Analysis and Control of Emergent Dynamics in Epidemiology

摘要

The overall objective of this work is to understand information flow on a network through the analogous process of biological disease spread in a noisy environment. Currently, the PI is developing new multi-patch models that address the issue of scalability, where the size of the groupings is determined by the accuracy and scope of the results needed. She has developed a computational tool to predict changes in dynamics due to noise probabilistically. This method numerically approximates the mechanisms of transport in a mathematical space, and provides a way to visualize it using a matrix representation. Commonly, the only data available in the field is the number of infected individuals reported. Using embedding techniques, this data can emulate the dynamics of the full system and be used in our methods. In practice, the PI has successfully compared a stochastic bifurcation in a controlled experiment to a theoretical laser model. The transport tools developed to date allow control of the system by targeting or avoiding high probability regions. The PI has a working algorithm submitted for publication and is planning its implementation in a future experiment.