Final Report Summary - VIRALPHYLOGEOGRAPHY (Evolutionary reconstruction of viral spread in time and space)
To identify the causal mechanisms leading to disease emergence, endemic maintenance and epidemic expansion, epidemiologists benefit tremendously from a detailed characterization of pathogen spread in space and time. The extensive sequencing efforts in recent epidemics, e.g. pandemic influenza A/H1N1 and Ebolavirus in West Africa, demonstrate that analyses of pathogen genetic data constitute increasingly important sources of information in epidemiology. Technological developments have enabled sequence data generation in unprecedented quantities with remarkable rapidity.
With the objective to assist in designing effective intervention and prevention strategies, we have developed a comprehensive statistical framework for uncovering the spatial and temporal dynamics of pathogen genomes. To this aim, we designed and extended a series of computationally tractable models that use the rapidly proliferating viral genome data to their full potential, connect molecular evolution to underlying spatial processes, and pave the path to rigorous and powerful phylogeographic hypothesis testing. The framework includes models for phylogenetic diffusion in discrete and continuous space. These models and the associated inference methodologie have been implemented in a popular and freely available Bayesian statistical software package (BEAST: http://beast.bio.ed.ac.uk). Armed with these tools, we have investigated how genetic variation within important viral pathogens, such as influenza, rabies, Ebola and HIV, arises and persists across a diverse range of hosts and environments.
With the objective to assist in designing effective intervention and prevention strategies, we have developed a comprehensive statistical framework for uncovering the spatial and temporal dynamics of pathogen genomes. To this aim, we designed and extended a series of computationally tractable models that use the rapidly proliferating viral genome data to their full potential, connect molecular evolution to underlying spatial processes, and pave the path to rigorous and powerful phylogeographic hypothesis testing. The framework includes models for phylogenetic diffusion in discrete and continuous space. These models and the associated inference methodologie have been implemented in a popular and freely available Bayesian statistical software package (BEAST: http://beast.bio.ed.ac.uk). Armed with these tools, we have investigated how genetic variation within important viral pathogens, such as influenza, rabies, Ebola and HIV, arises and persists across a diverse range of hosts and environments.