How Input Parameters and Calculation Rules Influence On-Farm Antimicrobial Use Indicators in Animals

Abstract

A variety of indicators of antimicrobial use are available in veterinary medicine, their choice should depend on the study objective as none has been recognized as the most appropriate metric. Calculation of indicators of antimicrobial use is based on a number of parameters (e.g., treatment dose or weight at treatment) that can be informed using theoretical (also called “standard”) or actual (also called “used”) values. Although few studies compare the application of several indicators to the same antimicrobial data, the obtained results lead to apparent discrepancies or contradictions. This study aimed to investigate antimicrobial use at the weaning stage in French pig farms and, more specifically, the impact the sources of information regarding doses, body weight at treatment and treatment length, had on the indicators results. A cross-sectional survey was conducted, and data collected from 70 farms made it possible to calculate four indicators at the weaning stage using different input values. The indicator values did not show significant differences when calculated based on the theoretical dose and length of treatment (as recommended by the summary of product characteristics) or when calculated based on the dose used and treatment length as applied by the farmer. However, all of the indicators showed significant differences when calculated using the standard theoretical weight (15 kg) or actual weight (P < 0.05). It appears that if data collection plans cannot be harmonized, clarification of indicator calculations in the literature is needed to allow comparisons between studies.

Antimicrobial Use Indices—The Value of Reporting Antimicrobial Use in Multiple Ways Using Data From Canadian Broiler Chicken and Turkey Farms

“…For characterizing national temporal trends, we explored the use of different weights in the denominator, as the reported antimicrobial use estimates for a specific indicator could also change depending on the input parameters (9). In the present study, the mg/PCU and analysis using alternate biomass using the broiler chicken and turkey live pre-slaughter weight, showed similar temporal trends, indicative that the choice of which weight in the denominator to use is a preference, which affects the magnitude of the measure, but will not alter the reported trends; provided that a consistent weight is applied over time.…”

“…In the context of poultry production, when making comparisons across AMU indicators, there are several factors which can influence the resulting estimates, such as dose of the antimicrobial active ingredient (AAI), mortality levels (suggestive of a disease condition) and timing of administration of the antimicrobial (8). A change in an input parameter, such as the contextualizing denominator (animal biomass), can thus impact the overall interpretation of the AMU findings (9).…”

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

“…In pigs, the studies to date have focused on comparing national indicators to those based on ESVAC methodology (27,30); a wider comparison of currently available indicators is lacking. Furthermore, since these comparisons were limited to specific age groups (27,28,30), metrics to benchmark AMU amongst farrow-to-finish farms have not yet been evaluated. The objective of this study was to determine if the use of different indicators to benchmark antimicrobial use affected farm ranking amongst a sample population of Irish farrow-to-finish pig farms.…”

Antimicrobial use in wean to market pigs in the United States assessed via voluntary sharing of proprietary data

“…‘defined daily doses’) that are then applied across herds using general assumptions regarding the doses and weights of animals treated (Jensen et al., 2004; Postma et al., 2015; Speksnijder et al., 2015). However, the generalized assumptions on administered dose (assumed constant regardless of indication) and weight at administration (using opinion‐based assumptions of when animals are most likely treated) are problematic and can misclassify herds in relation to actual administration (Kasabova et al, 2019; Waret‐Szkuta et al, 2019). A simple example from the current study illustrates this dilemma.…”