Comparison of the novel ResPlex III assay and existing techniques for the detection and subtyping of influenza virus during the influenza season 2006–2007

Influenza virus is a major cause of disease worldwide. The accurate detection and further subtyping of influenza A viruses are important for epidemiologic surveillance, and subsequent comprehensive characterization of circulating influenza viruses is essential for the selection of an optimal vaccine composition. ResPlex III is a new multiplex reverse transcriptase polymerase chain reaction (RT-PCR)-based method for detecting, typing, and subtyping influenza virus in clinical specimens. The ResPlex III assay was compared with other methods with respect to sensitivity and accuracy, using 450 clinical specimens obtained from subjects throughout Germany during the 2006–2007 influenza season. Samples were analyzed for the presence of influenza virus in Madin-Darby canine kidney (MDCK) cells by rapid cell culture using peroxidase staining and conventional cell culture confirmed by hemagglutination inhibition assay, a rapid diagnostic assay (Directigen Flu A+B test; BD Diagnostic Systems, Heidelberg, Germany), in-house real-time RT-PCR (RRT-PCR), and ResPlex III (Qiagen, Hilden, Germany). ResPlex III had the highest sensitivity for detecting influenza virus in clinical specimens, followed by in-house RRT-PCR (96% compared with ResPlex III). Conventional cell culture in MDCK cells, rapid culture, and quick test assays were substantially less sensitive (55%, 72%, and 39%, respectively). Virus subtyping results were identical using ResPlex III and the standard virological subtyping method, hemagglutination inhibition. ResPlex III is a quick, accurate, and sensitive assay for detecting and typing influenza A and B viruses and subtyping influenza A viruses in clinical specimens, and might be considered for a supplemental role in worldwide seasonal and pandemic influenza surveillance

Sensitive Commercial NASBA Assay for the Detection of Respiratory Syncytial Virus in Clinical Specimen

The aim of the study was to evaluate the usability of three diagnostic procedures for the detection of respiratory syncytial virus in clinical samples. Therefore, the FDA cleared CE marked NOW® RSV ELISA, the NucliSENS® EasyQ RSV A+B NASBA, and a literature based inhouse RT-PCR protocol were compared for their relative sensitivities. Thereby, NASBA turned out to be the most sensitive method with a total number of 80 RSV positive samples out of a cohort of 251 nasopharyngeal washings from patients suffering from clinical symptoms, followed by the inhouse RT-PCR (62/251) and ELISA (52/251). Thus, NASBA may serve as a rapid and highly sensitive alternative for RSV diagnostics

Predicting the start week of respiratory syncytial virus outbreaks using real time weather variables

<p>Abstract</p> <p>Background</p> <p>Respiratory Syncytial Virus (RSV), a major cause of bronchiolitis, has a large impact on the census of pediatric hospitals during outbreak seasons. Reliable prediction of the week these outbreaks will start, based on readily available data, could help pediatric hospitals better prepare for large outbreaks.</p> <p>Methods</p> <p>Naïve Bayes (NB) classifier models were constructed using weather data from 1985-2008 considering only variables that are available in real time and that could be used to forecast the week in which an RSV outbreak will occur in Salt Lake County, Utah. Outbreak start dates were determined by a panel of experts using 32,509 records with ICD-9 coded RSV and bronchiolitis diagnoses from Intermountain Healthcare hospitals and clinics for the RSV seasons from 1985 to 2008.</p> <p>Results</p> <p>NB models predicted RSV outbreaks up to 3 weeks in advance with an estimated sensitivity of up to 67% and estimated specificities as high as 94% to 100%. Temperature and wind speed were the best overall predictors, but other weather variables also showed relevance depending on how far in advance the predictions were made. The weather conditions predictive of an RSV outbreak in our study were similar to those that lead to temperature inversions in the Salt Lake Valley.</p> <p>Conclusions</p> <p>We demonstrate that Naïve Bayes (NB) classifier models based on weather data available in real time have the potential to be used as effective predictive models. These models may be able to predict the week that an RSV outbreak will occur with clinical relevance. Their clinical usefulness will be field tested during the next five years.</p

Surveillance recommendations based on an exploratory analysis of respiratory syncytial virus reports derived from the European Influenza Surveillance System

BACKGROUND: Respiratory syncytial virus (RSV) is an important pathogen that can cause severe illness in infants and young children. In this study, we assessed whether data on RSV collected by the European Influenza Surveillance Scheme (EISS) could be used to build an RSV surveillance system in Europe. METHODS: Influenza and RSV data for the 2002–2003 winter season were analysed for England, France, the Netherlands and Scotland. Data from sentinel physician networks and other sources, mainly hospitals, were collected. Respiratory specimens were tested for influenza and RSV mainly by virus culture and polymerase chain reaction amplification. RESULTS: Data on RSV were entered timely into the EISS database. RSV contributed noticeably to influenza-like illness: in England sentinel RSV detections were common in all age groups, but particularly in young children with 20 (40.8%) of the total number of sentinel swabs testing positive for RSV. Scotland and France also reported the highest percentages of RSV detections in the 0–4 year age group, respectively 10.3% (N = 29) and 12.2% (N = 426). In the Netherlands, RSV was detected in one person aged over 65 years. CONCLUSION: We recommend that respiratory specimens collected in influenza surveillance are also tested systematically for RSV and emphasize the use of both community derived data and data from hospitals for RSV surveillance. RSV data from the EISS have been entered in a timely manner and we consider that the EISS model can be used to develop an RSV surveillance system equivalent to the influenza surveillance in Europe

Comparing Pandemic to Seasonal Influenza Mortality: Moderate Impact Overall but High Mortality in Young Children

Background: We assessed the severity of the 2009 influenza pandemic by comparing pandemic mortality to seasonal influenza mortality. However, reported pandemic deaths were laboratory-confirmed - and thus an underestimation - whereas seasonal influenza mortality is often more inclusively estimated. For a valid comparison, our study used the same statistical methodology and data types to estimate pandemic and seasonal influenza mortality. Methods and Findings: We used data on all-cause mortality (1999-2010, 100% coverage, 16.5 million Dutch population) and influenza-like-illness (ILI) incidence (0.8% coverage). Data was aggregated by week and age category. Using generalized estimating equation regression models, we attributed mortality to influenza by associating mortality with ILI-incidence, while adjusting for annual shifts in association. We also adjusted for respiratory syncytial virus, hot/cold weather, other seasonal factors and autocorrelation. For the 2009 pandemic season, we estimated 612 (range 266-958) influenza-attributed deaths; for seasonal influen

Molecular characteristics and successful management of a respiratory syncytial virus outbreak among pediatric patients with hemato-oncological disease

Abstract Background Respiratory syncytial virus (RSV) is responsible for upper and lower respiratory tract infection in adults and children. Especially immunocompromised patients are at high risk for a severe course of infection, and mortality is increased. Moreover RSV can spread in healthcare settings and can cause outbreaks. Herein we demonstrate the successful control and characteristics of a RSV outbreak that included 8 patients in our Department of Pediatric Hematology and Oncology. Methods We performed an epidemiologic investigation and a molecular analysis of the outbreak strains. Moreover we present the outbreak control bundle and our concept for RSV screening in the winter season. Results RSV A and B strains caused the outbreak. RSV B strains affected 3 patients, 2 of whom were co-infected with RSV A. Exactly this RSV A strain was detected in another 5 patients. Our multimodal infection control bundle including prophylactic RSV screening was able to rapidly stop the outbreak. Conclusion An infection control bundle in RSV outbreaks should address all potential transmission pathways. In pediatric settings the restriction of social activities might have a temporal negative impact on quality of life but helps to limit transmission opportunities. Molecular analysis allows better understanding of RSV outbreaks and, if done in a timely manner, might be helpful for guidance of infection control measures