title: Getting to the root of epidemic spread with phylodynamic analysis of genomic data.
abstract: When epidemiological and evolutionary dynamics occur on similar timescales, pathogen genomes sampled from infected hosts carry a signature of the dynamics of epidemic spread. Phylodynamic inference methods aim to extract this signature from genetic data. We discuss the contribution of phylodynamics toward understanding the 2014 West African Ebola virus epidemic.
authors.affiliation: Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland; Institute of Integrative Biology, ETH Zürich, Zürich, Switzerland; Swiss Institute of Bioinformatics (SIB), Switzerland. Electronic address: louis.duplessis@env.ethz.ch.
authors.forename: Louis
authors.initials: L
authors.lastname: du Plessis
authors.affiliation: Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland; Swiss Institute of Bioinformatics (SIB), Switzerland.
authors.forename: Tanja
authors.initials: T
authors.lastname: Stadler
mesh_terms: D001499:Bayes Theorem; D029043:Ebolavirus / Q000235:genetics*; D019143:Evolution, Molecular; D016679:Genome, Viral; D023281:Genomics / Q000379:methods; D019142:Hemorrhagic Fever, Ebola / Q000453:epidemiology* / Q000821:virology*; D006801:Humans; D017720:Molecular Epidemiology; D010802:Phylogeny
keywords: Bayesian statistics; Ebola virus disease; MCMC; epidemiology; infectious diseases; phylogenetics