| EPSRC Reference: |
EP/J013528/1 |
| Title: |
Bayesian Nonparametric Inference for Stochastic Epidemic Models |
| Principal Investigator: |
Kypraios, Professor T |
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| Department: |
Sch of Mathematical Sciences |
| Organisation: |
University of Nottingham |
| Scheme: |
First Grant - Revised 2009 |
| Starts: |
15 October 2012 |
Ends: |
14 October 2014 |
Value (£): |
96,432
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| EPSRC Research Topic Classifications: |
| Statistics & Appl. Probability |
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Summary on Grant Application Form |
Understanding the spread of communicable infectious diseases is of great importance in order to prevent major future outbreaks and therefore it remains high on the global scientific agenda. It has been widely recognised that mathematical and statistical modelling has become a valuable tool in the analysis of infectious disease dynamics by supporting the development of control strategies, informing policy-making at the highest levels, and in general playing a fundamental role in the fight against the spread of disease.
Despite the enormous attention given to the development of methods for efficient parameter estimation, there has been relatively little activity in the area of non-parametric inference. That is, drawing inference for the quantities which govern transmission, i) the force of infection and ii) the period during which an individual remains infectious, without making certain modelling assumptions about its (parametric) functional form or that it belongs to a certain family of parametric distributions.
The proposed research is concerned with the development of new methodology which will enable non-parametric estimation of the parameters which govern transmission within a Bayesian framework and the application of the proposed methods to large disease outbreak datasets.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.nottingham.ac.uk |