CODA -CERVA
Transcript of CODA -CERVA
CODA -CERVA Centrum voor Onderzoek in Diergeneeskunde en Agrochemie
Centre de Recherches et d’Etudes Vétérinaires et Agrochimiques
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Antimicrobial Resistance in indicator commensal bacteria
from livestock in Belgium:
Trend Analysis 2011-2013
Table of contents
Acknowledgments
I. Introduction and Objectives of the study
II. Material and Methods
A. Sampling methods
B. Isolation of the strains and susceptibility testing
C. Data used and data management
D. Statistical Methods
III. Results
A. Tables: sample size, Resistance prevalence + Confidence Intervals
B. Descriptive statistics and Trend Analysis/ bacteria /animal species:
1. E. coli
2. Enterococci
C. Multiresistance
1. E. coli
2. Enterococci
IV. Discussion: Summary of observed trends and Comments
V. Conclusion and Recommendations
Annexes:
1. List of Antimicrobial drugs tested and ECOFF values
2. Tables of outputs of the Multivariate models GEE- (E. coli)
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Acknowledgments:
This study was commissioned by the Federal Agency for the Safety of the Food Chain and
carried out in close collaboration with the Center for Statistics (CentStat, University of
Hasselt, Belgium http://www.uhasselt.be/censtat ) which developed the statistical models
adapted to the available data and the expected results. We are particularly thankful to Prof.
Marc Aerts and to Mr Stijn Jaspers for their personal contribution and their availability to
carry out this work.
We are also very grateful to other contributors for the exchange of the information and
comments during the analysis: Dr Katie Vermeersch (FAVV/AFSCA), Dr Pierre Wattiau and
Prof. dr Patrick Butaye (Bacteriology Dept, CODA/CERVA).
Jean-Baptiste HANON
Estelle Méroc
Yves Van der Stede
Unit Coordination of Veterinary Diagnostics –
Epidemiology and Risk Assessment
(CVD-ERA)
June 2014
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I. Introduction and Objectives of the study
This report summarises the results of the trend analysis of the data related to antimicrobial
resistance of three consecutive years (2011-2012-2013) regarding commensal intestinal flora
of several livestock categories in Belgium. The samples were taken from the following animal
categories/species:
- Veal calves
- Young Beef cattle
- Slaughter pigs
- Broiler chickens
Bacterial species which were included in the study are commensal Escherichia coli and
Enterococcus spp. (E. faecium and E. faecalis). E. coli are regarded as a general indicator for
resistance amongst Gram-negative bacteria while Enterococci are regarded as general
indicators for resistance amongst Gram-positive bacteria. Both types of bacteria can be
frequently isolated from all animal species and are therefore suitable for comparisons and
surveillance programmes.
During sampling, faecal material was taken at the slaughterhouse or directly at the farms
depending on the animal category. E. coli and Enterococcus spp. were isolated and thereafter
tested for their susceptibility to a panel of several antimicrobial substances/drugs (Annex 1)
For each bacterial species and each antimicrobial separately, the percentage of observed
resistant strains compared to the total number of tested isolates was calculated per year and
per animal category.
The objectives of this study were:
- To provide a trend analysis of this prevalence over the three consecutive years. The
results were compared for the three years and then analysed by appropriate statistical
methods to check whether the observed trends (increase or decrease) were significant
- To evaluate the level of multiresistance and its trend over the same period: using the
same data we calculated for each animal category the percentage of multiresistant
strains i.e. resistance to more than two antimicrobials (= at least three) by the same
strain, and we checked whether there was a significant trend over the three years
However, it is important to keep in mind that the trends described in this report are based
upon observations of 3 years only, which is a strict minimum. When analysing the Belgian data
of the coming years it will be possible to confirm or adjust these trends. On the other hand, we
may observe some trends in the future that could not be detected after only three years of
surveillance. In the EFSA report mentioned hereafter, trends for European countries are
analysed when data are available for at least 5 years.
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For more details about description and analysis of annual data in Belgium, please refer to
annual reports published by CODA-CERVA for the years 2011, 2012 and 2013 (author Prof.
dr Patrick Butaye):
- Antimicrobial resistance in commensal E. coli from poultry, pigs, cows and veal calves
- Antimicrobial resistance in commensal Enterococcus spp. from poultry, pigs, cows and
veal calves
Available at: http://www.coda-
cerva.be/index.php?option=com_content&view=article&id=121&Itemid=286&lang=en
For trends in other European countries please refer to the EFSA/ECDC summary report
published in March 2014:
Antimicrobial resistance in zoonotic and indicator bacteria for humans, animals and food in the
EU in 2012. EFSA Journal 2014 ; 12(3): 3590, 336pp., doi:10.2903/j.efsa.2014.3590
Available at: www.efsa.europa.eu/efsajournal
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II. Material and Methods
A. Sampling method
Samples of faeces were collected each year by veterinarians of the Federal Agency for Safety
of the Food Chain (AFSCA-FAVV) according to standardized technical sampling instructions
(PRI codes) as part of a nationwide surveillance programme. The same faecal samples were
used to produce isolates of E. coli and Enterococcus spp.
Samples were taken from the following categories of livestock species:
- Veal calves: young cattle kept in specialized units for fattening and slaughtered at an
average age of 8 months. In 2011 faecal samples were taken on the floor at the farm level
(PRI-516: 10 animals <7months/farm) while in 2012 and2013 the samples were taken
directly from the rectum of the animals at the slaughterhouse (PRI-036: 1 animal
sampled/farm)
- Beef Cattle (meat production): young animals (< 7months) from farms raising Beef cattle
for meat production. Faecal samples were taken from the floor at the farm (PRI-515:10
animals/sample/farm).
- Broiler chickens: samples were taken at the slaughter house (PRI-019: pairs of caeca
from 10 chickens /batch)
- Pigs: faecal samples of fattened pigs > 3 months were taken from the rectum at the
slaughter house (PRI-035: 1 animal /farm)
B. Isolation of the strains and susceptibility testing
Isolates of E. coli and Enterococcal strains were obtained from the faecal samples at the two
Regional laboratories ARSIA and DGZ. Isolation methods are described in annual reports and
were performed according to the SOP’s. The isolates were sent to the National Reference
Laboratory (CODA-CERVA) for susceptibility testing. Enterecoccal isolates were identified by
specific techniques t-DNA PCR. Susceptibility was tested by a micro-broth method following
the SOP of CODA-CERVA (SOP/BAC/ANA/11) as it is described in the annual reports. Two
different panels of antimicrobials were used based on the EFSA recommendations: one for E.
coli (Table A) and one for Enterococci (Table B). For each strain and each antimicrobial
substance, the Minimal Inhibitory Concentration (MIC) was read: MIC is defined as the lowest
concentration by which no visible growth could be detected. MICs were semi-automatically
recorded and exported to Excel files.
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Table A. Panel for E. coli
Symbol Antimicrobial
AMP Ampicillin CHL Chloramphenicol CIP Ciprofloxacin COL Colistin FFN Florphenicol FOT Cefotaxime GEN Gentamicin KAN Kanamycin NAL Nalidixic acid SMX Sulphonamide STR Streptomycin TAZ Ceftazidime TET Tetracycline TMP Trimethoprim
Table B. Panel for Enterococci spp.
Symbol Antimicrobial
AMP Ampicillin
CHL Chloramphenicol
CIP Ciprofloxacin
ERY Erythromycin
FFN Florfenicol
GEN Gentamicin
LZD Linezolid
SAL Salinomycin
STR Streptomycin
SYN Synercid (quinupristin/dalfopristin)
TET Tetracycline
VAN Vancomycin
C. Data used
The datasets for 2011, 2012 and 2013 were formatted in Excel and were provided by the
Department of Bacteriology of CODA/CERVA. They included identification of the samples
corresponding to each isolate recorded in the LIMS merged with the corresponding MIC value
for each tested antibiotic. After several steps of cross-checking and cleaning of the data, three
yearly distinct data sets were produced for each bacterial species, imported and analysed in
SAS 9.2 (data management). Emphasis was put on verifying that the animal category (species)
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of the sample was correct. If it could not be confirmed, the sample was exluded. The final
annual datasets contained the following fields:
- E. coli isolates:
- isolate identification number
- animal category
- sampling date
- MIC values for each of the 14 tested antimicrobials;
- Enterococci isolates:
- isolate identification number
- bacteria species (E. faecium / E. faecalis)
- animal category
- sampling date
- MIC values for each of the 12 tested antimicrobials.
D. Statistical Methods
All subsequent statistics were carried out using SAS 9.2 software. The R software was used
to plot on graphs some of the outputs from SAS (Multivariate models) and to calculate diversity
indices (entropy, weighted entropy)
1. Descriptive statistics:
Yearly data sets were merged in SAS to produce two distinct data sets: one for E. coli and one
for Enterococci. Quantitative MIC values were converted in binary qualitative values (Resistant
/Susceptible) based on the susceptibility breakpoints defined by the European Committee on
Antimicrobial Susceptibility Testing (EUCAST). The ECOFFs (Epidemiological cut-offs values)
were used in order to define strains as Resistant (R) or Susceptible (S). (Annex 1)
The observed number of resistant strains provides an estimate for p (the proportion of resistant
isolates) and its according standard deviation: sd (p). Therefore, for each animal category and
each year the proportion of resistant isolates was calculated for each tested antimicrobial
(resistance prevalence). A 95% confidence interval (CI) was then calculated for these
proportions.
Comments regarding CI calculation:
Following a normal distribution, a CI is usually calculated by [p-1.96*sd (p) ; p+1.96 *sd (p)]. This could
lead to boundaries outside 0-1, which does not make sense for probabilities. Therefore, CI were
constructed for logit(p). Using the delta method, one can find that sd(logit(p)) = 1/(p*(1-p)) * sd(p). So a
CI on the log-scale equals: [logit(p)-1.96*sd (logit(p)) ; logit(p)+1.96*sd(logit(p))]. The CI presented here
is the expit of this latter one: expit { [logit(p)-1.96*sd(logit(p)) ; logit(p)+1.96*sd(logit(p))] } which is
always located between 0-1. In cases when the proportion of resistant strains was 0% (no resistant
isolates observed) or 100% (all tested isolates resistant), the binomial distribution (Clopper and Pearson
1934) was used to calculate CI as the normal distribution does not provide a CI figure if p = 0 or 100%.
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2. Trend Analysis:
The trends analysis aims at finding models to describe the variation of antimicrobial resistance
over the years and to check if this variation is significant or not. Several statistical methods
were initially tested to analyse these trends:
Univariate models:
- Based on categorical data: Logistic regression, generalized logit models
- Based on continuous data: models for interval-censored data, mixture models
Multivariate model: Generalised Estimating Equation models (GEE)
After evaluating the models cited above for their capacity to analyse the data, comparing the
results and their possible interpretation, it was decided to restrict the trend analysis to the
Logistic regression and to the GEE. These models offered the best convergence, they gave
outputs easy to interpret and compare and the results could be plotted on clear graphs.
Comments about the models used:
Logistic Regression (Univariate model)
In the logistic regression model 𝜋𝑖 represents the probability for an isolate to be resistant to a certain
antimicrobial at year of reporting 𝑡𝑖. Let 𝑛𝑖 be the number of isolates tested for a certain antimicrobial
at time point 𝑡𝑖. Inference on antimicrobial resistance is based on the binomial distribution for the
number of resistant isolates 𝑦𝑖 at time point 𝑡𝑖:
𝑦𝑖 ~𝐵(𝑛𝑖, 𝜋𝑖).
In order to link 𝜋𝑖 to a time trend, one can consider a link function 𝑔(. ) as
𝑔(𝜋𝑖) = 𝛽0 + 𝑓(𝑡𝑖),
where 𝛽0𝑖 is an intercept and 𝑓(𝑡𝑖) represents a function of time. Focus in this report is on a linear time
trend and the logit link function, which is the logarithm of the odds of the probability:
log (𝜋𝑖
1 − 𝜋𝑖) = 𝛽0 + 𝛽1𝑡𝑖.
The results can be described in the form of Odds Ratio (OR) as in the logistic regression β = Ln OR. In
this model, an OR > 1 means that the probability to be resistant increases with time
GEE: Generalised Estimating Equation (Multivariate model)
For each of the sampled isolates, MIC values are collected on distinct antimicrobials. It is possible that
not all of these observations are therefore independent. While in the logit (univariate) model all
antimicrobial substances are separately analyzed, multivariate models take into account possible
correlation between antimicrobial substances in a single model We can employ a generalised estimating
equations approach to estimate the parameters of a generalized linear model with a possible unknown
correlation between outcomes. Through the specification of one of a variety of possible working
correlation matrix structures to account for the within-subject correlations, the GEE method estimates
model parameters by iteratively solving a system of equations based on quasi-likelihood distributional
assumptions. In this report, the focus is on the unstructured working correlation matrix, which means
that the correlations between any two responses are unknown and need to be estimated.
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3. Multiresistance:
Multiresistance was defined as resistance of an isolate to at least 3 different antimicrobials.
Based on this, for each animal category, the estimate for the proportion of multi-resistant
drugs was calculated together with the 95% CI, calculated using normal distribution.
A logistic model was used to check whether there was a significant trend (increase or
decrease) over the years regarding the prevalence of multiresistant strains, for each animal
category. In this model an OR >1 means that the probabillity for a strain to be multiresistant
increases with time.
In addition a diversity index was calculated for multiresistance.
Diversity index: Entropy and Weighted entropy
These indices are calculated to describe the degree of diversity of multiresistance for a specific
year and a specific animal category. Unweighted Entropy takes value between 0 and 1. It will
take the value 0 if the diversity is minimum thus the multiresistance is only of one type (for
example all isolates are resistant to 4 antimicrobials). It will take the maximum value 1, if all
types are evenly represented (for example the frequency of resistance against 3 antibiotics is
equal to the frequency of resistance against 4, 5, 6 or more antibacterial substances. The
Weighted entropy index takes into account order and will take higher values when
multiresistance is more frequent for large number of antimicrobials. Therefore a higher
weighted entropy index reflects a shift to multiresistance to a greater number of antibiotics.
This latter index was calculated using R software based on the formula of Guiasu (1971).
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III. Results
E. Descriptive statistics per Bacteria species, per Year and per
Animal category:
Summary Tables: sample size, Prevalence + Confidence Intervals (CI)
The following tables summarize for each bacterial species the data obtained in 2011, 2012
and 2013 regarding prevalence of resistant isolates for each animal category and each
tested antimicrobial substance:
- N = number of tested samples
- Percentage (prevalence) of resistant isolates (+ confidence intervals)
1. Escherichia coli
2. Enterococcus faecalis
3. Enterococcus faecium
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E. coli 2011 2012 2013
N % Resistance N % Resistance N % Resistance
Veal AMP 34 70,59 ( 52,45 - 83,93) 181 74,03 ( 67,09 - 79,95) 202 64,36 ( 57,46 - 70,71)
Calves CHL 34 50 (33 - 67) 181 42,54 ( 35,48 - 49,92) 202 33,66 ( 27,44 - 40,52)
CIP 34 44,12 ( 27,9 - 61,7) 181 45,3 ( 38,13 - 52,67) 201 31,84 ( 25,72 - 38,66)
COL 34 14,71 ( 5,96 - 31,91) 181 6,08 ( 3,38 - 10,69) 202 5,94 ( 3,39 - 10,21)
FFN 34 14,71 ( 5,96 - 31,91) 181 8,29 ( 5,03 - 13,35) 202 12,38 ( 8,47 - 17,73)
FOT 34 0 ( 0 - 10,28) 181 9,94 ( 6,33 - 15,29) 202 3,47 ( 1,65 - 7,13)
GEN 34 20,59 ( 9,75 - 38,37) 181 6,63 ( 3,78 - 11,37) 202 7,92 ( 4,89 - 12,59)
KAN 34 29,41 ( 16,07 - 47,55) 181 29,28 ( 23,06 - 36,39) 202 24,75 ( 19,25 - 31,23)
NAL 34 41,18 ( 25,42 - 58,98) 181 38,12 ( 31,28 - 45,47) 202 27,72 ( 21,94 - 34,35)
SMX 34 79,41 ( 61,63 - 90,25) 181 75,14 ( 68,26 - 80,94) 202 70,3 ( 63,58 - 76,24)
STR 34 55,88 ( 38,3 - 72,1) 181 64,64 ( 57,34 - 71,32) 202 56,44 ( 49,46 - 63,17)
TAZ 34 0 ( 0 - 10,28) 181 11,05 ( 7,21 - 16,57) 202 3,96 ( 1,98 - 7,76)
TET 34 73,53 ( 55,45 - 86,11) 181 79,01 ( 72,39 - 84,37) 202 76,73 ( 70,35 - 82,09)
TMP 34 70,59 ( 52,45 - 83,93) 181 69,61 ( 62,46 - 75,93) 202 57,92 ( 50,94 - 64,59)
Beef AMP 154 25,32 ( 19,02 - 32,87) 175 35,43 ( 28,64 - 42,86) 204 19,12 ( 14,25 - 25,15)
Cattle CHL 154 14,29 ( 9,55 - 20,83) 175 17,71 ( 12,7 - 24,16) 204 16,67 ( 12,12 - 22,48)
CIP 154 12,99 ( 8,49 - 19,36) 175 20,57 ( 15,17 - 27,27) 204 10,78 ( 7,18 - 15,88)
COL 154 0,65 ( 0,09 - 4,56) 175 2,86 ( 1,18 - 6,73) 204 1,47 ( 0,47 - 4,5)
FFN 154 6,49 ( 3,5 - 11,72) 175 7,43 ( 4,34 - 12,43) 204 11,76 ( 7,98 - 17)
FOT 154 4,55 ( 2,16 - 9,3) 175 6,29 ( 3,49 - 11,05) 204 3,43 ( 1,63 - 7,06)
GEN 154 2,6 ( 0,97 - 6,78) 175 4 ( 1,9 - 8,21) 204 6,86 ( 4,09 - 11,3)
KAN 154 5,19 ( 2,6 - 10,12) 175 13,14 ( 8,86 - 19,07) 204 11,76 ( 7,98 - 17)
NAL 154 11,69 ( 7,45 - 17,87) 175 17,14 ( 12,21 - 23,53) 204 8,82 ( 5,61 - 13,62)
SMX 154 30,52 ( 23,69 - 38,32) 175 42,29 ( 35,12 - 49,8) 204 32,84 ( 26,7 - 39,64)
STR 154 27,27 ( 20,76 - 34,93) 175 37,14 ( 30,24 - 44,61) 204 27,94 ( 22,17 - 34,55)
TAZ 154 3,9 ( 1,74 - 8,47) 175 7,43 ( 4,34 - 12,43) 204 2,45 ( 1,02 - 5,79)
TET 154 19,48 ( 13,92 - 26,58) 175 36 ( 29,17 - 43,45) 204 21,57 ( 16,42 - 27,8)
TMP 154 19,48 ( 13,92 - 26,58) 175 28,57 ( 22,31 - 35,78) 204 20,59 ( 15,55 - 26,74)
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E. coli 2011 2012 2013
N % Resistance N % Resistance N % Resistance
Chickens AMP 420 84,76 ( 80,98 - 87,9) 320 81,56 ( 76,9 - 85,46) 234 84,62 ( 79,36 - 88,72)
CHL 420 24,29 ( 20,41 - 28,64) 320 45,94 ( 40,52 - 51,45) 234 32,48 ( 26,75 - 38,79)
CIP 420 64,05 ( 59,32 - 68,52) 320 80,31 ( 75,56 - 84,33) 234 76,07 ( 70,14 - 81,14)
COL 420 0,48 ( 0,12 - 1,89) 320 4,69 ( 2,84 - 7,65) 234 1,71 ( 0,64 - 4,5)
FFN 420 0,71 ( 0,23 - 2,2) 320 4,06 ( 2,37 - 6,89) 234 2,14 ( 0,89 - 5,06)
FOT 420 19,05 ( 15,56 - 23,11) 320 29,38 ( 24,62 - 34,63) 234 10,26 ( 6,95 - 14,89)
GEN 420 4,05 ( 2,53 - 6,43) 320 6,25 ( 4,06 - 9,51) 234 5,13 ( 2,92 - 8,85)
KAN 419 6,92 ( 4,84 - 9,8) 320 14,69 ( 11,2 - 19,03) 234 8,97 ( 5,91 - 13,41)
NAL 420 62,86 ( 58,11 - 67,37) 320 78,44 ( 73,57 - 82,62) 234 70,09 ( 63,86 - 75,64)
SMX 420 75 ( 70,62 - 78,92) 320 81,25 ( 76,57 - 85,18) 234 69,23 ( 62,98 - 74,85)
STR 419 68,97 ( 64,36 - 73,24) 320 82,5 ( 77,91 - 86,3) 234 73,93 ( 67,88 - 79,19)
TAZ 420 17,14 ( 13,82 - 21,07) 320 25,94 ( 21,41 - 31,05) 234 10,68 ( 7,3 - 15,37)
TET 420 64,76 ( 60,05 - 69,2) 320 70,63 ( 65,37 - 75,38) 234 59,83 ( 53,37 - 65,96)
TMP 420 63,1 ( 58,35 - 67,6) 319 70,22 ( 64,94 - 75,01) 234 60,26 ( 53,8 - 66,37)
Pigs AMP 157 49,04 ( 41,23 - 56,91) 217 47,47 ( 40,85 - 54,17) 206 45,15 ( 38,43 - 52,05)
CHL 157 26,75 ( 20,35 - 34,3) 217 28,57 ( 22,91 - 34,99) 206 26,21 ( 20,62 - 32,7)
CIP 156 15,38 ( 10,48 - 22,01) 217 17,51 ( 12,98 - 23,2) 206 6,8 ( 4,05 - 11,19)
COL 157 0,64 ( 0,09 - 4,47) 217 0,92 ( 0,23 - 3,65) 206 2,43 ( 1,01 - 5,74)
FFN 157 4,46 ( 2,12 - 9,12) 217 4,61 ( 2,48 - 8,39) 206 1,94 ( 0,72 - 5,1)
FOT 157 4,46 ( 2,12 - 9,12) 217 2,76 ( 1,24 - 6,05) 206 0,97 ( 0,24 - 3,84)
GEN 157 3,82 ( 1,71 - 8,31) 217 0,92 ( 0,23 - 3,65) 206 1,94 ( 0,72 - 5,1)
KAN 157 3,18 ( 1,32 - 7,49) 217 4,15 ( 2,16 - 7,82) 206 5,34 ( 2,97 - 9,43)
NAL 157 11,46 ( 7,31 - 17,54) 217 12,9 ( 9,03 - 18,1) 206 3,88 ( 1,94 - 7,61)
SMX 157 58,6 ( 50,66 - 66,12) 217 58,06 ( 51,34 - 64,5) 206 54,37 ( 47,47 - 61,1)
STR 157 54,14 ( 46,22 - 61,85) 217 52,53 ( 45,83 - 59,15) 206 56,31 ( 49,4 - 62,98)
TAZ 157 4,46 ( 2,12 - 9,12) 217 3,69 ( 1,84 - 7,23) 206 1,46 ( 0,47 - 4,46)
TET 157 56,69 ( 48,75 - 64,3) 217 58,06 ( 51,34 - 64,5) 206 52,43 ( 45,55 - 59,22)
TMP 157 50,32 ( 42,47 - 58,15) 217 52,53 ( 45,83 - 59,15) 206 48,54 ( 41,73 - 55,41)
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E,faecalis 2011 2012 2013
N % Resistance N % Resistance N % Resistance
Veal AMP 4 0 (0-60,24) 28 7,14 (1,63-26,28) 46 6,52 (2,03-19,05)
Calves CHL 4 50 (2,47-97,53) 28 17,86 (7,2-37,87) 46 63,04 (47,8-76,06)
CIP 4 25 (0,48-95,87) 28 0 (0-12,34) 46 4,35 (1,03-16,54)
ERY 4 100 (39,76-100) 28 46,43 (28,19-65,67) 46 86,96 (73,22-94,21)
FFN 4 0 (0-60,24) 28 0 (0-12,34) 46 4,35 (1,03-16,54)
GEN 4 0 (0-60,24) 28 7,14 (1,63-26,28) 46 13,04 (5,79-26,78)
LZD 4 0 (0-60,24) 28 0 (0-12,34) 46 0 (0-7,71)
SAL 4 25 (0,48-95,87) 28 0 (0-12,34) 46 4,35 (1,03-16,54)
STR 4 100 (39,76-100) 28 60,71 (40,78-77,62) 46 69,57 (54,34-81,45)
SYN 4 0 (0-60,24) 28 0 (0-12,34) 46 4,35 (1,03-16,54)
TET 4 75 (4,13-99,52) 28 57,14 (37,51-74,76) 46 91,3 (78,34-96,82)
VAN 4 0 (0-60,24) 28 0 (0-12,34) 46 2,17 (0,28-14,83)
Beef AMP 24 8,33 (1,87-30,21) 58 1,72 (0,23-11,86) 20 0 (0-16,84)
Cattle CHL 24 8,33 (1,87-30,21) 58 51,72 (38,66-64,56) 20 45 (23,76-68,23)
CIP 24 0 (0-14,25) 58 5,17 (1,62-15,3) 20 0 (0-16,84)
ERY 24 62,5 (40,61-80,25) 58 82,76 (70,4-90,64) 20 50 (27,68-72,32)
FFN 24 0 (0-14,25) 58 1,72 (0,23-11,86) 20 0 (0-16,84)
GEN 24 4,17 (0,5-27,35) 58 6,9 (2,53-17,42) 20 5 (0,58-32,27)
LZD 24 0 (0-14,25) 58 1,72 (0,23-11,86) 20 0 (0-16,84)
SAL 24 4,17 (0,5-27,35) 58 0 (0-9,24) 20 5 (0,58-32,27)
STR 24 62,5 (40,61-80,25) 58 74,14 (61-84,01) 20 60 (36,02-79,99)
SYN 24 0 (0-14,25) 58 1,72 (0,23-11,86) 20 0 (0-16,84)
TET 24 75 (52,56-89,04) 58 89,66 (78,39-95,39) 20 60 (36,02-79,99)
VAN 24 0 (0-14,25) 58 1,72 (0,23-11,86) 20 0 (0-16,84)
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E,faecalis 2011 2012 2013
N % Resistance N % Resistance N % Resistance
Chickens AMP 81 11,11 (5,8-20,24) 149 6,71 (3,62-12,1) 71 5,63 (2,08-14,37)
CHL 81 9,88 (4,94-18,77) 149 2,68 (1-7,01) 71 4,23 (1,33-12,61)
CIP 81 3,7 (1,17-11,11) 149 2,68 (1-7,01) 71 1,41 (0,19-9,75)
ERY 81 76,54 (65,87-84,65) 149 72,48 (64,68-79,12) 71 70,42 (58,54-80,06)
FFN 81 0 (0-4,45) 149 0 (0-2,45) 71 1,41 (0,19-9,75)
GEN 81 3,7 (1,17-11,11) 149 4,03 (1,8-8,75) 71 0 (0-5,06)
LZD 81 6,17 (2,54-14,22) 149 2,68 (1-7,01) 71 0 (0-5,06)
SAL 81 13,58 (7,59-23,13) 149 14,09 (9,33-20,74) 71 11,27 (5,64-21,25)
STR 81 59,26 (48,05-69,58) 149 51,01 (42,93-59,03) 71 50,7 (38,97-62,36)
SYN 81 1,23 (0,17-8,57) 149 2,68 (1-7,01) 71 2,82 (0,68-10,91)
TET 81 90,12 (81,23-95,06) 149 86,58 (80,02-91,22) 71 88,73 (78,75-94,36)
VAN 81 3,7 (1,17-11,11) 149 2,68 (1-7,01) 71 0 (0-5,06)
Pigs AMP 8 0 (0-36,94) 22 0 (0-15,44) 13 0 (0-24,71)
CHL 8 12,5 (0,95-68,06) 22 18,18 (6,41-41,89) 13 23,08 (6,32-57,17)
CIP 8 0 (0-36,94) 22 4,55 (0,54-29,61) 13 0 (0-24,71)
ERY 8 25 (4,06-72,42) 22 63,64 (40,52-81,8) 13 30,77 (10,21-63,46)
FFN 8 0 (0-36,94) 22 0 (0-15,44) 13 0 (0-24,71)
GEN 8 0 (0-36,94) 22 18,18 (6,41-41,89) 13 0 (0-24,71)
LZD 8 12,5 (0,95-68,06) 22 0 (0-15,44) 13 0 (0-24,71)
SAL 8 25 (4,06-72,42) 22 0 (0-15,44) 13 0 (0-24,71)
STR 8 37,5 (8,65-79,17) 22 31,82 (14,98-55,28) 13 23,08 (6,32-57,17)
SYN 8 0 (0-36,94) 22 0 (0-15,44) 13 0 (0-24,71)
TET 8 62,5 (20,83-91,35) 22 81,82 (58,11-93,59) 13 53,85 (24,83-80,47)
VAN 8 0 (0-36,94) 22 0 (0-15,44) 13 0 (0-24,71)
15
E,faecium 2011 2012 2013
N % Resistance N % Resistance N % Resistance
Veal AMP 3 0 (0-70,76) 58 6,9 (2,53-17,42) 107 17,76 (11,54-26,33)
Calves CHL 3 0 (0-70,76) 58 1,72 (0,23-11,86) 107 3,74 (1,39-9,68)
CIP 3 0 (0-70,76) 58 3,45 (0,83-13,25) 107 1,87 (0,46-7,32)
ERY 3 66,67 (0,31-99,92) 58 24,14 (14,62-37,16) 107 52,34 (42,75-61,75)
FFN 3 0 (0-70,76) 58 1,72 (0,23-11,86) 107 4,67 (1,93-10,88)
GEN 3 0 (0-70,76) 58 0 (0-6,16) 107 2,8 (0,89-8,48)
LZD 3 0 (0-70,76) 58 1,72 (0,23-11,86) 107 1,87 (0,46-7,32)
SAL 3 0 (0-70,76) 58 3,45 (0,83-13,25) 107 1,87 (0,46-7,32)
STR 3 66,67 (0,31-99,92) 58 18,97 (10,63-31,53) 107 39,25 (30,34-48,94)
SYN 3 100 (29,24-100) 58 82,76 (70,4-90,64) 107 89,72 (82,24-94,27)
TET 3 66,67 (0,31-99,92) 58 25,86 (15,99-39) 107 51,4 (41,84-60,86)
VAN 3 0 (0-70,76) 58 1,72 (0,23-11,86) 107 2,8 (0,89-8,48)
Beef AMP 29 13,79 (4,95-32,96) 100 9 (4,7-16,56) 54 3,7 (0,89-14,19)
Cattle CHL 29 17,24 (6,96-36,73) 100 1 (0,14-6,97) 54 0 (0-6,6)
CIP 29 13,79 (4,95-32,96) 100 2 (0,49-7,82) 54 7,41 (2,72-18,64)
ERY 29 58,62 (39,23-75,66) 100 42 (32,59-52,03) 54 20,37 (11,43-33,64)
FFN 29 0 (0-11,94) 100 2 (0,49-7,82) 54 3,7 (0,89-14,19)
GEN 29 0 (0-11,94) 100 1 (0,14-6,97) 54 1,85 (0,24-12,71)
LZD 29 0 (0-11,94) 100 0 (0-3,62) 54 1,85 (0,24-12,71)
SAL 29 20,69 (9,12-40,42) 100 3 (0,95-9,05) 54 7,41 (2,72-18,64)
STR 29 44,83 (27,17-63,89) 100 37 (27,98-47,02) 54 12,96 (6,15-25,27)
SYN 29 96,55 (77,04-99,57) 100 82 (73,05-88,45) 54 85,19 (72,58-92,59)
TET 29 65,52 (45,7-81,1) 100 47 (37,29-56,94) 54 16,67 (8,72-29,52)
VAN 29 0 (0-11,94) 100 1 (0,14-6,97) 54 1,85 (0,24-12,71)
16
E,faecium 2011 2012 2013
N % Resistance N % Resistance N % Resistance
Chickens AMP 33 24,24 (12,14-42,58) 161 39,13 (31,83-46,96) 113 38,05 (29,46-47,46)
CHL 33 9,09 (2,78-25,92) 161 1,24 (0,31-4,9) 113 0 (0-3,21)
CIP 33 18,18 (8,03-36,11) 161 8,07 (4,72-13,48) 113 8,85 (4,78-15,8)
ERY 33 72,73 (54,3-85,68) 161 73,91 (66,51-80,17) 113 75,22 (66,3-82,41)
FFN 33 0 (0-10,58) 161 0 (0-2,27) 113 0 (0-3,21)
GEN 33 0 (0-10,58) 161 1,86 (0,59-5,68) 113 0,88 (0,12-6,18)
LZD 33 6,06 (1,41-22,59) 161 0 (0-2,27) 113 0 (0-3,21)
SAL 33 51,52 (34,08-68,59) 161 37,27 (30,08-45,07) 113 53,98 (44,62-63,07)
STR 33 60,61 (42,41-76,27) 161 62,73 (54,93-69,92) 113 55,75 (46,36-64,75)
SYN 33 100 (89,42-100) 161 91,3 (85,78-94,81) 113 88,5 (81,05-93,26)
TET 33 87,88 (70,63-95,62) 161 78,26 (71,14-84,02) 113 67,26 (57,95-75,38)
VAN 33 9,09 (2,78-25,92) 161 0 (0-2,27) 113 0,88 (0,12-6,18)
Pigs AMP 8 0 (0-36,94) 121 17,36 (11,53-25,29) 69 8,7 (3,88-18,35)
CHL 8 12,5 (0,95-68,06) 121 1,65 (0,41-6,49) 69 0 (0-5,21)
CIP 8 12,5 (0,95-68,06) 121 3,31 (1,23-8,59) 69 5,8 (2,14-14,77)
ERY 8 25 (4,06-72,42) 121 27,27 (19,99-36,01) 69 20,29 (12,24-31,72)
FFN 8 0 (0-36,94) 121 1,65 (0,41-6,49) 69 0 (0-5,21)
GEN 8 0 (0-36,94) 121 1,65 (0,41-6,49) 69 1,45 (0,19-10,02)
LZD 8 12,5 (0,95-68,06) 121 3,31 (1,23-8,59) 69 1,45 (0,19-10,02)
SAL 8 0 (0-36,94) 121 4,96 (2,22-10,71) 69 5,8 (2,14-14,77)
STR 8 25 (4,06-72,42) 121 26,45 (19,27-35,14) 69 14,49 (7,85-25,21)
SYN 8 100 (63,06-100) 121 90,08 (83,23-94,33) 69 86,96 (76,47-93,19)
TET 8 50 (14,34-85,66) 121 49,59 (40,66-58,54) 69 27,54 (18,1-39,51)
VAN 8 12,5 (0,95-68,06) 121 4,13 (1,71-9,66) 69 1,45 (0,19-10,02)
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F. Descriptive statistics (Graphs) and Trend Analysis
Preliminary comments about presentation and interpretation of the results:
For each bacteria species and each animal category, descriptive statistics and results of the
trend analysis are presented in this part of the report according to the following plan:
Prevalence of resistant strains
The annual values of resistance prevalence already presented in the previous tables (part A.)
were plotted on graphs in Excel for a better viewing of possible trends (prevalence graphs: one
line for each antimicrobial). However such visual observations had to be confirmed by
statistical analysis of the actual trends. Apart from apparent increasing or decreasing trend, on
these graphs it is also easy to detect antimicrobials which had high levels of resistance
(prevalence >50%) for the three consecutive years.
Trend analysis
Univariate models
The logistic regression provides Odds Ratios (OR) which can be interpreted in this case as the
association between time (year) and the level (prevalence) of antimicrobial resistance.
Confidence intervals (CI) of the ORs are given in order to check whether or not they are
significant. If the CI of the OR includes the value 1, it is not significant (no significant trend). An
OR with the lower CI value >1 means that there is an increasing trend for antimicrobial
resistance. An OR with the upper CI value < 1 means there is a decreasing trend for
antimicrobial resistance.
OR values and their CI are presented in this part of the report in tables with the following sign
whenever they are significant:
↑* for increasing trend
↓* for decreasing trend.
After each OR table, OR are also presented with their CI on bar charts.
Multivariate models (GEE)
Whenever GEE models converged, the results are presented hereafter on charts where the
probability for a bacteria strain to be resistant to a specific antimicrobial at a specific year is
plotted: a curve for each antibiotic shows the trend over time. Detailed figures of the GEE
models (estimates figures) are presented in Annex 2 for E. coli isolates.
Multivariate models did not converge for the Enterococcal data, probably due to the insufficient
number of tested samples, especially in the year 2011.
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1. E. coli
a) Veal Calves: Tested samples per year: N= 34 (2011) ; 181 (2012) ; 202 (2013)
Prevalence of resistant strains: (fig.1)
High levels of resistance were observed for this animal category with more than 50 % of
resistant strains for the three consecutive years for 4 substances: AMP, SMX, STR and TET.
fig.1
Trend analysis:
A significant decrease of resistance over time was observed for 4 substances (↓*): CHL, CIP,
NAL and TMP,both with univariate models (table 1 and fig.3) and multivariate models (fig 2)
Red = significant
Blue = not significant
Black = overall trend
fig.2
0
20
40
60
80
100
2011 2012 2013
%
Prevalence of Resistance Veal Calves -E.coli
AMP CHL CIP COL FFN FOT GEN
KAN NAL SMX STR TAZ TET TMP
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Table 1:The LOGISTIC Procedure
E. coli - species= Veal calves
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at substance=AMP 0.754 0.539 1.056
year0 at substance=CHL ↓*0.702 0.515 0.958
year0 at substance=CIP ↓*0.678 0.497 0.926
year0 at substance=COL 0.677 0.383 1.195
year0 at substance=FFN 1.112 0.681 1.818
year0 at substance=FOT 0.728 0.399 1.328
year0 at substance=GEN 0.684 0.408 1.147
year0 at substance=KAN 0.848 0.606 1.186
year0 at substance=NAL ↓*0.692 0.503 0.951
year0 at substance=SMX 0.787 0.555 1.117
year0 at substance=STR 0.869 0.637 1.185
year0 at substance=TAZ 0.737 0.416 1.306
year0 at substance=TET 0.999 0.696 1.433
year0 at substance=TMP ↓*0.682 0.492 0.945
fig.3
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b) Beef cattle: Tested samples per year: N= 154 (2011) ; 175 (2012) ; 204 (2013)
Prevalence of resistant strains:
Significantly lower prevalences of resistance were observed in E. coli from beef cattle
compared to veal calves: resistance prevalences against all drugs are below 50 %. However
the highest resistance prevalences were observed against the same substances as for veal
calves: AMP, SMX, STR and TET.(fig.4)
fig.4
Trend analysis: (fig5)
No significant trends are observed with univariate models (fig.6 and table 2) but there is a
slightly increasing resistance for 2 substances (GEN and KAN) with the multivariate model.
Red = significant
Blue = not significant
Black = overall trend
fig.5
0
20
40
60
80
100
2011 2012 2013
%
Prevalence of Resistance Beef Cattle - E.coli
AMP CHL CIP COL FFN FOT GEN
KAN NAL SMX STR TAZ TET TMP
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Table 2: The LOGISTIC Procedure E. coli - species= Beef cattle
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at substance=AMP 0.826 0.652 1.047
year0 at substance=CHL 1.081 0.815 1.434
year0 at substance=CIP 0.887 0.662 1.189
year0 at substance=COL 1.190 0.543 2.608
year0 at substance=FFN 1.408 0.962 2.061
year0 at substance=FOT 0.863 0.533 1.399
year0 at substance=GEN 1.647 0.971 2.793
year0 at substance=KAN 1.400 0.982 1.996
year0 at substance=NAL 0.852 0.622 1.166
year0 at substance=SMX 1.029 0.827 1.280
year0 at substance=STR 0.995 0.794 1.246
year0 at substance=TAZ 0.811 0.495 1.326
year0 at substance=TET 1.017 0.801 1.290
year0 at substance=TMP 1.008 0.787 1.292
fig.6
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c) Broiler Chickens: Tested samples per year: N= 420 (2011) ; 320 (2012) ; 234 (2013)
Prevalence of resistant strains:
A high prevalence of resistance was observed for this animal species with values ≥ 60% for
the three consecutive years for 7 substances: AMP, CIP, NAL, SMX, STR, TET and TMP (fig.7)
fig.7
Trend analysis:
Univariate model: significant increase of resistance (↑*) over time for 4 substances : CHL, CIP,
NAL and STR (table 3 and fig.9)
Multivariate model: significant increase of resistance over time for 5 substances: CHL, CIP,
COL, FFN, NAL and decrease for FOT (fig.8)
Red = significant
Blue = not significant
Black = overall trend
fig.8
0
20
40
60
80
100
2011 2012 2013
%Prevalence of Resistance
Chickens -E.coli
AMP CHL CIP COL FFN FOT GEN
KAN NAL SMX STR TAZ TET TMP
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Table 3.The LOGISTIC Procedure E. coli - species=chickens
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at substance=AMP 0.972 0.786 1.201
year0 at substance=CHL ↑*1.297 1.098 1.533
year0 at substance=CIP ↑*1.435 1.195 1.725
year0 at substance=COL 1.555 0.921 2.624
year0 at substance=FFN 1.555 0.921 2.624
year0 at substance=FOT 0.832 0.682 1.016
year0 at substance=GEN 1.158 0.814 1.648
year0 at substance=KAN 1.204 0.930 1.559
year0 at substance=NAL ↑*1.259 1.057 1.499
year0 at substance=SMX 0.898 0.749 1.078
year0 at substance=STR ↑*1.210 1.006 1.455
year0 at substance=TAZ 0.873 0.711 1.073
year0 at substance=TET 0.930 0.788 1.097
year0 at substance=TMP 0.975 0.827 1.149
fig.9
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d) Pigs: Tested samples per year: N= 157 (2011) ; 217 (2012) ; 206 (2013)
Prevalence of resistant strains:
A high prevalence of resistance was observed for this animal species with more than 45 % of
resistant strains for the three consecutive years for 5 substances: AMP, SMX, STR, TET and
TMP.(fig.10)
fig.10
Trend analysis:
A significant decrease of resistance over time was seen for 3 substances (↓*): CIP, FOT and
NAL (univariate and multivariate models) (table 4 and fig 12; fig.11)
Red = significant
Blue = not significant
Black = overall trend
fig.11
0
10
20
30
40
50
60
70
2011 2012 2013
%
Prevalence of Resistance Pigs -E.coli
AMP CHL CIP COL FFN FOT GEN
KAN NAL SMX STR TAZ TET TMP
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Table 4.The LOGISTIC Procedure E. coli - species=pig
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at substance=AMP 0.924 0.751 1.137
year0 at substance=CHL 0.981 0.778 1.237
year0 at substance=CIP ↓*0.668 0.491 0.910
year0 at substance=COL 1.974 0.761 5.123
year0 at substance=FFN 0.689 0.399 1.191
year0 at substance=FOT ↓*0.504 0.258 0.985
year0 at substance=GEN 0.671 0.331 1.362
year0 at substance=KAN 1.294 0.773 2.164
year0 at substance=NAL ↓*0.620 0.432 0.889
year0 at substance=SMX 0.915 0.742 1.128
year0 at substance=STR 1.050 0.853 1.293
year0 at substance=TAZ 0.606 0.334 1.101
year0 at substance=TET 0.911 0.739 1.122
year0 at substance=TMP 0.959 0.780 1.180
fig.12
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2) Enterococci spp. (NB : no convergence with multivariate models for Enterococci)
a) Veal Calves:Tested samples per year: E. faecalis: N= 4 (2011) ; 28 (2012) ; 46 (2013)
E. faecium: N= 3 (2011) ; 58 (2012) ; 107 (2013) Prevalence of resistant strains:
Due to the very limited number of samples in 2011 no conclusion can be drawn for that year.
In 2012/2013 high prevalences of resistance (>45%) were observed for E. faecalis for STR,
ERY and TET (fig.13) and a very high prevalence (>80%) for SYN for E. faecium (fig14).
fig.13
fig.14
0
20
40
60
80
100
2011 2012 2013
%
Prevalence of Resistance Veal Calves - E. faecalis
AMP CHL CIP ERY FFN GEN
LZD SAL STR SYN TET VAN
0
20
40
60
80
100
2011 2012 2013
%
Prevalence of Resistance Calves - E. faecium
AMP CHL CIP ERY FFN GEN
LZD SAL STR SYN TET VAN
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Trend analysis:
Univariate model: a significant increase of resistance prevalence (↑*) was seen for 2
substances (ERY and TET) both for E. faecalis and E. faecium. For E. faecalis also significant
increase of resistance prevalence was also observed for CHL. (Table 5 and 6 ; fig.15 and 16)
Table 5. The LOGISTIC Procedure species=Veal calves
E. faecalis
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at substance=AMP 1.047 0.249 4.403
year0 at substance=CHL ↑*3.378 1.396 8.171
year0 at substance=CIP 0.545 0.115 2.576
year0 at substance=ERY ↑*2.491 1.078 5.761
year0 at substance=FFN 2.871 0.181 45.451
year0 at substance=GEN 1.887 0.468 7.610
year0 at substance=LZD 0.342 0.018 6.334
year0 at substance=SAL 0.545 0.115 2.576
year0 at substance=STR 0.931 0.416 2.083
year0 at substance=SYN 2.871 0.181 45.451
year0 at substance=TET ↑*3.309 1.331 8.224
year0 at substance=VAN 1.564 0.102 23.859
fig.15
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Table 6. The LOGISTIC Procedure species= Veal calves
E. faecium
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at substance=AMP 2.759 0.960 7.929
year0 at substance=CHL 1.690 0.281 10.155
year0 at substance=CIP 0.602 0.124 2.919
year0 at substance=ERY ↑*2.420 1.279 4.580
year0 at substance=FFN 2.081 0.355 12.215
year0 at substance=GEN 3.781 0.210 67.948
year0 at substance=LZD 0.930 0.141 6.128
year0 at substance=SAL 0.602 0.124 2.919
year0 at substance=STR 1.845 0.949 3.590
year0 at substance=SYN 1.481 0.652 3.369
year0 at substance=TET ↑*2.183 1.164 4.094
year0 at substance=VAN 1.307 0.210 8.128
fig.16
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b) Beef Cattle: Tested samples per year: E. faecalis:N= 24 (2011) ; 58 (2012) ; 20 (2013)
E. faecium:N= 29 (2011) ; 100 (2012) ; 54 (2013)
Prevalence of resistant strains:
A high prevalence of resistance (> 50%) was observed for 3 consecutive years for E. faecalis
for 3 substances: ERY, STR and TET. Resistance to CHL increased to a prevalence close to
50% in 2012/2013 (fig.17)
A very high prevalence of resistance (>80%) was observed for 3 consecutive years for E.
faecium for 1 substance: SYN. Three substances which had a high resistance prevalence in
2011/2012 (ERY, STR and TET) reached much lower levels in 2013 (fig.18)
fig.17
fig.18
0
20
40
60
80
100
2011 2012 2013
%
Prevalence of Resistance Beef Cattle -E. faecalis
AMP CHL CIP ERY FFN GEN
LZD SAL STR SYN TET VAN
0
20
40
60
80
100
2011 2012 2013
%
Prevalence of Resistance Cattle -E. faecium
AMP CHL CIP ERY FFN GEN
LZD SAL STR SYN TET VAN
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Trend analysis: Table 7 and fig.19 ; Table 8 and fig.20
Univariate model: a significant increase (↑*) of resistance prevalence was seen for CHL in E.
faecalis . For E. faecium a significant decrease (↓*) of resistance prevalence for CHL, ERY,
STR,TET was observed.
Table 7. The LOGISTIC Procedure species= Beef cattle
E. faecalis
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at substance=AMP 0.228 0.036 1.457
year0 at substance=CHL ↑ *2.303 1.197 4.432
year0 at substance=CIP 1.095 0.235 5.100
year0 at substance=ERY 0.793 0.411 1.528
year0 at substance=FFN 1.091 0.127 9.410
year0 at substance=GEN 1.098 0.337 3.578
year0 at substance=LZD 1.091 0.127 9.410
year0 at substance=SAL 1.094 0.187 6.405
year0 at substance=STR 0.974 0.516 1.839
year0 at substance=SYN 1.091 0.127 9.410
year0 at substance=TET 0.676 0.320 1.428
year0 at substance=VAN 1.091 0.127 9.410
fig.19
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Table 8. The LOGISTIC Procedure species= Beef cattle
E. faecium
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at substance=AMP 0.518 0.234 1.144
year0 at substance=CHL ↓*0.066 0.011 0.385
year0 at substance=CIP 0.723 0.287 1.824
year0 at substance=ERY ↓*0.426 0.261 0.694
year0 at substance=FFN 2.225 0.503 9.841
year0 at substance=GEN 1.989 0.305 12.946
year0 at substance=LZD 4.824 0.287 81.076
year0 at substance=SAL 0.497 0.214 1.157
year0 at substance=STR ↓*0.439 0.265 0.727
year0 at substance=SYN 0.722 0.386 1.352
year0 at substance=TET ↓*0.323 0.193 0.540
year0 at substance=VAN 1.989 0.305 12.946
fig.20
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c) Broiler chickens: Tested samples/year: E. faecalis: N=81 (2011) ;149 (2012) ; 71 (2013)
E. faecium: N=33 (2011) ; 161 (2012) ;113 (2013)
Prevalence of resistant strains:
A high prevalence of resistance (> 50%) was observed during 3 consecutive years for E.
faecalis and E. faecium for 3 substances: ERY, STR and TET. (fig.21 and 22)
In addition a very high prevalence of resistance (≥ 90%) was observed during 3 consecutive
years for E. faecium for 1 substance: SYN.
fig.21
fig.22
0
20
40
60
80
100
2011 2012 2013
%
Prevalence of Resistance Chickens -E. faecalis
AMP CHL CIP ERY FFN GEN
LZD SAL STR SYN TET VAN
0
20
40
60
80
100
2011 2012 2013
%
Prevalence of Resistance Chickens -E. faecium
AMP CHL CIP ERY FFN GEN
LZD SAL STR SYN TET VAN
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Trend analysis: Table 9 and fig.23; Table 10 and fig.24
Univariate model: a significant decrease (↓*) of resistance prevalence for LZD was observed
in E. faecalis . In E. faecium a significant decrease (↓*) of resistance prevalence was observed
for CHL, LZD, TET and VAN
Table 9. The LOGISTIC Procedure species=chickens
E. faecalis
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at substance=AMP 0.676 0.370 1.237
year0 at substance=CHL 0.534 0.251 1.135
year0 at substance=CIP 0.658 0.251 1.727
year0 at substance=ERY 0.856 0.598 1.225
year0 at substance=FFN 5.243 0.377 72.836
year0 at substance=GEN 0.550 0.215 1.408
year0 at substance=LZD ↓*0.323 0.113 0.926
year0 at substance=SAL 0.911 0.571 1.452
year0 at substance=STR 0.839 0.609 1.155
year0 at substance=SYN 1.402 0.515 3.817
year0 at substance=TET 0.928 0.571 1.509
year0 at substance=VAN 0.454 0.153 1.342
fig.23
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Table 10. The LOGISTIC Procedure species=chickens
E. faecium
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at substance=AMP 1.197 0.831 1.724
year0 at substance=CHL ↓*0.123 0.028 0.537
year0 at substance=CIP 0.722 0.403 1.293
year0 at substance=ERY 1.069 0.718 1.594
year0 at substance=FFN 0.561 0.028 11.293
year0 at substance=GEN 0.929 0.234 3.692
year0 at substance=LZD ↓*0.042 0.002 0.724
year0 at substance=SAL 1.295 0.907 1.848
year0 at substance=STR 0.850 0.593 1.217
year0 at substance=SYN 0.540 0.279 1.046
year0 at substance=TET ↓*0.556 0.362 0.855
year0 at substance=VAN ↓*0.170 0.037 0.771
fig.24
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d) Pigs: Tested samples per year: E. faecalis:N= 8 (2011) ; 22 (2012) ; 13 (2013)
E. faecium:N= 8 (2011) ; 121 (2012) ; 69 (2013) Prevalence of resistant strains:
Due to the low number of E. faecalis isolates tested for this animal species it is difficult to draw
any conclusion. It seems there was a high prevalence of resistance (> 50%) against TET during
three consecutive years (fig.25). In E. faecium, as observed with other animal categories, there
was very a high level of resistance against SYN (>80%). (fig.26)
fig.25
fig.26
0
20
40
60
80
100
2011 2012 2013
%
Prevalence of Resistance Pigs -E. faecalis
AMP CHL CIP ERY FFN GEN
LZD SAL STR SYN TET VAN
0
20
40
60
80
100
2011 2012 2013
%
Prevalence of Resistance Pigs -E. faecium
AMP CHL CIP ERY FFN GEN
LZD SAL STR SYN TET VAN
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Trend analysis: Table 11 and fig 27; Table 12 and fig.28
Univariate model: no significant trend was observed in E. faecalis due to the limited number of
tested isolates. In E. faecium a significant decrease (↓*) of resistance prevalence was
observed against CHL and TET.
Table 11. The LOGISTIC Procedure species=pig E. faecalis
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at substance=AMP 0.812 0.043 15.159
year0 at substance=CHL 1.364 0.451 4.130
year0 at substance=CIP 0.796 0.098 6.468
year0 at substance=ERY 0.941 0.395 2.246
year0 at substance=FFN 0.812 0.043 15.159
year0 at substance=GEN 0.778 0.196 3.083
year0 at substance=LZD 0.138 0.008 2.379
year0 at substance=SAL 0.065 0.003 1.221
year0 at substance=STR 0.719 0.280 1.848
year0 at substance=SYN 0.812 0.043 15.159
year0 at substance=TET 0.726 0.279 1.885
year0 at substance=VAN 0.812 0.043 15.159
fig.27
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Table 12.The LOGISTIC Procedure species=pig E. faecium
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at substance=AMP 0.718 0.340 1.518
year0 at substance=CHL ↓*0.102 0.014 0.740
year0 at substance=CIP 1.094 0.337 3.553
year0 at substance=ERY 0.755 0.415 1.373
year0 at substance=FFN 0.358 0.040 3.209
year0 at substance=GEN 1.093 0.175 6.840
year0 at substance=LZD 0.340 0.078 1.479
year0 at substance=SAL 1.374 0.444 4.252
year0 at substance=STR 0.577 0.306 1.087
year0 at substance=SYN 0.638 0.279 1.460
year0 at substance=TET ↓*0.468 0.271 0.810
year0 at substance=VAN 0.337 0.084 1.344
fig.28
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G. Multiresistance
1. E. coli
Prevalence of multiresistance
The percentage of multiresistant strains (= strains resistant to at least 3 antibiotics) was high
for Pigs during the three consecutive years (> 50%) and very high for Veal calves (>70%) and
Chickens (>85%) but moderate for Beef cattle (<40%) (Table 13 and fig.29)
Table 13 : percentage of multiresistant strains (+95% CI) – E. coli
Veal calves Beef cattle Chickens Pigs
2011 76 (61-91) 29 (22-36) 86 (83-90) 57 (50-65)
2012 76 (70-83) 36 (29-43) 89 (85-92) 59 (52-65)
2013 73 (67-79) 27 (21-33) 86 (82-91) 56 (49-63)
fig.29
Trend analysis for Multiresistance: Table 13 and fig.30
No significant trends (increasing or decreasing) were observed regarding multiresistance in E. coli.
Table 13. The LOGISTIC Procedure - E. coli Probability modeled is multi=1.
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at species=calve 0.876 0.617 1.245
year0 at species=cattle 0.932 0.744 1.168
year0 at species=chickens 1.027 0.812 1.298
year0 at species=pig 0.976 0.792 1.203
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
calves2011
calves2012
calves2013
cattle2011
cattle2012
cattle2013
chicken2011
chicken2012
chicken2013
pig2011
pig2012
pig2013
Prevalence of Multiresistance - E.coli
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fig.30
Indice of diversity: Weighted Entropy (for definition see II.D. Material and Methods,
Statistical methods). Table 14 and fig.31
No increase of the indices was observed over time but there were marked differences between
animal categories: the index is higher for Veal calves meaning that for this species
multiresistance to high number of antibiotics is more frequent than for other species. The index
was the lowest for Pigs.
Table 14
Veal calves Beef cattle Chickens Pigs
2011 0,63 0,48 0,57 0,44
2012 0,67 0,61 0,71 0,44
2013 0,62 0,57 0,55 0,37
fig.31
0,00
0,20
0,40
0,60
0,80
1,00
calve cattle chicken pig
indices of diversity : Weighted EntropyE. coli
2011 2012 2013
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2. Enterococci
a) E. faecalis
Prevalence of multiresistance (Table 15 and fig.32)
Due to the low number of tested isolates the proportion of multiresistant strains is sometimes
very approximate (large CI) and comparisons between animal categories are therefore difficult.
Table 15 : percentage of multiresistant strains (+95% CI) – E. faecalis
Veal calves Beef cattle Chickens Pigs
2011 75 (19-99) 46 (24-67) 63 (52-74) 25 (0-64)
2012 36 (17-55) 76 (65-87) 56 (48-64) 41 (19-63)
2013 80 (69-92) 55 (31-79) 58 (46-70) 31 (2-60)
fig.32
Trend analysis: Table 16 and fig.33 There was a significant increasing trend for multiresistance for Veal calves. However, due to the few number of isolates tested in 2011, this trend is mostly based upon observations of 2012-2013.
Table 16.The LOGISTIC Procedure - E. faecalis Probability modeled is multi=1.
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at species=calve ↑*3.007 1.311 6.896
year0 at species=cattle 1.286 0.689 2.398
year0 at species=chickens 0.894 0.647 1.236
year0 at species=pig 1.049 0.424 2.599
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
calves2011
calves2012
calves2013
cattle2011
cattle2012
cattle2013
chicken2011
chicken2012
chicken2013
pig2011
pig2012
pig2013
Prevalence of Multiresistance - E. faecalis
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fig.33
Indices of diversity: Weighted Entropy (E. faecalis)
Index values were much lower than for E. coli reflecting that resistance to high number of
antimicrobials is less frequent. There are no marked differences between animal categories.
Table 17
Veal calves Beef cattle Chickens Pigs
2011 0,21 0,22 0,28 0,23
2012 0,22 0,28 0,25 0,23
2013 0,29 0,23 0,21 0,16
fig.34
0,00
0,20
0,40
0,60
0,80
1,00
calve cattle chicken pig
indices of diversity : Weighted EntropyE. faecalis
2011 2012 2013
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b) E. faecium Prevalence of multiresistance: Table 18 and fig.35
Multirestance was very high in Chickens (>70%) and fluctuating for other species
Table 18 : percentage of multiresistant strains (+95% CI) – E. faecium
% Veal calves Beef cattle Chickens Pigs
2011 67 (9-99) 66 (47-84) 88 (76-99) 50 (5-95)
2012 21 (10-31) 42 (32-52) 80 (73-86) 36 (27-44)
2013 48 (38-57) 19 (8-29) 79 (71-86) 23 (13-33)
fig.35
Trend analysis: Table 19 and fig.36
There was a decreasing trend for multiresistance in E. faecium isolated from Beef cattle and from Pigs and an increasing trend in strains from Calves. However for Beef cattle and Pigs, due to the limited number of tested isolates in 2011 (large CI for estimated prevalence) such trends are probably due to the observations in 2012 and 2013 and should therefore be interpreted with care.
Table 19.The LOGISTIC Procedure- E. faecium Probability modeled is multi=1.
Wald Confidence Interval for Odds Ratios
Label Estimate 95% Confidence Limits
year0 at species=calve ↑*2.353 1.222 4.530
year0 at species=cattle ↓*0.351 0.211 0.583
year0 at species=chickens 0.816 0.523 1.272
year0 at species=pig ↓*0.555 0.314 0.982
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
calves2011
calves2012
calves2013
cattle2011
cattle2012
cattle2013
chicken2011
chicken2012
chicken2013
pig2011
pig2012
pig2013
Prevalence of Multiresistance - E. faecium
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fig.36
Indices of diversity: Weighted Entropy:
As for E. faecalis, index values were low compared to E. coli
Table 20
Veal calves Beef cattle Chickens Pigs
2011 0,08 0,37 0,46 0,22
2012 0,18 0,27 0,35 0,30
2013 0,32 0,17 0,38 0,18
fig.37
0,00
0,20
0,40
0,60
0,80
1,00
calve cattle chicken pig
indices of diversity : Weighted EntropyE. faecium
2011 2012 2013
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IV. Discussion: Summary of observed trends and Comments.
Previous results are summarized hereafter in tables using simple symbols in order to get a
quick and general picture of the situation over the three consecutive years (2011 -2012- 2013)
and to make comparisons between animal categories.
Legend:
++ = High prevalence (close to or > 50%) for the three consecutive years
↑ = increasing trend of resistance
↓ = decreasing trend of resistance
1. E. coli Table 21
High levels of resistance to several antimicrobials for the three consecutive years were
observed in all animal categories except in Beef Cattle. Decreasing trends were observed in
Veal calves and Pigs for antimicrobials for which there was a low to moderate resistance
prevalence. Increasing trends were observed in Beef cattle for two antimicrobials (GEN, KAN)
for which there was a low to moderate resistance prevalence.
The situation is worrying in Broiler chickens: in this animal category, we observed a high
resistance prevalence (≥ 60%) for half of the tested antimicrobials (7/14). Moreover, in this
animal category, increasing trends of resistance were observed for 6 different antimicrobials
(CHL, CIP, COL, FFN, NAL, and STR), including three substances for which there was high
resistance prevalence (CIP, NAL, STR).
Table 21
E. coli Veal Calves Beef Cattle Chickens Pigs
AMP ++ ++ ++
CHL ↓ ↑
CIP ↓ ++ ↑ ↓
COL ↑
FFN ↑
FOT ↓ ↓
GEN ↑
KAN ↑
NAL ↓ ++ ↑ ↓
SMX ++ ++ ++
STR ++ ++ ↑ ++
TAZ
TET ++ ++ ++
TMP ↓ ++ ++
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NB : ESBL- producing strains of E. coli in Chickens
We were specifically interested in looking for a possible a trend in resistance prevalence
from ESBL-producing strains of E. coli in Chickens. Extended-spectrum beta-
lactamases (ESBL) are enzymes that confer resistance to most beta-lactam antibiotics,
including penicillins and cephalosporins but are inhibited by clavulanic acid. It has been
shown in the past that the prevalence of ESBL-strains of E. coli isolated from broiler
chickens in Belgium was high (Smet et al.,2008; Persoons et al.2010). Such a high
prevalence might be caused by the use off-label of cephalosporines in one-day chicks.
It can be considered that isolates that are resistant to either Cefotaxime (FOT) or
Ceftazidime (TAZ) are probably ESBL strains (co-resistance). When looking in detail at
the annual prevalence of resistance against these two antimicrobials, we observed that
for both of them, it increased significantly in 2012 compared to 2011 and then
decreased significantly in 2013 compared to 2012. (Chap. III.A, Table E. coli and
III.B,fig.7)
The trend analysis (Multivariate model) showed an overall significant decrease of
resistance prevalence against FOT but not against TAZ (fig.8 and Annex 2). With the
univariate models the trend was decreasing for both antimicrobials (OR < 1) but it was
not significant although it was very close to significance (upper CI of OR close to 1)
(Table 3 and Fig.9)
Thus, Cefotaxime (FOT) resistance seems to have a tendency to diminish, however
this is not confirmed significantly in Ceftazidime (TAZ) resistance. Speculatively, this
may be due to a diminishment of ctx-M genes (which have a specific activity on
cefotaxime), which frequently occurs in E. coli from poultry, however, only a
retrospective study may confirm this. The presence of AmpC enzymes, may also be a
cause the differences seen.
Therefore we must be careful before drawing definite conclusion and additional data
from the coming years are needed to confirm the current observed trends regarding
resistance against these two specific antimicrobials and more generally regarding
ESBL-producing E. coli strains in chickens
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2. Enterococci spp.
For these bacteria species, the number of tested isolates was sometimes insufficient to obtain
significant trends. This was especially the case for the year 2011.
For E. faecalis resistance prevalence was high for 3 antimicrobials (ERY, STR and TET) in all
animal categories except Pigs for which only the resistance against TET was high. Increasing
resistance was observed mostly in strains from Veal calves including against 2 antimicrobials
for which there was a high prevalence of resistance (ERY and TET). (Table 22)
Table 22
E. faecalis Veal Calves Beef Cattle Chickens Pigs
AMP
CHL ↑ ↑
CIP
ERY ++ ↑ ++ ++
FFN
GEN
LZD ↓
SAL
STR ++ ++ ++
SYN
TET ++ ↑ ++ ++ ++
VAN
For E. faecium the resistance prevalence was generally low to moderate except for SYN for
which there was a very high prevalence of resistance (> 80%) in all animal categories.
Decreasing trends were observed for several antimicrobials in all animal categories except in
Veal calves for which there was an increasing resistance to 2 substances (ERY, TET).(Table
23)
Table 23
E. faecium Veal Calves Beef Cattle Chickens Pigs
AMP
CHL ↓ ↓ ↓
CIP
ERY ↑ ↓
FFN
GEN
LZD ↓
SAL
STR ↓
SYN +++ +++ +++ +++
TET ↑ ↓ ↓
VAN ↓
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3. Multiresistance Table 24
In Chickens, the percentage of multiresistant strains remained very high (>80%)
during the three consecutive years both for E. coli and for Enterococci.
In Veal calves it was very high (>70%) during the three years for E. coli. It was
increasing for Enterococci although the lack of data in 2011 make such trend
questionable.
In Pigs it was high for E. coli and decreasing for E. faecium.
In Beef cattle the level of multiresistance was moderate.
Table 24
Veal Calves Beef Cattle Chickens Pigs
E. coli +++ +++ ++
E. faecalis ↑ ++
E. faecium ↑ ↓ +++ ↓
The comparison of Diversity indices (weighted entropy) shows that for E.coli strains
multiresistance against a high number of antibiotics was higher in isolates from Veal
calves category. The indices were lower for Enterococci isolates in all animal
categories meaning that resistance to high number of antimicrobials was less frequent
compared to E. coli.
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V. Conclusion / recommendations
This study, although based upon data from only three consecutive years (2011-2012-2013),
showed some significant trends for the different animal categories included in the surveillance
programme. However, as already mentioned, these trends will need to be confirmed when
more data will be available in the coming years. Trends were sometimes diverging within the
same animal species, showing an increasing resistance for some antibiotics and decreasing
for others without obvious explanation. The trends observed in Enterococci are sometimes
conflicting with the trends observed in E. coli. This maybe be partly due to the lower number
(in some cases only a few strains could be isolated) of tested isolates of Enterococci. Therefore
the observed trends should be interpreted carefully at this stage.
Nevertheless some of the results are obvious : high to very high prevalences of resistance
were observed for some of the tested antibiotics during the three consecutive years and the
use of such substances should be carefully monitored especially in livestock species with
intensive practices (Veal calves, Broiler chickens, Slaughter pigs), for which the highest
resistance prevalences were observed. The situation is particularly worrying in Broiler chickens
for E. coli: a high resistance prevalence to several antimicrobials was observed and yet, for
some of these antimicrobials, the resistance prevalence was still increasing. It is also in this
animal species that the level of multiresistance was the highest, both in E. coli and Enterococci
isolates. The prevalence of multiresistance was also high for Pigs and Veal calves in E. coli
isolates but no significant increasing/decreasing trend was detected.
Finally, we can conclude that the methodology developed with this study will facilitate the
analysis of the data in the coming years.
However some difficulties were encountered to trace the correct information of part of the
samples, especially regarding the animal category (species) of the samples. It is therefore
recommended to improve the protocol (instructions) for collecting and transmitting the
information along the different steps and by the different actors (sampling at the field by
FAVV/AFSCA, isolation of the strains by Regional laboratories DGZ/ARSIA, susceptibility
testing and data analysis by the Reference Laboratory and the Epidemiology Unit (CODA-
CERVA).
Moreover, the design of the surveillance programme with relation to sample size should be
adapted and calibrated in order to make sure that sufficient data are available to detect
significant trends in the evolution of antimicrobial resistance.
~
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ANNEX 1: List of antimicrobials tested
and Epidemiological cut-off values (ECOFF)
Resistant strain if MIC value of the isolate > Cut-off
1. Panel for E. coli
Symbol Antimicrobial Cut-off value (mg/ml) AMP Ampicillin 8 CHL Chloramphenicol 16 CIP Ciprofloxacin 0,03 COL Colistin 2 FFN Florphenicol 16 FOT Cefotaxime 0,25 GEN Gentamicin 2 KAN Kanamycin 8 NAL Nalidixic acid 16 SMX Sulphonamide 64 STR Streptomycin 16 TAZ Ceftazidime 0,5 TET Tetracycline 8 TMP Trimethoprim 2
2. Panel for Enterococci spp.
Symbol Antimicrobial Cut-off for E. faecalis (mg/ml)
Cut-off for E. faecium (mg/ml)
AMP Ampicillin 4 4 CHL Chloramphenicol 32 32 CIP Ciprofloxacin 4 4 ERY Erythromycin 4 4 FFN Florfenicol 8 8 GEN Gentamicin 32 32 LZD Linezolid 4 4 SAL Salinomycin 4 4 STR Streptomycin 512 128 SYN Synercid
(quinupristin/dalfopristin) 32 1 TET Tetracycline 2 2 VAN Vancomycin 4 4
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ANNEX 2 : Outputs of the Multivariate Models – E. coli
(Generalised Estimating Equation-GEE)
The GENMOD Procedure species= Veal calves – E. coli
Analysis Of GEE Parameter Estimates
Empirical Standard Error Estimates
Parameter Estimate Standard
Error
95% Confidence
Limits
Z Pr > |Z|
Intercept 0.0000 0.0000 0.0000 0.0000 . .
substance AMP 1.2477 0.2827 0.6936 1.8018 4.41 <.0001
substance CHL 0.0636 0.2419 -0.4106 0.5378 0.26 0.7928
substance CIP 0.1062 0.2432 -0.3704 0.5828 0.44 0.6622
substance COL -2.1459 0.4463 -3.0206 -1.2712 -4.81 <.0001
substance FFN -2.2517 0.4232 -3.0811 -1.4222 -5.32 <.0001
substance FOT -2.3141 0.3532 -3.0064 -1.6219 -6.55 <.0001
substance GEN -1.9009 0.4168 -2.7179 -1.0840 -4.56 <.0001
substance KAN -0.7364 0.2592 -1.2444 -0.2283 -2.84 0.0045
substance NAL -0.1565 0.2434 -0.6334 0.3205 -0.64 0.5203
substance SMX 1.3932 0.2884 0.8278 1.9585 4.83 <.0001
substance STR 0.6306 0.2532 0.1343 1.1268 2.49 0.0128
substance TAZ -2.2168 0.3409 -2.8850 -1.5486 -6.50 <.0001
substance TET 1.2907 0.2988 0.7050 1.8764 4.32 <.0001
substance TMP 1.1719 0.2748 0.6334 1.7105 4.27 <.0001
year0*substance AMP -0.3373 0.1864 -0.7026 0.0279 -1.81 0.0703
year0*substance CHL -0.3854 ↓* 0.1622 -0.7034 -0.0674 -2.38 0.0175
year0*substance CIP -0.4095 ↓* 0.1596 -0.7223 -0.0966 -2.57 0.0103
year0*substance COL -0.3095 0.3181 -0.9330 0.3141 -0.97 0.3307
year0*substance FFN 0.0898 0.2756 -0.4504 0.6299 0.33 0.7446
year0*substance FOT -0.3240 0.2208 -0.7567 0.1088 -1.47 0.1423
year0*substance GEN -0.3338 0.2963 -0.9146 0.2470 -1.13 0.2600
year0*substance KAN -0.1859 0.1716 -0.5223 0.1504 -1.08 0.2785
year0*substance NAL -0.3897 ↓* 0.1618 -0.7068 -0.0725 -2.41 0.0160
year0*substance SMX -0.3070 0.1926 -0.6844 0.0704 -1.59 0.1109
year0*substance STR -0.1763 0.1665 -0.5025 0.1499 -1.06 0.2895
year0*substance TAZ -0.3066 0.2134 -0.7249 0.1116 -1.44 0.1507
year0*substance TET -0.0725 0.2033 -0.4709 0.3259 -0.36 0.7214
year0*substance TMP -0.4414 ↓* 0.1803 -0.7949 -0.0879 -2.45 0.0144
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The GENMOD Procedure
species= Beef cattle – E. coli
Analysis Of GEE Parameter Estimates
Empirical Standard Error Estimates
Parameter Estimate Standard
Error
95% Confidence
Limits
Z Pr > |Z|
Intercept 0.0000 0.0000 0.0000 0.0000 . .
substance AMP -0.8345 0.1559 -1.1401 -0.5290 -5.35 <.0001
substance CHL -1.7479 0.2016 -2.1430 -1.3528 -8.67 <.0001
substance CIP -1.6446 0.1913 -2.0195 -1.2697 -8.60 <.0001
substance COL -4.3356 0.5438 -5.4013 -3.2698 -7.97 <.0001
substance FFN -2.7635 0.3027 -3.3568 -2.1703 -9.13 <.0001
substance FOT -2.8865 0.3129 -3.4997 -2.2733 -9.23 <.0001
substance GEN -3.7344 0.4576 -4.6313 -2.8375 -8.16 <.0001
substance KAN -2.6350 0.2626 -3.1497 -2.1202 -10.03 <.0001
substance NAL -1.7928 0.2012 -2.1872 -1.3984 -8.91 <.0001
substance SMX -0.6533 0.1505 -0.9483 -0.3583 -4.34 <.0001
substance STR -0.8208 0.1550 -1.1246 -0.5170 -5.30 <.0001
substance TAZ -2.8607 0.2937 -3.4363 -2.2851 -9.74 <.0001
substance TET -1.0949 0.1597 -1.4078 -0.7820 -6.86 <.0001
substance TMP -1.2451 0.1689 -1.5762 -0.9140 -7.37 <.0001
year0*substance AMP -0.1858 0.1146 -0.4104 0.0389 -1.62 0.1051
year0*substance CHL 0.1021 0.1437 -0.1797 0.3838 0.71 0.4777
year0*substance CIP -0.1118 0.1388 -0.3839 0.1603 -0.81 0.4207
year0*substance COL 0.2339 0.3373 -0.4271 0.8949 0.69 0.4879
year0*substance FFN 0.3599 0.2017 -0.0354 0.7552 1.78 0.0743
year0*substance FOT -0.1194 0.2299 -0.5699 0.3311 -0.52 0.6034
year0*substance GEN 0.5779 ↑* 0.2830 0.0233 1.1325 2.04 0.0411
year0*substance KAN 0.3973 ↑* 0.1687 0.0666 0.7279 2.35 0.0185
year0*substance NAL -0.1560 0.1491 -0.4482 0.1363 -1.05 0.2956
year0*substance SMX 0.0424 0.1093 -0.1719 0.2567 0.39 0.6982
year0*substance STR 0.0093 0.1128 -0.2118 0.2304 0.08 0.9341
year0*substance TAZ -0.1888 0.2107 -0.6017 0.2241 -0.90 0.3701
year0*substance TET 0.0307 0.1142 -0.1931 0.2545 0.27 0.7881
year0*substance TMP 0.0280 0.1221 -0.2113 0.2673 0.23 0.8186
CODA-CERVA
Scientific research at the service of safe food production and animal health
52
The GENMOD Procedure species= Broiler chickens– E. coli
Analysis Of GEE Parameter Estimates
Empirical Standard Error Estimates
Parameter Estimate Standard
Error
95% Confidence
Limits
Z Pr > |Z|
Intercept 0.0000 0.0000 0.0000 0.0000 . .
substance AMP 1.6532 0.1226 1.4129 1.8936 13.48 <.0001
substance CHL -0.9130 0.0968 -1.1027 -0.7233 -9.43 <.0001
substance CIP 0.7040 0.0983 0.5113 0.8967 7.16 <.0001
substance COL -4.2771 0.3019 -4.8689 -3.6854 -14.17 <.0001
substance FFN -4.3134 0.3333 -4.9666 -3.6602 -12.94 <.0001
substance FOT -1.2169 0.1148 -1.4419 -0.9918 -10.60 <.0001
substance GEN -3.0591 0.2122 -3.4751 -2.6432 -14.41 <.0001
substance KAN -2.3568 0.1513 -2.6533 -2.0602 -15.58 <.0001
substance NAL 0.6697 0.0982 0.4771 0.8622 6.82 <.0001
substance SMX 1.2194 0.1105 1.0028 1.4360 11.03 <.0001
substance STR 0.9326 0.1045 0.7279 1.1374 8.93 <.0001
substance TAZ -1.3708 0.1187 -1.6035 -1.1382 -11.55 <.0001
substance TET 0.7029 0.1025 0.5020 0.9038 6.86 <.0001
substance TMP 0.6292 0.0970 0.4391 0.8193 6.49 <.0001
year0*substance AMP -0.0234 0.1059 -0.2309 0.1841 -0.22 0.8253
year0*substance CHL 0.2644 ↑* 0.0818 0.1040 0.4247 3.23 0.0012
year0*substance CIP 0.3386 ↑* 0.0960 0.1505 0.5267 3.53 0.0004
year0*substance COL 0.4841 ↑* 0.1801 0.1312 0.8370 2.69 0.0072
year0*substance FFN 0.5196 ↑* 0.2090 0.1100 0.9292 2.49 0.0129
year0*substance FOT -0.1909 ↓* 0.0959 -0.3789 -0.0028 -1.99 0.0467
year0*substance GEN 0.1430 0.1718 -0.1938 0.4797 0.83 0.4054
year0*substance KAN 0.1829 0.1188 -0.0500 0.4157 1.54 0.1237
year0*substance NAL 0.2140 ↑* 0.0930 0.0316 0.3963 2.30 0.0215
year0*substance SMX -0.1032 0.0968 -0.2928 0.0864 -1.07 0.2862
year0*substance STR 0.1852 0.0989 -0.0087 0.3791 1.87 0.0613
year0*substance TAZ -0.1430 0.0992 -0.3374 0.0515 -1.44 0.1496
year0*substance TET -0.0746 0.0878 -0.2466 0.0975 -0.85 0.3955
year0*substance TMP -0.0262 0.0857 -0.1943 0.1418 -0.31 0.7595
CODA-CERVA
Scientific research at the service of safe food production and animal health
53
The GENMOD Procedure
species= Pigs – E. coli
Analysis Of GEE Parameter Estimates
Empirical Standard Error Estimates
Parameter Estimate Standard
Error
95% Confidence
Limits
Z Pr > |Z|
Intercept 0.0000 0.0000 0.0000 0.0000 . .
substance AMP -0.0146 0.1409 -0.2907 0.2615 -0.10 0.9172
substance CHL -0.9472 0.1601 -1.2609 -0.6334 -5.92 <.0001
substance CIP -1.5062 0.1823 -1.8636 -1.1488 -8.26 <.0001
substance COL -5.6045 1.0911 -7.7431 -3.4660 -5.14 <.0001
substance FFN -2.9245 0.3200 -3.5517 -2.2974 -9.14 <.0001
substance FOT -3.0338 0.3490 -3.7177 -2.3498 -8.69 <.0001
substance GEN -3.5529 0.5123 -4.5569 -2.5489 -6.94 <.0001
substance KAN -3.4548 0.3958 -4.2306 -2.6791 -8.73 <.0001
substance NAL -1.8138 0.2001 -2.2060 -1.4217 -9.07 <.0001
substance SMX 0.4098 0.1501 0.1155 0.7041 2.73 0.0063
substance STR 0.1348 0.1441 -0.1476 0.4172 0.94 0.3494
substance TAZ -3.0367 0.3484 -3.7195 -2.3538 -8.72 <.0001
substance TET 0.3729 0.1517 0.0756 0.6701 2.46 0.0140
substance TMP 0.0923 0.1458 -0.1935 0.3780 0.63 0.5267
year0*substance AMP -0.0854 0.1055 -0.2921 0.1213 -0.81 0.4181
year0*substance CHL -0.0239 0.1189 -0.2569 0.2090 -0.20 0.8404
year0*substance CIP -0.3857 ↓* 0.1433 -0.6667 -0.1048 -2.69 0.0071
year0*substance COL 0.9916 0.6304 -0.2440 2.2271 1.57 0.1157
year0*substance FFN -0.3652 0.2589 -0.8726 0.1422 -1.41 0.1583
year0*substance FOT -0.6980 ↓* 0.3315 -1.3478 -0.0482 -2.11 0.0353
year0*substance GEN -0.3502 0.4490 -1.2301 0.5297 -0.78 0.4354
year0*substance KAN 0.2993 0.2678 -0.2256 0.8242 1.12 0.2637
year0*substance NAL -0.4798 ↓* 0.1625 -0.7982 -0.1613 -2.95 0.0031
year0*substance SMX -0.1077 0.1101 -0.3234 0.1080 -0.98 0.3277
year0*substance STR 0.0431 0.1070 -0.1667 0.2529 0.40 0.6874
year0*substance TAZ -0.4541 0.2831 -1.0089 0.1006 -1.60 0.1086
year0*substance TET -0.1172 0.1108 -0.3343 0.1000 -1.06 0.2904
year0*substance TMP -0.0544 0.1078 -0.2656 0.1568 -0.50 0.6139