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Online inference and prediction for infectious diseases: a case study in Avian Influenza

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If you have a question about this talk, please contact Nikolaos Demiris .

Modelling spread of veterinary infectious diseases at the farm level has many advantages in terms of trying to understand prevalent modes of transmission, and the construction of appropriate control strategies. However for large numbers of farms, likelihood-based inference is methodologically challenging, particularly on-line inference as the epidemic progresses. This talk will describe a Bayesian approach to inference and prediction, focusing on Avian Infuenza in the poultry industry and Foot and Mouth Disease.

This talk is part of the MRC Biostatistics Unit Seminars series.

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