ClassyFarm is an integrated surveillance system for monitoring the Italian livestock farms on risks related to antimicrobial use (AMU) and resistance (AMR) and other indicators, such as animal welfare and farm biosecurity. In the framework of the CoEvalAMR network we evaluated ClassyFarm by using three evaluation tools: the OH-EpiCap, the FAO PMP-AMR and the NEOH evaluation tool. Evaluation was performed by interviewing representatives of ClassyFarm, National Health System veterinarians, farm vets, farmers, livestock industry entrepreneurs, academy experts in AMR/AMU. NEOH and PMP-AMR evaluation tools were applied twice (at 2 years interval) to detect changes in the implementation of the system over time, while OH-EpiCap was applied once. The three tools differ in evaluation objectives, depth of analysis, and time/training resources needed to perform the evaluation. However, each of them enables to gather different information, which can serve as a basis for the discussion of possible adaptations/improvements of ClassyFarm. Even though ClassyFarm has a limited degree of One Health (OH) implementation, the evaluation showed that the system has evolved from a barely biosecurity and welfare surveillance system towards a more integrated OH approach. A transdisciplinary nature is also emerging, with the involvement of the environmental sector. However, there is space for improvement in resource allocation, data sharing and communication. Beyond the structural evaluation, surveillance systems should be evaluated also in relation to cost-effectiveness and system impacts.

Evaluation of ‘ClassyFarm’, the Italian integrated surveillance system of livestock farms, in the context of antimicrobial use and antimicrobial resistance

Tomassone L.
;
Alborali G. L.;De Meneghi D.
2024-01-01

Abstract

ClassyFarm is an integrated surveillance system for monitoring the Italian livestock farms on risks related to antimicrobial use (AMU) and resistance (AMR) and other indicators, such as animal welfare and farm biosecurity. In the framework of the CoEvalAMR network we evaluated ClassyFarm by using three evaluation tools: the OH-EpiCap, the FAO PMP-AMR and the NEOH evaluation tool. Evaluation was performed by interviewing representatives of ClassyFarm, National Health System veterinarians, farm vets, farmers, livestock industry entrepreneurs, academy experts in AMR/AMU. NEOH and PMP-AMR evaluation tools were applied twice (at 2 years interval) to detect changes in the implementation of the system over time, while OH-EpiCap was applied once. The three tools differ in evaluation objectives, depth of analysis, and time/training resources needed to perform the evaluation. However, each of them enables to gather different information, which can serve as a basis for the discussion of possible adaptations/improvements of ClassyFarm. Even though ClassyFarm has a limited degree of One Health (OH) implementation, the evaluation showed that the system has evolved from a barely biosecurity and welfare surveillance system towards a more integrated OH approach. A transdisciplinary nature is also emerging, with the involvement of the environmental sector. However, there is space for improvement in resource allocation, data sharing and communication. Beyond the structural evaluation, surveillance systems should be evaluated also in relation to cost-effectiveness and system impacts.
2024
Inglese
Esperti anonimi
23
1
1426
1438
13
https://www.tandfonline.com/doi/full/10.1080/1828051X.2024.2407092
AMU/AMR; livestock farms; surveillance; evaluation; One Health
no
   Convergence in evaluation frameworks for integrated surveillance of AMR (CoEval-AMR)
   UK Research and Innovation
   MRC
   MR/S037721/1
1 – prodotto con file in versione Open Access (allegherò il file al passo 6 - Carica)
262
9
Tomassone L.; Scali F.; Formenti N.; Alborali G.L.; Aragrande M.; Canali M.; Romanelli C.; Suprani V.; De Meneghi D.
info:eu-repo/semantics/article
open
03-CONTRIBUTO IN RIVISTA::03A-Articolo su Rivista
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2025390
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