• DocumentCode
    2190918
  • Title

    Fitting contact networks to epidemic behavior with an evolutionary algorithm

  • Author

    Ashlock, Daniel ; Shiller, Elisabeth

  • Author_Institution
    Dept. of Math. & Stat., Univ. of Guelph in Guelph, Guelph, ON, Canada
  • fYear
    2011
  • fDate
    11-15 April 2011
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Epidemic models often incorporate contact networks along which the disease can be passed. This study incorporates a restarting-recentering evolutionary algorithm, previously developed to locate extremal epidemic networks, together with a new representation, the toggle-delete representation, for evolvable networks. The goal is to locate networks that were likely to have produced a given epidemic behavior. This goal subsumes a new fitness function for driving selection in network evolution. Earlier representations used networks with a fixed sequence of contact numbers. The new representation can add and remove edges from the network, permitting a search that varies contact numbers within the network. A parameter setting study is performed on an epidemic profile obtained from an random network and then tested on a bimodal profile invented by the researchers. The algorithm succeeds in producing networks that cause epidemics run on them to mimic the specified epidemic profiles.
  • Keywords
    biology computing; epidemics; evolutionary computation; bimodal profile; contact networks; epidemic profile; evolutionary algorithm; extremal epidemic networks; toggle-delete representation; Arrays; Diseases; Evolutionary computation; Mathematical model; Measurement; Social network services; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2011 IEEE Symposium on
  • Conference_Location
    Paris
  • Print_ISBN
    978-1-4244-9896-3
  • Type

    conf

  • DOI
    10.1109/CIBCB.2011.5948466
  • Filename
    5948466