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 …

The propagations of diseases, behaviors and information in real systems are rarely
independent of each other, but they are coevolving with strong interactions. To uncover the …

Topics These lecture notes are intended primarily for graduate students interested in
network systems, distributed algorithms, and cooperative control. The objective is to answer …

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 …

Abstract Models of epidemic spreading on complex networks have attracted great attention
among researchers in physics, mathematics, and epidemiology due to their success in …

Over the past two decades, epidemic spreading on complex network has been a vibrant and
highly successful research avenue. The dynamics of epidemic spreading on signed …

Multilayer networks, in particular multilayer social networks, where users belong to and
interact on different networks at the same time, are an active research area in social network …

The time variation of contacts in a networked system may fundamentally alter the properties
of spreading processes and affect the condition for large-scale propagation, as encoded in …

Mean-field deterministic epidemic models have been successful in uncovering several
important dynamic properties of stochastic epidemic spreading processes over complex …

Cells remember their identities, in part, by using epigenetic marks—chemical modifications
placed along the genome. How can mark patterns remain stable over cell generations …