Figure 2

Types of cities and COVID-19 spreading. Maps with the changes in mobility hotspots before and after the lockdown in three cities with different mobility hierarchy (higher \(\Phi\) indicates more hierarchical cities): (a–c) Atlanta, Chicago and New York City, respectively, in the week of February 2 for pre-lockdown mobility and the week April 5 for the post-lockdown. (d–f) The average Transfer Entropy \(\langle TE \rangle\), capturing the influence of an administrative division (county) to drive infection-spread as a function of time. Vertical red lines mark the date of the official lockdown. After lockdown, the ability of a single region to drive infection spread dissipates, and the transmission evolves independently in each area. (g–i) The temporal evolution of the effective reproduction number before and after lockdown versus the mobility change one week before \(R_{\text {eff}}\) is measured. Each symbol represents a county of the city. While sprawled cities like Atlanta have regions responding independently, in centralized New York City, we see a clear synchronized and monotonically decreasing reduction in \(R_{\text {eff}}\) as a function of mobility reduction.