Epidemic spreading on heterogeneous networks with identical infectivity

By Ruiling Yang, Bing-Hong Wang, Jie Ren, Wen-jie Bai, Zhiyong Shi, Wenxu Wang, Tao Zhou. 2006

207 citations recorded by the source corpus.

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.

Subfields: Public Health, Environmental and Occupational Health, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/997fca87524a70034d5685b7f88f0105a349aa9e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Public Health, Environmental and Occupational Health

1. Yi-Cheng Zhang
2. Linyuan Lu
3. Tao Zhou
4. Duanbing Chen
5. Qian-Ming Zhang
6. Xiaolong Ren

In Statistical and Nonlinear Physics

1. Tao Zhou
2. Duanbing Chen
3. Linyuan Lu
4. Yi-Cheng Zhang
5. Sophie Ahrens
6. Qian-Ming Zhang
7. Xiaolong Ren
8. Hui Gao

Citations in the corpus

• Vital nodes identification in complex networks (2016, background): “In fact, in the original paper for LeaderRank [94], a variant of SIR model [158] was considered as the target dynamics.”
• Identifying Influential Nodes in Large-Scale Directed Networks: The Role of Clustering (2013, background): “The present mechanism is usually used to mimic the limited spreading capability of individuals [42,43].”
• Leaders in Social Networks, the Delicious Case (2011, methodology): “Specifically, we employ a variant of the SIR model to examine the spreading influence of the topranked users [16].”