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 power spectrum, (iii) eigenvalue estimation methods (iv) moment methods that depend on more-than-second-order properties, and (v) pattern formation. Our plan is to “stress test” these methods against simulated data by applying them to increasingly complicated epidemic scenarios until they finally fall apart. Then we’ll know just how useful the theory of critical slowing down might be.