Monitoring of Farm-Level Antimicrobial Use to Guide Stewardship: Overview of Existing Systems and Analysis of Key Components and Processes

The acknowledgment of antimicrobial resistance (AMR) as a major health challenge in humans, animals and plants, has led to increased efforts to reduce antimicrobial use (AMU). To better understand factors influencing AMR and implement and evaluate stewardship measures for reducing AMU, it is important to have sufficiently detailed information on the quantity of AMU, preferably at the level of the user (farmer, veterinarian) and/or prescriber or provider (veterinarian, feed mill). Recently, several countries have established or are developing systems for monitoring AMU in animals. The aim of this publication is to provide an overview of known systems for monitoring AMU at farm-level, with a descriptive analysis of their key components and processes. As of March 2020, 38 active farm-level AMU monitoring systems from 16 countries were identified. These systems differ in many ways, including which data are collected, the type of analyses conducted and their respective output. At the same time, they share key components (data collection, analysis, benchmarking, and reporting), resulting in similar challenges to be faced with similar decisions to be made. Suggestions are provided with respect to the different components and important aspects of various data types and methods are discussed. This overview should provide support for establishing or working with such a system and could lead to a better implementation of stewardship actions and a more uniform communication about and understanding of AMU data at farm-level. Harmonization of methods and processes could lead to an improved comparability of outcomes and less confusion when interpreting results across systems. However, it is important to note that the development of systems also depends on specific local needs, resources and aims

Governing Antimicrobial Resistance (AMR) in a Changing Climate: A Participatory Scenario Planning Approach Applied to Sweden in 2050

Background: Antimicrobial resistance (AMR) is a growing global crisis with long-term and unpredictable health, social and economic impacts, with which climate change is likely to interact. Understanding how to govern AMR amidst evolving climatic changes is critical. Scenario planning offers a suitable approach. By envisioning alternative futures, stakeholders more effectively can identify consequences, anticipate problems, and better determine how to intervene. This study explored future worlds and actions that may successfully address AMR in a changing climate in a high-income country, using Sweden as the case.Methods: We conducted online scenario-building workshops and interviews with eight experts who explored: (1) how promising interventions (taxation of antimicrobials at point of sale, and infection prevention measures) could each combat AMR in 2050 in Sweden given our changing climate; and (2) actions to take starting in 2030 to ensure success in 2050. Transcripts were thematically analyzed to produce a narrative of participant validated alternative futures.Results: Recognizing AMR to be a global problem requiring global solutions, participants looked beyond Sweden to construct three alternative futures: (1) “Tax Burn Out” revealed taxation of antimicrobials as a low-impact intervention that creates inequities and thus would fail to address AMR without other interventions, such as infection prevention measures. (2) “Addressing the Basics” identified infection prevention measures as highly impactful at containing AMR in 2050 because they would contribute to achieving the Sustainable Development Goals (SDGs), which would be essential to tackling inequities underpinning AMR and climate change, and help to stabilize climate-induced mass migration and conflicts; and (3) ”Siloed Nations” described a movement toward nationalism and protectionism that would derail the “Addressing the Basics” scenario, threatening health and wellbeing of all. Several urgent actions were identified to combat AMR long-term regardless which future un-folds, such as global collaboration, and a holistic approach where AMR and climate change are addressed as interlinked issues.Conclusion: Our participatory scenario planning approach enabled participants from different sectors to create shared future visions and identify urgent actions to take that hinge on global collaboration, addressing AMR and climate change together, and achieving the SDGs to combat AMR under a changing climate

Antimicrobial Use and Antimicrobial Resistance Indicators—Integration of Farm-Level Surveillance Data From Broiler Chickens and Turkeys in British Columbia, Canada

Using data from the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS), we aimed to describe trends in antimicrobial use (AMU) in broiler chickens and turkeys, to compare AMU across species, to compare with trends in antimicrobial resistance (AMR), and to assess the effects of various AMU/AMR units of measurement (metrics and indicators) on data integration. Data on AMU and AMR in enteric bacteria, collected from 2013 to 2017 from broiler chickens (n = 143 flocks) and turkeys (n = 145) were used. In broiler chickens, the total AMU in milligrams/population correction unit (mg/PCUBr) decreased by 6%, the number (n) of defined daily doses for animals using Canadian standards (nDDDvetCA) per 1,000 broiler chicken-days decreased by 12%, and nDDDvetCA/PCU decreased by 6%. In turkeys, the mg/PCUTk decreased by 1%, whereas the nDDDvetCA/1,000 turkey-days and the nDDDvetCA/PCU increased by 1 and 5%, respectively. The types of antimicrobial classes used in both species were similar. Using the frequency of flocks reporting use (i.e., number of flocks reporting use/number of flocks participating) as a measurement, the use of certain antimicrobials changed over time (e.g., Broilers, decreased cephalosporin use, virginiamycin use, emerging use of lincomycin-spectinomycin, and avilamycin; Turkeys: increased trimethoprim-sulfonamides and macrolide use). The trends in resistance to specific antimicrobials paralleled the frequency and quantity of use (e.g., ceftriaxone use decreased—ceftriaxone resistance decreased, and gentamicin use increased—gentamicin resistance increased) in some situations, but not others (decreased fluoroquinolone use—increased ciprofloxacin resistance). AMR data were summarized using the AMR indicator index (AMR Ix). The most notable AMR Ix trend was the decrease in ceftriaxone AMR Ix among Escherichia coli (0.19 to 0.07); indicative of the success of the poultry industry action to eliminate the preventive use of third generation cephalosporins. Other trends observed were the increase in ciprofloxacin AMR Ix among Campylobacter from 0.23 to 0.41 and gentamicin AMR Ix among E. coli from 0.11 to 0.22, suggestive of the persistence/emergence of resistance related to previous and current AMU not captured in our surveillance timeframe. These data highlight the necessity of multiple AMU and AMR indicators for monitoring the impact of stewardship activities and interventions

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

Integrating Whole-Genome Sequencing Data Into Quantitative Risk Assessment of Foodborne Antimicrobial Resistance: A Review of Opportunities and Challenges

Whole-genome sequencing (WGS) will soon replace traditional phenotypic methods for routine testing of foodborne antimicrobial resistance (AMR). WGS is expected to improve AMR surveillance by providing a greater understanding of the transmission of resistant bacteria and AMR genes throughout the food chain, and therefore support risk assessment activities. At this stage, it is unclear how WGS data can be integrated into quantitative microbial risk assessment (QMRA) models and whether their integration will impact final risk estimates or the assessment of risk mitigation measures. This review explores opportunities and challenges of integrating WGS data into QMRA models that follow the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR. We describe how WGS offers an opportunity to enhance the next-generation of foodborne AMR QMRA modeling. Instead of considering all hazard strains as equally likely to cause disease, WGS data can improve hazard identification by focusing on those strains of highest public health relevance. WGS results can be used to stratify hazards into strains with similar genetic profiles that are expected to behave similarly, e.g., in terms of growth, survival, virulence or response to antimicrobial treatment. The QMRA input distributions can be tailored to each strain accordingly, making it possible to capture the variability in the strains of interest while decreasing the uncertainty in the model. WGS also allows for a more meaningful approach to explore genetic similarity among bacterial populations found at successive stages of the food chain, improving the estimation of the probability and magnitude of exposure to AMR hazards at point of consumption. WGS therefore has the potential to substantially improve the utility of foodborne AMR QMRA models. However, some degree of uncertainty remains in relation to the thresholds of genetic similarity to be used, as well as the degree of correlation between genotypic and phenotypic profiles. The latter could be improved using a functional approach based on prediction of microbial behavior from a combination of ‘omics’ techniques (e.g., transcriptomics, proteomics and metabolomics). We strongly recommend that methodologies to incorporate WGS data in risk assessment be included in any future revision of the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR

Factors impacting antimicrobial resistance in the South East Asian food system and potential places to intervene: A participatory, one health study

BackgroundWith AMU projected to increase, South East Asia (SEA) is at high risk of experiencing disproportionate health, social, and economic burdens due to antimicrobial resistance (AMR). Our objective was to identify factors influencing AMR in SEA’s food system and places for intervention by integrating the perspectives of experts from the region to inform policy and management decisions.Materials and methodsWe conducted two 6.5 h workshops and two 90-min interviews involving 18 AMR and other disciplinary experts from human, animal, and environment sectors who brainstormed the factors influencing AMR and identified leverage points (places) for intervention. Transcripts and workshop materials were coded for factors and their connections and transcribed into a causal loop diagram (CLD). Thematic analysis described AMR dynamics in SEA’s food system and leverage points for intervention. The CLD and themes were confirmed via participant feedback.ResultsParticipants constructed a CLD of AMR in the SEA food system that contained 98 factors interlinked by 362 connections. CLD factors reflected eight sub-areas of the SEA food system (e.g., government). Seven themes [e.g., antimicrobial and pesticide use and AMR spread (n = 40 quotes)], six “overarching factors” that impact the entire AMR system [e.g., the drive to survive (n = 12 quotes)], and 10 places for intervention that target CLD factors (n = 5) and overarching factors (n = 2) emerged from workshop discussions.ConclusionThe participant derived CLD of factors influencing AMR in the SEA food system demonstrates that AMR is a product of numerous interlinked actions taken across the One Health spectrum and that finding solutions is no simple task. Developing the model enabled the identification of potentially promising leverage points across human, animal, and environment sectors that, if comprehensively targeted using multi-pronged interventions, could evoke system wide changes that mitigate AMR. Even targeting some leverage points for intervention, such as increasing investments in research and capacity building, and setting and enforcing regulations to control antimicrobial supply, demand, and use could, in turn, shift mindsets that lead to changes in more difficult to alter leverage points, such as redefining the profit-driven intent that drives system behavior in ways that transform AMU and sustainably mitigate AMR

Monitoring of Farm-Level Antimicrobial Use to Guide Stewardship: Overview of Existing Systems and Analysis of Key Components and Processes

peer-reviewedThe acknowledgment of antimicrobial resistance (AMR) as a major health challenge in humans, animals and plants, has led to increased efforts to reduce antimicrobial use (AMU). To better understand factors influencing AMR and implement and evaluate stewardship measures for reducing AMU, it is important to have sufficiently detailed information on the quantity of AMU, preferably at the level of the user (farmer, veterinarian) and/or prescriber or provider (veterinarian, feed mill). Recently, several countries have established or are developing systems for monitoring AMU in animals. The aim of this publication is to provide an overview of known systems for monitoring AMU at farm-level, with a descriptive analysis of their key components and processes. As of March 2020, 38 active farm-level AMU monitoring systems from 16 countries were identified. These systems differ in many ways, including which data are collected, the type of analyses conducted and their respective output. At the same time, they share key components (data collection, analysis, benchmarking, and reporting), resulting in similar challenges to be faced with similar decisions to be made. Suggestions are provided with respect to the different components and important aspects of various data types and methods are discussed. This overview should provide support for establishing or working with such a system and could lead to a better implementation of stewardship actions and a more uniform communication about and understanding of AMU data at farm-level. Harmonization of methods and processes could lead to an improved comparability of outcomes and less confusion when interpreting results across systems. However, it is important to note that the development of systems also depends on specific local needs, resources and aims

WHO global research priorities for antimicrobial resistance in human health

The WHO research agenda for antimicrobial resistance (AMR) in human health has identified 40 research priorities to be addressed by the year 2030. These priorities focus on bacterial and fungal pathogens of crucial importance in addressing AMR, including drug-resistant pathogens causing tuberculosis. These research priorities encompass the entire people-centred journey, covering prevention, diagnosis, and treatment of antimicrobial-resistant infections, in addition to addressing the overarching knowledge gaps in AMR epidemiology, burden and drivers, policies and regulations, and awareness and education. The research priorities were identified through a multistage process, starting with a comprehensive scoping review of knowledge gaps, with expert inputs gathered through a survey and open call. The priority setting involved a rigorous modified Child Health and Nutrition Research Initiative approach, ensuring global representation and applicability of the findings. The ultimate goal of this research agenda is to encourage research and investment in the generation of evidence to better understand AMR dynamics and facilitate policy translation for reducing the burden and consequences of AMR

Editorial: Antimicrobial Usage in Companion and Food Animals: Methods, Surveys and Relationships With Antimicrobial Resistance in Animals and Humans, Volume II

Cognitive stimulation therapy (CST) is a manualized psychosocial group intervention for people with mild to moderate dementia. Because of its broad scientific evidence and cost effectiveness, CST is now used globally. To ensure replicability and quality standards of the intervention in other cultures, Aguirre et al. (2014) developed guidelines for cultural adaptation of CST based on the formative method for adapting psychotherapy (FMAP). Following this community-based approach, we adapted and translated the English CST manual into German, including multiprofessional focus groups, two adaptation cycles, and two pilot CST groups ( ; n = 13) in different settings representative of the German healthcare system. Effectiveness in both groups was assessed by pre-post comparison of standard scales on cognition, depression, quality of life, and self-efficacy. We were able to replicate previous findings of improved cognition as measured by the ADAS-Cog, with effect sizes in the same range as in previous randomized controlled trials. Additionally, self-efficacy increased in post-test compared to the pre-test, indicating that CST might trigger cognition through positive, self-rewarding activation

Identifying non-traditional stakeholders with whom to engage, when mitigating antimicrobial resistance in foodborne pathogens (Canada)

Abstract Objective Antimicrobial resistance (AMR) is a critical public health issue that involves interrelationships between people, animals, and the environment. Traditionally, interdisciplinary efforts to mitigate AMR in the food chain have involved public health, human and veterinary medicine, and agriculture stakeholders. Our objective was to identify a more diverse range of stakeholders, beyond those traditionally engaged in AMR mitigation efforts, via diagramming both proximal and distal factors impacting, or impacted by, use and resistance along the Canadian food chain. Results We identified multiple stakeholders that are not traditionally engaged by public health when working to mitigate AMR in the food chain, including those working broadly in the area of food (e.g., nutrition, food security, international market economists) and health (e.g., health communication, program evaluation), as well as in domains as diverse as law, politics, demography, education, and social innovation. These findings can help researchers and policymakers who work on issues related to AMR in the food chain to move beyond engaging the ‘traditional’ agri-food stakeholders (e.g., veterinarians, farmers), to also engage those from the wider domains identified here, as potential stakeholders in their AMR mitigation efforts