# 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

#### Paper Mentions

#### 81 Citations

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Simulation results show that the proposed reversed local path algorithm outperforms the existing methods in identifying the influential nodes with respect to localized targets in complex networks and can effectively avoid infecting the non-target nodes in the spreading process. Expand

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Simulation results show that the reversed local path algorithm outperforms the existing methods in identifying the influential nodes with respect to these localized targets and the influential spreaders identified by the method can effectively avoid infecting the non-target nodes in the spreading process. Expand

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It is proved that the recently introduced nonbacktracking centrality is the optimal criterion for the identification of influential spreaders in locally tree-like networks at criticality and is a highly reliable metric to identify top influential spreader also in generic graphs not embedded in space and for noncritical spreading. Expand

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- Computer Science, Physics
- ArXiv
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Some of the most important theoretical models that describe spreading processes are displayed, and the problem of locating both the individual and multiple influential spreaders respectively are discussed. Expand

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Abstract
Identifying the most influential spreaders is one of outstanding problems in physics of complex systems. So far, many approaches have attempted to rank the influence of nodes but there is… Expand

Accurate prediction of influential spreaders in complex networks via message-passing approach

- Physics, Computer Science
- ArXiv
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A new measure is proposed that quantifies relative impact of nodes based on their topological connectivity, as well as their percolation states, that can be extended to include random walk based definitions and its computational complexity is shown to be of the same order as that of betweenness centrality. Expand

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The Node Imposed Response (NiR), a measure which accurately evaluates node spreading power, is proposed which outperforms betweenness, degree, k-shell and h-index centrality in many cases and shows the similar accuracy to dynamics-sensitive centrality. Expand

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