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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Whooping cough re-emergence

Whooping cough has re-emerged in many places where it was previously eliminated, including California and the United Kingdom. Exactly why this happened isn’t clear, and it hasn’t happened everywhere. The re-emergence of previously eliminated “childhood” infections like whooping cough in places where vaccines are in wide use is one of the main motivations for this […]

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Postdoctoral opportunity: Forecasting emerging and re-emerging infectious diseases

Applications are being accepted for three postdoctoral associates to join a multi-institutional study (University of Georgia, University of Michigan, Penn State University) of the dynamics of emerging and re-emerging childhood infections (http://daphnia.ecology.uga.edu/midas). The overarching goal of this project is to identify statistical patterns that may serve as early warning signals of emergence. Sub-projects include developing […]

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