Maximal Sensitive Dependence and the Optimal Path to Epidemic Extinction
Document Type
Article
Publication Date
3-1-2011
Abstract
Extinction of an epidemic or a species is a rare event that occurs due to a large, rare stochastic fluctuation. Although the extinction process is dynamically unstable, it follows an optimal path that maximizes the probability of extinction. We show that the optimal path is also directly related to the finite-time Lyapunov exponents of the underlying dynamical system in that the optimal path displays maximum sensitivity to initial conditions. We consider several stochastic epidemic models, and examine the extinction process in a dynamical systems framework. Using the dynamics of the finite-time Lyapunov exponents as a constructive tool, we demonstrate that the dynamical systems viewpoint of extinction evolves naturally toward the optimal path.
DOI
10.1007/s11538-010-9537-0
MSU Digital Commons Citation
Forgoston, Eric; Bianco, Simone; Shaw, Leah B.; and Schwartz, Ira B., "Maximal Sensitive Dependence and the Optimal Path to Epidemic Extinction" (2011). Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works. 82.
https://digitalcommons.montclair.edu/appliedmath-stats-facpubs/82