A high-frequency mobility big-data reveals how COVID-19 spread across professions, locations and age groups
Fig 3
Infected professions and locations.
(A) The number of newly infected individuals of different professions p as a function of time t, i.e. ΔIp(t). Inset: the fraction of infected population from profession p who get infected at time t, i.e. ΔIp(t)/Ip(T), averaged over 1000 realizations. Periodic patterns still exist for different professions, but their infected population is largely different. (B) The number of transmissions in locations of different location category l as a function of time t, i.e. ΔIl(t). Inset: the fraction of transmissions in location category l which occur at time t, i.e. ΔIl(t)/Il(T). (C) Upper panel: the distribution of population over professions (orange bars), i.e. Np/N, which is proportional to the initial distribution of the infected population over professions Ip(0)/I(0), and the corresponding final infected distribution (green bars), i.e. Ip(T)/I(T); lower panel: the fraction of final infected individuals normalized by the population size in each profession, i.e. Ip(T)/Np. (D) Upper panel: the distribution of locations over location categories, i.e. Ml/M and the final distribution of transmissions over location categories, i.e. Il(T)/I(T); lower panel: the average number of transmissions in a single location of each location category, i.e. Il(T)/Ml.