Dynamical epidemic suppression using stochastic prediction and control

Ira B. Schwartz; Lora Billings; Erik M. Bollt

doi:10.1103/PhysRevE.70.046220

Dynamical epidemic suppression using stochastic prediction and control

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

Applied Mathematics and Statistics

Research output: Contribution to journal › Article › peer-review

20 Scopus citations

Abstract

The effects of noise on a model of epidemic outbreaks were studied. The outbreaks were assumed to appear randomly. An adaptive control scheme was derived that prevents large outbreaks from occurring. A transition approach was used that predicts large outbreaks prior to their occurrence. The theory was found to be applicable to a wide range of stochastic processes.

Original language	English
Article number	046220
Pages (from-to)	046220-1-046220-7
Journal	Physical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume	70
Issue number	4 2
DOIs	https://doi.org/10.1103/PhysRevE.70.046220
State	Published - Oct 2004

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10.1103/PhysRevE.70.046220

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title = "Dynamical epidemic suppression using stochastic prediction and control",

abstract = "The effects of noise on a model of epidemic outbreaks were studied. The outbreaks were assumed to appear randomly. An adaptive control scheme was derived that prevents large outbreaks from occurring. A transition approach was used that predicts large outbreaks prior to their occurrence. The theory was found to be applicable to a wide range of stochastic processes.",

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AB - The effects of noise on a model of epidemic outbreaks were studied. The outbreaks were assumed to appear randomly. An adaptive control scheme was derived that prevents large outbreaks from occurring. A transition approach was used that predicts large outbreaks prior to their occurrence. The theory was found to be applicable to a wide range of stochastic processes.

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Dynamical epidemic suppression using stochastic prediction and control

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