Deem and study co-author Jiankui He, a graduate student in physics and astronomy, developed a mathematical method that used freely available genetic profiles of new flu strains to predict whether a strain will become dominant. Using the method, they examined the H3N2 flu strain for the past 14 years and made their own predictions based on the available data in GenBank, where public health officials post all the latest genetic sequences of new flu strains.
Deem and He compared their predictions with the WHO's predictions from 1996 to 2010. They found their new method correctly predicted the dominant strain of H3N2 for most years, including three years -- 2002, 2003 and 2009 -- when the WHO vaccine was formulated with an H3N2 strain that turned out not to be the dominant strain that year.
The new method involves a statistical technique called multidimensional scaling that is used to create graphical plots of complex data in fields as diverse as marketing and physics. In their study, He and Deem used multidimensional scaling to create a graphical plot of amino acid sequence data for all strains of H3N2. They limited their study to a 329-amino-acid region of the virus that mutates regularly to avoid detection by immune system.
"Using multidimensional scaling, we project from those 329 dimensions to the two dimensions that contain the most information," Deem said. "We just plot all of the points as a function of two variables instead of listing all 329, which is too much information to work with. With the two-dimensional scaling, we have a workable problem and we still have enough information to see clusters of new strains that will eventually become dominant."
Deem said the results of the
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