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… 
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2,248 Citations
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2,248 Citations

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References

SHOWING 1-10 OF 971 REFERENCES
Dynamical patterns of epidemic outbreaks in complex heterogeneous networks.
Epidemic outbreaks in complex heterogeneous networks
TLDR
The large connectivity fluctuations usually found in these networks strengthen considerably the incidence of epidemic outbreaks and defines a new epidemiological framework characterized by a highly heterogeneous response of the system to the introduction of infected individuals with different connectivity.
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.
Epidemic dynamics and endemic states in complex networks.
TLDR
A dynamical model for the spreading of epidemics in complex networks that implies that scale-free networks are prone to the spreading and the persistence of infections whatever spreading rate the epidemic agents might possess.
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.
Epidemic modeling in metapopulation systems with heterogeneous coupling pattern: theory and simulations.
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.
...
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