FREE SHIPPING over $40
OVER 9000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Home / Equine Research Bank / Front Vet Sci / Potential and Challenges of Community-Based Surveillance in ...
Frontiers in veterinary science2021; 8; 641448; doi: 10.3389/fvets.2021.641448

Potential and Challenges of Community-Based Surveillance in Animal Health: A Pilot Study Among Equine Owners in Switzerland.

Abstract: Animal owners' potential to observe and report clinical signs, as the persons with the closest contact to their animals, is an often neglected source of information in surveillance. Allowing community members other than health care professionals, such as animal owners, to report health events can contribute to close current surveillance gaps and enhance early detection. In the present study, we tested a community-based surveillance (CBS) approach in the equine community in Switzerland. We aimed at revealing the attitudes and intentions of equine owners toward reporting clinical signs by making use of an online questionnaire. We further set up and operated an online CBS tool, named Equi-Commun. Finally, we investigated potential reasons for the lack of its use by applying qualitative telephone interviews. The majority of the respondents of the online questionnaire (65.5%, 707/1,078) answered that they could see themselves reporting clinical observations of their equine. The multivariate logistic regression analysis indicated that French-speaking equine owners and those belonging to the positive attitude cluster are more likely to report to a CBS tool. Equi-Commun operated between October 2018 and December 2019 yet received only four reports. With the addition of qualitative interviews, we identified three critical, interlinked issues that may have led to the non-use of Equi-Commun within the Swiss equine community: (1) for successfully implementing CBS, the need for surveillance within the community of interest must be given; (2) the respective population under surveillance, here the equine, needs to show enough clinical cases for owners to be able to maintain the memory of an existing tool and its possible use; and (3) targeted and high effort communication of the system is key for its success. While CBS relying only on lay animal owners, complementary to existing surveillance systems, could potentially provide a good proxy of timely surveillance data, it is questionable whether the added value of generated surveillance knowledge is in balance with efforts necessary to implement a successful system. With this study, we showcased both the potential and challenges of CBS in animal health, as this may be of relevance and guidance for future initiatives.
Copyright © 2021 Özçelik, Remy-Wohlfender, Küker, Visschers, Hadorn and Dürr.
Get Full Text
Publication Date: 2021-06-04 PubMed ID: 34150880PubMed Central: PMC8212947DOI: 10.3389/fvets.2021.641448Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This research explores the potential of using community-based surveillance (CBS) in animal health, specifically within the Swiss equine community, and highlights the challenges facing such an initiative. The use of an online tool for equine owners to report health events was explored, with analysis of attitudes and intentions towards reporting, and potential reasons for non-use.

Methodology and Findings

The researchers conducted an online questionnaire to understand the attitudes and intentions of equine owners towards reporting clinical observations. They also set up and operated a CBS tool named Equi-Commun, and analyzed its use over a specific period. Lastly, they conducted qualitative telephone interviews to understand potential reasons for non-use of Equi-Commun.

  • A majority of the equine owners (65.5%) responded that they could see themselves reporting clinical observations of their equines.
  • The tendency to report to a CBS tool was influenced by language (with French-speaking owners more likely to report), and by a positive attitude toward the CBS approach.
  • Despite this, the Equi-Commun tool received only four reports over its operation period from October 2018 to December 2019.

Key Issues Leading to Non-Use

The researchers identified three interlinked critical issues that could have led to the non-use of Equi-Commun within the Swiss equine community.

  • The first issue emphasizes the importance of the community understanding the need for surveillance.
  • Secondly, the equine population under surveillance needs to manifest enough clinical cases for owners to remember the existence of the reporting tool and its potential use.
  • Lastly, the system’s success depends heavily on effective and persistent communication about its existence and importance.

Conclusion

The study suggests that a CBS approach relying solely on animal owners could potentially provide timely surveillance data. However, it also questions whether the value of the generated surveillance knowledge is worth the effort needed to implement a successful system, considering the challenges of maintaining interest, awareness, and participation within the community. This study helps illuminate both the potential and challenges of CBS in animal health and may provide valuable insights for future initiatives.

Cite This Article

APA
Özçelik R, Remy-Wohlfender F, Küker S, Visschers V, Hadorn D, Dürr S. (2021). Potential and Challenges of Community-Based Surveillance in Animal Health: A Pilot Study Among Equine Owners in Switzerland. Front Vet Sci, 8, 641448. https://doi.org/10.3389/fvets.2021.641448

Publication

Frontiers in veterinary science
ISSN: 2297-1769
NlmUniqueID: 101666658
Country: Switzerland
Language: English
Volume: 8
Pages: 641448
PII: 641448

Researcher Affiliations

Özçelik, Ranya
  • Veterinary Public Health Institute, Vetsuisse Faculty, University of Bern, Bern, Switzerland.
Remy-Wohlfender, Franziska
  • ISME Equine Clinic Bern, Vetsuisse Faculty, University of Bern, Bern, Switzerland.
Küker, Susanne
  • Veterinary Public Health Institute, Vetsuisse Faculty, University of Bern, Bern, Switzerland.
Visschers, Vivianne
  • School of Applied Psychology, University of Applied Sciences and Arts Northwestern Switzerland, Olten, Switzerland.
Hadorn, Daniela
  • Federal Food Safety and Veterinary Office, Bern, Switzerland.
Dürr, Salome
  • Veterinary Public Health Institute, Vetsuisse Faculty, University of Bern, Bern, Switzerland.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

This article includes 60 references
  1. Dórea FC, Vial F. Animal health syndromic surveillance: a systematic literature review of the progress in the last 5 years (2011-2016).. Vet Med (Auckl) 2016;7:157-170.
    doi: 10.2147/VMRR.S90182pmc: PMC6044799pubmed: 30050848google scholar: lookup
  2. Hoinville LJ, Alban L, Drewe JA, Gibbens JC, Gustafson L, Häsler B, Saegerman C, Salman M, Stärk KD. Proposed terms and concepts for describing and evaluating animal-health surveillance systems.. Prev Vet Med 2013 Oct 1;112(1-2):1-12.
    doi: 10.1016/j.prevetmed.2013.06.006pubmed: 23906392google scholar: lookup
  3. Bisdorff B, Schauer B, Taylor N, Rodríguez-Prieto V, Comin A, Brouwer A, Dórea F, Drewe J, Hoinville L, Lindberg A, Martinez Avilés M, Martínez-López B, Peyre M, Pinto Ferreira J, Rushton J, VAN Schaik G, Stärk KD, Staubach C, Vicente-Rubiano M, Witteveen G, Pfeiffer D, Häsler B. Active animal health surveillance in European Union Member States: gaps and opportunities.. Epidemiol Infect 2017 Mar;145(4):802-817.
    doi: 10.1017/S0950268816002697pubmed: 27938416google scholar: lookup
  4. Tapprest J, Foucher N, Linster M, Laloy E, Cordonnier N, Amat JP, Hendrikx P. Resumeq: A Novel Way of Monitoring Equine Diseases Through the Centralization of Necropsy Data.. Front Vet Sci 2019;6:135.
    doi: 10.3389/fvets.2019.00135pmc: PMC6524722pubmed: 31134214google scholar: lookup
  5. Küker S, Faverjon C, Furrer L, Berezowski J, Posthaus H, Rinaldi F, Vial F. The value of necropsy reports for animal health surveillance.. BMC Vet Res 2018 Jun 18;14(1):191.
    doi: 10.1186/s12917-018-1505-1pmc: PMC6006731pubmed: 29914502google scholar: lookup
  6. Muellner P, Muellner U, Gates MC, Pearce T, Ahlstrom C, O'Neill D, Brodbelt D, Cave NJ. Evidence in Practice - A Pilot Study Leveraging Companion Animal and Equine Health Data from Primary Care Veterinary Clinics in New Zealand.. Front Vet Sci 2016;3:116.
    doi: 10.3389/fvets.2016.00116pmc: PMC5179563pubmed: 28066777google scholar: lookup
  7. Faverjon C, Andersson MG, Decors A, Tapprest J, Tritz P, Sandoz A, Kutasi O, Sala C, Leblond A. Evaluation of a Multivariate Syndromic Surveillance System for West Nile Virus.. Vector Borne Zoonotic Dis 2016 Jun;16(6):382-90.
    doi: 10.1089/vbz.2015.1883pmc: PMC4884334pubmed: 27159212google scholar: lookup
  8. Gibbens JC, Robertson S, Willmington J, Milnes A, Ryan JB, Wilesmith JW, Cook AJ, David GP. Use of laboratory data to reduce the time taken to detect new diseases: VIDA to FarmFile.. Vet Rec 2008 Jun 14;162(24):771-6.
    doi: 10.1136/vr.162.24.771pubmed: 18552327google scholar: lookup
  9. Doherr MG, Audigé L. Monitoring and surveillance for rare health-related events: a review from the veterinary perspective.. Philos Trans R Soc Lond B Biol Sci 2001 Jul 29;356(1411):1097-106.
    doi: 10.1098/rstb.2001.0898pmc: PMC1088504pubmed: 11516387google scholar: lookup
  10. Carrat F, Sahler C, Rogez S, Leruez-Ville M, Freymuth F, Le Gales C, Bungener M, Housset B, Nicolas M, Rouzioux C. Influenza burden of illness: estimates from a national prospective survey of household contacts in France.. Arch Intern Med 2002 Sep 9;162(16):1842-8.
    doi: 10.1001/archinte.162.16.1842pubmed: 12196082google scholar: lookup
  11. Espetvedt M, Lind AK, Wolff C, Rintakoski S, Virtala AM, Lindberg A. Nordic dairy farmers' threshold for contacting a veterinarian and consequences for disease recording: mild clinical mastitis as an example.. Prev Vet Med 2013 Feb 1;108(2-3):114-24.
    doi: 10.1016/j.prevetmed.2012.07.014pubmed: 22909789google scholar: lookup
  12. Mörk M, Lindberg A, Alenius S, Vågsholm I, Egenvall A. Comparison between dairy cow disease incidence in data registered by farmers and in data from a disease-recording system based on veterinary reporting.. Prev Vet Med 2009 Apr 1;88(4):298-307.
    doi: 10.1016/j.prevetmed.2008.12.005pmc: PMC7114122pubmed: 19178966google scholar: lookup
  13. Marquet RL, Bartelds AI, van Noort SP, Koppeschaar CE, Paget J, Schellevis FG, van der Zee J. Internet-based monitoring of influenza-like illness (ILI) in the general population of the Netherlands during the 2003-2004 influenza season.. BMC Public Health 2006 Oct 4;6:242.
    doi: 10.1186/1471-2458-6-242pmc: PMC1609118pubmed: 17018161google scholar: lookup
  14. Guerra J, Acharya P, Barnadas C. Community-based surveillance: A scoping review.. PLoS One 2019;14(4):e0215278.
    doi: 10.1371/journal.pone.0215278pmc: PMC6461245pubmed: 30978224google scholar: lookup
  15. . A definition for community-based surveillance and a way forward: results of the WHO global technical meeting, France, 26 to 28 June 2018.. Euro Surveill 2019 Jan;24(2).
    doi: 10.2807/1560-7917.ES.2019.24.2.1800681pmc: PMC6337056pubmed: 30646977google scholar: lookup
  16. Ndiaye SM, Quick L, Sanda O, Niandou S. The value of community participation in disease surveillance: a case study from Niger.. Health Promot Int 2003 Jun;18(2):89-98.
    doi: 10.1093/heapro/18.2.89pubmed: 12746380google scholar: lookup
  17. Dil Y, Strachan D, Cairncross S, Korkor AS, Hill Z. Motivations and challenges of community-based surveillance volunteers in the northern region of Ghana.. J Community Health 2012 Dec;37(6):1192-8.
    doi: 10.1007/s10900-012-9569-5pubmed: 22614535google scholar: lookup
  18. Norwegian Red Cross . First Covid-19 Case in Somaliland Detected through CBS. (2020) Available online at: https://uploads-ssl.webflow.com/5d1f301c241e1b056c29ecc6/5e99ad4064d69431fae937a8_5e878d25f99d7c6fa267961c_cbs-covid-19-so_45425167-p-800.png (accessed June 8, 2020).
  19. Catley A, Alders RG, Wood JL. Participatory epidemiology: approaches, methods, experiences.. Vet J 2012 Feb;191(2):151-60.
    doi: 10.1016/j.tvjl.2011.03.010pubmed: 21856195google scholar: lookup
  20. Mariner J, Catley A, Zepeda C. The Role of Community-Based Programmes and Participatory Epidemiology in Disease Surveillance and International Trade. Montpellier (2002).
  21. Pollard D, Wylie CE, Newton JR, Verheyen KLP. Incidence and clinical signs of owner-reported equine laminitis in a cohort of horses and ponies in Great Britain.. Equine Vet J 2019 Sep;51(5):587-594.
    doi: 10.1111/evj.13059pubmed: 30516850google scholar: lookup
  22. Smolinski MS, Crawley AW, Olsen JM, Jayaraman T, Libel M. Participatory Disease Surveillance: Engaging Communities Directly in Reporting, Monitoring, and Responding to Health Threats.. JMIR Public Health Surveill 2017 Oct 11;3(4):e62.
    doi: 10.2196/publichealth.7540pmc: PMC5658636pubmed: 29021131google scholar: lookup
  23. Allport R, Mosha R, Bahari M, Swai E, Catley A. The use of community-based animal health workers to strengthen disease surveillance systems in Tanzania.. Rev Sci Tech 2005 Dec;24(3):921-32.
    pubmed: 16642762
  24. Kongelf A, Bushby RM, Gejibo S, Kaur G, Tingberg T. Technology volunteerism - the red cross' approach to developing a digital community based surveillance tool for early detection of diseases with epidemic potential. Int J Infect Dis (2019) 79:26.
    doi: 10.1016/j.ijid.2018.11.078pubmed: 0google scholar: lookup
  25. Struchen R, Reist M, Zinsstag J, Vial F. Investigating the potential of reported cattle mortality data in Switzerland for syndromic surveillance.. Prev Vet Med 2015 Sep 1;121(1-2):1-7.
    doi: 10.1016/j.prevetmed.2015.04.012pubmed: 26032722google scholar: lookup
  26. Bronner A, Hénaux V, Fortané N, Hendrikx P, Calavas D. Why do farmers and veterinarians not report all bovine abortions, as requested by the clinical brucellosis surveillance system in France?. BMC Vet Res 2014 Apr 24;10:93.
    doi: 10.1186/1746-6148-10-93pmc: PMC4036594pubmed: 24762103google scholar: lookup
  27. Sanders P, Vanderhaeghen W, Fertner M, Fuchs K, Obritzhauser W, Agunos A, Carson C, Borck Høg B, Dalhoff Andersen V, Chauvin C, Hémonic A, Käsbohrer A, Merle R, Alborali GL, Scali F, Stärk KDC, Muentener C, van Geijlswijk I, Broadfoot F, Pokludová L, Firth CL, Carmo LP, Manzanilla EG, Jensen L, Sjölund M, Pinto Ferreira J, Brown S, Heederik D, Dewulf J. Monitoring of Farm-Level Antimicrobial Use to Guide Stewardship: Overview of Existing Systems and Analysis of Key Components and Processes.. Front Vet Sci 2020;7:540.
    doi: 10.3389/fvets.2020.00540pmc: PMC7475698pubmed: 33195490google scholar: lookup
  28. Cole FL, Hodgson DR, Reid SW, Mellor DJ. Owner-reported equine health disorders: results of an Australia-wide postal survey.. Aust Vet J 2005 Aug;83(8):490-5.
    doi: 10.1111/j.1751-0813.2005.tb13301.xpubmed: 16119422google scholar: lookup
  29. Ireland JL, Wylie CE, Collins SN, Verheyen KL, Newton JR. Preventive health care and owner-reported disease prevalence of horses and ponies in Great Britain.. Res Vet Sci 2013 Oct;95(2):418-24.
    doi: 10.1016/j.rvsc.2013.05.007pubmed: 23768693google scholar: lookup
  30. Legrand LJ, Pitel PH, Marcillaud-Pitel CJ, Cullinane AA, Couroucé AM, Fortier GD, Freymuth FL, Pronost SL. Surveillance of equine influenza viruses through the RESPE network in France from November 2005 to October 2010.. Equine Vet J 2013 Nov;45(6):776-83.
    doi: 10.1111/evj.12100pubmed: 23662725google scholar: lookup
  31. VigiRESPE. (2020). Available online at: https://www.vigirespe.net/ (accessed June 3, 2020).
  32. Valon F, Marcillaud-Pitel C, Fortier G, Chaffaux S, Tritz P, D'Ablon X. Le RESPE: réseaud'épidémiosurveillance en pathologie équine. Bull épidémiologique, Santé Anim Aliment (2012) p. 16.
  33. Wohlfender-Remy F, Struchen R, Graubner C, Balmer S, Hadorn D. Re-launch of Equinella: a web-based equine disease reporting and information platform. J Equine Vet Sci 39:S17.
    doi: 10.1016/j.jevs.2016.02.035google scholar: lookup
  34. Özçelik R, Graubner C, Remy-Wohlfender F, Dürr S, Faverjon C. Evaluating 5.5 Years of Equinella: A Veterinary-Based Voluntary Infectious Disease Surveillance System of Equines in Switzerland.. Front Vet Sci 2020;7:327.
    doi: 10.3389/fvets.2020.00327pmc: PMC7339941pubmed: 32695799google scholar: lookup
  35. Struchen R, Hadorn D, Wohlfender F, Balmer S, Süptitz S, Zinsstag J, Vial F. Experiences with a voluntary surveillance system for early detection of equine diseases in Switzerland.. Epidemiol Infect 2016 Jul;144(9):1830-6.
    doi: 10.1017/S0950268816000091pubmed: 26846449google scholar: lookup
  36. Agate. (2020) Available online at: https://www.blw.admin.ch/blw/de/home/politik/datenmanagement.html (accessed October 19, 2020).
  37. R Core Team. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing. (2019).
  38. Husson F, Josse J, Le S, Maintainer JM. Package “FactoMineR” Title Multivariate Exploratory Data Analysis and Data Mining. (2020).
  39. Helfferich C. Leitfaden- und Experteninterviews. Handbuch Methoden der empirischen Sozialforschung Wiesbaden: Springer VS; (2019).
    doi: 10.1007/978-3-658-21308-4_44google scholar: lookup
  40. Equine population distribution Switzerland . (2020) Available online at: https://tierstatistik.identitas.ch/de/map-equids-canton.html (accessed September 14, 2020).
  41. El Allaki F, Bigras-Poulin M, Michel P, Ravel A. A population health surveillance theory.. Epidemiol Health 2012;34:e2012007.
    doi: 10.4178/epih/e2012007pmc: PMC3521104pubmed: 23251837google scholar: lookup
  42. Alarcon P, Wieland B, Mateus AL, Dewberry C. Pig farmers' perceptions, attitudes, influences and management of information in the decision-making process for disease control.. Prev Vet Med 2014 Oct 1;116(3):223-42.
    doi: 10.1016/j.prevetmed.2013.08.004pubmed: 24016600google scholar: lookup
  43. Ajzen I. The Theory of Planned Behavior. Amherst: University of Massachusetts at Amherst Academic Press. Inc. (1991).
    doi: 10.1016/0749-5978(91)90020google scholar: lookup
  44. Thea F van de Mortel. Faking It: Social Desirability Response Bias in Selfreport Research. .
  45. Bethlehem J. Selection Bias in Web Surveys. Int Stat Rev (2010) 78:161–88.
    doi: 10.1111/j.1751-5823.2010.00112.xgoogle scholar: lookup
  46. Edwards AL. The Social Desirability Variable in Personality Assessment and Research. Dryden Press; (1957).
  47. Hammed NS, Owis MI. An integrated health monitoring system. Int Conf Adv Biomed Eng ICABME (2015) 9874732:197–200.
    doi: 10.1109/ICABME.2015.7323286google scholar: lookup
  48. Keller C, Visschers V, Siegrist M. Affective imagery and acceptance of replacing nuclear power plants.. Risk Anal 2012 Mar;32(3):464-77.
    doi: 10.1111/j.1539-6924.2011.01691.xpubmed: 21977961google scholar: lookup
  49. Fischer S, Bosshard G, Faisst K, Tschopp A, Fischer J, Bär W, Gutzwiller F. Swiss doctors' attitudes towards end-of-life decisions and their determinants: a comparison of three language regions.. Swiss Med Wkly 2006 Jun 10;136(23-24):370-6.
    pubmed: 16847759doi: 10.4414/smw.2006.11260google scholar: lookup
  50. Sheeran P. Intention—behavior relations: a conceptual and empirical review. Eur Rev Soc Psychol (2002) 12:1–36.
    doi: 10.1080/14792772143000003google scholar: lookup
  51. Sheeran P, Webb TL. The intention-behavior gap. Soc Personal Psychol Compass (2016) 10:503–18.
    doi: 10.1111/spc3.12265google scholar: lookup
  52. Faries MD. Why We Don't "Just Do It": Understanding the Intention-Behavior Gap in Lifestyle Medicine.. Am J Lifestyle Med 2016 Sep-Oct;10(5):322-329.
    doi: 10.1177/1559827616638017pmc: PMC6125069pubmed: 30202289google scholar: lookup
  53. Brugere C, Onuigbo DM, Morgan KL. People matter in animal disease surveillance: Challenges and opportunities for the aquaculture sector. Aquaculture (2017) 467:158–69.
    doi: 10.1016/j.aquaculture.2016.04.012google scholar: lookup
  54. Paul MC, Figuié M, Kovitvadhi A, Valeix S, Wongnarkpet S, Poolkhet C, Kasemsuwan S, Ducrot C, Roger F, Binot A. Collective resistance to HPAI H5N1 surveillance in the Thai cockfighting community: Insights from a social anthropology study.. Prev Vet Med 2015 Jun 1;120(1):106-14.
    doi: 10.1016/j.prevetmed.2015.02.021pubmed: 25800453google scholar: lookup
  55. Jerolmack C. Who's worried about turkeys? How 'organisational silos' impede zoonotic disease surveillance.. Sociol Health Illn 2013 Feb;35(2):200-12.
    doi: 10.1111/j.1467-9566.2012.01501.xpubmed: 22943436google scholar: lookup
  56. Fernandez ME, Ruiter RAC, Markham CM, Kok G. Intervention Mapping: Theory- and Evidence-Based Health Promotion Program Planning: Perspective and Examples.. Front Public Health 2019;7:209.
    doi: 10.3389/fpubh.2019.00209pmc: PMC6702459pubmed: 31475126google scholar: lookup
  57. Bonney R, Cooper CB, Dickinson J, Kelling S, Phillips T, Rosenberg K V. Citizen science: a developing tool for expanding science knowledge and scientific literacy. Bioscience (2009) 59:977–84.
    doi: 10.1525/bio.2009.59.11.9google scholar: lookup
  58. Brookes VJ, Kennedy E, Dhagapan P, Ward MP. Qualitative Research to Design Sustainable Community-Based Surveillance for Rabies in Northern Australia and Papua New Guinea.. Front Vet Sci 2017;4:19.
    doi: 10.3389/fvets.2017.00019pmc: PMC5319981pubmed: 28275611google scholar: lookup
  59. Meyers DC, Katz J, Chien V, Wandersman A, Scaccia JP, Wright A. Practical implementation science: developing and piloting the quality implementation tool.. Am J Community Psychol 2012 Dec;50(3-4):481-96.
    doi: 10.1007/s10464-012-9521-ypubmed: 22618025google scholar: lookup
  60. InfoSM. (2020) Available online at: https://www.infosm.blv.admin.ch/evaluation/frequency?lang=en&from=2017-10-09&to=2020-10-09 (accessed Jul 14, 2020).

Citations

This article has been cited 1 times.
  1. McGowan CR, Takahashi E, Romig L, Bertram K, Kadir A, Cummings R, Cardinal LJ. Community-based surveillance of infectious diseases: a systematic review of drivers of success. BMJ Glob Health 2022 Aug;7(8).
    doi: 10.1136/bmjgh-2022-009934pubmed: 35985697google scholar: lookup
Subscribe to our newsletter
Join 99,359 horse owners like you who receive our email updates on horse health and nutrition.