For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
0
views
Article has an altmetric score of 1
19
references
 Top references
cited by
0
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      120
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Introduction

          The Small Animal Veterinary Surveillance Network (SAVSNET) has developed mathematical models to analyse the veterinary practice and diagnostic laboratory data to detect genuine outbreaks of canine disease in the United Kingdom. There are, however, no validated methods available to establish the clinical relevance of these genuine statistical outbreaks before their formal investigation is conducted. This study aimed to gain an actionable understanding of a veterinary practitioner’s preferences regarding which outbreak scenarios have a substantial impact on veterinary practice for six priority canine diseases in the United Kingdom.

          Methodology

          An intensity sampling approach was followed to recruit veterinary practitioners according to their years of experience and the size of their practice. In-depth semi-structured and structured interviews were conducted to describe an outbreak notification and outbreak response thresholds for six canine endemic diseases, exotic diseases, and syndromes. These thresholds reflected participants’ preferred balance between the levels of excess case incidence and predictive certainty of the detection system. Interviews were transcribed, and a thematic analysis was performed using NVivo 12.

          Results

          Seven interviews were completed. The findings indicate higher preferred levels of predictive certainty for endemic diseases than for exotic diseases, ranging from 95 to 99% and 80 to 90%, respectively. The levels of excess case incidence were considered clinically relevant at values representing an increase of two to four times in the normal case incidence expectancy for endemic agents, such as parvovirus, and where they indicated a single case in the practice’s catchment area for exotic diseases such as leishmaniosis and babesiosis.

          Conclusion

          This study’s innovative methodology uses veterinary practitioners’ opinions to inform the selection of a notification threshold value in real-world applications of stochastic canine outbreak detection models. The clinically relevant thresholds derived from participants’ needs will be used by SAVSNET to inform its outbreak detection system and to improve its response to canine disease outbreaks in the United Kingdom.

          Related collections

          Most cited references19

          • Record: found
          • Abstract: not found
          • Article: not found

          Using thematic analysis in psychology

          Virginia Braun, Victoria Clarke (2016)
          Article 0 comments Cited 22101 times – based on 0 reviews     Review now
          Article has an altmetric score of 495
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Demonstrating Rigor Using Thematic Analysis: A Hybrid Approach of Inductive and Deductive Coding and Theme Development

            Jennifer Fereday, Eimear Muir-Cochrane (2016)
            Article 0 comments Cited 1335 times – based on 0 reviews     Review now
            Article has an altmetric score of 26
              Bookmark
              • Record: found
              • Abstract: not found
              • Book: not found

              Qualitative research\evaluation methods: Integrating theory and practice

              Q Patton M, MQ PATTON, MQ Patton … (2014)
              Book 0 comments Cited 113 times – based on 0 reviews
                Bookmark
                All references

                Author and article information

                Contributors
                Carmen Tamayo Cuartero: URI : https://loop.frontiersin.org/people/2378302/overviewRole: Role: Role: Role: Role: Role: Role: Role: Role: Role:
                Eszter Szilassy: URI : https://loop.frontiersin.org/people/2622354/overviewRole: Role:
                Alan D. Radford: Role: Role: Role: Role:
                J. Richard Newton: URI : https://loop.frontiersin.org/people/2635142/overviewRole:
                Fernando Sánchez-Vizcaíno: URI : https://loop.frontiersin.org/people/757464/overviewRole: Role: Role: Role: Role: Role: Role: Role:
                Journal
                Journal ID (nlm-ta): Front Vet Sci
                Journal ID (iso-abbrev): Front Vet Sci
                Journal ID (publisher-id): Front. Vet. Sci.
                Title: Frontiers in Veterinary Science
                Publisher: Frontiers Media S.A.
                ISSN (Electronic): 2297-1769
                Publication date (Electronic): 28 February 2024
                Publication date Collection: 2024
                Volume: 11
                Electronic Location Identifier: 1259021
                Affiliations
                [1] 1Bristol Veterinary School, Faculty of Health Sciences, University of Bristol , Bristol, United Kingdom
                [2] 2Bristol Medical School, Faculty of Health Sciences, University of Bristol , Bristol, United Kingdom
                [3] 3Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool , Liverpool, United Kingdom
                [4] 4Department of Veterinary Medicine, Cambridge Veterinary School, University of Cambridge , Cambridge, United Kingdom
                Author notes

                Edited by: Marta Martinez Aviles, Instituto Nacional de Investigación y Tecnología Agroalimentaria (INIA), Spain

                Reviewed by: Bernard J. Phiri, Ministry for Primary Industries, New Zealand

                Emilie Vallee, Massey University, New Zealand

                Article
                DOI: 10.3389/fvets.2024.1259021
                PMC ID: 10936540
                PubMed ID: 38482169
                SO-VID: 78e73b10-f581-44dd-ae72-085a46babb01
                Copyright © Copyright © 2024 Tamayo Cuartero, Szilassy, Radford, Newton and Sánchez-Vizcaíno.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                Date received : 14 July 2023
                Date accepted : 31 January 2024
                Page count
                Figures: 2, Tables: 7, Equations: 0, References: 35, Pages: 13, Words: 9431
                Funding
                The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was funded by Dogs Trust as part of SAVSNET-Agile.
                Categories
                Subject: Veterinary Science
                Subject: Original Research
                Custom metadata
                section-at-acceptance Veterinary Epidemiology and Economics

                Keywords: disease surveillance,canine diseases,qualitative research,outbreak detection,outbreak reporting
                Data availability:
                Keywords: disease surveillance, canine diseases, qualitative research, outbreak detection, outbreak reporting

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content120

                See all similar

                Most referenced authors274

                See all reference authors