Antibiotic use on German pig farms - A longitudinal analysis for 2011, 2013 and 2014

Antimicrobial use in pig herds in Ireland: analysis of a national database (2019-2023)

BACKGROUND

Antimicrobial resistance (AMR) in human and animal pathogens remains a global One-Health threat. The associations between antimicrobial use (AMU) and the evolution and dissemination of AMR bacteria, and their resistance genes, highlight the importance of monitoring and regulating AMU. Here, we present an analysis of national monitoring data of AMU in pig facilities in Ireland from 2019 to 2023 via the recently established National AMU Database. AMU was measured using two metrics (mg per corrected population units (mg/PCU) and defined daily dose (DDDvet/PCU)). Temporal trend models were fit using regression models with population average effects given there were multiple observations per herd, while controlling for herd type and size.

RESULTS

Linear spline models revealed no significant change in overall usage from Q1-2019 until mid-2020, followed by a significant decrease in usage until mid-2022. There was evidence of increases in usage from mid-2022 until the end of the time series; the exact timing of the changes in trends varied by the AMU metric. A multinomial logit regression model suggested that there was a significantly decreased probability of premix use relative to oral administration from Q3-2021 through Q4-2023 (OR: 0.70 - 0.58; P < 0.03). The predicted probability that a high priority critically important antimicrobial (HPCIA) was used in a herd during a year-quarter declined by an average of 9% per quarter (OR: 0.91; 95% CI: 0.90-0.92; p < 0.001) over the study period. The mean decline in use of cephalosporin (3rd /4th generation), fluoroquinolone and macrolide (a former HPCIA) per quarter were estimated to be -12% (95% CI: -8- -15%), -9% (95% CI: -8- -10%) and - 4% (95% CI: -2- -4%), respectively.

CONCLUSIONS

This exploration of AMU in pigs in Ireland revealed significant changes in overall usage, with both decreases and increases. There were declines in usage of HPCIA agents. Additionally, there was evidence of a significant decline in the use of oral premixes, coinciding with policy change. Further monitoring of AMU is essential to understand how the pig farming sector is responding to policy changes (e.g., increasing AMU in response to zinc oxide bans).

Evaluating slaughterhouse findings for lung and tail lesions in fattening pigs from secondary data

Using slaughterhouse findings to monitor animal health and welfare is not a new idea. The German Federal Veterinary Surgeon's Association even calls for the establishment of an animal health database that combines slaughterhouse findings with health and farm data from already existing monitoring programs to create a comprehensive monitoring and surveillance tool. In an attempt to combine secondary health data from slaughterhouse findings, antibiotic use monitoring as well as biosecurity and husbandry evaluations into an integrated dataset, data from 18,593 fattening pig farms across Germany participating in the private sector Quality scheme for food (from 2018 to 2020) were harmonized at the half-year level and combined. As an example, the combined data was used to evaluate lung and tail lesion findings from abattoirs as indicators of animal health and welfare with descriptive analysis and mixed model approaches. Differences between abattoirs due to different data collection methods were taken into account by either considering the abattoir as a random effect or standardizing the prevalence data using abattoir means. The mean prevalence of lung lesions per half-year varied between 8.69 % and 9.78 %. The mean prevalence of tail lesion increased continuously from 0.65 % in the first half of 2018-1.04 % in the second half of 2020. Farm size, agricultural region, half-year and antibiotic treatment frequency were found to be associated (p < 0.000001) with the prevalence of both lung and tail lesions. A lack of variance and specificity of the secondary biosecurity and husbandry evaluation data restricts the use of individual assessment criteria as well as biosecurity and husbandry indices (calculated from a subset of assessment criteria) in our analyses. We therefore used the data for a broad categorization of farms and it could be found, that the occurrence of a lower rating in any assessment criteria during farm evaluations is associated (p < 0.000001) with a higher prevalence of lung and tail lesions, but the interpretation remains uncertain. The already existing data in the fattening pig sector can be used for the evaluation of animal health and welfare indicators to a large extent. Nonetheless, missing information, differences and changes (over time) in data collection methods introduce biases into the dataset. By improving the data quality and harmonizing collection methods, secondary animal health data could prove to be a useful tool in promoting animal health and welfare.

Trends in Antimicrobial Usage on Swiss Pig Farms from 2018 to 2021: Based on an Electronic Treatment Journal

(1) Background: The aim of this retrospective observational study was to observe the trends in antimicrobial usage (AMU) from 2018 to 2021 in Swiss pigs based on an electronic treatment journal used nationwide by farmers. Thus, for the first time, standardized, longitudinal comparisons of AMU between the years could be analyzed, as well as the influence of targeted interventions, on farms with higher consumption. (2) Methods: The data was evaluated by different indicators, such as the amount of active ingredient in kilograms, treatment days per farm (ATI) and treatment incidence (TI) based either on animal-defined daily doses (TIADD) or used daily doses (TIUDD). Calculations were performed across the following five age categories: suckling piglets, weaners, fattening pigs, and gestating and lactating sows, and the proportions of antimicrobial classes were evaluated for each age category. (3) Results: The highest amount of the active ingredient was administered to the group of fattening pigs, while the suckling piglets received the lowest amount of the active ingredient. In 2021, there was a significant decrease in active ingredient consumption per pig, but a significant increase in ATI, TIADD and TIUDD compared to 2018. The largest proportion of AMU was attributed to penicillins each year, followed by sulfonamides and tetracyclines. The "Highest Priority Critically Important Antimicrobials" represented a proportion of overall usage, declining from 5.2% in 2018 to 3.1% in 2021, while polypeptides were the most used class of critical antimicrobials. Interventions on high-usage farms showed that some farms decreased their AMU in the following year while others did not. (4) Conclusions: This study reveals a decrease in the overall usage measured in kilograms per pig of antimicrobials in Swiss pigs between 2019 and 2021 through the monitoring of AMU, but, at the same time, there was an increase in treatment days or incidence per farm. Critical antimicrobials can be reduced regardless of the indicator. The significance and quality of interventions should be investigated in future studies.

Can Improved Farm Biosecurity Reduce the Need for Antimicrobials in Food Animals? A Scoping Review

Limited and judicious antimicrobial usage (AMU) is considered the key to saving the success of human and veterinary medicine in treating infections. With the limited alternatives for antimicrobials, farm biosecurity (and herd management) is considered a promising tool to mitigate the non-judicious AMU and to maintain animal health, production, and welfare. The present scoping review aims to analyse the effect of farm biosecurity on AMU in livestock systems and formulate recommendations. Peer-reviewed manuscripts published between 2001-2022 were analyzed using the PRISMA framework using PubMed, Scopus, and Science Direct databases. After applying the inclusion criteria, 27 studies were found to assess the effect of farm biosecurity (or management practices) on AMU at the herd/farm level in quantitative/semi-quantitative terms. These studies were carried out in 16 countries, of which 74.1% (20/27) were from 11 European countries. The highest number of studies were from pig farms [51.8% (14/27)], followed by poultry (chicken) farms [25.9% (7/27)], cattle farms [11.1% (3/27)], and a single study from a turkey farm. Two studies include both pig and poultry farms. Most of the studies were cross-sectional [70.4% (19/27)], seven were longitudinal, and one was a case-control study. Complex interactions were observed among factors influencing AMU, such as biosecurity measures, farm characteristics, farmers' attitudes, availability of animal health services, stewardship, etc. A positive association between farm biosecurity and reduction in AMU was observed in 51.8% (14/27) of the studies, and 18.5% (5/27) showed that improvement in farm management practices was associated with a reduction in AMU. Two studies highlighted that coaching and awareness among farmers might lead to a decrease in AMU. A single study on economic assessment concluded biosecurity practices as a cost-effective way to reduce AMU. On the other hand, five studies showed an uncertain or spurious association between farm biosecurity and AMU. We recommend the reinforcement of the concept of farm biosecurity, especially in lower- and middle-income countries (LMICs). Further, there is a need to strengthen the evidence on the association between farm biosecurity and AMU in region- and species-specific farm settings.

Determinants of farms' antibiotic consumption - A longitudinal study of pig fattening farms in Germany

As high consumption of antibiotics in livestock production poses risks to public health, Germany has implemented a monitoring system to decrease their administration to farm animals. Data from 1,984 German pig farms are used to describe prescription trends for different antibiotic subclasses between Autumn 2017 and Autumn 2019. A panel Tobit model with control function approach is implemented to identify determinants of antibiotic consumption, where variables studied include farm, farmer, and county characteristics as well as weather variables. The overall quantity of prescribed antibiotics has been stable but with seasonal fluctuations and a shift away from critically important antibiotics used. Biosecurity factors such as livestock farm density in a county and pigs per farm are shown to be important drivers of antibiotic consumption. In addition, the number of cold days within a season increases antibiotic consumption but precipitation and the number of hot days have no significant effect.

Biosecurity and antimicrobial use in broiler farms across nine European countries: toward identifying farm-specific options for reducing antimicrobial usage

Broiler chickens are among the main livestock sectors worldwide. With individual treatments being inapplicable, contrary to many other animal species, the need for antimicrobial use (AMU) is relatively high. AMU in animals is known to drive the emergence and spread of antimicrobial resistance (AMR). High farm biosecurity is a cornerstone for animal health and welfare, as well as food safety, as it protects animals from the introduction and spread of pathogens and therefore the need for AMU. The goal of this study was to identify the main biosecurity practices associated with AMU in broiler farms and to develop a statistical model that produces customised recommendations as to which biosecurity measures could be implemented on a farm to reduce its AMU, including a cost-effectiveness analysis of the recommended measures. AMU and biosecurity data were obtained cross-sectionally in 2014 from 181 broiler farms across nine European countries (Belgium, Bulgaria, Denmark, France, Germany, Italy, the Netherlands, Poland and Spain). Using mixed-effects random forest analysis (Mix-RF), recursive feature elimination was implemented to determine the biosecurity measures that best predicted AMU at the farm level. Subsequently, an algorithm was developed to generate AMU reduction scenarios based on the implementation of these measures. In the final Mix-RF model, 21 factors were present: 10 about internal biosecurity, 8 about external biosecurity and 3 about farm size and productivity, with the latter showing the largest (Gini) importance. Other AMU predictors, in order of importance, were the number of depopulation steps, compliance with a vaccination protocol for non-officially controlled diseases, and requiring visitors to check in before entering the farm. K-means clustering on the proximity matrix of the final Mix-RF model revealed that several measures interacted with each other, indicating that high AMU levels can arise for various reasons depending on the situation. The algorithm utilised the AMU predictive power of biosecurity measures while accounting also for their interactions, representing a first step toward aiding the decision-making process of veterinarians and farmers who are in need of implementing on-farm biosecurity measures to reduce their AMU.

Use of Antimicrobials by Class in Pigs in Germany-A Longitudinal Description Considering Different International Categorisation Systems

Antimicrobial usage in both human and veterinary medicine is considered one of the main drivers of antimicrobial resistance; its reduction poses a serious challenge. To analyse the associations between usage and resistance, data from monitoring systems and classification of all antimicrobial substances are crucial. In this analysis, we investigated longitudinal data collected between 2013 and 2020 within the Veterinary Consumption of Antibiotics project from pig farms in Germany, including all antimicrobial classes, but focusing on critically important antimicrobials: third- and fourth-generation cephalosporins, fluoroquinolones, macrolides, and polymyxins. Analysing the treatment frequency, we found that a reduction in antimicrobial use in all types of pig production has occurred over time, accompanied by a rising percentage of farms without any usage. The lists of the World Health Organisation, World Organisation for Animal Health, and European Medicine Agency classify different antimicrobial substances as critically important. The vast differences between the respective weighted treatment frequencies allocated to the antimicrobials of main interest reflect the huge impact of the three categorisation systems. We concluded that, with the aim of creating national treatment guidelines supporting veterinarians to make treatment decisions, the list of the European Medicine Agency is the most suitable.

Antibiotic Use in European Pig Production: Less Is More

The goal of this study is to describe the current use of antibiotics in the European pig industry based on an extensive literature review. To achieve this, an overview of results from national (n = 15) and multi-country (n = 2) cross-sectional and longitudinal (n = 2) surveys, which describe antimicrobial use in pigs, is presented. Results are further linked to the outcome of the European Surveillance of Veterinary Antimicrobial Consumption (ESVAC) project. Overall, it was found that weaned piglets received the most antibiotics, followed by suckling piglets resulting in over 80% of the treatments being administered to animals before 10 weeks of age. Furthermore, it was observed that antibiotic use (ABU) was significantly associated across age categories, indicating that farms with a high use in piglets also used more antibiotics in their finishers. This may, among other things, be explained by farmers' habits and behavior. However, above all, the studies showed surprisingly large differences in ABU between the countries. These differences may be related to the differences in disease prevalence and/or differences in the level of biosecurity. However, they may also reflect variations in rules and regulations between countries and/or a difference in attitude towards ABU of farmers and veterinarians that are not necessarily linked to the true animal health situation. Furthermore, it was observed that already a substantial proportion of the European pig production is able to successfully raise pigs without any group treatments, indicating that it is possible to rear pigs without systematic use of antibiotics. Based on the ESVAC data, a decline of 43.2% was observed in sales of antibiotics for animals in Europe between 2011 and 2020. To enable efficient antimicrobial quantification and stewardship, 15 European countries have already established systems for herd level monitoring ABU in pigs.

The sow microbiome: Current and future perspectives to maximize the productivity in swine herds

The development of new generation sequencing methods and the reduction in the cost per base sequenced over the past few years is drawing the attention of the pig industry to microbiome understanding and modulation. In recent years, there has been an increase in the number of articles published related to microbiome studies in swine. With respect to sows, microbiome studies mainly focused on the gut, with some studies evaluating the reproductive tract and mammary microbiome. However, studies about urinary microbiome are still lacking. The present literature indicates that the microbiome in the sow’s gut can affect the microbiome in other body parts. Moreover, the understanding of the dynamics and interactions among microbial populations within the sow or the herd has led to improvements in animal health and reproductive performance. This review provides new insights related to sow intestinal, urinary, mammary, and reproductive microbiomes and their relationships with reproductive outcomes, diseases, and early colonization in offspring by gathering the most recent work in this field as well as pinpoints information gaps that require further investigation. This literature review also sheds light on the knowledge regarding the role of microbiomes in the reduction of antimicrobial use.

Temporal Patterns of Phenotypic Antimicrobial Resistance and Coinfecting Pathogens in Glaesserella parasuis Strains Isolated from Diseased Swine in Germany from 2006 to 2021

Glaesserella parasuis (Gps) causes high economic losses in pig farms worldwide. So far no vaccine provides cross-protection for different serotypes, so antibiotic treatment is widely used to cope with this pathogen. In this study, routine diagnostic data from 2046 pigs with Gps related diseases sent for necropsy to a German laboratory in the time period 2006–2021 were analysed retrospectively. In the time period 2018–2021, the most frequent serotypes (ST) detected were ST4 (30%) and ST13 (22%). A comparison of the reference period 2006–2013 prior to obligatory routine recording of antimicrobial usage in livestock with the period 2014–2021 resulted in a statistically significant decrease of frequencies of resistant Gps isolates for ceftiofur, enrofloxacin, erythromycin, spectinomycin, tiamulin and tilmicosin. While in 2006–2013 all isolates were resistant for tetracyclin and cephalothin, frequencies of resistant isolates decreased in the second time period to 28% and 62%, respectively. Parallel to the reduction of antimicrobial usage, during recent years a reduction in resistant Gps isolates has been observed, so only a low risk of treatment failure exists. Most frequently, pigs positive for Gps were also positive for S.suis (25.4%), PRRSV-EU (25.1%) and influenza virus (23%). The viral pathogens may act as potential trigger factors.

Coinfections and Phenotypic Antimicrobial Resistance in Actinobacillus pleuropneumoniae Strains Isolated From Diseased Swine in North Western Germany-Temporal Patterns in Samples From Routine Laboratory Practice From 2006 to 2020

Actinobacillus pleuropneumoniae (APP) is one major bacterial porcine respiratory tract pathogen causing disease outbreaks worldwide, although effective commercial vaccines are available. Due to frequent failure of this preventive measure, treatment with antimicrobials is indispensable to prevent animal losses within an outbreak situation. To preserve the effectivity of antimicrobial substances to fight APP should therefore be the primary aim of any interventions. In this study, the temporal development of antimicrobial resistance in APP was analyzed retrospectively in the time period 2006-2020 from a routine diagnostic database. In parallel, frequent coinfections were evaluated to identify most important biotic cofactors as important triggers for disease outbreaks in endemically infected herds. The proportion of APP serotype 2 decreased over time but was isolated most often from diseased swine (57% in 2020). In ~1% of the cases, APP was isolated from body sites outside the respiratory tract as brain and joints. The lowest frequencies of resistant isolates were found for cephalothin and ceftiofur (0.18%), florfenicol (0.24%), tilmicosin (2.4%), tiamulin (2.4%), enrofloxacin (2.7%), and spectinomycin (3.6%), while the highest frequencies of resistant isolates were found for gentamicin (30.9%), penicillin (51.5%), and tetracycline (78.2%). For enrofloxacin, tiamulin, tilmicosin, and tetracycline, significantly lower frequencies of resistant isolates were found in the time period 2015-2020 compared to 2006-2014, while gentamicin-resistant isolates increased. In summary, there is only a low risk of treatment failure due to resistant isolates. In maximum, up to six coinfecting pathogens were identified in pigs positive for APP. Most often pigs were coinfected with Porcine Circovirus 2 (56%), Streptococcus suis (24.8%), or the Porcine Reproductive and Respiratory Syndrome Virus (23.3%). Potential synergistic effects between these pathogens published from experimental findings can be hypothesized by these field data as well. To prevent APP disease outbreaks in endemically infected herds more efficiently in the future, next to environmental trigger factors, preventive measures must also address the coinfecting agents.

Comparison of Consumption Data and Phenotypical Antimicrobial Resistance in E. coli Isolates of Human Urinary Samples and of Weaning and Fattening Pigs from Surveillance and Monitoring Systems in Germany

Antimicrobial resistance (AMR) data from humans are mostly collected from clinical isolates, whereas from livestock data also exist from colonizing pathogens. In Germany, livestock data are collected from clinical and nonclinical isolates. We compared resistance levels of clinical and nonclinical isolates of Escherichia coli from weaning and fattening pigs with clinical outpatient isolates of humans from urban and rural areas. We also studied the association of AMR with available antimicrobial use (AMU) data from humans and pigs. Differences between rural and urban isolates were minor and did not affect the comparison between human and pig isolates. We found higher resistance levels to most antimicrobials in human isolates compared to nonclinical isolates of fattening pigs. Resistance to ampicillin, however, was significantly more frequent in clinical isolates of fattening pigs and in clinical and nonclinical isolates of weaning pigs compared to isolates from humans. The opposite was observed for ciprofloxacin. Co-trimoxazole resistance proportions were higher in clinical isolates of weaning and fattening pigs as compared to isolates from humans. Resistance proportions were higher in clinical isolates than in nonclinical isolates from pigs of the same age group and were also higher in weaner than in fattening pigs. Significant associations of AMU and AMR were found for gentamicin resistance and aminoglycoside use in humans (borderline) and for ampicillin resistance in clinical isolates and penicillin use in fattening pigs. In summary, we found significant differences between isolates from all populations, requiring more detailed analyses supported by molecular data and better harmonized data on AMU and AMR.

Risk Factors for Antimicrobial Use on Irish Pig Farms

Simple Summary

Antimicrobial resistance (AMR) is a major threat to public health. There are concerns that antimicrobial use (AMU) in agriculture has a role in the development of AMR. Pigs are one of the main consumers of veterinary antimicrobials and a better understanding of the drivers for AMU in this sector will help in efforts to reduce use. The aim of this study was to investigate the associations between antimicrobial use, farm characteristics, biosecurity, the presence of respiratory disease on the farm and health management practices on Irish pig farms. Farms that manufactured their feed on-site had lower total AMU than farms that purchased their feed from a feed mill. Higher levels of lung abscesses and pericarditis (inflammation of the lining around the heart), both indicators of respiratory disease, were associated with increased AMU. Higher levels of pericarditis were also associated with increased use of critically important antimicrobials. Farms vaccinating against swine influenza also had higher AMU. Farms that administered prophylactic antimicrobial treatments to piglets had higher use of individual treatments and critically important antimicrobials. The results from this study show that prophylaxis and respiratory disease are the main drivers of AMU on Irish pig farms. These findings highlight areas of farm management where interventions may aid in reducing AMU on Irish pig farms.

Abstract

The threat to public health posed by antimicrobial resistance in livestock production means that the pig sector is a particular focus for efforts to reduce antimicrobial use (AMU). This study sought to investigate the risk factors for AMU in Irish pig production. Antimicrobial use data were collected from 52 farrow-to-finish farms. The risk factors investigated were farm characteristics and performance, biosecurity practices, prevalence of pluck lesions at slaughter and serological status for four common respiratory pathogens and vaccination and prophylactic AMU practices. Linear regression models were used for quantitative AMU analysis and risk factors for specific AMU practices were investigated using logistic regression. Farms that milled their own feed had lower total AMU (p < 0.001), whereas higher finisher mortality (p = 0.043) and vaccinating for swine influenza (p < 0.001) increased AMU. Farms with higher prevalence of pericarditis (p = 0.037) and lung abscesses (p = 0.046) used more group treatments. Farms with higher prevalence of liver milk spot lesions (p = 0.018) and farms practising prophylactic AMU in piglets (p = 0.03) had higher numbers of individual treatments. Farms practising prophylactic AMU in piglets (p = 0.002) or sows (p = 0.062) had higher use of cephalosporins and fluoroquinolones. This study identified prophylactic use and respiratory disease as the main drivers for AMU in Irish pig production. These findings highlight areas of farm management where interventions may aid in reducing AMU on Irish pig farms.

Antibiotic Usage Pattern in Broiler Chicken Flocks in Germany

In this work, antimicrobial usage data from 2,546 commercial broiler chicken flocks originating from 37 farms are presented. Antimicrobial usage data at the flock level were based on mandatory documentation of antibiotic treatments in livestock in Germany, collected retrospectively for the time period of 2013-2018. The data encompasses all antimicrobial treatments during the fattening period of each flock, starting with the placement of day-old chicks at the barn. The aim of this analysis was to investigate antibiotic usage patterns in broiler chicken flocks in Germany, temporal trends in treatment frequency, the proportions of different antimicrobial classes and the weights of the broiler chickens at the time of treatment. The median treatment frequency over all flocks was six, and veterinary medicinal products belonging to nine different antimicrobial classes were used. Overall, the most frequently used classes were aminoglycosides (25.6%) and lincosamides (25.6%), followed by polypeptides (21.4%) and beta-lactams (16.2%). Over the 6 years evaluated, a considerable increase in the relative usage of lincosamides and aminoglycosides was observed. Compared to the first year of data collection, the percentage of treatments with fluoroquinolones, macrolides and polypeptides decreased in consecutive years. The median age of the broiler chickens at the time of treatment was 5 days, which corresponded to a median body weight at the time of treatment of 111 g, with substantial differences among various antimicrobial classes. We showed that in Germany, the median weight of broiler chickens at the time of treatment was substantially lower than the standard weight of broilers of 1,000 g proposed by the European Surveillance of Veterinary Antimicrobial Consumption. The median weight at treatment is very much influenced by the frequency of age-specific diseases. As different antimicrobial classes are used to combat these diseases, variations in the weight at treatment may have a considerable impact on the estimated treatment indicators. Additionally, a decrease in the relative usage of the highest-priority critically important antimicrobials, such as fluoroquinolones, macrolides and polypeptides, was shown, which might be the consequence of increasing awareness of the antibiotic resistance situation as well as of antibiotic monitoring and benchmarking systems currently running in Germany.

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.

Health monitoring of finishing pigs by secondary data use - a longitudinal analysis

Background

In Germany, animal welfare has become an increasingly important issue. Since 2006, German legislation demands self-monitoring of animal welfare by farmers, but there is a lack of prescribed indicators for governmental monitoring. Since recording of the health status through examinations on individual farms requires many resources, secondary data use is obvious. Therefore, this study deals with the overall evaluation and utilization of existing production data from the German pork production. Performance data and information on antibiotic usage and meat inspection were used for a benchmarking system of animal health in finishing pigs.

Results

Seven health scores and one total score were evaluated for 184 finishing pig herds on semi-annual basis between July 2017 and June 2019, based on the health indicators mortality, average daily gain, feed conversion ratio, treatment frequency, respiratory lesions, exterior lesions and animal management. In preparation, the selected health indicators were brought to the same scale and skewed data were transformed to build scores (MOR, ADG, FCR, TF, RESP, EXT and MANG). A differentiated analysis was carried out for three classes of initial body weight regarding to farmers’ fattening management strategies.

Conclusions

The present study shows that existing production data of German finishing pigs are usable for welfare monitoring. However, preparatory editing steps are crucial. The total score can only be an estimate of health status because partly bad or good performance could be disguised. It has also been demonstrated, that relative benchmarking is suitable for depicting temporary fluctuations in the investigated collective.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40813-021-00197-z.

Antimicrobial Usage Among Different Age Categories and Herd Sizes in Swiss Farrow-to-Finish Farms

In the Swiss pig sector, the usage of antimicrobials has been recorded, evaluated and systematically reduced on a voluntary basis since 2015. This monitoring has been carried out using various methods thereby enabling continuous national scrutiny as well as international comparisons. To gain a better understanding of the dynamics of the antimicrobial usage on Swiss farms, consumption data of farrow-to-finish farms were analyzed for (i) the within-herd relationships among different age categories and (ii) the influence of the herd size. The data were collected on 71 farms for the year 2017, encompassing the amount of active ingredients and number of defined daily doses Switzerland (nDDDch) in total, and stratified for the different age categories of piglets, weaners, fattening pigs, and sows. The differences in nDDDch per animal among the age categories were determined by a Wilcoxon test and subsequent post-hoc analysis according to Bonferroni. The within-herd relationship among the individual age categories as well as the influence of the herd size on nDDDch per animal measured as kept sows were analyzed by simple linear regression. The evaluation of the treatment days showed that 50% of the nDDDch were used in piglets, 44% for weaners, and 3% each for fattening pigs and sows. Compared to the other age categories, the examination of the number of nDDDch per animal showed a significantly higher number for sows, whereas for fattening pigs the number was significantly lower (P < 0.01). The farm-based analysis using linear regression showed a relationship between antimicrobial usage in sows and piglets (P < 0.001; adj. R² = 0.19). Similarly, a significant relationship between larger herd size and increased antimicrobial usage was observed (P = 0.02; adj. R² = 0.06). The present study provides an insight into the antimicrobial treatment dynamics of farrow-to-finish farms. In particular, the age categories piglets and sows—with their higher number of treatment days in total or per animal—are of interest regarding the potential reduction in antimicrobial usage. Likewise, larger farms with higher management requirements were found to be of particular importance for the reduction of antimicrobial usage. Monitoring programs should therefore evaluate different age categories separately to identify problems for individual farms.

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.

Quantification, description and international comparison of antimicrobial use on Irish pig farms

Background

There is concern that the use of antimicrobials in livestock production has a role in the emergence and dissemination of antimicrobial resistance in animals and humans. Consequently, there are increasing efforts to reduce antimicrobial use (AMU) in agriculture. As the largest consumer of veterinary antimicrobials in several countries, the pig sector is a particular focus of these efforts. Data on AMU in pig production in Ireland are lacking. This study aimed to quantify AMU on Irish pig farms, to identify the major patterns of use employed and to compare the results obtained to those from other published reports and studies.

Results

Antimicrobial use data for 2016 was collected from 67 Irish pig farms which represented c. 35% of national production. The combined sample population consumed 14.5 t of antimicrobial by weight of active ingredient suggesting that the pig sector accounted for approximately 40% of veterinary AMU in Ireland in 2016. At farm level, median AMU measured in milligram per population correction unit (mg/PCU) was 93.9 (range: 1.0–1196.0). When measured in terms of treatment incidence (TI200), median AMU was 15.4 (range: 0.2–169.2). Oral treatments accounted for 97.5% of all AMU by weight of active ingredient and were primarily administered via medicated feed to pigs in the post weaning stages of production. AMU in Irish pig production in 2016 was higher than results obtained from the national reports of Sweden, Denmark, the Netherlands and France but lower than the United Kingdom.

Conclusions

Pig production in Ireland is an important consumer of veterinary antimicrobials. The quantities and patterns of AMU on Irish pig farms are comparable to pig production in other European countries but higher than some countries with more advanced AMU reduction strategies. This AMU is characterised by a high proportion of prophylactic use and is primarily administered to pigs post weaning via medicated feed. Further studies to better understand the reasons for AMU on Irish pig farms and strategies to improve health among weaner pigs will be of benefit in the effort to reduce AMU.

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.

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.

Standardization of Therapeutic Measures in Antibiotic Consumption Monitoring to Compare Different Livestock Populations

Using sales data, information on antimicrobial consumption in animals is collected cumulatively across the European Union and member countries of the European Economic Area, which is documented and reported by every country and published within annual reports by the European Surveillance of Veterinary Antimicrobial Consumption (ESVAC). These serve to perform cross-border comparisons of antimicrobial consumption, despite their ambiguity due to the different units and key figures used. To improve comparability, the European Medicines Agency has introduced the population correction unit (PCU), which represents the biomass of a livestock population and is related to antibiotic consumption. However, the PCU does not consider the variability of how a livestock population is composed structurally regarding the proportions of production types contained therein. To achieve better comparability between the different geographical areas, we therefore applied a system of standardization in different examples and in real antimicrobial consumption data. This was done by quantifying the consumption of antibiotics by livestock in exemplary regions and countries (Denmark, Germany, France) by means of the active substance used (mg/kg) and subjecting it to a direct and indirect standardization procedure to identify and measure differences in consumption in relation to the composition of livestock demographics. The consideration of livestock demographics results in substantial effects when comparing antimicrobial usage in livestock. To achieve a more compelling comparability in the context of monitoring antibiotic consumption in livestock populations, we recommend using an indirect standardization method, to control potential confounding effects caused by different livestock demographics. This assumes that animal populations can be structured accordingly well. Correspondingly, detailed information on antimicrobial usage by species should be available for this type of stratification.

Monitoring Antimicrobial Resistance and Drug Usage in the Human and Livestock Sector and Foodborne Antimicrobial Resistance in Six European Countries

INTRODUCTION

Antimicrobial resistance (AMR), associated with antimicrobial use (AMU), is a major public concern. Surveillance and monitoring systems are essential to assess and control the trends in AMU and AMR. However, differences in the surveillance and monitoring systems between countries and sectors make comparisons challenging. The purpose of this article is to describe all surveillance and monitoring systems for AMU and AMR in the human and livestock sectors, as well as national surveillance and monitoring systems for AMR in food, in six European countries (Spain, Germany, France, the Netherlands, the United Kingdom and Norway) as a baseline for developing suggestions to overcome current limitations in comparing AMU and AMR data.

METHODS

A literature search in 2018 was performed to identify relevant peer-reviewed articles and national and European grey reports as well as AMU/AMR databases.

RESULTS

Comparison of AMU and AMR systems across the six countries showed a lack of standardization and harmonization with different AMU data sources (prescription vs sales data) and units of AMU and AMR being used. The AMR data varied by sample type (clinical/non-clinical), laboratory method (disk diffusion, microdilution, and VITEK, among others), data type, ie quantitative (minimum inhibition concentration (MIC) in mg/L/inhibition zone (IZ) in mm) vs qualitative data (susceptible-intermediate-resistant (SIR)), the standards used (EUCAST/CLSI among others), and/or the evaluation criteria adopted (epidemiological or clinical).

DISCUSSION

A One Health approach for AMU and AMR requires harmonization in various aspects between human, animal and food systems at national and international levels. Additionally, some overlap between systems of AMU and AMR has been encountered. Efforts should be made to improve standardization and harmonization and allow more meaningful analyses of AMR and AMU surveillance data under a One Health approach.

Antimicrobial use on Italian Pig Farms and its Relationship with Husbandry Practices

The analysis of antimicrobial use (AMU) data in livestock allows for the identification of risk factors for AMU, thereby favoring the application of responsible AMU policies on-farm. Herewith, AMU in 36 finishing pig farms in northern Italy from 2015-2017 was expressed as defined daily doses for Italian pigs (DDDita) per population correction unit (DDDita/100kg). A retrospective analysis was then conducted to determine the effects of several husbandry practices on AMU. Overall, AMU ranged between 12 DDDita/100kg in 2015 and 8 DDDita/100kg in 2017, showing no significant trends, due to the large variability in AMU between farms. However, a 66% AMU reduction was observed in 19 farms during 2015-2017. Farm size, number of farm workers, air quality, average pig mortality, and presence of undocked pigs on the farm had no significant effects on AMU. Rather, welfare-friendly farms had 38% lower AMU levels (p < 0.05). In conclusion, animal welfare management seems to be relatively more important than farm structure and other managerial characteristics as drivers of AMU in finishing pig farms.

Phenotypic antimicrobial resistance in Escherichia coli strains isolated from swine husbandries in North Western Germany - temporal patterns in samples from laboratory practice from 2006 to 2017

Background

Since 2011, antibiotic usage has decreased continuously in livestock in Germany. Whether this is accompanied by a reduction in bacterial antimicrobial resistance has not been proven so far. In this study 3054 Escherichia coli (E. coli) isolates from pigs which had suffered from disease on 2161 farms in North Western Germany were evaluated retrospectively from 2006 to 2017 for trends in their antimicrobial resistance pattern. Data were substantially related to the “pre-reduction period” and were therefore suggested as a basis for this task.

Minimal inhibitory concentrations for selected antimicrobial substances were evaluated for E. coli strains isolated from different organs of diseased swine sampled for routine diagnostic. In total, 81% of E. coli were isolated from faeces or the gastrointestinal tract, 11% from the genito-urinary tract and 8% from other organs. Susceptibility testing and classification of isolates in accordance with clinical cut-offs followed the Clinical and Laboratory Standards Institute (CLSI). If no clinical cut-offs were available for the respective combination of species, substance and organ, other published clinical cut-offs were used.

Results

Differences in susceptibility patterns between isolates from the gastrointestinal and genito-urinary tract were found for most substances. Isolates from the genito-urinary tract were less frequently resistant to ampicillin, apramycin, colistin, neomycin, spectinomycin and tetracycline and more frequently resistant to enrofloxacin and florfenicol.

A multifactorial logistic regression model revealed time-dependent decreases in frequency of resistant isolates for neomycin, spectinomycin and tetracycline. For colistin, the highest percentage of resistant isolates with 16.0% was found in 2015 followed by a decrease to the level of 2009–2010 in 2017. A decrease in frequencies of ampicillin-resistant isolates was dependent on the age-group and time period. Irrespective of the year, less than 15% E. coli isolates were resistant to apramycin, cephalosporins, colistin, enrofloxacin, florfenicol, gentamicin and neomycin.

Conclusion

An overall time-dependent decrease in the percentage of resistant E. coli isolates was found for some substances. These data from diseased animals indicate an impact of a general reduction in antibiotic usage on development of bacterial antimicrobial resistance in the field and can support the decision-making of swine practitioners for treatment options in swine.

Monitoring Antibiotic Usage in German Dairy and Beef Cattle Farms-A Longitudinal Analysis

It is well-established that antimicrobial use is a major factor for the development of antimicrobial resistance. To analyze the associations between antimicrobial resistance and usage of antimicrobial agents, data from monitoring and surveillance systems are crucial. Within the project VetCAb (Veterinary Consumption of Antibiotics), antibiotic usage data in German livestock is regularly collected and evaluated. Based on a cross-sectional study in 2011, the project was continued as the longitudinal study VetCAb-Sentinel with ongoing participant recruitment and data collection from 2013. The data collection is based on official German application and delivery forms (ADF), voluntarily provided by veterinarians and farmers. In this study the results of antibiotic usage data of dairy cows, dairy calves and beef cattle were described, using a semi-annual treatment frequency, and 95,944 ADF issued between 2011 and 2015 were analyzed. Results show that the median of the treatment frequency in dairy calf and beef cattle holdings slightly decreased from 0.4 to 0.3 and from 0.2 to 0 days, respectively, whereas the median in dairy cow holdings ranged between 1.9 and 2.3 during the observed period. Temporal changes and the effect of the factors "farm size" and "region" on the treatment frequency were investigated, using multiple linear mixed and logistic regression models. Generally, the factor "time" has a statistically significant impact on the treatment frequency in all production types. In addition, a temporal trend test over the first six half-years shows that an increasing linear trend can be stated in dairy cows and dairy calves (p = 0.017; p = 0.004, respectively). If the time-period is extended to all eight half-years under study, this turns into a quadratic effect (dairy cows: p = 0.006; dairy calves: p < 0.001). In dairy calves and beef cattle the factor "farm size" also has a statistically significant impact. The factor "region," in contrast, shows no statistically significant impact at all. Compared to other livestock populations in Germany, the use of antimicrobials in dairy cows, dairy calves, and beef cattle appears to be low, but varies across several associated factors. Considering these effects, it is recommended that the size of dairy calf and beef cattle holdings is regularly considered in the evaluation of antimicrobial usage data over time.

Used Daily Dose vs. Defined Daily Dose-Contrasting Two Different Methods to Measure Antibiotic Consumption at the Farm Level

Tackling the problem of rising antibiotic resistance requires valid and comparable data on the use of antimicrobial drugs in livestock. To date, no harmonized monitoring of antimicrobial usage in animals is available, and there is no system to assess usage data throughout Europe, thus hampering a direct comparison between different European countries. Most of the currently applied monitoring systems are based on sales data. Placement of sales data in relation to the population at risk requires overall assumptions about the weights of the animals treated and the doses applied. Only a few monitoring systems collect data in which the number of treated animals is reported exactly and does not need to be estimated. To evaluate the influence of different calculation methods on the standardizing procedure of antibiotic usage and benchmarking of farms, the treatment frequency for several farms (broiler, suckling piglets, and fattening pigs) was calculated in the following two different ways: first, based on the Used Daily Dose (TF_UDD), and second, based on the Defined Daily Dose (TF_DDD). To support this evaluation, consumption data from the Veterinary Consumption of Antibiotics Sentinel (VetCAb-S) project in Germany were used as example data. The results show discrepancies between both outcomes depending on the calculation method applied. In broiler holdings, the median values of TF_DDD were 20.89% lower than the median values of TF_UDD. In suckling piglets and fattening pig holdings, the median values of TF_DDD were increased 77.14% and 16.33%, respectively, which may have serious implications for the benchmarking of farms. Furthermore, this finding reflects that the calculation procedure also has an impact on the comparison between populations. Therefore, UDD-based calculations should be preferred to run monitoring systems with a benchmark mission. If, in contrast, the DDD approach is chosen to compare antimicrobial usage between populations, additional considerations should be made to adjust for the addressed discrepancies.