Mining Google and Apple mobility data: Temporal Anatomy for COVID-19 Social Distancing

TL;DR

This study analyzes Google and Apple mobility data to identify social distancing patterns during COVID-19's first wave, revealing a consistent decrease in infection rates following mobility reductions across Europe and the US.

Contribution

It introduces a data-driven method to quantify social distancing independently of political measures using mobility data.

Findings

Mobility reduction correlates with decreased infection rates.

Social distancing periods are identifiable from mobility data.

Temporal lag between mobility decrease and infection rate decline.

Abstract

We employ the Google and Apple mobility data to identify, quantify and classify different degrees of social distancing and characterise their imprint on the first wave of the COVID-19 pandemic in Europe and in the United States. We identify the period of enacted social distancing via Google and Apple data, independently from the political decisions. Interestingly we observe a general decrease in the infection rate occurring two to five weeks after the onset of mobility reduction for the European countries and the American states.