BIG_IDEA

Building an Integrated Genetic Infectious Disease Epidemiology Approach

Coordinatore	UNIVERSITY COLLEGE LONDON    more Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie.
Nazionalità Coordinatore	United Kingdom [UK]
Totale costo	1˙483˙080 €
EC contributo	1˙483˙080 €
Programma	FP7-IDEAS-ERC Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	ERC-2010-StG_20091118
Funding Scheme	ERC-SG
Anno di inizio	2010
Periodo (anno-mese-giorno)	2010-11-01   -   2015-10-31

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE  Organization address address: SOUTH KENSINGTON CAMPUS EXHIBITION ROAD city: LONDON postcode: SW7 2AZ contact info Titolo: Ms. Nome: Tatjana Cognome: Palalic Email: send email Telefono: +44 20 75943866 Fax: +44 20 75943868	UK (LONDON)	beneficiary	170˙401.81
2	UNIVERSITY COLLEGE LONDON  Organization address address: GOWER STREET city: LONDON postcode: WC1E 6BT contact info Titolo: Ms. Nome: Greta Cognome: Borg-Carbott Email: send email Telefono: 442031000000 Fax: 442078000000	UK (LONDON)	hostInstitution	1˙312˙678.20
3	UNIVERSITY COLLEGE LONDON  Organization address address: GOWER STREET city: LONDON postcode: WC1E 6BT contact info Titolo: Prof. Nome: Francois Cognome: Balloux Email: send email Telefono: 442077000000 Fax: 442078000000	UK (LONDON)	hostInstitution	1˙312˙678.20

Mappa

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 Obiettivo del progetto (Objective)

'Epidemiology and public health planning will increasingly rely on the analysis of genetic sequence data. The recent swine-derived influenza A/H1N1 pandemic may represent a tipping point in this trend, as it is arguably the first time when multiple strains of a human pathogen have been sequenced essentially in real time from the very beginning of its spread. However, the full potential of genetic information cannot be fully exploited to infer the spread of epidemics due to the lack of statistical methodologies capable of reconstructing transmission routes from genetic data structured both in time and space. To address this urgent need, we propose to develop a methodological framework for the reconstruction of the spatiotemporal dynamics of disease outbreaks and epidemics based on genetic sequence data. Rather than reconstructing most recent common ancestors as in phylogenetics, we will directly infer the most likely ancestries among the sampled isolates. This represents an entirely novel paradigm and allows for the development of statistically coherent and powerful inference software within a Bayesian framework. The methodological framework will be developed in parallel with the analysis of real genetic/genomic data from important human pathogens. We will in particular focus on the 2009 A/H1N1 pandemic influenza, methicilin-resistant Staphylococcus aureus clones (MRSAs), Batrachochytrium dendrobatidis, a fungus currently devastating amphibian populations worldwide. The tools we are proposing to develop are likely to impact radically on the field of infectious disease epidemiology and affect the way infectious emerging pathogens are monitored by biologists and public health professionals.'