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科学证据是否足够?利用专家意见填补抗菌药物耐药性研究中数据的空白。

Is scientific evidence enough? Using expert opinion to fill gaps in data in antimicrobial resistance research.

机构信息

School of Public Health Sciences, University of Waterloo, Waterloo, Ontario, Canada.

Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada.

出版信息

PLoS One. 2023 Aug 24;18(8):e0290464. doi: 10.1371/journal.pone.0290464. eCollection 2023.

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.

摘要

背景

抗菌药物耐药性(AMR)是一个具有重大健康和经济影响的全球性问题。目前,定量数据的差距是创建旨在模拟 AMR 驱动因素的模型的主要限制。作为中间步骤,可以利用专家知识和意见来填补系统中定量数据尚不存在或难以量化的领域的知识空白。因此,本研究的目的是确定与推动 AMR 的因素的当前状态有关的可量化数据,以及来自欧洲背景下推动 AMR 发展和传播的 One Health 系统的一组专家的陈述中关于这些因素之间关系的强弱和方向。

方法

本研究是基于之前的工作,该工作使用 2019 年在瑞典举行的两次研讨会中来自欧洲食品系统背景下的专家的输入,开发了 AMR 的因果关系图。对研讨会记录的二次分析旨在确定参数化驱动因素的半定量数据,以建立 AMR 模型。

主要发现

参与者通过将个人经验与专业知识相结合来讨论 AMR。对参与者陈述的分析提供了半定量数据,可以帮助根据瑞典 One Health 系统背景下的 AMR 因果关系图,了解 AMR 出现和传播的未来。

结论

通过使用包括整个 AMR 驱动系统在内的具有不同专业知识的参与者的研讨会记录,我们深入了解了 AMR 的主要驱动因素的过去、现在和潜在未来状态,特别是在缺乏定量数据的情况下。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bc6/10449168/c2ffc853bf70/pone.0290464.g001.jpg

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