The aim of this theme is to develop improved methodology and practical software solutions for the rapid analysis of genomic data and associated metadata in order to accurately perform outbreak detection, investigation, monitoring and control. The strategy is to develop statistical software tools that can be applied in many situations, by initially focusing on specific examples of recent or ongoing outbreaks. Our work will focus around a generally applicable toolchain for analysis of linked cases developed over the years by Didelot and others, consisting of ClonalFrame (phylogenetic tool accounting for recombination), BactDating (inference of dated phylogenies) and TransPhylo (reconstruction of transmission trees). At its core is the concept of a dated phylogeny, a data structure informative about many important epidemiological aspects such as phylogeography, phylodynamics, who infected whom and key parameters such as the basic reproduction number or sampling proportion. In particular, transmission trees can be reconstructed from a dated phylogeny while accounting for within-host diversity and missing cases. Proof of concept of the utility of this concept and our toolchain exists for multiple diseases, but its predictive power is not yet being harnessed in public health systems in England; our research questions focus around development and deployment of these tools.