Clostridium difficile ribotypes in Austria: a multicenter, hospital-based survey

A prospective, noninterventional survey was conducted among Clostridium difficile positive patients identified in the time period of July until October 2012 in 18 hospitals distributed across all nine Austrian provinces. Participating hospitals were asked to send stool samples or isolates from ten successive patients with C.difficile infection to the National Clostridium difficile Reference Laboratory at the Austrian Agency for Health and Food Safety for PCR-ribotyping and in vitro susceptibility testing. A total of 171 eligible patients were identified, including 73 patients with toxin-positive stool specimens and 98 patients from which C. difficile isolates were provided. Of the 159 patients with known age, 127 (74.3 %) were 65 years or older, the median age was 76 years (range: 9–97 years), and the male to female ratio 2.2. Among these patients, 73 % had health care-associated and 20 % community-acquired C. difficile infection (indeterminable 7 %). The all-cause, 30-day mortality was 8.8 % (15/171). Stool samples yielded 46 different PCR-ribotypes, of which ribotypes 027 (20 %), 014 (15.8 %), 053 (10.5 %), 078 (5.3 %), and 002 (4.7 %) were the five most prevalent. Ribotype 027 was found only in the provinces Vienna, Burgenland, and Lower Austria. Severe outcome of C. difficile infection was found to be associated with ribotype 053 (prevalence ratio: 3.04; 95 % CI: 1.24, 7.44), not with the so-called hypervirulent ribotypes 027 and 078. All 027 and 053 isolates exhibited in vitro resistance against moxifloxacin. Fluoroquinolone use in the health care setting must be considered as a factor favoring the spread of these fluoroquinolone resistant C. difficile clones

Effectiveness of 2009 pandemic influenza A(H1N1) vaccines: a systematic review and meta-analysis

Background: The clinical effectiveness of monovalent influenza A(H1N1)pdm09 vaccines has not been comprehensively summarised. We undertook a systematic review and meta-analysis to assess vaccine effectiveness (VE) for adjuvanted and unadjuvanted vaccines. Methods: We searched healthcare databases and grey literature from 11 June 2009 to 12 November 2014. Two researchers independently assessed titles and abstracts to identify studies for full review. Random effects meta-analyses estimated the pooled effect size of vaccination compared to placebo or no vaccination for crude and adjusted odds ratios (OR) to prevent laboratory confirmed influenza illness (LCI) and related hospitalization. VE was calculated as (1-pooled OR) ∗ 100. Narrative synthesis was undertaken where meta-analysis was not possible. Results: We identified 9229 studies of which 38 at moderate risk of bias met protocol eligibility criteria; 23 were suitable for meta-analysis. Pooled adjusted VE against LCI with adjuvanted and unadjuvanted vaccines both reached statistical significance (adjuvanted: VE = 80%; 95% confidence interval [CI] 59–90%; unadjuvanted: VE = 66%; 95% CI 47–78%); in planned secondary analyses, VE in adults often failed to reach statistical significance and pooled point estimates were lower than observed in children. Overall pooled adjusted VE against hospitalization was 61% (95% CI 14–82%); in planned secondary analyses, adjusted VE attained statistical significance in adults aged 18–64 years and children for adjuvanted vaccines. Adjuvanted vaccines were significantly more effective in children compared to adults for both outcomes. Conclusions: Adjuvanted and unadjuvanted monovalent influenza A(H1N1)pdm09 vaccines were both effective in preventing LCI. Overall, the vaccines were also effective against influenza-related hospitalization. For both outcomes adjuvanted vaccines were more effective in children than in adults

CFEST Coupled Flow, Energy & Solute Transport Version CFEST005 User’s Guide

The CFEST (Coupled Flow, Energy, and Solute Transport) simulator described in this User’s Guide is a three-dimensional finite-element model used to evaluate groundwater flow and solute mass transport. Confined and unconfined aquifer systems, as well as constant and variable density fluid flows can be represented with CFEST. For unconfined aquifers, the model uses a moving boundary for the water table, deforming the numerical mesh so that the uppermost nodes are always at the water table. For solute transport, changes in concentra¬tion of a single dissolved chemical constituent are computed for advective and hydrodynamic transport, linear sorption represented by a retardation factor, and radioactive decay. Although several thermal parameters described in this User’s Guide are required inputs, thermal transport has not yet been fully implemented in the simulator. Once fully implemented, transport of thermal energy in the groundwater and solid matrix of the aquifer can also be used to model aquifer thermal regimes. The CFEST simulator is written in the FORTRAN 77 language, following American National Standards Institute (ANSI) standards. Execution of the CFEST simulator is controlled through three required text input files. These input file use a structured format of associated groups of input data. Example input data lines are presented for each file type, as well as a description of the structured FORTRAN data format. Detailed descriptions of all input requirements, output options, and program structure and execution are provided in this User’s Guide. Required inputs for auxillary CFEST utilities that aide in post-processing data are also described. Global variables are defined for those with access to the source code. Although CFEST is a proprietary code (CFEST, Inc., Irvine, CA), the Pacific Northwest National Laboratory retains permission to maintain its own source, and to distribute executables to Hanford subcontractors

Validation of Statistical Models for Estimating Hospitalization Associated with Influenza and Other Respiratory Viruses

BACKGROUND: Reliable estimates of disease burden associated with respiratory viruses are keys to deployment of preventive strategies such as vaccination and resource allocation. Such estimates are particularly needed in tropical and subtropical regions where some methods commonly used in temperate regions are not applicable. While a number of alternative approaches to assess the influenza associated disease burden have been recently reported, none of these models have been validated with virologically confirmed data. Even fewer methods have been developed for other common respiratory viruses such as respiratory syncytial virus (RSV), parainfluenza and adenovirus. METHODS AND FINDINGS: We had recently conducted a prospective population-based study of virologically confirmed hospitalization for acute respiratory illnesses in persons <18 years residing in Hong Kong Island. Here we used this dataset to validate two commonly used models for estimation of influenza disease burden, namely the rate difference model and Poisson regression model, and also explored the applicability of these models to estimate the disease burden of other respiratory viruses. The Poisson regression models with different link functions all yielded estimates well correlated with the virologically confirmed influenza associated hospitalization, especially in children older than two years. The disease burden estimates for RSV, parainfluenza and adenovirus were less reliable with wide confidence intervals. The rate difference model was not applicable to RSV, parainfluenza and adenovirus and grossly underestimated the true burden of influenza associated hospitalization. CONCLUSION: The Poisson regression model generally produced satisfactory estimates in calculating the disease burden of respiratory viruses in a subtropical region such as Hong Kong

Model Selection in Time Series Studies of Influenza-Associated Mortality

Background: Poisson regression modeling has been widely used to estimate influenza-associated disease burden, as it has the advantage of adjusting for multiple seasonal confounders. However, few studies have discussed how to judge the adequacy of confounding adjustment. This study aims to compare the performance of commonly adopted model selection criteria in terms of providing a reliable and valid estimate for the health impact of influenza. Methods: We assessed four model selection criteria: quasi Akaike information criterion (QAIC), quasi Bayesian information criterion (QBIC), partial autocorrelation functions of residuals (PACF), and generalized cross-validation (GCV), by separately applying them to select the Poisson model best fitted to the mortality datasets that were simulated under the different assumptions of seasonal confounding. The performance of these criteria was evaluated by the bias and root-mean-square error (RMSE) of estimates from the pre-determined coefficients of influenza proxy variable. These four criteria were subsequently applied to an empirical hospitalization dataset to confirm the findings of simulation study. Results: GCV consistently provided smaller biases and RMSEs for the influenza coefficient estimates than QAIC, QBIC and PACF, under the different simulation scenarios. Sensitivity analysis of different pre-determined influenza coefficients, study periods and lag weeks showed that GCV consistently outperformed the other criteria. Similar results were found in applying these selection criteria to estimate influenza-associated hospitalization. Conclusions: GCV criterion is recommended for selection of Poisson models to estimate influenza-associated mortality and morbidity burden with proper adjustment for confounding. These findings shall help standardize the Poisson modeling approach for influenza disease burden studies. © 2012 Wang et al.published_or_final_versio

Association between the 2008–09 Seasonal Influenza Vaccine and Pandemic H1N1 Illness during Spring–Summer 2009: Four Observational Studies from Canada

In three case-control studies and a household transmission cohort, Danuta Skowronski and colleagues find an association between prior seasonal flu vaccination and increased risk of 2009 pandemic H1N1 flu

Canadian oncogenic human papillomavirus cervical infection prevalence: Systematic review and meta-analysis

<p>Abstract</p> <p>Background</p> <p>Oncogenic human papillomavirus (HPV) infection prevalence is required to determine optimal vaccination strategies. We systematically reviewed the prevalence of oncogenic cervical HPV infection among Canadian females prior to immunization.</p> <p>Methods</p> <p>We included studies reporting DNA-confirmed oncogenic HPV prevalence estimates among Canadian females identified through searching electronic databases (e.g., MEDLINE) and public health websites. Two independent reviewers screened literature results, abstracted data and appraised study quality. Prevalence estimates were meta-analyzed among routine screening populations, HPV-positive, and by cytology/histology results.</p> <p>Results</p> <p>Thirty studies plus 21 companion reports were included after screening 837 citations and 120 full-text articles. Many of the studies did not address non-response bias (74%) or use a representative sampling strategy (53%).</p> <p>Age-specific prevalence was highest among females aged < 20 years and slowly declined with increasing age. Across all populations, the highest prevalence estimates from the meta-analyses were observed for HPV types 16 (routine screening populations, 8 studies: 8.6% [95% confidence interval 6.5-10.7%]; HPV-infected, 9 studies: 43.5% [28.7-58.2%]; confirmed cervical cancer, 3 studies: 48.8% [34.0-63.6%]) and 18 (routine screening populations, 8 studies: 3.3% [1.5-5.1%]; HPV-infected, 9 studies: 13.6% [6.1-21.1%], confirmed cervical cancer, 4 studies: 17.1% [6.4-27.9%].</p> <p>Conclusion</p> <p>Our results support vaccinating females < 20 years of age, along with targeted vaccination of some groups (e.g., under-screened populations). The highest prevalence occurred among HPV types 16 and 18, contributing a combined cervical cancer prevalence of 65.9%. Further cancer protection is expected from cross-protection of non-vaccine HPV types. Poor study quality and heterogeneity suggests that high-quality studies are needed.</p

The everchanging epidemiology of meningococcal disease worldwide and the potential for prevention through vaccination.

Neisseria meningitidis is a major cause of bacterial meningitis and septicaemia worldwide and is associated with high case fatality rates and serious life-long complications among survivors. Twelve serogroups are recognised, of which six (A, B, C, W, X and Y) are responsible for nearly all cases of invasive meningococcal disease (IMD). The incidence of IMD and responsible serogroups vary widely both geographically and over time. For the first time, effective vaccines against all these serogroups are available or nearing licensure. Over the past two decades, IMD incidence has been declining across most parts of the world through a combination of successful meningococcal immunisation programmes and secular trends. The introduction of meningococcal C conjugate vaccines in the early 2000s was associated with rapid declines in meningococcal C disease, whilst implementation of a meningococcal A conjugate vaccine across the African meningitis belt led to near-elimination of meningococcal A disease. Consequently, other serogroups have become more important causes of IMD. In particular, the emergence of a hypervirulent meningococcal group W clone has led many countries to shift from monovalent meningococcal C to quadrivalent ACWY conjugate vaccines in their national immunisation programmes. Additionally, the recent licensure of two protein-based, broad-spectrum meningococcal B vaccines finally provides protection against the most common group responsible for childhood IMD across Europe and Australia. This review describes global IMD epidemiology across each continent and trends over time, the serogroups responsible for IMD, the impact of meningococcal immunisation programmes and future needs to eliminate this devastating disease