Dataset Information

Antimicrobial Resistance: Its Surveillance, Impact, and Alternative Management Strategies in Dairy Animals.

ABSTRACT: Antimicrobial resistance (AMR), one among the most common priority areas identified by both national and international agencies, is mushrooming as a silent pandemic. The advancement in public health care through introduction of antibiotics against infectious agents is now being threatened by global development of multidrug-resistant strains. These strains are product of both continuous evolution and un-checked antimicrobial usage (AMU). Though antibiotic application in livestock has largely contributed toward health and productivity, it has also played significant role in evolution of resistant strains. Although, a significant emphasis has been given to AMR in humans, trends in animals, on other hand, are not much emphasized. Dairy farming involves surplus use of antibiotics as prophylactic and growth promoting agents. This non-therapeutic application of antibiotics, their dosage, and withdrawal period needs to be re-evaluated and rationally defined. A dairy animal also poses a serious risk of transmission of resistant strains to humans and environment. Outlining the scope of the problem is necessary for formulating and monitoring an active response to AMR. Effective and commendably connected surveillance programs at multidisciplinary level can contribute to better understand and minimize the emergence of resistance. Besides, it requires a renewed emphasis on investments into research for finding alternate, safe, cost effective, and innovative strategies, parallel to discovery of new antibiotics. Nevertheless, numerous direct or indirect novel approaches based on host-microbial interaction and molecular mechanisms of pathogens are also being developed and corroborated by researchers to combat the threat of resistance. This review places a concerted effort to club the current outline of AMU and AMR in dairy animals; ongoing global surveillance and monitoring programs; its impact at animal human interface; and strategies for combating resistance with an extensive overview on possible alternates to current day antibiotics that could be implemented in livestock sector.

SUBMITTER: Sharma C

PROVIDER: S-EPMC5766636 | biostudies-other | 2017

REPOSITORIES: biostudies-other

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Antimicrobial Resistance: Its Surveillance, Impact, and Alternative Management Strategies in Dairy Animals.

Sharma Chetan C Rokana Namita N Chandra Mudit M Singh Brij Pal BP Gulhane Rohini Devidas RD Gill Jatinder Paul Singh JPS Ray Pallab P Puniya Anil Kumar AK Panwar Harsh H

Frontiers in veterinary science 20180108

Antimicrobial resistance (AMR), one among the most common priority areas identified by both national and international agencies, is mushrooming as a silent pandemic. The advancement in public health care through introduction of antibiotics against infectious agents is now being threatened by global development of multidrug-resistant strains. These strains are product of both continuous evolution and un-checked antimicrobial usage (AMU). Though antibiotic application in livestock has largely cont ...[more]

PMID: 29359135

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Project description:Canada has implemented on-farm antimicrobial resistance (AMR) surveillance systems for food-producing animals under the Canadian Integrated Program for Antimicrobial Resistance (CIPARS); however, dairy cattle have not been included in that program yet. The objective of this manuscript was to describe the development and implementation of the Canadian Dairy Network for Antimicrobial Stewardship and Resistance (CaDNetASR). An Expert Panel (EP) of researchers was created to lead the development of the dairy surveillance system. The EP initiated a draft document outlining the essential elements of the surveillance framework. This document was then circulated to a Steering Committee (SC), which provided recommendations used by the EP to finalize the framework. CaDNetASR has the following components: (1) a herd-level antimicrobial use quantification system; (2) annually administered risk factor questionnaires; and (3) methods for herd-level detection of AMR in three sentinel enteric pathogens (generic Escherichia coli, Campylobacter spp., and Salmonella spp.) recovered from pooled fecal samples collected from calves, heifers, cows, and the manure pit. A total of 144 dairy farms were recruited in five Canadian provinces (British-Columbia, Alberta, Ontario, Québec, and Nova-Scotia), with the help of local herd veterinarians and regional field workers, and in September 2019, the surveillance system was launched. 97.1 and 94.4% of samples were positive for E. coli, 63.8, and 49.1% of samples were positive for Campylobacter spp., and 5.0 and 7.7% of samples were positive for Salmonella spp., in 2019 and 2020, respectively. E. coli was equally distributed among all sample types. However, it was more likely that Campylobacter spp. were recovered from heifer and cow samples. On the other hand, it was more common to isolate Salmonella spp. from the manure pit compared to samples from calves, heifers, or cows. CaDNetASR will continue sampling until 2022 after which time this system will be integrated into CIPARS. CaDNetASR will provide online access to farmers and veterinarians interested in visualizing benchmarking metrics regarding AMU practices and their relationship to AMR and animal health in dairy herds. This will provide an opportunity to enhance antimicrobial stewardship practices on dairy farms in Canada.

Project description:The aim of this study was to reduce antimicrobial use (AMU) on dairy farms that implemented evidence-based management strategies. The study not only examined whether these strategies led to a reduction in AMU in practice, but also examined the influence of the level of their implementation on AMU. For data analysis, practice software recordings of the farm veterinarians were used. The AMU data of 50 farms with prevention strategies applied (intervention group, IG) over 3 years (2017-2019) and of 74 farms without prevention strategies (control group, CG) over 2 years (2018-2019) were analyzed. Project participation was supported with 500 Swiss francs (~545 USD) per farmer per year. The AMU was compared between the IG and CG using the treatment incidence. In December 2017/January 2018, the farmers of the IG had chosen at least one of the proposed 17 prevention strategies from one of three sectors, i.e., udder health, uterine health and/or replacement calf health. The prevention strategies, were developed in a standard operating procedure protocol and were discussed in detail with the farmers before the implementation. Forty-eight farms chose at least one udder strategy, 10 farms at least one uterine strategy and 37 farms at least one calf strategy. By choosing an udder health strategy or a uterine health strategy, the corresponding systemically administered AMU could be significantly reduced (p < 0.04) in the IG compared with the CG. In addition, udder strategies that were well-implemented led to a significant reduction (p = 0.05) of intramammary "highest priority critically important antimicrobials (HPCIA)" (quinolones, cephalosporins 3rd and higher generation, macrolides and ketolides, glycopeptides, and polymyxins). The level of implementation was significantly lower in 2019 compared to 2018 (p < 0.05, Fisher's exact test). No significant reduction in AMU could be achieved for the calf sector. A reduction of AMU in dairy farms is possible by implementing evidence-based management-related prevention strategies. The level of implementation has only an influence on the consumption of HPCIA. The reduction of AMU in practice by means of evidence-based measures requires supportive human resources instead of financial support, because financial support for farmers seems not to motivate them sufficiently.

Project description:BackgroundRoutine microbiology results are a valuable source of antimicrobial resistance (AMR) surveillance data in low- and middle-income countries (LMICs) as well as in high-income countries. Different approaches and strategies are used to generate AMR surveillance data.ObjectivesWe aimed to review strategies for AMR surveillance using routine microbiology results in LMICs and to highlight areas that need support to generate high-quality AMR data.SourcesWe searched PubMed for papers that used routine microbiology to describe the epidemiology of AMR and drug-resistant infections in LMICs. We also included papers that, from our perspective, were critical in highlighting the biases and challenges or employed specific strategies to overcome these in reporting AMR surveillance in LMICs.ContentTopics covered included strategies of identifying AMR cases (including case-finding based on isolates from routine diagnostic specimens and case-based surveillance of clinical syndromes), of collecting data (including cohort, point-prevalence survey, and case-control), of sampling AMR cases (including lot quality assurance surveys), and of processing and analysing data for AMR surveillance in LMICs.ImplicationsThe various AMR surveillance strategies warrant a thorough understanding of their limitations and potential biases to ensure maximum utilization and interpretation of local routine microbiology data across time and space. For instance, surveillance using case-finding based on results from clinical diagnostic specimens is relatively easy to implement and sustain in LMIC settings, but the estimates of incidence and proportion of AMR is at risk of biases due to underuse of microbiology. Case-based surveillance of clinical syndromes generates informative statistics that can be translated to clinical practices but needs financial and technical support as well as locally tailored trainings to sustain. Innovative AMR surveillance strategies that can easily be implemented and sustained with minimal costs will be useful for improving AMR data availability and quality in LMICs.

Dataset Information

Antimicrobial Resistance: Its Surveillance, Impact, and Alternative Management Strategies in Dairy Animals.

Publications

Antimicrobial Resistance: Its Surveillance, Impact, and Alternative Management Strategies in Dairy Animals.

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