RESUMEN

Over the last months, cases of SARS-CoV-2 surged repeatedly in many countries and could often be controlled with non-pharmaceutical interventions such as social distancing. We analyzed de-identified GPS tracking data from 1.15 to 1.4 million cell phones in Germany per day between March-November 2020 to identify encounters between individuals and statistically evaluate large-scale contact behavior. Using graph sampling theory we estimated the contact index (CI), a metric for number and heterogeneity of contacts and found that the contact index, and not the total number of contacts, is an accurate predsictor for the effective reproduction number R. A high correlation between CI and R occurring more than two weeks later allows timely assessment of the social behavior well before the infections become detectable. The CI quantifies the role of superspreading and allows assigning risks to specific contact behavior. We provide a critical CI-value beyond which R is expected to rise above 1 and propose to use it to leverage the social distancing interventions for the coming months.