Detecting emerging pathogen lineages

Music City Center 

Because viruses belonging to lineages with higher fitness are expected to transmit rapidly to new hosts before incurring very many substitutions, large numbers of related sequences appearing in data are sometimes interpreted as a sign of elevated fitness. Tree statistics inspired by this idea, such as the local branching index, are easily calculated from a given phylogenetic tree (or a distribution of trees). However, epidemiological confounders like superspreading, host population heterogeneity, or sampling biases may introduce spurious patterns in phylogenetic trees that undermine our ability to identify emerging lineages. To address this, we use stochastic compartmental models to simulate outbreaks and generate distributions of phylogenies under a variety of epidemiological conditions and testing strategies. By characterizing the types of phylogenies expected under these situations, we characterize the types of signals we can detect.