{"title":"具有交通流的无标度网络中流行病的传播","authors":"Ya-Qi Wang, Guoping Jiang","doi":"10.1109/IWCFTA.2010.44","DOIUrl":null,"url":null,"abstract":"In this paper, based on the mean-field theory, we propose a new susceptible-infected-removed (SIR) model to study epidemic spreading on scale-free networks with traffic flow. Theoretical analysis shows that as the network traffic flow increases, the epidemic prevalence is obviously enhanced, and the epidemic threshold is reduced. We also find that the epidemic threshold is related to the ratio between the first and second moments of the network’s algorithm betweenness distribution. Moreover, the heterogeneity levels of the networks weaken the epidemic spreading. We confirm all results by sufficient numerical simulations.","PeriodicalId":157339,"journal":{"name":"2010 International Workshop on Chaos-Fractal Theories and Applications","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spreading of Epidemics on Scale-Free Networks with Traffic Flow\",\"authors\":\"Ya-Qi Wang, Guoping Jiang\",\"doi\":\"10.1109/IWCFTA.2010.44\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, based on the mean-field theory, we propose a new susceptible-infected-removed (SIR) model to study epidemic spreading on scale-free networks with traffic flow. Theoretical analysis shows that as the network traffic flow increases, the epidemic prevalence is obviously enhanced, and the epidemic threshold is reduced. We also find that the epidemic threshold is related to the ratio between the first and second moments of the network’s algorithm betweenness distribution. Moreover, the heterogeneity levels of the networks weaken the epidemic spreading. We confirm all results by sufficient numerical simulations.\",\"PeriodicalId\":157339,\"journal\":{\"name\":\"2010 International Workshop on Chaos-Fractal Theories and Applications\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Workshop on Chaos-Fractal Theories and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWCFTA.2010.44\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Workshop on Chaos-Fractal Theories and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWCFTA.2010.44","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spreading of Epidemics on Scale-Free Networks with Traffic Flow
In this paper, based on the mean-field theory, we propose a new susceptible-infected-removed (SIR) model to study epidemic spreading on scale-free networks with traffic flow. Theoretical analysis shows that as the network traffic flow increases, the epidemic prevalence is obviously enhanced, and the epidemic threshold is reduced. We also find that the epidemic threshold is related to the ratio between the first and second moments of the network’s algorithm betweenness distribution. Moreover, the heterogeneity levels of the networks weaken the epidemic spreading. We confirm all results by sufficient numerical simulations.