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
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