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
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