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CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:Epidemics on networks - Frank Granville Ball (Univ
ersity of Nottingham)
DTSTART;TZID=Europe/London:20160818T140000
DTEND;TZID=Europe/London:20160818T150000
UID:TALK66975AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/66975
DESCRIPTION:In this talk we consider two extensions of the sta
ndard stochastic epidemic SIR (Susceptible-Infecte
d-Recovered) on a configuration model network. &nb
sp\;The first extension\, which is joint work with
Peter Neal (Lancaster University)\, incorporates
casual contacts\, i.e. with people chosen uniforml
y at random from the population. \;The second
extension\, \;which is joint work with Tom Br
itton (Stockholm University) and David Sirl (Unive
rsity of Nottingham)\, involves the spread of an e
pidemic on a random network model which allows for
tunable clustering\, \;degree correlation an
d degree distribution. \;For each model\, app
roximating branching processes are used to obtain
a threshold parameter\, which determines whether o
r not an epidemic with few initial infectives can
become established and lead to a major outbreak\,
and the (approximate) probability and relative fin
al size of a major outbreak. \;For the model
with casual contacts\, an embedding argument is us
ed to derive a central limit theorem for the size
of a major epidemic\; similar methods lead to the
asymptotic variance of the giant component in a co
nfiguration model random graph. \;The theory
is illustrated by numerical studies\, which explor
e the impact of network properties on the outcome
of an epidemic.
LOCATION:Seminar Room 2\, Newton Institute
CONTACT:INI IT
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