David A. Rasmussen

TL;DR: A series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release are described.

TL;DR: The full range of new tools and models available on the BEAST 2.5 platform are described, which expand joint evolutionary inference in many new directions, especially for joint inference over multiple data types, non-tree models and complex phylodynamics.

TL;DR: The approach using a nonlinear Susceptible-Infected-Recovered (SIR) model for the transmission dynamics of an infectious disease is demonstrated and shown that it provides accurate estimates of past disease dynamics and key epidemiological parameters from genealogies with or without accompanying time series data.

TL;DR: In this paper, the authors describe the genomic epidemiology using a dataset of 8746 genomes from 33 African countries and two overseas territories and show that the epidemics in most countries were initiated by importations predominantly from Europe, which diminished following the early introduction of international travel restrictions.

TL;DR: A statistical framework for fitting stochastic epidemiological models with different forms of population structure to genealogies is developed by combining particle filtering methods with Bayesian Markov chain Monte Carlo methods and shows that the proposed method can be used to estimate the stage-specific transmission rates and prevalence of HIV.