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EPSRC Reference:
EP/F017006/1
Title:
Bayesian model assessment for stochastic epidemic models
Principal Investigator:
O'Neill, Professor PD
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department:
Sch of Mathematical Sciences
Organisation:
University of Nottingham
Scheme:
Standard Research
Starts:
01 March 2008
Ends:
30 June 2011
Value (£):
201,440
EPSRC Research Topic Classifications:
Medical science & disease
Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
Healthcare
Related Grants:
Panel History:
Panel Date
Panel Name
Outcome
06 Sep 2007
Mathematics Prioritisation Panel (Science)
Announced
Summary on Grant Application Form
Mathematical models for epidemic spread play an increasingly important role in understanding, predicting and controlling real-life disease outbreaks. During recent years, there has been considerable progress in the area of parameterising such models, i.e. estimating model parameters such as infection rates from data on epidemics. However, far less attention has been devoted to model assessment, i.e. determining whether or not models adequately fit the data, and determining whether or not different models would be more suitable. The proposed research seeks to systematically address model assessment for stochastic epidemic models. In particular, (i) simple situations will be analysed in detail to provide generic insights; (ii) new methods will be developed for model assessment for more complex models.
Key Findings
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Potential use in non-academic contexts
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Impacts
Description
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Summary
Date Materialised
Sectors submitted by the Researcher
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Project URL:
Further Information:
Organisation Website:
http://www.nottingham.ac.uk