Does the Use of Different Indicators to Benchmark Antimicrobial Use Affect Farm Ranking?

Abstract

The need to reduce antimicrobial use (AMU) in livestock production has led to the establishment of national AMU data collection systems in several countries. However, there is currently no consensus on which AMU indicator should be used and many of the systems have defined their own indicators. This study sought to explore the effect of using different internationally recognized indicators on AMU data collected from Irish pig farms and to determine if they influenced the ranking of farms in a benchmarking system. AMU data for 2016 was collected from 67 pig farms (c. 35% of Irish pig production). Benchmarks were defined using seven AMU indicators: two based on weight of active ingredient; four based on the defined daily doses (DDD) used by the European Medicines Agency and the national monitoring systems of Denmark and the Netherlands; and one based on the treatment incidence (TI200) used in several published studies. An arbitrary "action zone," characterized by farms above an acceptable level of AMU, was set to the upper quartile (i.e., the top 25% of users, n = 17). Each pair of indicators was compared by calculating the Spearman rank correlation and assessing if farms above the threshold for one indicator were also above it for the comparison indicator. The action zone was broadly conserved across all indicators; even when using weight-based indicators. The lowest correlation between indicators was 0.94. Fifteen farms were above the action threshold for at least 6 of the 7 indicators while 10 farms were above the threshold for all indicators. However, there were important differences noted for individual farms between most pairs of indicators. The biggest discrepancies were seen when comparing the TI200 to the weight-based indicators and the TI200 to the DDDA NED (as used by Dutch AMU monitoring system). Indicators using the same numerator were the most similar. All indicators used in this study identified the majority of high users. However, the discrepancies noted highlight the fact that different methods of measuring AMU can affect a benchmarking system. Therefore, careful consideration should be given to the limitations of any indicator chosen for use in an AMU monitoring system.

Why do Irish pig farmers use medications? Barriers for effective reduction of antimicrobials in Irish pig production

“…This emphasises the need to improve pig farmers’ knowledge of animal welfare and to ameliorate communication between stakeholders. Moreover, given that farmers’ perceive that AMU is generally low in Ireland, the implementation of on-farm monitoring systems at national level is fundamental because it will provide further data on the actual use, the potential associated cost and will improve the national benchmarking scheme recently started [ 80 , 81 ]. Finally, these findings are useful for national authorities as guidelines when proposing recommendations regarding prudent AMU on-farm and for the development of effective Irish policies and education strategies for its reduction.…”

Informing Stewardship Measures in Canadian Food Animal Species through Integrated Reporting of Antimicrobial Use and Antimicrobial Resistance Surveillance Data—Part I, Methodology Development

“…Variations in the diversity of antimicrobials used depending on the species (which could impact total or class-specific nDDDvetCA's) and the proportion of antimicrobial classes used have been described elsewhere [53]. The DDDvet/PCU has been utilized in several AMU research studies [17,24,58] and has been useful when other input parameters (i.e., the days at risk) for other more popular dose-based indicators, nDDDvetCA/1000 animal-days at risk, as above (TI 1000 ), or the alternate indicator, TI 100 , are unavailable. Ultimately, for our study, the nDDDvetCA/kg animal biomass was selected for other study objectives (e.g., AMU-AMR association) and was preferred over nDDDvetCA/PCU to reduce the analytic burden of obtaining denominator data (i.e., average weight at treatment).…”

“…These include the European Surveillance for Veterinary Antimicrobial Consumption's (ESVAC) mg of antimicrobial active ingredient per population correction unit (mg/PCU), [14] used for the harmonized reporting of AMU in the European Union/European Economic Area (EU/EEA), and the OIE's mg/kg animal biomass [15], used for reporting the global AMU data. Dose-based indicators such as Treatment Incidence [TI 100 and TI 1000 ], DDDvet per PCU and other derivatives of these indicators (e.g., annualized estimates such as DDDvet/Year) are also utilized by regional and national AMU monitoring systems and in AMU research [13,[16][17][18][19][20][21][22][23]. Unfortunately, there is no single AMU metric or indicator that can address all the objectives of an AMU surveillance program or study.…”

“…As such, AMU monitoring systems have developed AMU indicators to appropriately fit their circumstance, including the type of data available (qualitative vs. quantitative), the stage in the AMU distribution chain where data are collected (farm, veterinary practice, feed mills), the mechanism for data collection (voluntary vs. mandatory reporting), and the AMU objectives of the program. The Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) sentinel farm surveillance [24], and several researchers, have compared how AMU indicators relate to each other and how input parameters could change the interpretation [17,[25][26][27]. In order to describe the various aspects of AMU and address various AMU surveillance objectives, it is therefore necessary to include multiple complimentary indicators.…”

Establishing defined daily doses (DDDs) for antimicrobial agents used in pigs, cattle and poultry in Japan and comparing them with European DDD values

“…O'Neal at al. reported that by comparing the monitoring results using DDD values established by the EMA, Denmark and the Netherlands, different DDD systems produced different consumption patterns even though the underlying data for each was identical [24].…”