Evaluation of the use of antibiotic waste bins and medicine records to quantify antibiotic use on sheep, beef, and mixed species farms: A mixed methods study

Identifying veterinary surgeons' barriers to, and potential solutions for, improving antimicrobial stewardship among sheep farmers in Northern Ireland

Background

In order to improve antimicrobial stewardship (AMS), including changes in antimicrobial prescribing and use, an enhanced understanding is needed of the barriers that veterinary surgeons (vets) encounter to institute such change.

Methods

A qualitative approach, using grounded theory, was followed. Interviews and discussion groups, with vets and farm industry stakeholders in Northern Ireland (NI), were undertaken to identify and explore attitudes and behaviours surrounding AMS, with a particular emphasis on the barriers vets encountered and the context within which they were working.

Results

Seven inter-related themes associated with improving AMS among their sheep farming clients were identified. The first six addressed barriers were working under commercial and practical constraints, farmer behaviour, multiple medicine sources, poor prescribing practice, a perceived lack of incentive or facilitation to improve AMS and a perceived lack of action by regulators to challenge poor AMS. The seventh theme revealed suggestions vets considered that may improve AMS in NI, including greater state intervention in recording and regulating medicine sales.

Conclusions

Improving AMS will require vets and their client farmers to change behaviour. This will involve concerted effort over an extended period of time to enact and embed change. Veterinary surgeons believe that further action by the industry and state to develop centralised antimicrobial sales recording and by the state to enforce prescribing regulations will aid their efforts. However, critical to achieving this is the development of a sustainable and funded mechanism to create more meaningful farmer-vet consultation around flock health prior to every prescription to improve AMS and sheep welfare.

A qualitative survey approach to investigating beef and dairy veterinarians' needs in relation to technologies on farms

Globally, farmers are being increasingly encouraged to use technologies. Consequently, veterinarians often use farm data and technologies to provide farmers with advice. Yet very few studies have sought to understand veterinarians' perceptions of data and technologies on farms. The aim of this study was to understand veterinarians' experiences and opinions on data and technology on beef and dairy farms. An online qualitative survey was conducted with a convenience sample of 36 and 24 veterinarians from the United Kingdom and Ireland, respectively. The data were analysed using reflexive thematic analysis to generate four themes: (1) Improving veterinary advice through data; (2) Ensuring stock person skills are retained; (3) Longevity of technology; and (4) Solving social problems on farms. We show that technologies and data can make veterinarians feel more confident in the advice they give to farmers. However, the quality and quantity of data collected on cattle farms were highly variable. Furthermore, veterinarians were concerned that farmers can become over-reliant on technologies by not using their stockperson skills. As herd sizes increase, technologies can help to improve working conditions on farms with multiple employees of various skillsets. Veterinarians would like innovations that can help them to demonstrate their competence, influence farmers' behaviour, and ensure sustainability of the beef and dairy industries.

The need for One Health systems-thinking approaches to understand multiscale dissemination of antimicrobial resistance

Although the effects of antimicrobial resistance (AMR) are most obvious at clinical treatment failure, AMR evolution, transmission, and dispersal happen largely in environmental settings, for example within farms, waterways, livestock, and wildlife. We argue that systems-thinking, One Health approaches are crucial for tackling AMR, by understanding and predicting how anthropogenic activities interact within environmental subsystems, to drive AMR emergence and transmission. Innovative computational methods integrating big data streams (eg, from clinical, agricultural, and environmental monitoring) will accelerate our understanding of AMR, supporting decision making. There are challenges to accessing, integrating, synthesising, and interpreting such complex, multidimensional, heterogeneous datasets, including the lack of specific metrics to quantify anthropogenic AMR. Moreover, data confidentiality, geopolitical and cultural variation, surveillance gaps, and science funding cause biases, uncertainty, and gaps in AMR data and metadata. Combining systems-thinking with modelling will allow exploration, scaling-up, and extrapolation of existing data. This combination will provide vital understanding of the dynamic movement and transmission of AMR within and among environmental subsystems, and its effects across the greater system. Consequently, strategies for slowing down AMR dissemination can be modelled and compared for efficacy and cost-effectiveness.

Barriers to recording calf health data on dairy farms in Ontario

Establishing accurate illness and treatment rates in dairy calves is crucial, yet calf health records are often incomplete. Thus, the objective of this study was to investigate barriers for dairy farmers for recording calf illnesses and treatments on dairy farms in Ontario, Canada. An online survey was completed by a convenience sample of 88 Ontario dairy farms in 2022, with 34 questions regarding farm demographics, current practices surrounding record keeping and analysis, and factors that would improve recording compliance. Multivariable models were built to assess associations between explanatory variables and the following outcomes: likelihood of making management or treatment protocol changes based on records analysis, factors that would increase the use of electronic recording methods, and whether all calf illnesses and treatments are recorded. Pearson's chi-squared tests were also used to investigate associations between explanatory variables and whether the respondent agreed or disagreed with a proposed reason for why a calf illness or treatment would not be recorded on their farm. Producers had 3.45 times greater odds of recording all antimicrobial treatments if they used a computer software system compared with those that did not. With respect to anti-inflammatory treatments, producers had 3.11 times greater odds of recording these treatments if records were located in the calf barn than elsewhere. Nonfamily employees had 6.08 times greater odds of recording all supportive therapy treatments than farm owners. When calf health records were kept in the calf barn, respondents were less likely to report that illnesses were not recorded due to time constraints (5% vs. 36% if records were elsewhere) or because calf health records were not analyzed (10% vs. 34% if records were elsewhere). On farms that recorded calf treatments in a paper booklet, respondents were more likely to report that treatments were not recorded because calf health records were not analyzed (44% for paper records vs. 21% for other systems). The most commonly indicated factors that would increase recording of illness were recording with a mobile app (27% of respondents) and for the recording system to be easy to use (31% of respondents). Overall, these data indicate that recording may be improved by keeping calf health records in close proximity to the calves and using a recording method that allows for data analysis. An easy-to-use mobile app may also improve recording if it could be used in the calf barn, provide data analytics, and allow for time-efficient data entry.

Assessing antibiotic usage data capture accuracy on dairy farms in England and Wales

BACKGROUND

Accurate farm-level data on antibiotic usage (ABU) are needed for the surveillance of antibiotic resistance. Therefore, this study aimed to determine the accuracy of ABU data capture by dairy farmers in South West England and Wales.

METHODS

Through a cross-sectional survey of 48 dairy farmers, the accuracy of ABU recording was measured by farmers' assessment of the completeness and timeliness of ABU recording ('perceived accuracy') and the completeness and correctness of on-farm ABU records ('actual accuracy'). Completeness and correctness were compared for paper and software recording methods.

RESULTS

Perceived accuracy was higher than actual accuracy. Antibiotic names, withdrawal periods and dates that products were fit for human consumption were often incomplete or incorrect. More inaccuracies were seen with paper than software. In some software platforms, the date that milk would be fit for human consumption was frequently rounded down by half a day, increasing the risk of residue failures.

LIMITATION

The small number of on-farm records assessed limits the generalisability of the results.

CONCLUSIONS

Electronic recording of ABU should be encouraged. However, functionality needs improvement, alongside consultation with dairy farmers to increase awareness of inaccuracies.

A Scoping Review of Antimicrobial Usage and Antimicrobial Resistance in Beef Cow-Calf Herds in the United States and Canada

BACKGROUND

The magnitude and knowledge gaps regarding antimicrobial use (AMU) and antimicrobial resistance (AMR) have not been summarized for the North American cow-calf production sector, although estimates of AMU and AMR are essential to AMR risk analysis. The objectives of this scoping review were to map AMU and AMR in the beef cow-calf sector in Canada and the United States, summarize published AMU/AMR predictors, and identify research gaps.

METHODS

An electronic search was conducted of four bibliographic databases and Google Scholar, augmented by a hand-search of captured studies.

RESULTS

Twenty-three of three-hundred and forty-three publications screened advanced to data extraction. Of these, 10 were conducted in the USA and 13 in Canada. Thirteen studied AMR and twelve studied AMU, with two reporting both. Of twelve captured AMU studies, nine presented counts of herd AMU by antimicrobial class or specific antimicrobial. Antimicrobial resistance in Escherichia coli (E. coli) was reported in nine studies. Risk factors for AMU include herd size, vaccine use, and start date of calving season.

CONCLUSIONS

Overall, a small number of AMR studies were available for synthesis in primarily one population (cows) reporting E. coli AMR. Additional studies targeting reasons for AMU in calves, the impact of management procedures on AMU, potential environmental AMR sources, and AMR in respiratory pathogens and enteric organisms other than E. coli for pre-weaning calves are required to inform AMR risk mitigation strategies.

Antimicrobial usage in farm animal practices in the UK: A mixed-methods approach

Antimicrobial resistance (AMR) is a growing One Health problem. Monitoring antimicrobial usage in farm animals is crucial for tackling AMR. A cohort study using the electronic clinical records during 2019 from 23 farm animal veterinary practices across the UK belonging to two corporate groups, with a range of 2-14 veterinarians per practice, estimated the usage of antimicrobials and highest priority critically important antimicrobials (HP-CIAs). Risk factors for using HP-CIAs were evaluated using hierarchical mixed-effects logistic regression modelling with practice ID and farm ID added as random effects. Using a qualitative approach, veterinarians from one of the participating practice groups were recruited for a qualitative study to explore the barriers and facilitators in relation to antimicrobial use. Semi-structured interviews were conducted with participants and analysed thematically. During the year 2019, 98,824 antimicrobial prescribing events overall were recorded from the treatment records of the 23 participating practices. The median count of antimicrobial events per practice was 3226 (range 263-22,159). There were 17,111/98,824 (17.3%) HP-CIAs events overall, with a median of 15.4% at practice level (range 4.8-22.1%). Penicillins were the most frequently used antimicrobials 29,539/98,824 (29.9%) followed by tetracyclines 19,015/98,824 (19.2%). HP-CIA use was strongly clustered, with more clustering seen at the farm level (intraclass correlation coefficient (ICC)= 0.56) than at the practice level (ICC= 0.32). Country, route of administration, season and practice type were significantly associated with the usage of HP-CIAs. Four main themes were identified from the analysis of the veterinarians' interviews: pressure from the industry, drug-related factors, knowledge level of veterinarians and clinical factors. Supermarket contracts and farm assurance schemes were facilitators for reducing antimicrobial use and the use of HP-CIAs. Ease of administration and the withdrawal period of the antimicrobials influenced veterinarians' choice of antimicrobials. The clinical condition and clinical signs presented on farm were reported to influence participating veterinarians' prescribing decision. Participants showed a good understanding of AMR, responsible use of antimicrobials and the term 'critically important antimicrobials'. In conclusion, integrating the quantitative and qualitative findings can inform policymaking on antimicrobials stewardship in farm practice. By estimating the relative levels of clustering of antimicrobial use at the practice and farm level, as well as identifying major risk factors for using HP-CIAs, more targeted interventions can be designed to promote responsible antimicrobial use in farm practice. Furthermore, better understanding the industry pressures on farms to reduce antimicrobials usage could reduce the barriers for responsible antimicrobial use by veterinarians.

Monitoring of antimicrobial usage among adult bovines in dairy herds of Punjab, India: A quantitative analysis of pattern and frequency

The present study aimed to evaluate the antimicrobial usage (AMU) pattern in dairy herds of Punjab, India. The on-farm quantification of AMU in adult bovine animals by the manual collection of empty drug containers ("bin method") along with the records of the treatment was carried out in 38 dairy farms involving 1010 adult bovines for 1 year from July 2020 to June 2021. The farm owners were asked to record the antibiotic treatments as well as to deposit empty antibiotic packaging/vials into the provided bins placed at the farms. A total of 14 different antibiotic agents in 265 commercial antibiotic products were administered to the dairy herds during the study. A total of 179 (67.55%) administered products contained antimicrobials of "critical importance" as per the World Health Organization (WHO). Mastitis (54.72%), followed by the treatment of fever (19.62%), reproductive problems (15.47%), and diarrhea (3.40%) accounted for the majority of drugs administered in the herds during the study period. The most commonly used antibiotics were enrofloxacin (89.47% herds; 21.51% products), followed by ceftriaxone (50% herds; 12.83% products), amoxicillin (50% herds; 12.83% products), oxytetracycline (55.26% herds; 11.70% products), and procaine penicillin (47.37% herds; 12.83% products). The highest quantity of AMU [in terms of antimicrobial drug use rate (ADUR)] was observed for ceftiofur, followed by ceftriaxone, procaine benzyl penicillin ceftizoxime, enrofloxacin, cefoperazone, amoxicillin and ampicillin. A total of 125 (47.17%) products contained "highest priority critically important antimicrobials" (HPCIA) and 54 (20.37%) products contained "high priority critically important antimicrobials". In terms of overall number of animal daily doses (nADD), the highest priority critically important antimicrobials (HPCIA) of the WHO such as third-generation cephalosporins and quinolones, respectively accounted for 44.64 and 22.35% of the total antibiotic use in the herds. The bin method offers an alternative to monitoring AMU as a more accessible approach for recording the actual consumption of antimicrobials. The present study, to the best of our knowledge, is the first of its kind to provide an overview of the qualitative and quantitative estimate of AMU among adult bovines from India.