32 research outputs found

    I-Move towards monitoring seasonal and pandemic influenza vaccine effectiveness: lessons learnt from a pilot multi-centric case-control study in europe, 2008-9

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    Within I-MOVE (European programme to monitor seasonal and pandemic influenza vaccine effectiveness (IVE)) five countries conducted IVE pilot case-control studies in 2008-9. One hundred and sixty sentinel general practitioners (GP) swabbed all elderly consulting for influenza-like illness (ILI). Influenza confirmed cases were compared to influenza negative controls. We conducted a pooled analysis to obtain a summary IVE in the age group of >or=65 years. We measured IVE in each study and assessed heterogeneity between studies qualitatively and using the I2 index. We used a one-stage pooled model with study as a fixed effect. We adjusted estimates for age-group, sex, chronic diseases, smoking, functional status, previous influenza vaccinations and previous hospitalisations. The pooled analysis included 138 cases and 189 test-negative controls. There was no statistical heterogeneity (I2=0) between studies but ILI case definition, previous hospitalisations and functional status were slightly different. The adjusted IVE was 59.1% (95% CI: 15.3-80.3%). IVE was 65.4% (95% CI: 15.6-85.8%) in the 65-74, 59.6% (95% CI: -72.6 -90.6%) in the age group of >or=75 and 56.4% (95% CI: -0.2-81.3%) for A(H3). Pooled analysis is feasible among European studies. The variables definitions need further standardisation. Larger sample sizes are needed to achieve greater precision for subgroup analysis. For 2009-10, I-MOVE will extend the study to obtain early IVE estimates in groups targeted for pandemic H1N1 influenza vaccination.European Centre for Disease Prevention and Control (ECDC

    Excess mortality among the elderly in 12 European countries, February and March 2012

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    In February and March 2012, excess deaths among the elderly have been observed in 12 European countries that carry out weekly monitoring of all-cause mortality. These preliminary data indicate that the impact of influenza in Europe differs from the recent pandemic and post-pandemic seasons. The current excess mortality among the elderly may be related to the return of influenza A(H3N2) virus, potentially with added effects of a cold snap

    General and specified vulnerability to extreme temperatures among older adults

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    Extreme temperatures pose significant risks to human health and well-being. Older adults are particularly at risk and their susceptibility is a function of vulnerability to general daily life circumstances and to specified events or threats. For the first time, this paper develops a combined general and specified approach to understand the determinants of vulnerability. The findings show that most participants exhibit high levels of heat-related vulnerability, followed by cold-related vulnerability and lastly, general vulnerability. General vulnerability was shown to be primarily shaped by financial, physical and social assets. Whilst, specified vulnerability was found to be mainly shaped by human, physical and placed based assets. Such findings present opportunities to focus on the types of assets that contribute to reducing vulnerability. These findings also suggest that the role assets play in shaping vulnerability must be attended to if we are to fully understand and effectively implement strategies to reduce vulnerability

    Influenza activity in Europe during eight seasons (1999–2007): an evaluation of the indicators used to measure activity and an assessment of the timing, length and course of peak activity (spread) across Europe

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    <p>Abstract</p> <p>Background</p> <p>The European Influenza Surveillance Scheme (EISS) has collected clinical and virological data on influenza since 1996 in an increasing number of countries. The EISS dataset was used to characterise important epidemiological features of influenza activity in Europe during eight winters (1999–2007). The following questions were addressed: 1) are the sentinel clinical reports a good measure of influenza activity? 2) how long is a typical influenza season in Europe? 3) is there a west-east and/or south-north course of peak activity ('spread') of influenza in Europe?</p> <p>Methods</p> <p>Influenza activity was measured by collecting data from sentinel general practitioners (GPs) and reports by national reference laboratories. The sentinel reports were first evaluated by comparing them to the laboratory reports and were then used to assess the timing and spread of influenza activity across Europe during eight seasons.</p> <p>Results</p> <p>We found a good match between the clinical sentinel data and laboratory reports of influenza collected by sentinel physicians (overall match of 72% for +/- 1 week difference). We also found a moderate to good match between the clinical sentinel data and laboratory reports of influenza from non-sentinel sources (overall match of 60% for +/- 1 week). There were no statistically significant differences between countries using ILI (influenza-like illness) or ARI (acute respiratory disease) as case definition. When looking at the peak-weeks of clinical activity, the average length of an influenza season in Europe was 15.6 weeks (median 15 weeks; range 12–19 weeks). Plotting the peak weeks of clinical influenza activity reported by sentinel GPs against the longitude or latitude of each country indicated that there was a west-east spread of peak activity (spread) of influenza across Europe in four winters (2001–2002, 2002–2003, 2003–2004 and 2004–2005) and a south-north spread in three winters (2001–2002, 2004–2005 and 2006–2007).</p> <p>Conclusion</p> <p>We found that: 1) the clinical data reported by sentinel physicians is a valid indicator of influenza activity; 2) the length of influenza activity across the whole of Europe was surprisingly long, ranging from 12–19 weeks; 3) in 4 out of the 8 seasons, there was a west-east spread of influenza, in 3 seasons a south-north spread; not associated with type of dominant virus in those seasons.</p

    Excess mortality among the elderly in european countries, December 2014 to February 2015

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    Since December 2014 and up to February 2015, the weekly number of excess deaths from all-causes among individuals ≥ 65 years of age in 14 European countries have been significantly higher than in the four previous winter seasons. The rise in unspecified excess mortality coincides with increased proportion of influenza detection in the European influenza surveillance schemes with a main predominance of influenza A(H3N2) viruses seen throughout Europe in the current season, though cold snaps and other respiratory infections may also have had an effect

    Pooling European all-cause mortality: methodology and findings for the seasons 2008/2009 to 2010/2011

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    Several European countries have timely all-cause mortality monitoring. However, small changes in mortality may not give rise to signals at the national level. Pooling data across countries may overcome this, particularly if changes in mortality occur simultaneously. Additionally, pooling may increase the power of monitoring populations with small numbers of expected deaths, e.g. younger age groups or fertile women. Finally, pooled analyses may reveal patterns of diseases across Europe. We describe a pooled analysis of all-cause mortality across 16 European countries. Two approaches were explored. In the ‘summarized' approach, data across countries were summarized and analysed as one overall country. In the ‘stratified' approach, heterogeneities between countries were taken into account. Pooling using the ‘stratified' approach was the most appropriate as it reflects variations in mortality. Excess mortality was observed in all winter seasons albeit slightly higher in 2008/09 than 2009/10 and 2010/11. In the 2008/09 season, excess mortality was mainly in elderly adults. In 2009/10, when pandemic influenza A(H1N1) dominated, excess mortality was mainly in children. The 2010/11 season reflected a similar pattern, although increased mortality in children came later. These patterns were less clear in analyses based on data from individual countries. We have demonstrated that with stratified pooling we can combine local mortality monitoring systems and enhance monitoring of mortality across Europ

    Modelling the population effectiveness of the national seasonal influenza vaccination programme in Scotland : the impact of targeting all individuals aged 65 years and over Flu Vaccination Programme Effectiveness

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    Background: For the last 17 years, the UK has employed a routine influenza vaccination programme with the aim of reducing the spread of seasonal influenza. In mid-2000, the programme moved from a purely risk-based approach to a risk and age group targeted approach with all those aged 65+ years being included. To date, there has been no assessment of the population effectiveness of this age targeted policy in Scotland. Objectives: Statistical modelling techniques were used to determine what impact the routine vaccination of those aged 65+ years has had on influenza related morbidity and mortality in Scotland. Methods: Two Poisson regression models were developed using weekly counts of all-cause mortality, cause specific mortality and emergency hospitalisations for the period 1981 – 2012, one using week-in-year and the other using temperature to capture the seasonal variability in mortality/hospitalisations. These models were used to determine the number of excess deaths/hospitalisations associated with the introduction of the local risk and age-based vaccination programme in 2000. Results: Routinely vaccinating those aged 65+ years is associated with a reduction in excess allcause mortality, cardiovascular and COPD related mortality and COPD related hospitalisations. Our analysis suggests that using the week-in-year model, on average, 732 (95%CI 66 – 1,398) deaths from all-causes, 248 (95%CI 10 – 486) cardiovascular related deaths, 123 (95%CI 28 – 218) COPD related deaths, and 425 (95%CI 258 – 592) COPD related hospitalisations have been prevented each flu season among the those aged 65+. Similar results were found using the temperature model. There was no evidence to suggest that the change in policy was associated with reductions in influenza/pneumonia related mortality or influenza/cardiovascular related hospitalisations. Conclusions: Routinely vaccinating those aged 65+ years appears to have reduced influenza related morbidity and mortality in Scotland. With the childhood vaccination programme well underway, these data provide an importance benchmark which can be used to accurately assess the impact of this new seasonal influenza vaccination programme

    Genotypic characterisation and cluster analysis of Campylobacter jejuni isolates from domestic pets, human clinical cases and retail food

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    The genetic similarity of Campylobacter jejuni isolates from pets, compared to human clinical cases and retail food isolates collected in Ireland over 2001-2006 was investigated by cluster analysis of pulsed-field gel electrophoresis (PFGE) fingerprinting profiles. Comparison of the PFGE profiles of 60 pet isolates and 109 human isolates revealed that seven (4.1%) profiles were grouped in clusters including at least one human and one pet C. jejuni isolate. In total six (1.6%) of 60 pet and 310 food profiles were in clusters with at least one food and one pet C. jejuni isolate. The detection of only a small number of genetically indistinguishable isolates by PFGE profile cluster analysis from pets and from humans with enteritis in this study suggests that pets are unlikely to be an important reservoir for human campylobacteriosis in Ireland. However, genetically indistinguishable isolates were detected and C. jejuni from pets may circulate and may contribute to clinical infections in humans. In addition, contaminated food fed to pets may be a potential source of Campylobacter infection in pets, which may subsequently pose a risk to humans

    Using GIS to create synthetic disease outbreaks

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    BACKGROUND: The ability to detect disease outbreaks in their early stages is a key component of efficient disease control and prevention. With the increased availability of electronic health-care data and spatio-temporal analysis techniques, there is great potential to develop algorithms to enable more effective disease surveillance. However, to ensure that the algorithms are effective they need to be evaluated. The objective of this research was to develop a transparent user-friendly method to simulate spatial-temporal disease outbreak data for outbreak detection algorithm evaluation. A state-transition model which simulates disease outbreaks in daily time steps using specified disease-specific parameters was developed to model the spread of infectious diseases transmitted by person-to-person contact. The software was developed using the MapBasic programming language for the MapInfo Professional geographic information system environment. RESULTS: The simulation model developed is a generalised and flexible model which utilises the underlying distribution of the population and incorporates patterns of disease spread that can be customised to represent a range of infectious diseases and geographic locations. This model provides a means to explore the ability of outbreak detection algorithms to detect a variety of events across a large number of stochastic replications where the influence of uncertainty can be controlled. The software also allows historical data which is free from known outbreaks to be combined with simulated outbreak data to produce files for algorithm performance assessment. CONCLUSION: This simulation model provides a flexible method to generate data which may be useful for the evaluation and comparison of outbreak detection algorithm performance

    The community impact of the 2009 influenza pandemic in the WHO European Region: a comparison with historical seasonal data from 28 countries

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    Contains fulltext : 109779.pdf (publisher's version ) (Open Access)BACKGROUND: The world has recently experienced the first influenza pandemic of the 21st century that lasted 14 months from June 2009 to August 2010. This study aimed to compare the timing, geographic spread and community impact during the winter wave of influenza pandemic A (H1N1) 2009 to historical influenza seasons in countries of the WHO European region. METHODS: We assessed the timing of pandemic by comparing the median peak of influenza activity in countries of the region during the last seven influenza seasons. The peaks of influenza activity were selected by two independent researchers using predefined rules. The geographic spread was assessed by correlating the peak week of influenza activity in included countries against the longitude and latitude of the central point in each country. To assess the community impact of pandemic influenza, we constructed linear regression models to compare the total and age-specific influenza-like-illness (ILI) or acute respiratory infection (ARI) rates reported by the countries in the pandemic season to those observed in the previous six influenza seasons. RESULTS: We found that the influenza activity reached its peak during the pandemic, on average, 10.5 weeks (95% CI 6.4-14.2) earlier than during the previous 6 seasons in the Region, and there was a west to east spread of pandemic A(H1N1) influenza virus in the western part of the Region. A regression analysis showed that the total ILI or ARI rates were not higher than historical rates in 19 of the 28 countries. However, in countries with age-specific data, there were significantly higher consultation rates in the 0-4 and/or 5-14 age groups in 11 of the 20 countries. CONCLUSIONS: Using routine influenza surveillance data, we found that pandemic influenza had several differential features compared to historical seasons in the region. It arrived earlier, caused significantly higher number of outpatient consultations in children in most countries and followed west to east spread that was previously observed during some influenza seasons with dominant A (H3N2) ifluenza viruses. The results of this study help to understand the epidemiology of 2009 influenza pandemic and can be used for pandemic preparedness planning
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