video transcript

Mathematician Thomas House discussing his new equation, designed to help authorities vastly improve their response to future pandemics. During the 2009 H1N1 outbreak most diagnoses were made on the basis of nose and throat swabs taken from people with symptoms of the virus. But in some countries, data suggests many people felt their symptoms weren't severe enough to justify a doctor's visit, and up to 90 percent of cases were missed as a result. The University of Warwick's Mathematics Institute team has re-examined figures taken at the time from blood samples across the city of Birmingham. SOUNDBITE (English) DR THOMAS HOUSE, OF THE MATHEMATICS INSTITUTE AT THE UNIVERSITY OF WARWICK, SAYING: "We realised, those of us who were mathematicians, that you could analyse this data and try and find out which cases were being missed because they weren't ill enough. So one of the features of the last flu pandemic, while some people were very ill, it was a very serious disease, but quite a lot of people had symptoms no worse than the common cold and so wouldn't have aroused suspicion." House says his equation can give a real-time snapshot of a virus's spread at any stage of an outbreak, simply by running a computer model. It's based on the transmission rates within households. SOUNDBITE (English) DR THOMAS HOUSE, OF THE MATHEMATICS INSTITUTE AT THE UNIVERSITY OF WARWICK, POINTING AT THE EQUATION ON THE BOARD AND SAYING: "What you get is a distribution like this that's kind of got a u-shape.....It goes down, then up, corresponding to the fact that you get a cascade of cases.....You need to get the whole household but provided you're clear about how you've sampled those households from the population, the method works. It doesn't require you to get every case." Because pandemics usually occur in at least two waves, the second stronger than the first, accurate mathematical analysis of first wave sufferers would aid central planners. Unnecessary closure of schools and workplaces and cancellation of elective surgery to free up hospital beds could all be avoided with more accurate data, House believes. Decisions to order mass vaccination or instead target those at-risk could also be helped....by a more data specific approach to a serious public health issue.