Research in graph signal processing (GSP) aims to develop tools for processing data
defined on irregular graph domains. In this paper, we first provide an overview of core ideas …

This article reviews and presents various solved and open problems in the development,
analysis, and control of epidemic models. The proper modeling and analysis of spreading …

Over the past decade, the use of networks has led to a new modelling paradigm combining
several branches of science, including physics, mathematics, biology and social sciences …

During the ongoing COVID-19 pandemic, mathematical models of epidemic spreading have
emerged as powerful tools to produce valuable predictions of the evolution of the pandemic …

The process by which new ideas, innovations, and behaviors spread through a large social
network can be thought of as a networked interaction game: Each agent obtains information …

We present and discuss a variety of mathematical models that have been proposed to
capture the dynamic behavior of epidemic processes. We first present traditional group …

In this work we review a class of deterministic nonlinear models for the propagation of
infectious diseases over contact networks with strongly-connected topologies. We consider …

The interaction between epidemic spreading and information diffusion is an interdisciplinary
research problem. During an epidemic, people tend to take self-protective measures to …

Real-world networks, like social networks or the internet infrastructure, have structural
properties such as large clustering coefficients that can best be described in terms of an …

This review presents and reviews various solved and open problems in develo**,
analyzing, and mitigating epidemic spreading processes under human decision-making. We …