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Measuring edge importance to improve immunization performance

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  • Huang, He
  • Yan, Zhijun
  • Pan, Yaohui

Abstract

The edge heterogeneity has a remarkable influence on disease spreading, but it has seldom been considered in the disease-controlling policies. Based on the gravity model, we propose the edge importance index to describe the influence of edge heterogeneity on immunization strategies. Then the edge importance and contact weight are combined to calculate the infection rates on the I–S (Infected–Susceptible) edges in the complex network, and the difference of the infection rates on strong and weak ties is analyzed. Simulation results show that edge heterogeneity has a significant influence on the performance of immunization strategies, and better immunization efficiency is derived when the vaccination rate of the nodes in the weak I–S edges is increased.

Suggested Citation

  • Huang, He & Yan, Zhijun & Pan, Yaohui, 2014. "Measuring edge importance to improve immunization performance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 532-540.
    • Handle: RePEc:eee:phsmap:v:416:y:2014:i:c:p:532-540
    DOI: 10.1016/j.physa.2014.09.007
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    1. Sheng, Long & Li, Chunguang, 2009. "English and Chinese languages as weighted complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2561-2570.
    2. Lü, Linyuan & Zhou, Tao, 2011. "Link prediction in complex networks: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1150-1170.
    3. Li, Menghui & Wu, Jinshan & Wang, Dahui & Zhou, Tao & Di, Zengru & Fan, Ying, 2007. "Evolving model of weighted networks inspired by scientific collaboration networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(1), pages 355-364.
    4. Tao Zhou & Linyuan Lü & Yi-Cheng Zhang, 2009. "Predicting missing links via local information," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(4), pages 623-630, October.
    5. E. Almaas & B. Kovács & T. Vicsek & Z. N. Oltvai & A.-L. Barabási, 2004. "Global organization of metabolic fluxes in the bacterium Escherichia coli," Nature, Nature, vol. 427(6977), pages 839-843, February.
    6. Zhang, Jun & Cao, Xian-Bin & Du, Wen-Bo & Cai, Kai-Quan, 2010. "Evolution of Chinese airport network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(18), pages 3922-3931.
    7. Bagler, Ganesh, 2008. "Analysis of the airport network of India as a complex weighted network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2972-2980.
    8. Song, Dong-Ming & Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2009. "Statistical properties of world investment networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2450-2460.
    9. Lin Wang & Xiang Li & Yi-Qing Zhang & Yan Zhang & Kan Zhang, 2011. "Evolution of Scaling Emergence in Large-Scale Spatial Epidemic Spreading," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-11, July.
    10. Kai Gong & Ming Tang & Pak Ming Hui & Hai Feng Zhang & Do Younghae & Ying-Cheng Lai, 2013. "An Efficient Immunization Strategy for Community Networks," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-11, December.
    11. Shi, Xiaolin & Adamic, Lada A. & Strauss, Martin J., 2007. "Networks of strong ties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(1), pages 33-47.
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    Cited by:

    1. Chen, Yahong & Huang, He, 2022. "Modeling the impacts of contact tracing on an epidemic with asymptomatic infection," Applied Mathematics and Computation, Elsevier, vol. 416(C).
    2. Qin, Yang & Zhong, Xiaoxiong & Jiang, Hao & Ye, Yibin, 2015. "An environment aware epidemic spreading model and immune strategy in complex networks," Applied Mathematics and Computation, Elsevier, vol. 261(C), pages 206-215.
    3. Dong, Lijun & Wang, Yi & Liu, Ran & Pi, Benjie & Wu, Liuyi, 2016. "Toward edge minability for role mining in bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 274-286.
    4. Zhang, Yaming & Su, Yanyuan & Weigang, Li & Liu, Haiou, 2018. "Rumor and authoritative information propagation model considering super spreading in complex social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 395-411.
    5. Dong, Chao & Yin, Qiuju & Liu, Wenyang & Yan, Zhijun & Shi, Tianyu, 2015. "Can rewiring strategy control the epidemic spreading?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 169-177.

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