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

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Modelling an influenza pandemic

Planning ahead in terms of threatening infections such as influenza was the aim of the European consortium working on the Flumodcont project. By modelling the spread of an influenza pandemic, scientists believed they could determine the expected course of infection and design containment strategies.

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The emergence of the highly pathogenic avian H5N1 virus raised the alarm about the threat posed by novel strains of influenza A gaining transmissibility to people and causing a human pandemic. To mitigate the impact of such a pandemic on human health, the EU funded the ′Modelling the spread of pandemic influenza and strategies for its containment and mitigation′ (Flumodcont) project. Flumodcont was designed to support the development of policies, planning and response procedures in case of a flu pandemic. For this purpose, the consortium used mathematical models to simulate realistic pandemic spread scenarios and evaluate various control policies. The model took into account the role of virus transmission within schools, providing an assessment of the potential role of school holidays in shaping the infection impact. Data from 1889 to 1968 pandemics were used to standardise estimation procedures in computational models that could be used for performing detailed scenario analyses of interventions. One of the outputs of the project was a software package that simulated very efficiently, using an individual-based model, the spread of influenza pandemic at a European scale. During the A/H1N1 influenza pandemic of 2009, the consortium partners were actively involved in supporting national and international health agencies by providing an assessment of the situation. The Flumodcont-generated modelling approach was used to retrospectively analyse the epidemiological parameters and determinant factors that shaped the observed pattern of spread of the 2009 H1N1 pandemic in Europe. Also, by running two surveys, one before the infection had spread and a second after the main pandemic wave, researchers were to draw important conclusions on public intention and actual behaviour. This information could be essential for planning future communication strategies for infection management. The project’s technical advancements with respect to modelling of the spread of an influenza epidemic offer promising solutions for designing future surveillance, planning and responses.

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