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Is scientific evidence enough? Using expert opinion to fill gaps in data in antimicrobial resistance research.
Cousins, Melanie; Parmley, E Jane; Greer, Amy L; Neiterman, Elena; Lambraki, Irene A; Graells, Tiscar; Léger, Anaïs; Henriksson, Patrik J G; Troell, Max; Wernli, Didier; Søgaard Jørgensen, Peter; Carson, Carolee A; Majowicz, Shannon E.
Afiliação
  • Cousins M; School of Public Health Sciences, University of Waterloo, Waterloo, Ontario, Canada.
  • Parmley EJ; Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada.
  • Greer AL; Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada.
  • Neiterman E; School of Public Health Sciences, University of Waterloo, Waterloo, Ontario, Canada.
  • Lambraki IA; School of Public Health Sciences, University of Waterloo, Waterloo, Ontario, Canada.
  • Graells T; Global Economic Dynamics and the Biosphere, Royal Swedish Academy of Sciences, Stockholm, Sweden.
  • Léger A; Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden.
  • Henriksson PJG; Global Studies Institute, University of Geneva, Geneva, Switzerland.
  • Troell M; Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden.
  • Wernli D; Beijer Institute of Ecological Economics, Royal Swedish Academy of Sciences, Stockholm, Sweden.
  • Søgaard Jørgensen P; WorldFish, Penang, Malaysia.
  • Carson CA; Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden.
  • Majowicz SE; Beijer Institute of Ecological Economics, Royal Swedish Academy of Sciences, Stockholm, Sweden.
PLoS One ; 18(8): e0290464, 2023.
Article em En | MEDLINE | ID: mdl-37616319
ABSTRACT

BACKGROUND:

Antimicrobial Resistance (AMR) is a global problem with large health and economic consequences. Current gaps in quantitative data are a major limitation for creating models intended to simulate the drivers of AMR. As an intermediate step, expert knowledge and opinion could be utilized to fill gaps in knowledge for areas of the system where quantitative data does not yet exist or are hard to quantify. Therefore, the objective of this study was to identify quantifiable data about the current state of the factors that drive AMR and the strengths and directions of relationships between the factors from statements made by a group of experts from the One Health system that drives AMR development and transmission in a European context.

METHODS:

This study builds upon previous work that developed a causal loop diagram of AMR using input from two workshops conducted in 2019 in Sweden with experts within the European food system context. A secondary analysis of the workshop transcripts was conducted to identify semi-quantitative data to parameterize drivers in a model of AMR. MAIN

FINDINGS:

Participants spoke about AMR by combining their personal experiences with professional expertise within their fields. The analysis of participants' statements provided semi-quantitative data that can help inform a future of AMR emergence and transmission based on a causal loop diagram of AMR in a Swedish One Health system context.

CONCLUSION:

Using transcripts of a workshop including participants with diverse expertise across the system that drives AMR, we gained invaluable insight into the past, current, and potential future states of the major drivers of AMR, particularly where quantitative data are lacking.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Prova Pericial / Antibacterianos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Canadá

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Prova Pericial / Antibacterianos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Canadá