Phylodynamics on local sexual contact networks. PLOS Computational Biology
Phylodynamic models are widely used in infectious disease epidemiology to infer the dynamics and structure of pathogen populations. However, these models generally assume that individual hosts contact one another at random, ignoring the fact that many pathogens spread through highly structured contact networks.
In the current work, Rasmussen et al. presented a new framework for phylodynamics on local contact networks based on pairwise epidemiological models that track the status of pairs of nodes in the network rather than just individuals. By considering how local interactions among hosts shape the phylogeny of a pathogen, their models offered a “pathogen’s eye view” of these networks. By considering pathogen phylogenies in a probabilistic framework, these coalescent models could also be used to estimate the statistical properties of contact networks directly from phylogenies using likelihood-based inference. The authors used this framework to explore how much information phylogenies retain about the underlying structure of contact networks and to infer the structure of a sexual contact network underlying a large HIV-1 sub-epidemic in Switzerland.
In conclusion, the authors provided a simple theoretical framework to explore the relationship between contact networks, epidemic dynamics, and phylogenies. They showed that phylodynamic modeling framework provides a good approximation to the coalescent process on random networks and can recapitulate the major features of pathogen phylogenies simulated on different types of random graphs.