BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Bayesian inference for stochastic epidemic models in structured po
 pulations based on final outcome data - Philip O'Neill\, University of Not
 tingham
DTSTART:20070220T143000Z
DTEND:20070220T153000Z
UID:TALK6347@talks.cam.ac.uk
CONTACT:4904
DESCRIPTION:We consider the problem of Bayesian inference for infection ra
 tes in a multi-type stochastic epidemic model in which the population has 
 a given structure\, given data on final outcome. For such data\, a likelih
 ood is both analytically and numerically intractable. This problem can be 
 overcome by imputation of suitable latent variables. We describe two such 
 approaches based on different representations of the epidemic model. We al
 so consider extentions to the methodology for the situation where the obse
 rved data are a fraction of the entire population. The methods are illustr
 ated with data on influenza outbreaks.
LOCATION:Large Seminar Room\, 1st Floor\, Institute of Public Health\, Uni
 versity Forvie Site\, Robinson Way\, Cambridge
END:VEVENT
END:VCALENDAR