Evidence map›Paper›PMID 34109232›Full record

ArticleFrontiers in veterinary science2021

Engaging Stakeholders in the Design of One Health Surveillance Systems: A Participatory Approach.

Marion Bordier, Flavie Luce Goutard, Nicolas Antoine-Moussiaux, Phuc Pham-Duc, Renaud Lailler, Aurelie Binot

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

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  19. Effective Stakeholder Engagement for Collation, Analysis and Expansion of Antimicrobial Resistance (AMR) Data: A CAPTURA Experience.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    Article
  20. Developing One Health surveillance systems.One health (Amsterdam, Netherlands) · 2023
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Marion BordierASTRE, Univ Montpellier, CIRAD, INRAE, Montpellier, France.
Flavie Luce GoutardASTRE, Univ Montpellier, CIRAD, INRAE, Montpellier, France.
Nicolas Antoine-MoussiauxFundamental and Applied Research for Animals and Health Research Unit, Faculty of Veterinary Medicine, University of Liege, Liege, Belgium.
Phuc Pham-DucCenter for Public Health and Ecosystem Research, Hanoi University of Public Health, Hanoi, Vietnam.
Renaud LaillerLaboratoire de Sécurité des Aliments, Agence Nationale de Sécurité Sanitaire de l'Alimentation, de l'Environnement et du Travail (ANSES), Maisons-Alfort, France.
Aurelie BinotASTRE, Univ Montpellier, CIRAD, INRAE, Montpellier, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many One Health surveillance systems have proven difficult to enforce and sustain, mainly because of the difficulty of implementing and upholding collaborative efforts for surveillance activities across stakeholders with different values, cultures and interests. We hypothesize that only the early engagement of stakeholders in the development of a One Health surveillance system can create an environment conducive to the emergence of collaborative solutions that are acceptable, accepted and therefore implemented in sustainable manner. To this end, we have designed a socio-technical framework to help stakeholders develop a common vision of their desired surveillance system and to forge the innovation pathway toward it. We implemented the framework in two case studies: the surveillance of antimicrobial resistance in Vietnam and that of

Indexed as

antimicrobial resistanceco-constructionOne HealthparticipatorySalmonellasurveillance

Identifiers

PMID34109232
PMCPMC8180848

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.