EPSRC Reference: |
GR/K49317/01 |
Title: |
STOCHASTIC SPACE-TIME MODELLING IN EPIDEMIOLOGY AND AGRICULTURE |
Principal Investigator: |
Renshaw, Professor E |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Statistics and Modelling Science |
Organisation: |
University of Strathclyde |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
01 January 1996 |
Ends: |
31 December 1998 |
Value (£): |
116,016
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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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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
With few exceptions interest in spatial processes has often been centred on purely spatial aspects of pattern. This may be acceptable if the sole aim is to provide a summary of spatial structure. However, if we wish to understand the dynamics of the underlying processes which generate spatial pattern then temporal aspects cannot be ignored. Indeed, in practical examples of spatio-temporal processes, where the motivation may be to control a population or an epidemic, consideration of temporal aspects is essential. This research proposal sets out to apply recent theoretical advances in the modelling of stochastic spatio-temporal processes to several important biological systems currently under study within the Scottish agricultural research community. These involve the dynamics of populations, interactions between populations, and the spatial movements of populations in ecosystems. Their further study through mathematical modelling will represent a substantial contribution to the field of mathematical biology. The lack of understanding of these systems can lead to financial loss to farmers, risk to the health of humans or animals, and detrimental impacts on the environment. Their study therefore has considerable potential for making a substantial contribution to wealth creation, human and animal welfare, and environmental improvement. Specific issues which will be considered are the sensitivity of deterministic models to the inclusion of stochastic effects and the contrasts between different approaches to representing spatio-temporal processes and boundary conditions. These questions will be investigated in the context of applications in veterinary epidemiology, plant epidemiology and microbial population dynamics.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.strath.ac.uk |