Validation of the register-based lifetime antimicrobial usage measurement for finisher batches based on comparison with recorded antimicrobial usage at farm level

Antimicrobial resistance monitoring in the Danish swine production by phenotypic methods and metagenomics from 1999 to 2018

BackgroundIn Denmark, antimicrobial resistance (AMR) in pigs has been monitored since 1995 by phenotypic approaches using the same indicator bacteria. Emerging methodologies, such as metagenomics, may allow novel surveillance ways.AimThis study aimed to assess the relevance of indicator bacteria (Escherichia coli and Enterococcus faecalis) for AMR surveillance in pigs, and the utility of metagenomics.MethodsWe collated existing data on AMR and antimicrobial use (AMU) from the Danish surveillance programme and performed metagenomics sequencing on caecal samples that had been collected/stored through the programme during 1999-2004 and 2015-2018. We compared phenotypic and metagenomics results regarding AMR, and the correlation of both with AMU.ResultsVia the relative abundance of AMR genes, metagenomics allowed to rank these genes as well as the AMRs they contributed to, by their level of occurrence. Across the two study periods, resistance to aminoglycosides, macrolides, tetracycline, and beta-lactams appeared prominent, while resistance to fosfomycin and quinolones appeared low. In 2015-2018 sulfonamide resistance shifted from a low occurrence category to an intermediate one. Resistance to glycopeptides consistently decreased during the entire study period. Outcomes of both phenotypic and metagenomics approaches appeared to positively correlate with AMU. Metagenomics further allowed to identify multiple time-lagged correlations between AMU and AMR, the most evident being that increased macrolide use in sow/piglets or fatteners led to increased macrolide resistance with a lag of 3-6 months.ConclusionWe validated the long-term usefulness of indicator bacteria and showed that metagenomics is a promising approach for AMR surveillance.

The quantitative effect of antimicrobial usage in Danish pig farms on the abundance of antimicrobial resistance genes in slaughter pigs

Research has long established the connection between antimicrobial use (AMU) and antimicrobial resistance (AMR) in production animals, and shown that the ceasing of AMU reduces AMR. Our previous study of Danish slaughter-pig production found a quantitative relationship between lifetime AMU and abundance of antimicrobial resistance genes (ARGs). This study aimed to generate further quantitative knowledge on how changes in AMU in farms influence the abundance of ARGs both with immediate effect and over time. The study included 83 farms that were visited from 1 to 5 times. From each visit, a pooled faecal sample was produced. The abundance of ARGs was obtained by metagenomics. We used two-level linear mixed models for estimating the effect of AMU on the abundance of ARGs against six antimicrobial classes. The lifetime AMU of each batch was calculated from usage during their three rearing periods; as piglets, weaners and slaughter pigs (rearing pathway). AMU at farm level was estimated as the mean lifetime AMU of the sampled batches from each farm. At batch level, AMU was measured as the deviation between the batch-specific lifetime AMU and the general mean lifetime AMU at the farm. For peroral tetracycline and macrolide use there was a significant quantitative linear effect on the abundance of ARGs in batches within individual farms, indicating an immediate effect of changed AMU from batch to batch within farms. These estimated effects between batches within farms were approximately 1/2-1/3 of the effect estimated between farms. For all antimicrobial classes, the effect of the mean farm-level AMU and the abundance of ARGs present in the faeces of slaughter pigs was significant. This effect was identified only for peroral use, except for lincosamides, where the effect was for parenteral use. The results also indicated that the abundance of ARGs against a specific antimicrobial class also increased by the peroral usage of one or several other antimicrobial classes, except for ARGs against beta-lactams. These effects were generally lower than the AMU effect of the specific antimicrobial class. Overall, the farm peroral mean lifetime AMU affected the abundance of ARGs at antimicrobial class level and abundance of ARGs of other classes. However, the difference of AMU of the slaughter-pig batches affected only the abundance of ARGs at the same antimicrobial class level in the same antimicrobial class. The results do not exclude that parenteral usage of antimicrobials may have an effect on the abundance of ARGs.

The ALEX algorithm - estimating average lifetime antimicrobial exposure of danish slaughter pigs in a fast, automated and robust way

Calculating and estimating antimicrobial exposure at specific batch level is key to understanding consumption patterns of antimicrobials in the Danish pig sector. Understanding consumption and trading patterns can assist in developing treatment plans at national levels and might lead to reducing antimicrobial resistance levels. The ALEX algorithm is a fast, automated and robust algorithm developed to estimate the average lifetime antimicrobial exposure of Danish slaughter pigs. The algorithm estimates antimicrobial exposure in the different life stages of the pig (piglet, weaner and finisher) together with the type of production network (the number of farms within a network and ownership of these). We present the algorithm and give two examples of usage. Furthermore, we compare the ALEX algorithm with an acknowledged exposure estimation algorithm, and we present a sensitivity analysis.

Agreement of Benchmarking High Antimicrobial Usage Farms Based on Either Animal Treatment Index or Number of National Defined Daily Doses

Introduction: While treatment frequency as an indicator of antimicrobial consumption is often assessed using defined doses, it can also be calculated directly as an Animal Treatment Index (ATI). In this study, the correlation of calculating antimicrobial usage on Swiss pig farms using either national Defined Daily Doses (DDDch) or an ATI (number of treatments per animal per year) and the agreement between the different methods for the identification of high usage farms were investigated.

Material and Methods: The antimicrobial consumption of 893 Swiss pig herds was calculated separately for suckling piglets, weaned piglets, fattening pigs, lactating and gestating sows using the indicators nDDDch (number of DDDch) per animal per year and ATI. Correlations between the indicators were investigated by calculating Spearman's Rho coefficients. The 5, 10, and 25% highest usage farms were determined by applying both methods and the interrater reliability was described using Cohen's Kappa coefficients and visualized by Bland-Altman plots.

Results: The Spearman's Rho coefficients showed strong correlations (r > 0.5) between nDDDch/animal/year and ATI. The lowest coefficient was shown for the correlation of both indicators in gestating sows (r = 0.657) and the highest in weaned piglets (r = 0.910). Kappa coefficients identifying high usage farms were the highest in weaned piglets (k = 0.71, 0.85, and 0.91, respectively for 5, 10, and 25% most frequent users) and the lowest in gestating sows (k = 0.54, 0.58, and 0.55 for 5, 10, and 25% most frequent users).

Conclusions: In general, the investigated indicators showed strong correlations and a broad agreement in terms of the calculated levels of antimicrobial usage and the identification of high usage farms. Nevertheless, a certain proportion of the farms were defined differently depending on the indicator used. These differences varied by age category and were larger in all age categories except weaned piglets when a higher percentage benchmark was used to define high usage farms. These aspects should be considered when designing scientific studies or monitoring systems and considering which indicator to use.