Imperial College London
Alternate

DrErikVolz

Faculty of Medicine, School of Public Health

Reader in Population Biology of Infectious Diseases
 
 
 
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Contact

 

+44 (0)20 7594 1933e.volz Website

 
 
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Location

 

UG10Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Volz:2018:sysbio/syy007,
author = {Volz, E and Didelot, X},
doi = {sysbio/syy007},
journal = {Systematic Biology},
pages = {719--728},
title = {Modeling the growth and decline of pathogen effective population size provides insight into epidemic dynamics and drivers of antimicrobial resistance},
url = {http://dx.doi.org/10.1093/sysbio/syy007},
volume = {67},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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 ofβ-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.
AU  - Volz,E
AU  - Didelot,X
DO  - sysbio/syy007
EP  - 728
PY  - 2018///
SN  - 1063-5157
SP  - 719
TI  - Modeling the growth and decline of pathogen effective population size provides insight into epidemic dynamics and drivers of antimicrobial resistance
T2  - Systematic Biology
UR  - http://dx.doi.org/10.1093/sysbio/syy007
UR  - http://hdl.handle.net/10044/1/56881
VL  - 67
ER  -
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