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.

People

Amanda Minter (theme co-ordinator), Katherine Atkins, Roz Eggo, Akira Endo, Seb Funk, Alasdair Henderson, Adam Kucharski, Nicky McCreesh, Kathleen O’Reilly, Tom Sumner, Nayantara Wijayanandana