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)

CODA-CERVA

Scientific research at the service of safe food production and animal health

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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

http://www.uhasselt.be/censtat

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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

http://www.coda-cerva.be/index.php?option=com_content&view=article&id=121&Itemid=286&lang=en

http://www.coda-cerva.be/index.php?option=com_content&view=article&id=121&Itemid=286&lang=en

http://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


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


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


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


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


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)

CODA-CERVA


17

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.

CODA-CERVA


18

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

CODA-CERVA


19

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

CODA-CERVA


20

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



fig.5

0

20

40

60

80

100

2011 2012 2013

%

Prevalence of Resistance Beef Cattle - E.coli



CODA-CERVA


21

Table 2: The LOGISTIC Procedure E. coli - species= Beef cattle




year0 at substance=CHL 1.081 0.815 1.434

year0 at substance=CIP 0.887 0.662 1.189






year0 at substance=NAL 0.852 0.622 1.166





year0 at substance=TMP 1.008 0.787 1.292

fig.6

CODA-CERVA


22

c) Broiler Chickens: Tested samples per year: N= 420 (2011) ; 320 (2012) ; 234 (2013)


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



fig.8

0

20

40

60

80

100

2011 2012 2013

%Prevalence of Resistance

Chickens -E.coli



CODA-CERVA


23

Table 3.The LOGISTIC Procedure E. coli - species=chickens




year0 at substance=CHL ↑*1.297 1.098 1.533

year0 at substance=CIP ↑*1.435 1.195 1.725






year0 at substance=NAL ↑*1.259 1.057 1.499


year0 at substance=STR ↑*1.210 1.006 1.455




fig.9

CODA-CERVA


24

d) Pigs: Tested samples per year: N= 157 (2011) ; 217 (2012) ; 206 (2013)


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



fig.11

0

10

20

30

40

50

60

70

2011 2012 2013

%

Prevalence of Resistance Pigs -E.coli



CODA-CERVA


25

Table 4.The LOGISTIC Procedure E. coli - species=pig





year0 at substance=CIP ↓*0.668 0.491 0.910



year0 at substance=FOT ↓*0.504 0.258 0.985



year0 at substance=NAL ↓*0.620 0.432 0.889






fig.12

CODA-CERVA


26

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



CODA-CERVA


27

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




year0 at substance=CHL ↑*3.378 1.396 8.171


year0 at substance=ERY ↑*2.491 1.078 5.761



year0 at substance=LZD 0.342 0.018 6.334

year0 at substance=SAL 0.545 0.115 2.576


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

CODA-CERVA


28

Table 6. The LOGISTIC Procedure species= Veal calves

E. faecium






year0 at substance=ERY ↑*2.420 1.279 4.580







year0 at substance=TET ↑*2.183 1.164 4.094


fig.16

CODA-CERVA


29

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)


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



0

20

40

60

80

100

2011 2012 2013

%

Prevalence of Resistance Cattle -E. faecium



CODA-CERVA


30

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




year0 at substance=CHL ↑ *2.303 1.197 4.432


year0 at substance=ERY 0.793 0.411 1.528









fig.19

CODA-CERVA


31

Table 8. The LOGISTIC Procedure species= Beef cattle

E. faecium






year0 at substance=ERY ↓*0.426 0.261 0.694





year0 at substance=STR ↓*0.439 0.265 0.727


year0 at substance=TET ↓*0.323 0.193 0.540


fig.20

CODA-CERVA


32

c) Broiler chickens: Tested samples/year: E. faecalis: N=81 (2011) ;149 (2012) ; 71 (2013)

E. faecium: N=33 (2011) ; 161 (2012) ;113 (2013)


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



0

20

40

60

80

100

2011 2012 2013

%

Prevalence of Resistance Chickens -E. faecium



CODA-CERVA


33

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









year0 at substance=LZD ↓*0.323 0.113 0.926






fig.23

CODA-CERVA


34

Table 10. The LOGISTIC Procedure species=chickens

E. faecium









year0 at substance=LZD ↓*0.042 0.002 0.724





year0 at substance=VAN ↓*0.170 0.037 0.771

fig.24

CODA-CERVA


35

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



0

20

40

60

80

100

2011 2012 2013

%

Prevalence of Resistance Pigs -E. faecium



CODA-CERVA


36

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















fig.27

CODA-CERVA


37

Table 12.The LOGISTIC Procedure species=pig E. faecium















fig.28

CODA-CERVA


38

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.



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

CODA-CERVA


39

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


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

CODA-CERVA


40

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


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.



year0 at species=calve ↑*3.007 1.311 6.896

year0 at species=cattle 1.286 0.689 2.398


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

CODA-CERVA


41

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


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


indices of diversity : Weighted EntropyE. faecalis

2011 2012 2013

CODA-CERVA


42

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.



year0 at species=calve ↑*2.353 1.222 4.530

year0 at species=cattle ↓*0.351 0.211 0.583


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

CODA-CERVA


43

fig.36

Indices of diversity: Weighted Entropy:

As for E. faecalis, index values were low compared to E. coli

Table 20


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


indices of diversity : Weighted EntropyE. faecium

2011 2012 2013

CODA-CERVA


44

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

CODA-CERVA


46

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.

CODA-CERVA


48

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.

~

CODA-CERVA


49

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




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 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 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

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The GENMOD Procedure species= Broiler chickens– E. coli




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 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 TMP -0.0262 0.0857 -0.1943 0.1418 -0.31 0.7595

CODA-CERVA


53

The GENMOD Procedure

species= Pigs – E. coli




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 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 TMP -0.0544 0.1078 -0.2656 0.1568 -0.50 0.6139

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