Epidemic spreading in community networks

Zonghua Liu; H. U. Bambi

doi:10.1209/epl/i2004-10550-5

Epidemic spreading in community networks

Zonghua Liu^*
, H. U. Bambi

^*Corresponding author for this work

School of Physics and Electronic Science

Research output: Contribution to journal › Article › peer-review

223 Scopus citations

Abstract

Social networks have the structure of communities. To understand how the community structure affects epidemic spreading, we present a simplified model of community network, and investigate the epidemic propagation in this model. We find that, compared to the random network, the community network has a broader degree distribution, a smaller threshold of epidemic outbreak, and more prevalence to keep the outbreak endemic. The formulae of epidemic threshold are given and confirmed by numerical simulations.

Original language	English
Pages (from-to)	315-321
Number of pages	7
Journal	Europhysics Letters
Volume	72
Issue number	2
DOIs	https://doi.org/10.1209/epl/i2004-10550-5
State	Published - 15 Oct 2005

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@article{6fe0ecebfcfc4456b36316711428f341,

title = "Epidemic spreading in community networks",

abstract = "Social networks have the structure of communities. To understand how the community structure affects epidemic spreading, we present a simplified model of community network, and investigate the epidemic propagation in this model. We find that, compared to the random network, the community network has a broader degree distribution, a smaller threshold of epidemic outbreak, and more prevalence to keep the outbreak endemic. The formulae of epidemic threshold are given and confirmed by numerical simulations.",

author = "Zonghua Liu and Bambi, \{H. U.\}",

year = "2005",

month = oct,

day = "15",

doi = "10.1209/epl/i2004-10550-5",

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journal = "Europhysics Letters",

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T1 - Epidemic spreading in community networks

AU - Liu, Zonghua

AU - Bambi, H. U.

PY - 2005/10/15

Y1 - 2005/10/15

N2 - Social networks have the structure of communities. To understand how the community structure affects epidemic spreading, we present a simplified model of community network, and investigate the epidemic propagation in this model. We find that, compared to the random network, the community network has a broader degree distribution, a smaller threshold of epidemic outbreak, and more prevalence to keep the outbreak endemic. The formulae of epidemic threshold are given and confirmed by numerical simulations.

AB - Social networks have the structure of communities. To understand how the community structure affects epidemic spreading, we present a simplified model of community network, and investigate the epidemic propagation in this model. We find that, compared to the random network, the community network has a broader degree distribution, a smaller threshold of epidemic outbreak, and more prevalence to keep the outbreak endemic. The formulae of epidemic threshold are given and confirmed by numerical simulations.

UR - https://www.scopus.com/pages/publications/27444434464

U2 - 10.1209/epl/i2004-10550-5

DO - 10.1209/epl/i2004-10550-5

M3 - 文章

AN - SCOPUS:27444434464

SN - 0295-5075

VL - 72

SP - 315

EP - 321

JO - Europhysics Letters

JF - Europhysics Letters

IS - 2

ER -

Epidemic spreading in community networks

Abstract

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