Detection of HIV transmission clusters from phylogenetic trees using a multi-state birth-death model. Journal of the Royal Society Interface.
The Swiss HIV Cohort Study (SHCS) for many years uses phylogenetic methods to better understand transmission of HIV to ultimately improve public health interventions. Barido-Sottani et al., a collaborating group from ETHZ/BSSE Basel, developed a new method for identifying transmission clusters and applied it to data from the SHCS.
HIV patients form clusters in HIV transmission networks. Accurate identification of these transmission clusters is essential to target effectively public health interventions. One reason for clustering is that the underlying contact network contains many local communities.
They present a new maximum-likelihood method for identifying transmission clusters caused by community structure, based on phylogenetic trees. The method employs a multi-state birth-death (MSBD) model, which detects changes in transmission rate, which are interpreted as the introduction of the epidemic into a new susceptible community, i.e. the formation of a new cluster.
They show that the MSBD method is able to reliably infer the clusters and the transmission parameters from a pathogen phylogeny based on their simulations. In contrast to existing cutpoint-based methods for cluster identification, the new method does not require that clusters be monophyletic nor is it dependent on the selection of a difficult-to-interpret cutpoint parameter. They present an application of their method to data from the SHCS. The method is available as an easy-to-use R package.