Maths technique to predict disease spread

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150811 ULJGleeson 017A RESEARCHER at the University of Limerick has developed a mathematical technique to predict social phenomena in large populations.

Professor James Gleeson says the technique will help to answer questions such as whether an individual will become infected during an epidemic, or which candidate to vote for in an election.

According to Professor Gleeson, the answer depends not only on the individual in question, but also on their social or physical contacts with other individuals.

“Contagion can happen in many different contexts, from disease spread to viral marketing. Mathematical modelling helps us understand the mechanisms that drive contagions on networks.

“The increasing availability of data from social online networks can give a lot of information about how humans influence each other, but fast and accurate mathematical techniques are crucial to help process the flood of data.”

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The correct mathematical model can be used to predict a range of scenarios from voting models to infectious disease spread across populations.

To facilitate the spread of its use, the Mathematics Applications Consortium for Science and Industry (MACSI) have made the computational code freely available to download.

Professor Gleeson is the co-director of MACSI at UL; his research is funded by Science Foundation Ireland.