Theory of forecastability for emerging and eliminable infectious diseases

This project tackles four problems in the theory of emergence forecasting: Discrete systems Periodically forced systems Large dimensionality Hidden states These problems are not part of the basic theory of critical slowing down, but are common in the real world. Our basic strategy is to formulate the minimally complex model that exhibits the problem of […]

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Model-independent statistical methodology for detecting critical slowing down

This project focuses on the methodology. The goal of this project is to devise data mining techniques — online algorithms — suggested by the epidemiological theory developed in some of the other projects. Specifically, we are seeking to develop model-independent tools for epidemic transitions based on (i) critical slowing down (ii) frequency properties of the […]

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