Epidemic processes in complex networks

@article{PastorSatorras2014EpidemicPI,
  title={Epidemic processes in complex networks},
  author={Romualdo Pastor-Satorras and Claudio Castellano and Piet Van Mieghem and Alessandro Vespignani},
  journal={ArXiv},
  year={2014},
  volume={abs/1408.2701}
}
In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The… 
Link equations for discrete-time epidemic processes in complex network
TLDR
This work proposes a set of discrete-time governing equations that can be closed and analyzed, assessing the contribution of links to spreading processes in complex networks, and validate the approach in synthetic and real networks, obtaining a better determination of critical thresholds.
Analysis and Control of Epidemics: A Survey of Spreading Processes on Complex Networks
TLDR
Various solved and open problems in the development, analysis, and control of epidemic models are reviewed and presented.
Unification of theoretical approaches for epidemic spreading on complex networks.
TLDR
This short survey unifies the most widely used theoretical approaches for epidemic spreading on complex networks in terms of increasing complexity, including the mean-field, the heterogeneous mean- field, the quench mean-fields, dynamical message-passing, link percolation, and pairwise approximation.
Directionality reduces the impact of epidemics in multilayer networks
TLDR
The epidemic threshold of synthetic and real-world multilayer systems is calculated and it is shown that it is mainly determined by the directionality of the links connecting different layers, regardless of the degree distribution chosen for the layers.
Directionality reduces the impact of epidemics in multilayer networks
Our understanding of how diseases spread has greatly bene fi ted from advances in network modeling. However, despite of its importance for disease contagion, the directionality of edges has rarely
Coupling dynamics of epidemic spreading and information diffusion on complex networks
Coevolution spreading in complex networks
Analysis and control of diffusion processes in networks
TLDR
This work allows the rigorous analysis of the behavior of a network's characteristics when it converges, in a structural sense, to a given metric space, and could open the way to the application of control strategies on networks to spatial and macroscopic information about the contact network in a given population.
Dynamics of Epidemic Spreading in Complex Networks
Several mathematical models, mostly based on graph theory, have been developed over the past decades to predict and explain the behavior within complex interconnected dynamical systems. Here we
...
...

References

SHOWING 1-10 OF 971 REFERENCES
Competing epidemics on complex networks
  • B. Karrer, M. Newman
  • Economics
    Physical review. E, Statistical, nonlinear, and soft matter physics
  • 2011
TLDR
A model of two competing diseases spreading over the same network at the same time, where infection with either disease gives an individual subsequent immunity to both, is examined.
Networks and the Epidemiology of Infectious Disease
TLDR
A personalised overview into the areas of network epidemiology that have seen the greatest progress in recent years or have the greatest potential to provide novel insights is provided, focusing on the interplay between network theory and epidemiology.
Predicting epidemic outbreak from individual features of the spreaders
TLDR
This paper explores possible correlations between the heterogeneous spread of an epidemic disease governed by the susceptible–infected–recovered (SIR) model, and several attributes of the originating vertices, considering Erdos–Renyi (ER), Barabasi–Albert and random geometric graphs (RGG), as well as a real case study, the US air transportation network.
Networks and epidemic models
TLDR
A variety of methods are described that allow the mixing network, or an approximation to the network, to be ascertained and how the two fields of network theory and epidemiological modelling can deliver an improved understanding of disease dynamics and better public health through effective disease control are suggested.
Generalized Epidemic Mean-Field Model for Spreading Processes Over Multilayer Complex Networks
TLDR
A detailed description of the stochastic process at the agent level where the agents interact through different layers, each represented by a graph is provided, including spreading of virus and information in computer networks and spreading of multiple pathogens in a host population.
Bursts of Vertex Activation and Epidemics in Evolving Networks
TLDR
A stochastic model to generate temporal networks where vertices make instantaneous contacts following heterogeneous inter-event intervals, and may leave and enter the system is proposed, finding that prevalence is generally higher for heterogeneous patterns, except for sufficiently large infection duration and transmission probability.
Evolution of networks
TLDR
The recent rapid progress in the statistical physics of evolving networks is reviewed, and how growing networks self-organize into scale-free structures is discussed, and the role of the mechanism of preferential linking is investigated.
Infection dynamics on scale-free networks.
  • R. May, A. Lloyd
  • Mathematics
    Physical review. E, Statistical, nonlinear, and soft matter physics
  • 2001
TLDR
Approximate expressions for the final size of an epidemic in an infinite closed population and for the dependence of infection probability on an individual's degree of connectivity within the population are derived.
...
...