AUTHOR=Anwar Sani Rianna , Wagenaar Jaap A. , Dinar Tagrid E. H. A. , Sunandar Sunandar , Nurbiyanti Nofita , Suandy Imron , Pertela Gian , Jahja Elvina J. , Purwanto Budi , CORNERSTONE group , Geijlswijk Ingeborg M. van , Speksnijder David C. , Purwanto Tri S. , Bagaskara Muhammad A. , Rachmawati Annisa , Putra Rangga , Daradjat Hannan , Noreva Patricia , Arief Riana A. , Nugroho Erianto TITLE=The comparison and use of tools for quantification of antimicrobial use in Indonesian broiler farms JOURNAL=Frontiers in Veterinary Science VOLUME=10 YEAR=2023 URL=https://www.frontiersin.org/journals/veterinary-science/articles/10.3389/fvets.2023.1092302 DOI=10.3389/fvets.2023.1092302 ISSN=2297-1769 ABSTRACT=Introduction

Indonesia has a large broiler industry with extensive antimicrobial use (AMU) according to empirical evidence. However, there are no quantitative data of on-farm AMU. Quantification of AMU at farm level is crucial to guide interventions on antimicrobial stewardship (AMS). The objective of this study was to compare on-farm AMU monitoring methods, to assess which monitoring method is best suited to gain insight in the quantitative AMU at farm level in medium-scale Indonesian broiler farms.

Method

AMU was calculated using four different indicators—mg/PCU (mass-based), TFUDDindo (Treatment Frequency of Used Daily Dose, dose-based), TFDDDvet (Treatment Frequency of Defined Daily Dose, dose-based), and TFcount − based (count-based)—for the total AMU of 98 production cycles with an average length of 30 days.

Results

Broilers were exposed to an average of 10 days of antimicrobial treatments per production cycle, whereas 60.8% of the antimicrobials belonged to the Highest Priority Critically Important Antimicrobials (HPCIAs). For each pair of indicators, the Spearman rank correlation coefficient was calculated to assess if the production cycles were ranked consistently in increasing AMU across the different indicators. The correlation varied between 0.4 and 0.8.

Discussion

This study illustrates the considerable difference in the ranking of AMU between the different indicators. In a setting comparable to medium-scale broiler farms in Indonesia, where resources are scarce and there is no professional oversight, the TFcount − based method is best suitable. Before implementing an AMU monitoring method, careful consideration of the use-indicators is paramount to achieve fair benchmarking.