Systemic modelling applied to studying outbreaks of exotic animal diseases

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dc.contributor.advisor Longhurst, Phil
dc.contributor.advisor Pollard, Simon
dc.contributor.author Delgado, Joao Pedro Correa
dc.date.accessioned 2013-05-08T11:17:10Z
dc.date.available 2013-05-08T11:17:10Z
dc.date.issued 2011-11
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/7896
dc.description.abstract Context and rationale – This work originates from policy priorities established within Defra to manage exotic animal diseases (EAD); specifically to understand the causes of low probability events, and to establish contingencies to manage outbreak incidents. Outbreaks of exotic animal diseases, e.g. FMD, CSF and HPAI, can cause economic and social impacts of catastrophic proportions. The UK’s government develops and implements policies and controls to prevent EAD and thus minimise these impacts. Control policies to achieve this are designed to address the vulnerabilities within the control systems. However, data are limited for both the introduction of an EAD as well as its resurgence following the disposal of infected carcasses, i.e. the pre-outbreak and post-outbreak phases of an EAD event. These lack of data compromises the development of policy interventions to improve protection. To overcome these data limitations, predictive models are used to predict system vulnerabilities. Cont/d. en_UK
dc.language.iso en en_UK
dc.publisher Cranfield University en_UK
dc.rights © Cranfield University 2011. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright owner. en_UK
dc.subject Policy development en_UK
dc.subject Carcass disposal assessment en_UK
dc.subject Import risk assessment en_UK
dc.subject Low probability events en_UK
dc.subject Risk mitigation strategies en_UK
dc.title Systemic modelling applied to studying outbreaks of exotic animal diseases en_UK
dc.type Thesis or dissertation en_UK
dc.type.qualificationlevel Doctoral en_UK
dc.type.qualificationname PhD en_UK


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