Taking a BREATH (Bayesian Reconstruction and Evolutionary Analysis of Transmission Histories) to simultaneously infer phylogenetic and transmission trees for partially sampled outbreaks

Abstract We introduce and apply Bayesian Reconstruction and Evolutionary Analysis of Transmission Histories (BREATH), a method to simultaneously construct phylogenetic trees and transmission trees using sequence data for a host-to-host outbreak. BREATH's transmission process that accounts for a flexible natural history of infection (including a latent period if desired) and a separate process for sampling. It allows for unsampled individuals and within-host evolution. It also accounts for the fact that an outbreak may still be ongoing at the time of analysis, using right truncation adjustment. We perform a simulation study to verify our implementation and explore sensitivity to unknown or misspecified parameters. We then apply BREATH to a previously-described 13-year outbreak of tuberculosis. We find that using a transmission process to inform the phylogenetic reconstruction results in better resolution of the phylogeny (in topology, branch length and tree height) and a more precise estimate of the time of origin of the outbreak. Considerable uncertainty remains about transmission events in the outbreak, but our reconstructed transmission network resolves two major waves of transmission consistent with the previously-described epidemiology, estimates the numbers of unsampled individuals, and describes some high-probability transmission pairs. An open source implementation of BREATH is available from https://github.com/rbouckaert/BREATH as the BREATH package to BEAST 2.