Csegő Balázs Kolok, Gergely Ódor, Dániel Keliger, Márton Karsai
{"title":"Epidemic paradox induced by awareness driven network dynamics","authors":"Csegő Balázs Kolok, Gergely Ódor, Dániel Keliger, Márton Karsai","doi":"arxiv-2409.01384","DOIUrl":null,"url":null,"abstract":"We study stationary epidemic processes in scale-free networks with local\nawareness behavior adopted by only susceptible, only infected, or all nodes. We\nfind that while the epidemic size in the susceptible-aware and the all-aware\nscenarios scales linearly with the network size, the scaling becomes sublinear\nin the infected-aware scenario, suggesting that fewer aware nodes may reduce\nthe epidemic size more effectively. We explain this paradox via numerical and\ntheoretical analysis, and highlight the role of influential nodes and their\ndisassortativity to raise awareness in epidemic scenarios.","PeriodicalId":501043,"journal":{"name":"arXiv - PHYS - Physics and Society","volume":"61 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Physics and Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.01384","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We study stationary epidemic processes in scale-free networks with local
awareness behavior adopted by only susceptible, only infected, or all nodes. We
find that while the epidemic size in the susceptible-aware and the all-aware
scenarios scales linearly with the network size, the scaling becomes sublinear
in the infected-aware scenario, suggesting that fewer aware nodes may reduce
the epidemic size more effectively. We explain this paradox via numerical and
theoretical analysis, and highlight the role of influential nodes and their
disassortativity to raise awareness in epidemic scenarios.