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Title: Data mining for exotic pathogen spread
Author: Ross, David
ISNI:       0000 0004 5992 1410
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2016
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Major disease outbreaks command worldwide attention. Many recent outbreaks were caused by pathogens that were considered 'exotic' with severe implications from a health or economic standpoint. As such, there is need for an in depth examination of these threats and the means by which they might be introduced to effectively manage future risk. This thesis examines a means of identifying key emerging threats and, once identified, then modelling techniques are used to estimate the risk of introduction. To determine the relevant exotic pathogens, data from a survey of experts were examined. In 2010 the 4th Annual Meeting of the EPIZONE network was held at which work was carried out to elicit the opinions of delegates on current and future epidemic threats to the EU. Data from this study were examined using both univariate and multivariate analytical techniques to fully explore and understand what might become an emerging threat. This found that a particular group of zoonotic arboviruses are viewed as important potential emerging threats for Europe. Increasingly realistic and complex modelling approaches were utilised to give an increasingly accurate estimate of the risk of introduction of one of these viruses, Crimean-Congo Haemorrhagic Fever Virus (CCHFV),by means of migratory birds - a potentially key means of introduction. Evaluating this risk must take into account not just disease related factors but also geographic factors especially the migration distance. To model this risk, spatially explicit models that correctly re ect bird migratory behaviour were used in contrast to models published previously. The approaches in this thesis show that for CCHFV there is a de nite risk of introduction but it is smaller than has been estimated previously. Results also show that the bird species that should be focused on are not those intuitively identi ed. The migratory speed of birds is a key factor in identifying the species that represent the greatest risk of introducing CCHFV positive ticks into Europe.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral