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: nsih@wiv-isp.be | http://www.nsih.be

One Health

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)

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)

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

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

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: journals.permissions@oup.com

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: journals.permissions@oup.com

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: journals.permissions@oup.com

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: journals.permissions@oup.com

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.

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

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

Point prevalence survey: PPS (photo)

Surveillance contineously (film)

&

Surveillances

&

FEEDBACK

MRSA

Campagnes

Indicateurs USI & ISO

Septicémies

C. difficile

Gram -

ABU

Rectangle = mandatory

Annual N casulties

2000 in 2008 (www.wiv-isp.be)

Nosocomial infections: 6250 in 2007 (KCE 92A)

+850 in

2012 (bivv.be)

MRSA evolution

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!

Carbapenemase producing

enterobacteriaceae

SHC, 2012

Global evolution of hand hygiene compliance

4th campaign

preliminary results!

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

Point prevalence survey: PPS (photo)

Surveillance contineously (film)

&

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

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

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

DATA MANAGEMENT

Upload Feedback

• ‘Tarification Units’

• ljst TUC codes

• ‘molecules’

• expressed as DDD

(Defined Daily Dose)

use (TUC) / Factor = use (DDD)

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)

REALTIME FEEDBACK

FEEDBACK Compare own use with national mean

AUTOMATIC FEEDBACK Local follow up

FEEDBACK

OBJECTIVES MODULE

Hospitals • realtime feedback

• Automatic recalculation (TUC DDD)

• Local monitoring information for ABMT

Authorities • trend monitoring

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)

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

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

Non Pediatric Wards

Stratified by ward: antibacterials

Stratified by ward: antimycotics

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

Community

Hospitals

Evolution - long term

Point prevalence survey: PPS (photo)

Surveillance contineously (film)

&

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

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

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

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

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

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%

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: info@wiv-isp.be | www.wiv-isp.be

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

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

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

Résultats: la consommation d’antimicrobiens

• 68.5% prescriptions thérapeutiques

• 31.5% prescriptions prophylactiques

48.7% 31.8% 10.8%

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

Courtesy: Jans B. & Latour K.

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

One Health

MRSA evolution

n. hôpitaux 29 34 44 48 41 43

Evolution of MRSA-incidence upon admission

Vandendriessche et al, 2012

QUIZ: Prevalence Livestock associated MRSA

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

18 13

4

10

3

1

1

4

MRSA ST398 (infection + screening)

ReferentieLaboratorium voor Stafylokokken - MRSA

Courtesy:

Vandendriessche S

Swine farms density

Ribbens, Prev Vet Med 2009

Veal calves density

E. Ducheyne and B. Pardon, 2012

Courtesy:

Vandendriessche S

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

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

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

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

Possible outcomes of exposure

to resistant bacteria

P.L. Geenen, M.G.J. Koene, H. Blaak,

A.H. Havelaar, A.W. van de Giessen

Bacteria & Co-selection of Resistance

Evolution E. coli multiresistance

P.L. Geenen, M.G.J. Koene, H. Blaak,

A.H. Havelaar, A.W. van de Giessen

Evolution E. coli multiresistance

P.L. Geenen, M.G.J. Koene, H. Blaak,

A.H. Havelaar, A.W. van de Giessen Vaporization: ceftiofur

Evolution E. coli multiresistance

P.L. Geenen, M.G.J. Koene, H. Blaak,

A.H. Havelaar, A.W. van de Giessen

www.BelVet-SAC.ugent.be

Among European countries 2010: Belgium is the 3rd highest

consumer of antimicrobials in veterinary medicine.

www.BelVet-SAC.ugent.be

Comparison Oral (Feed) vs

Injection

Checkley e.a., CVJ / VOL 51 / AUGUST 2010

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

Vulnerable populations Veterinary

Co-selection = accumulation – persistence…

Dense communities

= hotspots for AB & ABR

FISH TO BE ADDED

Acknowledgements

Slides available on: www.nsih.be

Anne.Ingenbleek@wiv-isp.be (ABU, ESAC)

Dr. Stien Vandendriessche (LA-MRSA)

Drs. Katrien Latour (HALT)

Mevr. Beatrice Jans (MRSA, ESBL, CPE, HALT)

Participating hospitals

nsih@wiv-isp.be