摘要: 在典型的SIRS模型的基础上,提出了一种无标度网络中带人工免疫的SIRS类传染病模型。运用平均场理论方法分析了所提模型的动力学行为,研究了在两种不同的人工免疫策略下病毒在一种特定的无标度网络上的传播情况,并模拟了两种免疫策略对病毒传播的影响。模拟结果表明,通过人工免疫可以有效降低稳态感染比例,提高系统的传播阈值,从而有效控制病毒在复杂网络上的传播。
[1] Poletti P,Ajelli M,Merler S.The effect of risk perception on the 2009H1N1pandemic influenza dynamics[J].PloS one,2011,6(2): [2] 陈端兵,黄晟,尚明生.复杂网络模型及其在疫情传播和控制中的应用研究[J].计算机科学,2011,8(6) [3] 王亚奇,蒋国平.复杂网络中考虑不完全免疫的病毒传播研究[J].物理学报,2010,9(10) [4] Kermark M D,Mckendrick A G.Contributions to the mathematical theory of epidemics [J].Proc Roy Soc,A:Part I,1927,115(5):700-721 [5] Nian F,Wang X.Efficient immunization strategies on complex networks[J].Journal of Theoretical Biology,2010,4(1):77-83 [6] Kuperman M,Abramson G.Small-world effect in an epidemiological model [J].Phys Rev Lett,2001,86(14):2909-2912 [7] Stehle J,Voirin N,Barrat A,et al.Simulation of an SEIR infectious disease model on the dynamic contact network of confe-rence attendees[J].BMC Medicine,2011,9:87 [8] Parshani R,Carmi S,Havlin S.Epidemic Threshold for the Susceptible-Infectious-Susceptible Model on Random Networks [J].Physical Review Letters,2010,104(25):258701 [9] Costa L F,Oliverira O N,Travieso G,et al.Analyzing and mo-deling real-world phenomena with complex networks:A survey of applications[J].Advances in Physics,2011,0(3):329-412 |
No related articles found! |
|