A high-frequency mobility big-data reveals how COVID-19 spread across professions, locations and age groups
Fig 2
The spatiotemporal patterns of city-wise COVID-19 infection.
(A) The number of new infections ΔI(t) in the city as a function of time t at a 15-minute interval, given 70 randomly selected initial spreaders, averaged over 1000 realizations. A significant periodic pattern is observed, which is caused by the periodic human mobility behavior. Inset: The corresponding fraction of infected population, i.e. I(t)/N. (B) The distribution of the initial and the final infected population over the districts, i.e. Id(0)/I(0) and Id(T)/I(T) respectively; districts are numbered as shown in the map in C. (C) The evolution of the daily spatial pattern of the infected population in the city; the number of infected population in a location is represented by the color of the dot. The map was drawn based on open-source shape file with License Creative Commons BY 40 (CC BY 4.0) from OpenStreetMap (https://www.openstreetmap.org/).