Dynamical epidemic suppression using stochastic prediction and control

Ira B. Schwartz, Lora Billings, and Erik M. Bollt

Phys. Rev. E 70, 046220 – Published 28 October 2004

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.

Received 17 February 2004

DOI:https://doi.org/10.1103/PhysRevE.70.046220

Authors & Affiliations

Ira B. Schwartz

Plasma Physics Division, Code 6792, Naval Research Laboratory, Washington, DC 20375, USA

Lora Billings

Department of Mathematical Sciences, Montclair State University, Montclair, New Jersey 07043, USA

Erik M. Bollt

Department of Mathematics and Computer Science, Clarkson University, Potsdam, New York 13699, USA and Department of Physics, Clarkson University, Potsdam, New York 13699, USA

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Vol. 70, Iss. 4 — October 2004

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Physical Review E

covering statistical, nonlinear, biological, and soft matter physics

Dynamical epidemic suppression using stochastic prediction and control

Ira B. Schwartz, Lora Billings, and Erik M. Bollt

Phys. Rev. E 70, 046220 – Published 28 October 2004

Abstract

Authors & Affiliations

Article Text (Subscription Required)

References (Subscription Required)

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Physical Review E

covering statistical, nonlinear, biological, and soft matter physics

Dynamical epidemic suppression using stochastic prediction and control

Ira B. Schwartz, Lora Billings, and Erik M. Bollt

Phys. Rev. E 70, 046220 – Published 28 October 2004

Abstract

Authors & Affiliations

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