Introduction

Many modern epidemic models incorporate a level of complexity and realism that renders conventional likelihood-based fitting methods impractical at best.

 

This one-day workshop is designed to stimulate discussion on novel methods for fitting complex epidemic models to data. A focus will be on Approximate Bayesian Computation (ABC), which avoids computing likelihoods for systems that can be easily simulated.

 

The format of the day is intended to encourage discussion and collaboration with a mixture of sessions and talks delivered by leading epidemic modellers from around the UK.

 

 

 







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