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  • Applying the stochastic Galerkin method to epidemic models with individualised parameter distributions

    Author(s)
    Harman, David
    Johnston, Peter
    Griffith University Author(s)
    Johnston, Peter R.
    Harman, David B.
    Year published
    2016
    Metadata
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    Abstract
    There are many different models to help predict the likely course an epidemic will take. However, the parameters within these models are often not known with certainty. It is important for this uncertainty to be incorporated into these models to ensure accurate predictions. This article considers the stochastic Galerkin method to solve an sir model with uncertainty in its parameters. A data set from an influenza outbreak in a boarding school is then investigated. Rather than just finding the `best' values for the parameters, several possible probability distributions for the parameters in the sir model are determined. The ...
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    There are many different models to help predict the likely course an epidemic will take. However, the parameters within these models are often not known with certainty. It is important for this uncertainty to be incorporated into these models to ensure accurate predictions. This article considers the stochastic Galerkin method to solve an sir model with uncertainty in its parameters. A data set from an influenza outbreak in a boarding school is then investigated. Rather than just finding the `best' values for the parameters, several possible probability distributions for the parameters in the sir model are determined. The stochastic Galerkin method is then used to determine the mean solution of the model as well as its variance.
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    Journal Title
    ANZIAM Journal
    Volume
    57
    DOI
    https://doi.org/10.21914/anziamj.v57i0.10394
    Subject
    Biological Mathematics
    Mathematical Sciences
    Engineering
    Publication URI
    http://hdl.handle.net/10072/339577
    Collection
    • Journal articles

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