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SUMMARY:Probability seminar: Júlia Komjáthy
DTSTART;TZID=Europe/London:20260615T140000
DTEND;TZID=Europe/London:20260615T150000
DTSTAMP:20260608T005220Z
UID:39917786-6d3a-f111-88b4-7ced8d9a5614
CREATED:20260417T145600Z
DESCRIPTION:Title: How communities help epidemics survive\n\nAbstract: Rea
 l-world contact networks are rarely just homogeneous collections of indivi
 duals: they contain households\, workplaces\, classrooms\, social groups\,
  and many other overlapping communities. In this talk\, I will discuss a t
 oy model for understanding how such local community structure changes the 
 spread of an epidemic.\n\nThe network model will be a random intersection 
 graph\, where individuals belong to one or more microscopic-to-mesoscopic 
 communities\, and two individuals are connected if they share a community.
  On this graph we run a Markovian Susceptible-Infected-Susceptible epidemi
 c\, or equivalently the contact process: infected vertices recover at rate
  1\, while healthy vertices are infected by each infected neighbour at rat
 e lambda.\n\nThe main question is how the presence of communities changes 
 the epidemic threshold. More precisely\, we compare the contact process on
  a random intersection graph with the corresponding “community-free” r
 andom graph having the same/similar degree distribution. How does communit
 y structure affect the critical infection rate for long survival? And when
  the infection does survive for a long time\, how can we describe the meta
 stable density of infected individuals in terms of the community-size and 
 membership distributions? In this model\, these questions can be answered 
 quite explicitly\, giving a mathematically clean picture of how small loca
 l clusters can have a macroscopic effect on epidemic persistence.\n\nJoint
  work with Marco Seiler and Daniel Valesin.
LAST-MODIFIED:20260604T082258Z
LOCATION:Mathematical Institute - L5\, L5 Mathematical Institute Woodstock
  Road Oxford Oxfordshire OX2 6GG United Kingdom
SPEAKER:Júlia Komjáthy (TU Delft)
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