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Summary: Evolving Extremal Epidemic Networks
Daniel A. Ashlock
Mathematics and Statistics
University of Guelph
Guelph, ON Canada N1G 2R4
dashlock@uoguelph.ca
Fatemeh Jafargholi
Mathematics and Statistics
University of Geulph
Guelph, ON Canada N1G 2R4
fjafargh@uoguelph.ca
Abstract
The susceptible, infected, removed model for epidemics as-
sumes that the population in which the epidemic takes place is
well mixed. This strong assumption can be relaxed by permitting
the epidemic to spread only along the links of a contact network
or graph. This study uses evolutionary computation to search
for graphs that exhibit one of two extreme behaviors: maximum
epidemic duration or maximal number of individuals catching
the disease. The focus of the paper is on comparison of two
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