Author: Cacciapaglia, Giacomo; Cot, Corentin; Sannino, Francesco
Title: Mining Google and Apple mobility data: Twenty-one shades of European social distancing measures for COVID-19 Cord-id: uxyek0g2 Document date: 2020_8_5
ID: uxyek0g2
Snippet: We employ the mobility data released by Google and Apple to investigate the effects of social distancing on the spreading dynamics of COVID-19 in Europe. We identify and quantify different degrees of social distancing and characterise their imprint on the first wave of the pandemic. The analysis allows us to classify countries according to their level of mobility. Furthermore we identify a negative change in the infection rate occurring two to five weeks after the onset of mobility reduction for
Document: We employ the mobility data released by Google and Apple to investigate the effects of social distancing on the spreading dynamics of COVID-19 in Europe. We identify and quantify different degrees of social distancing and characterise their imprint on the first wave of the pandemic. The analysis allows us to classify countries according to their level of mobility. Furthermore we identify a negative change in the infection rate occurring two to five weeks after the onset of mobility reduction for the European countries studied here.
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