Date created: | Last Updated:

Category: Project

Description: A probabilistic approach to epidemic evolution on realistic social-contact networks 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 social-contact networks, we evaluatetheinfection loadandactivation marginof control scenarios; by con-finement, by vaccination, and by their combination. We compare the epidemic burden for sub-populations which apply competing or co-operative control scenarios. The simulation experiments are conductedon randomised social-contact graphs designed with realistic person-person characteristics and following near homogeneous or block-localised sub-population spreading. Observed control scenario interactions and Nash equilibria in the two sub-population spreadings are discussed.