Comparison of immunization strategies in geographical networks

被引:8
作者
Wang, Bing [3 ]
Aihara, Kazuyuki [3 ]
Kim, Beom Jun [1 ,2 ,4 ,5 ]
机构
[1] Sungkyunkwan Univ, Phys Res Div BK21, Suwon 440746, South Korea
[2] Sungkyunkwan Univ, Dept Energy Sci, Suwon 440746, South Korea
[3] Univ Tokyo, Inst Ind Sci, Tokyo, Japan
[4] Univ Tokyo, ERATO Aihara Complex Modelling Project, JST, Inst Ind Sci,Meguro Ku, Tokyo 1538505, Japan
[5] Royal Inst Technol, Dept Computat Biol, Sch Comp Sci & Commun, S-10044 Stockholm, Sweden
关键词
SCALE-FREE NETWORKS; SMALL-WORLD NETWORKS; EPIDEMICS; DISEASE;
D O I
10.1016/j.physleta.2009.08.023
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The epidemic spread and immunizations in geographically embedded scale-free (SF) and Watts-Strogatz (WS) networks are numerically investigated. We make a realistic assumption that it takes time which we call the detection time. for a vertex to be identified as infected, and implement two different immunization strategies: one is based on connection neighbors (CN) of the infected vertex with the exact information of the network structure utilized and the other is based on spatial neighbors (SN) with only geographical distances taken into account. We find that the decrease of the detection time is crucial for a successful immunization in general. Simulation results show that for both SF networks and WS networks, the SN strategy always performs better than the CN strategy. especially for more heterogeneous SF networks at long detection time. The observation is verified by checking the number of the infected nodes being immunized. We found that in geographical space, the distance preferences in the network construction process and the geographically decaying infection rate are key factors that make the SN immunization strategy outperforms the CN strategy. It indicates that even in the absence of the full knowledge of network connectivity we can still stop the epidemic spread efficiently only by using geographical information as in the SN strategy. which may have potential applications for preventing the real epidemic spread. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:3877 / 3882
页数:6
相关论文
共 32 条
[1]   Epidemic dynamics of two species of interacting particles on scale-free networks [J].
Ahn, Yong-Yeol ;
Jeong, Hawoong ;
Masuda, Naoki ;
Noh, Jae Dong .
PHYSICAL REVIEW E, 2006, 74 (06)
[2]   Analytical results for coupled-map lattices with long-range interactions - art. no. 045202 [J].
Anteneodo, C ;
Pinto, SED ;
Batista, AM ;
Viana, RL .
PHYSICAL REVIEW E, 2003, 68 (04)
[3]   Emergence of scaling in random networks [J].
Barabási, AL ;
Albert, R .
SCIENCE, 1999, 286 (5439) :509-512
[4]   Velocity and hierarchical spread of epidemic outbreaks in scale-free networks -: art. no. 178701 [J].
Barthélemy, M ;
Barrat, A ;
Pastor-Satorras, R ;
Vespignani, A .
PHYSICAL REVIEW LETTERS, 2004, 92 (17) :178701-1
[5]   Dynamical patterns of epidemic outbreaks in complex heterogeneous networks [J].
Barthélemy, M ;
Barrat, A ;
Pastor-Satorras, R ;
Vespignani, A .
JOURNAL OF THEORETICAL BIOLOGY, 2005, 235 (02) :275-288
[6]   Absence of epidemic threshold in scale-free networks with degree correlations -: art. no. 028701 [J].
Boguñá, M ;
Pastor-Satorras, R ;
Vespignani, A .
PHYSICAL REVIEW LETTERS, 2003, 90 (02) :4-028701
[7]   The scaling laws of human travel [J].
Brockmann, D ;
Hufnagel, L ;
Geisel, T .
NATURE, 2006, 439 (7075) :462-465
[8]   Efficient immunization strategies for computer networks and populations [J].
Cohen, R ;
Havlin, S ;
ben-Avraham, D .
PHYSICAL REVIEW LETTERS, 2003, 91 (24)
[9]  
Dybiec B, 2004, PHYS REV E, V70, DOI 10.1103/PhysRevE.70.066145
[10]   Transmission potential of smallpox: Estimates based on detailed data from an outbreak [J].
Eichner, M ;
Dietz, K .
AMERICAN JOURNAL OF EPIDEMIOLOGY, 2003, 158 (02) :110-117