{"title":"分类度混合网络中的流行病传播与免疫","authors":"X. Ge, Lili Li, Hui Li","doi":"10.1109/ICNC.2014.6975979","DOIUrl":null,"url":null,"abstract":"Epidemic spreading and immunization are influenced by network structure measured via metrics. Degree mixing is a common property of network reflecting links in regards of node degree. In this paper we study epidemics spreading and immunization on degree mixing using empirical network data, analytic models, and numerical simulation. We demonstrate that assortative (or disassortative) degree mixing indeed influence spreading and effect of immunization. In the point of epidemic spreading, assortativity decreases speed and stable infected ratio, resulting in a better result, but decrease epidemic threshold. In the point of immunization, strategy that targets hub nodes has better effect on disassortative network.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Epidemic spreading and immunization on assortative degree mixing networks\",\"authors\":\"X. Ge, Lili Li, Hui Li\",\"doi\":\"10.1109/ICNC.2014.6975979\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Epidemic spreading and immunization are influenced by network structure measured via metrics. Degree mixing is a common property of network reflecting links in regards of node degree. In this paper we study epidemics spreading and immunization on degree mixing using empirical network data, analytic models, and numerical simulation. We demonstrate that assortative (or disassortative) degree mixing indeed influence spreading and effect of immunization. In the point of epidemic spreading, assortativity decreases speed and stable infected ratio, resulting in a better result, but decrease epidemic threshold. In the point of immunization, strategy that targets hub nodes has better effect on disassortative network.\",\"PeriodicalId\":208779,\"journal\":{\"name\":\"2014 10th International Conference on Natural Computation (ICNC)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 10th International Conference on Natural Computation (ICNC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNC.2014.6975979\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 10th International Conference on Natural Computation (ICNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2014.6975979","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Epidemic spreading and immunization on assortative degree mixing networks
Epidemic spreading and immunization are influenced by network structure measured via metrics. Degree mixing is a common property of network reflecting links in regards of node degree. In this paper we study epidemics spreading and immunization on degree mixing using empirical network data, analytic models, and numerical simulation. We demonstrate that assortative (or disassortative) degree mixing indeed influence spreading and effect of immunization. In the point of epidemic spreading, assortativity decreases speed and stable infected ratio, resulting in a better result, but decrease epidemic threshold. In the point of immunization, strategy that targets hub nodes has better effect on disassortative network.