Phylodynamic

Phylodynamics is a field at the intersection of phylogenetics, population genetics, and epidemiology that studies how epidemiological, ecological, and evolutionary processes shape the genetic diversity of pathogens over time. By analyzing pathogen genome sequences collected during outbreaks, phylodynamics aims to infer transmission dynamics, population size changes, and selective pressures acting on the pathogen.

Core idea is to use genealogies reconstructed from sequence data to deduce past population dynamics, such as the growth rate, effective population size, and the time to the most recent common ancestor. Coalescent theory provides a framework that links the shape and timing of phylogenetic trees to epidemiological processes. Phylodynamic analyses can estimate time-varying reproductive numbers (R_t), outbreak origin, and geographic spread, often by combining sequence data with compartmental models like SIR or SEIR.

Methods commonly employ Bayesian inference and Monte Carlo methods, using software such as BEAST and BEAST2, and include models like Skygrid, the birth-death skyline, and other birth-death or coalescent-based approaches. They require accurate sampling times and accounting for uneven sampling, selection, and molecular clocks.

Applications include HIV, influenza, and SARS-CoV-2, where phylodynamics has helped reconstruct transmission chains, estimate introduction events, and monitor changes in transmission over time. The field supports public health by providing insights into outbreak dynamics and the impact of interventions, while recognizing limitations from sampling bias, model misspecification, and computational demands.