| A dynamic epidemic control model on uncorrelated complex networks |
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| 引用本文： | 裴伟东,陈增强,袁著祉. A dynamic epidemic control model on uncorrelated complex networks[J]. 中国物理 B, 2008, 17(2): 373-379 |
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| 作者姓名： | 裴伟东 陈增强 袁著祉 |
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| 作者单位： | Department of Automation, Nankai University, Tianjin 300071, China;College of Computer and Information Engineering, TianjinNormal University, Tianjin 300387, China;Department of Automation, Nankai University, Tianjin 300071, China;Department of Automation, Nankai University, Tianjin 300071, China |
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| 基金项目： | Project supported by the NationalNatural Science Foundation of China (Grant No. 60774088), theProgram for New Century Excellent Talents of Higher Education ofChina (Grant No NCET 2005-290), the Special Research Fund for theDoctoral Program of Higher Education ofChina (Grant No 20050055013). |
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| 摘 要： | In this paper, a dynamic epidemic control model on the uncorrelated complex networks is proposed. By means of theoretical analysis, we found that the new model has a similar epidemic threshold as that of the susceptible-infectedrecovered （SIR） model on the above networks, but it can reduce the prevalence of the infected individuals remarkably. This result may help us understand epidemic spreading phenomena on real networks and design appropriate strategies to control infections.
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| 关 键 词： | 复杂网路 动态检查器械 QSIR模式 流动端口 |
| 收稿时间： | 2007-05-22 |
| 修稿时间： | 2007-08-15 |
A dynamic epidemic control model on uncorrelated complex networks |
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| Pei Wei-Dong,Chen Zeng-Qiang and Yuan Zhu-Zhi. A dynamic epidemic control model on uncorrelated complex networks[J]. Chinese Physics B, 2008, 17(2): 373-379 |
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| Authors: | Pei Wei-Dong Chen Zeng-Qiang Yuan Zhu-Zhi |
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| Affiliation: | Department of Automation, Nankai University, Tianjin 300071, China; Department of Automation, Nankai University, Tianjin 300071, China;College of Computer and Information Engineering, TianjinNormal University, Tianjin 300387, China |
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| Abstract: | In this paper, a dynamic epidemic control model on the uncorrelatedcomplex networks is proposed. By means of theoretical analysis, wefound that the new model has a similar epidemic threshold as that ofthe susceptible-infected-recovered (SIR) model on the abovenetworks, but it can reduce the prevalence of the infectedindividuals remarkably. This result may help us understand epidemicspreading phenomena on real networks and design appropriatestrategies to control infections. |
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| Keywords: | complex networks dynamicquarantining mechanism QSIR model epidemic threshold |
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