Recording Antimicrobial Use on Irish Dairy Farms: Barriers & Facilitators to Using Technology and Sharing Data.

Antimicrobial use (AMU) data are essential to monitor the impact of AMU reduction strategies in animal health. The use of technology and herd recording software to record AMU will be vital to scale the collation of these data in the future. The aim of this study was to determine the barriers and facilitators to Irish dairy farmers recording their AMU using a herd recording software and sharing AMU data. Thirty-three Irish dairy farmers involved in a study on AMU monitoring were asked to record their AMU using a herd recording software over a 12-mo period. At the end of the 12-mo period, 10 of these farmers were selected to take part in semi-structured interviews exploring their opinions on recording AMU, the use of herd recording software, and sharing AMU data. Interviews were transcribed and qualitatively analyzed using inductive thematic analysis. Several barriers and facilitators to farmers recording their AMU using a herd recording software and sharing AMU data were identified. Barriers included the age and generation of the farmer, farm infrastructure, a lack of training and education, a lack of knowledge around the benefits of digital data, a lack of incentive to digitalise records, and a fear of repercussions. Facilitators identified by the farmers included the benefits of having instantly available data for making herd management decisions, reduced paperwork, increased organization for inspections, and a potential positive impact on the image of the dairy industry. To increase the uptake of new technology to record AMU at farm-level, farmers will need support in terms of education and training around the software available to them and reassurance around the perceived risks of repercussions with sharing data in a digital format.

Antimicrobial Resistance in Commensal Escherichia coli of the Porcine Gastrointestinal Tract.

Antimicrobial resistance (AMR) in Escherichia coli of animal origin presents a threat to human health. Although animals are not the primary source of human infections, humans may be exposed to AMR E. coli of animal origin and their AMR genes through the food chain, direct contact with animals, and via the environment. For this reason, AMR in E. coli from food producing animals is included in most national and international AMR monitoring programmes and is the subject of a large body of research. As pig farming is one of the largest livestock sectors and the one with the highest antimicrobial use, there is considerable interest in the epidemiology of AMR in E. coli of porcine origin. This literature review presents an overview and appraisal of current knowledge of AMR in commensal E. coli of the porcine gastrointestinal tract with a focus on its evolution during the pig lifecycle and the relationship with antimicrobial use. It also presents an overview of the epidemiology of resistance to extended spectrum cephalosporins, fluoroquinolones, and colistin in pig production. The review highlights the widespread nature of AMR in the porcine commensal E. coli population, especially to the most-used classes in pig farming and discusses the complex interplay between age and antimicrobial use during the pig lifecycle.

Changes in S100A8/A9 and S100A12 and Their Comparison with Other Analytes in the Saliva of Pigs with Diarrhea Due to E. coli.

The family of calgranulins includes S100A8 (calgranulin A), S100A9 (calgranulin B), which can appear as a heterodimer known as S100A8/A9 or calprotectin, and S100A12 (calgranulin C). These proteins are related to different inflammatory conditions, immune-mediated diseases, and sepsis and are considered biomarkers of potential interest. This study aims to evaluate if S100A8/A9 and A12 could change in pigs with diarrhea due to E. coli and to compare the changes of S100A8/A9 and A12 with other analytes in order to explore the possible causes or mechanisms involved. For this purpose, a panel integrated by analytes related to inflammation (haptoglobin, inter-alpha trypsin inhibitor 4 (ITIH4), and total protein); immune system (adenosine deaminase, ADA); stress (alpha-amylase); tissue damage (lactate and lactate dehydrogenase (LDH)); sepsis (aldolase) and redox status (ferric-reducing ability of saliva (FRAS) and advanced oxidation protein products (AOPP)) was evaluated. S100A8/A9 and A12 and the other analytes measured in this study showed increases in the saliva of pigs with diarrhea due to E. coli. S100A8/A9 and/or A12 showed a significant correlation of different magnitude with some of the other analytes evaluated. Further studies should be conducted to gain knowledge about the possible practical applications as biomarkers of the measurements of S100A8/A9 and A12 in the saliva of pigs.

Analysing biomarkers in oral fluid from pigs: influence of collection strategy and age of the pig.

BACKGROUND AND OBJECTIVES: Oral fluid (OF) is an easy-to-collect, inexpensive, fast and non-invasive sample to characterize health and welfare status of the pig. However, further standardisation of the collection methods is needed in order to use it regularly in veterinary practice. Cotton ropes are routinely used to collect OF for pathogen detection but they may not be optimal for biomarker analysis due to sample contamination. This study compared two methods (cotton ropes and sponges) to collect porcine OF for biomarker analysis. A panel of 11 biomarkers of stress, inflammation, sepsis, immunity, redox status and general homeostasis was studied. MATERIALS AND METHODS: Eighteen farrow-to-finish pig farms were included in the study. In each farm, three (for sponges) or four pens of pigs (for ropes) were sampled at four age categories: the week after weaning (5 weeks), before (11-12 weeks) and after (12-13 weeks) moving to finisher facility and the week before slaughter (22-25 weeks). In total, 288 OF samples were collected with cotton ropes and 216 with sponges and analysed for the biomarkers: cortisol, alpha-amylase, oxytocin (stress), haptoglobin (inflammation), procalcitonin (sepsis), adenosine deaminase, immunoglobulin G (immune system), ferric reducing antioxidant power (redox status), and creatine kinase, lactate dehydrogenase and total protein (general homeostasis). Samples were also scored visually for dirtiness using a score from 1 (clean) to 5 (very dirty). RESULTS: Rope-collected OF had higher levels of dirtiness (3.7 ± 0.04) compared to sponge-collected OF (2.7 ± 0.15) and had higher values than sponges for cortisol, procalcitonin, oxytocin, haptoglobin, total protein, lactate dehydrogenase and ferric reducing antioxidant power. All biomarkers decreased in value with age. Immunoglobulin G did not perform well for any of the two collection methods. DISCUSSION AND CONCLUSION: The results showed a clear effect of age on the biomarkers in OF collected with both, sponges or ropes. Sponges provided a cleaner sample than cotton ropes for biomarker analysis. Both methods are easy to apply under the commercial conditions in pig farms although sponges may take more time in early weaner stages. From a practical point of view, sampling with sponges achieved the best combination of reduced sampling time and low contamination.

Changes in salivary biomarkers of stress, inflammation, redox status, and muscle damage due to Streptococcus suis infection in pigs.

BACKGROUND: Streptococcus suis (S. suis) is a Gram-positive bacteria that infects pigs causing meningitis, arthritis, pneumonia, or endocarditis. This increases the mortality in pig farms deriving in severe economic losses. The use of saliva as a diagnostic fluid has various advantages compared to blood, especially in pigs. In this study, it was hypothesized that saliva could reflect changes in different biomarkers related to stress, inflammation, redox status, and muscle damage in pigs with S. suis infection and that changes in these biomarkers could be related to the severity of the disease. RESULTS: A total of 56 growing pigs from a farm were selected as infected pigs (n = 28) and healthy pigs (n = 28). Results showed increases in biomarkers related to stress (alpha-amylase and oxytocin), inflammation (haptoglobin, inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4), total protein, S100A8-A9 and S100A12), redox status (advanced oxidation protein producs (AOPP)) and muscle damage (creatine kinase (CK), CK-MB, troponin I, lactate, aspartate aminotransferase, and lactate dehydrogenase). An increase in adenosine deaminase (ADA), procalcitonin, and aldolase in infected animals were also observed, as previously described. The grade of severity of the disease indicated a significant positive correlation with total protein concentrations, aspartate aminotransferase, aldolase, and AOPP. CONCLUSIONS: This report revealed that S. suis infection caused variations in analytes related to stress, inflammation, redox status, and muscle damage in the saliva of pigs and these can be considered potential biomarkers for this disease.

Behaviour change interventions for responsible antimicrobial use on farms.

BACKGROUND: In the coming years, major governance changes in the form of policy directives and regulations will catalyse major top-down change with respect to animal health on European farms in an effort to combat the OneHealth threat of antimicrobial resistance. This top-down approach must be met with bottom-up strategies to ensure target actors (namely, farmers and vets) are supported and motivated to change their practices, thus, avoiding unintended consequences of forced change. Although much behavioural research has explored the factors influencing antimicrobial practices on farms, a gap exists translating these findings into evidence-based behaviour change interventions that can be put into practice. The current study aims to fill this gap. It provides insights into identifying, understanding, and changing the behaviours of farmers and veterinarians with respect to the responsible use of antimicrobials in farming. RESULTS: Through an inter-disciplinary and multi-actor approach, the study combines scientific knowledge from the behavioural sciences and animal health sciences, coupled with tacit knowledge from a co-design, participatory approach to recommend seven behaviour change interventions that can help to support good practices amongst farmers and vets, with respect to animal health, and reduce the use of antimicrobials on farms. The behaviour change interventions include message framing; OneHealth awareness campaign; specialised communications training; on-farm visual prompts and tools; social support strategies (for both farmers and vets); and antimicrobial use monitoring. The study details each intervention with respect to their evidence base and scientific concept, grounded in behavioural science, along with stakeholder feedback on design and delivery of the interventions. CONCLUSIONS: These behaviour change interventions can be taken, adapted, and put into practice by the agri-food community to support good animal health practices and responsible antimicrobial use on farms.

Measurement of Calprotectin (S100A8/A9) in the Saliva of Pigs: Validation Data of A Commercially Available Automated Assay and Changes in Sepsis, Inflammation, and Stress.

Calprotectin (CALP, S100A8/A9), also named myeloid-related protein 8/14, is a dimer complex of S100A8 and S100A9 that belongs to the S-100 protein family. It is involved in inflammation and has a wide range of proinflammatory functions, such as cytokine production and regulation of leukocyte adhesion, migration, and phagocytosis. In humans, CALP traditionally can be measured in faeces, serum, and saliva as a biomarker of inflammation and sepsis. The objective of this study was to validate an automated assay for CALP measurements in the saliva of pigs, having the advantage of the use of a non-invasive sample that is easy to collect. The assay was precise and accurate. CALP in saliva measured by this assay showed significant changes depending on the hour of the day. It also showed significant increases in the saliva of pigs after the administration of lipopolysaccharide (LPS), and showed a rise, although with increases of lower magnitude, after a stressful stimulus. Further studies should be made to gain knowledge about the possible practical applications of the measurements of CALP in the saliva of pigs as a biomarker to evaluate the animals' health and welfare.

Revealing the Changes in Saliva and Serum Proteins of Pigs with Meningitis Caused by Streptococcus Suis: A Proteomic Approach.

Meningitis due to Streptococcus suis causes high mortality and morbidity on pig farms and has increasing zoonotic potential worldwide. Saliva proteome analysis would potentially be useful in elucidating pathophysiological changes and mining for new biomarkers to diagnose and monitor S. suis infection. The objective of this study was to investigate the changes in the salivary and serum proteome profile of piglets with meningitis. The LC-MS/MS TMT proteomic approach was used to analyze saliva and serum samples from 20 male piglets: 10 with meningitis and 10 healthy. In saliva, 11 proteins had higher and 10 had lower relative abundance in piglets with meningitis. The proteins with the highest relative abundance were metavinculin (VCL) and desmocollin-2 (DSC2). Adenosine deaminase (ADA) was selected for validation using a spectrophotometric assay and demonstrated excellent performance in the differentiation between healthy and pigs with meningitis due to S. suis. In serum, the most protruding changes occurred for one SERPIN and haptoglobin (HP). In saliva and serum, the highest number of proteins with altered abundance were linked, via the enrichment analysis, with platelet and neutrophil pathways. Overall, meningitis caused by S. suis resulted in specific proteome changes in saliva and serum, reflecting different pathophysiological mechanisms, and marking new potential biomarkers for this infection.

Blood and faecal biomarkers to assess dietary energy, protein and amino acid efficiency of utilization by growing and finishing pigs.

BACKGROUND: Diet evaluation and optimization is a slow and expensive process and it is not possible to do it at a farm level. This study aimed to use the blood serum metabolite (BSM) and faecal volatile fatty acid (VFA) profiles as potential biomarkers to identify changes in protein, amino acid and energy dietary content in growing and finishing pig diets at farm level. RESULTS: Two studies were conducted. The first study (S1) included 20 pens of 11 pigs (87.0 ± 4.10 kg; 18 weeks old) assigned to 5 diets: control (C1), high or low crude protein (HP1 and LP1, respectively), and high or low net energy (HE1 and LE1, respectively). The second study (S2) included 28 pens of 11 pigs (41.3 ± 2.60 kg; 12 weeks old) assigned to 7 diets: control (C2), high or low crude protein (HP2 and LP2, respectively), high or low amino acid (HA2 and LA2, respectively), and high or low net energy (HE2 and LE2, respectively). Pigs were followed for 10 (S1) and 20 (S2) days, and blood and faecal samples were collected at 20 (S1) and 14 (S2) weeks of age. Data were analysed using general linear models and receiver operating characteristic curve analysis. Urea nitrogen showed the best results as a biomarker. Urea nitrogen was higher in pigs fed high protein diets, HP1 (13.6 ± 0.95 mg/dL) and HP2 (11.6 ± 0.61), compared to those fed low protein diets, LP1 (6.0 ± 0.95) and LP2 (5.2 ± 0.61; P < 0.001), showing good discrimination ability (Area under the curve (AUC) = 98.4 and 100%, respectively). These differences were not observed between diets LA2 (6.5 ± 0.61) and HA2 (8.7 ± 0.61; P > 0.05; AUC = 71.9%), which were formulated based on the ideal protein profile but with no excess of protein. Creatinine, triglycerides, branched-chain fatty acids, albumin, propionic acid, and cholesterol showed differences between at least 2 diets but only in one of the studies. CONCLUSIONS: Urea nitrogen showed high accuracy to detect excess of crude protein in growing and finishing pig diets. Other biomarkers like BCFA showed promising results and need to be further studied.

Antimicrobial resistance in Escherichia coli isolated from on-farm and conventional hatching broiler farms in Ireland.

BACKGROUND: On-farm hatching (OH) systems are becoming more common in broiler production. Hatching conditions differ from conventional farms as OH chicks avoid exposure to handling, transport, post-hatch water and feed deprivation. In contrast, chicks in conventional hatching conditions (CH) are exposed to standard hatchery procedures and transported post hatching. The objectives of this pilot study were to investigate the prevalence and frequency of Escherichia coli resistant to antimicrobials, including presumptive ESBL/AmpC-producing E. coli, isolated from environmental and faecal samples from OH versus CH hatching systems, and to investigate the presence of ESBL/AmpC-producing encoding genes. RESULTS: Environmental samples were collected from one flock in 10 poultry farms (5 OH farms, 5 CH farms) on day 0 post disinfection of the facilities to assess hygiene standards. On D10 and D21 post egg/chick arrival onto the farm, samples of faeces, boot swabs and water drinker lines were collected. E. coli were isolated on MacConkey agar (MC) and MacConkey supplemented with cefotaxime (MC+). Few E. coli were detected on D0. However, on D10 and D21 E. coli isolates were recovered from faeces and boot swabs. Water samples had minimal contamination. In this study, 100% of cefotaxime resistant E. coli isolates (n=33) detected on selective media and 44% of E. coli isolates (84/192) detected on nonselective media were multidrug resistant (MDR). The antimicrobial resistance (AMR) genotype for the 15 ESBL/AmpC producing isolates was determined using multiplex PCR. Six of these were selected for Sanger sequencing of which two were positive for blaCMY-2, two for blaTEM-1 and two were positive for both genes. CONCLUSIONS: There was no difference in E. coli isolation rates or prevalence of AMR found between the OH versus CH systems, suggesting that the OH system may not be an additional risk of resistant E. coli dissemination to broilers compared to the CH systems. The frequency of ß-lactam resistant E. coli in boot swab and faeces samples across both OH (24/33 (73%)) and CH (9/33 (27%)) systems may indicate that hatcheries could be a reservoir and major contributor to the transmission of AMR bacteria to flocks after entry to the rearing farms.

Effect of Phase Feeding, Space Allowance and Mixing on Productive Performance of Grower-Finisher Pigs.

This study investigates the effects of space allowance (SA), mixing and phase feeding (PF) on performance of grower-finisher pigs. Three trials (T) were conducted. In T1 and T2, 345 pigs/trial were moved to finisher stage at 11 weeks of age and assigned to two SAs: 0.96 (n = 15 pens; 10 pigs/pen) and 0.78 (n = 15; 13 pigs/pen) m2/pig. Mixing was applied to 5 pens of each SA leading to a 2 × 2 factorial arrangement (SA × Mixing). For PF, 2 diets with 0.95 and 0.82 g SID Lys/MJ NE were applied to 5 pens of each SA (not mixed) leading to another 2 × 2 factorial arrangement (SA × PF). In T3, 230 pigs were moved to the grower-finisher stage at 11 weeks of age, mixed, and assigned to 4 treatments (SA × PF; n = 5 pens). Data were analyzed using general linear mixed models. SA did not affect performance (p > 0.05). Non-mixed pigs were 5.40 (T1) and 5.25 (T2) kg heavier than mixed pigs at 21 weeks of age (p < 0.001). PF reduced performance of pigs by 3.45 (T1) and 4.05 (T2) kg at 21 weeks of age (p < 0.001). In conclusion, mixing and reducing SID Lys:NE ratio from 0.95 to 0.82 g/MJ at 15-16 weeks of age, have a more marked impact on performance than reducing SA from 0.96 to 0.78 m2/pig.

High levels of standardized ileal digestible amino acids improve feed efficiency in slow-growing pigs at late grower-finisher stage.

Slow-growing pigs negatively affect production efficiency in conventional pig farms by increasing the occupation time of the facilities and being a limiting factor for the All-In/All-Out swine production systems. This subset of pigs is usually managed with the rest of the pigs, and their nutrient requirements may not be fulfilled. The purpose of the present study was to compare the productive performance of slow- and fast-growing pigs to different standardized ileal digestible (SID) amino acids (AA) dietary levels at late grower-finisher stage. A total of 84 pigs were weighed, tagged, and classified as slow-growing (SG; n = 48; 24.1 ± 1.38 kg) or fast-growing pigs (FG; n = 36; 42.7 ± 1.63 kg) at 11 weeks of age. Pigs were housed in mixed sex pens (n = 8 SG+6 FG/pen) equipped with feeding stations to record daily feed intake per individual pig. Pigs were assigned to three dietary treatments resulting in a 2 × 3 factorial arrangement at 15 weeks of age. Isoenergetic diets were formulated by increasing the ideal protein profile based on the following SID lysine (Lys) levels: 0.92%, 1.18% and 1.45%. Pigs were weighed bi-weekly until 21 weeks of age. Fast-growing pigs were 33.7 kg heavier, gained 255 g/day and consumed 625.5 g/day more than SG pigs (p < 0.001). No interaction or diet effects were observed for final body weight, average daily gain and average daily feed intake (p > 0.05). However, feed conversion ratio was 0.3 lower for SG pigs fed 1.45% SID Lys/AA compared to SG pigs fed 0.92% SID Lys/AA (p = 0.002). Feed conversion ratio was not different within the FG pigs' dietary treatments (p > 0.05). The efficiency of SG pigs may be improved when dietary SID AA levels are increased from 0.92 up to 1.45% SID Lys/AA. Thus, nutrient requirements may vary depending on growth rate at the same age, and SG pigs may require higher dietary SID AA levels than FG pigs to achieve similar productive performance.

Risk Factors for Antimicrobial Use on Irish Pig Farms.

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.

Severe tail lesions in finisher pigs are associated with reduction in annual profit in farrow-to-finish pig farms.

OBJECTIVES: We investigated the financial impact of different prevalence levels of severe tail lesions (STL) during the finisher stage associated with changes in average daily gain (ADG) in farrow-to-finish pig farms. METHODS: Prevalence of STL was estimated for 31 farrow-to-finish pig farms. Regression tree analysis was used to identify a threshold for STL associated with differences in ADG. Then, a financial analysis was carried using the Teagasc Pig Production model. RESULTS: A threshold of ≥0.86% prevalence of STL was associated with a 4.8% decrease in ADG which translated into pigs requiring 7 days more to reach target slaughter weight than in farms below the threshold. Reduced ADG meant that farms with higher prevalence of STL used 3.6% more weaner and 1.4% more finisher feed per year increasing feed costs by 1.5%. This reduced mean annual farm profit by 15.1% in farms with higher prevalence of STL. CONCLUSIONS: Our results provide an indication of the financial effects of STL in intensive pig production systems. The identified threshold for the prevalence of STL could provide a tangible target for farmers to focus on in developing strategies to reduce tail lesions and allow farmers to complete a cost benefit analysis of controlling STL.

Associations between animal and herd management factors, serological response to three respiratory pathogens and pluck lesions in finisher pigs on a farrow-to-finish farm.

BACKGROUND: Serological screening is a common method to monitor antibody response to pathogen exposure, but results could vary due to several factors. This study aimed to quantify animal and management related factors associated with variation in antibody levels in finisher pigs at slaughter, in an Irish farrow-to-finish farm endemically infected with Actinobacillus pleuropneumonia (App), Mycoplasma hyopneumoniae (Mhyo) and swine influenza virus (SIV). A second objective was to estimate differences in antibody levels in pigs presenting pluck lesions. This was an observational study whereby pigs were managed as per routine farm practice. Data on sow parity, number of born alive (NBA) pigs per litter, cross-fostering status, birth and weaning body weight were recorded from 1016 pigs born from one farrowing batch. At slaughter, blood samples were collected for serological analysis and pigs were inspected for presence of enzootic pneumonia (EP)-like lesions, pleurisy, pericarditis and heart condemnations. Pigs were retrospectively classified into three production flows, depending on time spent in each production stage: flow 1 (F1; pigs followed the normal production flow); flow 2 (F2; pigs which were delayed by 1 week from advancing forward); and flow 3 (F3; pigs delayed by > 1 week from advancing forward). A nested case-control design was applied by matching pigs from each flow by sow parity, birth weight and NBA. RESULTS: Pigs born from primiparous sows had higher antibody levels for App than those born to parity ≥5 sows (P < 0.05) and there was no association between any of the pathogens investigated and other early life indicators (P > 0.05). Pigs in F1 had lower antibody levels for App but higher antibody levels for SIV than F2 and F3 pigs (P < 0.05). There was no association between pluck lesions and respiratory pathogens (P > 0.05), except for increased antibody levels for Mhyo when EP-like lesions were present (P = 0.006). CONCLUSION: Results indicate that offspring from primiparous sows develop higher antibody levels for App IV toxin when exposed to this disease and that enforcement of a strict all-in/all-out production system would reduce on-farm disease circulation. A high percentage of pigs were affected with EP-like lesions which were associated with higher antibody levels for Mhyo.

A cross-sectional survey on respiratory disease in a cohort of Irish pig farms.

BACKGROUND: Respiratory disease is one of the most important factors impacting pig production worldwide. There is no available information on the prevalence of key pathogens implicated in Irish pig production. The objective of this study was to describe the prevalence of pleurisy, pneumonia, lung abscesses, pericarditis and liver milk spots in finisher pigs of a cohort of Irish pig farms, and to describe the seroprevalence of: influenza A virus (IAV), porcine reproductive and respiratory syndrome virus (PRRSv), Mycoplasma hyopneumoniae (Mhyo) and Actinobacillus pleuropneumoniae (APP). RESULTS: In brief, 56 farrow-to-finish farms (29% of the Irish breeding herd) were enrolled in the study in 2017. Data on lungs, heart, and liver lesions were assessed for each farm at slaughter. An average of 417 (range 129-1154) plucks per farm were assessed for pleurisy, pneumonia, lung abscesses, pericarditis, and liver milk spots. Blood samples from 32 finisher pigs were collected at slaughter for each farm. The observed prevalence of pleurisy and pneumonia was one of the lowest reported in similar studies in Europe (13 and 11% estimated average within farm, respectively). Pleurisy lesions were mostly moderate and severe. Pneumonia lesions affected a low level of lung surface (5.8%). Prevalence of pericarditis was mid-high (8%) and the prevalence of liver milk spots was high, with an average of 29% of the livers affected. For serology, 78.6% of the farms were positive for IAV, 50% were positive for PRRSv, 71.4% were positive for Mhyo, and 98.2% were positive for APP. Influenza virus was the main pathogen associated with pleurisy (P < 0.001) and Mhyo was the main pathogen associated with pneumonia (P < 0.001) and pericarditis (P = 0.024). CONCLUSIONS: Farms affected with pleurisy had moderate to severe lesions. Farms affected with pneumonia had mild lesions, which could be the effect of the generalised use of Mhyo vaccination in piglets. The seroprevalence of IAV, PRRSv, Mhyo and APP in the present study sample is similar to or lower than in other European countries. Further research on the PRRSv and APP strains circulating in Ireland is necessary to support the design of national or regional control plans.

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.

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 DDDANED (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.

Current antimicrobial use in farm animals in the Republic of Ireland.

Antimicrobial resistance has been recognised as one of the most difficult challenges facing human and animal health in recent decades. The surveillance of antimicrobial use in animal health plays a major role in dealing with the growing issue of resistance. This paper reviews current data available on antimicrobial use in farmed animals in the Republic of Ireland, including each of the major livestock production sectors; pigs, poultry, dairy, beef and sheep. A systematic literature search was conducted to identify relevant published literature, and ongoing research was identified through the network of authors and searches of each of the research databases of the main agriculture funding bodies in Ireland. The varying quantities and quality of data available across each livestock sector underlines the need for harmonisation of data collection methods. This review highlights the progress that has been made regarding data collection in the intensive production sectors such as pigs and poultry, however, it is clear there are significant knowledge gaps in less intensive industries such as dairy, beef and sheep. To comply with European regulations an antimicrobial data collection system is due to be developed for all food-producing animals in the future, however in the short-term surveillance studies have allowed us to build a picture of current use within the Republic of Ireland. Further studies will allow us to fill current knowledge gaps and build a more comprehensive overview of antimicrobial use in farm animals in Ireland.