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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.

Sentinel surveillance for severe acute respiratory infection and influenza-like illness is effective in resource-limited settings.

The emergence of a novel strain of influenza virus A (H1N1) in April 2009 focused attention on influenza surveillance capabilities worldwide. In consultations before the 2009 outbreak of influenza subtype H1N1, the World Health Organization had concluded that the world was unprepared to respond to an influenza pandemic, due in part to inadequate global surveillance and response capacity. We describe a sentinel surveillance system that could enhance the quality of influenza epidemiologic and laboratory data and strengthen a country’s capacity for seasonal, novel, and pandemic influenza detection and prevention. Such a system would 1) provide data for a better understanding of the epidemiology and extent of seasonal influenza, 2) provide a platform for the study of other acute febrile respiratory illnesses, 3) provide virus isolates for the development of vaccines, 4) inform local pandemic planning and vaccine policy, 5) monitor influenza epidemics and pandemics, and 6) provide infrastructure for an early warning system for outbreaks of new virus subtypes.

Background

There is limited information about the epidemiology of influenza in Africa. We describe the epidemiology and seasonality of influenza in Morocco from 1996 to 2009 with particular emphasis on the 2007–2008 and 2008–2009 influenza seasons. Successes and challenges of the enhanced surveillance system introduced in 2007 are also discussed.

Methods

Virologic sentinel surveillance for influenza virus was initiated in Morocco in 1996 using a network of private practitioners that collected oro-pharyngeal and naso-pharyngeal swabs from outpatients presenting with influenza-like-illness (ILI). The surveillance network expanded over the years to include inpatients presenting with severe acute respiratory illness (SARI) at hospitals and syndromic surveillance for ILI and acute respiratory infection (ARI). Respiratory samples and structured questionnaires were collected from eligible patients, and samples were tested by immunofluorescence assays and by viral isolation for influenza viruses.

Results

We obtained a total of 6465 respiratory specimens during 1996 to 2009, of which, 3102 were collected during 2007–2009. Of those, 2249 (72%) were from patients with ILI, and 853 (27%) were from patients with SARI. Among the 3,102 patients, 98 (3%) had laboratory-confirmed influenza, of whom, 85 (87%) had ILI and 13 (13%) had SARI. Among ILI patients, the highest proportion of laboratory-confirmed influenza occurred in children less than 5 years of age (3/169; 2% during 2007–2008 and 23/271; 9% during 2008–2009) and patients 25–59 years of age (8/440; 2% during 2007–2009 and 21/483; 4% during 2008–2009). All SARI patients with influenza were less than 14 years of age. During all surveillance years, influenza virus circulation was seasonal with peak circulation during the winter months of October through April.

Conclusion

Influenza results in both mild and severe respiratory infections in Morocco, and accounted for a large proportion of all hospitalizations for severe respiratory illness among children 5 years of age and younger.

In this paper, we investigate the usefulness of work and school absenteeism surveillance as an early warning system for influenza. In particular, time trends in daily absenteeism rates collected during the A(H1N1)2009 pandemic are compared with weekly incidence rates of influenza-like illness (ILI) obtained from the Belgian Sentinel General Practitioner (SGP) network. The results indicate a rise in absenteeism rates prior to the onset of the influenza epidemic, suggesting that absenteeism surveillance is a promising tool for early warning of influenza epidemics. To convincingly conclude on the usefulness of absenteeism data for early warning, additional data covering several influenza seasons is needed.

Background

The weekly proportion of laboratory tests that are positive for influenza is used in public health surveillance systems to identify periods of influenza activity. We aimed to estimate the sensitivity of influenza testing in Canada based on results of a national respiratory virus surveillance system.

Methods and Findings

The weekly number of influenza-negative tests from 1999 to 2006 was modelled as a function of laboratory-confirmed positive tests for influenza, respiratory syncytial virus (RSV), adenovirus and parainfluenza viruses, seasonality, and trend using Poisson regression. Sensitivity was calculated as the number of influenza positive tests divided by the number of influenza positive tests plus the model-estimated number of false negative tests. The sensitivity of influenza testing was estimated to be 33% (95%CI 32–34%), varying from 30–40% depending on the season and region.

Conclusions

The estimated sensitivity of influenza tests reported to this national laboratory surveillance system is considerably less than reported test characteristics for most laboratory tests. A number of factors may explain this difference, including sample quality and specimen procurement issues as well as test characteristics. Improved diagnosis would permit better estimation of the burden of influenza.

Human metapneumovirus (HMPV) is a recently identified Paramyxovirus first isolated from hospitalized children with acute respiratory tract infections (ARTI). We sought evidence of HMPV infection in patients who had visited general practitioners, had influenzalike illnesses (ILI), and had negative tests for influenza and Human respiratory syncytial virus (HRSV). As part of national virologic surveillance, sentinel general practices in England and Wales collected samples from patients of all ages with ILI during winter 2000–01. Reverse transcriptase-polymerase chain reaction (PCR) for HMPV, influenza A (H1 and H3), influenza B, and HRSV was used to screen combined nose and throat swabs. PCR products from the HMPV-positive samples were sequenced to confirm identity and construct phylogenetic trees. Of 711 swabs submitted, 408 (57.3%) were negative for influenza and HRSV; HMPV was identified in 9 (2.2%) patients. HMPV appears to be associated with community-acquired ARTI. The extent of illness and possible complications related to this new human virus need to be clarified

Aims: To estimate excess morbidity during periods of influenza and respiratory syncytial virus (RSV) activity.

Methods: Retrospective analysis of a sentinel practice network database in active and non-active virus periods. Main outcome measures: clinical diagnoses of new episodes of influenza-like illness (ILI), acute bronchitis, asthma, and otitis media.

Results: The clinical diagnosis of ILI was consistent with influenza virus activity and acute bronchitis with RSV. During periods of virus activity, estimates of excess morbidity in children aged 1–4 and 5–14 years diagnosed as having acute otitis media exceeded those diagnosed with each of the other three conditions; in children <1 year estimates for acute bronchitis were highest. Using a broad definition of virus activity and summarising the data for all children diagnosed with ILI, 60% was attributable to influenza (40% RSV) as were 37% of episodes diagnosed as acute bronchitis, 9% of those with asthma and 48% of those with otitis media. Using a narrow definition, corresponding proportions were: for ILI diagnoses 77% (23% RSV), acute bronchitis 32%, asthma zero, and otitis media 45%. Acute bronchitis was diagnosed twice as frequently in association with RSV as with influenza in all age groups: excess asthma episodes were only evident in RSV active periods.

Conclusions: Except in relation to ILI, RSV caused more illness than the influenza virus in the respiratory diagnoses examined, emphasising the need for RSV prevention and treatment. Influenza was not associated with excess asthma episodes.

Background

The influenza A(H1N1)pdm09 virus has been a challenge for public health surveillance systems in all countries. In Antananarivo, the first imported case was reported on August 12, 2009. This work describes the spread of A(H1N1)pdm09 in Madagascar.

Methods

The diffusion of influenza A(H1N1)pdm09 in Madagascar was explored using notification data from a sentinel network. Clinical data were charted to identify peaks at each sentinel site and virological data was used to confirm viral circulation.

Results

From August 1, 2009 to February 28, 2010, 7,427 patients with influenza-like illness were reported. Most patients were aged 7 to 14 years. Laboratory tests confirmed infection with A(H1N1)pdm09 in 237 (33.2%) of 750 specimens. The incidence of patients differed between regions. By determining the epidemic peaks we traced the diffusion of the epidemic through locations and time in Madagascar. The first peak was detected during the epidemiological week 47-2009 in Antananarivo and the last one occurred in week 07-2010 in Tsiroanomandidy.

Conclusion

Sentinel surveillance data can be used for describing epidemic trends, facilitating the development of interventions at the local level to mitigate disease spread and impact.

Background

Syndromic surveillance is increasingly being evaluated for its potential for early warning of increased disease activity in the population. However, interpretation is hampered by the difficulty of attributing a causative pathogen. We described the temporal relationship between laboratory counts of influenza and respiratory syncytial virus (RSV) detection and alternative groupings of Emergency Department (ED) respiratory diagnoses.

Methods

ED and laboratory data were obtained for the south-eastern area of Sydney, NSW for the period 1 June 2001 - 1 December 2006. Counts of ED visits and laboratory confirmed positive RSV and influenza cases were aggregated by week. Semi-parametric generalized additive models (GAM) were used to determine the association between the incidence of RSV and influenza and the incidence of respiratory syndrome ED presentations while controlling for temporal confounders.

Results

For every additional RSV laboratory count, ED diagnoses of bronchiolitis increased by 3.1% (95%CI: 2.7%-3.5%) in the same week. For every additional influenza laboratory count, ED diagnoses of influenza-like illness increased by 4.7% (95%CI: 4.2%-5.2%) one week earlier.

Conclusion

In this study, large increases in ED diagnoses of bronchiolitis and influenza-like illness were independent and proxy indicators for RSV and influenza activity, respectively.

Objective: To use laboratory data to assess the specificity of syndromes used by the New York City emergency department (ED) syndromic surveillance system to monitor influenza activity. Design: For the period from October 1, 2009 through March 31, 2010, we examined the correlation between citywide ED syndrome assignment and laboratory-confirmed influenza and respiratory syncytial virus (RSV). In addition, ED syndromic data from five select NYC hospitals were matched at the patient and visit level to corresponding laboratory reports of influenza and RSV. The matched dataset was used to evaluate syndrome assignment by disease and to calculate the sensitivity and specificity of the influenza-like illness (ILI) syndrome. Results: Citywide ED visits for ILI correlated well with influenza laboratory diagnoses (R=0.92). From October 1, 2009, through March 31, 2010, there were 264,532 ED visits at the five select hospitals, from which the NYC Department of Health and Mental Hygiene (DOHMH) received confirmatory laboratory reports of 655 unique cases of influenza and 1348 cases of RSV. The ED visit of most (56%) influenza cases had been categorized in the fever/flu syndrome; only 15% were labeled ILI. Compared to other influenza-related syndromes, ILI had the lowest sensitivity (15%) but the highest specificity (90%) for laboratory-confirmed influenza. Sensitivity and specificity varied by age group and influenza activity level. Conclusions: The ILI syndrome in the NYC ED syndromic surveillance system served as a specific but not sensitive indicator for influenza during the 2009-2010 influenza season. Despite its limited sensitivity, the ILI syndrome can be more informative for tracking influenza trends than the fever/flu or respiratory syndromes because it is less likely to capture cases of other respiratory viruses. However, ED ILI among specific age groups should be interpreted alongside laboratory surveillance data. ILI remains a valuable tool for monitoring influenza activity and trends as it facilitates comparisons nationally and across jurisdictions and is easily communicated to the public.

The European Paediatric Influenza Analysis (EPIA) project is a multi-country project that was created to collect, analyse and present data regarding the paediatric influenza burden in European countries, with the purpose of providing the necessary information to make evidence-based decisions regarding influenza immunisation recommendations for children. The initial approach taken is based on existing weekly virological and age-specific influenza-like illness (ILI) data from surveillance networks across Europe. We use a multiple regression model guided by longitudinal weekly patterns of influenza virus to attribute the weekly ILI consultation incidence pattern to each influenza (sub)type, while controlling for the effect of respiratory syncytial virus (RSV) epidemics. Modelling the ILI consultation incidence during 2002/2003–2008 revealed that influenza infections that presented for medical attention as ILI affected between 0.3% and 9.8% of children aged 0–4 and 5–14 years in England, Italy, The Netherlands and Spain in an average season. With the exception of Spain, these rates were always higher in children aged 0–4 years. Across the six seasons analysed (five seasons were analysed from the Italian data), the model attributed 47–83% of the ILI burden in primary care to influenza virus infection in the various countries, with the A(H3N2) virus playing the most important role, followed by influenza viruses B and A(H1N1). National season averages from the four countries studied indicated that between 0.4% and 18% of children consulted a physician for ILI, with the percentage depending on the country and health care system. Influenza virus infections explained the majority of paediatric ILI consultations in all countries. The next step will be to apply the EPIA modelling approach to severe outcomes indicators (i.e. hospitalisations and mortality data) to generate a complete range of mild and severe influenza burden estimates needed for decision making concerning paediatric influenza vaccination.

The studied respiratory syndromes are suitable for syndromic surveillance because they reflect respiratory pathogen activity patterns

Syndromic surveillance is increasingly used to signal unusual illness events. To validate data-source selection, we retrospectively investigated the extent to which 6 respiratory syndromes (based on different medical registries) reflected respiratory pathogen activity. These syndromes showed higher levels in winter, which corresponded with higher laboratory counts of Streptococcus pneumoniae, respiratory syncytial virus, and influenza virus. Multiple linear regression models indicated that most syndrome variations (up to 86%) can be explained by counts of respiratory pathogens. Absenteeism and pharmacy syndromes might reflect nonrespiratory conditions as well. We also observed systematic syndrome elevations in the fall, which were unexplained by pathogen counts but likely reflected rhinovirus activity. Earliest syndrome elevations were observed in absenteeism data, followed by hospital data (+1 week), pharmacy/general practitioner consultations (+2 weeks), and deaths/laboratory submissions (test requests) (+3 weeks). We conclude that these syndromes can be used for respiratory syndromic surveillance, since they reflect patterns in respiratory pathogen activity.

Background

There is limited information on influenza and respiratory syncytial virus (RSV) seasonal patterns in tropical areas, although there is renewed interest in understanding the seasonal drivers of respiratory viruses.

Methods

We review geographic variations in seasonality of laboratory-confirmed influenza and RSV epidemics in 137 global locations based on literature review and electronic sources. We assessed peak timing and epidemic duration and explored their association with geography and study settings. We fitted time series model to weekly national data available from the WHO influenza surveillance system (FluNet) to further characterize seasonal parameters.

Results

Influenza and RSV activity consistently peaked during winter months in temperate locales, while there was greater diversity in the tropics. Several temperate locations experienced semi-annual influenza activity with peaks occurring in winter and summer. Semi-annual activity was relatively common in tropical areas of Southeast Asia for both viruses. Biennial cycles of RSV activity were identified in Northern Europe. Both viruses exhibited weak latitudinal gradients in the timing of epidemics by hemisphere, with peak timing occurring later in the calendar year with increasing latitude (P<0.03). Time series model applied to influenza data from 85 countries confirmed the presence of latitudinal gradients in timing, duration, seasonal amplitude, and between-year variability of epidemics. Overall, 80% of tropical locations experienced distinct RSV seasons lasting 6 months or less, while the percentage was 50% for influenza.

Conclusion

Our review combining literature and electronic data sources suggests that a large fraction of tropical locations experience focused seasons of respiratory virus activity in individual years. Information on seasonal patterns remains limited in large undersampled regions, included Africa and Central America. Future studies should attempt to link the observed latitudinal gradients in seasonality of viral epidemics with climatic and population factors, and explore regional differences in disease transmission dynamics and attack rates.

Seasonal epidemics of influenza and respiratory syncytial virus are responsible for significant morbidity and mortality worldwide. Infrequently, novel or reemergent strains of influenza A virus have caused rapid, severe global pandemics resulting in millions of fatalities. The ability to efficiently and accurately detect and differentiate respiratory viruses is paramount for effective treatment, infection control, and epidemiological surveillance. We evaluated the ability of two FDA-cleared nucleic acid-based tests, the semiautomated respiratory virus nucleic acid test (VRNAT) and the fully automated respiratory virus nucleic acid test SP (RVNATSP) (Nanosphere Inc., Northbrook, IL) to detect influenza A virus, influenza B virus, and respiratory syncytial virus A and B (RSV A/B) from clinical nasopharyngeal swab specimens. Detection of viral RNA in both tests is based on nucleic acid amplification followed by hybridization to capture probes immobilized on a glass slide. A novel technology utilizing gold nanoparticle-conjugated probes is utilized to detect the presence of captured target DNA. This microarray-based approach to detection has proven to be more sensitive than the traditional culture/direct fluorescent-antibody assay (DFA) method for detecting RSV and influenza viruses in clinical specimens, including the novel 2009 H1N1 strain. Specifically, we report 98.0% sensitivity and 96.5% specificity for the VRNAT compared to culture/DFA. Further, the VRNAT detected virus in an additional 58% of specimens that were culture negative. These data were confirmed using bidirectional sequencing. Evaluation of the fully automated RVNATSP, which is built on the same detection technology as the VRNAT but contains an updated processor enabling complete automation, revealed the two tests to be functionally equivalent. Thus, the RVNATSP is a fully automated sample-to-result test capable of reliable detection of select respiratory viruses directly from clinical specimens in 3.5 h.

Introduction

Although WHO declared the world moving into the post-pandemic period on August 10, 2010, influenza A(H1N1) 2009 virus continued to circulate globally. Its impact was expected to continue during the 2010–11 influenza season. This study describes the nationwide surveillance findings of the pandemic and post-pandemic influenza periods in Taiwan and assesses the impact of influenza A(H1N1) 2009 during the post-pandemic period.

Methods

The Influenza Laboratory Surveillance Network consisted of 12 contract laboratories for collecting and testing samples with acute respiratory tract infections. Surveillance of emergency room visits and outpatient department visits for influenza-like illness (ILI) were conducted using the Real-Time Outbreak and Disease Surveillance system and the National Health Insurance program data, respectively. Hospitalized cases with severe complications and deaths were reported to the National Notifiable Disease Surveillance System.

Results

During the 2009–10 influenza season, pandemic A(H1N1) 2009 was the predominant circulating strain and caused 44 deaths. However, the 2010–11 influenza season began with A(H3N2) being the predominant circulating strain, changing to A(H1N1) 2009 in December 2010. Emergency room and outpatient department ILI surveillance displayed similar trends. By March 31, 2011, there were 1,751 cases of influenza with severe complications; 50.1% reported underlying diseases. Of the reported cases, 128 deaths were associated with influenza. Among these, 93 (72.6%) were influenza A(H1N1) 2009 and 30 (23.4%) A(H3N2). Compared to the pandemic period, during the immediate post-pandemic period, increased number of hospitalizations and deaths were observed, and the patients were consistently older.

Conclusions

Reemergence of influenza A(H1N1) 2009 during the 2010–11 influenza season had an intense activity with age distribution shift. To further mitigate the impact of future influenza epidemics, Taiwan must continue its multifaceted influenza surveillance systems, remain flexible with antiviral use policies, and revise the vaccine policies to include the population most at risk.

Nasal swab from patients with acute flu-like illness were evaluated for the presence of respiratory viruses in the Rhone-Alpes region of France from 1 October 1994 through 2 May 1995. The relative frequencies and seasonal distributions of the specific viruses were assessed. In addition, virus type was correlated with specific clinical signs and symptoms. During the study, 962 samples were collected by 75 medical practitioners participating in the Groupe Regional d'Observation de la Grippe surveillance network. One or more viruses were detected from 348 samples (36.1%), including 108 respiratory syncytial virus (RSV), 64 influenza virus A type H3N2, 47 influenza virus B, 64 coronavirus, 35 rhinovirus, 22 adenovirus, 5 enterovirus, and 3 parainfluenza-fluenza strains. There were 16 mixed infections. RSV infections peaked in the early winter, and influenza viruses A and B infections peaked during the late winter and early spring. There were two peaks of coronavirus infections (late fall and late winter). Other viruses were detected at lower levels throughout the study period. Patients from whom adenovirus was isolated were significantly more likely to have a fever of > 39.5 degrees C than were patients with other detectable viruses (P < 0.001). Furthermore, there was a significant correlation between influenza and cough (P < 0.01) and RSV and bronchiolitis (P < .001). Thus, the current study defined the overall and relative frequencies of respiratory virus detection from nasal swab specimens in patients with an acute flu-like illness in the Rhone-Alpes region of France during a 7-month period. Correlation with clinical signs and symptoms and provisional conclusions regarding seasonality were also determined.

ICD-9 codes collected automatically in a syndromic system are sensitive and specific in detecting outbreaks caused by respiratory viruses.

With the spread of avian influenza, use of automated data streams to rapidly detect and track human influenza cases has increased. We performed correlation analyses to determine whether International Classification of Diseases, Ninth Revision (ICD-9), groupings used to detect influenzalike illness (ILI) within an automated syndromic system correlate with respiratory virus laboratory test results in the same population (r = 0.71 or 0.86, depending on group). We used temporal and signal-to-noise analysis to identify 2 subsets of ICD-9 codes that most accurately represent ILI trends, compared nationwide sentinel ILI surveillance data from the Centers for Disease Control and Prevention with the automated data (r = 0.97), and found the most sensitive set of ICD-9 codes for respiratory illness surveillance. Our results demonstrate a method for selecting the best group of ICD-9 codes to assist system developers and health officials who are interpreting similar data for daily public health activities.

Background

Antigenic variation of influenza virus necessitates annual reformulation of seasonal influenza vaccines, which contain two type A strains (H1N1 and H3N2) and one type B strain. We used a test negative case control design to estimate influenza vaccine effectiveness (VE) against influenza by type and subtype over two consecutive seasons in Victoria, Australia.

Methods

Patients presenting with influenza-like illness to general practitioners (GPs) in a sentinel surveillance network during 2007 and 2008 were tested for influenza. Cases tested positive for influenza by polymerase chain reaction and controls tested negative for influenza. Vaccination status was recorded by sentinel GPs. Vaccine effectiveness was calculated as [(1 - adjusted odds ratio) × 100%].

Results

There were 386 eligible study participants in 2007 of whom 50% were influenza positive and 19% were vaccinated. In 2008 there were 330 eligible study participants of whom 32% were influenza positive and 17% were vaccinated. Adjusted VE against A/H3N2 influenza in 2007 was 68% (95% CI, 32 to 85%) but VE against A/H1N1 (27%; 95% CI, -92 to 72%) and B (84%; 95% CI, -2 to 98%) were not statistically significant. In 2008, the adjusted VE estimate was positive against type B influenza (49%) but negative for A/H1N1 (-88%) and A/H3N2 (-66%); none was statistically significant.

Conclusions

Type- and subtype-specific assessment of influenza VE is needed to identify variations that cannot be differentiated from a measure of VE against all influenza. Type- and subtype-specific influenza VE estimates in Victoria in 2007 and 2008 were generally consistent with strain circulation data.

OBJECTIVE:

Respiratory syncytial virus (RSV) is the most common cause of severe lower respiratory tract infection in young children and is increasingly recognized as a cause of influenza-like illness in those older than 65 years of age. A surveillance system to provide timely local information about RSV activity in Nova Scotia (NS) is described.

METHODS:

A case report form was developed for weekly reporting of all laboratory isolates of RSV at diagnostic laboratories around the province. Laboratories were asked to send the forms by fax each Friday to the Nova Scotia Department of Health Promotion and Protection. Data were entered in Excel (Microsoft, USA) and aggregate results summarized by age, sex, health district and date of laboratory confirmation for 2005 to 2008.

RESULTS:

During three winter seasons (2005–2006, 2006–2007 and 2007–2008), there were 207, 350 and 186 isolates of RSV reported in NS, respectively. The average incidences of RSV in NS varied greatly by age, with the highest rates in infants younger than 24 months of age, and approaching 4000 cases per 100,000 population in infants up to five months of age. The duration of the RSV outbreak was approximately five to six months each year, but the month of onset varied.

CONCLUSIONS:

A RSV surveillance system was successfully established in NS that provides weekly data to the public health system, clinicians and infection control practitioners. The time of onset and severity of the RSV season varied over time. These data can be used to plan anti-RSV passive prophylaxis programs and infection control education, and distinguish RSV outbreaks from other viruses in acute care and long-term care settings.

Background

Hospital deaths following several hospital admissions or long hospital stays may be indicative of a low quality of dying. Although place of death has been extensively investigated at population level, hospital use in the last months of life and its determinants have been studied less often, especially in Europe and with a general end-of-life patient population. In this study we aim to describe hospital use in the last three months of life in Belgium and identify associated patient, disease and healthcare factors.

Methods

We conducted a retrospective registration study (13 weeks in 2004) with the Belgian Sentinel Network of General Practitioners, an epidemiological surveillance system representative of all GPs in Belgium, covering 1.75% of the total Belgian patient population. All registered non-sudden or expected deaths of patients (aged one year or older) at the GPs' practices were included. Bivariate and regression analyses were performed.

Results

The response rate was 87%. The GPs registered 319 deaths that met inclusion criteria. Sixty percent had been hospitalised at least once in the last three months of life, for a median of 19 days. The percentage of patients hospitalised increased exponentially in the last weeks before death; one fifth was admitted in the final week of life. Seventy-two percent of patients hospitalised at least once in the final three months died in hospital. A palliative treatment goal, death from cardiovascular diseases, the expression of a wish to die in an elderly home and palliative care delivery by the GP were associated with lower hospitalisation odds.

Conclusion

Hospital care plays a large role in the end of patients' lives in Belgium, especially in the final weeks of life. The result is a high rate of hospital deaths, showing the institutionalised nature of dying. Patients' clinical conditions, the expression of preferences and also healthcare characteristics such as being treated as a palliative care patient, seem to be associated with hospital transfers. It is recommended that hospitalisation decisions are only made after careful consideration. Short admissions in the final days of life should be prevented in order to make dying at home more feasible.

Results from a European multicentre case-control study reported by Marta Valenciano and colleagues suggest good protection by the pandemic monovalent H1N1 vaccine against pH1N1 and no effect of the 2009–2010 seasonal influenza vaccine on H1N1.

Background

A multicentre case-control study based on sentinel practitioner surveillance networks from seven European countries was undertaken to estimate the effectiveness of 2009–2010 pandemic and seasonal influenza vaccines against medically attended influenza-like illness (ILI) laboratory-confirmed as pandemic influenza A (H1N1) (pH1N1).

Methods and Findings

Sentinel practitioners swabbed ILI patients using systematic sampling. We included in the study patients meeting the European ILI case definition with onset of symptoms >14 days after the start of national pandemic vaccination campaigns. We compared pH1N1 cases to influenza laboratory-negative controls. A valid vaccination corresponded to >14 days between receiving a dose of vaccine and symptom onset. We estimated pooled vaccine effectiveness (VE) as 1 minus the odds ratio with the study site as a fixed effect. Using logistic regression, we adjusted VE for potential confounding factors (age group, sex, month of onset, chronic diseases and related hospitalizations, smoking history, seasonal influenza vaccinations, practitioner visits in previous year). We conducted a complete case analysis excluding individuals with missing values and a multiple multivariate imputation to estimate missing values. The multivariate imputation (n = 2902) adjusted pandemic VE (PIVE) estimates were 71.9% (95% confidence interval [CI] 45.6–85.5) overall; 78.4% (95% CI 54.4–89.8) in patients <65 years; and 72.9% (95% CI 39.8–87.8) in individuals without chronic disease. The complete case (n = 1,502) adjusted PIVE were 66.0% (95% CI 23.9–84.8), 71.3% (95% CI 29.1–88.4), and 70.2% (95% CI 19.4–89.0), respectively. The adjusted PIVE was 66.0% (95% CI −69.9 to 93.2) if vaccinated 8–14 days before ILI onset. The adjusted 2009–2010 seasonal influenza VE was 9.9% (95% CI −65.2 to 50.9).

Conclusions

Our results suggest good protection of the pandemic monovalent vaccine against medically attended pH1N1 and no effect of the 2009–2010 seasonal influenza vaccine. However, the late availability of the pandemic vaccine and subsequent limited coverage with this vaccine hampered our ability to study vaccine benefits during the outbreak period. Future studies should include estimation of the effectiveness of the new trivalent vaccine in the upcoming 2010–2011 season, when vaccination will occur before the influenza season starts.

Please see later in the article for the Editors' Summary

Editors' Summary

Background

Following the World Health Organization's declaration of pandemic phase six in June 2009, manufacturers developed vaccines against pandemic influenza A 2009 (pH1N1). On the basis of the scientific opinion of the European Medicines Agency, the European Commission initially granted marketing authorization to three pandemic vaccines for use in European countries. During the autumn of 2009, most European countries included the 2009–2010 seasonal influenza vaccine and the pandemic vaccine in their influenza vaccination programs.

The Influenza Monitoring Vaccine Effectiveness in Europe network (established to monitor seasonal and pandemic influenza vaccine effectiveness) conducted seven case-control and three cohort studies in seven European countries in 2009–2010 to estimate the effectiveness of the pandemic and seasonal vaccines. Data from the seven pilot case-control studies were pooled to provide overall adjusted estimates of vaccine effectiveness.

Why Was This Study Done?

After seasonal and pandemic vaccines are made available to populations, it is necessary to estimate the effectiveness of the vaccines at the population level during every influenza season. Therefore, this study was conducted in European countries to estimate the pandemic influenza vaccine effectiveness and seasonal influenza vaccine effectiveness against people presenting to their doctor with influenza-like illness who were confirmed (by laboratory tests) to be infected with pH1N1.

What Did the Researchers Do and Find?

The researchers conducted a multicenter case-control study on the basis of practitioner surveillance networks from seven countries—France, Hungary, Ireland, Italy, Romania, Portugal, and Spain. Patients consulting a participating practitioner for influenza-like illness had a nasal or throat swab taken within 8 days of symptom onset. Cases were swabbed patients who tested positive for pH1N1. Patients presenting with influenza-like illness whose swab tested negative for any influenza virus were controls.

Individuals were considered vaccinated if they had received a dose of the vaccine more than 14 days before the date of onset of influenza-like illness and unvaccinated if they were not vaccinated at all, or if the vaccine was given less than 15 days before the onset of symptoms. The researchers analyzed pandemic influenza vaccination effectiveness in those vaccinated less than 8 days, those vaccinated between and including 8 and 14 days, and those vaccinated more than 14 days before onset of symptoms compared to those who had never been vaccinated.

The researchers used modeling (taking account of all potential confounding factors) to estimate adjusted vaccine effectiveness and stratified the adjusted pandemic influenza vaccine effectiveness and the adjusted seasonal influenza vaccine effectiveness in three age groups (<15, 15–64, and ≥65 years of age).

The adjusted results suggest that the 2009–2010 seasonal influenza vaccine did not protect against pH1N1 illness. However, one dose of the pandemic vaccines used in the participating countries conferred good protection (65.5%–100% according to various stratifications performed) against pH1N1 in people who attended their practitioner with influenza-like illness, especially in people aged <65 years and in those without any chronic disease. Furthermore, good pandemic influenza vaccine effectiveness was observed as early as 8 days after vaccination.

What Do These Findings Mean?

The results of this study provide early estimates of the pandemic influenza vaccine effectiveness suggesting that the monovalent pandemic vaccines have been effective. The findings also give an indication of the vaccine effectiveness for the Influenza A (H1N1) 2009 strain included in the 2010–2011 seasonal vaccines, although specific vaccine effectiveness studies will have to be conducted to verify if similar good effectiveness are observed with 2010–2011 trivalent vaccines. However, the results of this study should be interpreted with caution because of limitations in the pandemic context (late timing of the studies, low incidence, low vaccine coverage leading to imprecise estimates) and potential biases due the study design, confounding factors, and missing values. The researchers recommend that in future season studies, the sample size per country should be enlarged in order to allow for precise pooled and stratified analyses.

Additional Information

Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000388.

The World Health Organization has information on H1N1 vaccination

The US Centers for Disease Control and Prevention provides a fact sheet on the 2009 H1N1 influenza virus

The US Department of Health and Human services has a comprehensive website on flu

The European Centre for Disease Prevention and Control provides information on 2009 H1N1 pandemic

The European Centre for Disease Prevention and Control presents a summary of the 2009 H1N1 pandemic in Europe and elsewhere

Background

Computerized morbidity registration networks might serve as early warning systems in a time where natural epidemics such as the H1N1 flu can easily spread from one region to another.

Methods

In this contribution we examine whether general practice based broad-spectrum computerized morbidity registration networks have the potential to act as a valid surveillance instrument of frequently occurring diseases. We compare general practice based computerized data assessing the frequency of influenza-like illness (ILI) and acute respiratory infections (ARI) with data from a well established case-specific sentinel network, the European Influenza Surveillance Scheme (EISS). The overall frequency and trends of weekly ILI and ARI data are compared using both networks.

Results

Detection of influenza-like illness and acute respiratory illness occurs equally fast in EISS and the computerized network. The overall frequency data for ARI are the same for both networks, the overall trends are similar, but the increases and decreases in frequency do not occur in exactly the same weeks. For ILI, the overall rate was slightly higher for the computerized network population, especially before the increase of ILI, the overall trend was almost identical and the increases and decreases occur in the same weeks for both networks.

Conclusions

Computerized morbidity registration networks are a valid tool for monitoring frequent occurring respiratory diseases and the detection of sudden outbreaks.

Background

Some studies have evaluated vaccine effectiveness in preventing outpatient influenza while others have analysed its effectiveness in preventing hospitalizations. This study evaluates the effectiveness of the trivalent influenza vaccine in preventing outpatient illness and hospitalizations from laboratory-confirmed influenza in the 2010–2011 season.

Methods

We conducted a nested case–control study in the population covered by the general practitioner sentinel network for influenza surveillance in Navarre, Spain. Patients with influenza-like illness in hospitals and primary health care were swabbed for influenza testing. Influenza vaccination status and other covariates were obtained from health care databases. Using logistic regression, the vaccination status of laboratory-confirmed influenza cases was compared with that of test-negative controls, adjusting for age, sex, comorbidity, outpatient visits in the previous 12 months, health care setting, time between symptom onset and swabbing, period and A(H1N1)pdm09 vaccination. Effectiveness was calculated as (1-odds ratio)x100.

Results

The 303 confirmed influenza cases (88% for A(H1N1)pdm09 influenza) were compared with the 286 influenza test-negative controls. The percentage of persons vaccinated against influenza was 4.3% and 15.7%, respectively (p<0.001). The adjusted estimate of effectiveness was 67% (95% CI: 24%, 86%) for all patients and 64% (95% CI: 8%, 86%) in those with an indication for vaccination (persons age 60 or older or with major chronic conditions). Having received both the 2010–2011 seasonal influenza vaccine and the 2009–2010 pandemic influenza vaccine provided 87% protection (95% CI: 30%, 98%) as compared to those not vaccinated.

Conclusion

The 2010–2011 seasonal influenza vaccine had a moderate protective effect in preventing laboratory-confirmed influenza.

Introduction

The 2011−12 trivalent influenza vaccine contains a strain of influenza B/Victoria-lineage viruses. Despite free provision of influenza vaccine among target populations, an epidemic predominated by influenza B/Yamagata-lineage viruses occurred during the 2011−12 season in Taiwan. We characterized this vaccine-mismatched epidemic and estimated influenza vaccine effectiveness (VE).

Methods

Influenza activity was monitored through sentinel viral surveillance, emergency department (ED) and outpatient influenza-like illness (ILI) syndromic surveillance, and case-based surveillance of influenza with complications and deaths. VE against laboratory-confirmed influenza was evaluated through a case-control study on ILI patients enrolled into sentinel viral surveillance. Logistic regression was used to estimate VE adjusted for confounding factors.

Results

During July 2011−June 2012, influenza B accounted for 2,382 (72.5%) of 3,285 influenza-positive respiratory specimens. Of 329 influenza B viral isolates with antigen characterization, 287 (87.2%) were B/Yamagata-lineage viruses. Proportions of ED and outpatient visits being ILI-related increased from November 2011 to January 2012. Of 1,704 confirmed cases of influenza with complications, including 154 (9.0%) deaths, influenza B accounted for 1,034 (60.7%) of the confirmed cases and 103 (66.9%) of the deaths. Reporting rates of confirmed influenza with complications and deaths were 73.5 and 6.6 per 1,000,000, respectively, highest among those aged ≥65 years, 50−64 years, 3−6 years, and 0−2 years. Adjusted VE was −31% (95% CI: −80, 4) against all influenza, 54% (95% CI: 3, 78) against influenza A, and −66% (95% CI: −132, −18) against influenza B.

Conclusions

This influenza epidemic in Taiwan was predominated by B/Yamagata-lineage viruses unprotected by the 2011−12 trivalent vaccine. The morbidity and mortality of this vaccine-mismatched epidemic warrants careful consideration of introducing a quadrivalent influenza vaccine that includes strains of both B lineages.

The World Health Organization estimates that lower respiratory tract infections (excluding tuberculosis) account for ∼35% of all deaths caused by infectious diseases. In many cases, the cause of death may be caused by multiple pathogens, e.g., the life-threatening bacterial pneumonia observed in patients infected with influenza virus. The ability to evolve more efficient immunity on each successive encounter with antigen is the hallmark of the adaptive immune response. However, in the absence of cross-reactive T and B cell epitopes, one lung infection can modify immunity and pathology to the next for extended periods of time. We now report for the first time that this phenomenon is mediated by a sustained desensitization of lung sentinel cells to Toll-like receptor (TLR) ligands; this is an effect that lasts for several months after resolution of influenza or respiratory syncytial virus infection and is associated with reduced chemokine production and NF-κB activation in alveolar macrophages. Although such desensitization may be beneficial in alleviating overall immunopathology, the reduced neutrophil recruitment correlates with heightened bacterial load during secondary respiratory infection. Our data therefore suggests that post-viral desensitization to TLR signals may be one possible contributor to the common secondary bacterial pneumonia associated with pandemic and seasonal influenza infection.