计算机科学 ›› 2011, Vol. 38 ›› Issue (6): 118-121.

• 计算机网络与信息安全 • 上一篇    下一篇

复杂网络模型及其在疫情传播和控制中的应用研究

陈端兵,黄晟,尚明生   

  1. (电子科技大学互联网科学中心 成都611731)
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金(60973069,90924011),中国博士后科学基金项目(20080437273),四川省科技厅国际合作项目(2010HH0002)资助。

Complex Network Model and Application in Epidemic Spreading and Controlling

CHEN Duan-bing, HUANG Sheng,SHANG Ming-sheng   

  • Online:2018-11-16 Published:2018-11-16

摘要: 复杂网络已成为一个热点研究问题,它在工程技术、社会、政治、医药、经济、管理等领域都有着广泛的应用。越来越多的科学家开始关注基于复杂网络拓扑结构的动力学研究。其中,关于疾病传播的研究是一个重要方面。分析和研究了小世界网络模型和I3A无标度网络模型两种经典的复杂网络模型,并模拟了传染病按照SIR传播模型在两种网络中的传播情况,讨论了其上的传播阂值以及随机免疫和目标免疫策略对传播阂值的影响。最后对H1N1病毒的传播情况进行了仿真模拟,包括H1N1病毒在自由传播和采取随机及目标免疫两种免疫策略时的传播情况。仿真结果表明,目标免疫策略可以有效抑制疾病的传播。

关键词: 复杂网络,流行病传播,SIR模型,免疫策略,仿真

Abstract: Study of complex networks becomes a hot research topic. Complex networks arc applied to many applications such as engineering technology, society, politics, economics, medicine and management. Many scientists paid much attenlion on structures and dynamics of complex networks. Epidemic spreading in complex networks is one of the most important aspects. hwo classical complex network models, small world network model and 13A scalcfrec network modelwere studied in this paper. SIR spreading model was used to simulate the epidemic spreading and the spreading threshold, and to study two immunization strategics, stochastic and target, how to influence the spreading threshold. Spreading and controlling of H1Nl were simulated in the non-immunization case as well as in the stochastic and target immunizalion cases. Simulation results demonstrate that target immunization can restrain the spreading of epidemic effectively.

Key words: Complex networks,Epidcmic spreading,SIR model,Immunization strategies,Simulation

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