Objectif
To identify the causal mechanisms leading to disease emergence, endemic maintenance and epidemic expansion,
epidemiologists would benefit tremendously from a full characterization of pathogen spread in space and time. The extensive
sequencing efforts for the ongoing swine-origin H1N1 influenza A epidemic testify that analyses of pathogen genetic data are
becoming increasingly important source of information in epidemiology. The new era of metagenomics promises to harvest
such data in unprecedented quantities with remarkable rapidity. With the objective to assist in designing effective intervention
and prevention strategies, we propose to develop a comprehensive statistical framework for uncovering the spatial and
temporal dynamics of pathogen genomes. To this aim, we will design and extend 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 approaches. Armed with these
tools, we will investigate how genetic variation within important viral pathogens, such as influenza, rabies and HIV, arises and
persists across a diverse range of hosts and environments.
Champ scientifique
- medical and health scienceshealth sciencespublic healthepidemiology
- natural sciencesbiological sciencesgeneticsgenomesviral genomes
- medical and health scienceshealth sciencesinfectious diseasesRNA virusesinfluenza
- medical and health scienceshealth sciencesinfectious diseasesRNA virusesHIV
- natural sciencesbiological sciencesmolecular biologymolecular evolution
Appel à propositions
ERC-2010-StG_20091118
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Régime de financement
ERC-SG - ERC Starting GrantInstitution d’accueil
3000 Leuven
Belgique