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对抗日益严重的全球健康危机的抗菌药物耐药性系统映射。

System Mapping of Antimicrobial Resistance to Combat a Rising Global Health Crisis.

机构信息

National Food Institute, Technical University of Denmark, Lyngby, Denmark.

出版信息

Front Public Health. 2022 Jun 17;10:816943. doi: 10.3389/fpubh.2022.816943. eCollection 2022.

Abstract

Antimicrobial resistance (AMR) decreases the effectiveness of antimicrobials to treat bacterial infections in humans and animals. The increased occurrence of AMR in bacterial population in humans, animals, and the environment requires the measures to combat a rising global health crisis. The aim of this research was to present current knowledge on AMR in a system map and to identify potential explanations of former identified variables significantly associated with AMR. This study applies a systems thinking approach and uses feedback loops to visualize the interconnections between human, animal, and environmental components in a circular AMR system map model. First, a literature review focusing on AMR and socioeconomic factors, wicked problem, and system change was carried out, which was then processed in a system map to conceptualize the present core challenges of AMR feedback loops. Second, to investigate possible underlying values of the society and those that influence humans' behavior in the present AMR system, an iceberg model was established. Third, leverage points were assessed to estimate which kinds of interventions would have the greatest effect to mitigate AMR in the system. The present AMR system map implies the potential to identify and visualize important risk factors that are direct or indirect drivers of AMR. Our results show that the tool of system mapping, which interconnects animals, humans, and environment in one model, can approach AMR holistically and be used to assess potential powerful entry points for system wide interventions. This study shows that system maps are beneficial as a model to predict the relative effect of different interventions and adapt to rapidly changing environments in a complex world. Systems thinking is considered as a complementing approach to the statistical thinking, and further research is needed to evaluate the use of such tools for the development and monitoring of interventions.

摘要

抗微生物药物耐药性(AMR)降低了抗菌药物治疗人类和动物细菌感染的有效性。人类、动物和环境中细菌种群中 AMR 的发生率增加,需要采取措施应对日益严重的全球健康危机。本研究旨在通过系统图呈现 AMR 的现有知识,并确定与 AMR 显著相关的先前确定变量的潜在解释。本研究应用系统思维方法,并使用反馈回路来可视化 AMR 系统图模型中人类、动物和环境组件之间的相互关系。首先,进行了一项重点关注 AMR 和社会经济因素、棘手问题和系统变革的文献综述,然后将其在系统图中进行处理,以概念化 AMR 反馈回路的当前核心挑战。其次,为了研究社会的潜在价值观以及这些价值观如何影响人类在当前 AMR 系统中的行为,建立了冰山模型。第三,评估了杠杆点,以估计哪种干预措施将对减轻系统中的 AMR 产生最大影响。当前的 AMR 系统图意味着有可能识别和可视化直接或间接驱动 AMR 的重要风险因素。我们的研究结果表明,系统图可以将动物、人类和环境相互连接,从而全面地研究 AMR,并评估针对系统范围干预的潜在有力切入点。本研究表明,系统图作为一种模型具有优势,可预测不同干预措施的相对效果,并适应复杂世界中快速变化的环境。系统思维被认为是对统计思维的补充方法,需要进一步研究以评估这些工具在干预措施的制定和监测中的使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c1e/9249020/507eca41b135/fpubh-10-816943-g0001.jpg

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