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Modelling the spread of pandemic influenza and strategies for its containment and mitigation

Objective

The public heath threat posed by novel strains of influenza A gaining transmissibility in people and causing a human pandemic has been recognised as potentially catastrophic, especially since the emergence and global spread of the highly pathogenic avian H5N1 virus. Several mathematical models have been developed to evaluate patterns of spatio-temporal spread of infection, and the effectiveness of various containment strategies. However, these require significant improvements, elaboration, and application, in order to better inform EU-wide policy and responses. Key to the determination of the spatio-temporal patterns of pandemic influenza are data on contact patterns, such as those that are being acquired by the EU projects INFTRANS and POLYMOD. Building on these projects, we will collect detailed data on population structure, workplace sizes, and population movement; while also doing new surveys focused on identifying potential behavioral super-spreaders, and attitudes towards, and potential behavioural changes during, a pandemic. A suite of mathematical models, ranging from deterministic and stochastic differential equations to individual-based microsimulations, will be developed and integrated; taking into account all of the new data that is acquired above. The models will be validated against data on past pandemics and on the dynamics of seasonal and endemic infectious diseases. The effectiveness of control/treatment strategies, including measures to increase social distance (school and workplaces closure, travel reductions), quarantine, antiviral prophylaxis and mass or targeted vaccination, which also consider contact tracing protocols, will be evaluated through these models. An essential ingredient to the usefulness of detailed models is the possibility of updating them on the basis of new information or on the patterns of an emerging epidemic; hence a specific effort will be devoted to develop modular and efficient algorithms allowing for real-time analysis.
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Coordinator

UNIVERSITA DEGLI STUDI DI TRENTO

Address

Via Calepina 14
38122 Trento

Italy

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 270 132

Administrative Contact

Raul Paolo Serapioni (Prof.)

Participants (10)

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IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE

United Kingdom

EU Contribution

€ 314 412

FONDAZIONE BRUNO KESSLER

Italy

EU Contribution

€ 212 757

UNIVERSITE PIERRE ET MARIE CURIE - PARIS 6

France

EU Contribution

€ 230 880

Public Health England an Executive Agency of the Dept of Health

United Kingdom

EU Contribution

€ 476 775

RIJKSINSTITUUT VOOR VOLKSGEZONDHEID EN MILIEU

Netherlands

EU Contribution

€ 42 626

TERVEYDEN JA HYVINVOINNIN LAITOS

Finland

EU Contribution

€ 199 080

UNIVERSITA COMMERCIALE LUIGI BOCCONI

Italy

EU Contribution

€ 107 550

ISTITUTO SUPERIORE DI SANITA

Italy

EU Contribution

€ 275 909

INSTITUTUL DE SANATATE PUBLICA

Romania

EU Contribution

€ 41 025

CLALIT HEALTH SERVICES

Israel

EU Contribution

€ 20 400

Project information

Grant agreement ID: 201601

Status

Closed project

  • Start date

    1 June 2008

  • End date

    31 May 2011

Funded under:

FP7-HEALTH

  • Overall budget:

    € 2 880 344,53

  • EU contribution

    € 2 191 546

Coordinated by:

UNIVERSITA DEGLI STUDI DI TRENTO

Italy