Sensitivity and uncertainty analyses for a SARS model with time-varying inputs and outputs
This paper presents a statistical study of a deterministic model for the transmissiondynamics and control of severe acute respiratory syndrome (SARS). The effect of themodel parameters on the dynamics of the disease is analyzed using sensitivity anduncertainty analyses. The response (or output) of i...
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| Format: | Article |
| Language: | English |
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AIMS Press
2006-04-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2006.3.527 |
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| author | Robert G. McLeod John F. Brewster Abba B. Gumel Dean A. Slonowsky |
| author_facet | Robert G. McLeod John F. Brewster Abba B. Gumel Dean A. Slonowsky |
| author_sort | Robert G. McLeod |
| collection | DOAJ |
| description | This paper presents a statistical study of a deterministic model for the transmissiondynamics and control of severe acute respiratory syndrome (SARS). The effect of themodel parameters on the dynamics of the disease is analyzed using sensitivity anduncertainty analyses. The response (or output) of interest is the control reproductionnumber, which is an epidemiological threshold governing the persistence or eliminationof SARS in a given population. The compartmental model includes parameters associatedwith control measures such as quarantine and isolation of asymptomatic and symptomaticindividuals. One feature of our analysis is the incorporation of time-dependentfunctions into the model to reflect the progressive refinement of these SARS controlmeasures over time. Consequently, the model contains continuous time-varying inputs andoutputs. In this setting, sensitivity and uncertainty analytical techniques are used inorder to analyze the impact of the uncertainty in the parameter estimates on the resultsobtained and to determine which parameters have the largest impact on driving thedisease dynamics. |
| format | Article |
| id | doaj-art-7e0f704f1d2c40969a87b68bcdb6176b |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2006-04-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-7e0f704f1d2c40969a87b68bcdb6176b2025-01-24T01:51:49ZengAIMS PressMathematical Biosciences and Engineering1551-00182006-04-013352754410.3934/mbe.2006.3.527Sensitivity and uncertainty analyses for a SARS model with time-varying inputs and outputsRobert G. McLeod0John F. Brewster1Abba B. Gumel2Dean A. Slonowsky3Department of Mathematics and Statistics, University of Winnipeg, Winnipeg, MB, Canada R3B 2E9Department of Mathematics and Statistics, University of Winnipeg, Winnipeg, MB, Canada R3B 2E9Department of Mathematics and Statistics, University of Winnipeg, Winnipeg, MB, Canada R3B 2E9Department of Mathematics and Statistics, University of Winnipeg, Winnipeg, MB, Canada R3B 2E9This paper presents a statistical study of a deterministic model for the transmissiondynamics and control of severe acute respiratory syndrome (SARS). The effect of themodel parameters on the dynamics of the disease is analyzed using sensitivity anduncertainty analyses. The response (or output) of interest is the control reproductionnumber, which is an epidemiological threshold governing the persistence or eliminationof SARS in a given population. The compartmental model includes parameters associatedwith control measures such as quarantine and isolation of asymptomatic and symptomaticindividuals. One feature of our analysis is the incorporation of time-dependentfunctions into the model to reflect the progressive refinement of these SARS controlmeasures over time. Consequently, the model contains continuous time-varying inputs andoutputs. In this setting, sensitivity and uncertainty analytical techniques are used inorder to analyze the impact of the uncertainty in the parameter estimates on the resultsobtained and to determine which parameters have the largest impact on driving thedisease dynamics.https://www.aimspress.com/article/doi/10.3934/mbe.2006.3.527epidemiological modelfunctional out-putcontrol reproduction numberlatin hypercube samplingpartial rank correlation coefficients. |
| spellingShingle | Robert G. McLeod John F. Brewster Abba B. Gumel Dean A. Slonowsky Sensitivity and uncertainty analyses for a SARS model with time-varying inputs and outputs Mathematical Biosciences and Engineering epidemiological model functional out-put control reproduction number latin hypercube sampling partial rank correlation coefficients. |
| title | Sensitivity and uncertainty analyses for a SARS model with time-varying inputs and outputs |
| title_full | Sensitivity and uncertainty analyses for a SARS model with time-varying inputs and outputs |
| title_fullStr | Sensitivity and uncertainty analyses for a SARS model with time-varying inputs and outputs |
| title_full_unstemmed | Sensitivity and uncertainty analyses for a SARS model with time-varying inputs and outputs |
| title_short | Sensitivity and uncertainty analyses for a SARS model with time-varying inputs and outputs |
| title_sort | sensitivity and uncertainty analyses for a sars model with time varying inputs and outputs |
| topic | epidemiological model functional out-put control reproduction number latin hypercube sampling partial rank correlation coefficients. |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2006.3.527 |
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