Within-host genetic diversity and large transmission bottlenecks confound phylodynamic inference of
epidemiological dynamics. Conventional phylodynamic approaches assume that nodes in a time-scaled
pathogen phylogeny correspond closely to the time of transmission between hosts that are ancestral to
the sample. However, when hosts harbour diverse pathogen populations, node times can substantially
pre-date infection times. Imperfect bottlenecks can cause lineages sampled in different individuals to
coalesce in unexpected patterns. To address realistic violations of standard phylodynamic assumptions
we developed a new inference approach based on a multi-scale coalescent model, accounting for nonlinear
epidemiological dynamics, heterogeneous sampling through time, non-negligible genetic diversity of
pathogens within hosts, and imperfect transmission bottlenecks. We apply this method to HIV-1 and
Ebola virus outbreak sequence data, illustrating how and when conventional phylodynamic inference may
give misleading results. Within-host diversity of HIV-1 causes substantial upwards bias in the number
of infected hosts using conventional coalescent models, but estimates using the multi-scale model have
greater consistency with reported number of diagnoses through time. In contrast, we find that within-
host diversity of Ebola virus has little influence on estimated numbers of infected hosts or reproduction
numbers, and estimates are highly consistent with the reported number of diagnoses through time.
The multi-scale coalescent also enables estimation of within-host effective population size using single
sequences from a random sample of patients. We find within-host population genetic diversity of HIV-1
p17 to be 2
Nμ
= 0
.
012(95% CI:0
.
0066
−
0
.
023), which is lower than estimates based on HIV envelope
serial sequencing of individual patients.