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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:20161214T093000
DTEND;TZID=Europe/London:20161214T103000
UID:TALK69495AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/69495
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. &nbsp\;The second
  extension\,&nbsp\;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\, &nbsp\;degree correlation an
 d degree distribution. &nbsp\;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. &nbsp\;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. &nbsp\;The theory 
 is illustrated by numerical studies\, which explor
 e the impact of network properties on the outcome 
 of an epidemic.
LOCATION:Seminar Room 1\, Newton Institute
CONTACT:INI IT
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