activity
20192026
most citedNetworked Multi-Virus Spread with a Shared Resource: Analysis and Mitigation Strategies

17 citations · 32 across the 18 of their papers we have counts for

collaborators

21 papers

eess.SY2026

On a Class of Decentralized Feedback Controllers for the Networked Bivirus SIS Model

Sebin Gracy, Mengbin Ye, Brian D. O. Anderson

Recent work has established many properties of systems modeling the spread of two competing viruses in a population, and for networks with multiple connected populations with diffe…

eess.SY2026

A Networked SIS Epidemic--Opinion Model with Higher-Order Interactions

Saba Samadi, José I. Caiza, Sebin Gracy +1

This paper studies a susceptible--infected--susceptible (SIS) epidemic model coupled with opinion dynamics over a network of communities with higher-order interactions. Unlike stan…

eess.SY2025

Game-theoretic Social Distancing in Competitive Bi-Virus SIS Epidemics

Benjamin Catalano, Keith Paarporn, Sebin Gracy

Numerous elements drive the spread of infectious diseases in complex real-world networks. Of particular interest is social behaviors that evolve in tandem with the spread of diseas…

eess.SY2023

A Discrete-time Networked Competitive Bivirus SIS Model

Sebin Gracy, Ji Liu, Tamer Basar +1

The paper deals with the analysis of a discrete-time networked competitive bivirus susceptible-infected-susceptible (SIS) model. More specifically, we suppose that virus 1 and viru…

eess.SY2023

Competitive Networked Bivirus SIS spread over Hypergraphs

Sebin Gracy, Brian D. O. Anderson, Mengbin Ye +1

The paper deals with the spread of two competing viruses over a network of population nodes, accounting for pairwise interactions and higher-order interactions (HOI) within and bet…

eess.SY2023

Analysis, Control, and State Estimation for the Networked Competitive Multi-Virus SIR Model

Ciyuan Zhang, Sebin Gracy, Tamer Basar +1

This paper proposes a novel discrete-time multi-virus susceptible-infected-recovered (SIR) model that captures the spread of competing epidemics over a population network. First, w…