UL Researcher Develops Mathematical Technique Which Will Better Predict the Spread of Epidemics
Prof James Gleeson
University of Limerick based researcher Prof James Gleeson, has invented a new mathematical technique which analyses and predicts the outcome of dynamic changes on large-scale networks. This new technique will provide more accurate prediction of a diverse range of spreading phenomena such as epidemics, computer viruses and social media trends. Professor Gleeson’s paper entitled ‘High-accuracy approximation of binary-state dynamics on networks’ has been published by leading science journal, Physical Review Letters.
Professor Gleeson explains the application of the model as “a way of seeing how links in our connected world affect us in many ways. This model can be applied to examine the spread of diseases such as H1N1 (swine flu) by understanding the complex networks within society. The airline network, for example, tells us how many people fly to and from each airport in the world every day, and these travellers are often the primary spreaders of epidemics and pandemics.”
Professor Gleeson sees the application of this research to have a significant impact for society; “As an applied mathematician my focus is to use maths to solve real-world problems, and to see how different spreading phenomena, like diseases or rumours on social networks, can have a unified mathematical description. One of the most significant results of this technique will be its application in global healthcare. This research will enable scientists in many different fields to obtain more accurate predictions for spreading behaviours, in particular epidemics. Better understanding how diseases spread can inform how vaccination should be rolled out and targeted at specific groups, and so guide the response required by governments and healthcare.”
Prediction of the spread of epidemics has implications in the impact on the wider healthcare community and its ability to respond effectively. In the case of swine flu in Ireland, the economic impact to the state in responding to a virus and understanding the reach it may have within the population is significant. This research can be applied to allow more accurate prediction of the size of an epidemic and therefore inform preparations to combat the disease.
Professor Gleeson is the co-director of the Mathematics Applications Consortium for Science and Industry (MACSI) at the University of Limerick. This research is funded by Science Foundation Ireland. Professor Gleeson’s paper is available to view on Physical Review Letters website.