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

IntroductionThe 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.MethodologyAn 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.ResultsSeven 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.ConclusionThis 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. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Carmen Tamayo Cuartero [verfasserIn] Eszter Szilassy [verfasserIn] Alan D. Radford [verfasserIn] J. Richard Newton [verfasserIn] Fernando Sánchez-Vizcaíno [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	disease surveillance canine diseases qualitative research outbreak detection outbreak reporting

Übergeordnetes Werk:	In: Frontiers in Veterinary Science - Frontiers Media S.A., 2015, 11(2024)
Übergeordnetes Werk:	volume:11 ; year:2024

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fvets.2024.1259021

Katalog-ID:	DOAJ091663059

Internformat


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245	1	0	\|a Setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study
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520			\|a IntroductionThe 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.MethodologyAn 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.ResultsSeven 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.ConclusionThis 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.
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allfields	10.3389/fvets.2024.1259021 doi (DE-627)DOAJ091663059 (DE-599)DOAJ02f5de71feb3450db623617f9c423db9 DE-627 ger DE-627 rakwb eng SF600-1100 Carmen Tamayo Cuartero verfasserin aut Setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier IntroductionThe 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.MethodologyAn 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.ResultsSeven 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.ConclusionThis 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. disease surveillance canine diseases qualitative research outbreak detection outbreak reporting Veterinary medicine Eszter Szilassy verfasserin aut Alan D. Radford verfasserin aut J. Richard Newton verfasserin aut Fernando Sánchez-Vizcaíno verfasserin aut In Frontiers in Veterinary Science Frontiers Media S.A., 2015 11(2024) (DE-627)835029417 (DE-600)2834243-4 22971769 nnns volume:11 year:2024 https://doi.org/10.3389/fvets.2024.1259021 kostenfrei https://doaj.org/article/02f5de71feb3450db623617f9c423db9 kostenfrei https://www.frontiersin.org/articles/10.3389/fvets.2024.1259021/full kostenfrei https://doaj.org/toc/2297-1769 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2024
spelling	10.3389/fvets.2024.1259021 doi (DE-627)DOAJ091663059 (DE-599)DOAJ02f5de71feb3450db623617f9c423db9 DE-627 ger DE-627 rakwb eng SF600-1100 Carmen Tamayo Cuartero verfasserin aut Setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier IntroductionThe 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.MethodologyAn 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.ResultsSeven 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.ConclusionThis 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. disease surveillance canine diseases qualitative research outbreak detection outbreak reporting Veterinary medicine Eszter Szilassy verfasserin aut Alan D. Radford verfasserin aut J. Richard Newton verfasserin aut Fernando Sánchez-Vizcaíno verfasserin aut In Frontiers in Veterinary Science Frontiers Media S.A., 2015 11(2024) (DE-627)835029417 (DE-600)2834243-4 22971769 nnns volume:11 year:2024 https://doi.org/10.3389/fvets.2024.1259021 kostenfrei https://doaj.org/article/02f5de71feb3450db623617f9c423db9 kostenfrei https://www.frontiersin.org/articles/10.3389/fvets.2024.1259021/full kostenfrei https://doaj.org/toc/2297-1769 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2024
allfields_unstemmed	10.3389/fvets.2024.1259021 doi (DE-627)DOAJ091663059 (DE-599)DOAJ02f5de71feb3450db623617f9c423db9 DE-627 ger DE-627 rakwb eng SF600-1100 Carmen Tamayo Cuartero verfasserin aut Setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier IntroductionThe 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.MethodologyAn 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.ResultsSeven 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.ConclusionThis 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. disease surveillance canine diseases qualitative research outbreak detection outbreak reporting Veterinary medicine Eszter Szilassy verfasserin aut Alan D. Radford verfasserin aut J. Richard Newton verfasserin aut Fernando Sánchez-Vizcaíno verfasserin aut In Frontiers in Veterinary Science Frontiers Media S.A., 2015 11(2024) (DE-627)835029417 (DE-600)2834243-4 22971769 nnns volume:11 year:2024 https://doi.org/10.3389/fvets.2024.1259021 kostenfrei https://doaj.org/article/02f5de71feb3450db623617f9c423db9 kostenfrei https://www.frontiersin.org/articles/10.3389/fvets.2024.1259021/full kostenfrei https://doaj.org/toc/2297-1769 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2024
allfieldsGer	10.3389/fvets.2024.1259021 doi (DE-627)DOAJ091663059 (DE-599)DOAJ02f5de71feb3450db623617f9c423db9 DE-627 ger DE-627 rakwb eng SF600-1100 Carmen Tamayo Cuartero verfasserin aut Setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier IntroductionThe 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.MethodologyAn 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.ResultsSeven 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.ConclusionThis 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. disease surveillance canine diseases qualitative research outbreak detection outbreak reporting Veterinary medicine Eszter Szilassy verfasserin aut Alan D. Radford verfasserin aut J. Richard Newton verfasserin aut Fernando Sánchez-Vizcaíno verfasserin aut In Frontiers in Veterinary Science Frontiers Media S.A., 2015 11(2024) (DE-627)835029417 (DE-600)2834243-4 22971769 nnns volume:11 year:2024 https://doi.org/10.3389/fvets.2024.1259021 kostenfrei https://doaj.org/article/02f5de71feb3450db623617f9c423db9 kostenfrei https://www.frontiersin.org/articles/10.3389/fvets.2024.1259021/full kostenfrei https://doaj.org/toc/2297-1769 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2024
allfieldsSound	10.3389/fvets.2024.1259021 doi (DE-627)DOAJ091663059 (DE-599)DOAJ02f5de71feb3450db623617f9c423db9 DE-627 ger DE-627 rakwb eng SF600-1100 Carmen Tamayo Cuartero verfasserin aut Setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier IntroductionThe 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.MethodologyAn 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.ResultsSeven 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.ConclusionThis 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. disease surveillance canine diseases qualitative research outbreak detection outbreak reporting Veterinary medicine Eszter Szilassy verfasserin aut Alan D. Radford verfasserin aut J. Richard Newton verfasserin aut Fernando Sánchez-Vizcaíno verfasserin aut In Frontiers in Veterinary Science Frontiers Media S.A., 2015 11(2024) (DE-627)835029417 (DE-600)2834243-4 22971769 nnns volume:11 year:2024 https://doi.org/10.3389/fvets.2024.1259021 kostenfrei https://doaj.org/article/02f5de71feb3450db623617f9c423db9 kostenfrei https://www.frontiersin.org/articles/10.3389/fvets.2024.1259021/full kostenfrei https://doaj.org/toc/2297-1769 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2024
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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.MethodologyAn 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.ResultsSeven 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.ConclusionThis 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.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">disease surveillance</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">canine diseases</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">qualitative research</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">outbreak detection</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">outbreak reporting</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Veterinary medicine</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Eszter Szilassy</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Alan D. 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callnumber-first	S - Agriculture
author	Carmen Tamayo Cuartero
spellingShingle	Carmen Tamayo Cuartero misc SF600-1100 misc disease surveillance misc canine diseases misc qualitative research misc outbreak detection misc outbreak reporting misc Veterinary medicine Setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study
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topic_title	SF600-1100 Setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study disease surveillance canine diseases qualitative research outbreak detection outbreak reporting
topic	misc SF600-1100 misc disease surveillance misc canine diseases misc qualitative research misc outbreak detection misc outbreak reporting misc Veterinary medicine
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title	Setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study
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title_full	Setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study
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author_browse	Carmen Tamayo Cuartero Eszter Szilassy Alan D. Radford J. Richard Newton Fernando Sánchez-Vizcaíno
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title_sort	setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study
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title_auth	Setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study
abstract	IntroductionThe 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.MethodologyAn 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.ResultsSeven 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.ConclusionThis 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.
abstractGer	IntroductionThe 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.MethodologyAn 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.ResultsSeven 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.ConclusionThis 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.
abstract_unstemmed	IntroductionThe 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.MethodologyAn 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.ResultsSeven 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.ConclusionThis 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.
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title_short	Setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study
url	https://doi.org/10.3389/fvets.2024.1259021 https://doaj.org/article/02f5de71feb3450db623617f9c423db9 https://www.frontiersin.org/articles/10.3389/fvets.2024.1259021/full https://doaj.org/toc/2297-1769
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author2	Eszter Szilassy Alan D. Radford J. Richard Newton Fernando Sánchez-Vizcaíno
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Interviews were transcribed, and a thematic analysis was performed using NVivo 12.ResultsSeven 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.ConclusionThis 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. 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Setting clinically relevant thresholds for the notification of canine disease outbreaks to veterinary practitioners: an exploratory qualitative interview study

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