Quantitative analysis of antibiotic usage in British sheep flocks

Davies, Peter N.; Remnant, John; Green, Martin J.; Gascoigne, Emily; Gibbon, Nick; Hyde, Robert; Porteous, Jack R; Schubert, Kiera; Lovatt, Fiona; Corbishley, Alexander

doi:10.1136/vr.104501

Cited by 41 publications

(54 citation statements)

References 13 publications

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“…When applied to the complete Irish AMU dataset, the seven indicators produced similar results. All AMU indicators showed similar right skewed distributions, as reported in other studies in pigs (54), in cattle (55) and in sheep (56), indicating a distinct subset of the population with high AMU. The action zone, which, for the purpose of this study consisted of the 17 farms with the highest AMU, was broadly conserved.…”

Section: Discussionsupporting

confidence: 84%

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

et al. 2020

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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.

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Section: Discussionsupporting

confidence: 84%

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

et al. 2020

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“…prevalence of penicillin resistance in international surveillance of S. aureus from other host species in Europe, including cattle (25% resistance; [22]), dogs (65.2% resistance; [23]) and people (78% resistance in nasal commensal S. aureus; [24]). Penicillin is among the most widely used antimicrobials in British sheep flocks [25], and remains the drug of first choice for bacterial infections in food-producing animals, including sheep, in Norway [26]. Our data provide no reason to suggest any change to this practice.…”

Section: Plos Onementioning

confidence: 74%

Antimicrobial resistance in ovine bacteria: A sheep in wolf’s clothing?

et al. 2020

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Background To monitor the prevalence of antimicrobial resistance (AMR), methods for interpretation of susceptibility phenotypes of bacteria are needed. Reference limits to declare resistance are generally based on or dominated by data from human bacterial isolates and may not reflect clinical relevance or wild type (WT) populations in livestock or other hosts. Methods We compared the observed prevalence of AMR using standard and bespoke interpretations based on clinical breakpoints or epidemiological cutoffs (ECOFF) using gram positive (Staphylococcus aureus) and gram negative (Escherichia coli) bacteria from sheep as exemplars. Isolates were obtained from a cross-sectional study in three lowland sheep flocks in Scotland, and from a longitudinal study in one flock in Norway. S. aureus (n = 101) was predominantly isolated from milk or mammary glands whilst E. coli (n = 103) was mostly isolated from faecal samples. Disc diffusion testing was used to determine inhibition zone diameters, which were interpreted using either clinical breakpoints or ECOFF, which distinguish the bacterial wild type population from bacteria with acquired or mutational resistance to the compound of interest (non-wild type). Standard ECOFF values were considered as well as sheep-specific values calculated from the data using Normalized Resistance Interpretation (NRI) methodology. Results The prevalence of AMR as measured based on clinical breakpoints was low, e.g. 4.0% for penicillin resistance in S. aureus. Estimation of AMR prevalence based on standard ECOFFs was hampered by lack of relevant reference values. In addition, standard ECOFFS, which are predominantly based on human data, bisected the normal distribution of inhibition zone diameters for several compounds in our analysis of sheep isolates. This contravenes recommendations for ECOFF setting based on NRI methodology and may

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“…of antibiotic use in sheep 16 . Despite the poor natural immune response of sheep to footrot, vaccination does initiate immunity 17 to homologous serogroups 18,19 .…”

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confidence: 99%

Serogroups of Dichelobacter nodosus, the cause of footrot in sheep, are randomly distributed across England

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Monaghan

Green

et al. 2020

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We present the largest and most representative study of the serological diversity of Dichelobacter nodosus in England. D. nodosus causes footrot and is one of the top five globally important diseases of sheep. The commercial vaccine, containing nine serogroups, has low efficacy compared with bivalent vaccines. Our aim was to investigate the prevalence and distribution of serogroups of D. nodosus in England to elucidate whether a bivalent vaccine could protect the national flock. Farmers from 164 flocks submitted eight interdigital swabs from eight, preferably diseased, sheep. All serogroups, A–I, were detected by PCR in 687/1150 D. nodosus positive swabs, with a prevalence of 2.6–69.3% of positive swabs per serogroup. There was a median of two serogroups per flock (range 0–6). Serogroups were randomly distributed between, but clustered within, flocks, with 50 combinations of serogroups across flocks. H and B were the most prevalent serogroups, present in > 60% of flocks separately but in only 27% flocks together. Consequently, a bivalent vaccine targeting these two serogroups would protect 27% of flocks fully (if only H and B present) and partially, if more serogroups were present in the flock. We conclude that one bivalent vaccine would not protect the national flock against footrot and, with 50 combinations of serogroups in flocks, flock-specific vaccines are necessary.

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Quantitative analysis of antibiotic usage in British sheep flocks

Cited by 41 publications

References 13 publications

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

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

Antimicrobial resistance in ovine bacteria: A sheep in wolf’s clothing?

Serogroups of Dichelobacter nodosus, the cause of footrot in sheep, are randomly distributed across England

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