  In this paper, we investigate the problem of designing event-triggered
controllers for containing epidemic processes in complex networks. We focus on
a deterministic susceptible-infected-susceptible (SIS) model, which is one of
the well-known, fundamental models that capture the epidemic spreading. The
event-triggered control is particularly formulated in the context of viral
spreading, in which control inputs (e.g., the amount of medical treatments, a
level of traffic regulations) for each subpopulation are updated only when the
fraction of the infected people in the subpopulation exceeds a prescribed
threshold. We analyze stability of the proposed event-triggered controller, and
derives a sufficient condition for a prescribed control objective to be
achieved. Moreover, we propose a novel emulation-based approach towards the
design of the event-triggered controller, and show that the problem of
designing the event-triggered controller can be solved in polynomial time using
geometric programming. We illustrate the effectiveness of the proposed approach
through numerical simulations using an air transportation network.
