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| Epidemic Spreading in Dynamic Small-World Networks with Community Structure |
| LI Chanchana, JIANG Guopingb, SONG Yurongb
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| a. College of Computer; b. College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210003, China |
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Abstract Since many real networks generally have community structures and characteristics of small world, we propose a dynamical small-world network model with strength-tunable community, which can describe the phenomena of local contacts and moving contacts in real life. Then we construct a SIR transmission model on the proposed network on the basis of mean-field theory. Simulations and analysis show that, with the increase of inter-community long range jump probabilities, the epidemic threshold will decrease. And the larger the community strength is, the larger the epidemic threshold will be. Namely, large community degree can reduce the spreading of the virus. Additionally, in order to suppress the epidemic spreading, it is effective to strengthen the control of inter-community long range jump.
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Received: 23 June 2013
Published: 22 June 2026
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