Getting to the root of epidemic spread with phylodynamic analysis of genomic data

Louis du Plessis; Tanja Stadler

doi:10.1016/j.tim.2015.04.007

Getting to the root of epidemic spread with phylodynamic analysis of genomic data

Trends Microbiol. 2015 Jul;23(7):383-6. doi: 10.1016/j.tim.2015.04.007.

Authors

Louis du Plessis¹, Tanja Stadler²

Affiliations

¹ 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.
² Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland; Swiss Institute of Bioinformatics (SIB), Switzerland.

PMID: 26139467
DOI: 10.1016/j.tim.2015.04.007

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.

Keywords: Bayesian statistics; Ebola virus disease; MCMC; epidemiology; infectious diseases; phylogenetics.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Bayes Theorem
Ebolavirus / genetics*
Evolution, Molecular
Genome, Viral*
Genomics* / methods
Hemorrhagic Fever, Ebola / epidemiology*
Hemorrhagic Fever, Ebola / virology*
Humans
Molecular Epidemiology
Phylogeny*