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A System Approach to Animal-Level Antimicrobial Use Monitoring in Dairy Cattle

Objective

PROJECT SUMMARY There is a fundamental gap in our ability to monitor antimicrobial use (AMU) at the individual animallevel in dairy cattle nationally. The continued existence of this gap hinders the development of data-drivenantimicrobial stewardship and understanding of the relationships between AMU in dairy cattle and antimicrobialresistanceone of the most pressing One Health challenges we face today. AMU monitoring requires anapproach to collecting and quantifying data on AMU. Also most herds must participate in data sharing for anAMU monitoring system to succeed. However farmers lack the incentive to participate in monitoring the laborinvolved in data collection is prohibitive for already busy farmers and they have concerns about the loss ofprivacy and business advantage through sharing their AMU data via a monitoring system. These majorbottlenecks are impeding the establishment of AMU monitoring in dairy cattle in the US. Thus there is anurgent need for a system approach to animal-level AMU monitoring in dairy cattle that provides private value tothe participating farmer automates laborious data collection tasks protects farmers privacy and advancesOne Health goals. Our long-term goal is to deploy a functional and efficient system for monitoring AMU in foodanimals. Thus the overall objective of this application is to develop a system for monitoring AMU in dairy cattlethat provides farmers with actionable clinical and business insights automates data collection and protectstheir proprietary information. The rationale that underlines the proposed research is that such an AMUmonitoring system will incentivize dairy farmer participation and enable One Health to benefit from the national-level AMU monitoring. This objective will be achieved by systematically building the three pillars of an effectiveAMU monitoring system: Data Models and People. Specifically we will pursue the following specific aims: (1)Collect detailed complete and validated multi-year animal-level AMU data on dairy farms; (2) Develop asystem approach to animal-level AMU monitoring in dairy cattle; and (3) Evaluate perceptions of farmers andveterinarians about AMU monitoring in dairy cattle. The AMU monitoring system developed in Aim 2 will havefour innovative elements: (i) instant private clinical/business insights for the farmer to incentivize theirparticipation in data collection and sharing (ii) standardization and automation to ease the data collectionburden on farmers (iii) augmentation with synthetic data and (iv) privatization techniques that give the farmerthe governance over their AMU data while allowing peer learning further incentivizing participation in AMUmonitoring. The proposed research is significant because it is expected to enable scaling up monitoringanimal-level AMU on dairy farms in the US with a system approach and technology that are tailored to the dairyfarming industry and have translational value to other food animal sectors. In addition to technologicalinnovations the project will generate multi-year AMU data in dairy cattle and data about farmers' perceptions ofAMU monitoring which will be instrumental in developing a use-inspired AMU monitoring system.

Investigators
IVANEK MIOJEVIC, RENATA
Institution
CORNELL UNIVERSITY
Start date
2024
End date
2029
Project number
1U01FD008421-01
Accession number
8421