Factors influencing antimicrobial resistance in the European food system and potential leverage points for intervention: A participatory, One Health study

Introduction Antimicrobial resistance (AMR) is a global crisis that evolves from a complex system of factors. Understanding what factors interact is key to finding solutions. Our objective was to identify the factors influencing AMR in the European food system and places to intervene. Materials and methods We conducted two workshops involving participants with diverse perspectives to identify the factors influencing AMR and leverage points (places) to target interventions. Transcripts were open coded for factors and connections, then transcribed into Vensim 8.0.4 to develop a causal loop diagram (CLD) and compute the number of feedback loops. Thematic analysis followed to describe AMR dynamics in Europe’s food system and places for intervention. The CLD and themes were confirmed via participant feedback. Results Seventeen participants representing human, animal and agricultural sectors identified 91 CLD factors and 331 connections. Seven themes (e.g., social and economic conditions) describing AMR dynamics in Europe’s food system, five ‘overarching factors’ that impact the entire CLD system (e.g., leadership) and fourteen places for intervention (e.g., consumer demand) emerged from workshop discussions. Most leverage points fell on highly networked feedback loops suggesting that intervening at these places may create unpredictable consequences. Conclusions Our study produced a CLD of factors influencing AMR in Europe’s food system that implicates sectors across the One Health spectrum. The high connectivity between the CLD factors described by participants and our finding that factors are connected with many feedback mechanisms underscores the complexity of the AMR problem and the challenge with finding long-term solutions. Identifying factors and feedbacks helped identify relevant leverage points in the system. Some actions, such as government’s setting AMU standards may be easier to implement. These actions in turn can support multi-pronged actions that can help redefine the vision, values and goals of the system to sustainably tackle AMR

Mapping out a One Health model of antimicrobial resistance in the context of the Swedish food system: A literature scan

Background: Antimicrobial resistance (AMR) causes worsening health, environmental, and financial burdens. Modeling complex issues such as AMR is important, however, how well such models and data cover the broader One Health system is unknown. Our study aimed to identify models of AMR across the One Health system (objective 1), and data to parameterize such models (objective 2) to inform a future model of the AMR in the Swedish One Health system. Methods: Based on an expert-derived qualitative description of the system, an extensive literature scan was performed to identify models and data from peer-reviewed and grey literature sources. Models and data were extracted, categorized in an Excel database, and visually represented on the existing qualitative model to illustrate coverage. Results: Articles described 106 models in various parts of the One Health system; 54 were AMR specific. Few multi-level, multi-sector models, and models within the animal and environmental sectors, were identified. We identified 414 articles containing data to parameterize the models. Data gaps included the environment and broad, ill-defined, or abstract ideas (e.g., human behaviour). Conclusions: No models addressed the entire system, and many data gaps were found. Existing models could be integrated into a mixed-methods model in the interim.</p

Exploring the factors that contribute to the successful implementation of antimicrobial resistance interventions: a comparison of high-income and low-middle-income countries

Introduction Antimicrobial resistance (AMR) is a challenge to modern medicine. Interventions have been applied worldwide to tackle AMR, but these actions are often not reported to peers or published, leading to important knowledge gaps about what actions are being taken. Understanding factors that influence the implementation of AMR interventions and what factors are relevant in low-middle-income countries (LMICs) and high-income countries (HICs) were the key objectives of this exploratory study, with the aim to identifying which priorities these contexts need. Methods A questionnaire was used to explore context, characteristics, and success factors or obstacles to intervention success based on participant input. The context was analyzed using the AMR-Intervene framework, and success factors and obstacles to intervention success were identified using thematic analysis. Results Of the 77 interventions, 57 were implemented in HICs and 17 in LMICs. Interventions took place in the animal sector, followed by the human sector. Public organizations were mainly responsible for implementation and funding. Nine themes and 32 sub-themes emerged as important for intervention success. The themes most frequently reported were ‘behavior’, ‘capacity and resources’, ‘planning’, and ‘information’. Five sub-themes were key in all contexts (‘collaboration and coordination’, ‘implementation’, ‘assessment’, ‘governance’, and ‘awareness’), two were key in LMICs (‘funding and finances’ and ‘surveillance, antimicrobial susceptibility testing and preventive screening’), and five were key in HICs (‘mandatory’, ‘multiple profiles’, ‘personnel’, ‘management’, and ‘design’). Conclusion LMIC sub-themes showed that funding and surveillance were still key issues for interventions, while important HIC sub-themes were more specific and detailed, including mandatory enforcement, multiple profiles, and personnel needed for good management and good design. While behavior is often underrated when implementing AMR interventions, capacity and resources are usually considered, and LMICs can benefit from sub-themes captured in HICs if tailored to their contexts. The factors identified can improve the design, planning, implementation, and evaluation of interventions.</p

Using a fuzzy cognitive map to assess interventions to reduce antimicrobial resistance in a Swedish One Health system context under potential climate change conditions

Abstract Introduction: Antimicrobial resistance (AMR) is a growing One Health crisis that can be impacted by other challenges of sustainable development, such as climate change, but few interventions have been assessed with a systems-wide lens. The objectives of this study were to use a previously defined fuzzy cognitive map (FCM) of the Swedish One Health system to: 1) identify areas in the system to target interventions; and 2) test the potential ability and viability of interventions to reduce AMR under a changing climate. Methods: The FCM, based on participatory modelling workshops and literature scan, was used to assess the sustainability of eight interventions under potential climate change conditions. Network metrics were calculated to describe the system structure and identify highly impactful nodes. Results: The network metrics identified high-leverage nodes including alternative productions systems and good farming practices. None of the scenarios evaluated were able to adequately reduce AMR within the system. Conclusions: Overall, fuzzy cognitive mapping provides an innovative way to analyse the AMR system, identify high-leverage interventions, and examine potential impact of interventions using a broader systems lens.</p

Studying Factors Affecting Success of Antimicrobial Resistance Interventions through the Lens of Experience: A Thematic Analysis

Antimicrobial resistance (AMR) affects the environment, and animal and human health. Institutions worldwide have applied various measures, some of which have reduced antimicrobial use and AMR. However, little is known about factors influencing the success of AMR interventions. To address this gap, we engaged health professionals, designers, and implementers of AMR interventions in an exploratory study to learn about their experience and factors that challenged or facilitated interventions and the context in which interventions were implemented. Based on participant input, our thematic analysis identified behaviour; institutional governance and management; and sharing and enhancing information as key factors influencing success. Important sub-themes included: correct behaviour reinforcement, financial resources, training, assessment, and awareness of AMR. Overall, interventions were located in high-income countries, the human sector, and were publicly funded and implemented. In these contexts, behaviour patterns strongly influenced success, yet are often underrated or overlooked when designing AMR interventions. Improving our understanding of what contributes to successful interventions would allow for better designs of policies that are tailored to specific contexts. Exploratory approaches can provide encouraging results in complex challenges, as made evident in our study. Remaining challenges include more engagement in this type of study by professionals and characterisation of themes that influence intervention outcomes by context

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

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

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

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.</p

Scope and applicability of social–ecological resilience to antimicrobial resistance

Social–ecological systems conceptualise how social human systems and ecological natural systems are intertwined. In this Personal View, we define the scope and applicability of social–ecological resilience to antimicrobial resistance. Resilience to antimicrobial resistance corresponds to the capacity to maintain the societal benefits of antimicrobial use and One Health systems’ performance in the face of the evolutionary behaviour of microorganisms in response to antimicrobial use. Social-ecological resilience provides an appropriate framework to make sense of the disruptive impacts resulting from the emergence and spread of antimicrobial resistance; capture the diversity of strategies needed to tackle antimicrobial resistance and to live with it; understand the conditions that underpin the success or failure of interventions; and appreciate the need for adaptive and coevolutionary governance. Overall, resilience thinking is essential to improve understanding of how human societies dynamically can cope with, adapt, and transform to the growing global challenge of antimicrobial resistance

Characterizing social-ecological context and success factors of antimicrobial resistance interventions across the One Health spectrum: analysis of 42 interventions targeting <i>E. coli</i>

Background: Antimicrobial resistance (AMR) is among the most pressing One Health issues. While interventions and policies with various targets and goals have been implemented, evidence about factors underpinning success and failure of interventions in different sectors is lacking. The objective of this study is to identify characteristics of AMR interventions that increase their capacity to impact AMR. This study focuses on AMR interventions targeting E. coli.Methods: We used the AMR-Intervene framework to extract descriptions of the social and ecological systems of interventions to determine factors contributing to their success.Results: We identified 52 scientific publications referring to 42 unique E. coli AMR interventions. We mainly identified interventions implemented in high-income countries (36/42), at the national level (16/42), targeting primarily one sector of society (37/42) that was mainly the human sector (25/42). Interventions were primarily funded by governments (38/42). Most intervention targeted a low leverage point in the AMR system, (36/42), and aimed to change the epidemiology of AMR (14/42). Among all included publications, 55% (29/52) described at least one success factor or obstacle (29/52) and 19% (10/52) identified at least one success factor and one obstacle. Most reported success factors related to communication between the actors and stakeholders and the role of media, and stressed the importance of collaboration between disciplines and external partners. Described obstacles covered data quality, access to data and statistical analyses, and the validity of the results.Conclusions: Overall, we identified a lack of diversity regarding interventions. In addition, most published E. coli interventions were poorly described with limited evidence of the factors that contributed to the intervention success or failure. Design and reporting guidelines would help to improve reporting quality and provide a valuable tool for improving the science of AMR interventions.</p

Data_Sheet_1_Exploring the factors that contribute to the successful implementation of antimicrobial resistance interventions: a comparison of high-income and low-middle-income countries.docx

IntroductionAntimicrobial resistance (AMR) is a challenge to modern medicine. Interventions have been applied worldwide to tackle AMR, but these actions are often not reported to peers or published, leading to important knowledge gaps about what actions are being taken. Understanding factors that influence the implementation of AMR interventions and what factors are relevant in low-middle-income countries (LMICs) and high-income countries (HICs) were the key objectives of this exploratory study, with the aim to identifying which priorities these contexts need.MethodsA questionnaire was used to explore context, characteristics, and success factors or obstacles to intervention success based on participant input. The context was analyzed using the AMR-Intervene framework, and success factors and obstacles to intervention success were identified using thematic analysis.ResultsOf the 77 interventions, 57 were implemented in HICs and 17 in LMICs. Interventions took place in the animal sector, followed by the human sector. Public organizations were mainly responsible for implementation and funding. Nine themes and 32 sub-themes emerged as important for intervention success. The themes most frequently reported were ‘behavior’, ‘capacity and resources’, ‘planning’, and ‘information’. Five sub-themes were key in all contexts (‘collaboration and coordination’, ‘implementation’, ‘assessment’, ‘governance’, and ‘awareness’), two were key in LMICs (‘funding and finances’ and ‘surveillance, antimicrobial susceptibility testing and preventive screening’), and five were key in HICs (‘mandatory’, ‘multiple profiles’, ‘personnel’, ‘management’, and ‘design’).ConclusionLMIC sub-themes showed that funding and surveillance were still key issues for interventions, while important HIC sub-themes were more specific and detailed, including mandatory enforcement, multiple profiles, and personnel needed for good management and good design. While behavior is often underrated when implementing AMR interventions, capacity and resources are usually considered, and LMICs can benefit from sub-themes captured in HICs if tailored to their contexts. The factors identified can improve the design, planning, implementation, and evaluation of interventions.</p