Dynamical epidemic suppression using stochastic prediction and control

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

Abstract

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.