Details of Grant 

EPSRC Reference:	EP/E038670/1
Title:	Stochastic epidemic models in structured populations
Principal Investigator:	Ball, Professor FG
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department:	Sch of Mathematical Sciences
Organisation:	University of Nottingham
Scheme:	Standard Research
Starts:	01 September 2007	Ends:	31 August 2010	Value (£):	228,495
EPSRC Research Topic Classifications:	Medical science & disease Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:	No relevance to Underpinning Sectors
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Panel History:
Summary on Grant Application Form
The aim of the proposed research is to develop and analyse stochastic epidemic models that incorporate realistic population structures and are mathematically tractable. Random network models that explicitly include household structure will be investigated, as will models that allow different severities of infection and models incorporating more complex structures, such as hierarchical mixing (e.g. a population of cities, each of which is partitioned into households, with different infection rates for within-household, within-city and between-city contacts), overlapping subgroups (in which the population is partitioned in several ways, e.g according to both the household and workplace of individuals) and spatial local mixing. For each model, a threshold parameter that governs whether or not an outbreak can become established will be determined, together with other properties, such as the probability that an outbreak does become established and the final outcome if it does. Implications for vaccination strategies will be explored, using a varitey of models for how vaccination affects a vaccinee's susceptibility to the disease in question and his/her ability to transmit the disease if he/she becomes infected. The theory developed will be tested by using simulations on realistic contact networks that have been proposed for diseases such as SARs and pandemic influenza. The planned research will lead to novel methods for analysing epidemic models and to increased understanding of the mechanisms underlying the spread of infection and the effect of such mechanisms on the performance of vaccination schemes.
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Organisation Website:	http://www.nottingham.ac.uk