中国物理B ›› 2007, Vol. 16 ›› Issue (9): 2498-2502.doi: 10.1088/1009-1963/16/9/002

• GENERAL • 上一篇    下一篇

Controlling disease spread on networks with feedback mechanism

王俐, 颜家壬, 张建国, 刘自然   

  1. Department of Physics, Hunan Normal University, Changsha 410081, China
  • 收稿日期:2006-11-05 修回日期:2007-01-18 出版日期:2007-09-20 发布日期:2007-09-20
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant No 10375022).

Controlling disease spread on networks with feedback mechanism

Wang Li(王俐), Yan Jia-Ren(颜家壬)†, Zhang Jian-Guo(张建国), and Liu Zi-Ran(刘自然)   

  1. Department of Physics, Hunan Normal University, Changsha 410081, China
  • Received:2006-11-05 Revised:2007-01-18 Online:2007-09-20 Published:2007-09-20
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant No 10375022).

PDF (PC)

546

赞

摘要： Many real-world networks have the ability to adapt themselves in response to the state of their nodes. This paper studies controlling disease spread on network with feedback mechanism, where the susceptible nodes are able to avoid contact with the infected ones by cutting their connections with probability when the density of infected nodes reaches a certain value in the network. Such feedback mechanism considers the networks' own adaptivity and the cost of immunization. The dynamical equations about immunization with feedback mechanism are solved and theoretical predictions are in agreement with the results of large scale simulations. It shows that when the lethality $\alpha$ increases, the prevalence decreases more greatly with the same immunization $g$. That is, with the same cost, a better controlling result can be obtained. This approach offers an effective and practical policy to control disease spread, and also may be relevant to other similar networks.

Abstract: Many real-world networks have the ability to adapt themselves in response to the state of their nodes. This paper studies controlling disease spread on network with feedback mechanism, where the susceptible nodes are able to avoid contact with the infected ones by cutting their connections with probability when the density of infected nodes reaches a certain value in the network. Such feedback mechanism considers the networks' own adaptivity and the cost of immunization. The dynamical equations about immunization with feedback mechanism are solved and theoretical predictions are in agreement with the results of large scale simulations. It shows that when the lethality $\alpha$ increases, the prevalence decreases more greatly with the same immunization $g$. That is, with the same cost, a better controlling result can be obtained. This approach offers an effective and practical policy to control disease spread, and also may be relevant to other similar networks.

Key words: complex network systems, disease spread, feedback mechanism

中图分类号:  (Diseases)

  • 87.19.X-
87.10.-e (General theory and mathematical aspects) 87.23.-n (Ecology and evolution) 89.75.Hc (Networks and genealogical trees)