Identifying crises through network connections

From a Wuhan market to Bavarian Stockdorf: A chain of infection enabled the spread of coronavirus. Global trade and travel played the deciding role.

What were locally confined outbreaks have now further connected and are damaging the global economy. International airlines hardly fly to China anymore; global supply chains are breaking. Economic growth has been noticeably slower than expected in many countries since coronavirus emerged.

When local networks become internationally connected, it is known as percolation. An international team of researchers can now better predict when percolation arises and disappears.

Dr Jan Nagler, professor of computer science and head of the Deep Dynamics Group at Frankfurt School of Finance & Management led a team of researchers to explain the emergence and collapse of large networks. Their study was published on 10 February in Nature Physics. The international research team, which also includes scientists from the Potsdam Institute for Climate Impact Research, evaluated large amounts of data and simulated the emergence and decay of various networks. In doing so, they discovered a generally applicable law that explains the largest network disruptions.

For example, a perfectly functioning network of proteins in our cells generally correlates with the absence of diseases such as Alzheimer's. In a protein-protein-interaction network with thousands of proteins and known interactions, the scientists were able to show how accumulated disturbances in a few interactions affects the entire network.

"We have developed a mathematical model that describes the probability of global collapse, regardless of the details of the particular network," said Dr Jingfang Fan from the Potsdam Institute for Climate Impact Research and first author of the study.

Professor Nagler adds: “Our research was helped by a concept from the financial world that quantifies extreme changes in fluctuating financial markets. We have shown that this concept also describes rapid growth or collapse of large-scale networks.”

In their interdisciplinary work, the scientists combined methods from finance, physics, biochemistry, engineering and social sciences, and were able to establish for the first time a conceptual link between small and large-scale network disruptions. In the future, the theory may help to rein in percolation with timely countermeasures - such as closing airports when an epidemic spreads.

The next step for the researchers is to work out how their theory can be used to better estimate risk of sudden collapse of ecological networks and networked banks; how to identify tipping elements in Earth’s climate system and how to anticipate disruptive weather phenomena. “Through our work, we want to ensure that we can better respond to future crises - regardless of whether economic, due to climate change or even disease - we have taken an important first step with our model," emphasised Professors Jan Nagler and Jürgen Kurths, Head of Research at Potsdam Institute for Climate Impact Research.

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