Epidemiological hypothesis testing using a phylogeographic and phylodynamic framework

Simon Dellicour (), Sebastian Lequime, Bram Vrancken, Mandev S. Gill, Paul Bastide, Karthik Gangavarapu, Nathaniel L. Matteson, Yi Tan, Louis Plessis, Alexander A. Fisher, Martha I. Nelson, Marius Gilbert, Marc A. Suchard, Kristian G. Andersen, Nathan D. Grubaugh, Oliver G. Pybus and Philippe Lemey
Additional contact information
Simon Dellicour: Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles
Sebastian Lequime: Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven
Bram Vrancken: Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven
Mandev S. Gill: Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven
Paul Bastide: Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven
Karthik Gangavarapu: Department of Immunology and Microbiology, The Scripps Research Institute
Nathaniel L. Matteson: Department of Immunology and Microbiology, The Scripps Research Institute
Yi Tan: Vanderbilt University Medical Center
Louis Plessis: University of Oxford
Alexander A. Fisher: University of California
Martha I. Nelson: Fogarty International Center, National Institutes of Health
Marius Gilbert: Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles
Marc A. Suchard: University of California
Kristian G. Andersen: Department of Immunology and Microbiology, The Scripps Research Institute
Nathan D. Grubaugh: Yale School of Public Health
Oliver G. Pybus: University of Oxford
Philippe Lemey: Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven

Nature Communications, 2020, vol. 11, issue 1, 1-11

Abstract: Abstract Computational analyses of pathogen genomes are increasingly 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 illustrate our approach by focusing on the West Nile virus (WNV) spread in North America that has substantially impacted public, veterinary, and wildlife health. We apply an analytical workflow to a comprehensive WNV genome collection to test the impact of environmental factors on the dispersal of viral lineages and on viral population genetic diversity through time. 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. By contrasting inference with simulation, we find no evidence for viral lineages to preferentially circulate within the same migratory bird flyway, suggesting a substantial role for non-migratory birds or mosquito dispersal along the longitudinal gradient.

Date: 2020
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DOI: 10.1038/s41467-020-19122-z

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