Developing the pillars for a canine disease surveillance and outbreak response framework in the UK

Student thesis: Doctoral ThesisDoctor of Philosophy (PhD)


Currently, no coordinated strategies exist for surveillance and control of canine diseases worldwide. Thus, our ability to detect and respond to outbreaks is limited, leaving canine populations unprotected. This thesis addresses this problem by focusing on four objectives:
Prioritisation of canine diseases for surveillance and control in the United Kingdom: Using a stakeholder opinion-led approach, criteria for evaluating diseases were established through a multicriteria decision analysis, and a consensus among 19 participants on the disease ranking was achieved through a Delphi technique. Leptospirosis, babesiosis, and respiratory disease were the top-priority endemic diseases, exotic diseases, and syndromes, respectively.
Developing a text mining tool to harness electronic health records for early disease detection: Canine parvovirus was used to illustrate this methodology. A dataset with cases was established for key term extraction from clinical annotations. Key terms were grouped into regular expressions, that were used to define the criteria for a rule-based classifier to estimate a parvovirus likelihood score for each dog. The tool performed successfully in a new dataset.
Exploring clinically relevant thresholds for outbreak notification: Seven veterinarians were interviewed to elicit their preferred levels of case incidence and predictive certainty of the alerts. Interview data were transcribed and coded for relevant elements through a thematic analysis. Notification thresholds were defined for six top-priority canine diseases.
Developing an outbreak response framework for canine diseases in the UK: A response framework was designed and tested in its application to a real-life outbreak through a formative process evaluation. Nine veterinarians were interviewed to improve the design and implementation process of a future response framework, and a Strengths, Weaknesses, Opportunities and Threats analysis identified strategies for its nation-wide implementation.
Together these studies create the opportunity to improve the detection and response to canine disease outbreaks and can be used to inform a surveillance and control system for the UK.
Date of Award19 Mar 2024
Original languageEnglish
Awarding Institution
  • University of Bristol
SupervisorFernando Sánchez-Vizcaíno (Supervisor) & Eszter Szilassy (Supervisor)


  • Outbreak response
  • Disease surveillance
  • Companion animal
  • Canine diseases
  • Canine disease surveillance
  • Epidemic preparedness
  • Epidemic threshold
  • Epidemiology
  • Preventative medicine

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