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 […]
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 […]
Case studies of near critical phenomena in re-emerging infectious diseases
This project is about validation. We would suggest that the best systems for testing the theory of critical slowing down are childhood infections like measles and mumps for which much of the global population is vaccinated. As is well known, some such infections have resurged in recent years, but the time and place at which […]
Software for epidemic time series analysis
A theory’s no good without the tools to use it. This project is developing software so that others can apply the theory and methods developed by the AERO team to their own data.