Eight challenges in phylodynamic inference

The field of phylodynamics, which attempts to enhance our understanding of infectious disease dynamics using pathogen phylogenies, has made great strides in the past decade. Basic epidemiological and evolutionary models are now well characterized with inferential frameworks in place. However, signif...

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Main Authors: Simon D.W. Frost, Oliver G. Pybus, Julia R. Gog, Cecile Viboud, Sebastian Bonhoeffer, Trevor Bedford
Format: Article
Language:English
Published: Elsevier 2015-03-01
Series:Epidemics
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1755436514000437
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author Simon D.W. Frost
Oliver G. Pybus
Julia R. Gog
Cecile Viboud
Sebastian Bonhoeffer
Trevor Bedford
author_facet Simon D.W. Frost
Oliver G. Pybus
Julia R. Gog
Cecile Viboud
Sebastian Bonhoeffer
Trevor Bedford
author_sort Simon D.W. Frost
collection DOAJ
description The field of phylodynamics, which attempts to enhance our understanding of infectious disease dynamics using pathogen phylogenies, has made great strides in the past decade. Basic epidemiological and evolutionary models are now well characterized with inferential frameworks in place. However, significant challenges remain in extending phylodynamic inference to more complex systems. These challenges include accounting for evolutionary complexities such as changing mutation rates, selection, reassortment, and recombination, as well as epidemiological complexities such as stochastic population dynamics, host population structure, and different patterns at the within-host and between-host scales. An additional challenge exists in making efficient inferences from an ever increasing corpus of sequence data.
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spelling doaj.art-10fb898006da46ecb29e0a56267b47812022-12-21T18:36:31ZengElsevierEpidemics1755-43651878-00672015-03-0110C889210.1016/j.epidem.2014.09.001Eight challenges in phylodynamic inferenceSimon D.W. Frost0Oliver G. Pybus1Julia R. Gog2Cecile Viboud3Sebastian Bonhoeffer4Trevor Bedford5Department of Veterinary Medicine, University of Cambridge, Cambridge, UKDepartment of Zoology, University of Oxford, Oxford, UKDepartment of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UKFogarty International Center, National Institutes of Health, Bethesda, USAInstitute of. Integrative Biology, ETH Zurich, Zurich, SwitzerlandVaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USAThe field of phylodynamics, which attempts to enhance our understanding of infectious disease dynamics using pathogen phylogenies, has made great strides in the past decade. Basic epidemiological and evolutionary models are now well characterized with inferential frameworks in place. However, significant challenges remain in extending phylodynamic inference to more complex systems. These challenges include accounting for evolutionary complexities such as changing mutation rates, selection, reassortment, and recombination, as well as epidemiological complexities such as stochastic population dynamics, host population structure, and different patterns at the within-host and between-host scales. An additional challenge exists in making efficient inferences from an ever increasing corpus of sequence data.http://www.sciencedirect.com/science/article/pii/S1755436514000437PhylodynamicsCoalescent modelsSelectionRecombination
spellingShingle Simon D.W. Frost
Oliver G. Pybus
Julia R. Gog
Cecile Viboud
Sebastian Bonhoeffer
Trevor Bedford
Eight challenges in phylodynamic inference
Epidemics
Phylodynamics
Coalescent models
Selection
Recombination
title Eight challenges in phylodynamic inference
title_full Eight challenges in phylodynamic inference
title_fullStr Eight challenges in phylodynamic inference
title_full_unstemmed Eight challenges in phylodynamic inference
title_short Eight challenges in phylodynamic inference
title_sort eight challenges in phylodynamic inference
topic Phylodynamics
Coalescent models
Selection
Recombination
url http://www.sciencedirect.com/science/article/pii/S1755436514000437
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