deliverable report wp2: d2.3: results of systematic reviews...nd4bb combacte-magnet deliverable...

Deliverable Report WP2 : D2.3

ND4BB COMBACTE-MAGNET Deliverable Report dated 16Jan2017

Project No. 115737

ND4BB COMBACTE-MAGNET

Combatting Bacterial Resistance in Europe

Deliverable Report

WP2: D2.3: Results of systematic reviews

Due date 13.01.2017

Delivery date 16.01.2017

Deliverable type1 Report

Dissemination level1 PU

Description of Work Version Date

V2.0 29June2016



Lead contributors

Evelina Tacconelli (7-EKUT) [email protected] Jesús Rodrigues Baño (9-SAS) [email protected]

Andreas Voss (8-RUNMC) [email protected]

Frangiscos Sifakis (1-AZ) [email protected]

Other contributors María Núñez-Núñez (9-SAS)

María Dolores Navarro (9-SAS)

Virginia Palomo (9-SAS)

Remco Schrijver (8-RUNMC)

Nithya Babu Rajendran (7-EKUT)



TABLE OF CONTENTS

1. Summary.......................................................................................................................................... 5

2. Surveillance Systems for Antimicrobial Resistance and Healthcare-Associated Infections in Europe (SUSPIRE): A Systematic Review ................................................................................................. 6

Introduction ............................................................................................................................................. 6

Methods .................................................................................................................................................. 7

Results ..................................................................................................................................................... 8

3. A systematic review of SURVeillance programs for Antimicrobial resistance In Livestock and meat thereof in the European Union (SURVAIL) ................................................................................... 67

Introduction ........................................................................................................................................... 67

Materials and Methods ......................................................................................................................... 67

Results ................................................................................................................................................... 68

4. EpideMiology and control measures of outBreaks due to Antibiotic-Resistant orGanisms in EurOpe (EMBARGO): a systematic review protocol .............................................................................. 78

Introduction ........................................................................................................................................... 78

Materials and Methods ......................................................................................................................... 79

Results ................................................................................................................................................... 81

5. Discussion .................................................................................................................................... 103



ABBREVIATIONS

AMR Antimicrobial resistance ARB Antimicrobial-resistant bacteria CI Cumulative incidence CR Carbapenem resistance CR-AB Carbapenem-resistant / carbapenemase-producing Acinetobacter baumannii CR-EC Carbapenem-resistant / carbapenemase-producing Escherichia coli CR-KP Carbapenem-resistant / carbapenemase-producing Klebsiella pneumoniae CR-PA Carbapenem-resistant / carbapenemase-producing Pseudomonas aeruginosa CZ-AB Ceftazidime-resistant Acinetobacter baumannii CZ-EC Ceftazidime-resistant Escherichia coli CZ-PA Ceftazidime-resistant Pseudomonas aeruginosa ECDC European Centre for Disease Control and Prevention EEA European Economic Area EFSA European Food Safety Authority EFTA European Free Trade Association EMA European Medicines Agency ESBL Extended-spectrum beta-lactamase ESBL-KP ESBL producing-Klebsiella pneumoniae ESBL-AB ESBL producing - Acinetobacter baumannii ESBL-EC ESBL producing - Escherichia coli ESBL-PA ESBL producing -Pseudomonas aeruginosa ESCMID European Society of Clinical Microbiology and Infectious Diseases ESICM European Society of Intensive Care Medicine EU European Union EUCAST European Committee on Antimicrobial Susceptibility Testing EUCIC European Committee on Infection Control GN Gram Negative GISA Glycopeptide Intermediate Staphylococcus aureus HAI Health-care associated infection HCF Healthcare facilities ID Incidence density IEA International Epidemiological Association ISID International Society for Infectious Diseases MDR Multi-drug resistant MRSA Methicilin Resistant Staphylococcus aureus MS Member States PRISMA Preferred Reporting Items for Systematic Reviews and Meta-analyses RT Real time VRE Vancomycin Resistant Enterococci VRSA Vancomycin Resistant Staphylococcus aureus WHO World Health Organization



1. Summary

Surveillance of healthcare-associated infections and antimicrobial resistance are essential to

providing the evidence for development and monitoring of appropriate antibiotic guidelines and

stewardship, public health interventions, infection control policies, and therapeutic or preventive

research and development. In order to define areas for improvement of surveillance, the EPI-Net

consortium performed two systematic reviews focused on the current status of surveillance systems

in humans (SUSPIRE) and in animals and food (SURVAIL) in European countries. Given that current

surveillance systems do not include data from outbreaks, a third review (EMBARGO) was conducted

and it focused on major epidemiological characteristics of bacterial outbreaks caused by

antimicrobial-resistant strains in European countries. The SUSPIRE review summarises the

characteristics of 56 national and international surveillance systems in Europe. Key results from this

study indicate substantial weaknesses and heterogeneity among national surveillance systems,

particularly for antimicrobial surveillance, with insufficient reporting of relevant epidemiological,

clinical, and health outcome data. The SURVAIL review reports data from 15 national and

international surveillance systems and shows the lack of coordination between human and

animal/food data in case of antibiotic resistance surveillance. Finally, the EMBARGO review reports

epidemiological data on 430 oubreaks and highlights high risk settings (e.g., neonatal intensive care

units, immunocompromised patients) and microorganisms associated with significant clinical burden

(e.g., carbapenem-resistant gram-negative).

The detailed objectives, methodologies, results and conclusions drawn from these reviews are

presented individually in this deliverable report.



2. Surveillance Systems for Antimicrobial Resistance and Healthcare-

Associated Infections in Europe (SUSPIRE): A Systematic Review

Authors

María Núñez-Núñez, María Dolores Navarro, Virginia Palomo, Nithya Babu Rajendran, Panagiota

Gkolia, María Dolores del Toro, Andreas Voss, Mike Sharland, Frangiscos Sifakis , Evelina Tacconelli,

Jesús Rodríguez-Baño

(Study protocol under review for publication)

Introduction

Surveillance of healthcare-associated infection (HAI) and antimicrobial resistance (AMR) are key parts

of all public health efforts to reduce the spread of antimicrobial-resistant pathogens and have been

traditionally used in healthcare systems to detect new patterns of resistance and outbreaks,

prioritise resources, define local guidelines, and provide therapeutic and infection control feedback

(Zingg et al., 2015). More recently, surveillance data are being increasingly used for benchmarking

and public reporting (Haustein et al., 2011). However, methodological heterogeneity and inadequate

control of confounders and data quality significantly lower the applicability of data from existing

surveillance systems for these purposes. In 2008, the European Centre for Disease Control and

Prevention (ECDC) reviewed the surveillance protocols/modules implemented by national or regional

networks for the purpose of HAI surveillance in European Union countries (ECDC, 2008) and

emphasised the presence of significant heterogeneity. Subsequently, in 2009, the European Council

recommended the establishment and/or strengthening of active surveillance systems at national or

regional level (EU council, 2009). As part of this effort, the ECDC implemented two major projects: in

2008 the HAI-net, a network of national/regional networks collecting surveillance data across

Europe, including specific modules on surgical site infections (SSIs), infections in intensive care units

(ICUs), Clostridium difficile and point prevalence surveys (PPS) in acute care and long term care

facilities, and in 2010 the European Antimicrobial Resistance Surveillance (EARS)-net. The

establishment of these networks has substantially reduced the differences in reporting among the

European countries and ECDC provides regular, standardised outcome measures of HAIs amd AMR

rates in Europe. However, very little information is available on the situation of surveillance systems

reporting national data at a local level.

The objectives of this review were to catalogue all active surveillance systems in European countries

or regions and to define methodology and indicators used for reporting HAIs and AMR rates.



Methods

A systematic scientific and grey literature search and review of surveillance systems for HAI and/or

AMR developed by official institutions in European countries/regions or endorsed by them was

performed. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA)

guideline (Shamseer et al., 2015) was followed.

Information sources and searching strategies

Three strategies were applied. First, a systematic search of peer-reviewed literature (PubMed,

EMBASE and Scopus) and references from the retrieved articles was done. Second, a comprehensive

search of grey literature, including Google search engine and targeted websites of ministries of

health, healthcare services, institutes of public health, ECDC, World Health Organization (WHO),

scientific societies in the field e.g. the European Society of Clinical Microbiology and Infectious

Diseases (ESCMID); the International Society for Infectious Diseases (ISID); the International

Epidemiological Association (IEA); the European Society of Intensive Care Medicine (ESICM) and the

European Respiratory Society (ERS) was performed. The search strategy used for grey literature

included the combination of the following terms in English and the local languages in European

countries: "Antimicrobial resistance" AND/OR "Hospital-associated" OR "Hospital-acquired" OR

"Nosocomial" AND "Surveillance" AND "epidemiology" OR "prevalence" OR "incidence". The time

period was until October 31, 2016. Third, national representatives of the European Committee on

Infection Control (EUCIC) of ESCMID were consulted.

Eligibility criteria

We targeted 32 European countries, including the 28 European Union member states and 4 countries

from the European Free Trade Association (EFTA) Iceland, Liechtenstein, Norway and Switzerland. A

HAI or AMR surveillance system was defined as a structured and systematic procedure to measure

the prevalence or incidence of HAI and/or AMR, performed continuously or periodically, with a

defined methodology and specified indicators. The surveillance systems were included if fulfilling the

following criteria: data were reported for at least one year from 2006; the methodology used was

publicly available for review; human data from European countries were included; and the system

was promoted or endorsed by a regional, national or transnational official health organisation or

scientific society. Surveillance systems referring their methodology to transnational systems (like

those promoted by ECDC) were included if protocols were publicly available.

The following surveillance systems were excluded for this review: systems exclusively

declaring/notifying individual cases of a specific disease or pathogen (e.g., compulsory reporting of

individual cases without denominators); systems providing only animal, environmental or food data



(included in the second review in this deliverable report); surveillance data promoted by private

companies; studies not including continuous or periodic surveillance; and outbreaks reports

(included in the third review in this deliverable report). Potentially eligible surveillance systems for

which the methodology was not publicly available were excluded. Regional systems using the same

methodology as national systems were also excluded from the analyses to avoid duplicities.

Three independent reviewers (MNN, MDN and NBR) performed a two-step selection process. Titles

and abstracts of the retrieved documents were initially assessed and non-relevant documents

excluded. For data from grey literature, executive summaries, table of contents and documents

(whichever was available) were screened. The full text of potentially eligible documents were then

obtained and assessed for relevance or duplication against predefined selection criteria. When

available, national experts were contacted to clarify protocol details.

Data extraction

Data extraction was performed using a tailored, pilot-tested electronic data extraction form. Periodic

quality controls were performed and disagreements resolved by review and consensus with other co-

authors (JRB, ET and PG).

The data collected included: objective of the surveillance system, population covered, modality of

reporting, quality audit, and dates of the information available. For systems reporting AMR: type of

sampling, type of infections, pathogens, antibiotics tested, patients’s clinical data and outcome. For

systems reporting HAIs in intensive care units (ICUs): target device related-infections (central line-

associated bloodstream infections [CLABSI], ventilator-associated pneumonia [VAP] and catheter-

associated urinary tract infection [CAUTI]) and relevant patients’s clinical data and outcome. For

systems reporting surgical site infections: data on type of interventions (coronary artery bypass

grafting [CABG], cardiac valve replacement [CVAL], cholecystectomy [CHOL], colon surgery [COLO],

caesarean section [CSEC], hip prosthesis [HPRO], knee prosthesis [KPRO] and laminectomy [LAM]),

antibiotic prophylaxis, and procedure indicators were extracted. Variables for which information was

not specified or was not available were noted down as “not reported/unknown”.

We did not seek ethical approval for this study because data collected is not linked to individuals.

Results

Using the three search strategies, 112 surveillance activities from 27 countries/regions were

identified. After reviewing the available data, 52 systems, plus the transnational systems from ECDC

and WHO, were finally included (Figure 1 and Table 1). The main reasons for exclusion were: no

public access or availability of data on methodology; regional systems using national-wide prescribed

methodologies; mandatory reporting of cases for specific infections/pathogens without



denominators; and surveillance activities not primarily intended for HAI/AMR. According to the study

protocol no surveillance systems could be reported for the following 12 countries (38%): Bulgaria,

Cyprus, Czech Republic, Estonia, Iceland, Latvia, Liechtenstein, Luxembourg, Malta, Poland, Romania

and Slovenia.

The general features of the surveillance systems for which data extraction was performed are shown

in Table 2. The coverage of the systems was international for 4, national for 35 and regional for 17.

The majority of the systems included all age groups (96%) in inpatient setting (40%) or inpatient and

outpatient settings (40%). The majority of the HAI surveillance systems targeted ICUs (67%) and

surgical departments (67%) and a very few nursing homes (3%). External quality audits were applied

or recommended in 16 systems (25%) and local quality assessments were used in 8 (14%).

Surveillance of HAI in intensive care units (ICUs)

A description of key features and indicators used in surveillance of HAI in ICU patients is provided in

Table 3. Overall, 32 systems plus one international system were included. The most frequent

surveillance metric for device related-infections was density of incidence (60% for CLABSI, 53% for

VAP and CAUTI) Individual risk factors were included in 17 systems (53%)and 11 (34%) of them

reported a severity score such as APACHE. As outcome measures, 13 systems (41%) reported ICU-

mortality and 2 (6%) included the length of ICU stay.

Surveillance of surgical site infections (SSI)

The features of the 32 systems for SSI plus the ECDC programme are shown in Table 4. The data were

stratified according to the NNIS risk index in 16 national or regional systems (50%). Urgent

procedures were included in 15 (47%) and data on antibiotic prophylaxis were collected in 14 (44%).

Among the systems reporting type of procedures, the most common were colon surgery, hip

prosthesis and knee prosthesis. Data on procedure indicators such as checklist were included in 47%

of the surveillance systems. No system included data on environmental cleaning in operating

theatres.

Surveillance systems for antimicrobial resistance

Forty surveillance systems from 19 countries and 4 international systems were included in our review

(see Table 5). The source of data was laboratory-based in the majority of the systems (36, 90%). Only

7 (16%) report patients’ data. A policy to avoid duplicates for laboratory-based data was specified in

23 systems (58%). The case definition included pathogens isolated from clinical samples in 21

systems (53%) both infections and colonisations. Nine (23%) systems included only patients with

infection due to resistant pathogens. Twenty-two systems (55%) applied the resistance breakpoints

recommended by EUCAST (in 11 28%, CLSI were also included).



Overall, the most frequent indicator used in the reporting was the proportion of resistant isolates

among 100 isolates (29 systems 63%). Sixteen (40%) systems reported incidence rates (either

cumulative or density). Potential predisposing factors for resistance were collected in 19 (43%)

systems, with antibiotic use being the most frequently reported (88%). No outcome data were

collected.

Most frequently targeted pathogens were Streptococcus pneumoniae (75%), Staphylococcus aureus

(98%), Enterococcus faecalis (80%), Escherichia coli (93%), Klebsiella species (90%), Pseudomonas

aeruginosa (88%), and Acinetobacter baumannii (85%). Clostridium difficile was included in 50% of

the surveillance systems. Most frequently reported resistance bacteria were MRSA (83%), VRE (78%),

cephalosporin-resistant E. coli or K. pneumoniae (73%), cephalosporin-resistant P. aeruginosa (70%),

carbapenem-resistant P. aeruginosa (68%), carbapenem-resistant E. coli or K. pneumoniae (65%) and

carbapenem-resistant A. baumannii (63%). The specimens and antimicrobials tested for resistance by

microorganisms are shown in Tables 6 and 7 and figure 2.



Figure 1. Flow diagram of the systematic review

Iden

tific

atio

n Sources identified through database

searches

Google search

engine

Targeted websites

Consultation with

experts

Scre

enin

g

Potentially relevant records

Records excluded with reasons:

- Privately funded - No public access from primary sources - Reference centres/ quality registers - Statutory notifications/ passive surveillance - Only animal - Outbreaks

Objective not clear/ public data limited

Inclu

ded

Surveillance systems included N=56


ND4BB CO

MBACTE-M

AGNET Deliverable Report dated 16Jan2017

Table 1. Surveillance activities in EU/EAA identified and classified according to the study criteria.

Country System

s included System

s excluded

Austria Austrian Nosocom

ial Infection Surveillance System

Austrian surveillance of nosocomial infections in Neonatal Care

1 National Reference Centre for Nosocom

ial infection and Antimicrobial Resistance

Epidemiologisches m

eldesystem/national reference centres 3,4

Belgium

Scientific Institute of Public Health (IPH) - Institut Scientifique de Santé Publique

Croatia Intersectoral Coordination M

echanism for the Control of AM

R Croatian Institute of Public Health

2 Cyprus

National antim

icrobial resistance surveillance system2

Czech Republic

SZU-Statni zdravotni Listav

2

Denmark

Hospital-acquired infections database Danish m

icrobiology database 5

Danish integrated antimicrobial resistance m

onitoring and research programm

e North Denm

ark region microbiological bacteraem

ia research database2

Com

pulsory notification of MRSA

4 Estonia

National institute for health developm

ent 2

Finland Finnish hospital infection program

National infectious diseases register

Finnish study group for antimicrobial resistance

France

l’Observatoire National de l’Epidém

iologie de la Résistance Bactérienne aux Antibiotiques Enquête nationale de prévalence des infections associées aux soins et des traitem

ents antibiotiques en EHPAD1

Réseau d’Alerte, d’Investigation et de Surveillance des Infections Nosocom

iales Centre de coordination de la lutte contre les infections nosocom

iales (C.CLIN) 1

(HAI) Institut de vieille sanitaire 1

Germany

Krankenhaus infektions surveillance system

National reference centre for Streptococci 3

Antibiotic resistance surveillance Com

pulsory notification of MRSA, carbapenem

-resistant or carbapenemase-

producing Acinetobacter spp. Enterobacteriaceae 4 Surveillance of antibiotic use and resistance in ICU

Statutory notification of m

ultidrug-resistant bacteria4

Antibiotika resistenz monitoring in N

iedersachsen

German netw

ork for antimicrobial resistance surveillance

Greece Greek system

for the surveillance of antimicrobial resistance

Procrustes, compulsory notification of bacteraem

ia due to AMR 4

Greek national reference centre for Neisseria gonorrhoeae 3

National Salmonella and Shigella Reference Centre 3

Hungary National Nosocom

ial Surveillance System

Iceland

Landlknisem

btti, Directorate of Health / EPI_ICE 2

Ireland Health Protection Surveillance Centre

Italy

Sorveglianza regionale delle infezioni in terapia intensiva National reference centre for Neisseria

Sorveglianza prospettica delle infezioni nosocomiali nella Unità di Terapia Intensiva

Laboratory-based surveillance of invasive infections 3 Sistem

a nazionale di sorveglianza delle infezioni del sito chirurgico

Margherita PRO

SAFE

Antibiotico resistenza - Istituto Superiore di Sanitá

Sorveglianza dell’antibioticoresistenza e uso di antibiotici sistemici in Em

ilia-Romagna

Sorveglianza antibiotico resistenza Toscana

M

icronet


ND4BB CO

MBACTE-M


Latvia

Infectology Centre Department of Epidem

iological Safety and Public Health (DESPH) 2 Centre for Disease Prevention and Control (CDPC) 2

Liechtenstein

Lithuania

Healthcare-associated infections epidemiological surveillance*

National public health surveillance laboratory and Institute of hygiene Vilnus 2 Luxem

burg

Centre de Recherche Public de la Santé 2 M

alta

Mater Dei Hospital 2

The N

etherlands

Preventie van ziekenhuisinfecties door surveillance* Kinderdagverblijven infectieziekten surveillance systeem

5 Surveillance netw

ork for infectious diseases in nursing homes*

Compulsory notification of M

RSA4

Infectious disease surveillance and information system

for antibiotic resistance Surveillance of antim

icrobial resistance in the Netherlands 5

Norw

ay Nasjonalt Folkehelseinstitutt (FHI) / The Norw

egian Institute of Public Health (NIPH): Healthcare Asssociated Infections m

odule for SSI (NOIS-SSI); Antim

icrobial drug Resistance m

odule (NORM

)

Norwegian Arthroplasty Register 3

Norwegian Hip Fracture Register 3

Norwegian Surveillance System

for Comm

unicable Diseases (MSIS) 4

Portugal Antibiotic Resistance Surveillance Program

in Portugal

Poland

Active Supervision of nosocomial infections Program

2 National M

edicines Institute 2 National reference centre for diagnosis of bacterial infections of the central nervous system

3 Rom

ania

Sentinel Surveillance System of Nosocom

ial Infections and AMR

2

Slovakia Slovak national antim

icrobial resistance surveillance system

EPIS, Epidemiology inform

ation system 2

National reference centre for Salmonella

3 Slovenia

National Institute of Public Health, University of Ljubljana 2

Spain

Sistema de Vigilancia, prevención y control de IRAS en Principado de Asturias

Red Nacional de Vigilancia epidemiológica (RENAVE) 1

Sistema de Vigilancia Nosocom

ial de Galicia Program

a de Vigilancia y control de microorganism

os multirresistentes 4

Vigilancia de les Infeccions nosocomials als Hospitals de Cataluya (VIN

CAT) Spanish national nosocom

ial infection surveillance network 2

Programa Integral de Prevención, control de las Infecciones relacionadas con la Asistencia

Sanitaria y Uso apropiado de los Antimicrobianos en Andalucía (PIRASO

A)

Plan INOZ - Infekzio Nosocom

ialak Zaintzeko eta Kontrolatzeko del País Vasco

Vigilancia de las Infecciones Relacionadas con la Asistencia Sanitaria de Madrid (VIRAS)

Sistem

a de Vigilancia epidemiológica de Canarias

Estudio nacional de vigilancia de Infección nososcom

ial en servicios de medicina intensiva

(ENVIN-UCI)

Estudio de Prevalencia de las Infecciones Nosocomiales en España (EPIN

E)

Sweden

Swedish surveillance of antim

icrobial resistance ICU STRAM

A Program 2

Annual resistance monitoring and quality control program

me

Bi-annual point-prevelance surveillance of HAI*

Mandatory/voluntary notification of infections 4

National reference laboratory for pathogenic Neisseria

3

Switzerland

SWISSNO

SO

Mandatory notification of carbapenem

ase-producing Enterobacteriaceae4

Comm

unity-associated methicillin-resistant Staphylococcus aureus (CA-M

RSA) surveillance system

Hygiène hospitalière prévention et contrôle de l'infection* Sw

iss centre for antibiotic resistance


ND4BB CO

MBACTE-M


United

Kingdom

Healthcare Infection Centre

The Pan Celtic Network 1

Public Health England (Healthcare Protection Agency: inactive) Health Protection Scotland W

elsh Healthcare Associated Infections Programm

e

ECDC Healthcare-Associated Infections Surveillance Netw

ork

European Antim

icrobial Resistance Surveillance Network

WHO

Central Asian and Eastern European Surveillance of Antim

icrobial Resistance Global Antim

icrobial Resistance Surveillance System

* Systems exclusively declaring/notifying individual cases of a specific disease or pathogen (e.g., com

pulsory reporting of individual cases without denom

inators); systems providing only anim

al, environmental or

food data; surveillance data promoted by private com

panies; studies not including continuous or periodic surveillance; and outbreaks reports are not display in this table.

NR/ UNK= Not reported / Unknown; HAI: Healthcare Associated Infections; AM

R: Antimicrobial Resistance

1. Data included in other surveillance systems

2. Not public access or data available from prim

ary sources

3. Reference centers / Quality registers

4. Statutory notification/ passive surveillance

5. Currently not intended for HAI / AMR surveillance / does not m

eet all eligible criteria


ND4BB CO

MBACTE-M


Table 2. Main characteristics of 56 surveillance system

s reporting healthcare-associated infections and antimicrobial resistance

Country Coverage

Acronym N

ame

Focus Data source

Age Frequence of reporting

Modality of reporting

Quality

Audits Year of info used

Austria

National ANISS

Austrian nosocomial infection surveillance system

HAI

Inpatients All ages

Yearly Pooled data

External, voluntary

2012, 2014-2016

National NRZ

National reference centre for nosocomial infection

and antimicrobial resistance

AMR

Inpatients and outpatients

All ages Yearly

Pooled data External, voluntary

2014-2016

Belgium

National W

IV-ISSP Scientific institute of public health (IPH) - institut scientifique de santé publique

HAI+AMR

Laboratory All ages

Yearly Individual HCF and pooled data

Not specified 2011

Croatia National

ISKRA Intersectoral coordination m

echanism for the control

of AMR

AMR

Laboratory All ages

Yearly Pooled data

Not specified 2014

Denmark

National HAIBA

Hospital-acquired infections database HAI

Inpatients All ages

Weekly

Individual HCF data Not specified

2015, 2016

National DANM

AP Danish integrated antim

icrobial resistance monitoring

and research programm

e AM

R Inpatients and outpatients

All ages Yearly


2014-2016

Finland

National SIRO

Finnish hospital infection program

HAI

Inpatients All ages

Yearly Pooled data

External, voluntary

2006, 2011, 2014, 2016

National FIRE


AMR


All ages Yearly


2014-2016

France

National O

NERBA L’O

bservatoire national de l’epidémiologie de la

résistance bactérienne aux antibiotiques AM


All ages Yearly

Not specified Local

2015

National RAISIN

Réseau d’alerte, d’investigation et de surveillance des infections nosocom

iales HAI

Inpatients All ages

Yearly Com

parative data with

other HCF Not specified

2009

Germany

National KISS

Krankenhaus infektions surveillance system

HAI+AMR


All ages Yearly

Pooled data Not specified

2010, 2012-2016

National ARS

Antibiotic resistance surveillance AM


All ages Yearly


2015, 2016

National SARI

Surveillance of antibiotic use and resistance in ICU

AMR

Inpatients All ages

Yearly Pooled data

Not specified 2009,2016

Regional ARM

IN

Antibiotika resistenz monitoring in niedersachsen

AMR


All ages Yearly


2015, 2016

National GENARS

German netw

ork for antimicrobial resistance

surveillance AM

R Laboratory

All ages Not specified


2002, 2007

Greece National

GSSAR Greek system

for the surveillance of antimicrobial

resistance AM

R Inpatients

All ages Yearly

Comparative data w

ith other HCF

External, voluntary

2015, 2016


ND4BB CO

MBACTE-M


Hungary National

NNSR National nosocom

ial surveillance system

HAI+AMR

Inpatients All ages

Mixed


2010 Ireland

National HPSC

Health propection surveillance centre HAI+AM

R Not specified

All ages M

ixed Pooled data

Not specified 2014, 2016

Italy

Regional SITIER

Sorveglianza regionale delle infezioni in terapia intensiva HAI+AM

R Inpatients

All ages RT

Comparative data

with other HCF

Not specified 2013

National SNICh

Sistema nazionale di sorveglianza delle infezioni del sito

chirurgico HAI+AM

R Inpatients

All ages Yearly

Comparative data

with other HCF

Local, com

pulsory 2014

National SPIN-UTI

Sorveglianza prospettica delle infezioni nosocomiali nella

Unità di Terapia Intensiva HAI+AM

R Inpatients

All ages Yearly


2009, 2013, 2015

National M

argherita M

argherita PROSAFE

HAI+AMR

Inpatients All ages

Yearly Com

parative data w

ith other HCF Local

2014

National AR-ISS

Antibiotico resistenza - Istituto superiore di sanitá AM

R Laboratory

All ages M

ixed Com

parative data w

ith other HCF External, voluntary

2013

Regional LAB

Sorveglianza dell’antibioticoresistenza e uso di antibiotici sistem

ici in Emilia-Rom

agna AM


All ages Yearly

Comparative data

with other HCF

Local 2003 - 2014

Regional SART

Sorveglianza antibiotico resistenza Toscana AM




2015

National M

icronet M

icronet AM

R Laboratory



2007 Lithuania

National HAI E.S.LI

Healthcare-associated infections epidemiological

surveillance HAI

Inpatients All ages

Yearly Pooled data


Netherlands

National PREZIES

Preventie van ziekenhuisinfecties door surveillance HAI

Inpatients All ages

Yearly Pooled data


National SNIV

Surveillance network for infectious diseases in nursing

homes

HAI Inpatients

Only adults

Yearly Pooled data

Not specified 2014-2016

National ISIS-AR

Infectious disease surveillance and information system

for antibiotic resistance

AMR


All ages Q

uarterly Pooled data

Not specified 2012, 2015, 2016

Norw

ay National

FHI Nasjonalt Folkehelseinstitutt: Healthcare Asssociated Infections m

odule for SSI (NOIS-SSI); Antim

icrobial drug Resistance m

odule (NORM

)

HAI+AMR

Not specified All ages

Yearly Com

parative data w

ith other HCF Not specified

2014

Portugal National

ARSIP Antibiotic resistance surveillance program

in Portugal HAI+AM



Comparative data

with other HCF

Not specified 2014

Slovakia National

SNARS Slovak national antim

icrobial resistance surveillance system

AMR


All ages Yearly

Pooled data External, com

pulsory 2016


ND4BB CO

MBACTE-M


Spain

Regional SVPCIPA

Sistema de vigilancia, prevención y control de IRAS en

principado de Asturias HAI+AM

R Inpatients

All ages Yearly

Individual HCF data

Not specified 2011

Regional SVIN

Sistema de vigilancia nosocom

ial de Galicia HAI+AM


All ages M

onthly Com

parative data w

ith other HCF Local

2000

Regional VIN

CAT Vigilancia de les Infeccions nosocom

ials als hospitals de Cataluya

HAI+AMR

Inpatients All ages

Yearly Com

parative data w


2015

Regional PIRASOA

Programa Integral de Prevención, control de las Infecciones

relacionadas con la Asistencia Sanitaria y Uso apropiado de los Antim

icrobianos (PIRASOA)

HAI+AMR


All ages Q

uarterly Com

parative data w


2014

National ENVIN

-UCI Estudio nacional de vigilancia de Infección nososcom

ial en servicios de m

edicina intensiva HAI+AM


All ages Yearly

Individual HCF data

Not specified 2014

National EPINE

Estudio de prevalencia de las infecciones nosocomiales en

España HAI

Inpatients All ages

Yearly Com

parative data w

ith other HCF External

2015

Regional IN

OZ

Infekzio nosocomialak zaintzeko eta kontrolatzeko del País

Vasco HAI

Inpatients All ages

Not specified Individual HCF data

Not specified 2016

Regional VIRAS

Vigilancia de las Infecciones relacionadas con la asistencia sanitaria de M

adrid HAI

Inpatients All ages

Yearly Individual HCF data

Not specified 2012

Regional SVE Canarias

Sistema de Vigilancia epidem

iológica de Canarias HAI


All ages Yearly


2014

Sweden

National RESNET

Annual resistance monitoring and quality control program

me

AMR

Not specified Not specified

Yearly Pooled data

Not specified 2014, 2016

National SVEBAR

Swedish surveillance of antim

icrobial resistance AM


All ages Yearly

Pooled data External, com

pulsory 2016

Switzerland

National SW

ISSNOSO

SW

ISSNOSO

HAI

Inpatients All ages

Yearly Pooled data

Local, com

pulsory 2015, 2016

Regional HPCI

Hygiène hospitalière prévention et contrôle de l'infection HAI+AM




2016

National ANRESIS

Swiss centre for antibiotic resistance

AMR


All ages Yearly


2015, 2016

Regional CA-M

RSA CA-M

RSA surveillance system

AMR




2006,2012, 2016


ND4BB CO

MBACTE-M


United

Kingdom

Regional W

HAIP W

elsh healthcare associated infections programm

e HAI+AM


All ages M

onthly Com

parative data with

other HCF Not specified

2016

Regional HPS

Health protection Scotland HAI+AM

R Inpatients

All ages Q

uarterly Com

parative data with

other HCF External

2015

Regional PHE

Public health England HAI+AM

R Laboratory

All ages M

ixed Individual HCF data

Not specified 2014

Regional HISC/HPA

Healthcare infection centre/healthcare protection agency

HAI+AMR

Laboratory All ages

Not specified Pooled data

Local 2008

ECDC Transnational

HAINET

Healthcare-Associated Infections Surveillance Netw

ork HAI+AM

R Laboratory

All ages M

ixed Pooled data (country)

External 2015 ICU; 2012 SSI

Transnational EARSNET

European Antimicrobial Resistance Surveillance

Network

AMR

Not specified All ages

Yearly Pooled data (country)

External 2015

WHO

Transnational

CAESAR Central Asian and Eastern European Surveillance of Antim

icrobial Resistance AM



Comparative data w

ith other HCF

External, voluntary

2015

Transnational GLASS

Global Antimicrobial Resistance Surveillance

System

AMR

Laboratory All ages

Yearly Com

parative data with

other HCF Local, com

pulsory 2015

*HCF= Healthcare facilities.


ND4BB CO

MBACTE-M



s for healthcare-associated infections in intensive care units

Country System

Risk factors others than invasive procedures

Clinical outcomes

CLABSI indicators VAP indicators

CAUTI indicators

Austria ANISS

Antibiotic use, comorbidities, severity score, previous

hospitalisations M

ortality ID, UR

ID, UR ID, UR

Belgium

WIV-ISSP

Comorbidities, severity score

Not specified ID, CI, UR

ID, CI, UR ID, CI

Denmark

HAIBA Not specified

Not specified ID

Not specified ID

Finland SIRO

Antibiotic use, com

orbidities M

ortality ID


France RAISIN



Not specified Germ

any KISS

Antibiotic use M

ortality ID, UR

ID, UR ID, UR

Hungary NNSR



Not specified Ireland

HPSC Antibiotic use

Mortality

ID, UR ID, UR

ID, UR Italy

SITIER Antibiotic use, com

orbidities, severity score, previous hospitalisations

Mortality, length of

stay ID, UR

ID, UR ID

SPIN-UTI Antibiotic use, severity score, previous hospitalisations

Mortality

ID, UR ID, UR

ID, UR M

argherita Antibiotic use, severity score, previous hospitalisations

Mortality

ID, UR ID, UR

ID, UR SNICh



Not specified Lithuania

HAI E.S.LI Antibiotic use, severity score, previous hospitalisations.

Mortality

ID, CA ID, CA

ID, CA N

etherlands PREZIES

Antibiotic use, comorbidities

Mortality

CI Not specified

Not specified SNIV

Antibiotic use M

ortality Not specified

ID ID

Norw

ay FHI



Not specified Portugal

ARSIP Not specified



Spain

SVPCIPA Not specified

Not specified ID, UR

ID, UR ID, UR

SVIN Severity score

Not specified ID, UR

ID, UR Not specified

VINCAT

Comorbidities, severity score, length of stay

Not specified ID, CI, UR

ID, CI, UR ID, CI, UR

PIRASOA Antibiotic use, com

orbidities, severity score, length of stay, antibiotic use

Mortality


ID, CI, UR

ENVIN-UCI

Antibiotic use, comorbidities, severity score, length of

stay, antibiotic use M

ortality ID, CI, UR


INO

Z Com

orbidities, Severity score Not specified

ID, UR ID, UR

ID, UR SVE Canarias



Not specified VIRAS



Not specified EPINE



Not specified

Switzerland

HPCI Not specified

Not specified ID, CI


SWISSNO

SO



Not specified

United

Kingdom

WHAIP


ID, UR ID, UR

ID, UR

HPS Com

orbidities, severity score M

ortality, length of stay

ID, UR ID, UR

ID, UR PHE



Not specified HISC/HPA



Not specified ECDC

HAINET

Antibiotic use, comorbidities, severity score, previous

hospitalisations M

ortality, length of stay

ID, UR ID, UR

ID, UR

CLABSI: Central line-associated bloodstream

infection VAP: Ventilator-associated pneum

onia CAUTI: Catheter-associated urinary tract infections ID: Incidence density CI: Cum

ulative incidence UR: Utilisation rate


ND4BB CO

MBACTE-M



s for surgical site infections

Country System

N

NIS Risk Index

Include urgent procedures

Data on antibiotic prophylaxis

Peri- operative checklist

CABG CVAL

CHOL

COLO

CSEC

HPRO

KPRO

LAM

Austria ANISS

Yes Yes

Yes PO

ST-op

Belgium

WIV-ISSP

Yes Yes

Yes PO

ST-op

Denmark

HAIBA Not specified


Not specified

Finland SIRO

Yes

Yes Yes

POST-op

France RAISIN

Yes Not specified

Yes Not specified

Germany

KISS Yes

Yes Not specified

Not specified

Hungary NNSR



Ireland HPSC



Italy

SNICh Yes

Yes Yes

Not specified

SITIER Not specified


Not specified

SPIN-UTI Not specified


Not specified

Margherita



Lithuania HAI E.S.LI

Yes Yes

Yes Not specified

Netherlands

PREZIES Yes

Yes Yes

POST-op

SNIV Not specified


Not specified

Norw

ay FHI

Yes Yes

Yes PO

ST-op

Portugal ARSIP



Spain



POST-op

VINCAT

Yes Yes

Yes PO

ST-op

PIRASOA Yes

Yes Not specified

PRE+POST-op

INO

Z Not specified


PRE-op

VIRAS Not specified


PRE-op

SVIN Not specified


Not specified

SVE Canarias Not specified


Not specified

EPINE Not specified


Not specified

ENVIN-UCI



Switzerland

SWISSNO

SO

Yes Yes

Yes PO

ST-op

HPCI Not specified


Not specified


ND4BB CO

MBACTE-M


United Kingdom

WHAIP

Yes Yes

Not specified PRE+PO

ST-op

HPS Yes

Yes Yes

PRE+POST-op

PHE Yes

Yes Yes

POST-op

HISC/HPA Yes

Yes Yes

PRE+POST-op

ECDC HAIN

ET Yes

Yes Yes

POST-op

PRE-op: Preoperative checklist, POST-op: Post-operative checklist, PRE+PO

ST-op: Pre- and post- operative checklist. CABG: Coronary artery bypass grafting. CVAL: cardiac valve replacement. CHO

L: cholecystectomy.

COLO

: colon surgery. CSEC: caesarean section. HPRO: hip prosthesis. KPRO

: knee prosthesis. LAM: lam

inectomy.


ND4BB CO

MBACTE-M


Table 5. Characteristics of 44 surveillance systems reporting antim

icrobial resistance

Country Acronym

Source of data

Duplicates policy

Type of sam

pling

Resistance definition criteria

Indicator Patients’ risk factors

Streptococcus pneumoniae

Staphylococcus aureus

Enterococcus faecalis

Enterococcus faecium

Escherichia coli

Klebsiella pneumoniae

Pseudomonas aeruginosa

Acinetobacter baumannii

Clostridium difficile

Austria NRZ

Laboratory Yes

Infection EUCAST or CLSI

Prev Not specified

Belgium

WIV-ISSP

Laboratory Not specified

Infection + colonisation

Not specified CI

Antibiotic use, comorbidities

Croatia ISKRA

Laboratory Yes


EUCAST Not specified

Not specified

Denmark

DANMAP

Laboratory Yes


EUCAST or CLSI Prev, CI 1, %

Infection Not specified

Finland FIRE

Laboratory Yes

Infection EUCAST

Prev Not specified

France O

NERBA Laboratory

Yes Infection

Local Not specified

Not specified

Germany

KISS Laboratory+cases

Yes Infection + colonisation

Local Prev, CI, ID, %

Infection Invasive procedures, Antibiotic use

ARS Laboratory

Yes Not specified

EUCAST or CLSI or Local

Prev Not specified

SARI Laboratory

Yes Not specified


Prev, ID Antibiotic use

ARMIN

Laboratory

Yes Not specified


Prev Not specified

GENARS Laboratory

Not specified

Not specified Local

Prev Not specified

Greece GSSAR

Laboratory Yes

Not specified CLSI

Prev Not specified

Hungary NNSR


Not specified EUCAST or CLSI



ND4BB CO

MBACTE-M


Ireland HPSC

Laboratory+cases Yes

Infection EUCAST

Prev, ID, %

Infection Previous hospitalisations, ICU stay

Italy

SITIER Laboratory

Not specified


Prev, CI, %

Infection Invasive procedures

SNICh Laboratory

Not specified


CI Antibiotic use

SPIN-UTI Laboratory

Not specified


Not specified Prev, ID

Invasive procedures, antibiotic use, com

orbidities, previous hospitalisation

Margherita

Laboratory Yes


Prev, %

Infection Invasive procedures, antibiotic use, com


AR-ISS Laboratory

Yes Not specified

EUCAST Prev, Prev

Not specified

LAB Laboratory


EUCAST Prev, Prev, ID

Not specified

SART Laboratory


EUCAST Prev, Prev

Antibiotic use, lenght of stay, com

orbidities

Micronet



Not specified Prev

Not specified

Netherlands

ISIS-AR Laboratory


EUCAST Prev

Not specified

Norw

ay FHI

Laboratory+cases Yes

Not specified EUCAST

Prev, Prev Antibiotic use

Portugal ARSIP




Slovakia SNARS

Laboratory Yes


EUCAST or CLSI Prev

Not specified

Spain

SVPCIPA Laboratory

Not specified


Not specified ID

Not specified

SVIN Laboratory

Not specified


Not specified Antibiotic use

VINCAT

Laboratory Yes



Antibiotic use

PIRASOA Laboratory


EUCAST or CLSI ID

Invasive procedures, antibiotic use

ENVIN-UCI



EUCAST or CLSI ID

Antibiotic use


ND4BB CO

MBACTE-M


Sweden

RESNET Laboratory

Not specified

Not specified EUCAST

Prev Not specified

SVEBAR Laboratory

Not specified


EUCAST Prev

Not specified

Switzerland

HPCI Laboratory+cases

Not specified


EUCAST CI, ID

Not specified

ANRESIS Laboratory


EUCAST or CLSI Prev

Not specified

CA-MRSA

Cases Not specified


EUCAST %

Infection Invasive procedures, antibiotic use, com

orbidities, previous hospitalisation, other *

United Kingdom

WHAIP



Not specified CI

Not specified

HPS Cases


Not specified CI, Prev

Antibiotic use

PHE Cases


Not specified Prev, CI, ID

Invasive procedures, antibiotic use

HISC/HPA Laboratory

Not specified



ECDC

EARSNET Laboratory

Yes Infection

EUCAST or CLSI Prev

Invasive procedures, antibiotic use, com

orbidities, previous hospitalisation, other **

HAINET

Laboratory Yes

Infection EUCAST

Prev, CI, ID Invasive procedures, antibiotic use, com


WHO

GLASS Laboratory


EUCAST or CLSI Prev

Not specified

CAESAR Laboratory


EUCAST or CLSI Prev, CI

Not specified

CI: cumulative incidence of resistant isolate/cases. ID: incidence density of resistant isolates/cases. Prev: prevalence

1. Only reported for m

ethicillin-resistant S. aureus.

* Other predisposing factors registered: contacts, travels, substance abuse, and sexual preferences

**Other predisposing factors registered: exposure to colonised patients


ND4BB CO

MBACTE-M


Table 6. Key antibiotics tested and type of sampling reported for gram

-positive pathogens in 40 surveillance systems (ECDC and W

HO not included)


Staphylococcus aureus Enterococcus faecalis/ Enterococcus faecium

Country Acronym

Type of sam

ple PEN

LVX or M

FX CTX or CRO

AZM

, CLR or ERY

Type of sample

OXA

FQ

LNZ

VAN GEN

or TO

B

Type of sample

AMP

VAN

GEH

Austria NRZ

Blood, CSF, respiratory

√ √

√ √

All √

√ √

√ √

Blood √

√ √

Belgium

WIV-ISSP

Not specified

Blood, CSF

√

√

Blood, CSF

√ √

Croatia ISKRA

Blood, CSF, respiratory

√ √

√

Blood, CSF √

√ √

√ √

Blood, CSF √

√ √

Denmark

DANMAP

Blood, CSF √

√ All

√

√

Blood

√ √

Finland FIRE

All √

√ √

√ All

√ √

All

√ √

France

ONERBA

Not specified

Not specified

Not specified

Germany

KISS Not specified

Not specified √

Not specified

√

ARS All*

√ √

√ √

All* √

√ √

√ √

All* √

√ √

SARI Not specified

√ √

√ √

Not specified √

√ √

√ ?

UNK √

√

ARMIN

All

√ √

√ √

All √

√ √

√ √

All √

√ √

GENARS All*

√ √

√ √

All* √

√ √

√ √

All* √

√ √

Greece GSSAR

All* √

√ √

√ All*

√ √

√ √

√ All*

√ √

√ Hungary

NNSR Blood, CSF

All √

√

All

√

Ireland HPSC

Blood, CSF √

Blood, CSF

√

Blood, CSF

√ √

√

Italy


Not specified √

√

Not specified √

√

SNICh Not specified

Surgical site √

√

Surgical site √

√


Not specified √

Not specified

Margherita

Not specified √

Not specified

√

Not specified

√

AR-ISS

Blood, CSF √

√

√ Blood, CSF

√ √

√

√ Blood, CSF

√ √

LAB

All √

√ √

√ All

√

All

√ √

SART

Blood √

√ √

√ Blood

√ √

√ √

Blood

√ √

M

icronet All*

√ √

√ √

All* √

√ √

√ √

All* √

√ √

Netherlands

ISIS-AR All*

√ √

√ √

All* √

√ √

√ √

All* √

√ √

Norw

ay FHI

Blood, CSF √

√ √

√ All

√ √

√ √

Blood

√ √

√ Portugal

ARSIP Not specified

Not specified

Not specified

Slovakia SNARS

All* √

√ √

√ All*

√ √

√ √

√ All*

V √

√

Spain


Blood

Not specified

SVIN Not specified

Not specified

Not specified

VINCAT

Not specified

Blood

Not specified

PIRASOA

Not specified

Blood

Not specified

√

ENVIN

-UCI All

√

√

All √

√

All √

√

Sweden

RESNET Not specified

Not specified

Not specified

SVEBAR All*

√ √

√ √

All* √

√ √

√ √

All* V

√ √


ND4BB CO

MBACTE-M


Switzerland

HPCI Not specified

Blood √

Blood

√

ANRESIS All*

√ √

√ √

All* √

√ √

√ √

All* V

√ √

CA-MRSA

Not specified

All

√

Not specified

United Kingdom

WHAIP

Not specified

Blood

√

Blood

√ HPS

Blood, respiratory

√ √

√ √

Blood, respiratory

√ √

√ √

Blood, respiratory

√ √

√

PHE Respiratory specim

en

Blood

√

Blood

√

HISC/HPA Not specified

√

Blood √

Not specified

√ √

PEN: peniclllin. FQ: fluoroquinolones. CTX: cefotaxim

e or ceftriaxone. MACR: m

acrolydes. OXA: oxacillin. LNZ: linezolid. VAN: vancom

ycin. GEN: gentamicin. GHLR: gentam

icin, high level resistance. TOB: tobram

ycin.

AMP: am

picillin.

√: Yes. Blank cell : not specified.

CSF: cerebrospinal fluid

*Any clinically relevant or routinely cultured pathogens/antibiotics


ND4BB CO

MBACTE-M


Table 7. Key antibiotics tested and type of sampling reported for gram

-negative pathogens in 40 surveillance systems (ECDC and W

HO not included)

Escherichia coli/ Klebsiella pneumoniae



Country Acronym

Type of sam

ple AM

P or AM

X

AMC

TZP FEP, CTX, CAZ or CRO

ERT M

EM

or IPM

AMK,

GEN

or TO

B

CIP, LVX, M

FX or O

FX

COL

Type of sam

ple FEP or CAZ

TZP M

EM

or IPM

AMK,

GEN

or TO

B

CIP, LVX, M

FX or O

FX

COL

Type of sam

ple M

EM

or IPM

COL

AMK,

GEN

or TO

B

TGC SU

L

Austria NRZ

Urinary, blood, CSF

√ √

√ √

√ √

√ √

M

ixed √

√ √

√ √

√ Blood, CSF

√ √

√ √

√

Belgium

WIV-ISSP

Blood

√

√ √

√

Blood √

√ √

√ Blood

√ √

Croatia

ISKRA Blood, CSF

√ √

√ √

√ √

√ √

√ Blood, CSF

√ √

√ √

√ √

Blood, CSF √

√ √

√

Denmark

DANMAP

Blood, urine

√

√

√ √

√

Blood

√ √

√ √

√

Not specified

Finland FIRE

All √

√ √

√

√ √

√

All √

√ √

√ √

All

√

√

France

ONERBA

All

All

All

Germany

KISS Not specified

√ √

√ √

√ √

√

Not specified

√ √

√

√

Not specified

√

ARS All*

√ √

√ √

√ √

√ √

√ All*

√ √

√ √

√ √

All* √

√ √

√ √

SARI Not specified

√ √

√ √

√

√ √

Not specified

√ √

√ √

√

Not specified

√

√ √

√

ARMIN

All

√ √

√ √

√

√ √

All

√ √

√ √

√ √

All √

√ √

GENARS All*

√ √

√ √

√ √

√ √

√ All*

√ √

√ √

√ √

All* √

√ √

√ √

Greece GSSAR

All* √

√ √

√ √

√ √

√ √

All* √

√ √

√ √

√ All*

√ √

√ √

√ Hungary

NNSR All

√

√ √

All

√

√

All √

Ireland HPSC

Blood, CSF

√

√

√

√ √

Blood, CSF

√ √

√

√

Blood, CSF √

√

Italy


√

√

√ √

Not specified

√

√

√

Not specified

√ √

SNICh Not specified

Surgical site

√

Surgical site


√

√ √

Not specified

Not specified

√

Margherita

Not specified

Not specified

√

√

Not specified

√

AR-ISS Blood, CSF

√ √

√ √

√ √

√ √

Blood, CSF

√ √

√ √

√

Blood, CSF

LAB All

√ √

√ √

√ √

√ √

? All

√ √

√ √

√ √

All √

√ √

SART Blood

√ √

√ √

√ √

√ √

√ Blood

√ √

√ √

√ √

Blood √

√ √

Micronet

All* √

√ √

√ √

√ √

√ √

All* √

√ √

√ √

√ All*

√ √

√ √

√


ND4BB CO

MBACTE-M


Netherlands

ISIS-AR All*

√ √

√ √

√ √

√ √

√ All*

√ √

√ √

√ √

All* √

√ √

√ √

Norw

ay FHI

All √

√ √

√ √

√ √

√ √

Not specified

√ √

√ √

√ √

Not specified

√ √

√ √

Portugal ARSIP

Not specified

Not specified

Not specified

Slovakia SNARS

All* √

√ √

√ √

√ √

√ √

All* √

√ √

√ √

√ All*

√ √

√ √

√

Spain


Blood

Not specified

SVIN Not specified

Not specified

Not specified

VINCAT

Blood

Not specified

Not specified

PIRASOA Blood

√

Blood

Not specified

ENVIN-UCI

All

√

√

All √

√ √

√

√ All

Sw

eden RESNET

Not specified

Not specified

Not specified

SVEBAR All*

√ √

√ √

√ √

√ √

√ All*

√ √

√ √

√ √

All* √

√ √

√ √

Switzerland

HPCI Blood

√

√ √

Not specified

Not specified

ANRESIS All*

√ √

√ √

√ √

√ √

√ All*

√ √

√ √

√ √

All* √

√ √

√ √

CA-MRSA

Not specified

Not specified

Not specified

United Kingdom

WHAIP

Blood

Not specified

Not specified

HPS All

√ √

√ √

√ √

√ √

√ All

√ √

√ √

√ √

All √

√ √

√

PHE Blood

Not specified

Blood

HISC/HPA Blood

Not specified

Not specified

AMP: Am

picillin. AMX: am

oxicillin. AMC: am

oxicillin/clavulanate; TZP: Piperacillin/tazobactam. FEP: cefepim

e. CTX: cefotaxime. CAZ: ceftazidim

e. CRO: ceftriaxone. ERT: ertapenem

. MEM

: meropenem

. IPM:

imipenem

. AMK: am

ikacin. GEN: gentamicin. TO

B: tobramycin. CIP: ciprofloxacin. LVX: levofloxacin. M

FX: moxifloxacin. O

FX: ofloxacin. COL: colistin. TGC: tigecycline. SUL: sulbactam

.

√=Yes. Blank cell = not specified. CSF: cerebrospinal fluid. *Any clinically relevant or routinely cultured pathogens/antibiotics



Figure 2A. National surveillance systems in European countries reporting MRSA and VRE (ECDC and

WHO not included)

Country System/ institution

Austria NRZ

Belgium WIV-ISSP

Croatia ISKRA

Denmark DANMAP

Finland FIRE

Germany KISS ARS SARI ARMIN GENARS

Greece GSSAR

Hungary NNSR

Ireland HPSC

Italy SITIER SNICh Margherita AR-ISS LAB SART Micronet

Netherlands ISIS-AR

Norway FHI

Slovakia SNARS

Spain PIRASOA ENVIN-UCI

Sweden SVEBAR

Switzerland HPCI ANRESIS

United Kingdom

HPS PHE HISC/HPA

Country System/ Institution

Austria

NRZ

Belgium

WIV-ISSP

Croatia

ISKRA

Denmark

DANMAP

Finland

FIRE

Germany

KISS ARS SARI ARMIN GENARS

Greece

GSSAR

Hungary

NNSR

Ireland

HPSC

Italy

SITIER SNICh SPIN-UTI Margherita AR-ISS LAB SART Micronet

Netherlands

ISIS-AR

Norway

FHI

Slovakia

SNARS

Spain

ENVIN-UCI

Sweden

SVEBAR

Switzerland

HPCI ANRESIS CA-MRSA

United Kingdom

WHAIP HPS PHE HISC/HPA

MRSA

VRE


ND4BB CO

MBACTE-M


Figure 2B. National surveillance system

s in European countries reporting colistin-resistant E. coli/K. pneumoniae, P. aeruginosa, A. baum

annii (ECDC and

WHO

not included)

Carbapenem-resistant

A. baumannii

Country System

/ institution Austria

NRZ Belgium

W

IV-ISSP Croatia

ISKRA Denm

ark

DANM

AP Finland

FIRE Germ

any

KISS

ARS

SARI

ARM

IN

GENARS Greece

GSSAR Hungary

NNSR Ireland

HPSC Italy

SITIER

SPIN-UTI

AR-ISS

LAB

SART

Micronet

Netherlands

ISIS-AR N

orway

FHI Slovakia

SNARS Sw

eden

SVEBAR

Switzerland

HPCI

ANRESIS U

nited Kingdom

HPS

Country System


NRZ Belgium

W

IV-ISSP Croatia

ISKRA Denm

ark

DANM

AP Finland

FIRE Germ

any

KISS

ARS

SARI

ARM

IN

GENARS Greece

GSSAR Hungary

NNSR Ireland

HPSC Italy

SITIER

Margherita

AR-ISS

LAB

SART

M

icronet N

etherlands

ISIS-AR

Norw

ay

FHI

Slovakia

SNARS

Spain

ENVIN-UCI

Sweden

SVEBAR Sw

itzerland

ANRESIS

United

Kingdom

HPS

Country System


NRZ Belgium

W

IV-ISSP Croatia

ISKRA Finland

FIRE Germ

any

KISS

ARS

SARI

ARM

IN

GENARS

Greece

GSSAR

Hungary

NNSR

Ireland

HPSC

Italy

SITIER

SPIN-UTI

M

argherita

LAB

SART

Micronet

Netherlands

ISIS-AR N

orway

FHI Slovakia

SNARS Sw

eden

SVEBAR

Switzerland

ANRESIS U

nited Kingdom

HPS

Carbapenem-resistant

E. coli/K. pneumoniae

Carbapenem

-resistant P. aeruginosa



Figure 2C. National surveillance systems in European countries reporting cephalosporin-resistant E. coli/K. pneumoniae and P. aeruginosa (ECDC and WHO not included)


Austria NRZ

Belgium WIV-ISSP

Croatia ISKRA

Denmark DANMAP

Finland FIRE


Greece GSSAR

Hungary NNSR

Ireland HPSC

Italy SITIER SNICh Margherita AR-ISS LAB SART Micronet

Netherlands ISIS-AR

Norway FHI

Slovakia SNARS

Spain ENVIN-UCI

Sweden SVEBAR

Switzerland ANRESIS

United Kingdom

HPS


Austria NRZ

Belgium WIV-ISSP

Croatia ISKRA

Denmark DANMAP

Finland FIRE


Greece GSSAR

Hungary NNSR

Ireland HPSC

Italy SITIER SPIN-UTI AR-ISS LAB SART Micronet

Netherlands ISIS-AR

Norway FHI

Slovakia SNARS

Spain PIRASOA

Sweden SVEBAR

Switzerland ANRESIS

United Kingdom

HPS

Cephalosporin-resistant E. coli/K. pneumoniae

Cephalosporin-resistant P. aeruginosa


ND4BB CO

MBACTE-M


Figure 2D. National surveillance system

s in European countries reporting colistin-resistant E.coli/K. pneumoniae, P. aeruginosa, A. baum

annii (ECDC and W

HO not included)

Colistin-resistant A. baum

annii

Country System

/ institution

Croatia

ISKRA

Germany

ARS

GENARS Greece

GSSAR Italy

SART

Micronet

Netherlands

ISIS-AR

Norway

FHI Slovakia

SNARS Sw

eden

SVEBAR

Switzerland

ANRESIS United Kingdom

HPS

Country System

/ institution

Austria

NRZ

Belgium

WIV-ISSP

Croatia

ISKRA

Germany

ARS

ARMIN

GENARS Greece

GSSAR Italy

SITIER

LAB

SART

Micronet

Netherlands

ISIS-AR

Norway

FHI Slovakia

SNARS Spain

ENVIN-UCI

Sweden

SVEBAR Sw

itzerland

ANRESIS

United Kingdom

HPS

Country System

/ institution

Austria

NRZ

Belgium

WIV-ISSP

Croatia

ISKRA

Germany

ARS

ARMIN

GENARS Greece

GSSAR Italy

SITIER

LAB

SART

Micronet

Netherlands

ISIS-AR

Norway

FHI Slovakia

SNARS Sw

eden

SVEBAR

Switzerland

ANRESIS United Kingdom

HPS

Colistin-resistant E.coli/K. pneum

oniae

Colistin-resistant P. aeruginosa



• National • AMR, voluntary participation • Inpatients and outpatients, all ages • Number of participating hospitals:

139

•

Source of data Laboratory Clinical status Infection Duplicates policy Yes Resistance definition EUCAST or CLSI Metrics and dissemination Prevalence. Yearly, pooled data. Quality Assessment External, voluntary

Pathogens under surveillance

Specimen source Antibiotics


Blood, CSF, respiratory PEN

LVX or MFX

CTX or CRO

MAC

Staphylococcus aureus All OXA FQ LNZ VAN

GEN or TOB

Enterococcus faecalis/ Enterococcus faecium Blood AMP VAN GEH


Urinary, blood, CSF

AMP or AMX

AMC TZP CG ERT MEM or IPM

AG FQ

Pseudomonas aeruginosa Mixed FEP or CAZ

TZP MEM or IPM

AG FQ COL

Acinetobacter baumannii Blood, CSF MEM or IPM

COL AG TGC SUL

NRZ

National reference centre for nosocomial infection and antimicrobial resistance

ANISS

Austrian nosocomial infection surveillance system

• National • HAI, voluntary participaton • Inpatients, all ages • Number of participating hospitals:

60 • :

PEN: peniclllin. CIP: ciprofloxacin. LVX: levofloxacin. MFX: moxifloxacin. OFX: ofloxacin. FQ: CIP/LVX/MFX/OFX. FEP: cefepime. CTX: cefotaxime. CAZ: ceftazidime. CRO: ceftriaxone.CG:FEP/CTX/CAZ/CRO. MAC: macrolides (erythromycin/ clarithromycin). OXA: oxacillin. LNZ: linezolid. VAN: vancomycin. GEN: gentamicin. GHLR: gentamicin, high level resistance. TOB: tobramycin. AMK: amikacin. AG:GEN/TOB/AMK. AMP: Ampicillin. AMX: amoxicillin. AMC: amoxicillin/clavulanate; TZP: Piperacillin/tazobactam.. ERT: ertapenem. MEM: meropenem. IPM: imipenem. COL: colistin. TGC: tigecycline. SUL: sulbactam.

NRZ

The Austrian strategy

Total population: 9 million

NNIS Risk Index Yes Include urgent procedures Yes Data on antibiotic prophylaxis Yes Peri- operative checklist POST-op Interventions CABG CVAL CHOL COLO CSEC HPRO KPRO LAM

Risk factors Antibiotic use, comorbidities, severity score, previous hospitalizations Clinical outcomes Mortality Metrics and dissemination Incidence density, device utilisation rate.

Quality Assessment:

External, voluntary

SSI CLABSI

VAP CAUTI

CLABSI: Central line-associated bloodstream infection. VAP: Ventilator-associated pneumonia. CAUTI: Catheter-associated urinary tract infections SSI: surgical site infection. POST-op: Post-operative checklist. CABG: Coronary artery bypass grafting. CVAL: cardiac valve replacement. CHOL: cholecystectomy. COLO: colon surgery. CSEC: caesarean section. HPRO: hip prosthesis. KPRO: knee prosthesis. LAM: laminectomy.

Dissemination: Yearly, pooled

data

ANISS




Source of data Laboratory Clinical status Infection+colonisation Metrics and dissemination CI. Yearly, individual HCF and pooled data

Risk factors Comorbidities, severity score Metrics Incidence density and cumulative incidence , device utilisation rate.

SSI CLABSI

VAP CAUTI

Pathogens under surveillance Specimen source Antibiotics

Staphylococcus aureus Blood, CSF OXA VAN GEN or TOB

Enterococcus faecalis/ Enterococcus faecium Blood, CSF AMP VAN

Escherichia coli/ Klebsiella pneumoniae Blood AMC CG ERT

MEM or IPM

Pseudomonas aeruginosa Blood FEP or CAZ

TZP MEM or IPM

COL

Acinetobacter baumannii Blood MEM or IPM

COL

• National • AMR+HAI, voluntary participation • Laboratory, all ages • Number of participating labs:

138

CI: cumulative incidence. HCF: healthcare facilities. FEP: cefepime. CAZ: ceftazidime. OXA: oxacillin. VAN: vancomycin. GEN: gentamicin. TOB: tobramycin. AMP: Ampicillin. AMC: amoxicillin/clavulanate; TZP: Piperacillin/tazobactam. ERT: ertapenem. MEM: meropenem. IPM: imipenem. COL: colistin.


The Belgian strategy


WIV-ISSP Scientific institute of public health (IPH) –

Institut scientifique de santé publique

Dissemination: Yearly,

individual HCF and pooled

data



Source of data Laboratory Clinical status Infection+colonisation Duplicates policy Yes Resistance definition EUCAST Dissemination Yearly, pooled data

• National • AMR, voluntary participation • Laboratory, all ages • Number of participating hospitals:

38

PEN: peniclllin. CIP: ciprofloxacin. LVX: levofloxacin. MFX: moxifloxacin. OFX: ofloxacin. FQ: CIP/LVX/MFX/OFX. MAC: macrolides (erythromycin/ clarithromycin). OXA: oxacillin. FEP: cefepime. CTX: cefotaxime. CAZ: ceftazidime. CRO: ceftriaxone. CG:FEP/CTX/CAZ/CRO. LNZ: linezolid. VAN: vancomycin. GEN: gentamicin. GHLR: gentamicin, high level resistance. TOB: tobramycin. AMK: amikacin. AG:GEN/TOB/AMK. AMP: Ampicillin. AMX: amoxicillin. AMC: amoxicillin/clavulanate; TZP: Piperacillin/tazobactam.. ERT: ertapenem. MEM: meropenem. IPM: imipenem. COL: colistin. SUL: sulbactam.

ISKRA

Intersectoral coordination mechanism for the control of AMR

The Croatian strategy




Streptococcu pneumoniae

Blood, CSF, respiratory PEN

LVX or MFX

MAC

Staphylococcus aureus Blood, CSF OXA FQ LNZ VAN

GEN or TOB

Enterococcus faecalis/ Enterococcus faecium Blood, CSF AMP VAN GEH


Blood, CSF AMP or AMX


AG FQ COL

Pseudomonas aeruginosa Blood, CSF

FEP or CAZ

TZP MEM or IPM

AG FQ COL

Acinetobacter baumannii Blood, CSF

MEM or IPM

COL AG SUL



Source of data Laboratory Clinical status Infection+colonisation Duplicates policy Yes Resistance definition EUCAST or CLSI Metrics and dissemination Prevalence and CI1. Yearly, pooled data. Quality Assessment External, voluntary

Metrics and dissemination Incidence density. Weekly, individual HCF data

CLABSI CAUTI


Streptococcus pneumoniae Blood, CSF PEN MAC

Staphylococcus aureus All OXA LNZ

Enterococcus faecalis/ Enterococcus faecium Blood AMP VAN

Escherichia coli/ Klebsiella pneumoniae Blood, urine

AMP or AMX

CG ERT MEM or IPM FQ

Pseudomonas aeruginosa Blood FEP or CAZ TZP MEM

or IPM AG FQ

CI: cumulative incidence (reported only for MRSA). PEN: peniclllin. MAC: macrolides (erythromycin/ clarithromycin). OXA: oxacillin. LNZ: linezolid. AMP: Ampicillin. VAN: vancomycin. AMX: amoxicillin. CG: cefepime (FEP)/cefotaxime/ceftazidime (CAZ)/ceftriaxone. ERT: ertapenem. MEM: meropenem. IPM: imipenem. FQ: ciprofloxacin/levofloxacin /moxifloxacin /ofloxacin. TZP: Piperacillin/tazobactam. AG: gentamicin/tobramycin/amikacin.

CLABSI: Central line-associated bloodstream infection. CAUTI: Catheter-associated urinary tract. HCF: healthcare facilities.

The Danish strategy


• National • HAI, voluntary participation • Inpatients, all ages • Number of participating hospitals:

312

• National • AMR, voluntary participation • Inpatients and outpatients, all ages • Number of participating labs: 10

Departments of clinical microbiology

DANMAP

Danish integrated antimicrobial resistance monitoring and research programme

DANMAP

HAIBA

HAIBA

Hospital-acquired infections database




Source of data Laboratory Clinical status Infection Duplicates policy Yes Resistance definition EUCAST Metrics and dissemination Prevalence. Yearly, pooled data. Quality Assessment External, voluntary

Risk factors Antibiotic use, comorbidities Clinical outcomes Mortality Metrics Incidence density.

Quality Assessment:

External, voluntary

SSI CLABSI


Streptococcus pneumoniae All PEN LVX or MFX

CTX or CRO

MAC

Staphylococcus aureus All OXA FQ

Enterococcus faecalis/ Enterococcus faecium All AMP VAN

Escherichia coli/ Klebsiella pneumoniae All

AMP or AMX

AMC TZP CG MEM or IPM

AG FQ

Pseudomonas aeruginosa All FEP or CAZ

TZP MEM or IPM

AG FQ COL

Acinetobacter baumannii All MEM or IPM

AG

PEN: peniclllin. CIP: ciprofloxacin. LVX: levofloxacin. MFX: moxifloxacin. OFX: ofloxacin. FQ: CIP/LVX/MFX/OFX. FEP: cefepime. CTX: cefotaxime. CAZ: ceftazidime. CRO: ceftriaxone. CG:FEP/CTX/CAZ/CRO. MAC: macrolides (erythromycin/ clarithromycin). OXA: oxacillin. AMP: Ampicillin. VAN: vancomycin. AMX: amoxicillin. AMC: amoxicillin/clavulanate; TZP: Piperacillin/tazobactam. MEM: meropenem. IPM: imipenem. . AG: gentamicin/ tobramycin/ amikacin. COL: colistin.

CLABSI: Central line-associated bloodstream infection. SSI: surgical site infection. POST-op: Post-operative checklist. CABG: Coronary artery bypass grafting. CVAL: cardiac valve replacement. CHOL: cholecystectomy. COLO: colon surgery. CSEC: caesarean section. HPRO: hip prosthesis. KPRO: knee prosthesis. LAM: laminectomy.

The Finnish strategy


SIRO

Finnish hospital infection program


258

• National • AMR, voluntary participation • Inpatients and outpatients, all ages • Number of participating labs:

28

FIRE



data

FIRE

SIRO



NNIS Risk Index Yes Data on antibiotic prophylaxis Yes Interventions

CABG CVAL CHOL COLO CSEC HPRO KPRO LAM

Dissemination Yearly, comparative with other HCF Quality assessment External, voluntary

Source of data Laboratory Clinical status Infection Duplicates policy Yes Resistance definition Local Dissemination Yearly.

RAISIN

Réseau d’alerte, d’investigation et de surveillance des infections nosocomiales

• National • HAI, voluntary participation • Inpatients, all ages • Number of participating

labs/hospitals: Not specified • :

The French strategy


• National • AMR, voluntary participation • Inpatients and outpatients, all ages • Number of participating

labs/hospitals: Not specified •

ONERBA

L’Observatoire national de l’epidémiologie de la résistance bactérienne aux antibiotiques

SSI

ONERBA

RAISIN

SSI: surgical site infection. HCF: healthcare facilities. CABG: Coronary artery bypass grafting. CVAL: cardiac valve replacement. CHOL: cholecystectomy. COLO: colon surgery. CSEC: caesarean section. HPRO: hip prosthesis. KPRO: knee prosthesis. LAM: laminectomy.


ND4BB CO

MBACTE-M


The German strategy


• N

ational •

AMR+HAI, voluntary participation

• Inpatients, all ages

• N

umber of hospitals: 1482

• N

ational •

AMR, voluntary participation

• Inpatients and outpatients, all ages

• N


ARS Antibiotic resistance

surveillance

• N

ational •



• N


SARI Surveillance of antibiotic use and resistance in ICU

• N

ational, Inactive •


• Laboratory, all ages

GENARS Germ

an network for

antimicrobial resistance surveillance

KISS Krankenhaus infektions

surveillance system

• Regional

• AM

R, voluntary participation •

Inpatients and outpatients, all ages •

Num

ber of labs: 13

ARMIN

Antibiotika resistenz m

onitoring in niedersachsen

NN

IS Risk Index

Yes Include urgent procedures

Yes Interventions CABG

CVAL CHO

L CO

LO

CSEC HPRO

KPRO

LAM

Risk factors Antibiotic use Clinical outcom

es M

ortality M

etrics and dissemination

Incidence density, device utlisation rate

SSI

CLABSI: Central line-associated bloodstream infection. VAP: Ventilator-associated pneum

onia. CAUTI: Catheter-associated urinary tract infections

SSI: surgical site infection. CABG: Coronary artery bypass grafting. CVAL: cardiac valve replacem

ent. CHOL: cholecystectom

y. COLO

: colon surgery. CSEC: caesarean section. HPRO

: hip prosthesis. KPRO: knee prosthesis. LAM

: laminectom

y. Dissemination:

Yearly, pooled data

CLABSI VAP

CAUTI

KISS



ARS

SARI

KISS

Source of data Laboratory Duplicates policy Yes Resistance definition EUCAST or CLSI or Local Risk factors Not specified Metrics and dissemination Prevalence. Yearly, pooled data. Quality Assessment External, voluntary

Source of data Laboratory Duplicates policy Yes Resistance definition EUCAST or CLSI or Local Risk factors Antibiotic use Metrics and dissemination Prevalence, ID. Yearly, pooled data.

Source of data Laboratory+charts Clinical status Infection+colonisation Duplicates policy Yes Resistance definition Local Risk factors Invasive procedures, Antibiotic use Metrics and dissemination Prevalence, ID, CI. Yearly, pooled data.

ID: incidence density: CI: cumulative incidence. PEN: peniclllin. CIP: ciprofloxacin. LVX: levofloxacin. MFX: moxifloxacin. OFX: ofloxacin. FQ: CIP/LVX/MFX/OFX. FEP: cefepime. CTX: cefotaxime. CAZ: ceftazidime. CRO: ceftriaxone.CG:FEP/CTX/CAZ/CRO. MAC: macrolides (erythromycin/ clarithromycin). OXA: oxacillin. LNZ: linezolid. VAN: vancomycin. GEN: gentamicin. GHLR: gentamicin, high level resistance. TOB: tobramycin. AMK: amikacin. AG:GEN/TOB/AMK. AMP: Ampicillin. AMX: amoxicillin. AMC: amoxicillin/clavulanate; TZP: Piperacillin/tazobactam.. ERT: ertapenem. MEM: meropenem. IPM: imipenem. COL: colistin. TGC: tigecycline. SUL: sulbactam.



Streptococcus pneumoniae All PEN

LVX or MFX

CTX or CRO

MAC

Staphylococcus aureus All OXA FQ LNZ VAN GEN or TOB

Enterococcus faecalis/ Enterococcus faecium All AMP VAN GEH


AMP or AMX


AG FQ COL

Pseudomonas aeruginosa All

FEP or CAZ

TZP MEM or IPM

AG FQ COL

Acinetobacter baumannii All

MEM or IPM

COL AG TGC SUL




Not specified PEN

LVX or MFX

CTX or CRO

MAC

Staphylococcus aureus Not specified OXA FQ LNZ VAN

Enterococcus faecalis/ Enterococcus faecium

Not specified AMP VAN


Not specified

AMP or AMX


AG FQ


Not specified

FEP or CAZ

TZP MEM or IPM

AG FQ


Not specified

MEM or IPM

AG TGC SUL



Staphylococcus aureus Not specified OXA


Not specified VAN


Not specified

AMP or AMX


FQ


Not specified

FEP or CAZ

TZP MEM or IPM

FQ


Not specified

MEM or IPM

COL



ARMIN

GENARS

Source of data Laboratory Duplicates policy Yes Resistance definition EUCAST or CLSI or Local Metrics and dissemination Prevalence. Yearly, pooled data.

Source of data Laboratory Resistance definition Local Metrics and dissemination Prevalence. Pooled data.




LVX or MFX

CTX or CRO

MAC




AMP or AMX


AG FQ


FEP or CAZ

TZP MEM or IPM

AG FQ COL


MEM or IPM

COL AG




LVX or MFX

CTX or CRO

MAC




AMP or AMX


AG FQ COL


FEP or CAZ

TZP MEM or IPM

AG FQ COL


MEM or IPM

COL AG TGC SUL

PEN: peniclllin. CIP: ciprofloxacin. LVX: levofloxacin. MFX: moxifloxacin. OFX: ofloxacin. FQ: CIP/LVX/MFX/OFX. FEP: cefepime. CTX: cefotaxime. CAZ: ceftazidime. CRO: ceftriaxone.CG:FEP/CTX/CAZ/CRO. MAC: macrolides (erythromycin/ clarithromycin). OXA: oxacillin. LNZ: linezolid. VAN: vancomycin. GEN: gentamicin. GHLR: gentamicin, high level resistance. TOB: tobramycin. AMK: amikacin. AG:GEN/TOB/AMK. AMP: Ampicillin. AMX: amoxicillin. AMC: amoxicillin/clavulanate; TZP: Piperacillin/tazobactam.. ERT: ertapenem. MEM: meropenem. IPM: imipenem. COL: colistin. TGC: tigecycline. SUL: sulbactam.



Source of data Laboratory Duplicates policy Yes Resistance definition CLSI Metrics and dissemination Prevalence. Yearly, comparative data with other HCF Quality Assessment External, voluntary

• National • AMR, voluntary participation • Inpatients, all ages • Number of participating hospitals:

52

GSSAR

Greek system for the surveillance of antimicrobial resistance




LVX or MFX

CTX or CRO

MAC


GEN or TOB


All AMP VAN GEH


All AMP or AMX


AG FQ COL


FEP or CAZ

TZP MEM or IPM

AG FQ COL


MEM or IPM

COL AG TGC SUL

The Greek strategy


HCF: healthcare facilities. PEN: peniclllin. CIP: ciprofloxacin. LVX: levofloxacin. MFX: moxifloxacin. OFX: ofloxacin. FQ: CIP/LVX/MFX/OFX. FEP: cefepime. CTX: cefotaxime. CAZ: ceftazidime. CRO: ceftriaxone.CG:FEP/CTX/CAZ/CRO. MAC: macrolides (erythromycin/ clarithromycin). OXA: oxacillin. LNZ: linezolid. VAN: vancomycin. GEN: gentamicin. GHLR: gentamicin, high level resistance. TOB: tobramycin. AMK: amikacin. AG: GEN/TOB/AMK. AMP: Ampicillin. AMX: amoxicillin. AMC: amoxicillin/clavulanate; TZP: Piperacillin/tazobactam.. ERT: ertapenem. MEM: meropenem. IPM: imipenem. COL: colistin. TGC: tigecycline. SUL: sulbactam.



Resistance definition EUCAST or CLSI Dissemination Not specified. Mixed, pooled data


Staphylococcus aureus All OXA VAN

Enterococcus faecalis/ Enterococcus faecium All VAN

Escherichia coli/ Klebsiella pneumoniae All CG ERT MEM or IPM


MEM or IPM


• National • AMR+HAI, voluntary participation • Inpatients, all ages • Number of participating

labs/hospitals: Not specified

OXA: oxacillin. VAN: vancomycin. CG: cefepime (FEP)/cefotaxime/ceftazidime (CAZ)/ceftriaxone. ERT: ertapenem. MEM: meropenem. IPM: imipenem.

NNSR

National nosocomial surveillance system

The Hungarian strategy


NNIS Risk Index Not specified Include urgent procedures Not specified Data on antibiotic prophylaxis Not specified Peri- operative checklist Not specified Interventions CABG CVAL CHOL COLO CSEC HPRO KPRO LAM

Dissemination Mixed, pooled data Quality Assessment Not specified

SSI

SSI: surgical site infection. CABG: Coronary artery bypass grafting. CVAL: cardiac valve replacement. CHOL: cholecystectomy. COLO: colon surgery. CSEC: caesarean section. HPRO: hip prosthesis. KPRO: knee prosthesis. LAM: laminectomy.



Source of data Laboratory+charts Clinical status Infection Duplicates policy Yes Resistance definition EUCAST Risk factors Previous hospitalisations, ICU stay Metrics and dissemination Prevalence and ID. Mixed, pooled data

Risk factors Antibiotic use Clinical outcomes Mortality Metrics and dissemination Incidence density, utlisation rate. Mixed, pooled data

CLABSI VAP

CAUTI


Streptococcus pneumoniae Blood, CSF PEN

Staphylococcus aureus Blood, CSF OXA

Enterococcus faecalis/ Enterococcus faecium Blood, CSF AMP VAN GEH

Escherichia coli/ Klebsiella pneumoniae Blood, CSF

AMP or AMX

CG MEM or IPM AG FQ

Pseudomonas aeruginosa Blood, CSF FEP or CAZ TZP MEM

or IPM FQ

Acinetobacter baumannii Blood, CSF MEM or IPM AG

ID: incidence density.PEN: peniclllin. MAC: macrolides (erythromycin/ clarithromycin). OXA: oxacillin. LNZ: linezolid. AMP: Ampicillin. VAN: vancomycin. AMX: amoxicillin. CG: cefepime (FEP)/cefotaxime/ceftazidime (CAZ)/ceftriaxone. ERT: ertapenem. MEM: meropenem. IPM: imipenem. FQ: ciprofloxacin/levofloxacin /moxifloxacin /ofloxacin. TZP: Piperacillin/tazobactam. AG: gentamicin/tobramycin/amikacin.

CLABSI: Central line-associated bloodstream infection. CAUTI: Catheter-associated urinary tract. VAP: Ventilator-associated pneumonia.

• National • AMR+HAI, voluntary participation • All ages • Number of participating


HPSC

Health propection surveillance centre

The Irish strategy



ND4BB CO

MBACTE-M


The Italian strategy

•

National

• AM


Laboratory, all ages •

Num

ber of participating labs: 51

AR-ISS

Antibiotico resistenza - Istituto superiore di sanitá

• Regional

• AM


Inpatients+outpatients, all ages •

Num

ber of participating hospitals: 59

LAB

Sorveglianza dell’antibioticoresistenza e uso di antibiotici sistem

ici in Emilia-Rom

agna

• Regional

• AM



Num

ber of participating labs: 14

SART

Sorveglianza antibiotico resistenza Toscana •

National, inactive

• AM


Laboratory, all ages

M

ICRONET


• N

ational •



• N

umber of participating hospitals:

98

SN

ICh Sistem

a nazionale di sorveglianza delle infezioni del sito chirurgico

• N

ational •



• N


23

SPIN-U

TI Sorveglianza prospettica delle infezioni

nosocomiali nella U

nità di Terapia Intensiva

• N

ational •



• N


256

M

ARGHERITA M

argherita PROSAFE

• Regional

• AM

R+HAI, voluntary participation •

Inpatients, all ages •

Num


SITIER

Sorveglianza regionale delle infezioni in terapia intensiva


ND4BB CO

MBACTE-M


SITIER

MARGHERITA

SPIN-U

TI

Risk factors Antibiotic use, severity score, previous hospitalisations Clinical outcom

es M

ortality M


Incidence density, utlisation rate. Yearly, pooled data

Risk factors Antibiotic use, severity score, previous hospitalisations Clinical outcom

es M

ortality M


Incidence density, utlisation rate. Yearly, comparative data

with other HCF

Quality Assessm

ent Local

Risk factors Antibiotic use, com

orbidities, severity score, previous hospitalisations Clinical outcom

es M

ortality, length of stay M


Incidence density, utlisation rate. RT, comparative data w

ith other HCF

SNICh

NN

IS Risk Index


Yes Data on antibiotic prophylaxis

Yes Peri- operative checklist

Not specified Interventions CABG

CVAL CHO

L CO

LO

CSEC HPRO

KPRO

LAM

Dissemination

Yearly, comparative

data with other HCF

Quality Assessm

ent

Local, compulsory

SSI


onia. CAUTI: Catheter-associated urinary tract infections. HCF: healthcare facilities. RT: real-tim

e SSI: surgical site infection. CABG: Coronary artery bypass grafting. CVAL: cardiac valve replacem

ent. CHOL:

cholecystectomy. CO

LO: colon surgery. CSEC: caesarean section. HPRO

: hip prosthesis. KPRO: knee prosthesis.

LAM: lam

inectomy.

CLABSI VAP

CAUTI

CLABSI VAP

CAUTI

CLABSI VAP

CAUTI



AR-ISS

SNICh

SPIN-UTI

Source of data Laboratory Duplicates policy Yes Resistance definition EUCAST Metrics and dissemination Prevalence. Mixed, comparative data with other HCF Quality Assessment External, voluntary

Source of data Laboratory Clinical status Infection Risk factors Antibiotic use Metrics and dissemination CI. Yearly, comparative data with other HCF Quality Assessment Local, compulsory

Source of data Laboratory Clinical status Infection+colonisation Risk factors Invasive procedures, antibiotic use, comorbidities, previous hospitalisation Metrics and dissemination Prevalence, ID. Yearly, pooled data




CTX or CRO

MAC

Staphylococcus aureus Blood, CSF OXA FQ VAN

GEN or TOB


Blood, CSF AMP VAN


Blood, CSF AMP or AMX


AG FQ

Pseudomonas aeruginosa Blood, CSF

FEP or CAZ

TZP MEM or IPM

AG FQ


Staphylococcus aureus Surgical site OXA VAN

Enterococcus faecalis/ Enterococcus faecium Surgical site AMP VAN

Pseudomonas aeruginosa Surgical site FEP or CAZ



Escherichia coli/ Klebsiella pneumoniae Not specified CG ERT MEM

or IPM

Pseudomonas aeruginosa Not specified FEP or CAZ

Acinetobacter baumannii Not specified MEM or IPM

CI: cumulative incidence. ID: incidence density. HCF: healthcare facilities. RT: real-time. PEN: peniclllin. CIP: ciprofloxacin. LVX: levofloxacin. MFX: moxifloxacin. OFX: ofloxacin. FQ: CIP/LVX/MFX/OFX. FEP: cefepime. CTX: cefotaxime. CAZ: ceftazidime. CRO: ceftriaxone.CG:FEP/CTX/CAZ/CRO. MAC: macrolides (erythromycin/ clarithromycin). OXA: oxacillin. LNZ: linezolid. VAN: vancomycin. GEN: gentamicin. GHLR: gentamicin, high level resistance. TOB: tobramycin. AMK: amikacin. AG: GEN/TOB/AMK. AMP: Ampicillin. AMX: amoxicillin. AMC: amoxicillin/clavulanate; TZP: Piperacillin/tazobactam.. ERT: ertapenem. MEM: meropenem. IPM: imipenem. COL: colistin. TGC: tigecycline. SUL: sulbactam.



MARGHERITA

LAB

SART

Source of data Laboratory+charts Clinical status Infection Duplicates policy Yes Risk factors Invasive procedures, antibiotic use, comorbidities, previous hospitalisation Metrics and dissemination Prevalence. Yearly, comparative data with other HCF Quality Assessment Local

Source of data Laboratory Clinical status Infection+colonisation Duplicates policy Yes Resistance definition EUCAST Metrics and dissemination Prevalence. Yearly, comparative data with other HCF Quality Assessment Local

Source of data Laboratory Clinical status Infection+colonisation Duplicates policy Yes Resistance definition EUCAST Risk factors Antibiotic use, length of stay, comorbidities Metrics and dissemination Prevalence, ID. Pooled data



Streptococcus pneumoniae Not specified PEN


Enterococcus faecalis/ Enterococcus faecium Not specified VAN


MEM or IPM

Acinetobacter baumannii Not specified MEM or IPM




LVX or MFX

CTX or CRO

MAC

Staphylococcus aureus All OXA


All AMP


All AMP or AMX


AG FQ


FEP or CAZ

TZP MEM or IPM

AG FQ COL


MEM or IPM

COL AG



Streptococcus pneumoniae Blood PEN

LVX or MFX

CTX or CRO

MAC

Staphylococcus aureus Bloodv OXA FQ LNZ VAN

Enterococcus faecalis/ Enterococcus faecium Blood AMP VAN

Escherichia coli/ Klebsiella pneumoniae Blood

AMP or AMX


AG FQ COL

Pseudomonas aeruginosa Blood

FEP or CAZ

TZP MEM or IPM

AG FQ COL

Acinetobacter baumannii Blood

MEM or IPM

COL AG



SITIER

MICRONET

Source of data Laboratory Clinical status Infection Risk factors Invasive procedures Metrics and dissemination Prevalence, CI. RT, comparative data with other HCF

Source of data Laboratory+charts Clinical status Infection+colonisation Metrics and dissemination Prevalence. Pooled data



Staphylococcus aureus Not specified OXA VAN

Enterococcus faecalis/ Enterococcus faecium Not specified AMP VAN

Escherichia coli/ Klebsiella pneumoniae Not specified AMC CG ERT MEM

or IPM


MEM or IPM

Acinetobacter baumannii Not specified MEM or IPM COL




LVX or MFX

CTX or CRO

MAC




AMP or AMX


AG FQ COL


FEP or CAZ

TZP MEM or IPM

AG FQ COL


MEM or IPM

COL AG TGC SUL



NNIS Risk Index Yes Include urgent procedures Yes Data on antibiotic prophylaxis Yes Interventions CABG CVAL CHOL COLO CSEC HPRO KPRO LAM

Risk factors Antibiotic use, severity score, previous hospitalizations Clinical outcomes Mortality Metrics Incidence density, cumulative incidence

Dissemination:

Yearly, pooled data


The Lithuanian strategy


HAI E.S.LI

Healthcare-associated infections epidemiological surveillance

• National • HAI, voluntary participation • Inpatients, all ages • Number of participating hospitals: 103

SSI

CLABSI VAP

CAUTI



The Dutch strategy


• National • AMR, voluntary participation • Inpatients+outpatients, all ages • Number of participating labs: 37

ISIS-AR

Infectious disease surveillance and information system for antibiotic resistance


43

PREZIES

Preventie van ziekenhuisinfecties door surveillance

• National • HAI, voluntary participation • Inpatients, only adults • Number of participating nursing

homes: 38

SNIV

Surveillance network for infectious diseases in nursing homes


Risk factors Antibiotic use, comorbidities Clinical outcomes Mortality Metrics Cumulative incidence

SSI CLABSI


data

PREZIES

Risk factors Antibiotic use Clinical outcomes Mortality Metrics and dissemination Incidence density. Yearly, pooled data

CLABSI VAP

CAUTI

SNIV




Source of data Laboratory Clinical status Infection+colonisation Duplicates policy Yes Resistance definition EUCAST Metrics and dissemination Prevalence. Weekly, pooled data




LVX or MFX

CTX or CRO

MAC


GEN or TOB


All AMP VAN GEH


All AMP or AMX


AG FQ COL


FEP or CAZ

TZP MEM or IPM

AG FQ COL


MEM or IPM

COL AG TGC SUL

PEN: peniclllin. CIP: ciprofloxacin. LVX: levofloxacin. MFX: moxifloxacin. OFX: ofloxacin. FQ: CIP/LVX/MFX/OFX. FEP: cefepime. CTX: cefotaxime. CAZ: ceftazidime. CRO: ceftriaxone.CG:FEP/CTX/CAZ/CRO. MAC: macrolides (erythromycin/ clarithromycin). OXA: oxacillin. LNZ: linezolid. VAN: vancomycin. GEN: gentamicin. GHLR: gentamicin, high level resistance. TOB: tobramycin. AMK: amikacin. AG: GEN/TOB/AMK. AMP: Ampicillin. AMX: amoxicillin. AMC: amoxicillin/clavulanate; TZP: Piperacillin/tazobactam.. ERT: ertapenem. MEM: meropenem. IPM: imipenem. COL: colistin. TGC: tigecycline. SUL: sulbactam.

ISIS-AR



The Norwegian strategy


NNIS Risk Index Yes Include urgent procedures Yes Data on antibiotic prophylaxis Yes Peri- operative checklist POST-op Intervention CABG CVAL CHOL COLO CSEC HPRO KPRO LAM

Dissemination Yearly, comparative

data with other HCF

• National • AMR+HAI, voluntary participation • All ages • Number of participating


FHI Nasjonalt Folkehelseinstitutt: Healthcare

Asssociated Infections module for SSI (NOIS-SSI); Antimicrobial drug Resistance module

(NORM)

SSI: surgical site infection. CABG: Coronary artery bypass grafting. CVAL: cardiac valve replacement. CHOL: cholecystectomy. COLO: colon surgery. CSEC: caesarean section. HPRO: hip prosthesis. KPRO: knee prosthesis. LAM: laminectomy.

Source of data Laboratory+charts Clinical status Not specified Duplicates policy Yes Resistance definition EUCSAT Risk factors Antibiotic use Metrics and dissemination Prevalence. Yearly, comparative data with other HCF Quality Assessment Not specified




LVX or MFX

CTX or CRO

MAC



Blood AMP VAN GEH


All AMP or AMX


AG FQ COL


Not specified

FEP or CAZ

TZP MEM or IPM

AG FQ COL


Not specified

MEM or IPM

COL AG TGC

SSI

HCF: healthcare facilities. PEN: peniclllin. CIP: ciprofloxacin. LVX: levofloxacin. MFX: moxifloxacin. OFX: ofloxacin. FQ: CIP/LVX/MFX/OFX. FEP: cefepime. CTX: cefotaxime. CAZ: ceftazidime. CRO: ceftriaxone.CG:FEP/CTX/CAZ/CRO. MAC: macrolides (erythromycin/ clarithromycin). OXA: oxacillin. LNZ: linezolid. VAN: vancomycin. GEN: gentamicin. GHLR: gentamicin, high level resistance. TOB: tobramycin. AMK: amikacin. AG: GEN/TOB/AMK. AMP: Ampicillin. AMX: amoxicillin. AMC: amoxicillin/clavulanate; TZP: Piperacillin/tazobactam. ERT: ertapenem. MEM: meropenem. IPM: imipenem. COL: colistin. TGC: tigecycline.



The Portugese strategy


• National • AMR+HAI, voluntary participation • Inpatients+outpatients, all ages • Number of participating


ARSIP

Antibiotic resistance surveillance program in Portugal

Source of data Laboratory Clinical status Infection Dissemination Comparative data with other HCF



The Slovak strategy


Source of data Laboratory Clinical status Infection+colonisation Duplicates policy Yes Resistance definition EUCAST or CLSI Metrics and dissemination Prevalence. Yearly, pooled data Quality Assessment External, compulsory

• National • AMR, voluntary participation • Inpatients+outpatients, all ages • Number of participating labs: 40

SNARS

Slovak national antimicrobial resistance surveillance system




LVX or MFX

CTX or CRO

MAC


GEN or TOB


All AMP VAN GEH


All AMP or AMX


AG FQ COL


FEP or CAZ

TZP MEM or IPM

AG FQ COL


MEM or IPM

COL AG TGC SUL



ND4BB CO

MBACTE-M


The Spanish strategy

•

National

• HAI, voluntary participation


• N

umber of participating


EPINE

Estudio de prevalencia de las infecciones nosocom

iales en España

• N

ational •


• Inpatients+outpatients, all ages

• N



EN

VIN-UCI

Estudio nacional de vigilancia de Infección nososcom

ial en servicios de medicina

intensiva

• Regional



• N



IN

OZ

Infekzio nosocomialak zaintzeko eta

kontrolatzeko del País Vasco

• Regional


• Inpatients+outpatients, all ages

• N



SVE Canarias

Sistema de Vigilancia epidem

iológica de Canarias

• Regional

• AM



Num

ber of participating labs/hospitals: Not specified

VIN

CAT Vigilancia de les Infeccions nosocom

ials als hospitals de Cataluya

• Regional

• AM



Num

ber of participating labs/hospitals: N

ot specified

SVPCIPA

Sistema de vigilancia, prevención y control

de IRAS en principado de Asturias

• Regional

• AM



Num

ber of participating labs/hospitals: Not specified

PIRASOA

Programa Integral de Prevención, control de

las Infecciones relacionadas con la Asistencia Sanitaria y Uso apropiado de los

Antimicrobianos

• Regional

• AM



Num


ot specified

SVIN

Sistema de vigilancia nosocom

ial de Galicia

• Regional



• N



VIRAS

Vigilancia de las Infecciones relacionadas con la asistencia sanitaria de M

adrid



ND4BB CO

MBACTE-M


VIRAS EN

VIN-UCI


orbidities, severity score, length of stay, antibiotic use. Clinical outcom

es M

ortality M


ID,CI,UR. Yearly, individual HCF data

CLABSI VAP

CAUTI


onia. CAUTI: Catheter-associated urinary tract infections

ID: Incidence density. CI: Cumulative incidence. UR: Utilisation rate. HCF: Healthcare facilities

SSI: surgical site infection. PRE-op: PRE-operative checklist. CABG: Coronary artery bypass grafting. CVAL: cardiac valve replacem


y. COLO

: colon surgery. CSEC: caesarean section. HPRO

: hip prosthesis. KPRO: knee prosthesis. LAM

: laminectom

y.

SVIN

Risk factors Severity score M


ID,UR. Monthly, com

parative data with other HCF

CLABSI VAP


PRE-op Intervention CABG

CVAL CHO

L CO

LO

CSEC HPRO

KPRO

LAM

Dissemination

Yearly, individual HCF data

SSI

SVPCIPA

Metrics

ID, UR. Peri- operative checklist

PO

ST-op Intervention CABG

CVAL CHO

L CO

LO

CSEC HPRO

KPRO

LAM

Dissemination

Yearly, individual HCF data SSI

CLABSI VAP

CAUTI


ND4BB CO

MBACTE-M


VIN

CAT

Risk factors Com

orbidities, severity score, length of stay M

etrics ID,CI,UR.

CLABSI VAP

CAUTI

NN

IS Risk Index




PO


CVAL CHO

L CO

LO

CSEC HPRO

KPRO

LAM

SSI

Dissemination

Yearly, comparative data w

ith other HCF

PIRASOA


orbidities, severity score, length of stay, antibiotic use. Clinical outcom

es M

ortality M

etrics ID,CI,UR.

CLABSI VAP

CAUTI

NN

IS Risk Index



PRE+PO


CVAL CHO

L CO

LO

CSEC HPRO

KPRO

LAM

SSI

Dissemination

Quarterly, com

parative data with other

HCF

INO

S

Risk factors Com

orbidities, severity score Clinical outcom

es M

ortality M

etrics ID, UR.

CLABSI VAP

CAUTI


PRE-op Intervention CABG

CVAL CHO

L CO

LO

CSEC HPRO

KPRO

LAM

SSI

Dissemination

Individual HCF data



onia CAUTI: Catheter-associated urinary tract infections ID: Incidence density CI: Cum

ulative incidence UR: Utilisation rate HCF: Healthcare facilities SSI: surgical site infection PRE-op: PRE-operative checklist PO

ST-op: POST-operative

checklist CABG: Coronary artery bypass grafting CVAL: cardiac valve replacem

ent CHO

L: cholecystectomy

COLO

: colon surgery CSEC: caesarean section HPRO

: hip prosthesis KPRO

: knee prosthesis LAM

: laminectom

y



ENVIN-UCI



Streptococcus pneumoniae All PEN CTX or CRO

Staphylococcus aureus All OXA VAN

Enterococcus faecalis/ Enterococcus faecium All AMP VAN

Escherichia coli/ Klebsiella pneumoniae All CG FQ


TZP MEM or IPM

FQ COL

Source of data Laboratory Clinical status Infection+colonisation Resistance definition EUCAST+CLSI Risk factors Antibiotic use Metrics and dissemination Incidence density. Yearly, individual HCF data

PIRASOA

Source of data Laboratory Clinical status Infection+colonisation Duplicates policy Yes Resistance definition EUCAST+CLSI Risk factors Invasive procedures, antibiotic use Metrics and dissemination Incidence density. Quarterly, comparative data with other HCF



Enterococcus faecalis/ Enterococcus faecium Not specified VAN

Escherichia coli/ Klebsiella pneumoniae Blood CG

SVPCIPA

SVIN

VINCAT

Source of data Laboratory Clinical status Infection+colonisation Metrics and dissemination Incidence density. Yearly, individual HCF data

Source of data Laboratory Clinical status Infection Risk factors Antibiotic use Dissemination Monthly, comparative data with other HCF Quality Assessment Local

Source of data Laboratory Clinical status Infection+colonisation Duplicates policy Yes Risk factors Antibiotic use Dissemination Yearly, comparative data with other HCF

HCF: Healthcare facilities. PEN: peniclllin. FEP: cefepime. CTX: cefotaxime. CAZ: ceftazidime. CRO: ceftriaxone. CG:FEP/CTX/CAZ/CRO. OXA: oxacillin. VAN: vancomycin. AMP: Ampicillin. CIP: ciprofloxacin. LVX: levofloxacin. MFX: moxifloxacin. OFX: ofloxacin. FQ: CIP/LVX/MFX/OFX. TZP: Piperacillin/tazobactam. MEM: meropenem. IPM: imipenem. COL: colistin.



• National • AMR, voluntary participation • Inpatients and outpatients, all ages • Number of participating labs: 25

•

Source of data Laboratory Clinical status Infection+colonisation Resistance definition EUCAST Metrics and dissemination Prevalence. Yearly, pooled data. Quality Assessment External, compulsory

The Swedish strategy





CTX or CRO

MAC




AMP or AMX


AG FQ COL


TZP MEM or IPM

AG FQ COL


COL AG TGC SUL

SVEBAR

Swedish surveillance of antimicrobial resistance

SVEBAR

• National • AMR, voluntary participation • Number of participating labs: 24

RESNET

Annual resistance monitoring and quality control programme

Source of data Laboratory Resistance definition EUCAST Metrics and dissemination Prevalence. Yearly, pooled data.

RESNET



ND4BB CO

MBACTE-M


• N

ational •


• Inpatients and outpatients, all ages

• N

umber of participating labs: 19

•

The Swiss strategy


AN

RESIS Sw

iss centre for antibiotic resistance

• Regional

• AM


Inpatients and outpatients, all ages •

Num


ot specified •

: •

CA-M

RSA CA-M

RSA surveillance system

• N

ational •

HAI, voluntary participation •


Num


SW

ISSNO

SO

• Regional

• AM



Num


ot specified

HPCI

Hygiène hospitalière prévention et contrôle de l'infection

SWISSN

OSO

HPCI M


ID,CI. Not specified NN

IS Risk Index




POST-op

Intervention CABG

CVAL CHO

L CO

LO

CSEC HPRO

KPRO

LAM

Dissemination

Yearly, pooled data Q

uality Assessment

Local, com

pulsory

CLABSI

SSI

SSI: surgical site infection. POST-op: PO

ST-operative checklist. CABG: Coronary artery bypass grafting. CVAL: cardiac valve replacem


y. COLO

: colon

surgery. CSEC:

caesarean section.

HPRO:

hip prosthesis.

KPRO:

knee prosthesis.

LAM:

laminectom

y. CLABSI: Central line-associated bloodstream

infection. ID: Incidence density. CI: Cumulative incidence.



ANRESIS

CA-MRSA

Source of data Laboratory Clinical status Infection+colonisation Duplicates policy Yes Resistance definition EUCAST or CLSI Metrics and dissemination Prevalence. Yearly, pooled data Quality Assessment External voluntary

Source of data Charts Clinical status Infection+colonisation Resistance definition EUCAST Risk factors Invasive procedures, antibiotic use, comorbidities, previous hospitalisation, others (contact, travel, substance use, sexual preference) Metrics and dissemination % infections Pooled data

HPCI

Source of data Laboratory+charts Clinical status Infection+colonisation Duplicates policy Not specified Resistance definition EUCAST Metrics and dissemination CI, ID. Not specified




CTX or CRO

MAC




AMP or AMX


AG FQ COL


TZP MEM or IPM

AG FQ COL


COL AG TGC SUL



Staphylococcus aureus Blood OXA

Enterococcus faecalis/ Enterococcus faecium Blood VAN

Escherichia coli/ Klebsiella pneumoniae Blood CG ERT

MEM or IPM




ID: Incidence density: CI: Cumulative incidence. PEN: peniclllin. CIP: ciprofloxacin. LVX: levofloxacin. MFX: moxifloxacin. OFX: ofloxacin. FQ: CIP/LVX/MFX/OFX. FEP: cefepime. CTX: cefotaxime. CAZ: ceftazidime. CRO: ceftriaxone.CG:FEP/CTX/CAZ/CRO. MAC: macrolides (erythromycin/ clarithromycin). OXA: oxacillin. LNZ: linezolid. VAN: vancomycin. GEN: gentamicin. GHLR: gentamicin, high level resistance. TOB: tobramycin. AMK: amikacin. AG:GEN/TOB/AMK. AMP: Ampicillin. AMX: amoxicillin. AMC: amoxicillin/clavulanate; TZP: Piperacillin/tazobactam.. ERT: ertapenem. MEM: meropenem. IPM: imipenem. COL: colistin. TGC: tigecycline. SUL: sulbactam.



• Regional • AMR+HAI, voluntary participation • Inpatients and outpatients, all ages • Number of participating hospitals:

86 • :

•

The British strategy


WHAIP

Welsh healthcare associated infections programme

• Regional • AMR+HAI, voluntary participation • Inpatients, all ages • Number of participating

labs/hospitals: Not specified • :

•

HPS

Health protection Scotland

• Regional • AMR+HAI, voluntary participation • Laboratory , all ages • Number of participating hospitals:

26

HISC/HPA

Healthcare infection centre/healthcare protection agency

• Regional • AMR+HAI, voluntary participation • Laboratory, all ages • Number of participating

labs/hospitals: Not specified • : •

PHE

Public health England


ND4BB CO

MBACTE-M


PHE

NN

IS Risk Index




PO


CVAL CHO

L CO

LO

CSEC HPRO

KPRO

LAM

Dissemination

Mixed, individual HCF data



onia CAUTI: Catheter-associated urinary tract infections ID: Incidence density UR: Utilisation rate HCF: Healthcare facilities SSI: surgical site infection PRE-op: PRE-operative checklist PO

ST-op: POST-operative

checklist CABG: Coronary artery bypass grafting CVAL: cardiac valve replacem

ent CHO

L: cholecystectomy

COLO

: colon surgery CSEC: caesarean section HPRO

: hip prosthesis KPRO

: knee prosthesis LAM

: laminectom

y

WHAIP

Metrics

ID,UR N

NIS Risk Index



PRE+PO


CVAL CHO

L CO

LO

CSEC HPRO

KPRO

LAM

Dissemination

Monthly, com

parative data with other

HCF

HPS

Risk factors Com

orbidities, severity score Clinical outcom

es M

ortality, length of stay M

etrics ID,UR N

NIS Risk Index




PRE+PO


CVAL CHO

L CO

LO

CSEC HPRO

KPRO

LAM

Dissemination

Quarterly, com

parative data with

other HCF Q

uality Assessment

External

HISC/HPA

NN

IS Risk Index




PRE+PO


CVAL CHO

L CO

LO

CSEC HPRO

KPRO

LAM

Dissemination

Pooled data

CLABSI VAP

CAUTI

SSI

SSI

SSI SSI

CLABSI VAP

CAUTI



WHAIP

PHE

Source of data Laboratory Clinical status Infection+colonisation Metrics and dissemination CI. Monthly, comparative data with other HCF

Source of data Charts Clinical status Infection+colonisation Duplicates policy Yes Risk factors Invasive procedures, antibiotic use Metrics and dissemination CI,DI, Prevalence. Mixed, individual HCF data

HPS

HISC/HPA

Source of data Charts Clinical status Infection+colonisation Duplicates policy Yes Risk factors Antibiotic use Metrics and dissemination CI, Prevalence. Quarterly, comparative data with other HCF Quality Assessment External

Source of data Laboratory Dissemination Pooled data Quality Assessment Local




Blood, respiratory PEN

LVX or MFX

CTX or CRO

MAC

Staphylococcus aureus Blood, respiratory OXA FQ LNZ VAN


Blood, respiratory AMP VAN GEH


AMP or AMX


AG FQ COL


TZP MEM or IPM

AG FQ COL


COL AG TGC


Staphylococcus aureus Blood

OXA


Blood VAN


Streptococcus pneumoniae Not specified PEN


Enterococcus faecalis/ Enterococcus faecium Blood VAN GEH



Enterococcus faecalis/ Enterococcus faecium Blood GEN or

TOB

CI: Cumulative incidence. ID: Incidence density HCF: Healthcare facilities.PEN: peniclllin. CIP: ciprofloxacin. LVX: levofloxacin. MFX: moxifloxacin. OFX: ofloxacin. FQ: CIP/LVX/MFX/OFX. FEP: cefepime. CTX: cefotaxime. CAZ: ceftazidime. CRO: ceftriaxone.CG:FEP/CTX/CAZ/CRO. MAC: macrolides (erythromycin/ clarithromycin). OXA: oxacillin. LNZ: linezolid. VAN: vancomycin. GEN: gentamicin. GHLR: gentamicin, high level resistance. TOB: tobramycin. AMK: amikacin. AG:GEN/TOB/AMK. AMP: Ampicillin. AMX: amoxicillin. AMC: amoxicillin/clavulanate; TZP: Piperacillin/tazobactam.. ERT: ertapenem. MEM: meropenem. IPM: imipenem. COL: colistin. TGC: tigecycline. SUL: sulbactam.



References

1. Cassini A, Plachouras D, Eckmanns T, et al. Burden of Six Healthcare-Associated Infections on European Population Health: Estimating Incidence-Based Disability-Adjusted Life Years through a Population Prevalence-Based Modelling Study. PLoS Med. 2016 Oct 18;13(10):e1002150.

2. European com-mission. Action plan against the rising threats from Antimicrobial Resistance. Communication from the commission to the European parliament and the council. Brussels, September 2011. Available at: http://ec.europa.eu/dgs/health_consumer/docs/communication_amr_2011_748_es.pdf

3. ECDC/EMEA Joint technical report. The bacterial challenge: time to react. ref. EMEA/576176/2009. Stockholm, September 2009. ISBN 978-92-9193-193-4. doi 10.2900/2518.

4. Zingg W, Holmes A, Dettenkofer M, et al. Hospital organisation, management, and structure for prevention of health-care-associated infection: a systematic review and expert consensus. Lancet Infect Dis. 2015 Feb;15(2):212-24. doi: 10.1016/S1473-3099(14)70854-0. Epub 2014 Nov 11.

5. Haustein T, Gastmeier P, Holmes A, Lucet JC, Shannon RP, Pittet D, Harbarth S. Use of benchmarking and public reporting for infection control in four high-income countries. Lancet Infect Dis 2011;11:471-81.

6. European Centre for Disease Prevention and Control: Annual Epidemiological Report on Communicable Diseases in Europe 2008. Stockholm, European Centre for Disease Prevention and Control, 2008. Available at: http://ecdc.europa.eu/en/publications/publications/0812_sur_annual_epidemiological_report_2008.pdf.

7. Council Recommendation of 9 June 2009 on patient safety, including the prevention and control of healthcare associated infections (2009/C 151/01). Available at: http://ec.europa.eu/health/patient_safety/docs/council_2009_en.pdf.

8. Shamseer L, Moher D, Clarke M et al, PRISMA-P Group. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ 2015;349:g7647 doi: 10.1136/bmj.g7647.

9. Blot K, Bergs J, Vogelaers D, Blot S, Vandijck D. Prevention of central line-associated bloodstream infections through quality improvement interventions: a systematic review and meta-analysis. Clin Infect Dis. 2014 Jul 1;59(1):96-105.

10. Tanner J, Padley W, Assadian O, Leaper D, Kiernan M, Edmiston C. Do surgical care bundles reduce the risk of surgical site infections in patients undergoing colorectal surgery? A systematic review and cohort meta-analysis of 8,515 patients. Surgery. 2015 Jul;158(1):66-77.

11. Helmick RA, Knofsky ML, Braxton CC, Subramanian A, Byers P, Lan CK, Awad SS. Mandated self-reporting of ventilator-associated pneumonia bundle and catheter-related bloodstream infection bundle compliance and infection rates. JAMA Surg. 2014 Oct;149(10):1003-7.

12. Zarb P, Coignard B, Griskeviciene J, Muller A, Vankerckhoven V, Weist K, Goossens M, Vaerenberg S, Hopkins S, Catry B, Monnet D, Goossens H, Suetens C; National Contact Points for the ECDC pilot point prevalence survey.; Hospital Contact Points for the ECDC pilot point prevalence survey. The European Centre for Disease Prevention and Control (ECDC) pilot point prevalence survey of healthcare-associated infections and antimicrobial use. Euro Surveill. 2012 Nov 15;17(46). pii: 20316.

13. de Kraker ME, Stewardson AJ, Harbarth S. Will 10 Million People Die a Year due to Antimicrobial Resistance by 2050? PLoS Med. 2016 Nov 29;13(11):e1002184.

14. van Mourik MS, Troelstra A, van Solinge WW, Moons KG, Bonten MJ. Automated surveillance for healthcare-associated infections: opportunities for improvement. Clin Infect Dis. 2013 Jul;57(1):85-93.



3. A systematic review of SURVeillance programs for Antimicrobial resistance In Livestock and meat thereof in the European Union (SURVAIL) Authors

Remco Schrijver, Jesús Rodríguez-Baño, Nithya Babu Rajendran, Evelina Tacconelli, Andreas

Voss

Introduction

Antibiotics usage in animal production has been associated with resistance in humans,

although bacteria and antibiotics of veterinary and human interest differ deeply. Depending

on the aim, veterinary surveillance programmes may not necessarily include bacteria for

human interest, though such information might be very valuable. The “one-health concept”

clearly underlines the importance of connecting human and animal data on antibiotic

resistance to antibiotics. However at the moment, to the best of our knowledge, there is no

comprehensive information on this connection.

The aim of this study was to describe national and international surveillance programs and

networks collecting multi-annual data on antimicrobial resistance of bacterial isolates from

livestock and meat and compare the antibiotics and bacteria monitored with the antibiotics

and bacteria relevant for human health.

Materials and Methods

Surveillance systems including data from livestock and meat were identified through

systematic search of peer-reviewed (PubMed, EMBASE and Scopus) and grey literature

(Google search engine and targeted websites of public health institutions and scientific

societies). The following terms were used for the searches: “antimicrobial resistance” or

“antimicrobial susceptibility” combined with “livestock”, “cattle”, “bulls”, “calves”, “veal

calves”, “pigs”, “fatteners”, “poultry” (“chicken and “turkey”), “broilers” and geographical

(Europe). Time period was limited to the last 10 years. A three-step screening strategy was

used: 1. text words contained in the title, abstract and the index (MESH) terms in PubMed

along with title searches; 2. keywords and index terms across all other included databases;

and 3. The reference lists of all identified reports and articles were searched for additional

studies. No language restriction was applied. Additionally, data was obtained through

consulation with national authorities in European Union (EU) member states (MS) or



representatives of national as well as European organisations active in AMR recording in

animals and food.

Results

International AMR monitoring programmes in Europe

Table 1 summarises the characterisitcs of the following international AMR surveillance

systems for animals and food.

• Harmonised monitoring and reporting of AMR in zoonotic and commensal bacteria: an

initiative of the European commission which mandates and recommends the surveillance of

specific bacterial species and antibiotic combinations in its member states under the

Decision 2013/652/EU.

• EASSA, European Antimicrobial Susceptibility Surveillance in Animals: a voluntary

programme – coordinated by the Centre Européen d’Etudes pour la Santé Animale (CEESA)-

examining the antimicrobial susceptibility of zoonotic and commensal bacteria in healthy

food animals.

• Vetpath: a voluntary programme, coordinated by CEESA, examining the antimicrobial

susceptibility of disease-causing bacterial pathogens in animals.

National antimicrobial monitoring programmes

Besides the mandatory AMR reporting, several MS have undertaken other AMR surveillance

activities, particularly for animal bacteria. Table 2 presents the characteristics of national

antimicrobial monitoring programmes in Europe, including thoss which adhere to mandatory

EU monitoring by Decision 2013/652/EU (Figure 1, Table 2).



Table 1. International antimicrobial-resistance monitoring programmes in Europe Programme Target bacteria Animals and

derived meat Origin of samples

Susceptibility tests

Breakpoints Laboratories

Harmonised monitoring and reporting of AMR in EU

Salmonella spp Campylobacter jejuni Campylobacter coli Escherichia coli Enterococcus faecalis Enterococcus. faecium ESBL- or AmpC- or carbapenemase-producing Salmonella spp. and E. coli

Bovines, pigs, poultry

(broilers, laying hens,

fattening turkeys)

farm, slaughterhouse,

retail

dilution tests, diffusion tests

epidemiological cutoff values

(ECOFFs)

National laboratories

EASSA

beef cattle, slaughter pigs,

broiler chickens

intestinal samples taken at

slaughter microdilution

clinical breakpoints

(CLSI) or epidemiological

breakpoints (EFSA/EUCAST)

National laboratories

Salmonella spp. Campylobacter Enterococcus spp E. coli

VetPath

Staphylococcus. aureus E. coli Pasteurella multocida Mannheimia haemolytica Histophilus somni Actinobacillus pleuropneumoniae Haemophilus parasuis Bordetella bronchiseptica Streptococcus suis Streptococcus uberis

cattle, pigs

lung samples or nasopharyngeal

/nasal swabs, mastitis samples

microdilution clinical

breakpoints (CLSI)

Central laboratory

Figure 1A. European countries with national antimicrobial-resistance monitoring programmes in

animals and food


ND4BB CO

MBACTE-M


Figure 1B. Main characteristics of national antim

icrobial-resistance monitoring program

mes in Europe

Austria

Surveillance programm

e AURES Target bacteria, anim

als and food In accordance w

ith EU regulations

Suceptibility tests and read-outs M

icrodilution. ECOFF follow

ing EUCAST standards

Belgium

Surveillance institution CO

DA-CERVA, Veterinary and agrochem

ical research centre Target bacteria Salm

onella spp., C. jejuni, C. coli,E. coli m

ethicillin-resistant S. aureus (MRSA),

comm

ensal enterococci Target anim

als and food Cattle, pigs, poultry and m

eat and meat

products Suceptibility tests and read-outs M



Denmark


e DANM

AP, Danish integrated antim

icrobial resistance monitoring and

research programm

e Target bacteria, anim


ith EU regulations


icrodilution. ECOFF and EUCAST clinical

breakpoints

Germany

1. Surveillance programm

e DARLink, Germ

an antimicrobial

situation in the food chain Target bacteria Salm

onella spp. Cam

pylobacter spp. verotoxin-form

ing E. coli(VTEC) comm

ensal E. coli M

RSA Suceptibility tests and read-outs M

icrodilution. ECOFF

2. Surveillance programm

e GERM

Vet, German national

monitoring program

me

Target bacteria E. coli, Klebsiella pneum

oniae E. faecalis, E. faecium

, S. aureus Streptococcus agalactiae, Streptococcus dysgalactiae, S. uberis, M

. haemolytica

Pasteurella haemolytica, A. pleuropneum

oniae B. bronchiseptica Target anim

als and food Cattle, pigs, chickens and non-m

eat producing anim

als (clinical samples)


icrodilution. CLSI clinical breakpoints

Finland


e FINRES-Vet, Finnish veterinary antim

icrobial resistance m

onitoring and consumption of

antimicrobial agents

Target bacteria, animals and food

In accordance with EU

regulations. Veterninary pathogens (from

clinical samples) additional

Suceptibility tests and read-outs Dilution. ECO

FF

France


e RESAPATH, French surveillance netw

ork for antim

icrobial resistance in pathogenic bacteria of anim

al origin Target bacteria Arcanobacterium

, Corynebacterium spp.

Salmonella spp., Klebsiella spp.

Pasteurella spp., Pseudomonas spp.

E. coli, Enterococcus spp. Streptococcus spp., S. aureus Staphylococcus hyicus Actinobacillus pleuropneum

oniae Clostridum

perfringens O

rnithobacterium tracheale

Target animals and food

Cattle, pigs, and poultry (clinical samples)

Suceptibility tests and read-outs Disk diffusuion. Resistance follow

ing antibiogram

comm

ittee of the French society of m

icrobiology (CA-SFM) guidelines.


ND4BB CO

MBACTE-M


Figure 1C. Main characteristics of national antim

icrobial-resistance monitoring program

mes in Europe

Netherlands


e M

ARAN, M

onitoring of antim

icrobial resistance and antibiotic usage in anim

als in Netherlands Target bacteria ESBL- producing Salm

onella spp. and E. coli, carbapenem

ase-producing Enterobacteriaceae, M

RSA, colistin-resistant E. coli Suceptibility tests and read-outs M



Norw

ay Surveillance program

me

NORM

-Vet Target bacteria, anim


ith EU regulations




Spain Surveillance program

me

VAV, Veterinary Antim

icrobial Resistance Surveillance Netw

ork Target bacteria Salm

onella, Campylobacter,

E. coli, enterococci,S.aureus Target anim

als and food Healthy and infected anim

als Suceptibility tests and read-outs M

icrodilution and agar diffusion.

Sweden


e SVARM

, Swedish veterinary

antimicrobial resistance m

onitoring program

me

Target bacteria Salm


E. coli, enterococci, carbapenemase-producing

Enterobacteriaceae, Pasteurella spp., A. pleuropneum

oniae, Brachyspira hyodysenteriae, M

. haemolytica, Bibersteinia trehalosi

Target animals and food

Healthy and infected farm anim

als Suceptibility tests and read-outs M



United kingdom

Surveillance institution VARSS, Veterinary antibiotic resistance and sales surveillance program

me

Target bacteria Salm


E. coli, enterococci, P. m

ultocida, Histophilus somnus,

A. pleuropneumonia, Trueperella pyogenes,

M. haem

olytica, B. trehalosi, S. dysgalactiae, S. uberis, S. aureus, Klebsiella pneum

oniae, Pseudom

onas aeruginosa, Brachyspira hyodysenteriae Target anim

als and food Cattle, pigs, poultry, and sheeps (healthy and infected) Suceptibility tests and read-outs M

icrodilution and agar diffusion. ECOFF and

human clinical breakpoints


ND4BB CO

MBACTE-M


Table 2. Microorganism

s tested in 15 antimicrobial-resistance surveillance program

mes in livestock

Gram-positive bacteria

Resistance risk for humans

Surveillance in Geographical areas

Cattles Pigs

Poultry Food (m

eat) Staphylococcus aureus

Methicillin resistance (M

RSA); vancomycin-interm

ediate resistance and resistance (VISA/VRSA)

Yes Yes

Yes Yes

EU,DE, FI, SE, UK

Enterococcus faecalis Vancom

ycin resistance (VRE) Yes

DE

Enterococcus faecium

Yes

DE


Penicillin resistance

Streptococcus suis

EU, UK

Streptococcus agalactiae

Yes

DE, FI

Streptococcus uberis

Yes

EU, DE, FR, UK

Streptococcus dysgalactiae

Yes

DE, FI, FR, UK

Gram-negative bacteria

Resistance risk for humans

Surveillance in Geographical areas

Cattles Pigs

Poultry Food (m

eat)


Ceftazidime and carbapenem

Actinobacillus pleuropneum

oniae

Yes

EU,DE, SE

Bordetella bronchiseptica

Yes

Yes

EU

Campylobacter

Fluroquinolone and macrolide resistance

Yes Yes

Yes Yes

EU

Escherichia coli ESBL (third-generation cephalosporin resistance); carbapenem

resistance; ciprofloxacine resistance

Yes Yes

Yes Yes

EU,DE, FI, FR, SE

Haemophilus parasuis

Yes

EU

Histophilus somnus

Yes

EU

Klebsiella ESBL (third-generation cephalosporin resistance); carbapenem

resistance

Yes

DE, FR

Mannheim

ia haemolytica

Yes

EU, DE, FR

Pasteurella haemolytica

Yes

DE

Pasteurella multocida

Yes

Yes

EU,DE, FR, SE, UK


Carbapenem resistance

Salmonella

ESBL (third-generation cephalosporin resistance)

EU, FR


ND4BB CO

MBACTE-M


Table 3. Antibiotics included in 15 antimicrobial-resistance surveillance program

mes in livestock

ATC Codes ATC Vet codes

Therapeutic group Antibiotics intended for veterinary use (ATC Vet)

Antibiotics intended for human

use (ATC) Antibiotics in veterinary/food

surveillance programm

es Geographical areas

J01CA Q

J01CA Penicillins w

ith extended spectrum

Ampicillin

Ampicillin

Ampicillin

EU,DE, FI, FR, SE, UK Am

oxicillin Am

oxicillin Am

oxicillin EU,FR,

Penicillin

Penicillin EU,DE, FI, SE, UK

Temocillin

Temocillin

Temocillin

EU

Oxacillin

Oxacillin

FI

J01D Q

J01D

Cephalosporin 1st generation

Cefalexin Cefalexin

Cefalexin FR

Cefalotin

Cefalotin FI, FR, SE

Cephalosporin 2nd generation

Cefoxitin

Cefoxitin EU, FI, FR

Cefuroxim

e Cefuroxim

e FR

Cephalosporin 3nd generation

Cefoperazone

Cefoperazone DE,FR

Cefotaxime

Cefotaxime

Cefotaxime

EU,DE, FI, SE

Cefpodoxime

Cefpodoxime

UK

Ceftazidime

Ceftazidime

FR Ceftiofur

Ceftiofur

EU,DE, FR, SE

Cephalosporin 4th generation

Cefquinome

Cefquinom

e DE,FR

Cefepim

e Cefepim

e EU, FR

Ertapenem

Ertapenem

EU, FR

Im

ipenem

Imipenem

EU

M

eropenem

Meropenem

EU

J01GB Q

J01G Am

inoglycosides Gentam

icin

Gentamicin

EU, FI, FR, SE

Kanamycin

Kanamycin

EU, FI, FR, SE Neom

ycin

Neomycin

FI, FR, SE, UK

J01A Q

01A Tetracyclines

Doxycyclin Doxycyclin

Doxycyclin DE, FR, UK

Tetracycline Tetracycline

Tetracycline EU,DE, FI, FR, SE, UK

Tigecycline

Tigecycline EU

J01B Q

01B Am

phenicols Chloram

phenicol

Chloramphenicol

EU, FI, FR, SE Florfenicol

Florfenicol

EU,DE, FI, FR, SE, UK

J01E Q

J01E Trim

ethoprim derivatives

Trimethoprim

Trimethoprim

EU, FI, FR, SE

Sulfamethoxazole and

trimethoprim

Sulfamethoxazole

EU,DE, FI, SE, UK

J01FA Q

J01F M

acrolides

Apramycin

Apramycin

Apramycin

FR, UK Azithrom

ycin Azithrom

ycin Azithrom

ycin EU

Erthromycin

Erthromycin

Erthromycin

FI, FR, SE, UK Pristinam

ycin

Pristinamycin

FR Streptom

ycin Streptom

ycin Streptom

ycin EU,DE, FI, FR, SE, UK

Spiramycin

Spiramycin

Spiramycin

FR Tulathrom

ycin Tulathrom

ycin Tulathrom

ycin EU,DE

Tylosin

Tylosin FR, UK


ND4BB CO

MBACTE-M


J01FF Q

J01F Lincosam

ides

Clindamycin

Clindamycin

EU, FI, SE Lincom

ycin Lincom

ycin Lincom

ycin FR, UK

Pirilimycin

Pirilim

ycin DE

J01FG02 Q

J01FG02 Streptogram

ins Q

uinupristin/dalfopristin Q

uinupristin/dalfopristin Q

uinupristin/dalfopristin EU,DE

J01MA

QJ01M

A Fluoroquinolones

Ciprofloxacin Ciprofloxacin

Ciprofloxacin EU,FI,SE

Danofloxacin

Danofloxacin EU, FR

Difloxacin

Difloxacin FR

Enrofloxacin

Enrofloxacin EU,DE, FR, SE, UK

Levofloxacin

Levofloxacin

Marbofloxacin

M

arbofloxacin EU,DE, FR

J01MB

QJ01M

O

ther quinolones Flum

equin

Flumequin

FR Nalidixic acid

Nalidixic acid

EU,DE, FI, FR, SE

J01XB Q

J01XB Polym

yxins Colistin

Colistin

EU,SE

Vancomycin

Vancomycin

EU,DE J01XC01

QJ01XC01

Steriod antimicrobials

Fusidic acid Fusidic acid

Fusidic acid EU, FI, SE

J01XX04

Spectinom

ycin

Spectinomycin

EU,DE, FR, UK

Pleuorom

utilins Tiam

ulin

Tiamulin

EU,DE J01XX08

QJ01XX08

Other antim

icrobials Linezolid

Linezolid Linezolid

EU J04AM

Antibioitcs specific for TB

Rifampicin

Rifampicin

EU, FR D06AX09

QD06AX09

Topical use M

upirocin M

upirocin M

upirocin EU



References

1. A. de Jong, V. Thomas, S. Simjee, K.Godinho, B. Schiessl, U.Klein, P.Butty, M.Valle, H. Marion and T. R. Shryock. Pan-European monitoring of susceptibility to human-use antimicrobial agents in enteric bacteria isolated from healthy food-producing animals. Antimicrob Chemother 2012; 67: 638–651

2. A de Jong et al; Pan-European resistance monitoring programmes encompassing food-borne bacteria and target pathogens of food-producing and companion animals. International Journal of Antimicrobial Agents 41 (2013) 403– 409

3. A de Jong et al; Antimicrobial susceptibility monitoring of respiratory tract pathogens isolated from diseased cattle and pigs across Europe: The VetPath study. Veterinary Microbiology 172 (2014) 202–215 (VetPath Study)

4. A. de Jong, H. Moyaert, and S. Simjee. Antimicrobial susceptibility testing of foodborne bacteria related to national and international resistance-monitoring programmes. In: Antimicrobial Food Packaging; chapter 9; 117 ev. 2016. ISBN 978-0-12-800723-5

5. ARSIA, 2013. Antibiogrammes. Rapport d’activité et résultats de l’ARSIA. ARSIA esbl. http://www.arsia.be/?page_id=3991#

6. AURES 2014. Austrian report on antimicrobial resistance . http://www.ages.at/en/topics/ages-topics/antibiotika-resistenzen/aures-berichte/#downloads

7. BVL, 2016. GERMVET. Resistenzsituation bei klinisch wichtigen tierpathogenen Bakterien 2012/2013. ISBN 978-3-319-31696-3. http://www.bvl.bund.de/DE/09_Untersuchungen/01_Aufgaben/03_Nationales%20Resistenz-Monitoring/untersuchungen_NatResistenzmonitoring_node.html

8. DARLink; German Antimicrobial Resistance Situation in the Food Chain –2009 Federal Institute for Risk Assessment (2013) ISBN 3-938163-98-4. http://www.bfr.bund.de/cm/350/german-antimicrobial-resistance-situation-in-the-food-chain-2009.pdf

9. DGZ, Diergezondheidszorg Vlaanderen. Antibiotica resistentie evolutie 2012-2015. http://www.dgz.be/publicatie/antibioticaresistentie-evolutie-2012-2015

10. ECDC/EMEA JOINT TECHNICAL REPORT. 2009 The bacterial challenge: time to react A call to narrow the gap between multidrug-resistant bacteria in the EU and the development of new antibacterial agents. EMEA doc. ref. EMEA/576176/2009 ISBN 978-92-9193-193-4. doi 10.2900/2518

11. ECDC/EFSA/EMA, 2015. ECDC (European Centre for Disease Prevention and Control), EFSA (European Food Safety Authority) and EMA (European Medicines Agency). 2015. ECDC/EFSA/EMA first joint report on the integrated analysis of the consumption of antimicrobial agents and occurrence of antimicrobial resistance in bacteria from humans and food-producing animals. Stockholm/Parma/London: ECDC/EFSA/EMA, 2015. EFSA Journal 2015;13(1):4006, 114 pp. doi:10.2903/j.efsa.2015.4006

12. EFSA, 2012. Technical specifications on the harmonised monitoring and reporting of antimicrobial resistance in Salmonella, Campylobacter and indicator Escherichia coli and Enterococcus spp. bacteria transmitted through food EFSA Journal 2012;10(6):2742

13. EFSA (European Food Safety Authority) and ECDC (European Centre for Disease Prevention and Control), 2016. The European Union summary report on antimicrobial resistance in zoonotic and indicator bacteria from humans, animals and food in 2014. EFSA Journal 2016;14(2):4380, 207 pp. doi:10.2903/j.efsa.2016.4380

14. El Garch F., De Jong A., Simjee S., Moyaer H, Klein U., Ludwig C., Marion H., Haag-Diergarten S., Richard-Mazet A, Thomas V, Siegwart E. Monitoring of antimicrobial susceptibility of respiratory tract pathogens isolated from diseased cattle and pigs across Europe, 2009–2012: VetPath results .Vet. Microbiol. (2016), http://dx.doi.org/10.1016/j.vetmic.2016.04.009

15. FAVV-AFSCA, 2015. Trends in 2012-2013. Report on zoonotic agents in Belgium. http://www.coda-cerva.be/images/pdf/Report%20on%20Zoonotic%20agents%20in%20Belgium_2012_2013.pdf

16. FINRES-Vet 2007-2009, Finnish Veterinary Antimicrobial Resistance Monitoring and Consumption of Antimicrobial Agents, Finnish Food Safety Authority Evira, Helsinki, Finland, ISSN 1797-299X. https://www.evira.fi/en/animals/animal-health-and-diseases/animal-medication/monitoring-of-antibiotic-resistance/

17. FVO, 2016a. Final report of an audit carried out in Denmark from 15 September to 22 September in order to evaluate the monitoring and reporting of antimicrobial resistance in zoonotic and



commensal bacteria in certain foodproducing animal populations and food. DG(SANTE) 2015-7383 – MR.

18. FVO, 2016b. Final report of an audit carried out in Denmark from 10 November to 20 November in order to evaluate the monitoring and reporting of antimicrobial resistance in zoonotic and commensal bacteria in certain foodproducing animal populations and food. DG(SANTE) 2015-7404 – MR.

19. GERMAP, Antibiotika-Resistenz und -Verbrauch. Bundesamt für Verbraucherschutz und Lebensmittelsicherheit; 1st ed.(2011). ISBN 978-3-00-031622. http://www.bvl.bund.de/DE/09_Untersuchungen/01_Aufgaben/03_Nationales%20Resistenz-Monitoring/untersuchungen_NatResistenzmonitoring_node.html

20. K. Supre et al; Antimicrobial susceptibility and distribution of inhibition zone diameters of bovine mastitis pathogens in Flanders, Belgium. Veterinary Microbiology 171 (2014) 374–381

21. Lourdes Garcia-Migura et al; Antimicrobial resistance of zoonotic and commensal bacteria in Europe: The missing link between consumption and resistance in veterinary medicine. Veterinary Microbiology 170 (2014) 1–9

22. MARAN 2014. Monitoring of Antimicrobial Resistance and Antibiotic Usage in Animals in the Netherlands in 2014. http://www.wageningenur.nl/upload_mm/2/2/2/0ab4b3f5-1cf0-42e7-a460-d67136870ae5_NethmapMaran2015.pdf

23. Miguel A. Moreno, Lucas Dominguez, Tirushet Teshager, Inmaculada A. Herrero, M. Concepcion Porrero. The VAV Network Antibiotic resistance monitoring: the Spanish programme. Int J Antimicrobial Agents 14 (2000) 285–290

24. Moyaert H, De Jong A, Simjee S, Thomas V. Antimicrobial resistance monitoring projects for zoonotic and indicator bacteria of animal origin: Common aspects and differences between EASSA and EFSA. Veterinary Microbiology 171 (2014) 279–283

25. NORM/NORM-VET 2013. Usage of Antimicrobial Agents and Occurrence of Antimicrobial Resistance in Norway. Tromsø / Oslo 2014. ISSN:1502-2307 (print) / 1890-9965 (electronic). http://www.vetinst.no/Publikasjoner/NORM-NORM-VET

26. Noyes NR et al. Mannheimia haemolytica in Feedlot Cattle: Prevalence of Recovery and Associations with Antimicrobial Use, Resistance, and Health Outcomes. J Vet Intern Med 2015;29:705–713 (USA paper)

27. P. Silley, S. Simjee , S. Schwarz. Surveillance and monitoring of antimicrobial resistance and antibiotic consumption in humans and animals. Rev. sci. tech. Off. int. Epiz., 2012, 31 (1), 105-120

28. Peter Silley, Anno de Jong, Shabbir Simjee, Valérie Thomas. Harmonisation of resistance monitoring programmes in veterinary medicine: an urgent need in the EU? International Journal of Antimicrobial Agents 37 (2011) 504–512

29. Rene Hendriksen et al; Prevalence of antimicrobial resistance among bacterial pathogens isolated from cattle in different European countries: 2002–2004 Acta Veterinaria Scandinavica 2008, 50:28 (ARBAO-II Study)

30. RESAPATH, 2016. French surveillance network for antimicrobial resistance in pathogenic bacteria of animal origin. Annual Report 2014. ANSES.

31. Rui Figueiredo et al; Antimicrobial Resistance and Extended-Spectrum b-Lactamases of Salmonella enterica Serotypes Isolated from Livestock and Processed Food in Portugal: An Update. Foodborne pathogens and disease Volume 12, Number 2, 201

32. Silley P, De Jong A, Simjee S, Thomas V. 2011. Harmonisation of resistance monitoring programmes in veterinary medicine: an urgent need in the EU? International Journal of Antimicrobial Agents 37 (2011) 504–512

33. Stefan Schwarz. The BfT-GermVet monitoring program – Aims and basics. Berl.Münch.Tierärztl.Wochenschr. 120, Heft 9/10, 357–362 (2007)

34. Strauss R, Muchl R, Metz-Gercek S, Sagl M, Allerberger F, Hrabcik H, Mittermayer H. AURES – the first Austrian report on antimicrobial resistance – perspective of the human sector. Euro Surveill. 2007;12(50):pii=3329. Available online: http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=3329

35. SVARM 2014. Consumption of antibiotics and occurrence of antibiotic resistance in Sweden. Solna/Uppsala ISSN 1650-6332. http://www.sva.se/om-sva/publikationer/antibiotikaresistens?lid=32744



36. V.Thomas, A. de Jong, H. Moyaert, S. Simjee, F.El Garch, I.Morrissey, H.Marion, M. Vallé. Antimicrobial susceptibility monitoring of mastitis pathogens isolated from acute cases of clinical mastitis in dairy cows across Europe:VetPath results. International Journal of Antimicrobial Agents 46 (2015) 13–20

37. UK-VARSS 2014. Uk Veterinary Antibiotic Resistance and Sales Surveillance Report. http://webarchive.nationalarchives.gov.uk/20140909112428/http://www.vmd.defra.gov.uk/pharm/antibiotic_salesdata.aspx

38. Urdahl AM, Bergsjø B, Hofshagen M, Nordström M, Lium B. The surveillance programme for methicillin resistant Staphylococcus aureus in pigs in Norway in 2014. Surveillance programmes for terrestrial and aquatic animals in Norway. Annual report 2014. Oslo: Norwegian Veterinary Institute 2014

39. VAV 2005; Veterinary monitoring of antimicrobial resistance in Spain. 12th Report. 2005. https://www.visavet.es/en/research/networks/vav.php



4. EpideMiology and control measures of outBreaks due to Antibiotic-

Resistant orGanisms in EurOpe (EMBARGO): a systematic review protocol

Authors

Nithya Babu Rajendran, Beryl Primrose Gladstone, Jesús Rodríguez-Baño, Frangiscos Sifakis, Andreas

Voss, Yehuda Carmeli, Francesco Robert Burkert, Panagiota Gkolia, and Evelina Tacconelli

(Study protocol published in BMJ Open 2016)

Introduction

The genetic capabilities of bacteria and indiscriminate use of antibiotics have resulted in the wide-

spread development of resistance, hindering the effectiveness of antibiotic therapy (Wright, 2007,

Davies and Davies, 2010, Tacconelli et al., 2009, Brown and Wright; 2016, Schroeder et al,2016).

Notably, resistance to single antibiotics has further progressed into multi-drug resistance which

advantageously protects bacterial pathogens against several commonly used therapeutic agents.

Multidrug resistances are rapidly evolving in several bacterial species: most predominant and

difficult-to-deal-with multi-drug resistant (MDR) organisms include methicillin-resistant

Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), extended-spectrum beta-

lactamase (ESBL)-producing Escherichia coli, and MDR-Pseudomonas aeruginosa, Acinetobacter

baumannii and Klebsiella pneumoniae (Nikaido, 2009, Alekshun and Levi, 2007, Munita et al., 2015,

McGowan, 2006).

In the 2011-2012 point-prevalence survey conducted by the European Centre for Disease Prevention

and Control (ECDC), methicillin resistance was reported in 41% of invasive S. aureus isolates,

vancomycin resistance in 10% of enterococci isolates, third-generation cephalosporin resistance in

33% of all Enterobacteriaceae isolates, and carbapenem resistance in 8% of Enterobacteriaceae, 32%

of P. aeruginosa, and 81% of A. baumannii isolates (ECDC, 2013). Mortality from antimicrobial

resistance was estimated at 50,000 deaths per year in the US and Europe alone (Teilannt et al.,

2015).

A well-recognized tool in the strategy to contain antibiotic resistance is surveillance (Williams and

Heymann, 1998, Williams and Ryan, 1998, Roca et al., 2015, Grundmann et al., 2011).Based on the

information gathered, surveillance data on antimicrobial resistance drive clinical decision making on

empiric therapy and infection prevention policy (O'Brien and Stelling, 2011). Overall, surveillance

enables improved patient outcome at the local level, while guiding public health policy-making and

interventions at the national level, and helps identify emerging threats on a global scale.



The objective of the systematic review was to systematically review the past and ongoing outbreaks

of target antimicrobial resistant bacteria (ARB) in order to map and characterise the epidemiological

aspects of outbreaks due to ARB and infection control measures in European countries, analyse

effectiveness of infection control measures or bundles of measures to control the outbreaks and

assess the quality of outbreak studies.

Materials and Methods

Target ARB: MRSA, vancomycin-resistant S. aureus (VRSA), vancomycin-resistant Enterococcus

faecalis and Enterococcus faecium (VRE), EBSL (extended-spectrum beta-lactamase)-producing E. coli

(ESBL-EC), K. pneumoniae (ESBL-KP), A. baumannii (ESBL-AB), and P. aeruginosa (ESBL-PA),

carbapenem-resistant/carbapenemase-producing E. coli (CR-EC), K. pneumoniae (CR-KP),

A. baumannii (CR-AB), and P. aeruginosa (CR-PA) and ceftazidime-resistant E. coli (CZ-EC),

K. pneumoniae (CZ-KP), A. baumannii (CZ-AB), and P. aeruginosa (CZ-PA).

No restriction was applied regarding languages, countries and settings. Since the definition of what

an ESBL producer is, has changed overtime, we included the following definitions for ESBL: 1)

resistant to ceftazidime and/or ceftriaxone (the two may have different detection at different

locations and may have changed over time) 2) phenotypic confirmation (e.g. using beta-lactamase

inhibitor combination). 3) gene identification (likely to exist initially only in single isolates, and more

recently for larger number of strains). Due to the high heterogeneity in defining carbapenemase

production, carbapenems resistance and MDR strains, the definitions reported by the authors were

used and accounted for during the data analysis. Infection rate was defined as the number of

patients infected with an ARB on the number of patients tested positive for ARB during the outbreak.

Study design: systematic review of the literature. Types of studies: all studies regardless of their

design reporting either an outbreak or a sentinel case, irrespective of it resulting in an outbreak,

were included. Outbreaks were searched for at least 10 years after the first one or until endemicity is

established. Endemicity was defined as a prevalence of an ARB higher than 5% in surveillance

programs or large scale reports in the relevant geographical area or worldwide. An outbreak was

defined as an unusual or unexpected increase of cases of infection due to ARB, already isolated with

or without molecular analysis of strains.

Inclusion criteria: reports an outbreak or a single case report of the target ARB, reports the detection

of the ARB using standard laboratory techniques for the period studied, and reports the time of

detection of the outbreak or availability of this information with the corresponding author.

Exclusion criteria: diagnostic studies, reviews, conference abstracts and study protocols.



Study setting: all settings including clinic, hospitals, health care facilities and community and all

population groups including elderly, immuno-compromised, and children.

Screening strategy: eligibility of the resulting articles from the initial search based on title and

abstract screening were assessed by two reviewers and discrepancies sorted out. The reasons for

exclusion of articles were noted down. The full texts of the resulting eligible articles were carefully

read through to extract and enter the data onto a standardised pre-formatted data sheet by two

reviewers. The databases were cross verified to find any discrepancies and inconsistencies were

discussed among the study team and sorted out by consensus.

Data extraction: the following data were extracted: article related variables: name of the author,

email of the corresponding author, institute, country, year of publication, title of the article, journal:

outbreak / sentinel case - related general variables: time of data collection, study design, sampling,

study setting (hospital based, other health care facilities, community based..) population profile

(immuno-compromised, elderly, children, etc); socio-demographic characteristics: age, sex; ARB

specific characteristics: laboratory test used to confirm isolation, type of sample tested (serum,

throat swab, rectal swab, etc), type of infection or colonisation; outbreak specific characteristics:

how outbreak was detected (routine surveillance, clinical samples, etc.), how many patients were

screened, how many were positive, how many patients were infected and how many were colonized,

date of sentinel case, date of first infection control intervention, number of cases before the

intervention, date of last case, endemicity, duration of outbreak, country and city/region of the

outbreak, any mode of spread reported, clonality (clonal vs polyclonal/plasmid/gene), control

measures.

Data synthesis and analysis: data were synthesized for each ARB and linked chronologically and

spatially. For each outbreak report, case rate was calculated as the proportion of the population

screened who are positive (colonisations and/or infections). Attack rate as the proportion of

population screened who develop an infection; and infection rate as the proportion of positively

screened individuals who develop an infection. Pooled estimates of case rate, attack rate and

infection rate were estimated based on random effects models of meta-analysis with Freeman-Tukey

Double Arcsine Transformation for variance stability using STATA’s metaprop command. Outbreak

characteristics as well as infection control measures were studied and effectiveness of infection

control measures studied using logistic regression models. The outbreak numbers were further

standardised per 1 million country population. .



Results

Overall 2647 abstracts and 923 papers were read in detail. According to the study´s inclusion criteria

data from 430 outbreaks (1976-2014) were extracted. The 430 outbreaks were reported from 22

countries; Western Europe (52%), Northern Europe (14%), Eastern Europe (5%), Southwest Europe

(22%) and Southeast Europe (6%). The majority of the outbreaks were published between 1990 and

2010 (84%) as detailed in Table 1 and involved mainly hospitals (386/418, 92%). The UK (18%)

reported the highest number of outbreaks followed by France (14%), Spain (11%), Germany (9%) and

Italy (9%). Standardised number of outbreaks by the latest country population is reported in Table 2

and Figure 1. The majority of published outbreaks were caused by MRSA (45%), followed by VRE

(13%), ESBL KP (12%), CR-AB (9.3%) and CR-KP (8%). Among the European countries, MRSA outbreaks

were reported from Western and Northern European regions (54% vs 28%) while those due to CR-KP

(16% vs 4%), CR-AB(19% vs 5%), CR-PA (6% vs 1%) and ESBL-KP (14% vs 11%) from Eastern,

Southwest and Southeast Europe.

The majority of outbreaks were monocentric (88%) although in 53 outbreaks more than one centre

was involved (range, 2-40), mainly in Western and Northern European countries. Among the 61

outbreaks reporting the age distribution, individuals were on an average 58 years old (IQR: 44 – 66;

range: 0 – 102) and the gender ratio (based on 86 outbreaks) was 33% females (IQR: 20 – 45; range: 0

– 100). Majority of the outbreaks were reported from ICUs (46%) followed by surgical (25%) and

neonatal (14%) settings (Table 4). Community onset outbreaks were more frequently due to MRSA

(15%) and ESBL-EC outbreaks (11%), while CR-GN outbreaks were more often reported from ICUs.

The duration of outbreaks was on an average (median), 274 days (inter quartile range: 114 – 602

days). Table 6 and Figure 2 present the duration according to the type of ARB.

The overall as well as ARB specific case rates, attack rates and infection rates have been presented in

Table 7. Screening of staff and relatives was reported in 26.5% and 6.5% of the overall outbreaks.

Screening of staff (14.4% vs 4.8%) and relatives (3.5% vs 0.7%) were more often reported from

Western and Northern Europe for MRSA outbreaks.

Staff personnel were screened in 114 outbreaks and on an average, 65 staff (IQR: 35 – 152; range: 0 –

459) were screened per outbreak; 3 tested positive (IQR: 1 – 7; range: 0 – 223) and number of staff

with an infection caused by ARB ranged from 0 to 8. Relatives of patients were screened in 28

outbreaks and on an average, 6 individuals (IQR: 4 – 16; range: 3 – 68) were screened per outbreak; 2

tested positive (IQR: 1 – 3; range: 0 – 37) and number of relatives with an infection caused by ARB

ranged from 0 to 8 (median: 0; IQR: 0 – 1).



The attack rate in hospital staff was lower compared to that among patients (00.0% vs 4.4%). Attack

rate was also different among ARB: a lower attack rate was observed among VRE outbreaks (0.63%)

while MRSA, ESBL-KP, ESBL-EC had higher attack rates (>=4%) except for a single CZ-PA outbreak

reporting an attack rate of 32.7%. (p=0.006)

Table 9 presents the distribution of the various types of infections according to ARB. Blood stream

infections (33%), respiratory tract infections (16%), urinary tract infections (16%), and wound

infections (12%) were the type of infections more commonly reported in the outbreaks. Considering

the primary ARB involved in the outbreak, skin (83%) and wound infections (67%) were more often

MRSA infections, while ventilator associated pneumonia were more commonly reported in CR-AB

outbreaks (63%).

The majority of the hospitals (70%) provided information about infection control measures used to

control the outbreak. One hundred and thirty studies reported clinical and/or microbiological details

of the outbreaks without mentioning any infection control measures (30%). The distribution of the

various infection control measures reported is presented in Table 10. Targeted screening, isolation

and hand washing were the most frequently reported infection control measures.

Post-outbreak endemicity was reported in 25 studies (5.8%). High endemicity rate was associated

with CR-KP (26%), CZ-EC (33%) and CZ-PA (36%). A bundle approach (at least 2 infection control

measures introduced) was significantly associated with controlling the outbreak (p =0.03)

Analyses were undertaken to determine factors associated with longer duration of outbreak using

logistic regression. All the outbreaks with duration longer than the overall median duration in our

systematic review (274 days) were labelled as longer. 193/395 outbreaks with data available on

outbreak duration were defined as unsuccessfully contained. The ARB distribution among the

unsuccessful was as follows: CR-AB (19), CR-EC (1), CR-KP (14), CR-PA (8), CZ-PA (8), ESBL-AB (1),

ESBL-EC (7), ESBL-KP (29), ESBL-PA (1), GISA (1), MRSA (83), VRE (23). The ARB distribution was not

very different between the two groups (p=0.48). The results are presented in Table 11. Univariate

analysis showed that hospital-wide outbreaks (OR=2.49 (1.33 – 4.66), p=0.004)) and those involving

urinary tract infections (UTI) (OR=2.58 (1.42 - 4.68)) were significantly longer and more difficult to

contain. This result was confirmed after adjusted multivariate regression.

Among the infection control measures, targeted screening and ward closure were significantly

associated with the duration of the outbreak. Outbreaks implementing targeted screening and ward

closure were 46% and 54% less likely to be of a longer duration respectively.

Mandatory reporting of outbreaks due to ARB: Out of the 32 European Union and European Free

Trade Association nations, Germany, Hungary, the Netherlands, Norway and Sweden have an



outbreak-specific surveillance programme implemented. Germany (since 2011), Hungary (2010) and

Norway (2005) mandate the reporting of nosocomial outbreaks, irrespective of the causative

organism, from hospitals and healthcare centres, while in Sweden the surveillance programme based

on an automated outbreak detection system (2009) targets penicillin-resistant Streptococcus

pneumoniae, MRSA, VRE, and ESBL/carbapenemase-producing Enterobacteriaceae in community and

healthcare facilities. Interestingly, in the Netherlands, incidence of MRSA clusters outside hospitals

(community) must be reported to the national public health agency as part of the national

surveillance agenda (since 2008). Hospital outbreaks due to any pathogen are reported voluntarily to

the outbreak surveillance programme, SO-ZI/AMR, since 2012. All countries, excepting Germany,

provide outbreak data stratified by resistant pathogens. The characteristics of these surveillance

programmes and the number of outbreaks reported by these systems are described in tables 12 and

13.



Table 1. Outbreak period and associated frequencies (published reports)

Frequency of outbreaks (percentage) in European regions

Period of outbreak Western Northern Eastern Southwest Southeast Total

1976 -1999 112 24 9 30 5 180

(50.22) (38.71) (39.13) (31.58) (18.52) (41.86)

2000 - 2009 83 34 13 48 15 193

(37.22) (54.84) (56.52) (50.53) (55.56) (44.88)

2010 - 2014 28 4 1 17 7 57

(12.56) (6.45) (4.35) (17.89) (25.93) (13.26)

Total 223 62 23 95 27 430

Table 2. Outbreak numbers in correlation with total population according to published reports

Country Total population*

Number of outbreaks

Standardised outbreak rate (published reports) per million population

ARB most frequently associated with published outbreak

Bulgaria 7098000 1 0,14 CRGN Slovakia 5429000 1 0,18 CRGN Austria 8570000 2 0,23 MRSA, ESBLGN Poland 38593000 15 0,39 VRE Belgium 11372000 5 0,44 ESBLGN Germany 80682000 40 0,5 MRSA Hungary 9821000 6 0,61 MRSA Italy 59801000 39 0,65 CRGN Croatia 4225000 3 0,71 ESBLGN Portugal 10304000 8 0,78 MRSA France 64668000 61 0,94 ESBLGN, MRSA Slovenia 2069000 2 0,97 MRSA Latvia 1956000 2 1,02 CRGN, ESBLGN Spain 46065000 48 1,04 CRGN United Kingdom

65111000 79 1,21 MRSA

Netherlands 16980000 24 1,41 MRSA Switzerland 8379000 12 1,43 MRSA Denmark 5691000 9 1,58 MRSA Sweden 9852000 19 1,93 MRSA Greece 10919000 22 2,01 CRGN Finland 5524000 14 2,53 MRSA Norway 5272000 18 3,41 MRSA

*Population as per the latest census as provided by the UN statistics



Figure 1. Outbreak etiology by country inhabitants according to published reports

0

0.5

1

1.5

2

2.5

3

3.5

4

0

10

20

30

40

50

60

70

80

90

Num

ber o

f out

brea

ks

Carbapenem-resistant GN Cefatzidime-resistant GN ESBL-GN

VRE GISA MRSA

Frequency per million



CR-AB

Country Frequency Percentage Belgium 1 2,5 Bulgaria 1 2,5 Croatia 1 2,5 Finland 1 2,5 France 6 15,0 Germany 2 5,0 Greece 4 10,0 Italy 11 27,5 Latvia 1 2,5 Poland 1 2,5 Spain 9 22,5 UK 2 5,0 Total 40 100

CR-EC

Country Frequency Percentage France 1 50 Greece 1 50 Total 2 100

CR-KP

Country Frequency Percentage France 5 14,3 Germany 4 11,4 Greece 7 20,0 Italy 9 25,7 Norway 1 2,9 Portugal 1 2,9 Spain 6 17,1 UK 2 5,7 Total 35 100

CR-PA

Country Frequency Percentage France 1 7,7 Germany 1 7,7 Greece 3 23,1 Italy 2 15,4 Netherlands 1 7,7 Slovakia 1 7,7 Spain 3 23,1 UK 1 7,7 Total 13 100

CZ-AB

Country Frequency Percentage Netherlands 1 100 Total 1 100

CZ-EC

Country Frequency Percentage Germany 1 33,3 Sweden 1 33,3 UK 1 33,3 Total 3 100

CZ-PA

Country Frequency Percentage Denmark 1 9,1 France 5 45,5 Germany 1 9,1 Greece 2 18,2 Italy 1 9,1 Spain 1 9,1 Total 11 100

Table 3A. Outbreaks stratified by countries (alphabetical order) and antibiotic-resistant bacteria



ESBL-AB

Country Frequency Percentage Belgium 1 100 Total 1 100

ESBL-EC

Country Frequency Percentage Finland 1 5,3 France 3 15,8 Italy 1 5,3 Netherlands 1 5,3 Norway 1 5,3 Poland 1 5,3 Spain 1 5,3 Sweden 4 21,1 Switzerland 1 5,3 UK 5 26,3 Total 19 100

ESBL-KP

Country Frequency Percentage Austria 1 2,0 Belgium 1 2,0 Croatia 2 3,9 Denmark 2 3,9 France 12 23,5 Germany 3 5,9 Greece 2 3,9 Hungary 1 2,0 Italy 4 7,8 Latvia 1 2,0 Netherlands 3 5,9 Norway 1 2,0 Poland 4 7,8 Portugal 1 2,0 Spain 7 13,7 Sweden 2 3,9 UK 4 7,8 Total 51 100

ESBL-PA

Country Frequency Percentage Italy 1 100 Total 1 100

VRE

Country Frequency Percentage Belgium 1 1,8 Finland 1 1,8 France 10 17,9 Germany 11 19,6 Greece 1 1,8 Hungary 1 1,8 Italy 2 3,6 Netherlands 3 5,4 Poland 6 10,7 Spain 6 10,7 Sweden 3 5,4 Switzerland 2 3,6 UK 9 16,1 Total 56 100

MRSA

Country Frequency Percentage Austria 1 0,5 Belgium 1 0,5 Denmark 6 3,1 Finland 11 5,7 France 15 7,7 Germany 17 8,8 Greece 2 1,0 Hungary 4 2,1 Italy 8 4,1 Netherlands 15 7,7 Norway 15 7,7 Poland 3 1,5 Portugal 6 3,1 Slovenia 2 1,0 Spain 15 7,7 Sweden 9 4,6 Switzerland 9 4,6 UK 55 28,4 Total 194 100

GISA

Country Frequency Percentage France 3 100 Total 3 100

Table 3B. Outbreaks stratified by countries (alphabetical order) and antibiotic-resistant bacteria


ND4BB CO

MBACTE-M


Table 3C. Outbreaks stratified by countries and antibiotic-resistant bacteria – a com

prehensive overview

Country CR-AB

CR-EC CR-KP

CR-PA CZ-AB

CZ-EC CZ-KP

CZ-PA ESBL-AB

ESBL-EC ESBL-KP

ESBL-PA VRE

MRSA

GISA Total

Austria

1

1

2 Belgium

1

1

1

1

1

5 Bulgaria

1

1

Croatia 1

2

3 Denm

ark

1

2

6

9 Finland

1

1

1 11

14

France 6

1 5

1

5

3 12

10

15 3

61 Germ

any 2

4

1

1

1

3

11

17

40 Greece

4 1

7 3

2

2

1 2

22

Hungary

1

1

4

6 Italy

11

9 2

1

1

4 1

2 8

39

Latvia 1

1

2 Netherlands

1

1

1

3

3 15

24

Norway

1

1

1

15

18

Poland 1

1 4

6

3

15 Portugal

1

1

6

8

Slovakia

1

1 Slovenia

2

2

Spain 9

6

3

1

1 7

6

15

48 Sw

eden

1

4 2

3

9

19 Sw

itzerland

1

2

9

12 UK

2

2 1

1

5

4

9 55

79

Total 40

2 35

13 1

3 0

11 1

19 51

1 56

194 3

430



Table 4. Distribution of 430 outbreaks based on the hospital setting

Outbreak setting Number of outbreaks (%) Day care 1 (0,24) Elderly home 1 (0,24) Rehabilitation Center 1 (0,24) Emergency 2 (0,48) Trauma care 3 (0,72) Dermatology 5 (1,2) Obst. & Gyn 6 (1,44) Transplantation 10 (2,4) Burns Unit 10 (2,4) Cardiology 13 (3,13) Pediatric 19 (4,57) Hematology 36 (8,65) Nephrology 43 (10,34) Medical 49 (11,78) Hospital wide 57 (13,7) Neonatal 59 (14,18) Surgical 103 (24,76) ICU 192 (46,15)


ND4BB CO

MBACTE-M


Table 5. Outbreaks by antibiotic-resistant bacteria, type of setting – num

bers and percentage

Setting \ ARO

CR-AB CR-EC

CR-KP CR-PA

CZ-AB CZ-EC

CZ-PA ESBL-AB

ESBL-EC ESBL-KP

ESBL-PA GISA

MRSA

VRE Surgery

9%

1%

13%

3%

1%

2%

17%

1%

46%

8%

Medicine

14%

2%

20%

4%

4%

2%

12%

35%

6%

N

eonatal 3%

2%

10%

20%

58%

7%

Pediatric

11%

5%

5%

16%

37%

26%

Hospital wide

11%

2%

11%

7%

2%

18%

2%

33%

16%

ICU

17%

1%

14%

4%

1%

1%

4%

1%

2%

17%

1%

1%

29%

10%

Burns U

nit 10%

10%

10%

10%

10%

50%

Hem

atology 6%

8%

6%

3%

6%

3%

6%

11%

53%

Elderly 8%

17%

17%

33%

25%

Nephrology

7%

9%

2%

5%

14%

26%

37%

Cardiology

8%

31%

38%

23%

Transplantation

20%

10%

20%

30%

20%

Setting \ ARO

CR-AB CR-EC

CR-KP CR-PA

CZ-AB CZ-EC

CZ-PA ESBL-AB

ESBL-EC ESBL-KP

ESBL-PA GISA

MRSA

VRE Total

Surgery 9

1 13

3

1

2

18

1 47

8 103

Medicine

7 1

10 2

2

1 6

17 3

49 N

eonatal 2

1

6

12

34

4 59

Pediatric

2

1 1

3

7

5 19

Hospital wide

6 1

6 4

1 10

1

19 9

57 ICU

32

1 27

7 1

1 7

1 4

33 1

2 55

20 192

Burns Unit

1

1

1 1

1

5

10 Hem

atology 2

3

2

1 2

1

2

4

19 36

Elderly 1

2

2

4

3 12

Nephrology

3

4 1

2 6

11 16

43 Cardiology

1

4

5 3

13 Transplantation

2

1 2

3 2

10



Table 6. Duration of outbreaks according to antibiotic-resistant bacteria

ARB Number of studies reporting duration

Duration of outbreak in days

Median (Inter quartile range) Range ESBL-AB 1 539

CZ-PA 11 519 ( 151 - 609 ) 61 - 1614 CR-PA 13 395 ( 151 - 882 ) 15 - 1096 CR-EC 1 365

ESBL-KP 48 345 ( 153 - 609.5 ) 30 - 1460 ESBL-PA 1 303

VRE 47 274 ( 153 - 730 ) 11 - 1553 CR-AB 39 267 ( 132 - 546 ) 32 - 1461 CZ-AB 1 243

ESBL-EC 15 242 ( 37 - 638 ) 1 - 1399 MRSA 176 228 ( 91 - 516.5 ) 3 - 1825 CR-KP 35 182 ( 65 - 390 ) 5 - 1095 CZ-EC 2 137 ( 122 - 152 ) 122 - 152 GISA 3 91 ( 50 - 378 ) 50 - 378

Total 393 274 ( 114 - 602 ) 1 - 1825

Figure 2. Duration of outbreaks according to antibiotic-resistant bacteria

GISA

CZEC

CRKP

MRSA

ESBLE

CZAB

CRAB

VRE

ESBLPA

ESBLKP

CREC

CRPA

CZPA

ESBLAB

0

100

200

300

400

500

600

700

800

900

1000

Med

ian

(IQR)

dur

atio

n of

out

brea

k in

day

s



Table 7. Case and Infection rates according to antibiotic-resistant bacteria

ARB Case rate (%) Attack rate (%) Infection rate (%) n pooled estimate* n pooled estimate* n pooled estimate*

ESBL-AB 1 88.89 ( 56.50 - 98.01 ) ESBL-KP 3 15.18 ( 1.91 - 37.36 ) 3 4.66 ( 1.26 - 9.88 ) 26 74.69 ( 55.32 - 90.36 ) CR-PA 2 9.44 ( 8.13 - 10.83 ) 1 2.10 ( 1.02 - 4.26 ) 8 68.38 ( 45.29 - 87.90 ) CR-KP 3 5.91 ( 1.42 - 12.76 ) 3 3.69 ( 0.61 - 8.69 ) 1 59.59 ( 47.23 - 71.45 ) CR-AB 2 7.23 ( 4.92 - 9.92 ) 2 3.85 ( 2.17 - 5.94 ) 26 58.25 ( 49.68 - 66.60 ) MRSA 31 14.92 ( 11.54 - 18.62 ) 19 6.31 ( 3.23 - 10.20 ) 99 54.91 ( 48.30 - 61.45 ) CZ-PA 2 77.29 ( 69.11 - 84.58 ) 1 32.65 ( 21.21 - 46.62 ) 4 54.77 ( 26.62 - 81.43 ) CR-EC 1 54.55 ( 28.01 - 78.73 ) GISA 21 52.38 ( 32.37 - 71.66 ) ESBL-EC 2 33.27 ( 24.15 - 43.03 ) 2 3.98 ( 0.69 - 9.15 ) 8 49.45 ( 17.35 - 81.77 ) VRE 12 15.63 ( 9.73 - 22.59 ) 9 0.63 ( 0.04 - 1.66 ) 35 20.21 ( 13.06 - 28.34 ) CZ-EC 1 47.73 ( 33.75 - 62.06 ) Overall 58 16.55 ( 13.52 - 19.80 ) 40 4.37 ( 2.75 - 6.29 ) 230 52.76 47.58 - 57.90 )

*pooled estimate derived from random effects meta-analysis using Wilson score method only for categories where more than one estimate is available

Table 8. Case and Infection rates among staff personnel according to antibiotic-resistant bacteria

ARB Case rate (%) Attack rate (%) Infection rate (%) n pooled estimate* n pooled estimate* n pooled estimate*

MRSA 36 5.26 ( 3.58 - 7.20 ) 28 0.00 ( 0.00 - 0.08 ) 58 0.00 ( 0.00 - 1.21 ) ESBL-KP 1 0.00 ( 0.00 - 11.35 ) 1 0.00 ( 0.00 - 11.35 ) 1 0.00 ( 0.00 - 1.10 ) ESBL-EC 1 6.45 ( 1.79 - 20.72 ) CZ-EC CZ-PA CR-AB 2 0.00 ( 0.00 - 4.25 ) CR-PA 1 1.82 ( 0.50 - 6.39 ) VRE 2 1.03 ( 0.06 - 2.70 ) CR-KP GISA 1 2.04 ( 0.36 - 10.69 ) CR-EC ESBL-AB Overall 44 4.39 ( 2.99 - 6.00 ) 29 0.00 ( 0.00 - 0.07 ) 59 0.00 ( 0.00 - 1.10 )

*pooled estimate derived from random effects meta-analysis using Wilson score method only for categories where more than one estimate is available


ND4BB CO

MBACTE-M


Table 9. Type of infections according to antibiotic-resistant bacteria (in numbers and percentages)

Type of infections \ARB CR-AB

CR-EC CR-KP

CR-PA CZ-AB

CZ-EC CZ-PA

ESBL-AB ESBL-EC

ESBL-KP ESBL-PA

GISA M

RSA VRE

Total Blood stream

infection 23

1 19

6

1 4

4

17

2 47

16 140

Urinary tract infection

8 1

10 4

1

4

6 7

1 2

15 8

67

Respiratory tract infection 15

1 13

2

5

1

10

1 19

2 69

Skin infection 3

1

29

2 35

Wound infection

5 1

3

1

1

1 2

1

34 2

51

Surgical site infection 4

3

2

4

5

18

Meningitis

3

1

1 1

1 1

8

Ventilator-ssociated infection 10

1

2

1

2

16

Type of infections \ARB CR-AB

CR-EC CR-KP

CR-PA CZ-AB

CZ-EC CZ-PA

ESBL-AB ESBL-EC

ESBL-KP ESBL-PA

GISA M

RSA VRE

Blood stream infection

16%

1%

14%

4%

1%

3%

3%

12%

1%

34%

11%

U

rinary tract infection 12%

1%

15%

6%

1%

6%

9%

10%

1%

3%

22%

12%

Respiratory tract infection

22%

1%

19%

3%

7%

1%

14%

1%

28%

3%

Skin infection 9%

3%

83%

6%

W

ound infection 10%

2%

6%

2%

2%

2%

4%

2%

67%

4%

Surgical site infection

22%

17%

11%

22%

28%

M

eningitis 38%

13%

13%

13%

13%

13%

Ventilator-ssociated infection

63%

6%

13%

6%

13%


ND4BB CO

MBACTE-M


Table 10 A. Infection control measures applied during the outbreak according to antibiotic-resistant bacteria (in num

bers)

ARB Hand

washing

Room

isolation ATBS

Ward

closure U

niversal screening

Targeted screening

Environental screening

Cohorting personnel

Education Cohorting patients

Decolonisation Total

CR-AB

24 21

8 16

18 6

20 10

14 13

6 31

CR-EC 1

1 1

1

2

1 1

1

2 CR-KP

19 18

8 3

21 11

9 3

11 13

2 31

CR-PA 6

6 3

7

1 6

1 4

3 1

9 CZ-AB

1

1

CZ-EC

CZ-PA 1

1 3

1

2

1

7 ESBL-AB

ESBL-EC 3

1 2

2 2

3 4

1 3

3 3

10 ESBL-KP

7 9

1 2

8 13

14 1

3 8

7 25

ESBL-PA

GISA 2

2

1

1 1

1

1

2 M

RSA 61

72 2

23 65

106 55

18 29

46 96

138 VRE

17 18

16 3

8 17

19 7

14 20

3 44

Total

142 149

44 49

131 160

129 43

81 107

120 300


ND4BB CO

MBACTE-M


Table 10 B. Infection control measures applied during the outbreak according to antibiotic-resistant bacteria (in percentages)

ARB Hand

washing

Room

isolation ATBS

Ward

closure U

niversal screening

Targeted screening

Environental screening

Cohorting personnel

Education Cohorting patients

Decolonisation

CR-AB 77%

68%

26%

52%

58%

19%

65%

32%

45%

42%

19%

CR-EC 50%

50%

50%

50%

100%

50%

50%

50%

CR-KP 61%

58%

26%

10%

68%

35%

29%

10%

35%

42%

6%

CR-PA 67%

67%

33%

78%

11%

67%

11%

44%

33%

11%

CZ-AB 100%

CZ-EC

CZ-PA 14%

14%

43%

14%

29%

14%

ESBL-AB

ESBL-EC 30%

10%

20%

20%

20%

30%

40%

10%

30%

30%

30%

ESBL-KP 28%

36%

4%

8%

32%

52%

56%

4%

12%

32%

28%

ESBL-PA

GISA 100%

100%

50%

50%

50%

50%

50%

MRSA

44%

52%

1%

17%

47%

77%

40%

13%

21%

33%

70%

VRE 39%

41%

36%

7%

18%

39%

43%

16%

32%

45%

7%

Total 47%

50%

15%

16%

44%

53%

43%

14%

27%

36%

40%



Table 11. Outbreak characteristics associated with longer duration of outbreak (duration longer than the overall median (> 274 days)) – logistic regression analyses

Factors Univariate Multivariate

OR (95% CI) p-value Adjusted OR (95% CI)

p-value

Outbreak setting ICU 0.73 ( 0.49 - 1.08 ) 0.11 0.73 ( 0.47 - 1.14 ) 0.17 Surgery 0.75 ( 0.47 - 1.19 ) 0.23 Medicine 1.13 ( 0.6 - 2.11 ) 0.71 Hospital wide 2.49 ( 1.33 - 4.66 ) 0.004 1.87 ( 0.96 - 3.64 ) 0.07 Type of infection involved Bloodstream infection 0.96 ( 0.63 - 1.45 ) 0.83 Urinary tract infection 2.58 ( 1.42 - 4.68 ) 0.002 2.62 ( 1.40 - 4.89 ) 0.003 Respiratory tract infection 1.27 ( 0.74 - 2.18 ) 0.38 Ventilator associated pneumonia 0.6 ( 0.21 - 1.68 ) 0.33


ND4BB CO

MBACTE-M


Table 12. Main characterisitics of surveillance program

mes m

onitoring outbreaks in Europe

Country System

/institution Active since

Surveillance structure

Target resistance

Setting O

utbreak definition Resistance definition

Demographic

s O

utcome

Control m

easures to tackle outbreaks

Acronym

Nam

e

Germany

RKI Robert Koch Institute

2011

Mandatory

notification of nosocom

ial outbreaks

Any Healthcare facilities

Two or m

ore epidemiologically-

linked nosocomial infections

Not specified

Not specified M

ortality Not specified

Hungary NNSR

National nosocomial

surveillance system

2010

Mandatory

notification of nosocom

ial outbreaks




Not specified

Netherlands

RIVM

Dutch National Institute for Public Health and the Environm

ent

2008

Mandatory

notification of clusters due to M

RSA

MRSA

Comm

unity Not specified

Not specified

Age, gender Not specified

Not specified

Netherlands

SO-ZI/AM

R

Signaling Consultation of Hospital acquired Infections and AntiM

icrobial Resistance

2012

Voluntary notification of outbreaks due to resistant+ susceptible pathogens

Any Hospitals



Not specified

Norw

ay VESUV

Web-based outbreak

alert system

2005

Mandatory

notification of outbreaks due to resistant+ susceptible pathogens


(1) number of cases of an

infectious disease which clearly

exceeds the expected level within

a given time and area, or (2) ⩾

2 cases of the sam

e infectious diseases w

here a comm

on source is suspected

Not specified

Not specified M

ortality Yes

Sweden

CASE/ Sm

iNet

Computer Assisted

Search for Epidem

ics/ Swedish

national electronic surveillance system

2009

Automated

outbreak detection based on m

andatory notification of diseases due to susceptible and resistant pathogens

PNSP, MRSA,

VRE, ESBL/carbapenem

ase-producing Enterobacteriaceae

Comm

unity+ healthcare facilities

Two or m

ore cases of a disease Not specified

Age, gender Not specified

Not specified



Table 13. Comparision of antibiotic-resistant bacteria outbreaks reported annually: peer-reviewed vs surveillance system reports

Germany

MRSA 2012 2013 2014 2015 1

RKI 19

VRE 2012 2013 2014 2015 1

RKI 2

ESBL-EC 2012 2013 2014 2015

RKI 7

ESBL-KP 2012 2013 2014 2015

RKI 6

CR-KP 2012 2013 2014 2015

1

RKI

Hungary

MRSA 2010 2011 2012 2013 2014 2015

NNSR 6 3 1 9 1

VRE 2010 2011 2012 2013 2014 2015

NNSR

2 2 2

ESBL-KP 2010 2011 2012 2013 2014 2015

NNSR 3 8 5

1

Netherlands

MRSA 2008 2009 2010 2011 2012 2013 2014 2015

1

RIVM (community) 4 16 14 6 2 11 3 11

SO-ZI/AMR (hospitals)

4 10 19 22

VRE 2012 2013 2014 2015 *Years considered according to surveillance commencement



SO-ZI/AMR 7 11 14 16

ESBL-EC 2012 2013 2014 2015

1

SO-ZI/AMR

2

ESBL-KP 2012 2013 2014 2015

SO-ZI/AMR 3 4 1 2

Norway MRSA 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

1 2 1 1 1 1 1

VESUV

9 10 9 4 12 8 10 10

VRE 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

VESUV

1 1 1 2 4 1

ESBL-EC 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

VESUV

2 2 4

CR-KP 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

1

VESUV

ESBL-KP 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

1

VESUV

*Years considered according to surveillance commencement

Sweden



MRSA 2009 2010 2011 2012 2013 2014 2015

CASE

25 30 20 13

VRE 2009 2010 2011 2012 2013 2014 2015

CASE

2 3 5 10 13 12

ESBL-KP 2009 2010 2011 2012 2013 2014 2015

1

CASE

*Years considered according to surveillance commencement



References

1. Wright GD. The antibiotic resistome: the nexus of chemical and genetic diversity. Nat Rev Microbiol 2007;5(3):175-86.doi: 10.1038/nrmicro1614.

2. Davies J, Davies D. Origins and evolution of antibiotic resistance. Microbiol Mol Biol Rev 2010;74(3):417-33.doi: 10.1128/MMBR.00016-10.

3. Tacconelli E, De Angelis G, Cataldo MA, et al. Antibiotic usage and risk of colonization and infection with antibiotic-resistant bacteria: a hospital population-based study. Antimicrob Agents Chemother 2009;53(10):4264-9.doi: 10.1128/AAC.00431-09|.

4. Brown ED, Wright GD. Antibacterial drug discovery in the resistance era. Nature 2016;529(7586):336-43.doi: 10.1038/nature17042.

5. Schroder W, Sommer H, Gladstone BP, et al. Gender differences in antibiotic prescribing in the community: a systematic review and meta-analysis. J Antimicrob Chemother 2016;71(7):1800-6.doi: 10.1093/jac/dkw054.

6. Nikaido H. Multidrug resistance in bacteria. Annu Rev Biochem 2009;78:119-46.doi: 10.1146/annurev.biochem.78.082907.145923.

7. Alekshun MN, Levy SB. Molecular mechanisms of antibacterial multidrug resistance. Cell 2007;128(6):1037-50.doi: 10.1016/j.cell.2007.03.004.

8. Munita JM, Bayer AS, Arias CA. Evolving resistance among Gram-positive pathogens. Clin Infect Dis 2015;61 (Suppl 2):S48-57.doi: 10.1093/cid/civ523.

9. McGowan JE, Jr. Resistance in nonfermenting gram-negative bacteria: multidrug resistance to the maximum. Am J Infect Control 2006;34(5 Suppl 1):S29-37; discussion S64-73.doi: 10.1016/j.ajic.2006.05.226.

10. European Centre for Disease Prevention and Control. Point prevalence survey of healthcare-associated infections and antimicrobial use in European acute care hospitals 2011-2012. Stockholm:ECDC, 2013. http://ecdc.europa.eu/en/publications/surveillance_reports/Pages/index.aspx (accessed 08 June 2016).

11. Teillant A, Gandra S, Barter D, et al. Potential burden of antibiotic resistance on surgery and cancer chemotherapy antibiotic prophylaxis in the USA: a literature review and modelling study. Lancet Infect Dis 2015;15(12):1429-37.doi: 10.1016/S1473-3099(15)00270-4.

12. O'Neill J. Antimicrobial Resistance:Tackling a crisis for the health and wealth of nations. Review on Antimicrobial Resistance 2014: http://amr-review.org/Publications (accessed 15 June 2016).

13. Williams RJ, Heymann DL. Containment of antibiotic resistance. Science 1998;279(5354):1153-4.doi: 10.1126/science.279.5354.1153.

14. Williams RJ, Ryan MJ. Surveillance of antimicrobial resistance--an international perspective. BMJ 1998;317(7159):651.doi: http://dx.doi.org/10.1136/bmj.317.7159.651.

15. Roca I, Akova M, Baquero F, et al. The global threat of antimicrobial resistance: science for intervention. New Microbes New Infect 2015;6:22-9.doi: 10.1016/j.nmni.2015.02.007.

16. Grundmann H, Klugman KP, Walsh T, et al. A framework for global surveillance of antibiotic resistance. Drug Resist Updat 2011;14(2):79-87.doi: 10.1016/j.drup.2011.02.007.

17. O'Brien TF, Stelling J. Integrated Multilevel Surveillance of the World's Infecting Microbes and Their Resistance to Antimicrobial Agents. Clin Microbiol Rev 2011;24(2):281-95.doi: 10.1128/CMR.00021-10.

18. O'Neill J. Tackling drug-resistant infections globally: final report and recommendations. Review on Antimicrobial Resistance 2016. http://amr-review.org/Publications (accessed 15 June 2016).

19. ND4BB COMBACTE-MAGNET. http://www.combacte.com/COMBACTE-MAGNET/About (accessed 20 June 2016).

20. Kostyanev T, Bonten MJ, O'Brien S, et al. The Innovative Medicines Initiative's New Drugs for Bad Bugs programme: European public-private partnerships for the development of new strategies to tackle antibiotic resistance. J Antimicrob Chemother 2016;71(2):290-5.doi: 10.1093/jac/dkv339.

21. Moher D, Shamseer L, Clarke M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev 2015;4:1.doi: 10.1186/2046-4053-4-1.

22. Tacconelli E, Cataldo MA, Dancer SJ, et al. ESCMID guidelines for the management of the infection control measures to reduce transmission of multidrug-resistant Gram-negative bacteria in hospitalized patients. Clin Microbiol Infect 2014;20 (Suppl 1):1-55.doi: 10.1111/1469-0691.12427.



23. Rawat D, Nair D. Extended-spectrum beta-lactamases in Gram Negative Bacteria. J Glob Infect Dis 2010;2(3):263-74.doi: 10.4103/0974-777X.68531.

24. Paterson DL, Bonomo RA. Extended-spectrum beta-lactamases: a clinical update. Clin Microbiol Rev 2005;18(4):657-86.doi: 10.1128/CMR.18.4.657-686.2005.

25. Stone SP, Cooper BS, Kibbler CC, et al. The ORION statement: guidelines for transparent reporting of outbreak reports and intervention studies of nosocomial infection. Lancet Infect Dis 2007;7(4):282-8.doi: 10.1016/S1473-3099(07)70082-8.

26. Nyaga VN, Arbyn M, Aerts M. Metaprop: a Stata command to perform meta-analysis of binomial data. Archives of Public Health. 2014;72:39. doi:10.1186/2049-3258-72-39.



5. Discussion

(The following statements are partly extracted from the paper “Improved Surveillance is Essential for

Control of Antimicrobial Resistance: A Call to Action” from the EPI-Net group, currently under revision

for publication).

Surveillance is essential to all aspects of HAI and AMR management. It provides the necessary

information to develop and monitor therapy guidelines, antibiotic formularies, antibiotic stewardship

programmes, public health interventions, infection control policies, and antimicrobial and vaccine

development. The key role played by surveillance starts with the development of algorithms for

empiric antibiotic therapy and of stewardship programmes. Indeed, active monitoring of AMR is

essential to effective antibiotic stewardship supporting appropriate antimicrobial use that optimises

patients´ clinical outcomes while minimising unintended consequences of antibiotics, including

toxicity and the emergence of resistance. Knowledge of up-to-date surveillance data improves public

health not only at the local level (clinical outcomes for patients) but also globally (hospital and

community AMR rates). Moreover, data from global surveillance systems provide information on

new and worrisome AMR trends and allow policymakers at national and international level to design

new strategies to counter the threat.

European surveillance data are publicly available from the ECDC as well as from many national

cohorts. EARS-Net, the largest publicly funded AMR surveillance system in Europe, was established in

1998 by the European Commission and from 2010 has been coordinated and funded by the ECDC.20

This network, which significantly improved the quality of surveillance data in Europe, provides yearly

reference data on AMR. As AMR has emerged as a significant threat, many national surveillance

systems have also been implemented in Europe.

Our systematic reviews show that limitations of these national surveillance systems can be grouped

into three categories: (1) structural problems, (2) lab-based surveillance issues, and (3) lack of

coordination with animal and food surveillance systems. Structural problems are manifold. In

general, the national surveillance efforts in Europe are still fragmented and heterogeneous.

Numerous local and national systems for HAI and AMR data collection have different goals and little

or no coordination, harmonisation, or information sharing with international networks. Lack of

standardisation of epidemiological definitions, samples and data collected, settings included,

microbiological testing methods (including susceptibility testing), and data sharing policies are

potential obstacles to reliable and informative collaborative surveillance. Almost half of the systems

do not report if European Committee on Antimicrobial Susceptibility Testing (EUCAST) or Clinical &



Laboratory Standards Institute (CLSI) guidelines are used to define resistance, and a clear definition

of AMR is provided for only one-third of the systems. Although point-prevalence surveys and lab-

based surveillance can provide comprehensive information, publication of these results often

appears years after data collection, limiting their utility in clinical, institutional, and regulatory

decision-making and in targeting of resources and research priorities. Only 7% of the surveillance

systems in Europe provide real-time access to resistance data.

Inherent limitations of the methods used also challenge adequate interpretation of the data.

Laboratory-based systems have a number of specific limitations. First, the microbiological results

reported usually have no associated relevant epidemiological, clinical, or outcome data. Thus, these

systems provide no information on identification of at-risk patient populations, types of infections,

sources (community-onset versus healthcare-associated versus truly hospital-acquired), treatment

failure, or real burden of disease associated with HAIs and AMR. Second, genetic typing and

characterisation is not routinely included for all relevant isolates or mechanisms of resistance; this

testing would facilitate determination of whether AMR trends are caused by spread of resistant

strains or by transfer of resistance determinants among different strains and species. Third, sample

collection may introduce biases that result in lack of external validity, inability to measure impact of

HAIs or AMR within an institution or a community, and failure to predict upcoming trends. Difference

in the frequency and distribution of sampling among physicians, institutions, and countries and the

inclusion of screening isolates rather than only clinical isolates undermine the representatives of the

data. In many settings, sample collection is more likely for more severe infections or ones for which

first-line treatment has failed. In these cases, AMR rates may be inflated, and use of these data may

lead to inappropriate choice of therapy, more resistance, and increased health care costs. In

contrast, underreporting of HAIs and AMR may occur if samples are not routinely collected, and

reliance on laboratory-based surveillance underestimates the incidence of clinically relevant HAIs. In

addition, because samples are collected only from affected sites in patients (and probably just a

subset of those), laboratory-based surveillance based on only clinical samples is not like to be useful

as an early-warning system for emerging pathogens and resistance mechanisms, which are more

likely to be first detected as colonisation in samples such as sputum or urine.

High-quality surveillance of AMR in animals and in the food chain is essential to understanding and

predicting AMR trends and mechanisms in humans, but current surveillance in these areas is also

inadequate. In their recent report exploring associations between consumption of antimicrobials and

AMR in humans and food-producing animals,the ECDC, EFSA, and EMA emphasised major limitations

of the available evidence and highlighted the need for enhanced combined surveillance.Few



European countries have implemented national AMR surveillance programmes in animals or food,

and these systems have limited goals. They were set up to monitor resistance mainly in Salmonella,

C. jejuni, and E. coli as required by the European Commission’s mandate, and only a very few monitor

resistance in Klebsiella and S. aureus. Our systematic reviews show that even where such systems

have been established, the lack of coordination with human AMR surveillance systems limits the

data’s applicability to humans. Data collection in animals is directed mainly towards treatment of

disease and less towards detection of resistance to either veterinary or human drugs. The data

largely cover veterinary pathogens and antibiotics, so, while there is some overlap with human

disease, they are difficult to interpret with regard to human health or are not at all relevant.

Furthermore, surveillance in animals and food suffer from the same structural problems as human

surveillance systems, namely fragmentation, lack of standardisation and coordination, and reporting

delays. Results from food surveillance are usually not released publicly and can be difficult to obtain

from regulators because they are considered commercially sensitive.

The impact on patient care

The limitations of current surveillance systems significantly affect patients’ care and outcomes.

Inadequate, delayed reporting of surveillance data can lead to suboptimal empiric prescribing and

overprescribing that may jeopardise the outcome for the individual, increase risk of transmission

among hospitalised patients and in the community, and further drive the cycle of AMR development.

In a recent meta-analysis of 27 studies, the rate of inappropriate antibiotic therapy in patients with

severe infections ranged from 14% to 78%, and more than half of the studies had an inappropriate

prescribing rate of more than 50%. Successful empiric therapy of bacterial infections requires

knowledge of the likely microorganism and related susceptibility patterns. Surveillance should thus

provide up-to-date information to the clinician to determine a patient’s risk for resistance in a

specific setting. Increasing globalisation (which includes refugee movements, international travel,

and medical tourism) requires that geographic and temporal changes in AMR be closely monitored

and available in a timely manner. New molecular tests should also be included to increase

understanding of traceability and spread of new AMR threats. Furthermore, an ideal surveillance

system would correlate these data with demographic and clinical data. Surveillance data should be

easily accessible and continuously updated, and detect the emergence and spread of previously

uncommon or completely novel types of resistance.

In addition to the deleterious effects on patient treatment, inadequate surveillance data may also

hamper efforts in other areas. Lack of adequate surveillance data can place susceptible hospital

patients and individuals in the community at risk when infection control measures needed to stop



the spread of AMR are delayed or incorrectly targeted. Results that lack external validity can limit

understanding of AMR and complicate implementation of agricultural, food industry, and

environmental regulations to reduce animal, food, and water transmission. Inferences drawn from

inaccurate or incomplete surveillance data may lead academia and industry in sub-optimal allocation

of research and development resources, including toward the promising translational approach.

The way forward

Under the pressure of increasing AMR, several initiatives have been launched in Europe in the last

few years to address the limitations of current surveillance systems. The European Surveillance of

Veterinary Antimicrobial Consumption (ESVAC) project of the EMA, which since 2009 has collected

and reported data on sales of veterinary antimicrobials, has recently announced their strategy for

improved surveillance over the next 5 years. ESVAC’s goals include expansion of data collection to all

EEA countries (bolstered by a new regulatory requirement), transition to ongoing annual reporting,

standardisation and harmonisation of data collection, automation of data analysis and presentation,

database linkage, and integration of animal, food, and human data.

The Central Asian and Eastern European Surveillance of Antimicrobial Resistance (CAESAR) network

is a joint initiative of the WHO Regional Office for Europe, the European Society of Clinical

Microbiology and Infectious Diseases, and the Dutch National Institute for Public Health and the

Environment. CAESAR is a network of national AMR surveillance systems and includes all countries of

the WHO European Region that are not part of the EARS-Net. The second annual CAESAR report was

published in November 2016. Currently, 20 countries are participating in CAESAR and six have

submitted national surveillance data to the CAESAR database.

The European Survey on Carbapenemase-Producing Enterobacteriaceae (EuSCAPE) project was

funded by the ECDC in 2013 with the goal to reduce gaps in the diagnostic capacity and

heterogeneity of national surveillance and reporting standards in Europe. The network recently

completed a multicenter study of carbapenemase-producing Enterobacteriaceae prevalence in

European countries and demonstrated that challenges in the establishment of continent-wide

enhanced sentinel AMR surveillance can be overcome.

EPI-net was launched in 2015 to contribute to the improvement of HAI and AMR surveillance in

Europe. The project is one of the four pillars of the COMBACTE consortium (LAB-net, CLIN-net, STAT-

net, and EPI-net) within the New Drugs for Bad Bugs (ND4BB) programme. ND4BB is a joint

undertaking of the European Commission and the European Federation of Pharmaceutical Industries

and Associations under the Innovative Medicines Initiative with the objective to accelerateof the

development and patient access to new medications addressing the AMR crisis in Europe. The major



innovation of this new project is the creation of a network of representatives from all sectors

involved in surveillance (including stakeholders, public health, academia, and pharmaceutical

industry) to build consensus and drive funding without duplicating efforts. This deliverable

summarizes the first step of the network with the production of a database including all active

surveillance programmes in humans, animals, and food to identify strengths, limitations, areas for

mitigation or improvement, and possible linkages. Concomitantly, short-term goals include the

testing and implementation of semiautomated surveillance systems in different European countries

to test feasibility and data sensitivity. Long-term goals include a central data repository that for the

first time will include different sources of automated surveillance data (ND4BB clinical trials, national

networks, and pharmaceutical companies) and produce standardised indicators with real-time data

access and evaluation of the cost-effectiveness of connected sentinel laboratories for human and

animal data.

A call to action

Timely and targeted dissemination of surveillance data ought to be an essential component of efforts

to combat the AMR threat. Development of a reliable, comprehensive, and sustainable HAI and AMR

surveillance network is critical to adequately support stakeholders and physicians involved in

patients’ care. It requires the involvement of national and international medical and veterinary

societies, environmental advocates, health care systems, academia, the pharmaceutical industry, and

governments. High-quality surveillance data collection, timely analysis, and wide dissemination will

enable a variety of stakeholders to commit the resources and take the actions necessary to combat

the spread of AMR. No country or professional group can achieve this goal without more extensive

collaboration. Such collaboration will ultimately reduce the burden of disease from HAIs and AMR

and provide both health and economic benefits in Europe and worldwide.

The incessant tide of threats posed by HAIs and AMR cannot be stemmed without improving

surveillance systems. Two short-term priorities are urgent in our opinion: (1) agreement at the

European level on goals of AMR surveillance and on definitions and standardised measures to be

applied at the national level to increase comparability of data and feasibility international projects

and (2) agreement on data sharing among European countries. These achievements would allow

increased and simplified data transmission and thus definitively contribute to the development of

automated systems for AMR alerts that could have a significant impact on the effectiveness of

infection control measures in European countries. Long-term goals must include (1) development of

automated linkage of routine surveillance data with other existing databases containing relevant

clinical data (such as treatments and outcomes) and epidemiological data to provide large integrated



patient-level datasets and to enable definition of the burden of AMR infections in different patients

settings and population communities, (2) enhancement of surveillance systems of AMR in animals

and the food chain, and (3) connection among surveillance systems in humans, animals, and the food

chain, including agreement on key human and veterinary pathogens and key antibiotics to be

monitored and periodic update of these based on AMR trends. These goals cannot be achieved

without increased dedicated financial resources and active involvement of policy makers.

Conclusions

This era of escalating AMR presents an urgent need for improvements in surveillance to streamline

empiric therapy, drive antimicrobial stewardship and infection control measures, and inform

development of new drugs and vaccines. Without such improvements, it will be difficult—almost

impossible—to significantly reduce the medical and economic burdens imposed by AMR. New

initiatives like EPI-net can directly counter the existing inadequacies of surveillance systems, such as

fragmentation, heterogeneity, and time lag, and support their advancement

deliverable report wp2: d2.3: results of systematic reviews...nd4bb combacte-magnet deliverable...

Documents