Evaluation of Epidemic Intelligence Systems Integrated in the Early Alerting and Reporting Project for the Detection of A/H5N1 Influenza Events

Web-based expert systems dedicated to epidemic intelligence were developed to detect health threats. The Early Alerting and Reporting (EAR) project, launched under the Global Health Initiative, aimed at assessing the feasibility and opportunity of pooling seven of those expert systems. A qualitative survey was carried out with EAR participants to document epidemic intelligence strategies and to assess perceptions regarding the performance of participating systems. Timeliness and sensitivity were rated with high scores illustrating the overall perceived value of all systems while weaknesses were underlined especially in terms of representativeness, completeness and flexibility. These findings were corroborated by the quantitative analysis performed on signals potentially related to influenza A/H5N1 events which occurred in March 2010. For the six systems for which this information was available; the detection rate ranged from 31% to 38%, and increased to 72% when considering the virtual combined system. The positive predictive values (PPV) ranged from 3% to 24% and the F1-score ranged from 6% to 27%. These low scores point out false positive signals related to varying abilities of the systems to efficiently sort-out information and reduce background noise. For the seven systems sensitivity ranged from 38% to 72%. An average difference of 23% was observed between the sensitivities calculated for human cases and epizootics, underlining the difficulties to develop an efficient algorithm or a single pathology. The sensitivity increased to 93% when the virtual combined system was considered, clearly illustrating the systems’ complementarities. The average delay between the detection of the A/H5N1 events by the systems and their official reporting by WHO or OIE was 10.2 days (CI95%, 6.7; 13.8). This work illustrates the diversity in implemented epidemic intelligence activities, differences in systems designs and the potential added values and opportunities for synergy: between systems, between users and between systems and users.JRC.G.2-Global security and crisis managemen

Factors Influencing Performance of Internet-Based Biosurveillance Systems Used in Epidemic Intelligence for Early Detection of Infectious Diseases Outbreaks

Background: Internet-based biosurveillance systems have been developed to detect health threats using information available on the Internet, but system performance has not been assessed relative to end-user needs and perspectives. Method and Findings: Infectious disease events from the French Institute for Public Health Surveillance (InVS) weekly international epidemiological bulletin published in 2010 were used to construct the gold-standard official dataset. Data from six biosurveillance systems were used to detect raw signals (infectious disease events from informal Internet sources): Argus, BioCaster, GPHIN, HealthMap, MedISys and ProMED-mail. Crude detection rates (C-DR), crude sensitivity rates (C-Se) and intrinsic sensitivity rates (I-Se) were calculated from multivariable regressions to evaluate the systems’ performance (events detected compared to the gold-standard) 472 raw signals (Internet disease reports) related to the 86 events included in the gold-standard data set were retrieved from the six systems. 84 events were detected before their publication in the gold-standard. The type of sources utilised by the systems varied significantly (p,0001). I-Se varied significantly from 43% to 71% (p = 0001) whereas other indicators were similar (C-DR: p = 020; C-Se, p = 013). I-Se was significantly associated with individual systems, types of system, languages, regions of occurrence, and types of infectious disease. Conversely, no statistical difference of C-DR was observed after adjustment for other variables. Conclusion: Although differences could result from a biosurveillance system’s conceptual design, findings suggest that the combined expertise amongst systems enhances early detection performance for detection of infectious diseases. While all systems showed similar early detection performance, systems including human moderation were found to have a 53% higher I-Se (p = 00001) after adjustment for other variables. Overall, the use of moderation, sources, languages, regions of occurrence, and types of cases were found to influence system performance.JRC.G.2-Global security and crisis managemen

VEB-1 Extended-Spectrum β-lactamase–producing Acinetobacter baumannii, France1

VEB-1 extended-spectrum β-lactamase–producing Acinetobacter baumannii was responsible for an outbreak in hospitals in France. A national alert was triggered in September 2003 when 4 hospitals reported clusters of A. baumannii infection with similar susceptibility profiles. Case definitions and laboratory guidelines were disseminated, and prospective surveillance was implemented; strains were sent to a single laboratory for characterization and typing. From April 2003 through June 2004, 53 hospitals reported 290 cases of A. baumannii infection or colonization; 275 isolates were blaVEB-1-positive and clonally related. Cases were first reported in 5 districts of northern France, then in 10 other districts in 4 regions. Within a region, interhospital spread was associated with patient transfer. In northern France, investigation and control measures led to a reduction of reported cases after January 2004. The national alert enabled early control of new clusters, demonstrating the usefulness of early warning about antimicrobial drug resistance

Factors Influencing Performance of Internet-Based Biosurveillance Systems Used in Epidemic Intelligence for Early Detection of Infectious Diseases Outbreaks

Background: Internet-based biosurveillance systems have been developed to detect health threats using information available on the Internet, but system performance has not been assessed relative to end-user needs and perspectives. Method and Findings Infectious disease events from the French Institute for Public Health Surveillance (InVS) weekly international epidemiological bulletin published in 2010 were used to construct the gold-standard official dataset. Data from six biosurveillance systems were used to detect raw signals (infectious disease events from informal Internet sources): Argus, BioCaster, GPHIN, HealthMap, MedISys and ProMED-mail. Crude detection rates (C-DR), crude sensitivity rates (C-Se) and intrinsic sensitivity rates (I-Se) were calculated from multivariable regressions to evaluate the systems’ performance (events detected compared to the gold-standard) 472 raw signals (Internet disease reports) related to the 86 events included in the gold-standard data set were retrieved from the six systems. 84 events were detected before their publication in the gold-standard. The type of sources utilised by the systems varied significantly (p<0001). I-Se varied significantly from 43% to 71% (p = 0001) whereas other indicators were similar (C-DR: p = 020; C-Se, p = 013). I-Se was significantly associated with individual systems, types of system, languages, regions of occurrence, and types of infectious disease. Conversely, no statistical difference of C-DR was observed after adjustment for other variables. Conclusion: Although differences could result from a biosurveillance system's conceptual design, findings suggest that the combined expertise amongst systems enhances early detection performance for detection of infectious diseases. While all systems showed similar early detection performance, systems including human moderation were found to have a 53% higher I-Se (p = 00001) after adjustment for other variables. Overall, the use of moderation, sources, languages, regions of occurrence, and types of cases were found to influence system performance

How to measure hospital antibiotic consumption: comparison of two methods from data surveillance in France

BACKGROUND: Antibiotic use (ABU) surveillance in healthcare facilities (HCFs) is essential to guide stewardship. Two methods are recommended: antibiotic consumption (ABC), expressed as the number of DDD/1000 patient-days; and prevalence of antibiotic prescription (ABP) measured through point prevalence surveys. However, no evidence is provided about whether they lead to similar conclusions. OBJECTIVES: To compare ABC and ABP regarding HCF ranking and their ability to identify outliers. METHODS: The comparison was made using 2012 national databases from the antibiotic surveillance network and prevalence study. HCF rankings according to each method were compared with Spearman's correlation coefficient. Analyses included the ABU from entire HCFs as well as according to type, clinical ward and by antibiotic class and specific molecule. RESULTS: A total of 1076 HCFs were included. HCF rankings were strongly correlated in the whole cohort. The correlation was stronger for HCFs with a higher number of beds or with a low or moderate proportion of acute care beds. ABU correlation between ABC or ABP was globally moderate or weak in specific wards. Furthermore, the two methods did not identify the same outliers, whichever HCF characteristics were analysed. Correlation between HCF ranking varied according to the antibiotic class. CONCLUSIONS: Both methods ranked HCFs similarly overall according to ABC or ABP; however, major differences were observed in ranking of clinical wards, antibiotic classes and detection of outliers. ABC and ABP are two markers of ABU that could be used as two complementary approaches to identify targets for improvement

Efecte d'una estratègia de millora ambiental enfront l'estrès tèrmic en vaques Frisones

Aquest estudi descriu una possible millora ambiental, amb l'objectiu d’incrementar la producció lletera disminuint l’estrès tèrmic durant l’època d’estiu. Per portar a terme l’avaluació, es van utilitzar 142 vaques lleteres d’alta producció. Aquestes es van dividir en dos grups, el grup experimental (aplicació de l'estratègia ambiental) i grup control (no aplicació de l'estratègia ambiental).

Syndromic surveillance and heat wave morbidity: a pilot study based on emergency departments in France

<p>Abstract</p> <p>Background</p> <p>The health impacts of heat waves are serious and have prompted the development of heat wave response plans. Even when they are efficient, these plans are developed to limit the health effects of heat waves. This study was designed to determine relevant indicators related to health effects of heat waves and to evaluate the ability of a syndromic surveillance system to monitor variations in the activity of emergency departments over time. The study uses data collected during the summer 2006 when a new heat wave occurred in France.</p> <p>Methods</p> <p>Data recorded from 49 emergency departments since July 2004, were transmitted daily via the Internet to the French Institute for Public Health Surveillance. Items collected on patients included diagnosis (ICD10 codes), outcome, and age. Statistical t-tests were used to compare, for several health conditions, the daily averages of patients within different age groups and periods (whether 'on alert' or 'off alert').</p> <p>Results</p> <p>A limited number of adverse health conditions occurred more frequently during hot period: dehydration, hyperthermia, malaise, hyponatremia, renal colic, and renal failure. Over all health conditions, the total number of patients per day remained equal between the 'on alert' and 'off alert' periods (4,557.7/day vs. 4,511.2/day), but the number of elderly patients increased significantly during the 'on alert' period relative to the 'off alert' period (476.7/day vs. 446.2/day p < 0.05).</p> <p>Conclusion</p> <p>Our results show the interest to monitor specific indicators during hot periods and to focus surveillance efforts on the elderly. Syndromic surveillance allowed the collection of data in real time and the subsequent optimization of the response by public health agencies. This method of surveillance should therefore be considered as an essential part of efforts to prevent the health effects of heat waves.</p

PRAISE: providing a roadmap for automated infection surveillance in Europe

Introduction: Healthcare-associated infections (HAI) are among the most common adverse events of medical care. Surveillance of HAI is a key component of successful infection prevention programmes. Conventional surveillance - manual chart review - is resource intensive and limited by concerns regarding interrater reliability. This has led to the development and use of automated surveillance (AS). Many AS systems are the product of in-house development efforts and heterogeneous in their design and methods. With this roadmap, the PRAISE network aims to provide guidance on how to move AS from the research setting to large-scale implementation, and how to ensure the delivery of surveillance data that are uniform and useful for improvement of quality of care. Methods: The PRAISE network brings together 30 experts from ten European countries. This roadmap is based on the outcome of two workshops, teleconference meetings and review by an independent panel of international experts. Results: This roadmap focuses on the surveillance of HAI within networks of healthcare facilities for the purpose of comparison, prevention and quality improvement initiatives. The roadmap does the following: discusses the selection of surveillance targets, different organizational and methodologic approaches and their advantages, disadvantages and risks; defines key performance requirements of AS systems and suggestions for their design; provides guidance on successful implementation and maintenance; and discusses areas of future research and training requirements for the infection prevention and related disciplines. The roadmap is supported by accompanying documents regarding the governance and information technology aspects of implementing AS. Conclusions: Large-scale implementation of AS requires guidance and coordination within and across surveillance networks. Transitions to large-scale AS entail redevelopment of surveillance methods and their interpretation, intensive dialogue with stakeholders and the investment of considerable resources. This roadmap can be used to guide future steps towards implementation, including designing solutions for AS and practical guidance checklists

Evaluation of Epidemic Intelligence Systems Integrated in the Early Alerting and Reporting Project for the Detection of A/H5N1 Influenza Events

Peer reviewe

Training infection control and hospital hygiene professionals in Europe, 2010 : agreed core competencies among 33 European countries

The harmonisation of training programmes for infection control and hospital hygiene (IC/HH) professionals in Europe is a requirement of the Council recommendation on patient safety. The European Centre for Disease Prevention and Control commissioned the ‘Training Infection Control in Europe’ project to develop a consensus on core competencies for IC/HH professionals in the European Union (EU). Core competencies were drafted on the basis of the Improving Patient Safety in Europe (IPSE) project’s core curriculum (CC), evaluated by questionnaire and approved by National Representatives (NRs) for IC/HH training. NRs also re-assessed the status of IC/HH training in European countries in 2010 in comparison with the situation before the IPSE CC in 2006. The IPSE CC had been used to develop or update 28 of 51 IC/HH courses. Only 10 of 33 countries offered training and qualification for IC/ HH doctors and nurses. The proposed core competencies are structured in four areas and 16 professional tasks at junior and senior level. They form a reference for standardisation of IC/HH professional competencies and support recognition of training initiatives.peer-reviewe