Epidemiology of Clostridium difficile infection in Belgium. C. VALENCIA, M.-L. LAMBERT For the National Reference Laboratory: M. DELMÉE, J.

Transcription

1 Epidemiology of Clostridium difficile infection in Belgium Report 2016 AUTHORS C. VALENCIA, M.-L. LAMBERT For the National Reference Laboratory: M. DELMÉE, J. VAN BROECK

2

3 Epidemiology of Clostridium difficile infection in Belgium Report 2016 Hospital surveillance data Hospital stay data Death registrations AUTHORS C. VALENCIA, M.-L. LAMBERT For the National Reference Laboratory: M. DELMÉE, J. VAN BROECK

4 4 OD Public Health and Surveillance July 2016 Brussels, Belgium Edited by: Boudewijn Catry Internal reference: PHS Report Legal deposit: D/2016/2505/25 ISSN number (paper copy) (e-copy)

5 Executive Summary Clostridium difficile infection (CDI) is a major cause of diarrhoea and pseudomembranous colitis in both acute and chronic healthcare institutions. An increase in incidence has been reported in many countries across the world over the last decade. This increase has been attributed to a number of factors: the rising use of certain antibiotics, an increase in the population at risk (older people) and the emergence of CDI hypervirulent strains. This report summarizes the different sources of available data concerning the epidemiology of CDI in Belgium: national surveillance in hospitals ( ), including data from the national reference laboratory (NRC), hospital stays (RHM/MZG ) and death registration data ( ). Surveillance data Participation in the national surveillance programme of Clostridium difficile in Belgian hospitals was compulsory at least one semester per year between 2008 and In 2015 the first year in which it was no longer mandatory participation remained high, with 140 hospitals participating at least one semester and reporting a cumulative number of 2975 episodes. The median number of reported episodes per hospital, per semester was 9 (maximum 62, minimum 0). For 60% of these episodes, onset of symptoms was 2 days or more after admission in the reporting hospital (definition of hospital-associated CDI, HA-CDI). Episodes of HA-CDI were mainly diagnosed in the geriatrics department (49%), intensive care unit (9%), and onco-haematology (9%) (these figures exclude 20% for whom department of diagnosis was not recorded). Patients were predominantly females (58%); median age was 80 (HA-CDI) and 73 (non HA-CDI); 3% died within 30 days with CDI being considered as directly or indirectly related to their death. These figures are comparable with previous years. The mean incidence of CDI in hospitals in /1000 admissions is the highest reported since (figure 1) Figure 1 Mean incidence of Clostridium difficile infection (CDI) in acute Belgian hospitals Episodes CDI/1000 admissions 2,50 2,00 1,50 1,00 0,50 Hospital associated episodes Total episodes 0, Year 5 Acute hospitals: defined on the basis of mean length of stay <14 days. Mean incidence: sum of episodes/ sum of admissions for all acute hospitals providing data for the whole year. There is a large variability in incidence between hospitals. In 2015, an increase in incidence of HA-CDI was observed in all 3 regions; but it was noteworthy in Flanders, probably related to outbreaks in Limburg and West- Flanders. Differences between provinces are shown below. Although Flanders still has the lowest CDI incidence and Wallonia the highest, the differences between regions in 2015 are negligible.

6 Figure 2 Mean incidence of hospital- associated Clostridium difficile infections per hospital days in acute hospitals, by province. Belgium, Mean incidence: sum of episodes / sum of hospital-days for all acute hospitals providing data (one or two semesters) in Categories based on quartiles of the incidence distribution. In 2015, 97 hospitals participating in the surveillance programme sent isolates to the NRC; 689 isolates met the criteria of the surveillance protocol (first five strains typed in one hospital during a semester). Ribotyping of these 689 isolates resulted in the identification of 138 ribotypes of which 86 were encountered only once. The most prevalent ribotype was BR014 (UCL16) (67/689, 10%). The most notable change compared to the previous year is the spread of the hypervirulent strain BR078 (UCL 3), identified in 42% of the reporting hospitals in Ribotype 027 was isolated in 34% of the hospitals in 2009 and 16% in Table 1 Top 5 CDI ribotypes isolated within the national surveillance programme, by the number of hospitals in which they are isolated. Belgium, Year N hospitals sending strains for typing (100%) N hospitals with... BR014 (UCL16) BR078 (UCL3) BR020 (UCL16a) BR002 (UCL32) BR106 (UCL48d) N % N % N % N % N % Hospital stay (RHM/MZG) Because this data collection dates back to 1999, counting the number of hospital stays with ICD-9-CM code (intestinal infections due to Clostridium difficile) allowed for a long time trend analysis, and because of its

7 exhaustive nature, a measure of the burden of disease and a validation of surveillance data. In 2013 (last available data), 3989 hospital stays included a CDI (primary or secondary) diagnosis, translating into an incidence of CDI in hospital of 36/ population, and 2.03/1000 admissions. This later incidence is 25% higher than the corresponding incidence computed from surveillance data, but trends observed are similar. Death registration data In 2013 (latest year available), 78 deaths could be attributed to CDI (death certificates with underlying cause of death code ICD-10 A04.7 death due to a Clostridium difficile related enterocolitis ). This figure shows a constant decline since a peak of 137 deaths in Age-standardised specific mortality rate in 2013 was 0.61/ inhabitants (1.20 in 2009). Brussels has the highest standardised mortality rate, followed by Flanders and Wallonia. Research project: transmission of CDI in Belgian hospitals A research project was initiated in The objectives were (1) to measure what proportion of HA-CDI results from transmission from symptomatic episodes within the same hospital, and (2) to study how transmission varies between hospitals in Belgium. Between January 2015 and January 2016, 30 hospitals participating in the study were requested to send all their Clostridium difficile strains for typing to the NRC. In a subset of 28 hospitals with more complete data (more than 65% of all strains ribotyped), the proportion of HA-CDI that could be related to another episode with the same ribotype less than one month before in the same hospital varied from 0% to 51% (average 25%). MLVA typing is required to establish a definitive genetic link between episodes with the same ribotype. It has started in June 2016 in the NRC. International comparisons In an (yet unpublished) 2015 ECDC study comparing CDI rates in hospitalised patients across European countries, Belgium has the lowest CDI incidence; however differences in surveillance methods make comparisons difficult. The future of CDI surveillance in Belgium The transition from the obsolete NSIHweb1 to the new Health data collection system is expected to be completed by the end of Belgian CDI surveillance data will be submitted to the ECDC database in October Key points The key points from data available in 2015 are: Participation of Belgian hospitals in CDI surveillance has remained high despite the fact that it was no longer compulsory The mean incidence of CDI in Belgian hospitals (1.87/1000 admissions) is the highest reported since The increase in HA-CDI incidence was marked in Flanders. The differences between regions are now negligible. The severity of the disease has not changed in recent years. There is a high diversity of circulating Clostridium difficile strains in Belgium, pointing to a large diversity of sources of transmission. The hypervirulent strain BR078 (UCL 3) was found in 42% of the hospitals (25% in 2014). Preliminary results from the 2015 CDI transmission study point to a relatively low proportion of HA-CDI episodes in Belgian hospitals that can be attributable to in-hospital transmission from CDI symptomatic cases Belgium has the lowest incidence of CDI reported in European countries; however differences in surveillance methods make comparisons difficult. 7

8

9 Table of contents Executive Summary...5 Glossary Introduction Clostridium difficile infection Epidemiology CDI surveillance in Belgian Hospitals The national reference laboratory The ECDC CDI protocol Objectives of this report Methodology Hospital epidemiological surveillance programme co-ordinated by the Scientific Institute of Public Health (WIV-ISP) Hospital stay data Death Registration Data Reference Laboratory data Denominator data Rate Calculations Linkage of patient episode information and ribotyping data Results Hospital surveillance data Annual incidence Variation in CDI incidence in Belgium Seasonal variation Hospital stay (RHM/MZK) data Death registration data Microbiological surveillance National Laboratory Reference Centre (NRC-CD) data Participation Ribotype distribution Trends in ribotype prevalence Study on the transmission of C. difficile in Belgian hospitals International comparisons Discussion and conclusions Discussion Conclusions and key points for CDI surveillance ANNEX Changes for the 2016 surveillance (following the 2015 CDI working group meeting) Outcome of 2015 Working Group meeting Distribution of incidence of hospital associated Clostridium difficile infections (CDI in Belgium) Incidence of Clostridium difficile infection in chronic hospitals Variation of CDI in acute Hospital by region Flanders Wallonia Brussels Reference laboratory (NRC-CD) methods

10 Ribotyping MLVA International comparisons (ECDC data) Interim Study report: transmission of Clostridium difficile infection (CDI) in Belgian Hospitals Background Definitions Episodes registered, samples sent to reference laboratory ribotypes Total eligible episodes, hospital-associated episodes, proportion processed by reference laboratory Recurrent Episodes Possible secondary CDI episodes Conclusions Reference List

11 List of tables Table 1 Table 2 Table 3 Epidemiological surveillance of Clostridium difficile infection (CDI): hospital participation Belgium Epidemiological surveillance of Clostridium difficile infection (CDI): age distribution, Belgium Epidemiological surveillance of Clostridium difficile infection (CDI): episodes of CDI in hospitalized patients in Belgian hospitals Table 4 Complications in patients with Clostridium difficile infection (CDI) in Belgian hospitals, Table 5 Department of diagnosis for hospital-associated Clostridium difficile infections (CDI), Table 6 Incidence of infection with Clostridium difficile (CDI) in acute care $ Belgian hospitals, : surveillance data...19 Table 7 Table 8 Hospital associated Clostridium difficile infections (CDI) per hospital days in acute hospitals $, by region - Belgium, Hospital stays and incidence of Clostridium difficile infection (CDI) using hospital stay data, Table 9 Mean incidence of Clostridium difficile infections (CDI) per 1000 admissions, Belgium, , according to data source...24 Table 10 Deaths attributed to enterocolitis due to Clostridium difficile* by region, Belgium Table 11 Number of samples sent to NRC-CD by local laboratories in Table 12 Number of the most common ribotypes isolated in 2015 by province, Belgium...26 Table 13 Number of isolates included in the surveillance programme and description of the most common ribotypes, Belgium Table 14 Participation in the surveillance programme (by hospital site) and evolution of the most common ribotypes, Belgium Table 15 Table 16 Incidence of hospital associated Clostridium difficile (HA-CDI) in chronic $ care Belgian hospitals, : surveillance data...34 Equivalent European (Brazier- BR) and Belgian (UCL) classification of Clostridium difficile ribotypes...37 Table 17 International comparison of incidence of Clostridium difficile infection in hospitals Table 18 CDI rates in published national reports, EU/EEA, Table 19 Number of episodes, and samples received by the reference laboratory, Jan-Dec Table 20 Number of recurrent episodes per patient...43

12 List of figures Figure 1 Figure 2 Mean annual incidence of infection with Clostridium difficile (CDI) total cases and hospital associated cases /1000 admissions, in acute care $ Belgian hospitals, Hospital associated Clostridium difficile infections (CDI) per hospital days in acute hospitals $, by region - Belgium, Figure 3 Distribution of incidence of hospital associated Clostridium difficile infections (CDI) per hospital days in acute hospitals $, by region. Belgium, Figure 4 Funnel plots of CDI incidence per 10,000 hospital days in acute hospitals $, Belgium, Figure 5 Monthly incidence (moving average*) of Clostridium difficile infections (CDI) in Belgian hospitals per 1000 admissions Figure 6 Hospital stays with an intestinal infection due to Clostridium difficile* (CDI), Belgium Figure 7 Clostridium difficile infections (CDI): age-standardised mortality rate, by region, Belgium Figure 8 Figure 9 Evolution of number of isolates belonging to the most common ribotypes in Belgian hospitals Evolution of the percentage of ribotypes belonging to the most common ribotypes in Belgian hospitals Figure 10 Evolution of the frequency of the most commonly identified ribotypes in Belgian hospitals, Figure 11 Distribution of incidence of hospital associated Clostridium difficile infections (CDI) in Belgium, per hospital days comparison of acute and chronic hospitals, Figure 12 Funnel plot of CDI incidence per 10,000 hospital days in acute hospitals $ in Flanders, Figure 13 Funnel plot of CDI incidence per 10,000 hospital days in acute hospitals $ in Wallonia, Figure 14 Funnel plot of CDI incidence per 10,000 hospital days in acute hospitals $ in Brussels, Figure 15 Example of trace obtained by capillary electrophoresis for ribotyping...36 Figure 16 Clostridium difficile ribotypes detections reported in national surveillance reports, EU/EEA,

13 Glossary CDI CI HA-CDI CA-CDI ECDC EIA LTCF ICD-10 ICD-9-CM ICU INAMI/RIZIV LoS LTCF MRSA MLVA N or n NAAT NRC-CD PCR Popn Pts RHM/MZG RNA RR EU UK US WIV-ISP Clostridium difficile infection Confidence interval Hospital-associated Clostridium difficile infection (onset of diarrhoea 2 days or more after admission in declaring hospital) Community associated Clostridium difficile infection (onset of diarrhoea less than two days after admission to hospital with no previous admission to any hospital or long term care facility in previous 12 weeks) European centre for disease prevention and control Toxi Enzyme immunoassay Long term care facility International Classification of Diseases, 10th Revision International Classification of Diseases, 9th Revision, Clinical Modification Intensive care unit Institut national d assurance maladie-invalidité / Rijksinstituut voor ziekte- en invaliditeitsverzekering Length of stay Long term care facility Methicillin resistant Staphylococcus aureus Multi Locus Variable number tandem repeat Analysis Number Nucleic acid amplification test National reference centre (laboratory) Clostridium difficile Polymerase chain reaction Population Patients Résumés hospitaliers minima/ Minimale ziekenhuis gegevens (minimum hospital data set) Ribonucleic acid Relative risk or risk ratio European Union United Kingdom United States L Institut Scientifique de Santé Publique 13

14

15 1. Introduction 1.1. Clostridium difficile infection Clostridium difficile is an anaerobic, spore-forming bacterium which can colonize the intestine of humans and animals. Pathogenic C. difficile strains produce protein toxins (toxin A and/or B, and/or binary toxin) that disrupt the intestinal wall and thereby cause mild diarrhoea, severe colitis or a life-threatening toxic megacolon depending on host susceptibility and the virulence of the infecting strain (1). The diagnosis of C. difficile infection (CDI) is based on clinical symptoms (diarrhoeal stools or toxic megacolon), and either a positive laboratory assay for C. difficile toxin A and/or B in stools or a toxin-producing C. difficile organism detected in stool via culture or other means, or endoscopy, or histopathology (2). Additionally, C. difficile can be subtyped by Polymerase chain reaction (PCR) ribotyping using the type dependent differences in profiles generated by PCR amplification of the intergenic spacer regions between the 23S and 16S rrna genes (3) Epidemiology In 2004, several Canadian publications reported a significant increase in the incidence of Clostridium difficile infections (CDIs) in the country over the last two years (4, 5). In the elder population, mortality was higher with the increase in severity of the cases (6). Strains isolated during the Canadian outbreak belonged mainly to toxinotype III (or ribotype 027) which produced higher amounts of toxin A and B than usual. In addition, such strains produced a third toxin (binary toxin) and were resistant to multiple antibiotics including the fluoroquinolones (7). In September 2005, this strain was identified for the first time in Belgium (8), and in 2006 in France (9). The existence and identification of this strain, as well as the increased number of people with risk factors (age, immunodepression ) contributed to the increase of CDIs. Transmission of C. difficile in the hospital setting is common, though one recent study from the UK suggested other sources of infection since 45% of the CDI cases in one region was caused by a strain that was genetically different from all previous CDI cases (10). In Belgium CDI incidence more than doubled between 1999 and 2007, and is more or less stable since 2010 at 1.50 episodes of CDI for 1000 admissions. The incidence peaked in and then declined from CDI surveillance in Belgian Hospitals Given the increasing incidence of CDIs and the emergence of virulent strains, the Belgian Infection Control Society (BICS) in collaboration with the Scientific Institute of Public Health (WIV-ISP) organized a national surveillance system to monitor the incidence of CDIs in the country. From July 2007 until December 2014, participation in CDI surveillance was mandatory for one semester per year for all non-psychiatric hospitals. As of 2015, the participation in this surveillance is no longer mandatory. There is, however, a requirement for hospitals to participate in at least one of four surveillance programs (C. difficile infections, vancomycin-resistant enterococci, pneumonia and bloodstream infections in intensive care units, surgical site infections) The national reference laboratory The National laboratory Reference Centre for Clostridium difficile (NRC-CD) was officially established in 2011 but has been actively involved in the national surveillance since It is hosted at the Catholic University of Louvain on the site of Woluwe-St-Lambert, Brussels The ECDC CDI protocol In May 2015, the ECDC CDI surveillance protocol version 2.1 became available after the European Surveillance of Clostridium difficile Infections (ECDIS-Net) pilot; it was officially launched in January The protocol suggests member states to adhere to one of the three surveillance options (15).

16 1. Minimal surveillance: aggregate hospital denominator and numerator, diagnostic algorithms, testing frequency 2. Light surveillance: minimal + case-based numerator data 3. Enhanced surveillance: light + descriptive microbiology (eg. ribotyping).(this is very similar to the Belgian surveillance protocol) In 2016, the ECDC launched the European CDI surveillance. Preliminary data from 18 countries (2016) lead to an estimation of health-care associated CDI at European level is 3.0/10,000 hospital days and the total (HA+CA) CDI is 3.8/10,000 hospital days. 81% of all CDI in Europe are health-care associated, a number which is much higher than those reported by individual European countries (refer to section 3.6 international comparisons). In 2017 the first European CDI report will become available which will allow for better country comparison Objectives of this report The objective of this report is to describe the epidemiology of Clostridium difficile infection in Belgium. For this 2016 report, we have analysed the latest data available: Hospital surveillance data (including reference laboratory data) for the years Hospital stay data for the years Death registration data for the years

17 2. Methodology 2.1. Hospital epidemiological surveillance programme co-ordinated by the Scientific Institute of Public Health (WIV-ISP) The methods are described in detail in the protocol, available online in French and Dutch: The data analysed for this report are for the period 1st January December 2015 An electronic information portal collects the surveillance data for cases of C. difficile (NSIH Web 1). An episode of Clostridium difficile infection (CDI) is defined as a case which fulfils one or more of the following criteria: 1. Diarrhoea* or toxic megacolon, and a laboratory test confirmed for C. difficile toxin A and/or B in the stool or a strain producing toxins identified in the stools, by culture or another method 2. Pseudomembranous colitis observed by proctocolonoscopy of the lower gastro-intestinal tract 3. Histopathology characteristic of C. difficile in the colon (with or without diarrhoea) obtained by biopsy during endoscopy, colectomy or autopsy *At least three liquid or non-formed stools (the stools take the form of the container) during 24 hours or less. Hospital-associated CDI (HA-CDI) is defined in this report as CDI with an onset of diarrhoea 2 days or more after admission in the declaring hospital (onset date admission date 2) Hospital stay data In Belgium, each hospital stay gives rise to a registration (RHM/MZG minimum hospital data set). Diagnoses are coded using ICD-9-CM (International Classification of Diseases, 9th Revision, Clinical Modification) (11). We analysed the hospital stays with a code (Intestinal infections due to C. difficile) from 1999 to 2013 (latest available year). The diagnoses are classified as primary diagnosis the pathology considered to explain the most of the hospital stay most commonly, but not necessarily, the reason for admission), and secondary diagnosis Death Registration Data Death certificates in Belgium are coded according to ICD-10 (11) system. We counted deaths with code A04.7 as underlying cause of death: death due to a Clostridium difficile related enterocolitis for the years (latest available data). The underlying cause of death is the original disease causing the chain of events immediately leading to death. Death registrations data have been extracted from the database of causes of death in Belgium, provided by DGSIE ( Statistics Belgium ) (12). The age standardised mortality rate is based on direct standardisation using as a standard the mid-year population figures for 2005 (13); and using three age groups: 0-64, 65-79, > 80 years Deaths are counted according to region of death, not according to region of residence of the deceased. The denominator for each region remains as the resident population of the region Reference Laboratory data Since 2007, the surveillance program has included a mandatory bacteriological component for every participating Belgian hospital clinical laboratory. It requires each hospital laboratory to send five consecutively isolated C. difficile strains during one semester of the year, with additional accompanying information as listed on the website of the WIV-ISP (available in French and Dutch) and download_nl.asp

18 In addition, a hospital may send locally isolated strains to the reference laboratory for typing in order to support the investigation of local increases in the number of cases or suspected outbreaks. Each received sample is confirmed and typed. The currently applied method of ribotyping is that which is used in the majority of European reference centres. The details of the typing techniques are presented in the Annex Denominator data Participating hospitals provide the institute with the monthly number of patient admissions and the number of patients-days for the corresponding surveillance period. One-day admissions are excluded. These denominator data are used to calculate the annual incidence rates presented in this report Rate Calculations Mean incidence rate per 1,000 patient admissions= per year 1,000 Mean incidence rate per 10,000 days of hospitalization = per year 10, Linkage of patient episode information and ribotyping data Linkage is established between the epidemiological data from the hospital surveillance programme (NISHweb1 case based reporting) and the reference laboratory ribotyping data through the automatic code generated in NSIHweb1. This code is then sent (as part of the patient information) by the hospital laboratory, together with the patient sample to the NRC-CD for ribotyping. 18

19 3. Results 3.1. Hospital surveillance data The data analysed was last updated on 10 Apr The participation of hospitals remained high in 2015, despite the fact that participation became voluntary. Table 1 Epidemiological surveillance of Clostridium difficile infection (CDI): hospital participation Belgium Year N hospitals participating at least 1 semester/ year N hospitals participating 2 semesters/year Total hospital-semesters % hospital-semesters reporting no cases 11% 10% 8% 8% 10% 11% 10% 7% In 2015, the median reported per semester (P25-P75) was 9 (4-17) episodes per hospital with a maximum of 62 episodes and a minimum of 0. In 2015, there were 2799 patients, of whom 58% were female. The median age of patients with HA-CDI was 80 whereas for other cases was 73. This is similar to previous years ( ). The age distribution of cases varied little between 2008 and 2015 and has remained consistent with what is reported in Table 2 for the year 2015 Table 2 Epidemiological surveillance of Clostridium difficile infection (CDI): age distribution, Belgium 2015 Age group No. of patients % max Total Table 3 describes episodes of CDI in hospitalised patients in Belgium for the period There continues to be an increase in the proportion of community associated cases (CA-CDI) between 2008 and There has been an increase in the proportion of recurrent episodes between Table 3 Epidemiological surveillance of Clostridium difficile infection (CDI): episodes of CDI in hospitalized patients in Belgian hospitals Year Episodes Total episodes reported Episodes with hospital-associated (HA) 65% 62% 62% 63% 61% 60% 59% CDI* (%) 60% For episodes other than HA-CDI Suspected origin of infection Community 56% 57% 59% 60% 63% 62% 63% 67% Declaring hospital** 18% 17% 17% 18% 16% 15% 17% 15% Other hospital 16% 14% 12% 10% 10% 10% 8% 9% Unknown/missing 10% 12% 11% 12% 12% 12% 11% 9% Recurrent episodes*** (%) Yes 16% 12% 12% 11% 13% 13% 12% 15% No 68% 70% 69% 72% 67% 68% 72% 70% Unknown 16% 18% 19% 16% 20% 18% 16% 16% 19 * Defined as onset of diarrhoea 2 days or more after admission in the declaring hospital (onset date admission date >=2) ** Declaring hospital : episodes with onset less than 2 days after admission subjectively thought to have their origin in the declaring hospital (eg readmissions within 4 weeks after discharge ) *** Defined as the proportion of episodes which are recurrent, and not the incidence of recurrences in patients presenting with a new episode of CDI

20 The severity of the disease appears to remain stable in the last years Table 4 Complications in patients with Clostridium difficile infection (CDI) in Belgian hospitals, Year N Patients Death within 30 days of onset CDI indirect or direct cause (% ) 3 Pseudomembranous colitis, ICU or surgery (colectomy) (%) 2 Any severe complications* No complications (%) Unknown/missing (%) * Severe complication: death (as a direct or indirect result of CDI) within 30 days of onset of infection, or pseudomembranous colitis, or admission to the intensive care unit or colectomy as a result of CDI ICU- Intensive care unit For 20% of cases, the specialty of the department where the patient was diagnosed is not recorded. For the remaining patients approximately 60% of cases for whom department of diagnosis was recorded arise from four geriatrics, intensive care (ICU), onco-haematology and gastroenterology. Almost half (48.8%) of the hospital-associated CDI had their onset in the geriatric department. (Table 5). Table 5 Department of diagnosis for hospital-associated Clostridium difficile infections (CDI), Belgium, 2015 Department Frequency % Geriatrics Intensive care (ICU) Haemato-oncology Internal medicine Gastro-enterology Respiratory medicine Nephrology/haemodialysis General Medicine Cardiology Other Total Annual incidence In 2015, the mean incidence (for HA-CDI, other episodes and total episodes) has increased and is the highest reported to date for the number of HA-CDI per 10,000 days of hospitalisation (Table 6) 20

21 Table 6 Incidence of infection with Clostridium difficile (CDI) in acute care $ Belgian hospitals, : surveillance data Year Denominators N hospitals included in the calculation of incidence (hospitals participating for whole year only) Hospital associated episodes (HA-CDI)* N / 10,000 days of hospitalisation : Mean Incidence** Median / 1000 admissions Mean incidence ** Median Other episodes N / 1000 admissions Mean Incidence ** Median Total episodes N /1000 admissions Mean Incidence** Median * Defined as onset of diarrhoea 2 days or more after admission in the declaring hospital (onset date admission date >2) ** Mean Incidence: total episodes/total denominator, acute hospitals $ Acute hospitals: defined on the basis of mean length of stay <14 days The overall incidence of CDI for both acute and chronic hospitals has declined between however there has been an increase in incidence between for both hospital-associated and non-hospital associated CDI cases. Incidence for HA-CDI is the highest since Figure 1 Episodes CDI/1000 admissions 2,50 2,00 1,50 1,00 0,50 Mean annual incidence of infection with Clostridium difficile (CDI) total cases and hospital associated cases /1000 admissions, in acute care $ Belgian hospitals, Hospital associated episodes Total episodes 21 0, Year * Only acute hospitals providing data for the whole year are included. $ Acute hospitals: defined on the basis of mean length of stay <14 days

22 Table 7 shows the mean incidence of HA-CDI in acute hospitals, comparing the three regions of Belgium from The increase in incidence in 2015 has been observed in the 3 regions, but was more marked in Flanders. Since 2010, the mean incidence has consistently been lowest in Flanders and highest in Wallonia. However the differences between regions have decreased in Table 7 Hospital associated Clostridium difficile infections (CDI) per hospital days in acute hospitals $, by region, Belgium, Year Flanders N hospitals Mean incidence Median Wallonia N hospitals Mean incidence Median Brussels N hospitals Mean incidence Median Figure 2 Episodes HA CDI per hospital days $ Acute hospitals: defined on the basis of mean length of stay <14 days * Only hospitals providing data for the whole year are included. Mean incidence: total episodes/total denominators. 2,5 2 1,5 1 0,5 Hospital associated Clostridium difficile infections (CDI) per hospital days in acute hospitals $, by region, Belgium, Flanders Wallonie Brussels Belgium Year $ Acute hospitals: defined on the basis of mean length of stay <14 days Only hospitals providing data for the whole year are included. Mean incidence: total episodes/total denominators.

23 Variation in CDI incidence in Belgium Figure 4 shows the wide variation in incidence between hospitals in each of the three regions Figure 3 Distribution of incidence of hospital associated Clostridium difficile infections (CDI) per hospital days in acute hospitals $, by region. Belgium, Flanders Wallonia Hospital-associated CDI per hosp_days Hospital-associated CDI per hosp_days Brussels Hospital-associated CDI per hosp_days Hospital-associated CDI per hosp_days $ Acute hospitals: defined on the basis of mean length of stay <14 days Only hospitals providing data for the whole year are included All Funnel plots, like the one in Figure 5, are a graphical aid for institutional comparisons, where an estimate of the parameter (here: incidence of HA-CDI) is plotted against a measure of its precision (here: number of hospital-days). Indeed in smaller hospitals chance variation is larger. Funnel plot allow a visual identification of outliers (those falling of 95% or 99.8% confidence intervals) (14). Region specific funnel plots can be found in the Annex. 23

24 Figure 4 Funnel plots of CDI incidence per 10,000 hospital days in acute hospitals $, Belgium, 2015 $ Each dot represents a hospital-semester. Acute hospitals defined by mean length of stay <14 days Seasonal variation Figure 6 shows a seasonal peak of incidence during January to April. HA-CDI largely follows the same pattern as other cases, although for the year 2015, the peak occurring in January is the largest observed since Figure 5 Monthly incidence (moving average*) of Clostridium difficile infections (CDI) in Belgian hospitals per 1000 admissions Only acute and chronic hospitals providing data for the whole year are included. *Moving average: each monthly incidence is the mean of the month, the preceding month and the following month.

25 3.2. Hospital stay (RHM/MZK) data Hospital stay records mentioning a primary or a secondary diagnostic code of Intestinal infection due to Clostridium difficile almost tripled between 1999 and 2008, reaching a peak in 2008, subsided again between but has risen again in the year See Table 8 and Figure 7. The percentage of stays with a primary diagnostic code of CDI presumed in this case to be the reason for admission remains stable in 2013 (25%). Table 8 Hospital stays and incidence of Clostridium difficile infection (CDI) using hospital stay data, Belgium, N CDI* primary diagnostic secondary diagnostic Total/1000 admissions Total/100,000 population Total no. cases CDI *code ICD-9_CM Population of Belgium (21) Figure 6 Hospital stays with an intestinal infection due to Clostridium difficile* (CDI), Belgium Episodes CDI/1000 admissions CDI=primary diagnosis Total CDI diagnoses 3,00 2,50 2,00 1,50 1,00 0,50 0, Year * code ICD-9_CM * So: hospital stay data, Ministry of Health 25

26 Table 9 shows CDI incidence measured using hospital stay data is 25% higher than CDI incidence using surveillance data. However, differences between the two measures remain approximately constant, indicating that the surveillance data provide a valid measure of incidence trends for CDI. Table 9 Mean incidence of Clostridium difficile infections (CDI) per 1000 admissions, Belgium, , according to data source Hospital stay (administrative) data (RHM/ MZG)(a) Surveillance data (acute and chronic hospitals) (b) a/b (*100) 127% 134% 134% 125% 130% 125% RHM/MZG: Resumés hospitaliers minima/ Minimale ziekenhuis gegevens (minimum hospital data set) 3.3. Death registration data The following data are taken from death certificates recording underlying cause of death as enterocolitis due to Clostridium difficile (Code ICD-10 A04.7). Table 10 Deaths attributed to enterocolitis due to Clostridium difficile* by region, Belgium Number of death certificates with ICD-10 code A04.7 as underlying cause of death Brussels Flanders Wallonia 3 3 NA NA NA Belgium 8 9 NA NA NA Crude specific mortality rate per inhabitants Brussels Flanders Wallonia NA NA NA Belgium NA NA NA * code ICD-10 A 04.7 Mortality rates from enterocolitis due to Clostridium difficile increased rapidly from 1998 until Since 2006, there has been a decline in deaths attributable to Clostridium difficile. In 2013, mortality due to Clostridium difficile has continued to decrease in Brussels and Flanders; however it has increased in Wallonia. Brussels has the highest standardised mortality rate, followed by Wallonia and Flanders and (see Figure 8). 26

27 Figure 7 Clostridium difficile infections (CDI): age-standardised mortality rate, by region, Belgium ,00 No. deaths per inhabitants 6,00 5,00 4,00 3,00 2,00 1,00 0, Enterocolitis due to Clostridium difficile as underlying cause of death (Code ICD-10 A04.7). Direct standardisation using Belgian mid-year 2005 population as reference population, according to 3 age groups (0-64, 65-79, 80+) Microbiological surveillance National Laboratory Reference Centre (NRC-CD) data Participation Belgique Bruxelles Flandre Wallonie In 2015, 97 different hospital sites participated in the annual surveillance program, of which 52 participated during both semesters. Table 11 lists the distribution of laboratories according to the number of samples sent as part of the annual surveillance. Thirty four laboratories sent more than 10 isolates most because of their participation to a national study. Table 11 Number of samples sent to NRC-CD by local laboratories in 2015 No. of isolates sent to NRC-CD No. of local laboratories >10 34 Total: In total, 2011 isolates were received by the NRC-CD in Among these, 108 (5.3%) isolates were not confirmed as Clostridium difficile (other species identified or culture not possible). For those laboratories exceeding their quota of 5 isolates per semester, only the first five samples were entered into the calculation in table 13. A total of 689 isolates were considered and ribotyped. This number is higher than that of the preceding year (616) and the highest number since surveillance was started.

28 Ribotype distribution Ribotyping of these 689 isolates in 2015 resulted in the identification of 138 different ribotypes of which 86 were only encountered a single time, 1 twice and 14 three times. The most common ribotypes are found across most of the regions of the country (see Table 12). Table 12 Number of the most common ribotypes isolated in 2015 by province, Belgium Ribotypes 2015 BR014 BR078 BR020 BR002 BR005 BR106 BR027 UCL 16L BR001 UCL 23f BR023 BR126 BR015 BR012 BR076 BR070 Antwerpen Vlaams-Brabant Brabant wallon Bruxelles / Brussel West Vlaanderen Oost-Vlaanderen Hainaut Liège Limburg Luxembourg 1 1 Namur Trends in ribotype prevalence Table 13 shows the most common ribotypes typed as part of the surveillance programme. Table 14 shows how many hospitals (and the percentage of participating hospitals) where these ribotypes were isolated. These tables also show the change in prevalence of these ribotypes over time ( ). As indicated in Table 13 and Table 14, ribotype BR027 as a proportion of all ribotypes isolated in 2015 continued to decline (2.6% in 2015 versus 3.2% in 2014). The number of hospitals where this ribotype was isolated (15 versus 14) increased slightly but stays a minority (15, 5%). The outbreak of this ribotype detected in West Flanders in 2014 continued in Ribotype BR014 (UCL16) remains, as in 2011, 2012, 2013 and 2014, the most prevalent ribotype, slightly decreasing in proportion to other ribotypes since last year (9.7% in 2015 versus 11.5% in 2014) but the number of hospital sites affected (47.4 versus 37.5)increased. Ribotypes BR002 (UCL32 and UCL 32*) and BR078 (UCL3) occupy positions 2 and 4 for the most commonly isolated ribotypes and all have increased since last year. Ribotype BR020 (UCL16a and UCL16a*) is the third most frequent ribotype but decreased from 9.6% in 2014 to 7.9% in Ribotype BR070 (UCL47) continues its decline. It was isolated 10 times in 2015 (1.4% of all ribotypes), 17 times in 2014 (2.8%) and 29 times in 2013 (4.9%) and was found in 10 different hospitals in 2015 (versus 14 in 2014 and 12 in 2013). The proportion of isolates that are typed as ribotype BR106 (UCL48d) continues to rise, after its emergence in Twenty four isolates were found in 21 different hospitals in 2015 (versus 20 isolates in 18 hospitals in 2014).

29 Table 13 Number of isolates included in the surveillance programme and description of the most common ribotypes, Belgium ECHANTILLONS Total N of strains that were typed N Strains BR027 (UCL027) % 18,5 12,3 7,8 4,9 3,76 3,2 2,6 N Strains BR014 (UCL 16) % 11,3 10,1 12,1 10,3 8,55 11,5 9,7 N Strains BR078 (UCL 3) % 3,3 6,5 7,6 7,4 5,13 6,7 8,7 N Strains BR020 (UCL16a, UCL16a*) % 5,14 6,14 6,71 8,64 7,18 9,4 8 N Strains BR002 (UCL32, UCL32*) % 3,86 4,16 8,01 8,02 6,15 6 6,2 N StrainsBR070 (UCL 47) % 1,54 4,96 2,8 1,4 N Strains BR106 (UCL 48d) % 1,08 3,08 3,6 3,4 N Strains BR087 (UCL 24) % 1,19 2,8 1 N Strains BR005 (UCL 46) % 2,8 3,4 4,7 2,7 3,4 2,9 4,2 N Strains BR106 (UCL 48d) % 3,2 3,6 3,5 N Strains UCL 16L % 2,1 3,3 2,2 2,8 2,6 N Strains BR023 (UCL 4) % 3,1 2,1 2,4 2,5 2,4 2,4 N Strains UCL 23f % 2 1,9 2,5 2,5 N Strains BR126 (UCL 5a) % 2 2,5 3,2 2,5 N Strains BR001 (UCL 23e) % 4,7 2,1 2,2 3,4 2,6 N 14 Strains BR015 (UCL 23) % 2 N Strains BR012 (UCL 44) % 2,4 1,7 N 9 12 Strains BR076 (UCL 16b) % 2 1,7 N 9 Strains BR029 (UCL 28) % 1,3 N 7 Strains BR 017(UCL 14) % 1 N 7 Strains UCL 22 % 1 29

30 Table 14 Participation in the surveillance programme (by hospital site) and evolution of the most common ribotypes, Belgium PARTICIPATIONS A LA SURVEILLANCE N of hospitals that sent strains for typing N Hospitals with BR027 (UCL027) % 33,6 33,0 20,2 17,1 14,6 12,5 15,5 N Hospitals with BR014 (UCL16) % 33,6 33,0 38,0 40,5 36,9 37,5 47,4 N Hospitals with BR078 (UCL 3) % 10,6 25,3 23,8 31,5 24,3 25,0 42,3 N Hospitals with BR020 (UCL16a,UCL16a*) % 37,8 28,2 36,6 36,1 N Hospitals with BR002 (UCL32, UCL32*) % 35,1 27,2 24,1 30,9 N Hospitals with BR070 (UCL47) % 9,0 23,3 12,5 10,3 N Hospitals with BR106 (UCL48d) % 5,4 12,6 16,0 21,6 N 13 7 Hospitals with BR087 (UCL 24) % 11,6 7,2 N 25 Hospitals with BR005 (UCL 46) % 25,8 N Hospitals with BR106 (UCL 48d) % 5,4 12, ,6 N 14 Hospitals with UCL 16L % 14,4 N 14 Hospitals with BR023 (UCL 4) % 14,4 N 13 Hospitals with UCL 23f % 13,4 N 15 Hospitals with BR126 (UCL 5a) % 15,5 N 14 Hospitals with BR001 (UCL 23e) % 14,4 N 10 Hospitals with BR015 (UCL 23) % 10,3 N 12 Hospitals with BR012 (UCL 44) % 12,4 N 11 Hospitals with BR076 (UCL 16b) % 11,3 N 9 Hospitals with BR029 (UCL 28) % 9,3 N 7 Hospitals with BR 017(UCL 14) % 7,2 N 7 Hospitals with UCL 22 % 7,2

31 Figure 9 and Figure 10 illustrate the evolution of the most common ribotypes in number and percentage. Figure 8 Evolution of number of isolates belonging to the most common ribotypes in Belgian hospitals Figure 9 Evolution of the percentage of ribotypes belonging to the most common ribotypes in Belgian hospitals Figure 10 Evolution of the frequency of the most commonly identified ribotypes in Belgian hospitals, RIBO N=389 RIBO N=505 RIBO N=462 RIBO N=648 RIBO N=590 RIBO N=582 RIBO N=689 BR027 18,50 % BR027 12,2 % BR014 12,1 % BR014 10,5 % BR014 8,5 % BR014 12,2 % BR014 9,7 % BR014 11,30 % BR014 10,1 % BR002 8 % BR020 8,8 % BR020 7,1 % BR020 9,6 % BR078 8,7 % BR020 5,10 % BR078 6,5 % BR027 7,8 % BR002 8,2 % BR002 6,1 % BR078 6,5 % BR020 7,9 % BR001 4,10 % BR020 6,1 % BR078 7,6 % BR078 7,5 % BR078 5,1 % BR002 6,2 % BR002 6,2 % BR002 3,80 % BR001 4,7 % BR020 6,7 % BR027 5 % BR070 4,9 % BR027 4,0 % BR005 4,2 % BR015 3,60 % BR002 4,1 % BR005 4,7 % BR005 2,7 % BR027 3,7 % BR106 3,8 % BR106 3,5 % BR078 3,30 % BR005 3,36 % UCL16L 3,3 % UCL23f 1,9 % BR005 3,4 % BR005 3,6 % BR027 2,6 % BR005 2,80 % BR023 3,10 % UCL 26 2,6 % BR012 1,7 % BR106 3,1 % BR126 3,3 % BR001 2,6 % BR076 2,60 % BR076 2,40 % BR001 2,1 % BR070 1,6 % UCL23f 2,5 % BR087 3,1 % UCL16L 2,6 % BR003 2,60 % BR012 2,40 % BR023 2,1 % BR106 1,1 % BR012 1,7 % BR070 2,9 % BR023 2,5 % BR056 1,90 % UCL16L 2,10 % UCL23f 2 % BR017 <1 % BR017 <1 % UCL16L 2,7 % UCL23f 2,5 % BR012 1,50 % BR126 2,00 % BR012 2 % BR001 2,4 % BR126 2,5 % BR126 1,50 % BR015 1,80 % BR076 1,7 % BR023 2,1 % BR015 2,0 % BR023 1,00 % BR056 1,10 % BR106 <1 % UCL23f 2,1 % BR012 1,7 % UCL 26 0,50 % BR003 0,90 % BR017 <1 % UCL 35 1,7 % BR076 1,7 % UCL16L 0,50 % UCL 26 0,60 % BR070 <1 % BR012 1,7 % BR070 1,5 % UCL23f 0,00 % UCL23f 0,00 % BR015 0,87 % BR076 1,7 % BR029 1,3 % BR126 0,87 % BR015 1,5 % BR017 1,0 % BR056 0,87 % BR056 1,4 % UCL 22 1,0 % BR003 0,43 % BR081 1,2 % BR087 1,0 % 31

32 3.5. Study on the transmission of C. difficile in Belgian hospitals The objectives of this study are (1) to measure what proportion of hospital-associated Clostridium difficile infections (CDI) results from transmission from symptomatic episodes within the same hospital, and (2) to study how transmission varies between hospitals in Belgium. 30 hospitals participating in the study have registered 1334 episodes of clinical C. difficile infections (CDI) between January 2015 and January 2016 ; 85% have been ribotyped in the reference laboratory. In a subset of 28 hospitals with more complete data: The proportion of hospital-associated CDI that could be related to another episode with the same ribotype less than one month before in the same hospital varied from 0% to 51% (average 25%). 85 different clusters (cluster: an index case and at least one possibly- secondary episode) have been observed in 27 hospitals; 15/85 were due to ribotype 16; 50/85 clusters involved only one secondary case. MLVA typing is required to establish a definitive genetic link between index case and secondary cases and to analyze patterns of transmission. It has started in April in the reference laboratory. A more detailed interim report is available in the annexes International comparisons Based on an (yet unpublished) 2015 ECDC study comparing CDI rates in hospitalised patients across European countries up to 2014 (15), it seems that Belgium has the lowest CDI incidence of European countries with available data ; however differences in surveillance methods make comparisons difficult. Details from the ECDC study are given in annex. We also reviewed the published literature (see table in annexes). On the basis of these data, even given the caveats in making comparisons, we believe it can be said that Belgium has a low incidence compared to other European countries, and lower than the United States and Australia. 32

33 4. Discussion and conclusions 4.1. Discussion This report summarises the different sources of available data on the epidemiology of Clostridium difficle infection (CDI) in Belgium. A large number of hospitals have participated in the surveillance programme whilst it has been mandatory between In 2015, participation in the surveillance programme became voluntary, yet a large number of hospitals continued to participate, and there has been an increase in the number of hospitals providing data for the whole year. Incidence of CDI in hospitalised patients has declined almost continuously between In 2015 (latest data), the mean incidence of all CDI from all participating hospitals was 1.89 per admissions (1.87 episodes for acute hospitals and 4.72 episodes for chronic hospitals per 1000 admissions), more than the preceding year and the highest incidence reported since 2008, probably due to outbreaks in some hospitals particularly in West Vlanderen, Limburg, and Hainaut provinces. The proportion of hospital- associated CDI out of all cases remains stable (60% in 2015). For patients admitted with CDI, (onset before 2 days after admission), the proportion of those thought to have an episode with onset in the community was 63% in 2014 and 67% in The proportion of patients suffering severe complications of CDI (deaths as a direct or indirect result of CDI, pseudomembranous colitis, admission to the intensive care unit or the need for surgery as a result of CDI) has been stable in the last years. It is important to highlight that almost 15 % of CDI cases have unknown or missing complication statuses. There is a seasonal variation in incidence of CDI with a peak during January-April months each year. Hospital associated cases follow the same seasonal pattern as other cases. In 2015, the seasonal variation shows a sharp peak in January which then subsides; this trend follows what has been reported in earlier years. There exists a large variability in the incidence of hospital associated CDI between hospitals and between regions. Because RHM/MKG data collection dates back to 1999, counting the number of hospital stays with ICD-9-CM code (intestinal infections due to Clostridium difficile) allowed for a long time trend analysis, and because of its exhaustive nature, a measure of the burden of disease and a validation of surveillance data. In 2013 (last available data), 3989 hospital stays included a CDI (primary or secondary) diagnosis, translating into an incidence of CDI in hospital of 36/ population, and 2.03/1000 admissions. This later incidence is 25% higher than the corresponding incidence computed from surveillance data, but trends observed are similar. CDI-specific mortality rates for CDI decreased markedly after the peak in and now are either stable or decreasing in all regions. Mortality rates (crude or age standardized) are highest in Brussels; this probably reflects the high number of tertiary hospitals in the region. The recent use of whole genome sequencing (WGS) suggests that there may be genetically diverse sources of C. difficile, in addition to symptomatic patients, that play a part in C. difficile transmission. Inter-European country comparisons show a wide variation in reported CDI incidence. Although the majority of European countries have reported a decrease in their rate, in 2015, Belgian figures are still in the lower range in comparison to the rest of Europe. Methodological practices such as the use of case definitions (national vs. European), diagnostic tests, demographic factors, socioeconomic factors and healthcare utilization can contribute to the differences in reported incidence. In 2016, the ECDC launched the CDI surveillance and outsourced lab support program which aims to generate a collaborative use of the European surveillance protocol. This will standardize some of the incongruences observed between countries; nevertheless the adoption of the ECDC CDI surveillance protocol is optional at country level. In 2017 the first European CDI report will become available In conclusion, incidence of HA-CDI has increased in Belgium in 2015 as compared to The increase was marked in Flanders. 33

34 4.2. Conclusions and key points for CDI surveillance Key points The key points from data available in 2015 are: Participation of Belgian hospitals in CDI surveillance has remained high despite the fact that it was no longer compulsory. The mean incidence of CDI in Belgian hospitals (1.87/1000 admissions) is the highest reported since The increase in HA-CDI incidence was marked in Flanders. The differences between regions are now negligible. The severity of the disease has not changed in recent years. There is a high diversity of circulating Clostridium difficile strains in Belgium, pointing to a large diversity of sources of transmission. The hypervirulent strain BR078 (UCL 3) was found in 42% of the hospitals (25% in 2014). Preliminary results from the 2015 CDI transmission study point to a relatively low proportion of HA-CDI episodes in Belgian hospitals that can be attributable to in-hospital transmission from CDI symptomatic cases. Belgium has the lowest incidence of CDI reported in European countries; however differences in surveillance methods make comparisons difficult. 34

35 5. ANNEX 5.1. Changes for the 2016 surveillance (following the 2015 CDI working group meeting) Outcome of 2015 Working Group meeting ECDC Belgium Adapt to ECDC? Objectives include inter-hospital comparison Focus is on intra-hospital comparisons for monitoring trends. No. (Decision already taken by WG many years ago) CDI: diarrheal stools or toxic CDI: diarrhea (at least 3 liquid megacolon AND positive lab assay stools/24h) or toxic megacolon AND Yes. Criteria 3 liquid stools difficult for toxin A and/or B in stools or a positive lab assay for toxin A and/ to confirm (PCR already implicitly toxin-producing C. difficile organism or B in stools or a toxin-producing included) detected in stools via culture or other C. difficile organism detected in stools means eg PCR via culture or other means Def: Recurrence: Episode of CDI More than 2 weeks, less than 8 weeks following onset of a previous episode Def: Health-care (HC) associated: Onset of symptoms >=2 days after admission in HC facility OR In the community within 4 weeks of discharge from a HC facility Collect data on algorithm used for CDI diagnosis 11 items provided categorized in decreasing order of expected test validity (+ other, specify ). Number of tests. Proposal minimal (aggregated data only) vs. enhanced Surveillance period minimal: 3 months (based on expected incidence 3/10000 pt-days; ribotyping of first 10 episodes Episode of CDI less than 8 weeks following onset of previous episode (Provided symptoms subsided after first episode ) Hospital-associated : Onset of symptoms >=2 days after admission in declaring hospital Very limited data on diagnosis test used. N tests is requested, but rarely done. Very similar enhanced protocol but for Mc Cabe score categories and AM susceptibility testing Minimal: 6 months (observed mean incidence 2014: 1.2/10000 pt-days), ribotyping of first 5 episodes Yes (Add more than two weeks ) No. Our definition serves better our operational objectives at hospital level. (Our data do permit to calculate HCassociated CDI and we might do it in next annual report) Yes. Use ECDC list but do not comment on expected test validity as there is no consensus on this. Yes. To encourage hospitals to enter number of tests No minimal protocol - CDI surveillance is not so time consuming. No McCabe score categories. AM testing? No 35

36 5.2. Distribution of incidence of hospital associated Clostridium difficile infections (CDI in Belgium) Figure 11 Distribution of incidence of hospital associated Clostridium difficile infections (CDI) in Belgium, per hospital days comparison of acute and chronic hospitals, Hospital-associated CDI per hosp_days Graphs by 1: LoS <14 days; 2 >=14 days Only hospitals providing data for the whole year are included: LOS: length of stay in acute hospitals defined by mean length of stay <14 days, chronic >= 14 days 5.3. Incidence of Clostridium difficile infection in chronic hospitals Table 15 Incidence of hospital associated Clostridium difficile (HA-CDI) in chronic $ care Belgian hospitals, : surveillance data Year Denominators N hospitals included in the calculation of incidence (hospitals participating for whole year only) Hospital associated episodes (HA-CDI)* N / 10,000 days of hospitalisation : Mean Incidence* Median / 1000 admissions Mean incidence ** Median * Defined as onset of diarrhoea 2 days or more after admission in the declaring hospital (onset date admission date >2) ** Mean Incidence: total episodes/total denominator, LoS: length of stay $ Acute hospitals defined by mean length of stay <14 days, chronic >= 14 days

37 5.4. Variation of CDI in acute Hospital by region Flanders Figure 12 Funnel plot of CDI incidence per 10,000 hospital days in acute hospitals $ in Flanders, 2015 $ Acute hospitals defined by mean length of stay <14 days, chronic >= 14 days Only hospitals providing data for the whole year are included Wallonia Figure 13 Funnel plot of CDI incidence per 10,000 hospital days in acute hospitals $ in Wallonia, $ Acute hospitals defined by mean length of stay <14 days, chronic >= 14 days Only hospitals providing data for the whole year are included

38 Brussels Figure 14 Funnel plot of CDI incidence per 10,000 hospital days in acute hospitals $ in Brussels, 2015 $ Acute hospitals defined by mean length of stay <14 days, chronic >= 14 days Only hospitals providing data for the whole year are included 5.5. Reference laboratory (NRC-CD) methods Ribotyping The ribotyping technique is based on the existence of several ribosomal RNA loci within the bacterium which code for the genes 16S-23S-5S. The genes 16S and 23S are separated by an intergenic non-coding region of variable size. The ribotyping technique consists of amplification of these regions by PCR. The selected primers allow amplification from one segment of the 16S gene to another of the 23S gene. The resulting amplicons are analysed by capillary electrophoresis in a sequencer. Figure 16 shows an example of such a profile obtained. The strains are then analysed and interpreted by the software GeneMapper. Figure 15 Example of trace obtained by capillary electrophoresis for ribotyping 38 A European collection of reference strains allows classification of 21 ribotypes. Table 26 shows the how the 21 European reference ribotypes (Brazier classification) correspond to the internal nomenclature that is used within Belgium. In the Belgian NRC-CD, nearly 500 different profiles/ribotypes have so far been identified. The European ribotyping nomenclature is indicated by the prefix «BR» and the Belgian nomenclature by «UCL»

39 MLVA The technique of MLVA typing (Multi-Locus Variable number tandem repeat Analysis) allows a different characterisation of strains which enables distinction of clones within the same ribotype. It is based on the existence within the Clostridium difficile chromosome of a series of tandem repeat sequences of DNA situated in a number of different loci within the bacterial genome. Several of these loci, chosen for their discriminatory power, are amplified and the size of these amplicons is measured by capillary electrophoresis. Once the length of a repeat element is known, the number of repetitions can be calculated. This can be done with a software programme (BioNumerics) which also allows visual analysis by means of a dendrogram or a Minimum Spanning Tree (MST). This technique is used during hospital outbreaks or to follow up the more common ribotypes in Belgium. Table 16 Equivalent European (Brazier- BR) and Belgian (UCL) classification of Clostridium difficile ribotypes European Ribotype Nomenclature (Brazier) Ribotype Nomenclature (UCL) e * a* a d d c 39

40 5.6. International comparisons (ECDC data) Table 17 International comparison of incidence of Clostridium difficile infection in hospitals 40 Scotland (32,33) England (30,31) US (27-29) Poland (24-26) Belgium (23) Italy (21,22) Netherlands (20) Germany (19) Australia (17, 18) Ireland (16) continuous continuous continuous 2015 continuous year continuous continuous year 2015 quarterly Year & duration of study Mandatory surveillance Mandatory surveillance Mandatory surveillance (in certain states) Voluntary surveillance Survey Voluntary surveillance Sentinel surveillance Voluntary surveillance Voluntary surveillance Mandatory surveillance Data source Age15+ Hosp&comm Age2+ Hosp&comm Age >1 Hosp&comm Age 2+ In-pts All ages In-pts All ages In-pts All ages In-pts All ages In-pts Age 2+ In-pts & clinic pts Age 2+ In-pts Population N hospitals Total cases / hosp days NA NA 9.6 NA admissions NA NA NA 1.87 NA NA NA NA 100,000 population NA NA NA NA NA NA NA Hospital associated cases / hosp days NA NA NA NA 100,000 population NA NA NA NA 40 NA NA NA NA % Hospital associated (origin of infection) 62 ac 78 a 58 b 53 b 54 a 60 b NA 65 a 40 a 73 a Prevalent ribotypes 074, , / , ,106, ,002 a all episodes in-patient and out-patient b in-patient episodes only c 65 years and over, popn: population (inhabitants) Pts= patient

41 Table 18 CDI rates in published national reports, EU/EEA, Source: oral presentation at the 26 TH ECCMID conference, April 10, C. Suetens, personal communication The ECDC has estimated based on the point prevalence survey (PPS) on the burden of CDI that in the EU there are approximately 124,000 (95% CI 61, ,000) healthcare-associated CDI cases per year with an attributable mortality of 3% (34). It is the 8 th most frequent microorganism reported in the PPS with 3700 attributable deaths per year. The international comparisons we present above highlight the inter-european country variations in reported infection rates. There has been an increase in the reported CDI testing frequency from that recorded in 2008 (52.1) to 62.3 tests/10,000 patient bed days (35). There has also been a marked increase in measured CDI incidence from 4.1 to 6.6 CDI cases/10,000 patent bed days (35). Despite these increases some countries such as Ireland, Germany, and the UK have reported a decrease in their incidence in the last year ( ). Others, such as Belgium and Poland report an increase in CDI incidence in the year Reported variations between European countries could be explained by methodological differences such as: the use of case definitions (national vs. European), diagnostic tests, demographic factors, socioeconomic factors and healthcare utilization. Direct comparisons between countries are difficult. Completeness of surveillance varies widely with only Ireland, UK and Scotland using mandatory surveillance. Other countries such as Belgium, Germany and Poland use continuous voluntary surveillance and others such as Italy undertake surveys every couple of years to quantify infection in a subset of hospitals over a short period. There is an observed difference in the definitions of infection, such as hospital-acquired/ hospital-associated/ hospital-onset cases which can be defined as onset of symptoms anywhere between >2 days to 4 days after admission. Moreover, post-discharge infections which can be attributed to hospital care may be included in some countries and excluded in others. Denominators have also varied between countries with some reporting their data by hospital days, per 1000 admissions or per 100,000 population. Table 17 shows that the reported national incidence of CDI in hospitalised patients in Belgium is less than that of Germany and Italy and similar with the Netherlands (for the respective years given in the table). Poland has a reported incidence of CDI (9.6/10,000 hospital days) this increase can be attributed to the recent outbreak of ribotype 027 in Ribotypes 014, 020 and 027 remain the most prevalent within the EU. Moreover, preva- 41

42 lence studies have noted an increase in the prevalence of ribotype 027 across Europe as a whole, in marked contrast to the declining trend in UK (27-29) and Belgium. The proportion of hospitalised patients who have hospital associated CDI is remarkably similar in Belgium, Germany and England (58%, 53% and 60%). Scotland still reports that 73% of CDI cases are hospital associated and have implemented a more stringent surveillance at hospital level. Inter-continental comparisons show that the United States (population and laboratory based CDI surveillance) in 2011 reported (95% CI 397, ,500) healthcare and community associated CDI, almost quadruple the number reported in the EU of 124,000 population HA-CDI in hospitalised patients associated to acute care hospital stay only. U.S. hospitals reported a significant increase in CDI between 2013 and 2014 this could be partly due to the change of diagnostic methods. Switching from enzyme immunoassay (EIA) to nucleic acid amplification test (NAAT) increased CDI incidence rates by %. Also, the proportion of stool tests that were positive almost doubled (10.4% to 19.4%) with NAAT compared to toxin EIA. Like the US, Australia has reported an increase in the incidence of CDI in (most recent data). The number of total cases per 10,000 hospital days is high and correlates to estimates from the EU. Explanations for the increase in CDI cases in Australia include a change in circulating strains of C. difficile (ribotype 27) and improved laboratory detection. The hypervirulence of ribotype 027 is believed to be associated with the ability to produce high concentrations of toxins and high transmissibility. Ribotype 27 has also been reported in many European countries and has been recently associated with outbreaks in hospitals in Scotland and Poland. Figure 16 Clostridium difficile ribotypes detections reported in national surveillance reports, EU/EEA, Interim Study report: transmission of Clostridium difficile infection (CDI) in Belgian Hospitals Background The objectives of this study are (1) to measure what proportion of hospital-associated Clostridium difficile infections (CDI) results from transmission from symptomatic episodes within the same hospital, and (2) to study how transmission varies between hospitals in Belgium. (Complete study protocol: CDIF/CDIF_transmission_study_protocol_v7.pdf).