Proximity networks and epidemics

Proximity Networks and Epidemics

Disease spread in most biological populations requires the proximity of agents. In populations where the individuals have spatial mobility, the contact graph is generated by the “collision dynamics” of the agents, and thus the evolution of epidemics couples directly to the spatial dynamics of the population. We first briefly review the properties and the methodology of an agent-based simulation...

Networks and Epidemics

2 Inaugurated by D. Bernoulli (1700-1782), the analysis of epidemics and their dissemination have been studied by various mathematicians. The benets from epidemic modelling are threefold: understanding mechanisms of spread of epidemics, predicting their future course and developing strategies to control them. Recently, epidemic algorithms (also known as gossip algorithms) have been proposed as ...

Epidemics on Interconnected Networks

Populations are seldom completely isolated from their environment. Individuals in a particular geographic or social region may be considered a distinct network due to strong local ties but will also interact with individuals in other networks. We study the susceptible-infected-recovered process on interconnected network systems and find two distinct regimes. In strongly coupled network systems,...

Modelling Epidemics on Networks

Infectious disease remains, despite centuries of work to control and mitigate its effects, a major problem facing humanity. This paper reviews the mathematical modelling of infectious disease epidemics on networks, starting from the simplest Erdös-Rényi random graphs, and building up structure in the form of correlations, heterogeneity and preference, paying particular attention to the links be...

Proximity Networks Technology Assessment