Hindustan Times (Jalandhar)
How networks shape spread of disease, gossip
LONDON: A team of mathematicians at the University of Oxford has come up with a new approach to explore the spread of contagious diseases or the latest celebrity gossip by testing it using London’s street and underground networks.
The results could help to predict when a contagion will spread through space as a simple wave and when long-range connections, such as air travel, enable it to seemingly jump over long distances and emerge in locations far from an initial outbreak.
The team, that included mathematicians from the University of North Carolina at Chapel Hill and Rutgers University, used a set of mathematical rules to encode how a contagion spreads, and then studied the outcomes of these rules, a university release said. The researchers explored how disease or gossip might spread through London’s transit network. Specifically, they illustrated how the street network overlaid with the London Underground network enables contagions to hop to a distant location. To analyse the behaviour of a contagion, the researchers drew on ideas from ‘topology’, a branch of mathematics used to characterise the structure of complex shapes.
By studying the ‘shape’ of the data that results from a contagion, it is possible to distinguish between contagions that take long-distance hops across a network and those that exhibit a local (and slower) wave-like spreading pattern.
This ‘computational topology’ technique has the potential to overcome many barriers to extracting useful information from big, ‘noisy’ data sets, such as those gathered during a disease epidemic or from gossip spreading over social media.
A report of the research is published in the journal Nature Communications. “Underlying spatial networks have a big influence over how diseases or information spread... but there are numerous ‘shortcuts’ that these can take that makes their spreading patterns difficult to predict,” said author Mason Porter of Oxford University’s Mathematical Institute. “Our work shows a way to reconcile a wave-like model of spreading, which might approximate what happens at a local level, with behaviour that includes shortcuts to distant locations.”