摘要
出身背景
抗生素耐药性的出现和传播越来越威胁到人类、动物和环境健康。抗生素治疗的不当使用通常会造成这种威胁，但也越来越明显的是，多种相互关联的环境因素可能会发挥重要作用。因此，需要一种“同一健康”的方法来全面理解抗生素耐药性的环境层面，并为基于科学的决策和行动提供信息。该问题的广泛性和多学科性提出了几个悬而未决的问题，这些问题借鉴了各种各样的研究。
客观的
本研究旨在收集和编目环境因素对户外环境中抗生素耐药性决定因素的丰度或检测的潜在影响的证据，即抗生素耐药性细菌和携带抗生素耐药性基因的移动遗传元件，以及自然或人为原因对当地环境条件造成的影响。
方法
在这里，我们描述了系统证据图的方案，以解决这一问题，该方案将按照最佳实践指南执行。我们将使用以下电子数据库搜索1990年至今的文献：MEDLINE、Embase、Web of Science Core Collection以及灰色文献。我们将收录以英语发表的全文科学文章。审阅者将成对工作，首先筛选标题、摘要和关键字，然后筛选全文文档。数据提取将遵循专门设计的代码手册。偏差风险评估不会作为本SEM的一部分进行。
我们将结合表格、图表和其他合适的可视化技术，编制一个数据库，i）研究与环境中抗生素耐药性流行相关的因素，ii）绘制文献中的分布、网络、交叉学科、影响和趋势。
Abstract
Background
Human, animal, and environmental health are increasingly threatened by the emergence and spread of antibiotic resistance. Inappropriate use of antibiotic treatments commonly contributes to this threat, but it is also becoming apparent that multiple, interconnected environmental factors can play a significant role. Thus, a One Health approach is required for a comprehensive understanding of the environmental dimensions of antibiotic resistance and inform science-based decisions and actions. The broad and multidisciplinary nature of the problem poses several open questions drawing upon a wide heterogeneous range of studies.

Objective
This study seeks to collect and catalogue the evidence of the potential effects of environmental factors on the abundance or detection of antibiotic resistance determinants in the outdoor environment, i.e., antibiotic resistant bacteria and mobile genetic elements carrying antibiotic resistance genes, and the effect on those caused by local environmental conditions of either natural or anthropogenic origin.

Methods
Here, we describe the protocol for a systematic evidence map to address this, which will be performed in adherence to best practice guidelines. We will search the literature from 1990 to present, using the following electronic databases: MEDLINE, Embase, and the Web of Science Core Collection as well as the grey literature. We shall include full-text, scientific articles published in English. Reviewers will work in pairs to screen title, abstract and keywords first and then full-text documents. Data extraction will adhere to a code book purposely designed. Risk of bias assessment will not be conducted as part of this SEM.

We will combine tables, graphs, and other suitable visualisation techniques to compile a database i) of studies investigating the factors associated with the prevalence of antibiotic resistance in the environment and ii) map the distribution, network, cross-disciplinarity, impact and trends in the literature.

https://www.sciencedirect.com/science/article/pii/S0160412022006341