no code implementations • 15 May 2023 • Ciyuan Zhang, Sebin Gracy, Tamer Basar, Philip E. Pare
Second, we propose an observation model which captures the summation of all the viruses' infection levels in each node, which represents the individuals who are infected by different viruses but share similar symptoms.
no code implementations • 15 Mar 2023 • Sebin Gracy, YuAn Wang, Philip E. Pare, Cesar A Uribe
We study the spread of multi-competitive viruses over a (possibly) time-varying network of individuals accounting for the presence of shared infrastructure networks that further enables transmission of the virus.
no code implementations • 1 Apr 2022 • Ciyuan Zhang, Sebin Gracy, Tamer Basar, Philip E. Pare
This paper proposes a novel discrete-time multi-virus SIR (susceptible-infected-recovered) model that captures the spread of competing SIR epidemics over a population network.
no code implementations • 20 Sep 2021 • Philip E. Pare, Axel Janson, Sebin Gracy, Ji Liu, Henrik Sandberg, Karl H. Johansson
We develop a layered networked spread model for a susceptible-infected-susceptible (SIS) pathogen-borne disease spreading over a human contact network and an infrastructure network, and refer to it as a layered networked susceptible-infected-water-susceptible (SIWS) model.
