Quantifying the impact of social activities on SARS-CoV-2 transmission using Google mobility reports.

We developed a new state-space model to investigate which social activities had biggest impact on the spread of SARS-CoV-2. Our analyses suggest that data from four categories of the Google community mobility reports capture an important share of transmission-relevant social activity. The analyses were based on reported hospitalizations and data on vaccinations, temperature, and virus strains. We applied our model to Sweden and Norway on a regional level over 17 months, and to the regions of Berlin and Bavaria in Germany over 10 months. Most results were shared for all three countries: Activity in the four social settings explained between 40-65% of all infections; Public transport appeared as an important setting for infections; and the transmission potential drops by around 40% during summer as compared to winter. However, the analyses for Germany differ in that Retail and recreation was the second activity setting dominating transmission whereas it was contacts at the Workplace in Norway and Sweden, showing how our model is able to adapt to specific cases. Transmissions not captured by the Google data may happen in other settings, in particular in households. In future pandemics, our method could be used in real time to guide more targeted intervention strategies.