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

Research output: Contribution to journalArticlepeer-review

58 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)527-544
Number of pages18
JournalMathematical Biosciences and Engineering
Volume3
Issue number3
DOIs
StatePublished - Jul 2006
Externally publishedYes

Keywords

  • Control reproduction number
  • Epidemiological model
  • Functional output
  • Latin hypercube sampling
  • Partial rank correlation coefficients

ASJC Scopus subject areas

  • Modeling and Simulation
  • General Agricultural and Biological Sciences
  • Computational Mathematics
  • Applied Mathematics

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