Epidemiologists explain and predict the spread of infectious disease using what they call probabilistic cellular automata (PCA) models. A PCA consists of nodes in a network, each of which is in a state that changes from one time period to the next depending both on the states of nearby nodes and, to some extent, on chance, too. So imagine each node represents a person, and that each person can be in one of three states: healthy, ill, or deceased. Once researchers specify a rule for how likely you are to get sick or die tomorrow given the health of those around you today, they can run the model forward in time and begin to investigate patterns. Such techniques have helped explain how, when, and why to vaccinate, to quarantine, or to take other steps for managing the outbreak of a particular disease.
The same kind of model can also describe the spread of financial distress, where nodes represent banks that are connected to other banks through a network of loans or other obligations. This grant to economist Robert Mackay at the University of Warwick will fund a project to convene an international team of researchers to develop theorems, tools, and applicable techniques for constructing PCA models of how financial distress propagates through financial institutions, with the eventual goal of determining how circuit breakers, bailouts, enhanced regulation, or other interventions can mitigate systemic risk.