| EPSRC Reference: |
GR/N09091/01 |
| Title: |
STATISTICAL INFERENCE FOR STOCHASTIC EPIDEMIC MODELS IN STRUCTURED POPULATIONS |
| Principal Investigator: |
O'Neill, Professor PD |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Sch of Mathematical Sciences |
| Organisation: |
University of Nottingham |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
18 January 2000 |
Ends: |
17 January 2001 |
Value (£): |
2,600
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| EPSRC Research Topic Classifications: |
| Statistics & Appl. Probability |
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| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
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| Panel History: |
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Summary on Grant Application Form |
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The VF would work with PDO to develop, analyse and apply efficient MCMC algorithms for two kinds of network epidemic model. First, Bernoulli networks, these being simple models which can be explored in some depth to facilitate understanding and design of efficient algorithms. Second, multi-layer networks, these being more realistic models which take account of real-life social mixing phenomena. The VF would work with FGB to develop and implement martingale based estimators for the within- and between-household infection rates in models for the spread of an epidemic among a community of households, with partial observation. This would involve constructing estimating equations based on zero-mean martingales derived from counting processes embedded within the households epidemic process. The properties of these estimators would be compared with pseudo-likelihood based estimators that have been recently developed at Nottingham.
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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 |
| Summary |
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| Date Materialised |
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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 |