TY - JOUR T1 - Epidemiological and evolutionary analysis of the 2014 Ebola virus outbreak JF - bioRxiv DO - 10.1101/011171 SP - 011171 AU - Marta Łuksza AU - Trevor Bedford AU - Michael Lässig Y1 - 2015/01/01 UR - http://biorxiv.org/content/early/2015/01/05/011171.abstract N2 - The 2014 epidemic of the Ebola virus is governed by a genetically diverse viral population. In the early Sierra Leone outbreak, a recent study has identified new mutations that generate genetically distinct sequence clades [1]. Here we find evidence that major Sierra Leone clades have systematic differences in growth rate and reproduction number. If this growth heterogeneity remains stable, it will generate major shifts in clade frequencies and influence the overall epidemic dynamics on time scales within the current outbreak. Our method is based on simple summary statistics of clade growth, which can be inferred from genealogical trees with an underlying clade-specific birth-death model of the infection dynamics. This method can be used to perform realtime tracking of an evolving epidemic and identify emerging clades of epidemiological or evolutionary significance. ER -