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

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 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

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

Reduction in antimicrobial use and resistance to salmonella, campylobacter, and escherichia coli in broiler chickens, Canada, 2013–2019

Antimicrobial use contributes to the global rise of antimicrobial resistance (AMR). In 2014, the poultry industry in Canada initiated its Antimicrobial Use Reduction Strategy to mitigate AMR in the poultry sector. We monitored trends in antimicrobial use and AMR of foodborne bacteria (Salmonella, Escherichia coli, and Campylobacter) in broiler chickens during 2013 and 2019. We quantified the effect of antimicrobial use and management factors on AMR by using LASSO regression and generalized mixed-effect models. AMR in broiler chickens declined by 6%-38% after the decrease in prophylactic antimicrobial use. However, the withdrawal of individual compounds, such as cephalosporins and fluoroquinolones, prompted an increase in use of and resistance levels for other drug classes, such as aminoglycosides. Canada's experience with antimicrobial use reduction illustrates the potential for progressive transitions from conventional antimicrobial-dependent broiler production to more sustainable production with respect to antimicrobial use.ISSN:1080-605

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