New model of influenza transmission can provide real-time information about infections

Published on October 9, 2012 at 2:04 AM · No Comments

A new model of influenza transmission, published in BioMed Central's open access journal BMC Medicine, using more detailed information about patterns and severity of infection than previous models, finds that cases and transmission rates of H1N1 during the 2009-2010 flu pandemic have been underestimated. This model can provide a more robust and accurate real-time estimate of infection during a pandemic, which will help health services prepare and respond to future outbreaks.

During an epidemic one of the most important pieces of information health services need in order to respond efficiently is how 'transmissible' a disease is. In other words how many people are going to be infected and how easily the infection spreads. Although people exposed to flu can experience a range of symptoms from no infection through to serious illness, most models of disease transmission simplify this to infectious or not. Such a simplification makes the data easier to handle but also potentially disguises important aspects of how an epidemic develops.

A new model, developed by a team led by Dr Thomas House from the University of Warwick, includes within household transmission, as well as size of household, disease severity, and other key factors during the first seven weeks of the 2009 H1N1 epidemic in Birmingham. This information was collected by the BADGER flu clinic and Health Protection Agency centred on laboratory confirmed cases and their household contacts.

By combining transmission possibilities from people with a positive test for flu, people tested for flu and people who had flu symptoms but were not tested, this model gave a much more accurate picture of how the pandemic progressed.

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