Monitoring social distancing and SARS-CoV-2 transmission in Brazil using cell phone mobility data

Social distancing measures have emerged as the predominant intervention for containing the spread of COVID-19, but evaluating adherence and effectiveness remains a challenge. We assessed the relationship between aggregated mobility data collected from mobile phone users and the time-dependent reproduction number R(t), using severe acute respiratory illness (SARI) cases reported by Sao Paulo and Rio de Janeiro. We found that the proportion of individuals staying home all day (isolation index) had a strong inverse correlation with R(t) (rho<-0.7) and was predictive of COVID-19 transmissibility (p<0.0001). Furthermore, indexs of 46.7% had the highest accuracy (93.9%) to predict R(t) below one. This metric can be monitored in real time to assess adherence to social distancing measures and predict their effectiveness for controlling SARS-CoV-2 transmission.