{"title":"Halting Infectious Disease Spread in Social Network","authors":"Zhen-peng Li, Guo-liang Shao","doi":"10.1109/IWCFTA.2009.70","DOIUrl":null,"url":null,"abstract":"We present a hierarchical structure or multi-scales infectious diseases analysis based on meta-population model with heterogenous connectivity and mobility patterns, and study the effect of multi-scales hierarchical connectivity pattern of complex social network on the propagation dynamics of epidemics. The simulation results show that the scale of growth time of outbreaks is inversely proportional to the network degree ¿uctuations within each hierarchies(scales). We also provide the analysis of infected evolution density versus hierarchical degree and time scale. This paper presents an approach to understand the disease spreading in large transportation network or virus transmission in the Internet. In addition, our study offer some useful measures to control and eradicate epidemic or virus within the large scale complex network with hierarchical meta-population structure.","PeriodicalId":279256,"journal":{"name":"2009 International Workshop on Chaos-Fractals Theories and Applications","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Workshop on Chaos-Fractals Theories and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWCFTA.2009.70","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
We present a hierarchical structure or multi-scales infectious diseases analysis based on meta-population model with heterogenous connectivity and mobility patterns, and study the effect of multi-scales hierarchical connectivity pattern of complex social network on the propagation dynamics of epidemics. The simulation results show that the scale of growth time of outbreaks is inversely proportional to the network degree ¿uctuations within each hierarchies(scales). We also provide the analysis of infected evolution density versus hierarchical degree and time scale. This paper presents an approach to understand the disease spreading in large transportation network or virus transmission in the Internet. In addition, our study offer some useful measures to control and eradicate epidemic or virus within the large scale complex network with hierarchical meta-population structure.