OxTalks will soon move to the new Halo platform and will become 'Oxford Events.' There will be a need for an OxTalks freeze. This was previously planned for Friday 14th November – a new date will be shared as soon as it is available (full details will be available on the Staff Gateway).
In the meantime, the OxTalks site will remain active and events will continue to be published.
If staff have any questions about the Oxford Events launch, please contact halo@digital.ox.ac.uk
Genomic data are increasingly being used to understand infectious disease epidemiology. Isolates from a given outbreak are sequenced, and the patterns of shared variation are used to infer phylogenetic trees. However these are not directly informative about who infected whom: a phylogenetic tree is not a transmission tree. A transmission tree can be inferred from a phylogeny while accounting for within-host genetic diversity by coloring the branches of a phylogeny according to which host those branches were in. We show how this approach can be applied to partially sampled and ongoing outbreaks. This requires computing the correct probability of a partially observed transmission tree and we demonstrate how to do this for a large class of epidemiological models. The resulting uncertainty on who infected whom can be high and we explore two solutions to this problem: the use of several genomes per host, and the use of additional epidemiological data.