2020/12/30 by Kazumune Hashimoto, Hashimoto, Kazumune, Yuga Onoue +5 · 1 citation
Mathematics · Physics and Astronomy · #COVID-19 epidemiological studies #Complex Network Analysis Techniques #FOS: Mathematics #Opinion Dynamics and Social Influence #Optimization and Control (math.OC)
paper · pdf · doi:10.48550/arxiv.2012.15146
openalex publication_date 2020/12/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.