The estimation of evolutionary parameters provides essential information for designing public health policies. In short time intervals, however, nucleotide substitutions are ineffective to record all complexities of virus population dynamics. In this sense, the current SARS-CoV-2 pandemic poses a challenge for evolutionary analysis. We used computer simulation to evolve populations in scenarios of varying temporal intervals to evaluate the impact of the age of an epidemic on estimates of time and geography. Before estimating virus timescales, the shape of tree topologies can be used as a proxy to assess the effectiveness of the virus phylogeny in providing accurate estimates of evolutionary parameters. In short timescales, estimates have larger uncertainty. We compared the predictions from simulations with empirical data. The tree shape of SARS-CoV-2 was closer to shorter timescales scenarios, which yielded parametric estimates with larger uncertainty, suggesting that estimates from these datasets should be evaluated cautiously. To increase the accuracy of the estimates of virus transmission times between populations, the uncertainties associated with the age estimates of both the crown and stem nodes should be communicated. We place the age of the common ancestor of the current SARS-CoV-2 pandemic in late September 2019, corroborating an earlier emergence of the virus.
Challenges in estimating virus divergence times in short epidemic timescales with special reference to the evolution of SARS-CoV-2 pandemic