Stability of epidemic models over directed graphs: A positive systems approach

Ali Khanafer, Tamer Başar, Bahman Gharesifard

Research output: Contribution to journalArticlepeer-review

Abstract

We study the stability properties of a susceptible–infected–susceptible (SIS) diffusion model, so-called the n-intertwined Markov model, over arbitrary directed network topologies. As in the majority of the work on infection spread dynamics, this model exhibits a threshold phenomenon. When the curing rates in the network are high, the disease-free equilibrium is the unique equilibrium over the network. Otherwise, an endemic equilibrium state emerges, where some infection remains within the network. Using notions from positive systems theory, we provide novel proofs for the global asymptotic stability of the equilibrium points in both cases over strongly connected networks based on the value of the basic reproduction number, a fundamental quantity in the study of epidemics. When the network topology is weakly connected, we provide conditions for the existence, uniqueness, and global asymptotic stability of an endemic state, and study the stability of the disease-free equilibrium. Finally, we demonstrate that the n-intertwined Markov model can be viewed as a best-response dynamical system of a concave game among the nodes. This characterization allows us to cast new infection spread dynamics; additionally, we provide a sufficient condition for global convergence to the disease-free equilibrium, which can be checked in a distributed fashion.

Original languageEnglish (US)
Pages (from-to)126-134
Number of pages9
JournalAutomatica
Volume74
DOIs
StatePublished - Dec 1 2016

Keywords

  • Directed graphs
  • Interconnected systems
  • Networks
  • Nonlinear control systems
  • Stability analysis

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Stability of epidemic models over directed graphs: A positive systems approach'. Together they form a unique fingerprint.

Cite this