Uncertainty Quantification in Simulations of Epidemics Using Polynomial Chaos

Joint Authors

Santonja, Francisco-José
Chen-Charpentier, Benito

Source

Computational and Mathematical Methods in Medicine

Issue

Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2012-08-15

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Medicine

Abstract EN

Mathematical models based on ordinary differential equations are a useful tool to study the processes involved in epidemiology.

Many models consider that the parameters are deterministic variables.

But in practice, the transmission parameters present large variability and it is not possible to determine them exactly, and it is necessary to introduce randomness.

In this paper, we present an application of the polynomial chaos approach to epidemiological mathematical models based on ordinary differential equations with random coefficients.

Taking into account the variability of the transmission parameters of the model, this approach allows us to obtain an auxiliary system of differential equations, which is then integrated numerically to obtain the first-and the second-order moments of the output stochastic processes.

A sensitivity analysis based on the polynomial chaos approach is also performed to determine which parameters have the greatest influence on the results.

As an example, we will apply the approach to an obesity epidemic model.

American Psychological Association (APA)

Santonja, Francisco-José& Chen-Charpentier, Benito. 2012. Uncertainty Quantification in Simulations of Epidemics Using Polynomial Chaos. Computational and Mathematical Methods in Medicine،Vol. 2012, no. 2012, pp.1-8.
https://search.emarefa.net/detail/BIM-495114

Modern Language Association (MLA)

Santonja, Francisco-José& Chen-Charpentier, Benito. Uncertainty Quantification in Simulations of Epidemics Using Polynomial Chaos. Computational and Mathematical Methods in Medicine No. 2012 (2012), pp.1-8.
https://search.emarefa.net/detail/BIM-495114

American Medical Association (AMA)

Santonja, Francisco-José& Chen-Charpentier, Benito. Uncertainty Quantification in Simulations of Epidemics Using Polynomial Chaos. Computational and Mathematical Methods in Medicine. 2012. Vol. 2012, no. 2012, pp.1-8.
https://search.emarefa.net/detail/BIM-495114

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-495114