University of Cambridge > Talks.cam > DAMTP Statistical Physics and Soft Matter Seminar > Using Critical Slowing Down to suggest statistical indicators of disease emergence and elimination

Using Critical Slowing Down to suggest statistical indicators of disease emergence and elimination

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The theory of critical slowing down observes that as a steady state changes stability, its eigenvalue passes through zero and so perturbations away from the steady state recover increasingly slowly. This observation suggests that such transitions may be observed in the statistics of fluctuations in noisy timeseries data, with potential applications in many fields including epidemiology, ecology and climate change. Finding and applying robust statistical indicators that work in practice has proven difficult, however. We investigate such practicalities, and suggest using an equation free method to visually inspect the potential surface realised by stochastic simulations.

This talk is part of the DAMTP Statistical Physics and Soft Matter Seminar series.

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