’ reactions.