Competing control scenarios in probabilistic SIR epidemics on social-contact networks

Abstract

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.