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Genomic infectious disease epidemiology in partially sampled and ongoing outbreaks

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Title: Genomic infectious disease epidemiology in partially sampled and ongoing outbreaks
Authors: Didelot, X
Fraser, C
Gardy, J
Colijn, C
Item Type: Journal Article
Abstract: Genomic data is 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 which isolates within the outbreak are most closely related to each other. Unfortunately, the phylogenetic trees typically used to represent this variation are not directly informative about who infected whom { a phylogenetic tree is not a transmission tree. However, a transmission tree can be inferred from a phylogeny while accounting for within-host genetic diversity by colouring the branches of a phylogeny according to which host those branches were in. Here we extend this approach and show that it can be applied to partially sampled and ongoing outbreaks. This requires computing the correct probability of an observed transmission tree and we herein demonstrate how to do this for a large class of epidemiological models. We also demonstrate how the branch colouring approach can incorporate a variable number of unique colours to represent unsampled intermediates in transmission chains. The resulting algorithm is a reversible jump Monte-Carlo Markov Chain, which we apply to both simulated data and real data from an outbreak of tuberculosis. By accounting for unsampled cases and an outbreak which may not have reached its end, our method is uniquely suited to use in a public health environment during real-time outbreak investigations. We implemented this transmission tree inference methodology in an R package called TransPhylo, which is freely available from https://github.com/xavierdidelot/TransPhylo
Issue Date: 19-Jan-2017
Date of Acceptance: 21-Nov-2016
URI: http://hdl.handle.net/10044/1/42711
DOI: https://dx.doi.org/10.1093/molbev/msw275
ISSN: 1537-1719
Publisher: Oxford University Press (OUP)
Start Page: 997
End Page: 1007
Journal / Book Title: Molecular Biology and Evolution
Volume: 34
Issue: 4
Copyright Statement: © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Medical Research Council (MRC)
National Institute for Health Research
Medical Research Council (MRC)
Funder's Grant Number: EP/K026003/1
Keywords: Science & Technology
Life Sciences & Biomedicine
Biochemistry & Molecular Biology
Evolutionary Biology
Genetics & Heredity
genomic epidemiology
transmission analysis
infectious disease outbreak
0604 Genetics
0603 Evolutionary Biology
0601 Biochemistry And Cell Biology
Publication Status: Published
Appears in Collections:Applied Mathematics and Mathematical Physics
School of Public Health
Faculty of Natural Sciences