Phylodynamic inference across epidemic scales

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Title: Phylodynamic inference across epidemic scales
Author(s): Volz, E
Romero-Severson, E
Leitner, TK
Item Type: Journal Article
Abstract: Within-host genetic diversity and large transmission bottlenecks confound phylodynamic inference of epidemiological dynamics. Conventional phylodynamic approaches assume that nodes in a time-scaled pathogen phylogeny correspond closely to the time of transmission between hosts that are ancestral to the sample. However, when hosts harbour diverse pathogen populations, node times can substantially pre-date infection times. Imperfect bottlenecks can cause lineages sampled in different individuals to coalesce in unexpected patterns. To address realistic violations of standard phylodynamic assumptions we developed a new inference approach based on a multi-scale coalescent model, accounting for nonlinear epidemiological dynamics, heterogeneous sampling through time, non-negligible genetic diversity of pathogens within hosts, and imperfect transmission bottlenecks. We apply this method to HIV-1 and Ebola virus outbreak sequence data, illustrating how and when conventional phylodynamic inference may give misleading results. Within-host diversity of HIV-1 causes substantial upwards bias in the number of infected hosts using conventional coalescent models, but estimates using the multi-scale model have greater consistency with reported number of diagnoses through time. In contrast, we find that within- host diversity of Ebola virus has little influence on estimated numbers of infected hosts or reproduction numbers, and estimates are highly consistent with the reported number of diagnoses through time. The multi-scale coalescent also enables estimation of within-host effective population size using single sequences from a random sample of patients. We find within-host population genetic diversity of HIV-1 p17 to be 2 Nμ = 0 . 012(95% CI:0 . 0066 − 0 . 023), which is lower than estimates based on HIV envelope serial sequencing of individual patients.
Publication Date: 14-Feb-2017
Date of Acceptance: 6-Feb-2017
URI: http://hdl.handle.net/10044/1/44363
DOI: https://dx.doi.org/10.1093/molbev/msx077
ISSN: 1537-1719
Publisher: Oxford University Press (OUP)
Start Page: 1276
End Page: 1288
Journal / Book Title: Molecular Biology and Evolution
Volume: 34
Issue: 5
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: Medical Research Council (MRC)
National Institutes of Health
Funder's Grant Number: MR/K010174/1B
340798
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.
Keywords: Science & Technology
Life Sciences & Biomedicine
Biochemistry & Molecular Biology
Evolutionary Biology
Genetics & Heredity
phylodynamics
coalescent
HIV
Ebola
EFFECTIVE POPULATION-SIZE
TRANSMISSION HISTORY
COALESCENT INFERENCE
EVOLUTIONARY RATES
EFFECTIVE NUMBER
SEQUENCE DATA
RISK GROUPS
DRUG-USERS
HIV-1
DYNAMICS
Ebola
HIV
coalescent
phylodynamics
Evolutionary Biology
0604 Genetics
0603 Evolutionary Biology
0601 Biochemistry And Cell Biology
Publication Status: Published
Appears in Collections:Faculty of Medicine
Epidemiology, Public Health and Primary Care



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