Dynamical epidemic suppression using stochastic prediction and control

Ira Schwartz, US Naval Research Labratory
Lora Billings, Montclair State University
Erik Bollt, Clarkson University


We consider the effects of noise on a model of epidemic outbreaks, where the outbreaks appear randomly. Using a constructive transition approach that predicts large outbreaks prior to their occurrence, we derive an adaptive control scheme that prevents large outbreaks from occurring. The theory is applicable to a wide range of stochastic processes with underlying deterministic structure.