Inferring epidemic contact structure from phylogenetic trees.

Contact structure is believed to have a large impact on epidemic spreading and consequently using networks to model such contact structure continues to gain interest in epidemiology. However, detailed knowledge of the exact contact structure underlying real epidemics is limited. Here we address the...

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Main Authors: Gabriel E Leventhal, Roger Kouyos, Tanja Stadler, Viktor von Wyl, Sabine Yerly, Jürg Böni, Cristina Cellerai, Thomas Klimkait, Huldrych F Günthard, Sebastian Bonhoeffer
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2012-01-01
Series:PLoS Computational Biology
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22412361/?tool=EBI
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spelling doaj-e7921c13289d44fca8d68e80df4d24212021-04-21T14:55:15ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582012-01-0183e100241310.1371/journal.pcbi.1002413Inferring epidemic contact structure from phylogenetic trees.Gabriel E LeventhalRoger KouyosTanja StadlerViktor von WylSabine YerlyJürg BöniCristina CelleraiThomas KlimkaitHuldrych F GünthardSebastian BonhoefferContact structure is believed to have a large impact on epidemic spreading and consequently using networks to model such contact structure continues to gain interest in epidemiology. However, detailed knowledge of the exact contact structure underlying real epidemics is limited. Here we address the question whether the structure of the contact network leaves a detectable genetic fingerprint in the pathogen population. To this end we compare phylogenies generated by disease outbreaks in simulated populations with different types of contact networks. We find that the shape of these phylogenies strongly depends on contact structure. In particular, measures of tree imbalance allow us to quantify to what extent the contact structure underlying an epidemic deviates from a null model contact network and illustrate this in the case of random mixing. Using a phylogeny from the Swiss HIV epidemic, we show that this epidemic has a significantly more unbalanced tree than would be expected from random mixing.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22412361/?tool=EBI
collection DOAJ
language English
format Article
sources DOAJ
author Gabriel E Leventhal
Roger Kouyos
Tanja Stadler
Viktor von Wyl
Sabine Yerly
Jürg Böni
Cristina Cellerai
Thomas Klimkait
Huldrych F Günthard
Sebastian Bonhoeffer
spellingShingle Gabriel E Leventhal
Roger Kouyos
Tanja Stadler
Viktor von Wyl
Sabine Yerly
Jürg Böni
Cristina Cellerai
Thomas Klimkait
Huldrych F Günthard
Sebastian Bonhoeffer
Inferring epidemic contact structure from phylogenetic trees.
PLoS Computational Biology
author_facet Gabriel E Leventhal
Roger Kouyos
Tanja Stadler
Viktor von Wyl
Sabine Yerly
Jürg Böni
Cristina Cellerai
Thomas Klimkait
Huldrych F Günthard
Sebastian Bonhoeffer
author_sort Gabriel E Leventhal
title Inferring epidemic contact structure from phylogenetic trees.
title_short Inferring epidemic contact structure from phylogenetic trees.
title_full Inferring epidemic contact structure from phylogenetic trees.
title_fullStr Inferring epidemic contact structure from phylogenetic trees.
title_full_unstemmed Inferring epidemic contact structure from phylogenetic trees.
title_sort inferring epidemic contact structure from phylogenetic trees.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2012-01-01
description Contact structure is believed to have a large impact on epidemic spreading and consequently using networks to model such contact structure continues to gain interest in epidemiology. However, detailed knowledge of the exact contact structure underlying real epidemics is limited. Here we address the question whether the structure of the contact network leaves a detectable genetic fingerprint in the pathogen population. To this end we compare phylogenies generated by disease outbreaks in simulated populations with different types of contact networks. We find that the shape of these phylogenies strongly depends on contact structure. In particular, measures of tree imbalance allow us to quantify to what extent the contact structure underlying an epidemic deviates from a null model contact network and illustrate this in the case of random mixing. Using a phylogeny from the Swiss HIV epidemic, we show that this epidemic has a significantly more unbalanced tree than would be expected from random mixing.
url https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22412361/?tool=EBI
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