BackgroundIn 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.MethodsUsing 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.ResultsWe 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.ConclusionsResults 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.

BackgroundA new era of flu surveillance has already started based on the genetic characterization and exploration of influenza virus evolution at whole-genome scale. Although this has been prioritized by national and international health authorities, the demanded technological transition to whole-genome sequencing (WGS)-based flu surveillance has been particularly delayed by the lack of bioinformatics infrastructures and/or expertise to deal with primary next-generation sequencing (NGS) data.ResultsWe developed and implemented INSaFLU (“INSide the FLU”), which is the first influenza-oriented bioinformatics free web-based suite that deals with primary NGS data (reads) towards the automatic generation of the output data that are actually the core first-line “genetic requests” for effective and timely influenza laboratory surveillance (e.g., type and sub-type, gene and whole-genome consensus sequences, variants’ annotation, alignments and phylogenetic trees). By handling NGS data collected from any amplicon-based schema, the implemented pipeline enables any laboratory to perform multi-step software intensive analyses in a user-friendly manner without previous advanced training in bioinformatics. INSaFLU gives access to user-restricted sample databases and projects management, being a transparent and flexible tool specifically designed to automatically update project outputs as more samples are uploaded. Data integration is thus cumulative and scalable, fitting the need for a continuous epidemiological surveillance during the flu epidemics. Multiple outputs are provided in nomenclature-stable and standardized formats that can be explored in situ or through multiple compatible downstream applications for fine-tuned data analysis. This platform additionally flags samples as “putative mixed infections” if the population admixture enrolls influenza viruses with clearly distinct genetic backgrounds, and enriches the traditional “consensus-based” influenza genetic characterization with relevant data on influenza sub-population diversification through a depth analysis of intra-patient minor variants. This dual approach is expected to strengthen our ability not only to detect the emergence of antigenic and drug resistance variants but also to decode alternative pathways of influenza evolution and to unveil intricate routes of transmission.ConclusionsIn summary, INSaFLU supplies public health laboratories and influenza researchers with an open “one size fits all” framework, potentiating the operationalization of a harmonized multi-country WGS-based surveillance for influenza virus.INSaFLU can be accessed through https://insaflu.insa.pt.Electronic supplementary materialThe online version of this article (10.1186/s13073-018-0555-0) contains supplementary material, which is available to authorized users.

Influenza A(H3N2), A(H1N1)pdm09 and B viruses co-circulated in Europe in 2014/15. We undertook a multicentre case-control study in eight European countries to measure 2014/15 influenza vaccine effectiveness (VE) against medically-attended influenza-like illness (ILI) laboratory-confirmed as influenza. General practitioners swabbed all or a systematic sample of ILI patients. We compared the odds of vaccination of ILI influenza positive patients to negative patients. We calculated adjusted VE by influenza type/subtype, and age group. Among 6,579 ILI patients included, 1,828 were A(H3N2), 539 A(H1N1)pdm09 and 1,038 B. VE against A(H3N2) was 14.4% (95% confidence interval (CI): -6.3 to 31.0) overall, 20.7% (95%CI: -22.3 to 48.5), 10.9% (95%CI -30.8 to 39.3) and 15.8% (95% CI: -20.2 to 41.0) among those aged 0-14, 15-59 and  ≥60  years, respectively. VE against A(H1N1)pdm09 was 54.2% (95%CI: 31.2 to 69.6) overall, 73.1% (95%CI: 39.6 to 88.1), 59.7% (95%CI: 10.9 to 81.8), and 22.4% (95%CI: -44.4 to 58.4) among those aged 0-14, 15-59 and  ≥60 years respectively. VE against B was 48.0% (95%CI: 28.9 to 61.9) overall, 62.1% (95%CI: 14.9 to 83.1), 41.4% (95%CI: 6.2 to 63.4) and 50.4% (95%CI: 14.6 to 71.2) among those aged 0-14, 15-59 and ≥60 years respectively. VE against A(H1N1)pdm09 and B was moderate. The low VE against A(H3N2) is consistent with the reported mismatch between circulating and vaccine strains.

BackgroundWell-established influenza surveillance systems (ISS) can be used for respiratory syncytial virus (RSV) surveillance. In Portugal, RSV cases are detected through the ISS using the European Union (EU) influenza-like illness (ILI) case definition.AimTo investigate clinical predictors for RSV infection and how three case definitions (EU ILI, a modified EU acute respiratory infection, and one respiratory symptom) performed in detecting RSV infections in Portugal.MethodsThis observational retrospective study used epidemiological and laboratory surveillance data (October 2010–May 2018). Associations between clinical characteristics and RSV detection were analysed using logistic regression. Accuracy of case definitions was assessed through sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). A 0.05 significance level was accepted.ResultsThe study involved 6,523 persons, including 190 (2.9%) RSV cases. Among 183 cases with age information, RSV infection was significantly more frequent among individuals < 5 years (n = 23; 12.6%) and ≥ 65 years (n = 45; 24.6%) compared with other age groups (p < 0.0001). Cough (odds ratio (OR): 2.4; 95% confidence interval (CI): 1.2–6.5) was the best RSV-infection predictor considering all age groups, while shortness of breath was particularly associated with RSV-positivity among ≤ 14 year olds (OR: 6.7; 95% CI: 2.6–17.4 for 0–4 year olds and OR: 6.7; 95% CI: 1.5–28.8 for 5–14 year olds). Systemic symptoms were significantly associated with RSV-negative and influenza-positive cases. None of the case definitions were suitable to detect RSV infections (AUC = 0.51).ConclusionTo avoid underestimating the RSV disease burden, RSV surveillance within the Portuguese sentinel ISS would require a more sensitive case definition than ILI and, even a different case definition according to age.

A B S T R A C TIntroduction: Respiratory syncytial virus (RSV) is associated with substantial morbidity and mortality since it is a predominant viral agent causing respiratory tract infections in infants, young children and the elderly. Considering the availability of the RSV vaccines in the coming years, molecular understanding in RSV is necessary. Objective: The objective of the present study was to describe RSV epidemiology and genotype variability in Portugal during the 2014/15-2017/18 period. Material and methods: Epidemiological data and RSV-positive samples from patients with a respiratory infection were collected through the non-sentinel and sentinel influenza surveillance system (ISS). RSV detection, subtyping in A and B, and sequencing of the second hypervariable region (HVR2) of G gene were performed by molecular methods. Phylogenetic trees were generated using the Neighbor-Joining method and p-distance model on MEGA 7.0. Results: RSV prevalence varied between the sentinel (2.5%, 97/3891) and the non-sentinel ISS (20.7%, 3138/ 16779), being higher (P < 0.0001) among children aged < 5 years. Bronchiolitis (62.9%, 183/291) and influenza-like illness (24.6%, 14/57) were associated (P < 0.0001) with RSV laboratory confirmation among children aged < 6 months and adults ≥65 years, respectively. The HVR2 was sequenced for 562 samples. RSV-A (46.4%, 261/562) and RSV-B (53.6%, 301/562) strains clustered mainly to ON1 (89.2%, 233/261) and BA9