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Coupled effects of local movement and global interaction on contagion

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  • Zhong, Li-Xin
  • Xu, Wen-Juan
  • Chen, Rong-Da
  • Qiu, Tian
  • Shi, Yong-Dong
  • Zhong, Chen-Yang

Abstract

By incorporating segregated spatial domain and individual-based linkage into the SIS (susceptible–infected–susceptible) model, we propose a generalized epidemic model which can change from the territorial epidemic model to the networked epidemic model. The role of the individual-based linkage between different spatial domains is investigated. As we adjust the timescale parameter τ from 0 to unity, which represents the degree of activation of the individual-based linkage, three regions are found. Within the region of 0<τ<0.02, the epidemic is determined by local movement and is sensitive to the timescale τ. Within the region of 0.02<τ<0.5, the epidemic is insensitive to the timescale τ. Within the region of 0.5<τ<1, the outbreak of the epidemic is determined by the structure of the individual-based linkage. As we keep an eye on the first region, the role of activating the individual-based linkage in the present model is similar to the role of the shortcuts in the two-dimensional small world network. Only activating a small number of the individual-based linkage can prompt the outbreak of the epidemic globally. The role of narrowing segregated spatial domain and reducing mobility in epidemic control is checked. These two measures are found to be conducive to curbing the spread of infectious disease only when the global interaction is suppressed. A log–log relation between the change in the number of infected individuals and the timescale τ is found. By calculating the epidemic threshold and the mean first encounter time, we heuristically analyze the microscopic characteristics of the propagation of the epidemic in the present model.

Suggested Citation

  • Zhong, Li-Xin & Xu, Wen-Juan & Chen, Rong-Da & Qiu, Tian & Shi, Yong-Dong & Zhong, Chen-Yang, 2015. "Coupled effects of local movement and global interaction on contagion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 482-491.
  • Handle: RePEc:eee:phsmap:v:436:y:2015:i:c:p:482-491
    DOI: 10.1016/j.physa.2015.05.023
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    References listed on IDEAS

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    1. M. E. J. Newman & D. J. Watts, 1999. "Scaling and Percolation in the Small-World Network Model," Working Papers 99-05-034, Santa Fe Institute.
    2. Dafang Zheng & Güler Ergün, 2003. "Coupled Growing Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(04), pages 507-514.
    3. Frank Schweitzer & Laxmidar Behera, 2012. "Optimal Migration Promotes The Outbreak Of Cooperation In Heterogeneous Populations," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(supp0), pages 1-27.
    4. Wu, Xiaoyan & Liu, Zonghua, 2008. "How community structure influences epidemic spread in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 623-630.
    5. Cristopher Moore & M. E. J. Newman, 2000. "Epidemics and Percolation in Small-World Networks," Working Papers 00-01-002, Santa Fe Institute.
    6. 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.
    7. Sergey V. Buldyrev & Roni Parshani & Gerald Paul & H. Eugene Stanley & Shlomo Havlin, 2010. "Catastrophic cascade of failures in interdependent networks," Nature, Nature, vol. 464(7291), pages 1025-1028, April.
    8. Gräser, Oliver & Hui, P.M. & Xu, C., 2011. "Separatrices between healthy and endemic states in an adaptive epidemic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 906-913.
    9. Thomas Fent & Patrick Groeber & Frank Schweitzer, 2007. "Coexistence Of Social Norms Based On In- And Out-Group Interactions," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 271-286.
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    Cited by:

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    2. Zhong, Li-Xin & Xu, Wen-Juan & Chen, Rong-Da & Zhong, Chen-Yang & Qiu, Tian & Shi, Yong-Dong & Wang, Li-Liang, 2016. "A generalized voter model with time-decaying memory on a multilayer network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 95-105.

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