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…
84 Citations
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References
SHOWING 1-10 OF 32 REFERENCES
Spread of epidemic disease on networks.
- MathematicsPhysical review. E, Statistical, nonlinear, and soft matter physics
- 2002
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.
Universal behavior in a generalized model of contagion.
- MathematicsPhysical review letters
- 2004
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.
Breakdown of the internet under intentional attack.
- Computer SciencePhysical review letters
- 2001
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.
Diffusion of scientific credits and the ranking of scientists
- Computer SciencePhysical review. E, Statistical, nonlinear, and soft matter physics
- 2009
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.
Self-similar community structure in a network of human interactions.
- Computer SciencePhysical review. E, Statistical, nonlinear, and soft matter physics
- 2003
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.
Quantifying the influence of scientists and their publications: Distinguish prestige from popularity
- Computer ScienceArXiv
- 2011
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.
Fast algorithm for detecting community structure in networks.
- Computer SciencePhysical review. E, Statistical, nonlinear, and soft matter physics
- 2004
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.
The Giant Component in a Random Subgraph of a Given Graph
- MathematicsWAW
- 2009
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.
The self-avoiding walk
- Physics
- 1991
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 the…