Key farm characteristics associated with the level of antimicrobial use in rosé veal production - A Danish database study.

Abstract

Antimicrobial use (AMU) in veal production is high compared to other bovine production types and has been suggested as an area with potential for AMU reduction. High AMU is a public health concern due to its association with antimicrobial resistance (AMR). Identifying farm characteristics associated with AMU could provide valuable insights for stakeholders seeking to monitor and implement initiatives to reduce AMU. This study aimed at investigating farm characteristics associated with AMU in Danish rosé veal farms, which is the main veal production type in Denmark. The AMU and characteristics included were extracted from two Danish national databases; The Danish Central Husbandry Register (CHR) and the Danish Veterinary Medicines Statistics Program (VetStat). Characteristics included were farm size, mortality, number of suppliers, sites per farm, and farm-level composition of animals with regards to sex and breed. The 118 farms included in the study received 41 % of the total amount of antimicrobials prescribed for Danish calves and young stock in 2020 measured in Animal Daily Doses (ADD). A multivariable linear regression model with the annual average farm-level AMU as outcome was created. AMU was measured as ADD per 100 animals per day (ADD100) and square root-transformed in the model. Increasing farm size and number of suppliers and decreasing proportion of crossbred bulls were found to be significantly associated with higher AMU. However, proportion of crossbred bulls was correlated with proportion of females. Separating the effects of breed and sex was not possible, partly due to the highly summarised data structure. Mortality and number of sites were not significantly associated with AMU. Farms with the type "starter-farms" has previously been shown to have a higher AMU compared to other rosé veal farm types. An important finding in this study was that grouping multiple sites into farms by using ownership data made it possible to summarise AMU for the full line of production from arrival at the veal farm to exit for slaughter. The results and approaches from this paper present an opportunity for repeated evaluation of farm characteristics associated with AMU, which could be used to continuously adapt and target AMU monitoring and control. In addition, it is done on existing surveillance data which keeps the cost of the study low in terms of data collection and data management.