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Computation and inference

This theme provides a space for the exploration of ideas for efficient computation, to learn new methodologies for inference and to share knowledge across CMMID.

In the CMMID we use mathematical and statistical tools to understand the dynamics and control of infection. Members use methods of inference to inform data based decisions which can account for large and/or complex data, models and questions. In addition, to deal with these complexities, there is a need for efficient computation.  

From methods to account for partial observation of cases and uncertainty in confirmation of cases, to tools for creating fast and reproducible code, challenges arise in both computation and inference that are common to many infectious disease research questions. 

We are looking for speakers to lead sessions on Statistical Inference. If interested, please contact Danny Scarponi.

People

Danny Scarponi and Sam Abbott, Katherine Atkins,  Marc Baguelin, Lloyd Chapman, Sam Clifford, Nick Davies, Roz Eggo, Jon Emery, Akira Endo, Flavio Finger, Stefan Flasche, Seb Funk, Liza Hadley, Alasdair Henderson, Chris Jarvis, Petra Klepac, Gwen Knight, Adam Kucharski, Yang Liu, Nicky McCreesh, Hannah Meredith, James Munday, Amy Pinsent, Billy Quilty, Kathleen O’Reilly, Alexis Robert, Tom Sumner, Moritz Wagner, Naomi R Waterlow, Nayantara Wijayanandana, Kevin van Zandvoort.

Publications