Sensitivity and uncertainty analyses for a SARS model with time-varying inputs and outputs
Robert G. McLeod John F. Brewster Abba B. Gumel Dean A. Slonowsky
Mathematical Biosciences & Engineering 2006, 3(3): 527-544 doi: 10.3934/mbe.2006.3.527
This paper presents a statistical study of a deterministic model for the transmission dynamics and control of severe acute respiratory syndrome (SARS). The effect of the model parameters on the dynamics of the disease is analyzed using sensitivity and uncertainty analyses. The response (or output) of interest is the control reproduction number, which is an epidemiological threshold governing the persistence or elimination of SARS in a given population. The compartmental model includes parameters associated with control measures such as quarantine and isolation of asymptomatic and symptomatic individuals. One feature of our analysis is the incorporation of time-dependent functions into the model to reflect the progressive refinement of these SARS control measures over time. Consequently, the model contains continuous time-varying inputs and outputs. In this setting, sensitivity and uncertainty analytical techniques are used in order to analyze the impact of the uncertainty in the parameter estimates on the results obtained and to determine which parameters have the largest impact on driving the disease dynamics.
keywords: epidemiological model functional out-put control reproduction number Latin hypercube sampling partial rank correlation coefficients.

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