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{Didelot:2023:ve/vead028,
author = {Didelot, X and Franceschi, V and Frost, SDW and Dennis, A and Volz, EM},
doi = {ve/vead028},
journal = {Virus Evolution},
title = {Model design for nonparametric phylodynamic inference and applications to pathogen surveillance},
url = {http://dx.doi.org/10.1093/ve/vead028},
volume = {9},
year = {2023}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Inference of effective population size from genomic data can provide unique information about demographic history and, when applied to pathogen genetic data, can also provide insights into epidemiological dynamics. The combination of nonparametric models for population dynamics with molecular clock models which relate genetic data to time has enabled phylodynamic inference based on large sets of time-stamped genetic sequence data. The methodology for nonparametric inference of effective population size is well-developed in the Bayesian setting, but here we develop a frequentist approach based on nonparametric latent process models of population size dynamics. We appeal to statistical principles based on out-of-sample prediction accuracy in order to optimize parameters that control shape and smoothness of the population size over time. Our methodology is implemented in a new R package entitled mlesky. We demonstrate the flexibility and speed of this approach in a series of simulation experiments and apply the methodology to a dataset of HIV-1 in the USA. We also estimate the impact of non-pharmaceutical interventions for COVID-19 in England using thousands of SARS-CoV-2 sequences. By incorporating a measure of the strength of these interventions over time within the phylodynamic model, we estimate the impact of the first national lockdown in the UK on the epidemic reproduction number.
AU  - Didelot,X
AU  - Franceschi,V
AU  - Frost,SDW
AU  - Dennis,A
AU  - Volz,EM
DO  - ve/vead028
PY  - 2023///
SN  - 2057-1577
TI  - Model design for nonparametric phylodynamic inference and applications to pathogen surveillance
T2  - Virus Evolution
UR  - http://dx.doi.org/10.1093/ve/vead028
UR  - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000993957700001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
UR  - https://academic.oup.com/ve/article/9/1/vead028/7152969
UR  - http://hdl.handle.net/10044/1/110344
VL  - 9
ER  -
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