Cryptosporidium parvum infections in a cohort of veterinary students in Sweden.

In March 2013, a veterinary student tested positive for Cryptosporidium; four classmates reported similar gastrointestinal symptoms. We aimed to identify source(s) and risk factors for Cryptosporidium infection in university persons symptomatic between 21 January and 14 April 2013. Sixty-four (79%) students from a cohort of 81 fourth-year veterinary students completed questionnaires, identifying 13 cases; four were Cryptosporidium parvum GP60 subtype IIaA16G1R1b, two were IIdA24G1, seven did not submit stool samples. Thirteen cases attended the university's field clinic before symptom onset (13/37 attendees, 35%); 11 visited at least one of four farms where students recalled seeing calves with diarrhoea. C. parvum subtype IIaA16G1R1b was identified in calves at one of the farms. Entering pens of calves with diarrhoea [relative risk (RR) 7·6, 95% confidence interval (CI) 1·7-33·5] and eating in clinic cars (RR 9·1, 95% CI 1·3-65·8) were associated with being a case. Washing hands at least twice per farm visit (0 cases, P = 0·03) was protective. This outbreak investigation was notable for rapid and effective collaboration between public health, veterinary and environmental sectors, leading to swift identification of a microbiological and epidemiological link between cases, infected calves and their farms. We recommend frequent hand-washing using proper technique and dissuasion from eating in clinic cars to minimize possible exposure to contaminated surfaces.

Infectious diseases prioritisation for event-based surveillance at the European Union level for the 2012 Olympic and Paralympic Games.

In 2012, London hosted the Olympic and Paralympic Games (the Games), with events occurring throughout the United Kingdom (UK) between 27 July and 9 September 2012. Public health surveillance was performed by the Health Protection Agency (HPA). Collaboration between the HPA and the European Centre for Disease Prevention and Control (ECDC) was established for the detection and assessment of significant infectious disease events (SIDEs) occurring outside the UK during the time of the Games. Additionally, ECDC undertook an internal prioritisation exercise to facilitate ECDC's decisions on which SIDEs should have preferentially enhanced monitoring through epidemic intelligence activities for detection and reporting in daily surveillance in the European Union (EU). A team of ECDC experts evaluated potential public health risks to the Games, selecting and prioritising SIDEs for event-based surveillance with regard to their potential for importation to the Games, occurrence during the Games or export to the EU/European Economic Area from the Games. The team opted for a multilevel approach including comprehensive disease selection, development and use of a qualitative matrix scoring system and a Delphi method for disease prioritisation. The experts selected 71 infectious diseases to enter the prioritisation exercise of which 27 were considered as priority for epidemic intelligence activities by ECDC for the EU for the Games.

Multidisciplinary investigation of a multicountry outbreak of Salmonella Stanley infections associated with turkey meat in the European Union, August 2011 to January 2013.

Between August 2011 and January 2013, an outbreak of Salmonella enterica serovar Stanley (S. Stanley) infections affected 10 European Union (EU) countries, with a total of 710 cases recorded. Following an urgent inquiry in the Epidemic Intelligence Information System for food- and waterborne diseases (EPIS-FWD) on 29 June 2012, an international investigation was initiated including EU and national agencies for public health, veterinary health and food safety. Two of three local outbreak investigations undertaken by affected countries in 2012 identified turkey meat as a vehicle of infection. Furthermore, routine EU monitoring of animal sources showed that over 95% (n=298) of the 311 S. Stanley isolates reported from animal sampling in 2011 originated from the turkey food production chain. In 2004­10, none had this origin. Pulsed-field gel electrophoresis (PFGE) profile analysis of outbreak isolates and historical S. Stanley human isolates revealed that the outbreak isolates had a novel PFGE profile that emerged in Europe in 2011. An indistinguishable PFGE profile was identified in 346 of 464 human, food, feed, environmental and animal isolates from 16 EU countries: 102 of 112 non-human isolates tested were from the turkey production chain. On the basis of epidemiological and microbiological evidence, turkey meat was considered the primary source of human infection, following contamination early in the animal production chain.

Large outbreak of verocytotoxin-producing Escherichia coli O157 infection in visitors to a petting farm in South East England, 2009.

In the summer of 2009, an outbreak of verocytotoxigenic Escherichia coli O157 (VTEC O157) was identified in visitors to a large petting farm in South East England. The peak attack rate was 6/1000 visitors, and highest in those aged <2 years (16/1000). We conducted a case-control study with associated microbiological investigations, on human, animal and environmental samples. We identified 93 cases; 65 primary, 13 secondary and 15 asymptomatic. Cases were more likely to have visited a specific barn, stayed for prolonged periods and be infrequent farm visitors. The causative organism was identified as VTEC O157 PT21/28 with the same VNTR profile as that isolated in faecal specimens from farm animals and the physical environment, mostly in the same barn. Contact with farm livestock, especially ruminants, should be urgently reviewed at the earliest suspicion of a farm-related VTEC O157 outbreak and appropriate risk management procedures implemented without delay.

Risk of hospitalization and death for healthcare workers with COVID-19 in nine European countries, January 2020-January 2021.

This article presents and compares coronavirus disease 2019 attack rates for infection, hospitalization, intensive care unit (ICU) admission and death in healthcare workers (HCWs) and non-HCWs in nine European countries from 31st January 2020 to 13th January 2021. Adjusted attack rate ratios in HCWs (compared with non-HCWs) were 3.0 [95% confidence interval (CI) 2.2-4.0] for infection, 1.8 (95% CI 1.2-2.7) for hospitalization, 1.9 (95% CI 1.1-3.2) for ICU admission and 0.9 (95% CI 0.4-2.0) for death. Among hospitalized cases, the case-fatality ratio was 1.8% in HCWs and 8.2% in non-HCWs. Differences may be due to better/earlier access to treatment, differential underascertainment and the healthy worker effect.

Development of case vignettes for assessment of the inter-rater variability of national validation teams for the point prevalence survey of healthcare-associated infections and antimicrobial use in European acute care hospitals.

BACKGROUND: In 2016-17 the European Centre for Disease Prevention and Control (ECDC) organized the second point prevalence survey (PPS) of healthcare-associated infections (HCAIs) and antimicrobial use in European acute care hospitals. This survey included a validation study to maximize the accuracy of case identification and classification. AIM: ECDC developed case vignettes to assess the performance of the national validation teams. METHODS: Case vignettes were developed by two medical doctors with experience in the management of HCAIs and antimicrobial stewardship. The case vignettes were based on actual clinical cases. The distribution of HCAIs among the case vignettes reflected the distribution of HCAIs in the previous PPS. All case vignettes were pilot-tested by three expert raters. Agreement among the expert raters was measured using kappa statistics. FINDINGS: Sixty case vignettes were developed. Twenty-nine of them were HCAI cases and 31 were cases without an HCAI. The inter-rater reliability using kappa statistics was 0.78 for the presence of HCAI and 0.89 for the antimicrobial use, respectively. CONCLUSION: The agreement between the expert raters was very good for antimicrobial use and good for the presence of HCAI. Case vignettes can be a tool to support standardization of surveillance, improving the validity and comparability of the data.

Prevalence and incidence of surgical site infections in the European Union/European Economic Area: how do these measures relate?

BACKGROUND: In 2011-2012, the European Centre for Disease Prevention and Control (ECDC) initiated the first European point prevalence survey (PPS) of healthcare-associated infections (HCAIs) in addition to targeted surveillance of the incidence of specific types of HCAI such as surgical site infections (SSIs). AIM: To investigate whether national and multi-country SSI incidence can be estimated from ECDC PPS data. METHODS: In all, 159 hospitals were included from 15 countries that participated in both ECDC surveillance modules, aligning surgical procedures in the incidence surveillance to corresponding specialties from the PPS. National daily prevalence of SSIs was simulated from the incidence surveillance data, the Rhame and Sudderth (R&S) formula was used to estimate national and multi-country SSI incidence from the PPS data, and national incidence per specialty was predicted using a linear model including data from the PPS. FINDINGS: The simulation of daily SSI prevalence from incidence surveillance of SSIs showed that prevalence fluctuated randomly depending on the day of measurement. The correlation between the national aggregated incidence estimated with R&S formula and observed SSI incidence was low (correlation coefficient = 0.24), but specialty-specific incidence results were more reliable, especially when the number of included patients was large (correlation coefficients ranging from 0.40 to 1.00). The linear prediction model including PPS data had low proportion of explained variance (0.40). CONCLUSION: Due to a lack of accuracy, use of PPS data to estimate SSI incidence is recommended only in situations where incidence surveillance of SSIs is not performed, and where sufficiently large samples of PPS data are available.

How to: Surveillance of Clostridium difficile infections.

BACKGROUND: The increasing incidence of Clostridium difficile infections (CDI) in healthcare settings in Europe since 2003 has affected both patients and healthcare systems. The implementation of effective CDI surveillance is key to enable monitoring of the occurrence and spread of C. difficile in healthcare and the timely detection of outbreaks. AIMS: The aim of this review is to provide a summary of key components of effective CDI surveillance and to provide some practical recommendations. We also summarize the recent and current national CDI surveillance activities, to illustrate strengths and weaknesses of CDI surveillance in Europe. SOURCES: For the definition of key components of CDI surveillance, we consulted the current European Society of Clinical Microbiology and Infectious Diseases (ESCMID) CDI-related guidance documents and the European Centre for Disease Prevention and Control (ECDC) protocol for CDI surveillance in acute care hospitals. To summarize the recent and current national CDI surveillance activities, we discussed international multicentre CDI surveillance studies performed in 2005-13. In 2017, we also performed a new survey of existing CDI surveillance systems in 33 European countries. CONTENT: Key components for CDI surveillance are appropriate case definitions of CDI, standardized CDI diagnostics, agreement on CDI case origin definition, and the presentation of CDI rates with well-defined numerators and denominators. Incorporation of microbiological data is required to provide information on prevailing PCR ribotypes and antimicrobial susceptibility to first-line CDI treatment drugs. In 2017, 20 European countries had a national CDI surveillance system and 21 countries participated in ECDC-coordinated CDI surveillance. Since 2014, the number of centres with capacity for C. difficile typing has increased to 35 reference or central laboratories in 26 European countries. IMPLICATIONS: Incidence rates of CDI, obtained from a standardized CDI surveillance system, can be used as an important quality indicator of healthcare at hospital as well as country level.