• DocumentCode
    677690
  • Title

    Identifying superspreaders for epidemics using R0-adjusted network centrality

  • Author

    Taesik Lee ; Hyun-Rok Lee ; Kyosang Hwang

  • Author_Institution
    Ind. & Syst. Eng., Korea Adv. Inst. of Sci. & Technol., Daejeon, South Korea
  • fYear
    2013
  • fDate
    8-11 Dec. 2013
  • Firstpage
    2239
  • Lastpage
    2249
  • Abstract
    Identifying “superspreaders” in a network is a key problem to designing an effective mitigation strategy against a spread of an epidemic disease. Superspreaders are a set of nodes that play a hub role in a disease spread network, and classical network centrality measures are often used to identify such hubs. In this research, we test a hypothesis that a node´s intrinsic property plays a role in the dynamics of disease spreading in a network. Specifically, we test whether spreading of an epidemic disease is affected by a node´s property of being an amplifier or attenuator. Using GEM (Global Epidemic Model), we conducted experiments for epidemic spreading on a hypothetical, global network of 155 cities. We find that node´s intrinsic property plays a significant role in disease spreading dynamics. Based on these findings we propose a new metric, R0-adjusted centrality.
  • Keywords
    diseases; epidemics; network theory (graphs); GEM; R0-adjusted network centrality; amplifier; attenuator; disease spreading dynamics; epidemic disease spreading network; global epidemic model; global network; hubs identification; mitigation strategy; network centrality measures; node intrinsic property; superspreaders; Atmospheric modeling; Cities and towns; Diseases; Mathematical model; Sociology; Statistics; Weight measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Conference (WSC), 2013 Winter
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4799-2077-8
  • Type

    conf

  • DOI
    10.1109/WSC.2013.6721600
  • Filename
    6721600