RT Journal Article
SR Electronic
T1 Phylogeographic and phylodynamic approaches to epidemiological hypothesis testing
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 788059
DO 10.1101/788059
A1 Simon Dellicour
A1 Sebastian Lequime
A1 Bram Vrancken
A1 Mandev S. Gill
A1 Paul Bastide
A1 Karthik Gangavarapu
A1 Nate Matteson
A1 Yi Tan
A1 Louis du Plessis
A1 Alexander A. Fisher
A1 Martha I. Nelson
A1 Marius Gilbert
A1 Marc A. Suchard
A1 Nathan D. Grubaugh
A1 Kristian G. Andersen
A1 Oliver G. Pybus
A1 Philippe Lemey
YR 2019
UL http://biorxiv.org/content/early/2019/10/01/788059.abstract
AB Computational analyses of pathogen genomes are increasingly being used to unravel the dispersal history and transmission dynamics of epidemics. Here, we show how to go beyond historical reconstructions and use spatially-explicit phylogeographic and phylodynamic approaches to formally test epidemiological hypotheses. We focus on the spread and invasion of West Nile virus spread in North America that has been responsible for substantial impacts on public, veterinary and wildlife health. WNV isolates have been sampled at various times and locations across North America since its introduction to New York twenty years ago. We exploit this genetic data repository to demonstrate that factors hypothesised to affect viral dispersal and demography can be statistically tested. We find that WNV lineages tend to disperse faster in areas with higher temperatures and we identify temporal variation in temperature as a main predictor of viral genetic diversity through time. Finally, we compare inferred and simulated dispersal histories of lineages in order to assess the impact of migratory bird flyways on the rapid east-to-west continental spread of WNV. We find no evidence that viral lineages preferentially circulate within the same migratory flyway, suggesting a substantial role for non-migratory birds or mosquito dispersal along the longitudinal gradient. Our study demonstrates that the development and application of statistical approaches, coupled with comprehensive pathogen genomic data, can address epidemiological questions that might otherwise be difficult or unacceptably costly to answer.