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Preventive Veterinary Medicine 104 (2012) 34– 43
Contents lists available at SciVerse ScienceDirect
Preventive Veterinary Medicine
jo u rn al hom epage : w ww.elsev ier .com/ locate /prevetmed
onitoring of antibiotic consumption in livestock: A Germaneasibility study
oswitha Merlea,∗, Peter Hajekb, Annemarie Käsbohrerc, Christine Hegger-Gravenhorsta,vonne Mollenhauera, Matthias Robanusb, Fritz-R. Ungemachb, Lothar Kreienbrocka
University of Veterinary Medicine, Department of Biometry, Epidemiology and Information Processing, WHO-Centre Veterinary Public Health, Buenteweg 2,-30559 Hannover, GermanyUniversität Leipzig, Faculty of Veterinary Medicine, Institute for Pharmacology, Pharmacy and Toxicology, An den Tierkliniken 15, D-04103 Leipzig,ermanyFederal Institute for Risk Assessment, Department for Biological Safety, National Reference Laboratory for Antimicrobial Resistance, Diedersdorfer Weg 1,-12277 Berlin, Germany
r t i c l e i n f o
rticle history:eceived 17 January 2011eceived in revised form 24 October 2011ccepted 30 October 2011
eywords:etracyclinesacrolides
luoroquinolonesattleigsaily dose
a b s t r a c t
Every application of antibacterial drugs in veterinary medicine may encourage selectionfor resistant bacteria. In Germany no valid data are available which would be suitable for aspecies specific estimation of drug consumption especially regarding food producing ani-mals. Therefore, a representative monitoring of consumption of antibacterial drugs in foodproducing animals should be implemented.
As a first step, a feasibility project was conducted to identify the technical preconditionsand develop a concept for a regular monitoring system within Germany as a country witha non-central federal state system. The data were collected via the forms obligatory byGerman law concerning the treatment of animals and the delivery of animal drugs to theanimal owners by the veterinarian. 24 veterinary practices and 65 farmers were visited,and all applications of antibiotics to farm animals during the course of one year (September1, 2006 to August 31, 2007) were entered into a central database.
A total of 95,584 records were collected and analysed statistically. Consumption ofantibiotics was calculated in kg, but also the number of applications was analysed. Theconsumption of tetracyclines in kg reached 54.3% of all antimicrobial substances applied topigs, but only 25.7% of all doses applied to pigs were tetracyclines. For the farms’ data, thenumber of daily doses per animal year (DDay) was estimated based on the number of dailydoses recorded and on the number of animals kept in the farm.
Correct and detailed data regarding the structures of the farms as well as of veterinarypractices are necessary to estimate the consumption of antibiotics reliably. The proposedsystem is able to function as a monitoring system for antibiotic use in Germany, when themonitoring data are linked to the agricultural data (farm sizes) accounting for differencesbetween German regional agricultural and animal husbandry structures. Furthermore, the
results of the antibiotic use analyses may serve as basis to assess the results of the salesdata of the pharmaceutical industry. Results are comparable to the outcome of respectivesystems in other European countries, e.g. the Netherlands and Denmark, and therefore itwill contribute to a better understanding and development of strategies for the control ofantimicrobial resistances∗ Corresponding author. Tel.: +49 511 953 7970; fax: +49 511 953 7975.E-mail address: [email protected] (R. Merle).
167-5877/$ – see front matter © 2011 Elsevier B.V. All rights reserved.oi:10.1016/j.prevetmed.2011.10.013
on the European level.© 2011 Elsevier B.V. All rights reserved.
1. Introduction
The use of antibiotics includes a certain amount of riskregarding selection and transmission of resistant bacteria
terinary
R. Merle et al. / Preventive Ve(Schwarz and Chaslus-Dancla, 2001; Schwarz et al., 2001)and can promote the development of resistance reservoirs.Therefore, the selection for resistant bacteria is an increas-ing public health problem. Research has shown increasedresistance rates in pathogenic and commensal bacteria ofanimals related to antibiotic use (North and Christie, 1946;Linton, 1984; Aarestrup, 1999; Teuber, 2001; Harada andAsai, 2010). Bacterial resistances which emerge from muta-tion and spread of these bacteria or can be acquired bytransmission of genetic information via plasmids or othergenetic structures has been linked to the amount of antibi-otics used (Harada and Asai, 2010).
Stakeholders of OIE and WHO therefore recommend torecord the amount of antibiotics in livestock (Nicholls et al.,2001; WHO, 2003, 2004). The European Union is fundingprogrammes for the continuous evaluation and assess-ment of resistance rates and antibiotic use that highlightthe complex relations between antibiotic use and bacterialresistances (Anon., 2002). The Directive 2003/99/EC of theEuropean Commission (Anon., 2003) supports this neces-sity and lays down that the Member States have to carry outmonitoring of antibiotic resistance in zoonotic pathogens.
The European Medicines Agency (EMA) is responsiblefor the scientific evaluation of pharmaceutical productsdeveloped for use in the European Union.
EMA started the European Surveillance of VeterinaryAntimicrobial Consumption (ESVAC) project that coor-dinates the harmonization of collecting, collating andpublishing the data on sales of antibiotics taking intoaccount different national, regional and international levelsof legislation.
Some European Union Member States already imple-mented monitoring systems of antimicrobial resistancesand comprised a monitoring of antibiotic use in livestockbased on different strategies (Blix et al., 2007; Hammerumet al., 2007; Heuer et al., 2007; Bengtsson et al., 2009). TheDanish integrated antimicrobial resistance monitoring andresearch programme DANMAP was created in 1995 by theDanish Ministry of Food, Agriculture and Fisheries and theDanish Ministry of Health (2009a). Veterinary authoritiesas well as food and health authorities pursue commonlythe goal to evaluate comparable data of food producing ani-mals, food and humans including data of the consumptionof antimicrobial substances (Bager, 2000; Anon., 2009a).
Sweden introduced the “Swedish Veterinary Antimi-crobial Resistance Monitoring” (SVARM) in order to pointout the situation of antimicrobial resistances in veterinarypathogens. Data on the antibiotic use are evaluated rou-tinely (Bengtsson et al., 2009). In Sweden and Denmark,antibiotics are only available by prescription in the phar-macies.
In Norway (NORM/NORM-Vet, 2008c) as well as in theNetherlands (MARAN, 2008b) standardized data on theantibiotic use are centrally collected and also availablesince several years.
In Germany, veterinarians have the permission topurchase and administer drugs to livestock, and thus, vet-
erinarians usually deliver the drugs directly to the farmers.Farmers and veterinarians have to store documents ofdrug administration that include all required information(e.g. kind and number of animals, name and amount ofMedicine 104 (2012) 34– 43 35
drug, indication, dosage and treatment days) (Anon., 2008a,2009d). But these documents are only stored at the veteri-nary practices and a central evaluation is not implementedup to now. The veterinarians’ dispensaries are controlledregularly by the federal states’ authorities. These controlsonly concern correctness and completeness, and results arenot exchanged between states or reported to the federalauthorities. Thus, data on the consumption of drugs at theveterinary level exist, but are not collected in any centraldatabase until now.
In Germany, the report of veterinary use of antibiotics inGERMAP is based on a spot survey regarding the purchasebehaviours of veterinarians in 2003 and 2005. This reportincludes data on amounts only without the specificationof species, indication, application method, dosage or dura-tion of treatment. Thus, its value regarding food quality andsafety is limited. Even the consumption data of the Federa-tion of Animal Health from 1997 do not include informationon the species specific application of the applied antibiotics(Ungemach et al., 2006). Since the beginning of 2011, allpharmaceutical enterprises have to report their sales dataper truncated ZIP-Code to the Federal Office of ConsumerProtection and Food Safety (BVL) (DIMDI-AMV, 2010). Firstreporting will take place in 2012 for 2011.
Therefore, centralised data collections on the sales ofantibiotics shall be supplemented by a monitoring systemor longitudinal studies that provide more detailed infor-mation on the antibiotic use. As German veterinarians arepermitted to order and deliver drugs on their own, a Ger-man monitoring system has to account for these Germanconditions—including the federal state system. Therefore,in this feasibility study, a system to collect data on theantibiotics consumption in farm animals in Germany basedon drug administration records was developed and tested.
The feasibility was tested regarding data quality (com-pleteness and plausibility) as well as data availability(access to data, time consumption, etc.) by animal speciesand when data were evaluated in farms or in veterinarypractices, respectively.
The objectives of the data analysis were the summaryof the consumption of antibiotic substances in kg per farmsand per district as well as the calculation of the averagenumber of treatments per animal and year within a farmor a district in order to gain results that can be comparedbetween regions and years. Data should also allow com-parisons between different animal species, animal groups,administration routes and substance groups. The evaluateddata were tested, if they fulfilled these requirements esp.regarding differences between data from farms and frompractices.
2. Materials and methods
2.1. Veterinary practices and agricultural farms
Veterinary practices treating farm animals (recommen-dation of local veterinary chamber, n = 99) in five districts
in the federal state Lower Saxony, Germany, were askedby mail and telephone for participation. Twenty-four vet-erinary practices (practices) took part at the study on avoluntary basis. All practices treated pigs and cattle and
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ome of them also poultry (10 practices). Data from poultryre not presented in this paper. Following the veterinar-ans’ reports collected by a questionnaire, approximately28 cattle farms and 851 pig farms were served by theractices included in this study.
Furthermore, 65 agricultural farms (farms) – 39 farmseeping pigs, 18 farms keeping cattle and 8 farms keepingoth pigs and cattle – in one district in the federal stateorth Rhine-Westphalia participated. These farms weresked for voluntary participation by veterinarians of theocal breeding organisation for cattle and the veterinaryealth service for pigs.
.2. Data sources
The study data was derived from the drug delivery orpplication records of farm animals, which are statutoryocuments for veterinarians and farmers (Anon., 2008a,009d). These documents include information on the datef delivery/application, number, animal species, produc-ion type and identity of the animals, drug’s name andolume, dosage per animal and day as well as treatment’suration.
Data on farm attributes including animal numbers bypecies in the study districts were included into the analy-es (Statistische Ämter des Bundes und der Länder, 2008).or the study practices structural data (number of veteri-arians, number of consulted farms, animal species, etc.)ere collected through a questionnaire. The structures of
he study farms (kind and number of animals) were noteduring farms’ visits.
.3. Data recording
A study database was created including all variablesemanded by national law (Anon., 2009d). This databaseffers online access and an online form for entering data. Ifnline access was not available, data were recorded offlinen study laptops and transferred into the central databasefterwards.
All records from the study practices and study farmsetween September 1, 2006 and August 31, 2007 werentered manually into the database by the study person-el. Data were checked automatically for completenessefore storage. Incomplete records were corrected on siter else labelled as “incomplete”. Complete records passedhrough a plausibility check of dosage for the entered ani-
al species and the route of administration to avoid typingrrors. In case of strong discrepancies (factor 10 or more)he record was regarded as implausible, and the typistas asked for correction. For this plausibility check, the
tudy database was linked to the database “VETIDATA”http://www.vetidata.de) which offers information on alleterinary drugs registered in Germany including the sub-tance(s) (Ungemach et al., 2001). With this information forach of the veterinary antibiotics applied, the used dosage
or each drug was converted into the amount of activeubstances. Recommended dosages for all substances wereefined on the basis of the product information and pub-ished data.
Medicine 104 (2012) 34– 43
The database had strict access protection and locallystored data was encoded. Farmers’ and veterinarians’ datawere kept in confidence by pseudonymisation.
2.4. Data analysis
Data were imported into Access® (Access 2003,Microsoft Corp., Redmond, WA, USA) and analysed statis-tically using SAS®, Version 9.1 TS Level 1M3 (SAS InstituteInc., Cary, NC, USA). Data from skewed distributions wereconverted into the logarithmic scale. To display the resultsin tables and figures, these logarithmic values were recon-verted and presented as geometric means and geometricstandard deviations on the original scale. With the sameprocedure an upper and a lower (geometric) limit were cal-culated (Kirkwood, 1979). Statistical tests (chi-square-test)were performed using the SAS-procedures FREQ.
Every record displays the prescription of one substanceto a certain number of animals and for a certain treatmentperiod (up to 7 days). Continued treatment of the same ani-mals required a new prescription and thus a new recordwhich is not linked to the first one. Several substancesper drug were stored in separate records and thereforeregarded as several treatments.
VETIDATA (Ungemach et al., 2001) was used to calculatethe amount of free substance (in kg) per record based onthe drug amount administered per record. Afterwards theamounts were summarized in the substance classes.
In analogy to Jensen et al. (2004) the number (n) ofdaily doses was estimated by dividing the free substanceby the product of the dosage recommended in the sum-mary of product characteristics (in mg/kg animal weight;respecting the administration route) and the average ani-mal weight (Eq. (1)). Because of the variation of therecommended dosage in different products for the samesubstance, a recommended dosage was fitted for each sub-stance per animal species and per administration route andused through the calculations in the project. This defineddaily dosage for the substance was the basis to calculate thenumber (#) of daily doses. The average animal weight perspecies and animal age group was determined accordingto (Anon., 2008b): piglet: 12.5 kg, weaner: 25 kg, fattener:70.2 kg, sow: 220 kg, calf: 80 kg, heifer: 300 kg, cow: 600 kg,bull: 600 kg, and cattle: 600 kg.n daily doses
= free substance in mgrecommended dosage × average animal weight
(1)
This variable was calculated for each record and then sum-marized by the animal groups over the whole time period.
The number of daily doses per animal year (n DDay) wasestimated only for data from farms by summarizing then daily doses per animal group (piglets, fatteners, sows,calves, dairy cattle, beef cattle) over the whole study periodand dividing this sum by the respective sum of farms’animals (population size) for each animal group (Anon.,2008c):
n DDay = n daily dosespopulation size
(2)
Local applications – except intramammary therapy –were excluded as well as data with missing animal weight,
R. Merle et al. / Preventive Veterinary Medicine 104 (2012) 34– 43 37
Table 1Consumption of active substances by specified substance groups and species (n applications: Eq. (3)) from 65 cattle and pig farms in North Rhine-Westphaliaand 24 veterinary surgeries in Lower Saxony from September 1, 2006 through August 31, 2007.
Substance group Pigs Cattle
Amount Applications Amount Applications
kg % Number % kg % Number %
Macrolides 1636 5.17 3,813,561 13.26 98 2.44 36,320 2.71Beta-lactames 7275 23.01 6,354,797 22.09 663 16.45 212,480 15.83Aminoglycosides 252 0.80 1,004,626 3.49 120 2.98 124,029 9.24Fenicoles 29 0.09 43,051 0.15 28 0.70 12,832 0.96Tetracyclines 17,156 54.25 7,391,674 25.69 1940 48.12 363,979 27.12Lincosamides 298 0.94 1,065,198 3.70 19 0.47 29,781 2.22Polypeptides 619 1.96 3,249,793 11.30 35 0.86 46,785 3.49Sulfonamides 702 2.22 1,032,998 3.59 27 0.66 3989 0.30Fluoroquinolones 22 0.07 263,435 0.92 19 0.48 40,093 2.99Cephalosporines 8 0.03 200,414 0.70 21 0.51 42,590 3.17
28,835
19,143
67,525
Pleuromutilines 310 0.98 8Sulfonamide and Trimethoprim 3312 10.47 3,5All 31,622 100.00 28,7
because local applications were not dosed in mg/kg bodyweight. All in all, 6061 datasets were included in this anal-ysis. As the DDay was calculated for a one-year period, andas finisher pig’s lifetime is around five months, the DDay
per animal year is related to several pigs. The variable DDay
represents the calculated average treatment frequency peranimal and year which was calculated in a standardizedway from the amount of drugs administered in that animalpopulation.
To summarize the treatments for all data including localapplications and data with missing animal weight, thenumber (n) of applications was calculated by multiplyingthe number of animals treated by the treatment days (asdocumented):
n applications = n animals treated × n days of treatment(3)
To investigate differences between the administrationroutes (parenteral, oral and local), applications were calcu-lated separately by administration route.
To assess the feasibility of the two approaches, the fol-lowing hypothesis was tested by a formal statistic test:
The percentage of incomplete records did not differbetween data from farms and from practices (chi-square-test).
Descriptive statistics were used to investigate the fol-lowing aspects:
1. Differences between the substance groups regardingamount of active substances and n applications (per ani-mal species).
2. Differences between the amount of active substancesand n applications per substance group (per animalspecies).
3. Differences between the animal species regarding theamount of active substances and n applications per sub-stance group.
4. Differences between animal species of the administra-tion route regarding n applications.
5. Differences between animal species and animal groupsregarding DDay.
2.88 – – – –12.23 1061 26.32 429,111 31.98
100.00 4031 100.00 1,341,990 100.00
6. Differences between amount of active substances, napplications and DDay of the substance groups (per ani-mal species).
7. Differences in the distribution of substance groupsregarding the animal species and regarding the animalgroups.
8. Differences in the distribution of administration routes(oral, parenteral) regarding the animal groups.
Finally, the monitoring system was assessed for feasi-bility regarding
1. the calculation of DDay and2. the description, induction and generalisation of results
for larger regions.
3. Results
With 88,142 records from practices and 7450 recordsfrom farms, a total of 95,592 datasets formed the basis forthe further analyses of the data. In farms, a median of 77records were entered per farm, in practices the medianwas 3803 records per practice. The percentage of incom-plete records was significantly higher in farms (9.4%) thanin practices (3.1%) (chi-square test, p < 0.0001).
The n daily doses could not be calculated accounting forall records (Eq. (1)). Records with local applications or nonassessable animal weights were excluded as no informa-tion on the weight was available or was not relevant forlocal applications. A higher number of valid records origi-nated from cattle (n = 52,712) than from pigs (n = 39,436),although the n daily doses of pigs (n = 987,429) was about35-fold higher than that of cattle (n = 28,108).
In pigs and cattle, tetracyclines were the most fre-quently used substances, in pigs followed by beta-lactames,in cattle by the trimethoprim/sulfonamide group (Table 1).Due to different dosages of the individual substances, the
percentages of the consumption in kg and of the n appli-cations varied between the substance classes (Eq. (3)).The proportion of applications that were tetracyclines waslower than the proportion of consumption in kg that were
38 R. Merle et al. / Preventive Veterinary Medicine 104 (2012) 34– 43
Table 2Consumption of antimicrobials in amount and number of applicationsby route of administration and species from 65 cattle and pig farms inNorth Rhine-Westphalia and 24 veterinary surgeries in Lower Saxonyfrom September 1, 2006 through August 31, 2007.
Pigs Cattle
Parenteral Amount kg 778 428% 2.46 10.61
Applications Number 2,390,100 231,826% 8.31 17.27
Oral Amount kg 30,810 3277% 97.43 81.29
Applications Number 26,356,654 1,011,100% 91.62 75.34
Local Amount kg 33 326% 0.11 8.09
Applications Number 18,741 98,930% 0.07 7.37
Not specified Amount kg 0.7 0.2% 0.00 0.01
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Table 3Average number of daily doses per group and administration route from65 cattle and pig farms in North Rhine-Westphalia and 24 veterinarysurgeries in Lower Saxony from September 1, 2006 through August 31,2007.
Oral Parenteral Intra-mammary
Piglets 53.21 12.45 –Fattening pigs 27.93 1.02 –Sows 1.08 1.83 –Calves 7.61 0.91 –Dairy cattle – 1.29 1.48Non dairy cattle – 0.09 –
Applications Number 2030 134% 0.01 0.01
etracyclines, whereas the proportions of application thatere macrolides or polypeptides were higher than the pro-ortions of consumption in kg that were macrolides orolypeptides.
Ninety-two percent of all applications to pigs weredministered orally (Table 2). In cattle, the fraction of drugspplied orally was 75.3%, followed by 17.3% parenteral and.4% local applications.
The DDay was calculated for those farm data where dailyoses could be calculated (6061 records, see Section 2: onlyata from farms, Eq. (2)). Pigs were treated more frequentlyhan cattle. Most DDay were given to young animals (DDay:.33 for calves, 60.86 for piglets and 28.60 for fatteningigs), while sows had only 2.89, dairy cows 2.75 and beefattle 0.08 DDay.
As shown in Table 1, tetracyclines had the highestmount of consumption for pigs and cattle—and for pigslso the highest n applications. But for DDay calculations,s displayed in Figs. 1–6, other substance groups showedigher results (except for sows). Differences in the distri-ution of DDay by substance groups were observed not onlyegarding the animal species but also regarding the animalroups. In piglets, fattening pigs and calves, highest DDay
bserved was in the sulfonamides and trimethoprim group.he DDay of macrolides was also high in piglets and fatten-ng pigs. Cephalosporines and fluoroquinolones had highDay in dairy cattle.
Regarding the administration route, the DDay confirmedhat piglets, fattening pigs and calves were treated mainlyrally, while parenteral application was common in sowsnd cattle. More than half of all applications to dairy cowsere applied into the mammary (Table 3).
. Discussion
Monitoring of antibiotic consumption in livestock is a
ecessary tool for a better understanding of the develop-ent and spread of antimicrobial resistance. To improveontrol of resistant bacteria, this should be regular partf a national surveillance system. A concept for a German
DDay: n animal daily doses per animal year; treatment frequency esti-mated (Eq. (2)).
monitoring system was tested within this feasibility study.As the study presented investigated the feasibility of amonitoring system, focus was laid on the possibilities ofproper description, induction and generalisation of resultsfor larger regions and less on the results obtained.
The implementation of a monitoring system in Germanyrequires special measures, due to the federal structure ofthe country as well as to the veterinarians’ permissionto dispense drugs. Therefore, the study’s data acquisi-tion differed from established monitoring systems in othercountries, e.g. Denmark (Anon., 2009a).
As the data recording via pharmacies or other cen-tral dispensary locations is not suitable for Germany, therecording via practices and via farms were tested. Bothmethods were successful, because data could be obtained,and yielded into a sufficient amount of valid data records.The desired outcome (amount per substance, n daily doses,DDay) could be calculated for farms completely and forpractices partly.
In practices, complete and plausible records could begained shortly. Due to the legal compliance records usuallyare complete in all practices, so that a selection bias is notsuggested. As most of the practices use software, data eval-uation can be automated via interfaces between softwareand database in future. Farms do not offer this opportunitybecause most of the farms are not using electronic systemsfor storing this type of information. In other countries, e.g.the Netherlands and France, data evaluation in farms is onlyused for studies that supplement monitoring systems onantimicrobial sales (Anon., 2008b; Moulin et al., 2008).
The percentage of incomplete or implausible datasetswas higher in farms than in practices (9.4% in farms, 3.1%in practices). The reasons could not be fully explained,because farmers stored copies from the veterinarians’ doc-uments, and therefore, the data sources did not really differ.The higher percentage of invalid datasets in farms mightbe due to the high percentage of handwritten documenta-tion. Similar differences regarding completeness were seenbetween handwritten and electronic documentation (datanot shown) in the practices. From the practical point ofview the data recording via practices that administer theirdata electronically is preferable as long as farmers do notimplement such a system.
Livestock husbandry differs between cattle and pigs.Nevertheless the monitoring system tested fitted for bothspecies regarding access to data and calculation of DDay.
R. Merle et al. / Preventive Veterinary Medicine 104 (2012) 34– 43 39
. (2)) fro007.
Fig. 1. Antibiotic use on piglets in daily doses per animal year (DDay) (Eqsurgeries in Lower Saxony from September 1, 2006 through August 31, 2
The data offer many possibilities of analyses. The speci-fication of animal numbers and treatment days allows thecalculation of the amount applied, number of applications,dose as well as dosage. These variables can be summarized
by different criteria, e.g. the animal species, the indicationor the administration route.DDay is useful to observe changes from year to year– even considering changes of the population size – and
Fig. 2. Antibiotic use on sows in daily doses per animal year (DDay) (Eq. (2)) frosurgeries in Lower Saxony from September 1, 2006 through August 31, 2007.
m 65 cattle and pig farms in North Rhine-Westphalia and 24 veterinary
between regions or countries. It can be estimated, evenif less detailed information is available, because it isestimated based on the substance amount as well as onaverage animal weights and dosages. In our study this
measure estimated using on-farm records only, becausedata on farm size reflecting the number of animals undercare were missing in the practices’ data. Most farm datawere valid and complete (81.3% of oral, parenteral andm 65 cattle and pig farms in North Rhine-Westphalia and 24 veterinary
40 R. Merle et al. / Preventive Veterinary Medicine 104 (2012) 34– 43
F Day) (Ev gust 31
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ig. 3. Antibiotic use on fattening pigs in daily doses per animal year (Deterinary surgeries in Lower Saxony from September 1, 2006 through Au
ntramammary applications of on substance of farms), andeasons for bias by missing data could not be identified.
hus, systematic differences between regions or years areot expected regarding miscalculation of DDay. For theuture, data from practices shall include information onarm sizes to negotiate this disadvantage.
ig. 4. Antibiotic use on calves in daily doses per animal year (DDay) (Eq. (2)) frourgeries in Lower Saxony from September 1, 2006 through August 31, 2007.
q. (2)) from 65 cattle and pig farms in North Rhine-Westphalia and 24, 2007.
If the district’s average is not estimated properly, asystematic miscalculation of the n daily doses and DDay
may occur (overestimation, e.g. if the real animal weightwas higher than the expected average animal weight;underestimation, e.g. if the real dosage was higher thanthe expected recommended dosage). But for comparison
m 65 cattle and pig farms in North Rhine-Westphalia and 24 veterinary
R. Merle et al. / Preventive Veterinary Medicine 104 (2012) 34– 43 41
Fig. 5. Antibiotic use on dairy cows in daily doses per animal year (DDay) (Eq. (2)) from 65 cattle and pig farms in North Rhine-Westphalia and 24 veterinarysurgeries in Lower Saxony from September 1, 2006 through August 31, 2007.
Fig. 6. Antibiotic use on beef cattle in daily doses per animal year (DDay) (Eq. (2)) from 65 cattle and pig farms in North Rhine-Westphalia and 24 veterinarysurgeries in Lower Saxony from September 1, 2006 through August 31, 2007.
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urposes this miscalculation can be disregarded, if thealculation conditions (e.g. the average weight) are nothanged and thus the relation between the two valuesemain stable with or without error. For monitoring pur-oses the differences between groups (e.g. regions) areore important than absolute numbers. The interregional
omparison and the quantification of changes (e.g. follow-ng changes of legal rules) will be in the focus in the future.herefore, the declaration of DDay for pigs is useful, evenf their production cycle is less than one year. For pigs,he DDay is given for each fattening place and thus will beomparable between years and regions. If for communica-ion purposes the results per pig (division by 3) are used,he differences should be highlighted. Otherwise, misinter-retation might be encouraged giving animal species withhort life spans lower records.
In contrast to the detailed information gathered withinur study, sales data cannot provide sufficient informationo estimate DDay. But sales data can supplement our studyata following the concepts proposed in this paper. Jointata analysis can result in a reliable estimation of DDay forermany. In the Netherlands, such data were successfully
inked and analysed (Anon., 2008b).The n daily doses as well as DDay were generated accord-
ng to the methods used in the Netherlands (Anon., 2008b)nd Denmark (Anon., 2009c). This is a first step to enable
comparison between the countries with differences intructures.
Due to the different calculation method of dosagesbased on drugs in the Netherlands, based on substancesn our study), the results of DDay in our study differed tohat of the Dutch data. Therefore, the discussion of resultsocuses on trends instead of absolute numbers.
The results of DDay and the distribution of antibiotic useer substance group were similar to the published data ofhe Netherlands (Anon., 2008b) and of Denmark (Anon.,009a). In contrast to other publications and our results, inorway, beta-lactames and other substances predominatey far over tetracyclines (Anon., 2008c). It has to be con-idered that – corresponding to the Dutch methods – theDay must be regarded as “DDay per animal year”. But as
his parameter serves as comparative value between peri-ds or regions, the DDay fulfils its function although onenimal year includes more than one finisher animal andhe treatment frequency calculated per individual animals lower than the DDay calculated per year.
The high percentages of parenterally and locally appliedntibiotics in cattle compared to those of pigs reflect thatndividual therapy takes place only in cattle while pigsre treated mainly herd-wise. Oral application was byar higher in piglets and fattening pigs than parenteralpplication. These associations of species, indication,dministration route and substance are due to practicaleasons and are described in many reports on antimicrobialse (Anon., 2008c, 2009a,b).
As already mentioned, data of DDay per substance groupiffered slightly to the data of the Netherlands (Anon.,
008b). In our study, fluoroquinolones were used in dairyattle quite frequently, whereas in Dutch dairy herds theyre applied only seldom, while tetracyclines play a majorole. In piglets and fattening pigs, tetracyclines are alsoMedicine 104 (2012) 34– 43
applied more often in the Netherlands than in our study.Our study data showed a more frequent use of sulfon-amides and trimethoprim than the Dutch data. Presumingthat the health problems in the milk or meat productionlines are similar in both countries and that no severe ani-mal diseases occurred during this time period (time periodswere similar), these findings can be regarded as a hint todifferent prescription customs between the regions.
The data collected in this study can be considered asvaluable data which give already a quite important pictureon usage patterns in German husbandry of cattle and pigs.These data showed quite some similarities to the situationas described in other countries of the European Union andcan be used to give some input into the interpretation ofresistance data.
But overall, the comparison between several Europeancountries still is a task for the future, because until nowevery country has a similar but slightly different reportingsystem. Therefore, the calculation of DDay has to be stan-dardized and the dosage recommendations – which formthe basis for the DDay – have to be harmonized.
Most of the European countries, e.g. Norway andSweden, report the use of antimicrobials as sales data inkg active substance (Anon., 2008c, 2009b). A harmonizedanalysis parameter like DDay would be useful to enhancecontrol of antimicrobial resistances on the European level.
To estimate the DDay of a region reliably, representativestudy farms have to be selected and complete data on thefarms’ structures of the respective region are necessary. Toprovide for a successful monitoring, the permanent accessto agricultural data shall be guaranteed.
The monitoring of antibiotic use will serve to investi-gate associations between antibiotic use and the resistancesituation. Even if the impact of associations should be inter-preted carefully and should not be regarded per se as causalrelationships, the identification of special risks concern-ing the development of resistances may lead to concertedmeasures or the development of management recommen-dations. At the same time, the general restriction or evenprohibition of antibiotic use in livestock can be counter-acted by a prudent monitoring and surveillance system.
The successful communication of these objectives toinvolve all related stakeholders and the public is one ofthe main challenges in the course of the implementationof a monitoring and surveillance system. In Germany, thedata evaluation shall be carried out in farms and practiceswhich take part voluntarily. This feasibility study will befollowed by a pilot study including several districts that arerepresentative for a certain German region. For 2011, thefirst data of the DIMDI-AMV will be available (Anon., 2010).Thus, the results of the pilot study will help to analyse thedata of the DIMDI-AMV.
Additional actions are in preparation in order to harmo-nize monitoring systems of antibiotic use on a Europeanlevel.
5. Conclusion
In Germany, the recording of the antibiotic use in live-stock is possible via practices and via farms. To calculatecomparable and communicable results like DDay, access
terinary
R. Merle et al. / Preventive Veto current and detailed data of agricultural structures ofstudy farms, but also of the whole study region is nec-essary. The analyses of the study data showed results ofmasses and DDay which correspond to published data ofother countries (Anon., 2008b, 2009a,b). For future moni-toring, electronic transmission of practice data as well asthe inclusion of the related farms’ data will be consid-ered. Alternatively, the data recording can be affected bythe farms, corresponding to the Dutch study design (Anon.,2008b). Co-analyses of monitoring data and sales data ofthe pharmaceutical industry can output results that displaythe situation of antibiotics’ use in Germany reliably.
Acknowledgments
During the work on this paper our co-author, colleagueand friend Fritz-Rupert Ungemach sadly passed away. Weacknowledge this paper in deep and honest memory to hispowerful spirit. The project was not possible without him.
In addition we want to acknowledge the veterinarychamber of Lower Saxony and the veterinary authoritiesin the participating districts for assistance in the recruit-ment of farms and practices. Furthermore, we thank thefarm owners and the veterinarians who provided their data.Thanks to the editors of MARAN-2007 – namely Prof. Dr. D.Mevius and Dr. I. van Geijlswijk – for providing detailedinformation for the calculation of DDay in the Netherlands.
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