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Epidemic spreading on heterogeneous networks with identical infectivity
Open accessAbstract
In this Letter, we propose a modified susceptible-infected-recovered (SIR) model, in which each node is assigned with an identical capability of active contacts, A, at each time step. In contrast to the previous studies, we find that on scale-free networks, the density of the recovered individuals in the present model shows a threshold behavior. We obtain the analytical results using the mean-field theory and find that the threshold value equals 1/A, indicating that the threshold value is independent of the topology of the underlying network. The simulations agree well with the analytic results. Furthermore, we study the time behavior of the epidemic propagation and find a hierarchical dynamics with three plateaus. Once the highly connected hubs are reached, the infection pervades almost the whole network in a progressive cascade across smaller degree classes. Then, after the previously infected hubs are recovered, the disease can only propagate to the class of smallest degree till the infected individuals are all recovered. The present results could be of practical importance in the setup of dynamic control strategies.
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Citations
Cites
Maximal planar networks with large clustering coefficient and power-law degree distribution
Zhou, T., Yan, G., & Wang, B.-H. (2005) · Physical Review E · doi:10.1103/physreve.71.046141 · Cited by 265
Self-citation
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Leaders in Social Networks, the Delicious Case
Lü, L., Zhang, Y.-C., Yeung, C. H., & Zhou, T. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021202 · Cited by 871
Self-citationDynamics of information diffusion and its applications on complex networks
Zhang, Z.-K., Liu, C., Zhan, X.-X., Lu, X., Zhang, C.-X., & Zhang, Y.-C. (2016) · Physics Reports · doi:10.1016/j.physrep.2016.07.002 · Cited by 484
Identifying Influential Nodes in Large-Scale Directed Networks: The Role of Clustering
Chen, D.-B., Gao, H., Lü, L., & Zhou, T. (2013) · PLoS ONE · doi:10.1371/journal.pone.0077455 · Cited by 364
Self-citationOn agent-based modeling and computational social science
Conte, R., & Paolucci, M. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00668 · Cited by 160
“For example, topological properties of complex networks are found among the main factors affecting epidemic dynamics (for a review, see Yang et al., 2007).”
Background
Metadata
- Authors
- Yang, R., Wang, B.-H., Ren, J., Bai, W.-J., Shi, Z.-W., Wang, W.-X., & Zhou, T.
- Venue
- Physics Letters A
- Publisher
- Elsevier BV
- Published
- 2007-04
- Volume
- 364
- Issue
- 3-4
- Pages
- 189-193
- ISSN
- 0375-9601 (ISSN-L)
- OpenAlex
- W2170341635
- Cited by
- 221
- References
- 1
- FWCI
- 4.67
- Type
- journal article
- Language
- en
- Open access
- green
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- Yang, R., Wang, B.-H., Ren, J., Bai, W.-J., Shi, Z.-W., Wang, W.-X., & Zhou, T. (2007). Epidemic spreading on heterogeneous networks with identical infectivity. Physics Letters A. https://doi.org/10.1016/j.physleta.2006.12.021
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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