With the rapid growth of the aquaculture production since the 1980s, there has been a concomitant increase in disease outbreaks. The injudicious and/or incorrect use of antimicrobial agents against diseases of farmed aquatic species poses a considerable threat to the development and growth of a successful and sustainable aquaculture industry. An increase in antimicrobial resistance (AMR) is an important consequence, resulting to the difficulty in treating common bacterial diseases in populations of aquatic organisms, combined with the presence of antibiotic residues in food fish and their products, leading to import refusals and negative impacts on international trade. To reduce the frequency of AMR, good aquaculture and effective biosecurity practices should include the prudent and responsible use of antibiotics and also consider the use of alternatives to antibiotics, in addition to disease prevention management. This article reviews the literature discussing the scope of the problem pertaining to antibiotic use, the emergence of AMR in aquaculture and to consider and discuss viable alternatives (e.g., vaccination, bacteriophages, quorum quenching, probiotics and prebiotics, chicken egg yolk antibody and medicinal plant derivative). We also discuss lessons learnt, from specific case studies such as the vaccination of farmed salmon in Norway and the use of ‘specific pathogen‐free’ seed—as primary and essential part of a biosecurity strategy.

Since the establishment of a Global Action Plan (GAP) on Antimicrobial Resistance (AMR) (68th World Health Assembly, Geneva, Switzerland, 2015), most members of the World Health Organisation (WHO) have developed and implemented a National Action Plan (NAP) based on a “One Health” approach to AMR. Aquaculture, significant among the food producing sectors, has often been overlooked in AMR governance. We did a systematic review of 95 country NAPs and assessed the inclusion of aquaculture. We also reviewed the scientific literature from 1996 until April 2021 to retrieve data characterising AMR in aquaculture during the last 25 years. In our analysis, 37% of countries did not mention an aquaculture component within their AMR NAP. The South‐East Asia Region had the highest implementation rate of AMR‐aquaculture programmes. Our literature review indicated that most AMR‐aquaculture related studies have taken place in the People's Republic of China, followed by the United States of America and India. Beta‐lactamases, tetracyclines, sulfonamides, macrolides, and fluoroquinolones were the most represented classes of antibiotics, with Vibrio spp. and Aeromonas spp. as the most investigated antimicrobial‐resistant bacteria. This review highlighted the gaps in AMR‐aquaculture governance and the progress made across WHO members. Countries are encouraged to (i) fulfil their commitments by developing and/or fully implementing the AMR NAP, (ii) further engage in the research, monitoring, and surveillance of antimicrobial usage and AMR within the aquaculture sector, and (iii) collaborate at national and international level for a concerted “One Health” approach.

Introduction: Governments create policies to address societal needs and then assess their effectiveness through policy metrics. The UK Rare Diseases Framework and its England Rare Diseases Action Plans aim to improve the lives of people with lived experience of rare diseases and their carers. Reaching these goals requires more effective engagement with those least likely to interact with NHS services. This paper outlines a protocol to identify relevant high-level policy metrics while engaging underserved and underrepresented groups. Methods and Analysis: A long list of candidate metrics for the 36 Actions linked to the four Priority Areas of the Framework was compiled from government logic models. The list was discussed in three workshops, and irrelevant, ambiguous, or time-irrelevant metrics were removed. Additional metrics were identified through an evidence review and expert opinion. In the first round of a two-round eDelphi study, shortlisted metrics will be grouped into the four Priority Areas: Faster Diagnosis, Increased Healthcare Professional Awareness, Better Care Coordination, and Improved Access to Specialist Care, Treatment, and drugs. An eDelphi panel of 50 people living with rare disease or their carers, as well as 50 professional stakeholders, will rate each metric on a 1-9 scale. The sample size allows for 20% attrition. Consensus for inclusion or exclusion will be based on 70% agreement (7-9 for ‘very valuable’, 1-3 for ‘not valuable’), with fewer than 15% rating the metric at the opposite end of the scale. Metrics will be included or excluded if consensus is reached in both groups; otherwise, they will remain under consideration in Round 2. In Round 1, eDelphi participants may propose additional metrics, which will be included in Round 2. After two rounds, a final set of policy metrics will be selected. Any discrepancies in Round 2 ratings will be explored through further research. Ethics and Dissemination: The Coventry University Group Research Ethics Committee has approved the study (P183377). The results will be disseminated to people with lived experience of rare disease and professional stakeholders through conferences, events, and newsletters and submitted to a peer-reviewed journal. If adopted, the identified metrics will inform decision-making on rare disease policies in England and beyond. Registration Details: ISRCTN41639707 ARTICLE SUMMARY: Strengths and limitations of this study: The study’s strength lies in its equal representation of individuals with lived experience of rare diseases and professional stakeholders, ensuring contextually relevant and widely accepted policy metrics. Efforts are made to include underserved groups, ensuring the meaningful representation of underrepresented sub-populations. The findings will primarily apply to the England Rare Diseases Action Plans, limiting their generalisability to other countries or healthcare systems. The heterogeneity of the study population may pose challenges in reaching consensus, potentially impacting the robustness of the agreed-policy metrics. Despite targeted recruitment efforts, challenges in including underserved groups may result in a less representative sample, affecting the study’s generalisability.