Imperial College London
Alternate

ProfessorChristopheFraser

Faculty of Medicine, School of Public Health

Visiting Professor
 
 
 
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Contact

 

c.fraser Website

 
 
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Location

 

G28Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Le:2018:10.1016/j.epidem.2017.10.001,
author = {Le, Vu SOK and Ratmann, O and Delpech, V and Brown, AE and Gill, ON and Tostevin, A and Fraser, C and Volz, EM},
doi = {10.1016/j.epidem.2017.10.001},
journal = {Epidemics},
pages = {1--10},
title = {Comparison of cluster-based and source-attribution methods for estimating transmission risk using large HIV sequence databases},
url = {http://dx.doi.org/10.1016/j.epidem.2017.10.001},
volume = {23},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Phylogenetic clustering of HIV sequences from a random sample of patients can reveal epidemiological transmission patterns, but interpretation is hampered by limited theoretical support and statistical properties of clustering analysis remain poorly understood. Alternatively, source attribution methods allow fitting of HIV transmission models and thereby quantify aspects of disease transmission.A simulation study was conducted to assess error rates of clustering methods for detecting transmission risk factors. We modeled HIV epidemics among men having sex with men and generated phylogenies comparable to those that can be obtained from HIV surveillance data in the UK. Clustering and source attribution approaches were applied to evaluate their ability to identify patient attributes as transmission risk factors.We find that commonly used methods show a misleading association between cluster size or odds of clustering and covariates that are correlated with time since infection, regardless of their influence on transmission. Clustering methods usually have higher error rates and lower sensitivity than source attribution method for identifying transmission risk factors. But neither methods provide robust estimates of transmission risk ratios. Source attribution method can alleviate drawbacks from phylogenetic clustering but formal population genetic modeling may be required to estimate quantitative transmission risk factors.
AU  - Le,Vu SOK
AU  - Ratmann,O
AU  - Delpech,V
AU  - Brown,AE
AU  - Gill,ON
AU  - Tostevin,A
AU  - Fraser,C
AU  - Volz,EM
DO  - 10.1016/j.epidem.2017.10.001
EP  - 10
PY  - 2018///
SN  - 1755-4365
SP  - 1
TI  - Comparison of cluster-based and source-attribution methods for estimating transmission risk using large HIV sequence databases
T2  - Epidemics
UR  - http://dx.doi.org/10.1016/j.epidem.2017.10.001
UR  - http://hdl.handle.net/10044/1/52023
VL  - 23
ER  -
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