The INI has a new website!

This is a legacy webpage. Please visit the new site to ensure you are seeing up to date information.

Skip to content



Bayesian inference for structured population models given final outcome data

O'Neill, PD (Nottingham)
Friday 24 November 2006, 10:00-11:00

Seminar Room 1, Newton Institute


We consider the problem of Bayesian inference for infection rates in a multi-type stochastic epidemic model in which the population has a given structure, given data on final outcome. For such data, a likelihood 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 also consider extentions to the methodology for the situation where the observed data are a fraction of the entire population. The methods are illustrated with data on influenza outbreaks.


[pdf ]



Slideshow (view full screen)

Flash Player is required to view the Flash presentation. Get the Flash Player.

Back to top ∧