Each time SARS-CoV-2 is transmitted from one host to the next, a small random number of point mutations are acquired. These mutations can be used to infer the branching structure of the evolving viruses, which is called a viral phylogenetic tree. Phylogenetic trees inferred from viral sequence data can provide much insight into the dynamics of an epidemic, this is the focus of an area of research called phylodynamics.
However, for this sequencing data to be a useful part of the non-pharmaceutical COVID response, important computation improvements are needed in current phylodynamic software tools, as the computational cost of phylodynamic inference can be in the order of days or weeks. This project aims at applying recent advances to enable these models to be run in real time.