Summary
Amongst newly developed approaches to analyse molecular data,
phylodynamic models are receiving much attention because of their
potential to reveal changes to viral populations over short periods.
This knowledge can be very important for understanding disease impacts.
However, their accuracy needs to be fully understood, especially in
relation to wildlife disease epidemiology, where sampling and prior
knowledge may be limited. The release of the rabbit haemorrhagic disease
virus (RHDV) as biological control in naïve rabbit populations in
Australia in 1996 provides a unique dataset with which to validate
phylodynamic models. By comparing the results obtained for RHDV1 with
our current understanding of the RHDV epidemiology in Australia, we
evaluated the performances of these recently developed models.
In line with our expectations, coalescent analyses detected a sharp
increase in the virus trajectory in the first few months after the virus
release, followed by a more gradual increase. The phylodynamic analyses
with a birth-death tree prior generated effective reproductive number
estimates (the average number of secondary infections per each
infectious case, R e) larger than one for most of
the epochs considered. However, the possible range of the initialR e included estimates lower than one despite the
known rapid spread of RHDV1 in Australia. Furthermore, the analyses that
took into account the geographical structuring failed to converge. We
argue that the difficulties that we encountered most likely stem from
the fact that the samples available from 1996 to 2014 were too sparse
with respect to geographic and within outbreak coverage to adequately
infer some of the model parameters. In general, while these Bayesian
analyses proved to be greatly informative in some regards, we caution
that their interpretation may not be straight forward and recommend
further research in evaluating the robustness of these models to
assumption violations and sensitivity to sampling regimes.