Quantifying Pathogen Surveillance Using Temporal Genomic Data

Chan, Joseph M.; Rabadan, Raul

Comparison to phylogenetic methods. One may wonder if other alternative methods that account for pathogen evolution may suffice to characterize the genetic surveillance of a pathogen. Phylogenetics has been used in many studies to characterize pathogen surveillance qualitatively without producing a quantitative measure of sampling completeness (36) . A possible phylogenetic analogue to the q2 coefficient might entail the reconstruction of a tree based on available sequences and measurement of the distribution of branch lengths. The true distance between two isolates, A and B, is represented by the sum of their patristic distances, d A and d B , which are the branch lengths from each respective sequence to their common ancestral node. Sequences are time ordered, however, and if we assume an approximate molecular clock, then d A Ͻ d B given that sequence A occurs before sequence B. An estimate of distance is then the larger patristic distance. A parallel to our q2 coefficient would predict high surveillance to correspond to a maximal number (#) of patristic distances d to their closest ancestor in the past less than 2 years as follows: Phylogenies can be divided into those that are distance based and those that are character based. Since the q2 coefficient readily incorporates different genetic distance methods, it is equivalent to any p2 coefficient calculated from distance-based trees. On the other hand, character-based trees, including maximumlikelihood and Bayesian inference methods, incorporate site heterogeneity by considering one character (a site in the alignment) at a time to reconstruct a tree (37); moreover, Markov chain Monte Carlo (MCMC) methods like BEAST (38) can incorporate relaxed clock rates. The q2 coefficient does not take into account either site or clock rate heterogeneity.