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Hotspots of antimicrobial resistance in
human & veterinary medicine
Anne Ingenbleek
Mat Goossens
Natacha Viseur
Sylvanus Fonguh
Naima Hammami
Marie-Laurence Lambert
Karl Mertens
Katrien Latour
Béatrice Jans
Boudewijn Catry*
www.nsih.be
Rue Juliette Wytsmanstraat 14 | 1050 Brussels | Belgium
T +32 2 642 51 11 | F +32 2 642 54 10 | email: [email protected] | http://www.nsih.be
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One Health
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Causal relationship antibiotic consumption & resistance
Carb
apenem
-resi
stant
Pse
udom
onas
aeru
gin
osa
(%
)
Carb
apenem
use
(D
DD
s)
Lepper PM et al., 2002 (Germany)
Intervention programmes (AST)
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Causal relationship inadequate
therapy & mortality
The Influence of Inadequate Antimicrobial
Treatment of Bloodstream Infections on
Patient Outcomes in the ICU Setting*
Ibrahim et al., Chest 2000, 118 (1)
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Objective
To demonstrate at the individual patient level
associations between antibiotic (AB)
consumption and antibacterial resistance
• Infections & colonisation (Pathogens & commensals)
• Dosis/response effect (Defined Daily Dose, WHO)
• Adjusting for covariates
Risk factors for antibacterial resistance at the individual level:
a multicentric study (IARG)
Evidence: aggregated population level
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Risk factors MRSA infection/colonisation
multivariate analysis (n= 6844)
Variable Adjusted OR (95%CI) p-value
MRSA positive related to type of health care setting
No admission 1527 1 -
Acute hospital 4647 0,86 0,74 1,01 0,069
Nursing home (LTCF) 560 3,53 2,79 4,46
<0,001
Other setting 110 1,43 0,93 2,19
0,102
AB consumption prior to sampling (prescription prior or on the day of sampling)
Absent 1519 1 -
Ambulant (FARM) 3706 0,91 0,73-1,14
0,425
In hospital (HOSP) 1619 1,62 1,30 2,01
<0,001
Amount of AB use prior to sampling
per DDD 1,32 1,25 1,40
<0,001
Age category
0-14 757 1 -
15-54 1837 1,63 1,23 2,16 0,001
55-104 4250 4,32 3,32 5,63
<0,001
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Monthly FQ consumption, expressed as DDD/1000 PD. Filled circles, pre-intervention period values; open circles, intervention period values; diamonds, post-intervention period values.
Lafaurie M et al. J. Antimicrob. Chemother. 2012;67:1010-1015
© The Author 2012. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: [email protected]
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Monthly consumption of ABHR solution.
Lafaurie M et al. J. Antimicrob. Chemother. 2012;67:1010-1015
© The Author 2012. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: [email protected]
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Change in monthly FQ-resistant P. aeruginosa rates, from 2002 to 2010.
Lafaurie M et al. J. Antimicrob. Chemother. 2012;67:1010-1015
© The Author 2012. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: [email protected]
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Change in monthly MRSA rates, from 2002 to 2010.
Lafaurie M et al. J. Antimicrob. Chemother. 2012;67:1010-1015
© The Author 2012. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: [email protected]
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Mission
To provide standardized definitions and tools for the containment
of health care associated infections in hospitals and nursing
homes, and to establish national reference data on incidence of
nosocomial infections and antimicrobial resistance.
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SURVEILLANCE (1/2)
Four Mandatory Surveillances in Acute Care Hospitals
1. Methicillin resistant Staphylococcus aureus
2. Clostridium difficile (optional: ribotyping)
3. Antimicrobial use in hospitals
4. One out of 4 optional surveillances:
• Septicaemias hospital wide
• Surgical site infections
• Intensive care units
• Extended spectrum beta-lactamases
In progress: quality indicators
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SURVEILLANCE (2/2)
Volontary projects in Hospitals & Nursing homes
Hand hygiene campaigns (fifth in preparation, launch 2012)
Point Prevalence survey on HCAI & AM
MRSA, ESBL & VRE in Nursing homes (BAPCOC)
Other projects - Expertise
EARSS, ESAC,
BelVet-SAC, ESVAC, PILGRIM…
TATFAR, CODEX alimentarius (WHO/FAO/OIE)
promotor Master Thesis, reviewing articles, parlementary questions
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Point prevalence survey: PPS (photo)
Surveillance contineously (film)
&
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Surveillances
&
FEEDBACK
MRSA
Campagnes
Indicateurs USI & ISO
Septicémies
C. difficile
Gram -
ABU
Rectangle = mandatory
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Annual N casulties
2000 in 2008 (www.wiv-isp.be)
Nosocomial infections: 6250 in 2007 (KCE 92A)
+850 in
2012 (bivv.be)
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MRSA evolution
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Portage connu 43,6%
Transfert d'un hôpital 14,1%
Transfert d'une MR/MRS
12,6%
Transfert d'un Hôpital et MR/MRS
6%
Communautaire 14,4%
Contacts inconnus9,3%
Jans & Denis, 2011 Individual hospital/NH is client!
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Carbapenemase producing
enterobacteriaceae
SHC, 2012
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Global evolution of hand hygiene compliance
4th campaign
preliminary results!
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Fourth Handhygiene campagne
Rolemodel physicians
!New module: January 11 2013 – www.nsih.be
.2.4
.6.8
1nurse MD
Com
plia
nce H
H (
%)
Graphs by hhfct
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Point prevalence survey: PPS (photo)
Surveillance contineously (film)
&
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Materials & methods
Specialities to be reported (WHO, ESAC,
pubMED)
ATC classification:
A07A Antibiotics for gastro-intestinal use
J01, P01AB Antibiotics
J02, D01BA Antimycotics for systemic use
J04A Tuberculostatics
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ATC Class
J01C Beta-lactam antibacterials, penicillins
J01D Other beta-lactam antibacterials
J01M Quinolone antibacterials
J01X Other antibacterials
J02A Antimycotics for systemic use
J01F Macrolides, lincosamides and streptogramins
J01G Aminoglycoside antibacterials
J04A Drugs for treatment of tuberculosis
J01E Sulfonamides and trimethoprim
A07A Intestinal anti-infectives
P01A Agents against amoebiasis/protozoal diseases
J01A3 Tetracyclines
D01B Antifungals for systemic use
J01B0 Amphenicols
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Outils informatiques
SEP, SI (ICU), ISO (SSI), HH: NSIHwin (Application MS Access)
CDIF, MRSA … ABU (déc 07)…: NSIHweb • => comparaison immédiate avec les données nationales
• => mise à jour « automatique »
• => input & upload des données ( charge de travail)
• Données communes (dénominateurs/mois, charactéristiques des hôpitaux, services & unités)
• Autres fonctions d’analyse etc (ex. détection des épidémies) à définir avec groupe de travail
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DATA MANAGEMENT
Upload Feedback
• ‘Tarification Units’
• ljst TUC codes
• ‘molecules’
• expressed as DDD
(Defined Daily Dose)
use (TUC) / Factor = use (DDD)
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Example
Example : amoxicillin
J01CA04
J01CA04
ATC code
20 units
40 units
Use (TUC)
1000
1000
DDD
20 2
AMOXICILLINE TEVA
CAPS 1 X 500 MG
744185
5 4 AMOXICILLINE TEVA
SIR 1 X 250MG/5ML
744433
Use (DDD) Factor Label TUC
use (TUC) / Factor = use (DDD)
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REALTIME FEEDBACK
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FEEDBACK Compare own use with national mean
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AUTOMATIC FEEDBACK Local follow up
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FEEDBACK
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OBJECTIVES MODULE
Hospitals • realtime feedback
• Automatic recalculation (TUC DDD)
• Local monitoring information for ABMT
Authorities • trend monitoring
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DDD/1000 patient days
DDD/1000 admissions
J01: ANTIBACTERIALS FOR SYSTEMIC USE
Antibacterials for Systemic Use (JO1)
0
100
200
300
400
500
600
700
2006 2007 2008 2009 2010
DD
D/1
000 h
osp
italisati
on
days
National mean
median (p50)
Antibacterials for Systemic Use (J01)
0
1000
2000
3000
4000
5000
6000
2006 2007 2008 2009 2010
DD
D/1
000 a
dm
issio
ns
National mean
median (p50)
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Graph 1 - Total AMD use ALL antimicrobials (DDD/1000 beddays), 2006-2010 J01 + J02 + J04A + A07A + P01AB + D01B
2006 2007 2008 2009 2010
p50 479 565 558 570 573
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Graph 1 – use ANTIBACTERIALs (DDD/1000 beddays), 2006-2010
ANTIBACTERIALS FOR SYSTEMIC USE J01
2006 2007 2008 2009 2010
p50 467 527 530 545 537
J01
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Non Pediatric Wards
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Stratified by ward: antibacterials
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Stratified by ward: antimycotics
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ESAC
National level, all antimicrobials included
Year Participants Total DDD for the year DDD/1000 Nights
2008 121 7315319.20 579.734
2009 124 7273099.57 583.651
2010 120 6940067.65 585.087
2011* 106 6561559.15 581.215
2011*: The data collection for the year 2011* is on-going.
HOSPITALS
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Community
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Hospitals
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Evolution - long term
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Point prevalence survey: PPS (photo)
Surveillance contineously (film)
&
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Point Prevalence Survey: Hai - ABU
Why? - A need to standardize protocols in EU
- Measuring prevalence, not incidence short measuring period
less labor intensive
What is measured? AB use – Hai
Result:
• estimate the total burden
• describe patients
• invasive procedures
• infections
• antimicrobials prescribed
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Point Prevalence Survey: Hai - ABU
Percentage patients with HAI: 7.0%
0%
5%
10%
15%
20%
25%
11
13
15
20
38
59
58
34
27
63
49
30
50 2
62
14
51
61
40
37 7
48
55
41
16
18
17
46
33
24
57
21
12
36
56
19
39
43
60 5
53
22
42 4
29
45
23
28
32
44
52
35 6
54 8
47 3 1
26
31 9
25
10
Hospital number
% p
ati
en
ts w
ith
HA
I
Mean prevalence: 7% [0%-23%]
Courtesy UA
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Prevalence of AM use by Hospital
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
% on AM
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
10
17
44 7
19
20 8
13 6
60
28 4
23
18 9 5
12 3
22
21
11
59
25
45
26
43
47
16
34
36
avera
ge
61
52
54
39
32
40
46
49
35
42
41
24
33
58 1
37
27
56
62 2
63
29
50
51
48
53
57
31
55
14
38
30
15
Mean: 38% [2% – 100%] Net: 35%
Courtesy UA
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Point Prevalence Survey: Hai - ABU
23%
44%
1%
13%
4% 4%
3%
8%
15%
Indication for Antimicrobial N=5543
HI
CI
LI
M
U
S1
S2
S3
On antimicrobials: 36.6% Mean antimicrobials for those on antimicrobials: 1.5
:acute hospital-acquired
:community-acquired
:acquired in NH
:medical prophylaxis
:unknown reason
:single dose
:one day
:> 1 day Surg
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Point Prevalence Survey: Hai - ABU
Zarb et al., 2012 Eurosurveillance
Healthcare-associated infection sites Indication for antimicrobial treatment
N pts (a) Prevalence% (95%CI) (b)
N HAI (c) Relative % HAI (d)
Total Relative
% use
CI* % HI** %
Pneumonia & other LRTI 392 2.0% (1.8-2.2) 394 25.7% 1328 29.2% 922 31.6% 382 24.8%
Surgical site infections (e) 290 1.5% (1.3-1.6) 290 18.9%
Urinary tract infections 263 1.3% (1.2-1.5) 264 17.2% 679 14.9% 412 14.1% 237 15.4%
Bloodstream infections (BSI)(f)
216 1.1% (0.9-1.2) 217 14.2% 219 4.8% 67 2.3% 145 9.4%
Gastro-intestinal system infections
118 0.6% (0.5-0.7) 119 7.8% 593 13.0% 466 16.0% 117 7.6%
Skin and soft tissue infections 59 0.3% (0.2-0.4) 59 3.9% 646 14.2% 357 12.2% 279 18.1%
Bone and joint infections 38 0.2% (0.1-0.3) 39 2.5% 154 3.4% 92 3.2% 60 3.9%
Eye, Ear, Nose or Mouth infection
47 0.2% (0.2-0.3) 47 3.1% 211 4.6% 170 5.8% 41 2.7%
Systemic infections(f) 40 0.2% (0.1-0.3) 40 2.6% 668 14.7% 318 10.9% 334 21.7%
Cardiovascular system infections
26 0.1% (0.1-0.2) 26 1.7% 76 1.7% 40 1.4% 36 2.3%
Central nervous system infections
15 0.1% (0.0-0.1) 15 1.0% 67 1.5% 54 1.8% 12 0.8%
Catheter-related infections w/o BSI(e)
11 0.1% (0.0-0.1) 11 0.7%
Reproductive tract infections 10 0.1% (0.0-0.1) 10 0.7% 65 1.4% 49 1.7% 16 1.0%
Missing/Unknown NA 65 1.4% 39 1.3% 25 1.6%
Total 1408 7.1% (6.7-7.5) 1531 100% 4552 100% 2919 100% 1539 100%
Table 2. Healthcare associated infection (HAI) and antimicrobial use prevalence by site
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Point Prevalence Survey: Hai - ABU
Zarb et al., 2012 Eurosurveillance
N pts (a) Prevalence%
(95%CI) (b)
N HAI (c) Relative
% HAI (d)
Pneumonia & other LRTI 392 2.0% (1.8-2.2) 394 25.7%
Surgical site infections (e) 290 1.5% (1.3-1.6) 290 18.9%
Urinary tract infections 263 1.3% (1.2-1.5) 264 17.2%
Bloodstream infections (BSI)(f) 216 1.1% (0.9-1.2) 217 14.2%
Gastro-intestinal system
infections
118 0.6% (0.5-0.7) 119 7.8%
Skin and soft tissue infections 59 0.3% (0.2-0.4) 59 3.9%
Bone and joint infections 38 0.2% (0.1-0.3) 39 2.5%
Eye, Ear, Nose or Mouth infection 47 0.2% (0.2-0.3) 47 3.1%
Systemic infections(f) 40 0.2% (0.1-0.3) 40 2.6%
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Les infections liées aux soins et la consommation d’antimicrobiens dans les institutions de soins chroniques belges (projet HALT, 2010)
Rue Juliette Wytsmanstraat 14 | 1050 Brussels | Belgium
T +32 2 642 51 11 | F +32 2 642 50 01 | email: [email protected] | www.wiv-isp.be
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Résultats: Nursing homes
• 722 LTCF de 25 pays européens
• 111 établissements belges
• 107 MRS
• 3 institutions Sp
• 1 institution de psychiatrie
chronique
• 12 727 résidents éligibles
Eligible residents: < 250 250 - 499 500 - 999 1000 - 4999 > 5000
Courtesy: K. Latour
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Résultats: caractéristiques des résidents
50% 85+ ans 25.7% masculin
8.1%3.4%0.2%2.6%
41.1%48.3%
59.0%
0
20
40
60
80
100
Incontinence
Désorientatio
n
Chaise roulanté ou alité
e
Cathéter urin
aire
Cathéter vasculaire
Plaie d'escarre
Autre plaie
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Résultats: la consommation d’antimicrobiens
• 554 résidents, 578 molécules
• Prévalence: 4.7% (0-15.7%)
• 96% antibactériens à usage systémique (classe ATC J01)
Aminoglycosid
es (J01G) 0,4%
Tétracyclines
(J01A) 2,3%
Sulfamides
(J01E) 3,2%Autres beta-
lactams
(J01D) 4,1%Macrolides
(J01F) 4,7%
Quinolones
(J01M) 20,4%Beta-lactam
pen. (J01C)
27,9%
Autres
antibactériens
(J01X) 36,9%
1
3
2
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Résultats: la consommation d’antimicrobiens
• 68.5% prescriptions thérapeutiques
• 31.5% prescriptions prophylactiques
48.7% 31.8% 10.8%
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Résultats: les infections liées aux soins
•390 infections confirmées, 361 résidents
•Prévalence: 3.1% (0-11.9%)
Infection GI; 21;
5%Fièvre; 3; 1%
BSI; 2; 1% Autre infection;
21; 5%
Nez/gorge/oreil
les/yeux; 39;
10%
Infection
respiratoire;
187; 48%
Infection
cutanée; 81;
21%
Infection
urinaire; 36; 9%1
3
2
4
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Courtesy: Jans B. & Latour K.
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Concluding remarks HUMAN
Within hospital evolution >> bench marking
stratification: service (ICU), type, size, region
Hospital evolution
MRSA, MRE, Cdiff, HH compliance… can be combined
- Monthly introductin required - Many have done this retrospectively!!!
Future: evolution i.f.v. DRG (project AMTABU)
- hip/knee replacement & CAP
Nursing homes:
less AB use
profylaxis UTI can be improved
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One Health
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MRSA evolution
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n. hôpitaux 29 34 44 48 41 43
Evolution of MRSA-incidence upon admission
Vandendriessche et al, 2012
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QUIZ: Prevalence Livestock associated MRSA
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Veal calves farmer a 72% LA-MRSA
Swine farmer 38% LA-MRSA
Inpatient hospital 1.6-25% MRSA
Nursing home resident 13% MRSA
Veterinarians 7.5% LA-MRSA
Poultry farmers a 3% LA-MRSA
Upon hospital admission 1.6% MRSA
General population 0.5% MRSA
a Samples from non-mixed farms
Livestock-associated MRSA
Gordts, 2007 Denis, JAC 2010 Denis, EID 2009
Vandendriessche, JAC 2012 Garcia-Graells, E&I 2011
Goossens et al., 2012
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18 13
4
10
3
1
1
4
MRSA ST398 (infection + screening)
ReferentieLaboratorium voor Stafylokokken - MRSA
Courtesy:
Vandendriessche S
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Swine farms density
Ribbens, Prev Vet Med 2009
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Veal calves density
E. Ducheyne and B. Pardon, 2012
Courtesy:
Vandendriessche S
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Consumption patterns across animal species
76
Persoons et al., 2012 Callens et al., 2012 Catry et al., under revision Pardon et al., 2012
0
100
200
300
400
500
600
poultry pigs dairy cattle beef cattle veal calves
Tre
atm
en
t in
cid
en
ce o
n U
DD
(an
imal
s/1
00
0 d
aily
tr
eae
d)
Antimicrobial use in livestock in Belgium
Courtesy: B. Pardon
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Indications and timing
BRD (53%)
Arrival prophylaxis (13%), diarrhea (12%), dysbacteriosis (12%)
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Pe
rce
nta
ge
of
vea
l co
ho
rts
Weeks on feed
respiratory disease
arrival prophylaxis
diarrhea
dysbacteriosis
enterotoxaemia
idiopathic peritonitis
Pardon ea, JAC 2012
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Which compounds are used?
Oxytetracycline (23,7%), amoxicillin (18,5%), tylosin (17,2%) and colistin (15,2%) were most
frequently used
0.00 20.00 40.00 60.00 80.00 100.00 120.00 140.00 160.00
colistin
sulphonamides + trimethoprim
doxycyclin
oxytetracycline
tilmicosin
tylosin
ampicillin
amoxycillin
flumequine
enrofloxacin
per 1000 animals
Cla
ssif
icat
ion
of
anti
mic
rob
ials
acc
ord
ing
to
imp
ort
ance
fo
r h
um
an m
ed
icin
e
TIUDD
II
I
Pardon ea, JAC 2012
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Resistentieprofiel LA-MRSA
Aminosides Macrolides, lincosamides
Co-selectie van resistentie
MRSA huidinfecties bij de mens worden vaak behandeld met doxycycline
of clindamycine Niet aangewezen voor LA-MRSA infecties
0
20
40
60
80
100
VarkensMensen
Vandendriessche, JAC 2012
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Possible outcomes of exposure
to resistant bacteria
P.L. Geenen, M.G.J. Koene, H. Blaak,
A.H. Havelaar, A.W. van de Giessen
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Bacteria & Co-selection of Resistance
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Evolution E. coli multiresistance
P.L. Geenen, M.G.J. Koene, H. Blaak,
A.H. Havelaar, A.W. van de Giessen
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Evolution E. coli multiresistance
P.L. Geenen, M.G.J. Koene, H. Blaak,
A.H. Havelaar, A.W. van de Giessen Vaporization: ceftiofur
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Evolution E. coli multiresistance
P.L. Geenen, M.G.J. Koene, H. Blaak,
A.H. Havelaar, A.W. van de Giessen
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www.BelVet-SAC.ugent.be
Among European countries 2010: Belgium is the 3rd highest
consumer of antimicrobials in veterinary medicine.
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www.BelVet-SAC.ugent.be
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Comparison Oral (Feed) vs
Injection
Checkley e.a., CVJ / VOL 51 / AUGUST 2010
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Resistance E. coli
Type period
(N
herds)
N ARIa AMP
b
AMC CEF TET TMP NEO GEN SPT STR NAL FLU ENR
Dairy I (10) 447 0.04 2.91 0.45 0.45 8.28 4.25 0.67 1.12 0.22 24.83 1.34 0.22 0
II (10) 396 0.01 2.02 0.25 0 3.79 0.25 1.52 0 0.25 4.55 0.76 0.25 0.25
III (10) 419 0.02 4.3 0.24 0 4.3 3.58 2.15 0.48 0 7.88 1.19 0.72 0.24
Beef I (10) 436 0.03 9.17 1.15 0 6.88 4.13 2.52 0.92 0.69 13.3 2.52 0.46 0.46
II (9) 346 0.06 12.14 1.45 0.58 17.05 5.49 4.91 2.31 0.87 18.21 8.67 4.33 2.89
Veal T1 (5) 276 0.62 93.12 4.71 0.36 94.93 92.75 83.33 45.29 22.46 89.49 79.00 73.13 64.23
T2 (5)
230 0.32 79.57 2.61 1.74 95.22 65.22 27.83 5.22 5.65 78.26 14.01 6.22 4.12
> 25%
Catry et al., 2008 National Report
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Vulnerable populations Veterinary
Co-selection = accumulation – persistence…
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Dense communities
= hotspots for AB & ABR
FISH TO BE ADDED
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Acknowledgements
Slides available on: www.nsih.be
[email protected] (ABU, ESAC)
Dr. Stien Vandendriessche (LA-MRSA)
Drs. Katrien Latour (HALT)
Mevr. Beatrice Jans (MRSA, ESBL, CPE, HALT)
Participating hospitals