The influenza landscape and vaccination coverage in older adults during the SARS-Cov-2 pandemic: data from Several European Countries and Israel.

INTRODUCTION: The Raise Awareness of Influenza Strategies in Europe (RAISE) group gathered information about the healthcare burden of influenza (hospitalizations, intensive care unit [ICU] admissions, and excess deaths), surveillance systems, and the vaccine coverage rate (VCR) in older adults in 18 European countries and Israel. AREAS COVERED: Published medical literature and official medical documentation on the influenza disease burden in the participating countries were reviewed from 2010/11 until the 2022/23 influenza seasons. Information on the framework for monitoring the disease burden and the provision for ensuring older adults had access to vaccination in their respective countries was provided. Data on influenza VCR in older adults were collected for the 2019/20 to 2022/23 influenza seasons. Data are reported descriptively. EXPERT OPINION: Influenza presents a significant healthcare burden in older adults. Reporting outcomes across participating countries is heterogeneous, highlighting the need for standardized approaches. Although older adults receive free influenza vaccination, vaccine uptake is highly variable among countries. Moreover, hospitalization rates remain high even in countries reporting a high VCR. Increased awareness and education on the burden of disease and the broader use of improved influenza vaccines for older adults may help reduce the disease burden on this population.

Prospective screening for significant liver fibrosis by fibrosis-4 in primary care patients without known liver disease.

BACKGROUND: Fibrosis-4 test (FIB-4) is one of the simplest, free of charge, noninvasive scoring tests. We aimed to prospectively measure the prevalence of liver fibrosis in adults with no previously known liver disease and who consulted a general practitioner by FIB-4 score; compare this test to an NAFLD Fibrosis Score (NFS) and Fibrometer (FM); explore the prevalence of risk factors (obesity, diabetes, alcohol, and hypertension) and reconsider a possible cause of liver disease in patients recognized as FIB-4-positive. METHODS: Over a 6-month period, 40 general practitioners (GPs) offered all their consecutive adult primary care patients with no previously known liver pathology and a liver fibrosis screening via a blood test of three scores. RESULTS: Among the consecutive 2121 patients included in the study, 39% had a BMI greater than 25 kg/m2, 13% had an alcohol consumption greater than 100 g/week, 10% had type 2 diabetes, and 29% had hypertension. The prevalence of significant liver fibrosis by FIB-4, according to age was 19.1% (95% confidence interval: 17.5-20.9%). By comparison, prevalence was 16.8% (15.0-18.5%) by the NFS and 8.2% (6.9-9.6%) by the FM. A significant relationship was observed between FIB-4 fibrosis risk stages and NFS and FM scores. GPs identified the cause of disease in 2/3 of FIB-4-positive cases, mainly nonalcoholic steatohepatitis. CONCLUSION: Liver fibrosis was suspected by FIB-4 score in 19.1% of patients with no previously known liver disease. The detection of significant fibrosis by the FIB-4 allowed the GP to suspect liver disease. The FIB-4 score that can be automatically generated should allow earlier recognition of liver disease in the general population.

Salivary and Nasal Detection of the SARS-CoV-2 Virus After Antiviral Mouthrinses (BBCovid): A structured summary of a study protocol for a randomised controlled trial.

OBJECTIVES: - To describe the evolution of the SARS-CoV-2 salivary viral load of patients infected with Covid-19, performing 7 days of tri-daily mouthwashes with and without antivirals. - To compare the evolution of the SARS-CoV-2 nasal and salivary viral load according to the presence or absence of antivirals in the mouthwash. TRIAL DESIGN: This is a multi-center, randomised controlled trial (RCT) with two parallel arms (1:1 ratio). PARTICIPANTS: Inclusion criteria - Age: 18-85 years old - Clinical diagnosis of Covid-19 infection - Clinical signs have been present for less than 8 days - Virological confirmation - Understanding and acceptance of the trial - Written agreement to participate in the trial Exclusion criteria - Pregnancy, breastfeeding, inability to comply with protocol, lack of written agreement - Patients using mouthwash on a regular basis (more than once a week) - Patient at risk of infectious endocarditis - Patients unable to answer questions - Uncooperative patient The clinical trial is being conducted with the collaboration of three French hospital centers: Hospital Center Emile Roux (Le Puy en Velay, France), Clinic of the Protestant Infirmary (Lyon, France) and Intercommunal Hospital Center (Mont de Marsan, France). INTERVENTION AND COMPARATOR: Eligible participants will be allocated to one of the two study groups. Intervention group: patients perform a tri-daily mouthwash with mouthwash containing antivirals (ß-cyclodextrin and Citrox®) for a period of 7 days. CONTROL GROUP: patients perform a tri-daily mouthwash with a placebo mouthwash for a period of 7 days. MAIN OUTCOMES: Primary Outcome Measures: Change from Baseline amount of SARS-CoV-2 in salivary samples at 4 and 9 hours, 1, 2, 3, 4, 5 and 6 days. Real-time PCR assays are performed to assess salivary SARS-CoV 2 viral load. SECONDARY OUTCOME MEASURES: Change from Baseline amount of SARS-CoV-2 virus in nasal samples at 6 days. Real-time PCR assays are performed to assess nasal SARS-CoV-2 viral load. RANDOMISATION: Participants meeting all eligibility requirements are allocated to one of the two study arms (mouthwash with ß-cyclodextrin and Citrox® or mouthwash without ß-cyclodextrin and Citrox®) in a 1:1 ratio using simple randomisation with computer generated random numbers. BLINDING (MASKING): Participants, doctors and nurses caring for participants, laboratory technicians and investigators assessing the outcomes will be blinded to group assignment. NUMBERS TO BE RANDOMISED (SAMPLE SIZE): Both the intervention and control groups will be composed of 103 participants, so the study will include a total of 206 participants. TRIAL STATUS: The current protocol version is 6, August 4th, 2020. Recruitment began on April 6, 2020 and is anticipated to be complete by April 5, 2021. As of October 2, 2020, forty-two participants have been included. TRIAL REGISTRATION: This trial was registered on 20 April 2020 at www.clinicaltrials.gov with the number NCT04352959 . FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol." The study protocol has been reported in accordance with the Standard Protocol Items: Recommendations for Clinical Interventional Trials (SPIRIT) guidelines (Additional file 2)."

Failure to Reach a Consensus in Polypharmacy Definition: An Obstacle to Measuring Risks and Impacts-Results of a Literature Review.

INTRODUCTION: The risk of polypharmacy is on the rise in most industrialized countries, threatening to burden their health systems. Although many definitions exist and numerous concepts are found in literature as synonyms, the phenomenon of polypharmacy remains poorly defined. The aim of this literature review is to provide an overview of available definitions of polypharmacy, to analyse their convergences and divergences and to discuss the consequences on the assessment of the problem. METHODS: A literature review was conducted to identify all published systematic reviews on definitions of polypharmacy available via Scopus and Pubmed databases. The Assessment of Multiple Systematic Reviews (AMSTAR) tool was used to appraise the methodological quality of the selected reviews. Available definitions and other characteristics were extracted; summarised in a table and analysed. RESULTS: Six systematic reviews were identified. They were published between 2000 and 2018. Three focussed on definitions of polypharmacy in the elderly; two in the general population and one in children. The strategy adopted in reviews is more rigorous in the most recent ones. However, they remain, at best, partially exhaustive. The definitions found in the literature used two main approaches, either (i) quantitative, applying varying thresholds and types of polypharmacy based on the number of medications being taken by the patient (ii) qualitative, based on the clinical indications and effects of a given drug regimen, with a growing number of characteristics to describe polypharmacy. The term "inappropriate" is increasingly associated with polypharmacy especially in studies that aimed to use this definition to identify possible solutions for healthcare providers in the field related to aging. CONCLUSION: This review confirms a high variability and an evolution in the approaches defining "polypharmacy" in the absence of a consensus following standardized criteria. That makes it very difficult to estimate and measure the outcomes associated with this phenomenon.

Linking influenza epidemic onsets to covariates at different scales using a dynamical model.

BACKGROUND: Evaluating the factors favoring the onset of influenza epidemics is a critical public health issue for surveillance, prevention and control. While past outbreaks provide important insights for understanding epidemic onsets, their statistical analysis is challenging since the impact of a factor can be viewed at different scales. Indeed, the same factor can explain why epidemics are more likely to begin (i) during particular weeks of the year (global scale); (ii) earlier in particular regions (spatial scale) or years (annual scale) than others and (iii) earlier in some years than others within a region (spatiotemporal scale). METHODS: Here, we present a statistical approach based on dynamical modeling of infectious diseases to study epidemic onsets. We propose a method to disentangle the role of covariates at different scales and use a permutation procedure to assess their significance. Epidemic data gathered from 18 French regions over six epidemic years were provided by the Regional Influenza Surveillance Group (GROG) sentinel network. RESULTS: Our results failed to highlight a significant impact of mobility flows on epidemic onset dates. Absolute humidity had a significant impact, but only at the spatial scale. No link between demographic covariates and influenza epidemic onset dates could be established. DISCUSSION: Dynamical modeling presents an interesting basis to analyze spatiotemporal variations in the outcome of epidemic onsets and how they are related to various types of covariates. The use of these models is quite complex however, due to their mathematical complexity. Furthermore, because they attempt to integrate migration processes of the virus, such models have to be much more explicit than pure statistical approaches. We discuss the relation of this approach to survival analysis, which present significant differences but may constitute an interesting alternative for non-methodologists.

Performance of influenza case definitions for influenza community surveillance: based on the French influenza surveillance network GROG, 2009-2014.

International case definitions recommended by the Centers for Disease Control and Prevention (CDC), the European Centre for Disease Prevention and Control (ECDC), and the World Health Organization (WHO) are commonly used for influenza surveillance. We evaluated clinical factors associated with the laboratory-confirmed diagnosis of influenza and the performance of these influenza case definitions by using a complete dataset of 14,994 patients with acute respiratory infection (ARI) from whom a specimen was collected between August 2009 and April 2014 by the Groupes Régionaux d'Observation de la Grippe (GROG), a French national influenza surveillance network. Cough and fever ≥ 39 °C most accurately predicted an influenza infection in all age groups. Several other symptoms were associated with an increased risk of influenza (headache, weakness, myalgia, coryza) or decreased risk (adenopathy, pharyngitis, shortness of breath, otitis/otalgia, bronchitis/ bronchiolitis), but not throughout all age groups. The WHO case definition for influenza-like illness (ILI) had the highest specificity with 21.4%, while the ECDC ILI case definition had the highest sensitivity with 96.1%. The diagnosis among children younger than 5 years remains challenging. The study compared the performance of clinical influenza definitions based on outpatient surveillance and will contribute to improving the comparability of data shared at international level.

Does seasonal vaccination affect the clinical presentation of influenza among the elderly? A cross-sectional analysis in the outpatient setting in France, 2003-2014.

Vaccine-induced protection against influenza is not optimal, however it has been suggested that the vaccine may reduce the severity of symptoms among those who develop illness despite being vaccinated. We tested this hypothesis within a countrywide, sentinel general practitioners-based surveillance system in France. We included 2277 individuals aged 65years or older (of whom 1293 had been vaccinated against influenza, 56.8%) who consulted a general practitioner because of an acute respiratory infection (ARI) during 2003-2014. All patients were taken a nasopharyngeal swab, and information was collected on demographic characteristics and symptoms at disease onset. All specimens were tested for respiratory viruses and, if positive for influenza, the virus type and subtype were determined. We compared the average maximum temperature and the frequency of each symptom, between non-vaccinated and vaccinated influenza patients. We then used logistic regression models to calculate the odds of presenting with each symptom between vaccinated vs. non-vaccinated patients, adjusting by age group, virus (sub)type and season. Overall, 675 ARI patients (29.6%) tested positive for influenza. The A(H3) virus caused the majority of cases (55.1%), followed by influenza B (22.9%), A not-subtyped (11.7%), and A(H1) (10.3%) viruses. Compared to non-vaccinated influenza patients, those who had been vaccinated had a slightly reduced maximum temperature and presented less frequently with myalgia, shivering and headache. In stratified analyses, the observed effect was limited to patients infected with A(H3) or type B viruses. After adjusting by age group, virus (sub)type and season, the difference remained statistically significant only for headache, which was less frequent among vaccinated individuals (odds ratio 0.69, 95% confidence intervals 0.48-0.98). In conclusion, the vaccine was found to be modestly associated with less severe clinical presentation of influenza among the elderly. Our findings reinforce the need for influenza vaccines providing better protection.

Development of Seasonal Influenza Vaccination Recommendations: Relevance and Influence of the Evidence on the Decision-Making Process in France and the Netherlands.

BACKGROUND: Target groups for seasonal influenza vaccination are defined at the country level and are based on several factors. However, little is known about the national decision-making procedures. OBJECTIVE: The purpose of this study was to compare the evidence used for the development of recommendations and its impact on the choice of target groups in France and the Netherlands. METHODS: A preliminary documentary analysis identified institutions to include in the assessment: governmental authorities, research institutions, associations, and manufacturers. At least one expert from each group was invited to our study. Thirty-three semi-structured interviews were conducted in 2013 (16 France, 17 the Netherlands). We used NVivo10® to perform a thematic content analysis. RESULTS: Clinical/epidemiological studies were the evidence most used in both countries. Economic models were increasingly being used; these had greater influence on the decision making in the Netherlands than in France, probably because of the presence of a modeler. Generally, the quality of the evidence used was poor, although no systematic use of standard protocol for its assessment was observed. A general protocol was sometimes used in France; however, the personal judgment of the experts was crucial for the assessment in both countries. CONCLUSIONS: There were differences in the target groups, for example, pregnant women, recommended only in France. France and the Netherlands use similar evidence for developing vaccination recommendations, although different decisions are sometimes made regarding target groups. This could be associated with the lack of systematic standard appraisals, increasing the influence of the experts' judgment on decision making. The development of standards for the appraisal of evidence is recommended.

Quantifying the role of weather on seasonal influenza.

BACKGROUND: Improving knowledge about influenza transmission is crucial to upgrade surveillance network and to develop accurate predicting models to enhance public health intervention strategies. Epidemics usually occur in winter in temperate countries and during the rainy season for tropical countries, suggesting a climate impact on influenza spread. Despite a lot of studies, the role of weather on influenza spread is not yet fully understood. In the present study, we investigated this issue at two different levels. METHODS: First, we evaluated how weekly (intra-annual) incidence variations of clinical diseases could be linked to those of climatic factors. We considered that only a fraction of the human population is susceptible at the beginning of a year due to immunity acquired from previous years. Second, we focused on epidemic sizes (cumulated number of clinical reported cases) and looked at how their inter-annual and regional variations could be related to differences in the winter climatic conditions of the epidemic years over the regions. We quantified the impact of fifteen climatic variables in France using the Réseau des GROG surveillance network incidence data over eleven regions and nine years. RESULTS: At the epidemic scale, no impact of climatic factors was highlighted. At the intra-annual scale, six climatic variables had a significant impact: average temperature (5.54 ± 1.09 %), absolute humidity (5.94 ± 1.08 %), daily variation of absolute humidity (3.02 ± 1.17 %), sunshine duration (3.46 ± 1.06 %), relative humidity (4.92 ± 1.20 %) and daily variation of relative humidity (4.46 ± 1.24 %). Since in practice the impact of two highly correlated variables is very hard to disentangle, we performed a principal component analysis that revealed two groups of three highly correlated climatic variables: one including the first three highlighted climatic variables on the one hand, the other including the last three ones on the other hand. CONCLUSIONS: These results suggest that, among the six factors that appeared to be significant, only two (one per group) could in fact have a real effect on influenza spread, although it is not possible to determine which one based on a purely statistical argument. Our results support the idea of an important role of climate on the spread of influenza.

I-MOVE multicentre case-control study 2010/11 to 2014/15: Is there within-season waning of influenza type/subtype vaccine effectiveness with increasing time since vaccination?

Since the 2008/9 influenza season, the I-MOVE multicentre case-control study measures influenza vaccine effectiveness (VE) against medically-attended influenza-like-illness (ILI) laboratory confirmed as influenza. In 2011/12, European studies reported a decline in VE against influenza A(H3N2) within the season. Using combined I-MOVE data from 2010/11 to 2014/15 we studied the effects of time since vaccination on influenza type/subtype-specific VE. We modelled influenza type/subtype-specific VE by time since vaccination using a restricted cubic spline, controlling for potential confounders (age, sex, time of onset, chronic conditions). Over 10,000 ILI cases were included in each analysis of influenza A(H3N2), A(H1N1)pdm09 and B; with 4,759, 3,152 and 3,617 influenza positive cases respectively. VE against influenza A(H3N2) reached 50.6% (95% CI: 30.0-65.1) 38 days after vaccination, declined to 0% (95% CI: -18.1-15.2) from 111 days onwards. At day 54 VE against influenza A(H1N1)pdm09 reached 55.3% (95% CI: 37.9-67.9) and remained between this value and 50.3% (95% CI: 34.8-62.1) until season end. VE against influenza B declined from 70.7% (95% CI: 51.3-82.4) 44 days after vaccination to 21.4% (95% CI: -57.4-60.8) at season end. To assess if vaccination campaign strategies need revising more evidence on VE by time since vaccination is urgently needed.

Influenza vaccination policy-making processes in France and The Netherlands: Framework and determinants.

OBJECTIVES: Target groups for seasonal influenza vaccination are nationally defined based on several factors. However, few studies have explored the policy-making processes at the country-level. We investigated key differences in the policy-making process for the development of vaccination recommendations between France (FR) and The Netherlands (NL). This paper presents preliminary results on the evidence used in the decision-making process and focuses on the interactions between the experts and stakeholders. METHODS: A documentary analysis identified the stakeholders of this process as governmental authorities, research institutions, associations, and manufacturers. This qualitative study included at least one expert from each stakeholder group. Thirty-three semi-structured interviews were performed in 2013 (16 FR, 17 NL). We used NVivo10® to perform a thematic content analysis on the data. RESULTS: National Immunization Technical Advisory Groups (NITAGs) were the key stakeholders in the development of recommendations. There was no systematic standard evaluation of evidence during the decision-making process in both countries. Likewise, voting was not systematic, although it did occur more often in FR. A declaration of interests was obligatory in both countries. Experts with no conflicts of interest were rare because many depend on private funding for their research on influenza vaccination. CONCLUSIONS: The transparency of the NITAGs' procedures for the development of recommendations should be improved. We believe improvements might be achieved by the systematic standard evaluation of evidence, consistent voting, clear declarations of interest, and increased public funding for vaccination research.

Striking Similarities in the Presentation and Duration of Illness of Influenza A and B in the Community: A Study Based on Sentinel Surveillance Networks in France and Turkey, 2010-2012.

Influenza B represents a high proportion of influenza cases in some seasons (even over 50%). The Influenza B study in General Practice (IBGP) is a multicenter study providing information about the clinical, demographic and socio-economic characteristics of patients affected by lab-confirmed influenza A or B. Influenza B patients and age-matched influenza A patients were recruited within the sentinel surveillance networks of France and Turkey in 2010-11 and 2011-12 seasons. Data were collected for each patient at the swab test day, after 9±2 days and, if not recovered, after 28±5 days. It was related to patient's characteristics, symptoms at presentation, vaccination status, prescriptions of antibiotics and antivirals, duration of illness, follow-up consultations in general practice or emergency room. We performed descriptive analyses and developed a multiple regression model to investigate the effect of patients and disease characteristics on the duration of illness. Overall, 774 influenza cases were included in the study: 419 influenza B cases (209 in France and 210 in Turkey) and 355 influenza A cases (205 in France and 150 in Turkey). There were no differences between influenza A and B patients in terms of clinical presentation and number of consultations with a practitioner; however, the use of antivirals was higher among influenza B patients in both countries. The average (median) reported duration of illness in the age groups 0-14 years, 15-64 years and 65+ years was 7.4 (6), 8.7 (8) and 10.5 (9) days in France, and 6.3 (6), 8.2 (7) and 9.2 (6) days in Turkey; it increased with age but did not differ by virus type; increased duration of illness was associated with antibiotics prescription. In conclusion, our findings show that influenza B infection appears not to be milder disease than influenza A infection.

Clinical Characteristics Are Similar across Type A and B Influenza Virus Infections.

BACKGROUND: Studies that aimed at comparing the clinical presentation of influenza patients across virus types and subtypes/lineages found divergent results, but this was never investigated using data collected over several years in a countrywide, primary care practitioners-based influenza surveillance system. METHODS: The IBVD (Influenza B in Vircases Database) study collected information on signs and symptoms at disease onset from laboratory-confirmed influenza patients of any age who consulted a sentinel practitioner in France. We compared the clinical presentation of influenza patients across age groups (0-4, 5-14, 15-64 and 65+ years), virus types (A, B) and subtypes/lineages (A(H3N2), pandemic A(H1N1), B Victoria, B Yamagata). RESULTS: Overall, 14,423 influenza cases (23.9% of which were influenza B) were included between 2003-2004 and 2012-2013. Influenza A and B accounted for over 50% of total influenza cases during eight and two seasons, respectively. There were minor differences in the distribution of signs and symptoms across influenza virus types and subtypes/lineages. Compared to patients aged 0-4 years, those aged 5-14 years were more likely to have been infected with type B viruses (OR 2.15, 95% CI 1.87-2.47) while those aged 15-64 years were less likely (OR 0.83, 95% CI 0.73-0.96). Males and influenza patients diagnosed during the epidemic period were less likely to be infected with type B viruses. CONCLUSIONS: Despite differences in age distribution, the clinical illness produced by the different influenza virus types and subtypes is indistinguishable among patients that consult a general practitioner for acute respiratory infections.

Ten influenza seasons in France: distribution and timing of influenza A and B circulation, 2003-2013.

BACKGROUND: Describing the circulation of influenza viruses and the characteristics of seasonal epidemics remains an essential tool to optimize the strategies of influenza prevention and control. Special attention has been recently paid to influenza B in the context of the availability of a quadrivalent vaccine, containing two influenza B strains. METHODS: We used data from a practitioners-based influenza surveillance network to describe the circulation of influenza viruses in France from 2003-2004 to 2012-2013. Nasopharyngeal swabs taken from acute respiratory infection (ARI) patients between October and April were tested for influenza. We reported the number of influenza cases by virus type (A, B), subtype (A(H1), A(H3)) and B lineage (Yamagata, Victoria) in each season and determined the frequency of influenza B vaccine mismatch. We estimated weekly incidence of influenza by extrapolating reported influenza cases to the French population. We compared the temporal characteristics of the epidemics caused by influenza A(H1), A(H3) and B. RESULTS: Overall, 49,919 ARI patients were tested, of which 16,287 (32.6 %) were positive for influenza. Type B virus caused 23.7 % of all influenza cases. Virus subtypes A(H1) and A(H3) caused 51.6 % and 48.4 % of influenza A cases, respectively. Viruses of the B-Yamagata and B-Victoria lineage caused 62.8 % and 37.2 % of influenza B cases, respectively. There was an influenza B vaccine mismatch in three of the five seasons where influenza B caused 10 % or more of all influenza cases. Influenza A(H3) had the highest average value of estimated weekly incidence during the study period. Influenza B peaked an average 3.8 weeks later than influenza A when both virus types were circulating. No differences in the duration of influenza A and B epidemics were observed. CONCLUSIONS: Influenza A(H3) was the most prevalent influenza type during the study period. Influenza B caused around one fourth of all influenza cases and tended to circulate later than influenza A. The frequency of influenza B vaccine mismatches was substantial. Timely data on the circulation of influenza viruses collected within influenza surveillance systems are essential to optimize influenza prevention and control strategies.

A literature review to identify factors that determine policies for influenza vaccination.

OBJECTIVES: To conduct a literature review of influenza vaccination policy, describing roles and interactions between stakeholders and the factors influencing policy-making. METHODS: Major databases were searched using keywords related to influenza vaccination, decision-making and health policy. Titles and abstracts were screened according to defined criteria using independent reviewers. Selected articles were analysed and compared against a checklist. RESULTS: 342 papers were identified, but only 111 included. A wide range of countries was represented in articles published in 1994-2012. We identified numerous stakeholders at the national and international level and found a variety of interactions between them. Using these data, we suggest a scheme for the most important stakeholders and their interactions. Determinants of policy-making were mainly related to the vaccine/disease, political-economic context, and stakeholders communication. The most relevant evidence was clinical/epidemiological studies. After the 2009 pandemic: the importance of mathematical modelling and ethical issues was greater; and the need for better communication between stakeholders was emphasised. CONCLUSIONS: The relevance of evidence and factors influencing policy-making varied between countries, according to complex interactions between the stakeholders involved at different levels of decision-making process. These interactions remain unclear, especially at national level, where the most important influenza policy decisions are made. To better define and understand the exact interactions and use of evidence, we recommend undertaking future qualitative studies at national level using small number of countries.

Economic burden of seasonal influenza B in France during winter 2010-2011.

BACKGROUND: In France, 2-15% of the population is affected annually by influenza, which causes significant socioeconomic disruption. Nevertheless, despite its importance for policy makers, few published studies have evaluated the impact of influenza B. Therefore, we assessed the costs associated with influenza B during 2010-2011 in France. METHODS: Cases of lab-confirmed influenza B were analyzed as part of the Influenza B in General Practice Study. Cost calculations were based on micro-costing methods according to the French Health Insurance (FHI) perspective (in Euros, 2011). Costs were compared between age groups using the Kruskal-Wallis test, and when significant, by multiple comparisons based on rank. Moreover, uncertainties were assessed using one-way sensitivity and probabilistic analyses. Overall economic burden was estimated by multiplying cost per patient, flu attack rate, and the French population. RESULTS: A total of 201 patients were included in the study. We found that the mean cost associated with Influenza B was 72€ (SD: 205) per patient: 70€ (SD: 262) for younger children, 50€ (SD: 195) for older children, 126€ (SD: 180) for adults, and 42€ (SD: 18) for elderly. Thus, we observed significantly different costs between the distinct age groups (p<0.0001). Finally, the economic burden of influenza B for the FHI was estimated to be 145 million Euros (95% CI: 88-201). CONCLUSIONS: Our findings highlight the important impact of influenza B and encourage further investigation on policy regarding vaccination strategies in France.

I-MOVE multi-centre case control study 2010-11: overall and stratified estimates of influenza vaccine effectiveness in Europe.

BACKGROUND: In the third season of I-MOVE (Influenza Monitoring Vaccine Effectiveness in Europe), we undertook a multicentre case-control study based on sentinel practitioner surveillance networks in eight European Union (EU) member states to estimate 2010/11 influenza vaccine effectiveness (VE) against medically-attended influenza-like illness (ILI) laboratory-confirmed as influenza. METHODS: Using systematic sampling, practitioners swabbed ILI/ARI patients within seven days of symptom onset. We compared influenza-positive to influenza laboratory-negative patients among those meeting the EU ILI case definition. A valid vaccination corresponded to > 14 days between receiving a dose of vaccine and symptom onset. We used multiple imputation with chained equations to estimate missing values. Using logistic regression with study as fixed effect we calculated influenza VE adjusting for potential confounders. We estimated influenza VE overall, by influenza type, age group and among the target group for vaccination. RESULTS: We included 2019 cases and 2391 controls in the analysis. Adjusted VE was 52% (95% CI 30-67) overall (N = 4410), 55% (95% CI 29-72) against A(H1N1) and 50% (95% CI 14-71) against influenza B. Adjusted VE against all influenza subtypes was 66% (95% CI 15-86), 41% (95% CI -3-66) and 60% (95% CI 17-81) among those aged 0-14, 15-59 and ≥60 respectively. Among target groups for vaccination (N = 1004), VE was 56% (95% CI 34-71) overall, 59% (95% CI 32-75) against A(H1N1) and 63% (95% CI 31-81) against influenza B. CONCLUSIONS: Results suggest moderate protection from 2010-11 trivalent influenza vaccines against medically-attended ILI laboratory-confirmed as influenza across Europe. Adjusted and stratified influenza VE estimates are possible with the large sample size of this multi-centre case-control. I-MOVE shows how a network can provide precise summary VE measures across Europe.

Field effectiveness of pandemic and 2009-2010 seasonal vaccines against 2009-2010 A(H1N1) influenza: estimations from surveillance data in France.

BACKGROUND: In this study, we assess how effective pandemic and trivalent 2009-2010 seasonal vaccines were in preventing influenza-like illness (ILI) during the 2009 A(H1N1) pandemic in France. We also compare vaccine effectiveness against ILI versus laboratory-confirmed pandemic A(H1N1) influenza, and assess the possible bias caused by using non-specific endpoints and observational data. METHODOLOGY AND PRINCIPAL FINDINGS: We estimated vaccine effectiveness by using the following formula: VE  =  (PPV-PCV)/(PPV(1-PCV)) × 100%, where PPV is the proportion vaccinated in the population and PCV the proportion of vaccinated influenza cases. People were considered vaccinated three weeks after receiving a dose of vaccine. ILI and pandemic A(H1N1) laboratory-confirmed cases were obtained from two surveillance networks of general practitioners. During the epidemic, 99.7% of influenza isolates were pandemic A(H1N1). Pandemic and seasonal vaccine uptakes in the population were obtained from the National Health Insurance database and by telephonic surveys, respectively. Effectiveness estimates were adjusted by age and week. The presence of residual biases was explored by calculating vaccine effectiveness after the influenza period. The effectiveness of pandemic vaccines in preventing ILI was 52% (95% confidence interval: 30-69) during the pandemic and 33% (4-55) after. It was 86% (56-98) against confirmed influenza. The effectiveness of seasonal vaccines against ILI was 61% (56-66) during the pandemic and 19% (-10-41) after. It was 60% (41-74) against confirmed influenza. CONCLUSIONS: The effectiveness of pandemic vaccines in preventing confirmed pandemic A(H1N1) influenza on the field was high, consistently with published findings. It was significantly lower against ILI. This is unsurprising since not all ILI cases are caused by influenza. Trivalent 2009-2010 seasonal vaccines had a statistically significant effectiveness in preventing ILI and confirmed pandemic influenza, but were not better in preventing confirmed pandemic influenza than in preventing ILI. This lack of difference might be indicative of selection bias.

Estimates of pandemic influenza vaccine effectiveness in Europe, 2009-2010: results of Influenza Monitoring Vaccine Effectiveness in Europe (I-MOVE) multicentre case-control study.

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.

Health problems in returning travelers consulting general practitioners.

Over a 2-month period, 43 of 143 participating general practitioners included 97 patients with 113 health impairments, mainly gastrointestinal problems (35%), respiratory tract infections (30%), and skin diseases (11%). Systemic febrile illness or imported tropical disease accounted for less than 4% of cases.