Control Scenarios for Probabilistic SIR Epidemics on Social-Connection Graphs

A probabilistic approach to epidemic evolution on realistic social-connection graphs allows for characteristic differences among subjects, including the individual structure and number of social contacts (`ego networks') and the individual infection and recovery rates according to age or medical preconditions. Within our probabilistic Susceptible-Infectious-Removed (SIR) model on graphs, we compare the infection load and proxy cost of control scenarios by confinement, vaccination, and their combinations. The epidemic diffusion is explored on random social-connection graphs designed for more realistic person-person characteristics.