Molecular epidemiology with deep sequence pathogen data
The potential that pathogen genomics brings to the study of infectious disease transmission is now well-established. Until recently, however, researchers have generally used a single genome sequence to represent the infection of each individual in the transmission chain. Some approaches have simply made pairwise comparisons between sequences in order to identify closely-linked infections, while more complex “phylodynamic” methods have integrated single sequences with other epidemiological data and mathematical models of transmission. As sequencing technology has improved, however, a new approach has become viable, which is to use a sample of the pathogen diversity existing within each individual to generate multiple sequences per host. Methodological work has shown that the phylogenetic patterns identified from such data can identify not only hosts that are closely related in the transmission chain, but the direction of transmission between them.
In this talk, Dr Matthew Hall will describe these methodologies and the insights they have provided in several studies, with a particular emphasis on HIV data obtained using Illumina short-read sequencing and his software package phyloscanner.
Dr. Hall is a researcher in pathogen phylodynamics, with a particular interest in inference of who infected who. He is also interested in investigating the effects of sampling bias in molecular epidemiological studies. Dr. Hall obtained his PhD in 2015 at the University of Edinburgh and currently works at the BDI on the PANGEA HIV project, focussing on the reconstruction of transmission patterns within a very large and rich dataset of next-generation HIV sequences.
This session will be livestreamed/recorded - accessible to internal audience only.
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