  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.
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.
