| EPSRC Reference: |
GR/S43214/01 |
| Title: |
Application of HE Computing to Develop Complex Stochastic Models to aid Public Health and National Operational Responses to Infectious Disease Threats |
| Principal Investigator: |
Leach, Professor SA |
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| Department: |
Research |
| Organisation: |
HPA (Porton Down) |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
05 April 2004 |
Ends: |
04 October 2006 |
Value (£): |
90,776
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| EPSRC Research Topic Classifications: |
| Mathematical Aspects of OR |
Medical science & disease |
| Statistics & Appl. Probability |
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Summary on Grant Application Form |
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Recent high-profile epidemics (such as the UK 2001 foot-and-mouth outbreak), together with the threat of bio-terrorism or naturally occurring pandemics, have highlighted the need for detailed spatio-temporal epidemic models to predict the course of an outbreak and inform control policy. This project will utilize detailed census data to develop the most accurate stochastic epidemic model to-date for the UK, accounting for the vast range of heterogeneities in population density and movement patterns. Models at this resolution will require national high-end computing capabilities to realise their full potential and provide an effective tool in real-time situations.The natural spatial structure of human movements lends itself to parallelisation, where each processor deals with a localised set of populations. However these are linked by the random movement of individuals (either commuters or recreational visitors) and incorporating these movements in a biologically realistic but computationally efficient manner is a significant challenge.The results of simulations will be compared to the recorded spatio-temporal dynamics of influenza epidemics, which will allow fine-tuning of the few unknown parameters. Once developed and verified the model can extended to other infectious diseases and be used to consider various control strategies. Finally the detailed results allow us to extend current epidemiological theory, refining the simpler models and suggesting when such methods are applicable.
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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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