Spatial and temporal synchronization

A meta-population model incorporating 343 cities in China was used for spatial and temporal synchronization, and simulations were run for the period from January 16 to March 31, 2020. To simulate a realistic scenario, the parameters and initial conditions for the selected epicenter and its 16 most highly connected cities were based on values from the Hubei model (comprising Wuhan and 16 non-Wuhan cities in Hubei Province). We assumed that there were no infections in other cities at the beginning of the simulation. The hypothetical epicenter could be one of the 31 capital cities in China. Synchronization of NPIs was defined as selected cities (ni) implementing NPIs simultaneously at time ti, while the remaining cities implemented NPIs at a random time between ti and ti + 7. The implementation of travel restrictions (population movement between regions) and social distancing (measured as SIM) was represented by using the mobility data after the Wuhan lockdown (Fig. S3). To represent the strength of infection isolation, the strength in the city i was first set as constant between January 23 and ti and then allowed to increase after the implementation of NPIs: the growth coefficients of this increase in the epicenter and other cities were set using the estimated growth coefficients for Wuhan and non-Wuhan cities, respectively, in the Hubei model. The effect of synchronized NPIs was defined as the proportion of infections that were averted compared to the unsynchronized scenario. Linear regression was performed using the lm function in R software to determine the relationship between the effect of synchronized NPIs and the interconnectivity of a specific city (as a hypothetical epicenter).