Signal propagation in complex networks drives epidemics, is responsible for information
going viral, promotes trust and facilitates moral behavior in social groups, enables the …

The complexity of many biological, social and technological systems stems from the richness
of the interactions among their units. Over the past decades, a variety of complex systems …

Over the past two decades, complex network theory provided the ideal framework for
investigating the intimate relationships between the topological properties characterizing the …

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 …

There is a long tradition of using mathematical models to generate insights into the
transmission dynamics of infectious diseases and assess the potential impact of different …

Historically, infectious diseases caused considerable damage to human societies, and they
continue to do so today. To help reduce their impact, mathematical models of disease …

Reaction–diffusion processes have been widely used to study dynamical processes in
epidemics,–and ecology in networked metapopulations. In the context of epidemics, reaction …

During an infectious disease outbreak, biases in the data and complexities of the underlying
dynamics pose significant challenges in mathematically modelling the outbreak and …

In the early stages of an outbreak, the term 'pandemic'can be used to communicate about
infectious disease risk, particularly by those who wish to encourage a large-scale public …

We propose a theoretical framework for the study of spreading processes in structured
metapopulations, with heterogeneous agents, subjected to different recurrent mobility …