Farmer perceptions of dairy farm antibiotic use and transport pathways as determinants of contaminant loads to the environment

Dairy farmer, engagement and understanding of One Health and antimicrobial resistance - a pilot survey from the lower north island of Aotearoa New Zealand

BACKGROUND

Reducing antimicrobial resistance (AMR) requires a multidisciplinary One Health approach, which necessitates buy-in from all stakeholders. In Aotearoa New Zealand, where the dairy industry is one of the largest users of antimicrobials, there are ongoing efforts to optimise antimicrobial usage (AMU) to minimise the development of AMR. These include regulations around the veterinary authorisation of the use of antibiotics by farmers without the need for a specific prescription ("the RVM process") and programmes such as the New Zealand Veterinary Association's antibiotic 'Traffic Light System'. The goal of this pilot survey was to develop and trial a questionnaire to determine how much Aotearoa dairy farmers understand about One Health, AMR, the RVM process and how their actions regarding AMU affect the wider environment.

METHODS

A 55-question semi-structured questionnaire was piloted on 15 dairy farms in the Lower North Island of Aotearoa New Zealand via an in-person semi-structured interview between September and November 2021.

RESULTS

None of the interviewed farmers could define the term One Health. However, the majority found the RVM process to be of use on their farm, although admitted they generally felt frustration regarding AMR, seeing it as a blockage to productivity, and lacked awareness regarding how their actions were related to its development. Of the farmers interviewed over half had not heard of the traffic light system, and of those who had, one admitted they refused to adhere to it.

CONCLUSIONS

This survey's novel findings have highlighted that there are notable gaps within dairy farmer understanding of AMU, AMR and One Health as well as highlighting that veterinarians could do more to keep their clients informed of their important role within One Health. There is still a lot more work to do with regards to vets, farmers and industry representatives working together to embrace One Health. Simple solutions would be to encourage farmers returning unused drugs to their veterinarians for correct disposal and to actively engage farmers further regarding AMU and AMR, so that these end-product users do not feel disconnected from the process.

From Herd Health to Public Health: Digital Tools for Combating Antibiotic Resistance in Dairy Farms

The emergence of antimicrobial resistance (AMR) is a significant threat to global food security, human health, and the future of livestock production. Higher rates of antimicrobial use in dairy farming and the sheer lack of new antimicrobials available for use focused attention on the question of how the dairy production sector contributed to the development of AMR and paved the path toward taking action to curtail it on the targeted type of farms. This paper aims to provide an introduction to a phenomenon that has gained considerable attention in the recent past due to its ever-increasing impact, the use of antimicrobial drugs, the emergence of antimicrobial resistance (AMR) on dairy farms, and seeks to discuss the possibilities of approaches such as digital health monitoring and precision livestock farming. Using sensors, data, knowledge, automation, etc., digital health monitoring, as well as Precision Livestock Farming (PLF), is expected to enhance health control and minimize disease and antimicrobial usage. The work presents a literature review on the current status and trends of AMR in dairy farms, an understanding of the concept of digital health monitoring and PLF, and the presentation and usefulness of digital health monitoring and PLF in preventing AMR. The study also analyses the strengths and weaknesses of adopting and incorporating digital technologies and artificial intelligence for dairy farming and presents areas for further study and level of use.

More movement with manure: increased mobility of erythromycin through agricultural soil in the presence of manure

Antibiotic residues in the environment threaten soil and aquatic organisms and human and livestock health through the building of antimicrobial resistance. Manure spreading associated with animal agriculture is one source of environmental antibiotic residues. To better understand the risk of contamination, we studied the adsorption of erythromycin, a model macrolide antibiotic used across human and animal medicine. We conducted a series of equilibrium batch experiments to determine the kinetics and extent of adsorption and a continuous-flow column adsorption experiment to observe non-equilibrium adsorption patterns. We determined that the adsorption equilibration time to soil was approximately 72 h in our batch experiments. Erythromycin adsorbed to soil relatively strongly (K = 8.01 × 10-2 L/mg; qmax = 1.53 × 10-3 mg/mg), adsorbed to the soil in the presence of manure with less affinity (K = 1.99 × 10-4 L/mg) at a soil: manure ratio of 10:1 by mass, and did not adsorb to manure across the solid ratios tested. We observed multi-phased adsorption of erythromycin to the soil during the non-equilibrium column experiment, which was largely absent from the treatments with both soil and manure present. These results suggest that erythromycin is more mobile in the environment when introduced with manure, which is likely the largest source of agriculturally sourced environmental antibiotics.

Distribution and risk assessment of antibiotics under water level fluctuation in the riparian zone of the Hanjiang River

The riparian zone (RZ) is an important region connecting surface water and groundwater, and it has widely been acknowledged for its pollutant buffering capacity. However, the decontaminating effect of RZ on trace organic compounds such as antibiotics has received little attention. This study explored the distribution of 21 antibiotics and 4 sulfonamide metabolites in river water and groundwater in the lower reaches of the Hanjiang River. The diffusion and exchange of contaminants between the river and riverbanks under the influence of water conservancy projects (Xinglong Dam and the Yangtze-Hanjiang Water Diversion Project) were investigated. Macrolide antibiotics were prevalent in river water (62.5-100%) and groundwater samples (42.9-80.4%). Ofloxacin and chlortetracycline were detected with the highest concentrations in river water (12.2 ng L^-1) and groundwater (9.3 ng L^-1) respectively. Higher levels of antibiotics were observed in spring and winter than in other seasons. The river-groundwater interaction has a certain interception effect on antibiotics, especially near riverbanks. Redox sensitive element Fe²⁺ showed significantly positive correlations with some tetracycline and macrolide antibiotics (p < 0.05), and thus the migration mechanism between Fe²⁺ and antibiotics under the condition of redox change should be investigated further. Environmental risks posed by antibiotics were assessed for algae, daphnids, and fish in surface water and groundwater. Only clarithromycin and chlortetracycline presented a medium risk to algae (0.1 < RQ < 1), and the rest presented low risk (RQ < 0.1). Nevertheless, the risk range may be further extended by interactions between groundwater and surface water. Accurate understanding of antibiotic transport in RZ is critical for developing management strategies aimed at reducing the pollution load on the watershed.

Understanding Antibiotic Resistance as a Perceived Threat towards Dairy Cattle through Beliefs and Practices: A Survey-Based Study of Dairy Farmers

Antibiotic use is an important component in dairy herd management both to treat bacterial diseases and to maximize animal welfare. However, there is concern among scientists that antibiotic misuse and/or overuse by farmers might promote the emergence of resistant pathogens. We conducted a cross-sectional web-based questionnaire study with dairy farmers/managers in New York, USA to evaluate their (i) level of concern about antibiotic resistance and (ii) interest in adopting new judicious antibiotic use practices regarding mastitis treatment. A total of 118 responses were subjected to statistical analysis. The findings revealed that nearly half (45%) of study participants were undecided or disagreed that antibiotic resistance due to antibiotic use in dairy farming may negatively impact the health of dairy cattle. In contrast, the majority (78%) of participants self-reported that they do not treat with antibiotics at the first sign of mastitis, and the majority (66%) have either fully or partially implemented culture-based mastitis treatment on their farm. The self-reported adoption of culture-based mastitis treatment practices was statistically significantly associated with higher numbers of injectable and intramammary doses of antibiotics used on the participants' farms. These findings will aid future research investigations on how to promote sustainable antibiotic use practices in dairy cattle.

Dairy farmer perceptions of antibiotic transport and usage in animal agriculture dataset

These data were from semi-structured interviews with dairy farmers. The content of the interviews focused on antibiotic transport and usage on dairy farms. Twenty-seven interviews were conducted in Central New York in 2019. Interviews were recorded and subsequently transcribed for qualitative thematic analysis. Qualitative coding analysis was preformed using ATLAS.ti and content filtered to ensure farmer anonymity. The dataset includes direct quotations from dairy farmers paired with farm and farmer characteristics. Quotations are subdivided thematically into the themes of disease prevention, antibiotic usage, non-antibiotic treatments, antibiotic transport, and environmental residue presence impacts, as structured in Georgakakos et al. [1]. Farm characteristics include management practice, farm size, and farm generation. Farm size was determined by number of lactating cows: small (0-50), medium-small (51-100), medium (101-500), medium-large (501-1000), and large (>1000). Farmer characteristics were farmer age categorized by birth year: Baby Boomer (1946-1964), Gen X (1965-1980), and Millennial (1981-1996). This dataset is particularly promising for longitudinal studies, incorporation of human behaviour into contaminant load models, or for recoding and analysis for themes other than those discussed by Georgakakos et al. [1].