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Characteristics of One Health surveillance systems: A systematic literature review
- Source :
- Preventive Veterinary Medicine, Preventive Veterinary Medicine, Elsevier, 2020, 181, pp.104560. ⟨10.1016/j.prevetmed.2018.10.005⟩
- Publication Year :
- 2020
- Publisher :
- HAL CCSD, 2020.
-
Abstract
- International audience; The concept of One Health (OH) promotes the decompartmentalisation of human, animal, and ecosystem health for the more efficient and sustainable governance of complex health issues. This means that traditional boundaries between disciplines and sectors must be transgressed and that all relevant stakeholders must be involved in the definition and management of health problems. International efforts have been made to strengthen collaboration across sectors and disciplines and OH surveillance is strongly encouraged at global, national and local-level to efficiently manage hazards involving humans, animals and ecosystems.This concept is intuitively appealing and would suggest the enhanced performance and cost-effectiveness of surveillance systems, as compared to more conventional approaches. Nevertheless, confusion and uncertainty regarding the practical application, outcomes and impacts prevail. We believe that this is due to the lack of a conceptual and methodological framework which would (i) define the characteristics of OH surveillance, and (ii) identify the appropriate mechanisms for inter-sectoral and multi-disciplinary collaboration, to ensure that the surveillance system performs well, with regard to the objective, the context and the health hazard under surveillance.The objective of the study is to define the organisational and functional characteristics of OH surveillance systems, the context in which they are implemented, as well as the influential factors which may obstruct or support their implementation and performance. To achieve this, a systematic literature review of existing OH surveillance systems was conducted using the Prisma guidelines. The selected systems were assessed according to 38 predetermined variables. These allowed the characterisation of their objectives, organisation, functioning, performance and benefits. Data extraction was conducted using a spreadsheet and a database was built using an electronic multiple-choice questionnaire.The literature search identified a total of 1635 records. After the screening phase, 31 references were kept and 22 additional references retrieved from bibliographies were added. From these 53 selected documents, we retrieved 41 different surveillance systems in line with the definition proposed in this study. The analysis of this database enabled the identification of different dimensions and areas of collaboration. Barriers and levers for the implementation of OH surveillance systems were also identified and discussed.Based on our results, we propose a framework to characterise the organisation of collaboration for the governance and operation of an effective OH surveillance system.
- Subjects :
- Process management
040301 veterinary sciences
Computer science
[SDV]Life Sciences [q-bio]
030231 tropical medicine
Framework
Context (language use)
L73 - Maladies des animaux
Phase (combat)
0403 veterinary science
03 medical and health sciences
0302 clinical medicine
Food Animals
Animals
Humans
One Health
Ecosystem
Ecosystem health
Surveillance
Corporate governance
04 agricultural and veterinary sciences
Collaboration
3. Good health
Identification (information)
Systematic review
Data extraction
C30 - Documentation et information
Population Surveillance
Epidemiological Monitoring
Animal Science and Zoology
[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
P01 - Conservation de la nature et ressources foncières
Subjects
Details
- Language :
- English
- ISSN :
- 01675877
- Database :
- OpenAIRE
- Journal :
- Preventive Veterinary Medicine, Preventive Veterinary Medicine, Elsevier, 2020, 181, pp.104560. ⟨10.1016/j.prevetmed.2018.10.005⟩
- Accession number :
- edsair.doi.dedup.....dc805229c1351229a024eb6af02c1347
- Full Text :
- https://doi.org/10.1016/j.prevetmed.2018.10.005⟩