Modeling the growth and decline of pathogen effective population size provides insight into epidemic dynamics and drivers of antimicrobial resistance

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Title: Modeling the growth and decline of pathogen effective population size provides insight into epidemic dynamics and drivers of antimicrobial resistance
Author(s): Volz, E
Didelot, X
Item Type: Journal Article
Abstract: Nonparametric population genetic modeling provides a simple and flexible approach for studying demographic history and epidemic dynamics using pathogen sequence data. Existing Bayesian approaches are premised on stochastic processes with stationary increments which may provide an unrealistic prior for epidemic histories which feature extended period of exponential growth or decline. We show that nonparametric models defined in terms of the growth rate of the effective population size can provide a more realistic prior for epidemic history. We propose a nonparametric autoregressive model on the growth rate as a prior for effective population size, which corresponds to the dynamics expected under many epidemic situations. We demonstrate the use of this model within a Bayesian phylodynamic inference framework. Our method correctly reconstructs trends of epidemic growth and decline from pathogen genealogies even when genealogical data are sparse and conventional skyline estimators erroneously predict stable population size. We also propose a regression approach for relating growth rates of pathogen effective population size and time-varying variables that may impact the replicative fitness of a pathogen. The model is applied to real data from rabies virus and Staphylococcus aureus epidemics. We find a close correspondence between the estimated growth rates of a lineage of methicillin-resistant S. aureus and population-level prescription rates of β -lactam antibiotics. The new models are implemented in an open source R package called skygrowth which is available at https://github.com/mrc-ide/skygrowth.
Publication Date: 1-Jul-2018
Date of Acceptance: 7-Feb-2018
URI: http://hdl.handle.net/10044/1/56881
DOI: https://dx.doi.org/10.1093/sysbio/syy007
ISSN: 1063-5157
Publisher: Oxford University Press (OUP)
Start Page: 719
End Page: 728
Journal / Book Title: Systematic Biology
Volume: 67
Issue: 4
Sponsor/Funder: Medical Research Council (MRC)
National Institutes of Health
Funder's Grant Number: MR/K010174/1B
258162IMP
Copyright Statement: © The Author(s) 2018. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. 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. For Permissions, please email: jou rnals.permissions@oup.com
Keywords: MRSA
antimicrobial resistance
effective population size
growth rate
phylodynamics
skygrowth
0603 Evolutionary Biology
0604 Genetics
Evolutionary Biology
Publication Status: Published
Open Access location: https://www.biorxiv.org/content/early/2017/10/27/210054
Online Publication Date: 2018-02-07
Appears in Collections:Faculty of Medicine
Epidemiology, Public Health and Primary Care



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