Figure 1.

Time evolution of the estimated reproduction number [R_eff(t)] (black lines) and Google mobility data [retail/recreation mobility (continuous blue lines) and public transport mobility (dashed blue lines)] in (A) Ile-de-France and (B) Ireland. The mobility time series were smoothed using a moving average over a 7-day window. In (A), R_eff(t) was computed for two different models that did or did not account for hospital discharges. In the Ile-de-France model with hospital discharges, Pearson's correlation coefficients for retail/recreation mobility and public transport mobility were 0.70 and 0.77, respectively. In the Ile-de-France model without hospital discharges, Pearson's correlation coefficients for retail/recreation mobility and public transport mobility were 0.64 and 0.70, respectively. In Ireland, Pearson's correlation coefficients for retail/recreation mobility and public transport mobility were 0.86 and 0.56, respectively. Figures A2 and A3 (see online supplementary material) show the cross-correlation functions and their significance. Vertical dashed lines indicate the main mitigation measures (lockdown and curfew), and horizontal dashed lines indicate the threshold limit for R_eff(t). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)