The trajectories of complex disease
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.
Date: 6 February 2025, 15:30
Venue: 24-29 St Giles', 24-29 St Giles' OX1 3LB
Venue Details: Large Lecture Theatre, Department of Statistics
Speaker: Professor Xavier Didelot (University of Warwick)
Organising department: Department of Statistics
Organisers: Beverley Lane (Department of Statistics, University of Oxford), Professor Simon Myers (University of Oxford)
Organiser contact email address: events@stats.ox.ac.uk
Hosts: Professor Christl Donnelly (University of Oxford), Professor Simon Myers (University of Oxford)
Part of: Distinguished Speaker Seminar
Booking required?: Required
Booking url: https://www.stats.ox.ac.uk/events/distinguished-speaker-seminar-6th-february-2025
Booking email: events@stats.ox.ac.uk
Cost: No charge
Audience: Members of the University only
Editor: Beverley Lane