Identifying influential spreaders and efficiently estimating infection numbers in epidemic models: A walk counting approach

@article{Bauer2012IdentifyingIS,
  title={Identifying influential spreaders and efficiently estimating infection numbers in epidemic models: A walk counting approach},
  author={Frank Bauer and Joseph T. Lizier},
  journal={EPL},
  year={2012},
  volume={99},
  pages={68007}
}
We introduce a new method to efficiently approximate the number of infections resulting from a given initially infected node in a network of susceptible individuals. Our approach is based on counting the number of possible infection walks of various lengths to each other node in the network. We analytically study the properties of our method, in particular demonstrating different forms for SIS and SIR disease spreading (e.g., under the SIR model our method counts self-avoiding walks). In… Expand

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References

SHOWING 1-10 OF 32 REFERENCES
Spread of epidemic disease on networks.
  • M. Newman
  • Medicine, Physics
  • Physical review. E, Statistical, nonlinear, and soft matter physics
  • 2002
TLDR
This paper shows that a large class of standard epidemiological models, the so-called susceptible/infective/removed (SIR) models can be solved exactly on a wide variety of networks. Expand
Universal behavior in a generalized model of contagion.
TLDR
A general model of contagion is introduced which, by explicitly incorporating memory of past exposures to, for example, an infectious agent, rumor, or new product, includes the main features of existing contagion models and interpolates between them. Expand
Breakdown of the internet under intentional attack.
TLDR
It is argued that, near criticality, the average distance between sites in the spanning (largest) cluster scales with its mass, M, as square root of [M], rather than as log (k)M, as expected for random networks away from criticality. Expand
Diffusion of scientific credits and the ranking of scientists
TLDR
This work takes advantage of the entire Physical Review publication archive to construct authors' networks where weighted edges, as measured from opportunely normalized citation counts, define a proxy for the mechanism of scientific credit transfer. Expand
Self-similar community structure in a network of human interactions.
TLDR
The results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar, suggesting that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks. Expand
Quantifying the influence of scientists and their publications: Distinguish prestige from popularity
TLDR
This paper argues that from whom the paper is being cited is of higher significance than merely the number of received citations, and proposes an interactive model on author-paper bipartite networks as well as an iterative algorithm to get better rankings for scientists and their publications. Expand
Fast algorithm for detecting community structure in networks.
  • M. Newman
  • Computer Science, Medicine
  • Physical review. E, Statistical, nonlinear, and soft matter physics
  • 2004
TLDR
An algorithm is described which gives excellent results when tested on both computer-generated and real-world networks and is much faster, typically thousands of times faster, than previous algorithms. Expand
The Giant Component in a Random Subgraph of a Given Graph
TLDR
It is proved that for any e> 0, if $p > (1+ \epsilon)/{\tilde d}$ then asymptotically almost surely the percolated subgraph G p has a giant component. Expand
The self-avoiding walk
The self-avoiding walk is a mathematical model with important applications in statistical mechanics and polymer science. This text provides a unified account of the rigorous results for theExpand
Nature
  • R. Rosenfeld
  • Medicine
  • Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
  • 2009
TLDR
I am writing with a simple plea to balance the voluminous articles about treatment in your journal with a modicum of information about nature and caring effects to rekindle the perception of physicians as healers, not only treaters, who relish the gifts of nature, and foster the humanistic aspect of medicine that has thrived for millennia. Expand
...
1
2
3
4
...