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SUMMARY:Epidemics on networks - Frank Granville Ball (University of Nottin
 gham)
DTSTART:20160818T130000Z
DTEND:20160818T140000Z
UID:TALK66975@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:In this talk we consider two extensions of the standard stocha
 stic epidemic SIR (Susceptible-Infected-Recovered) on a configuration mode
 l network. &nbsp\;The first extension\, which is joint work with Peter Nea
 l (Lancaster University)\, incorporates casual contacts\, i.e. with people
  chosen uniformly at random from the population. &nbsp\;The second extensi
 on\,&nbsp\;which is joint work with Tom Britton (Stockholm University) and
  David Sirl (University of Nottingham)\, involves the spread of an epidemi
 c on a random network model which allows for tunable clustering\, &nbsp\;d
 egree correlation and degree distribution. &nbsp\;For each model\, approxi
 mating branching processes are used to obtain a threshold parameter\, whic
 h determines whether or not an epidemic with few initial infectives can be
 come established and lead to a major outbreak\, and the (approximate) prob
 ability and relative final size of a major outbreak. &nbsp\;For the model 
 with casual contacts\, an embedding argument is used to derive a central l
 imit theorem for the size of a major epidemic\; similar methods lead to th
 e asymptotic variance of the giant component in a configuration model rand
 om graph. &nbsp\;The theory is illustrated by numerical studies\, which ex
 plore the impact of network properties on the outcome of an epidemic.
LOCATION:Seminar Room 2\, Newton Institute
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