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

PRRSV-1 Stabilization Programs in French Farrow-to-Finish Farms: A Way to Reduce Antibiotic Usage

Infection with the porcine reproductive and respiratory syndrome virus type 1 (PRRSV-1) has serious economic consequences for the pig industry. Swine practitioners and other agricultural advisors often describe an increase in antibiotic use when PRRSV-1 is circulating. Our objective was to assess the impact of PRRSV-1 stabilization programs on reducing antibiotic use in 19 French farrow-to-finish farms that successfully implemented such a protocol between 2007 and 2019. For each farm, we compared the global antibiotic consumption, including all physiological stages (expressed in mg/PCU and ALEA) one year before (P1) and one year after (P2) the implementation of the protocol, and the change between P1 and P2 was calculated in percentages. The data were also analyzed by level of consumption. We showed that antibiotic use decreased significantly between P1 and P2 if expressed in mg/PCU and showed a decreased tendency in terms of exposure (ALEA) after PRRSV-1 stabilization. Concerning the change from P1 to P2, depending on the level of consumption in P1, our results showed that the higher the consumption levels were in P1, the greater the antibiotic reduction in P2. This study highlights the ability of a stabilization protocol against PRRSV-1 to reduce antibiotic use, especially on farms that have high consumption rates. These hopeful results show that further investigations about the relationship between PRRSV-1 and antibiotic usage could be beneficial.

The comparison and use of tools for quantification of antimicrobial use in Indonesian broiler farms

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.

Monitoring antimicrobial usage in companion animals: exploring the use of the Danish VetStat database

BACKGROUND

In the Danish Veterinary Statistics Program, VetStat, sales data on medicinal products prescribed for veterinary consumption is collected. The Danish Food and Veterinary Administration (DVFA) manages the database and each purchase contains detailed product-specific information linked with a species-specific ID. National surveillance systems are also implemented or being developed in the other European Union Member States. By 2029, all Member States are required to report data on antimicrobial usage for companion animals to the European Medicines Agency. This study aimed to assess the challenges encountered when using the VetStat database to quantify antimicrobial use in Danish companion animals. Raw VetStat data were propagated by the DVFA and originated from veterinary practitioners and Danish pharmacies.

RESULTS

Comprehensive estimates of antimicrobial use in Danish companion animals were not readily available due to database construct. Antimicrobials sold for use in companion animals (linked to a companion animal ID) comprised a large number of products licensed solely for horses or livestock, while data assigned a replacement code encompassed both topical and peroral antimicrobials licensed for companion animals. Additionally, antimicrobials sold from pharmacies to veterinary practitioners presented the biggest challenge in data retrieval and validation. Treatment data are only transferred to VetStat through the billing systems when Danish veterinarians are treating livestock, but not companion animals. Information on products sold for in-house use in companion animals is only available from pharmacy records without a species-specific ID. As a result, parenteral antimicrobials with multi-species authorization utilized by small animal veterinary practitioners are not accounted for in the overall estimate for companion animals.

CONCLUSIONS

Owing to the database structure and requirements for data entry, antimicrobial use in companion animals is an approximation. The actual consumption may be significantly higher than what is currently calculated from the database, as the majority of parenteral products are not included. Consumption data can be measured more accurately provided treatment data from veterinary practitioners in small or mixed practices are transferred to the database through the billing system. This would equal the legal requirements for Danish veterinary practitioners treating livestock.

Method to Assess Farm-Level Vaccine and Antibiotic Usage Utilizing Financial Documentation: A Pilot Study in a Commercial Pig Farm in South Africa From 2016 to 2018

The purpose of the study was to develop a blueprint using financial documentation to describe and quantify vaccine and antibiotic usage (ABU). This method was piloted in a commercial pig farm in South Africa, with the ultimate hope to serve as a tool in a future species-specific vaccine and ABU surveillance system. Data collection was based on templates from the European Surveillance of Veterinary Antimicrobial Consumption (ESVAC) network and the World Organisation for Animal Health (WOAH). Invoices from 2016 to 2018 were used as the main data source. In addition, monthly statement of accounts were used to check for missing invoices. An inventory check was done to ensure that the correct antibiotic concentrations were used in subsequent calculations. Livestock counts and slaughter statistics were also collected to be used as denominator data. Cost calculations for the procurement of antibiotics and vaccines were also done. The study showed that veterinary medicinal products were purchased only from a single veterinary practice. A total of 291 invoices were issued over 3 years, of which 2.75% (8/291) were missing and could therefore not be used in quantification. Tetracyclines (453.65 ± 25.49 kg and 135.16 ± 3.31 mg/kg), followed by quinoxalines (258.33 ± 8.04 kg and 77.07 ± 3.93 mg/kg) were used in the highest amounts, both in terms of weight (kg) and adjusted for animal biomass (mg/kg). Vaccines used on the farm targeted seven different diseases, namely enzootic pneumonia, erysipelas, ileitis, infectious infertility, leptospirosis, neonatal pig diarrhea and porcine circovirus disease. An average of 103 546 vaccine dosages was purchased for ZAR1 302,727 ($ 84,620¹) per year, whereas the average cost for the procurement of antibiotics was ZAR 907,372 ($ 69,561) per year. The study showed that invoices and monthly statement of accounts, in combination with an inventory check and on-farm production statistics, are useful data sources to quantify vaccine and ABU in the absence of veterinary prescriptions. In addition, vaccinating pigs were more expensive than administering antibiotics.

Quantification of antimicrobial use in Fijian livestock farms

Antimicrobial resistance (AMR) is a major threat to humans and animals globally. Antimicrobial stewardship has been acknowledged as a primary strategy to tackle AMR. An important first step for antimicrobial stewardship is to quantify antimicrobial use (AMU). In Fiji, there are currently no data on AMU in livestock farms. This study aimed to quantify AMU in different livestock enterprises (beef, dairy, broiler, and layer) and farming systems (backyard, semi-commercial and commercial) in Central and Western divisions of Viti Levu, Fiji. A survey with 210 livestock farmers and 26 managers representing 276 enterprises was conducted between May and September 2019. The difference in AMU between different livestock enterprises and farming systems was investigated using ANOVA. In Fiji, the estimated annual antibiotic use in livestock was lower than the global average (44 compared with 118 mg/PCU). However, this use was concentrated in 56% of participant farms (the remaining 44% did not use antimicrobials). Total estimated quarterly anthelmintic use (20,797 mg) was not affected by farming systems but was highest (P < 0.001) in dairy enterprises (24,120 mg) and lowest in broiler enterprises (4 mg). Quarterly antibiotic use was different between the enterprises regardless of the metrics used to quantify the use (P < 0.05). Total estimated quarterly mg/PCU of antibiotic use was highest (P < 0.001) in broiler enterprises (12.4 mg/PCU) and lowest in beef enterprises (0.2 mg/PCU). For all other ESVAC metrics, total estimated antibiotic use was higher in poultry and lower in cattle enterprises. Backyard systems used less antibiotics (total mg) than commercial systems, but for other metrics, the trend was reversed. The use of both antibiotics and anthelmintics (rather than antibiotics or anthelmintics alone, or no AMU) was associated with dairy enterprises (Χ2 = 123, P < 0.001). Further studies should be conducted to quantify and evaluate the drivers of AMU in Fijian livestock farms. In addition, differences in AMU between different enterprises and farming systems suggest that strategies to reduce AMU should be tailored to specific settings.

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

This study explores methodologies for the data integration of antimicrobial use (AMU) and antimicrobial resistance (AMR) results within and across three food animal species, surveyed at the farm-level by the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS). The approach builds upon existing CIPARS methodology and principles from other AMU and AMR surveillance systems. Species level data integration involved: (1) standard CIPARS descriptive and temporal analysis of AMU/AMR, (2) synthesis of results, (3) selection of AMU and AMR outcomes for integration, (4) selection of candidate AMU indicators to enable comparisons of AMU levels between species and simultaneous assessment of AMU and AMR trends, (5) exploration of analytic options for studying associations between AMU and AMR, and (6) interpretation and visualization. The multi-species integration was also completed using the above approach. In addition, summarized reporting of internationally-recognized indicators of AMR (i.e., AMR adjusted for animal biomass) and AMU (mg/population correction unit, mg/kg animal biomass) is explored. It is envisaged that this approach for species and multi-species AMU-AMR data integration will be applied to the annual CIPARS farm-level data and progressively developed over time to inform AMU-AMR integrated surveillance best practices for further enhancement of AMU stewardship actions.

Antimicrobial Use Surveillance Indicators for Finfish Aquaculture Production: A Review

Quantification and tracking of antimicrobial use (AMU) are key factors for the development of responsible antimicrobial stewardship programs and comparison between countries. Global finfish aquaculture growth and increased AMU creates the potential for exchange of antimicrobial resistance between aquatic and terrestrial environments, making AMU surveillance imperative for this industry. The objective of this review is to collate current literature on AMU surveillance indicators and their application to commercial finfish aquaculture production. A systematic search strategy was applied to five databases: Medline, Embase, Agricola, CAB abstracts, and Biosis. To be included, studies must report on at least one AMU surveillance indicator for use in animals. There is no single, standardized indicator suitable to report finfish aquaculture AMU. The type and availability of finfish aquaculture data presents unique considerations for AMU reporting. Ultimately, the indicator used should be fit-for-purpose to satisfy the objective of the surveillance program, motivation for comparison and provide useful information to the industry stakeholders. Finfish aquaculture total annual slaughter weight allows estimation of biomass for the population correction unit (PCU) to report annual total mg of active antimicrobial ingredient per PCU. These data are commonly reported by finfish aquaculture-producing countries, allowing for international comparisons. However, this precludes the ability to compare to terrestrial livestock where the PCU is based on animal numbers and an average treatment weight, which are not available for finfish aquaculture. The mg per adjusted PCU indicator provides an interesting alternative that incorporates the length of the marine grow-out phase for finfish, but is subject to the same limitations. The number of defined daily doses animal per animal-days-at-risk is useful but also limited by a lack of a defined average treatment weight. The concept of average treatment weight remains challenging for the industry as it does not accurately reflect the timing of actual AMU to fish in the system. The term “average biomass” is more reflective of the intent of AMU surveillance indicators. Defining an average treatment weight, or average biomass, will require industry engagement, which is crucial if AMU reporting is to be deemed credible and provide value back to the finfish aquaculture industry.

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

Data on antimicrobial use were collected for the 2016 and 2017 calendar years from swine producers in the United States. Nine large systems, collectively producing over 20 million market pigs annually, voluntarily provided data to advance understanding of antimicrobial use in the industry and to support antimicrobial stewardship initiatives. The scope of the study was limited to growing pigs, and the granularity of data varied across the systems. Data were summarized both qualitatively and quantitatively by antimicrobial class, active ingredient and route of administration (injection, water and feed). Data on the purpose of administration, doses and durations of administration were not available, but some information was provided by the responsible veterinarians. Aggregate data were similar both qualitatively and quantitatively in 2016 and 2017, although marked changes between years were evident within systems for some antimicrobials. Antimicrobial use (by weight) was dominated by the tetracycline class (approximately 60% of total use). Antimicrobials in classes categorized as critically important constituted 4.5% and 5.3% of total use in 2016 and 2017, respectively. In both years, fluoroquinolone (0.23%, 0.46%) and 3rd generation cephalosporin (0.15%, 0.11%) use collectively accounted for <1% of total use. Administration was predominantly oral in feed and water, and injection comprised approximately 2% of use overall, but around 12% for critically important antimicrobials. There was considerable variability among systems in patterns of antimicrobial use. This pilot project demonstrates the feasibility of acquiring antimicrobial use data via voluntary sharing. It is currently being expanded among larger swine production systems, and further efforts to enable confidential data sharing and benchmarking for smaller producers are being pursued by the swine industry. Recognized biases in the data caution against over-interpretation of these data as an index of national use.

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

We have previously described the importance of using multiple indicators for reporting national farm-level antimicrobial use (AMU) information, but the distribution of flock-level AMU and how these indicators relate to each other has not yet been fully explored. Using farm-level surveillance data (2013–2019), for broiler chickens (n = 947 flocks) and turkeys (n = 427), this study aims to (1) characterize flock-level AMU and identify high users, (2) identify appropriate AMU indicators and biomass denominator [population correction unit (PCU) vs. kg weight at pre-slaughter], and (3) make recommendations on the application to veterinarian-producer and national-level reporting. Diverse AMU patterns were identified in broiler chickens (156 patterns) and turkeys (68 patterns); of these, bacitracin, reported by 25% of broiler chicken and 19% of turkey producers, was the most frequently occurring pattern. Depending on the indicator chosen, variations in reported quantity of use, temporal trends and relative ranking of the antimicrobials changed. Quantitative AMU analysis yielded the following results for broiler chickens: mean 134 mg/PCU; 507 number (n) of Canadian (CA) defined daily doses (DDDvet) per 1,000 chicken-days and 18 nDDDvetCA/PCU. Analysis in turkey flocks yielded the following: mean 64 mg/PCU, 99 nDDDvetCA/1,000 turkey-days at risk and 9 nDDDvetCA/PCU. Flocks were categorized based on the percentiles of the mg/PCU distribution: “medium” to “low” users (≤75th percentile) and “high” users (>75th percentile). The odds of being a high user in both broiler chickens and turkeys were significantly increased: if water medications were used, and if trimethoprim-sulfonamides, bacitracins, and tetracyclines were used. Pairwise correlation analysis showed moderate correlation between mg/PCU and the nDDDvetCA/1,000 animal days at risk and between mg/PCU and nDDDvetCA/PCU. Significantly high correlation between nDDDvetCA/1,000 animal days at risk and nDDDvetCA/PCU was observed, suggestive that either of these could be used for routine monitoring of trends in AMU. One source of discrepancy between the indicators was the antimicrobial. Understanding the choice of parameter input and effects on reporting trends in AMU will inform surveillance reporting best practices to help industry understand the impacts of their AMU reduction strategies and to best communicate the information to veterinarians, their producers, and other stakeholders.

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

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.

Monitoring of Farm-Level Antimicrobial Use to Guide Stewardship: Overview of Existing Systems and Analysis of Key Components and Processes

The acknowledgment of antimicrobial resistance (AMR) as a major health challenge in humans, animals and plants, has led to increased efforts to reduce antimicrobial use (AMU). To better understand factors influencing AMR and implement and evaluate stewardship measures for reducing AMU, it is important to have sufficiently detailed information on the quantity of AMU, preferably at the level of the user (farmer, veterinarian) and/or prescriber or provider (veterinarian, feed mill). Recently, several countries have established or are developing systems for monitoring AMU in animals. The aim of this publication is to provide an overview of known systems for monitoring AMU at farm-level, with a descriptive analysis of their key components and processes. As of March 2020, 38 active farm-level AMU monitoring systems from 16 countries were identified. These systems differ in many ways, including which data are collected, the type of analyses conducted and their respective output. At the same time, they share key components (data collection, analysis, benchmarking, and reporting), resulting in similar challenges to be faced with similar decisions to be made. Suggestions are provided with respect to the different components and important aspects of various data types and methods are discussed. This overview should provide support for establishing or working with such a system and could lead to a better implementation of stewardship actions and a more uniform communication about and understanding of AMU data at farm-level. Harmonization of methods and processes could lead to an improved comparability of outcomes and less confusion when interpreting results across systems. However, it is important to note that the development of systems also depends on specific local needs, resources and aims.

Decrease in fluoroquinolone use in French poultry and pig production and changes in resistance among E. coli and Campylobacter

This paper presents the impact on antimicrobial resistance (AMR) in poultry and pig bacteria of the French EcoAntibio plan, a public policy to reduce antimicrobial use in animals. The analysis was performed using sales data of veterinary antimicrobials and AMR data from bacteria obtained at slaughterhouse and from diseased animals. From 2011-2018, fluoroquinolones exposure decreased by 71.5 % for poultry and 89.7 % for pigs. For Campylobacter jejuni isolated from broilers at slaughterhouses, ciprofloxacin resistance increased from 51 % in 2010 to 63 % in 2018, whereas for turkeys the percentages varied from 56 % in 2014 to 63 % in 2018. For commensal E. coli isolated from the caecal content of broilers at slaughterhouses, the resistance to ciprofloxacin - assessed using an epidemiological cut-off value - increased in broiler isolates from 30.7 % in 2010 to 38.1 % in 2018. In turkeys, the percentage of resistant E. coli isolates decreased from 21.3 % in 2014 to 15.2 % in 2018, whereas in pigs, it increased from 1.9 % in 2009 to 5.5 % in 2017. However, for E. coli isolated from diseased animals, when the breakpoints of 2018 were applied, resistance to fluoroquinolones significantly decreased between 2010 and 2018 from 9.0%-5.4% for broilers/hens, from 7.4 % to 3.4 % for turkeys and from 9.4 % to 3.6 % for pigs. These data show that the major, rapid decrease in the exposition to fluoroquinolones had contrasting effects on resistance in the diverse bacterial collections. Co-selection or fitness of resistant strains may explain why changes in AMR do not always closely mirror changes in use.