Grad Student Competition
Antimicrobial use indicators, patterns, and attitudes on 5 NY dairies
| Date/Time: |
8/28/2026
11:30
|
| Author: |
Katherine J Koebel |
| Clinic: |
Cornell University |
| City, State, ZIP: |
Ithaca, NY 14850 |
K.J. Koebel, DVM
1
;
M. Capel, DVM
2
;
D.V. Nydam, DVM, PhD
3
;
R. Ivanek, DVM, MS, PhD
1
;
1Dept. Population Medicine & Diagnostic Sciences, Cornell University College of Veterinary Medicine, Ithaca, NY 14850
2Perry Veterinary Clinic, Perry, NY 14530
3Dept. Public & Ecosystem Health, Cornell University College of Veterinary Medicine, Ithaca, NY 14850
Introduction:
The dairy industry lacks standardized metrics for antimicrobial use (AMU) quantification that reflect use across heterogeneous farms. AMU indicators (AUI) have been proposed; however, the effect of time and farm-level factors on AUI must be characterized before their use in herd health management can be recommended. Our objectives were to (i) describe patterns of AMU practices on participating dairies, (ii) determine the effects of temporal and inter-farm variation on AUI, and (iii) assess the beliefs of these farms’ managers towards antibiotic stewardship and data privacy.
Materials and methods:
We prospectively enrolled a cohort of five 1,000-5,000-head conventional dairy farms in NY through convenience sampling. From each farm, we collected health event records with associated metadata, written treatment protocols, drug purchase invoices, weekly herd sizes, and conducted starting- and end-enrollment antibiotic inventories. These data were manually standardized, then used to describe farm-specific AMU practices using treemaps and calculate a total of 6 count- (i.e., frequency), mass-, and dose-based AUI for each farm-week. We constructed generalized least squares regression models with autocorrelation structure AR(1), modeling weekly AUIs as a function of the fixed effects of farm, season, and farm-season interaction, with Tukey’s post-hoc pairwise comparison at α=0.05. To evaluate antibiotic audits as a source of AMU data, we calculated drug disappearance volumes using the invoices and inventories and compared this against the total volumes of recorded use in the event records. Additionally, we completed semi-structured interviews with the managers of the dairies to assess their attitudes towards AMU and analyzed transcripts using conventional content analysis. Quantitative and qualitative analyses were performed in R and NVivo (Lumivero, Denver, CO), respectively.
Results:
The dataset contained 29,987 health event records, of which 11,569 (38.5%) involved antibiotic administration. Over the 1-year follow-up, foot events was the highest-frequency event (range: 697-1,980 events-per-1,000 animals) but had the lowest antibiotic treatment proportion (1-15%). Farm-level treemaps revealed more antibiotic classes were used in youngstock (9) than in cows (4), and 28.2-63.1% of antibiotic regimens on a farm were cloxacillin given at dry-off. High within-farm weekly variation in AUI led to high variation within-season; however, farms tended to differ from each other consistently across seasons and in multiple AUI types. We attribute the latter to protocol differences across farms, primarily dry cow therapy and one- vs multi-shot calf treatment protocols. Farmers discussed both the welfare and economic aspects of reduced AMU. They valued accuracy in AMU recordkeeping but were concerned about the privacy and perceived benefits of sharing data. A key finding was a dichotomy in farmers’ interest in comparing AUI with others, with some farmers actively desiring anonymous benchmarking while others dismissed the idea. Finally, the audit method revealed 6 instances of unexplained net increases in drug volume, and of 50 usage volumes calculated, 35 differed from recorded use by >10%; therefore, these data were deemed unfit for AMU quantification.
Significance:
We identify udder and calf health as key drivers of AMU amongst our cohort and conclude that farm-level differences in these areas are reflected in AUI. Within-farm, high week-to-week variation in AUIs dominated over differences in weekly AUI summarized by season. Participating farmers are motivated to practice stewardship but hesitate to share data without guaranteed anonymity and monetary benefits. These findings highlight the need to develop privacy-protecting digital tools to facilitate AMU monitoring for farmers.
