Studies Of Influenza Vaccine Effectiveness Research Articles

Epidemiology of RSV in Adults and Children with Medically-Attended Acute Respiratory Illness over Three Seasons.

Data on the true prevalence of RSV among medically-attended acute respiratory illnesses (MAARI) has been limited by the lack of regular clinical testing of mild to moderate illnesses. Here we present a prospective evaluation of the epidemiology of RSV-associated MAARI across age groups and multimorbidity status over three seasons, which is informative in light of the recommendations for shared decision-making for vaccination in older adults. Ambulatory patients ≥6 months of age meeting a common MAARI case definition were prospectively enrolled in the Michigan Ford Influenza Vaccine Effectiveness (MFIVE) study, a subsite of the US Influenza Vaccine Effectiveness Network. All participants were tested by nasal-throat swab for RSV and influenza, including subtype, independently from clinician-directed testing. Participant illness characteristics and calculated Multimorbidity-Weighted Index (MWI) were collected by in-person survey and electronic medical record review. Over three surveillance seasons (fall 2017 to spring 2020), 9.9% (n=441) of 4,442 participants had RSV detected. RSV-associated MAARI was more prevalent than influenza for participants 6 months-4 years of age. Adults with RSV-MAARI had higher median MWI scores overall compared to influenza-MAARI and controls with neither virus (1.62, 0.40, and 0.64, respectively). RSV is a significant, underrecognized cause of MAARI in both children and adults presenting for ambulatory care. Multimorbidity is an important contributor to RSV-associated MAARI in outpatient adults, providing information to support shared clinical decision-making for vaccination.

Exploring the effect of clinical case definitions on influenza vaccine effectiveness estimation at primary care level: Results from the end-of-season 2022–23 VEBIS multicentre study in Europe

BackgroundWithin influenza vaccine effectiveness (VE) studies at primary care level with a laboratory-confirmed outcome, clinical case definitions for recruitment of patients can vary. We used the 2022–23 VEBIS primary care European multicentre study end-of-season data to evaluate whether the clinical case definition affected IVE estimates. MethodsWe estimated VE using a multicentre test-negative case-control design. We measured VE against any influenza and influenza (sub)types, by age group (0–14, 15–64, ≥65 years) and by influenza vaccine target group, using logistic regression. We estimated IVE among patients meeting the European Union (EU) acute respiratory infection (ARI) case definition and among those meeting the EU influenza-like illness (ILI) case definition, including only sites providing information on specific symptoms and recruiting patients using an ARI case definition (as the EU ILI case definition is a subset of the EU ARI one). ResultsWe included 24 319 patients meeting the EU ARI case definition, of whom 21 804 patients (90 %) meet the EU ILI case definition, for the overall pooled VE analysis against any influenza. The overall and influenza (sub)type-specific VE varied by ≤2 % between EU ILI and EU ARI populations. DiscussionAmong all analyses, we found similar VE estimates between the EU ILI and EU ARI populations, with few (10%) additional non-ILI ARI patients recruited. These results indicate that VE in the 2022–23 influenza season was not affected by use of a different clinical case definition for recruitment, although we recommend investigating whether this holds true for next seasons.

Evaluating risk of bias using ROBINS-I tool in nonrandomized studies of adjuvanted influenza vaccine

Seasonal variation in influenza vaccine effectiveness (VE) makes real-world evidence (RWE) useful in supplementing the clinical-evidence base from randomized clinical trials. Adjuvanted inactivated influenza vaccine (aIIV) VE has been evaluated in multiple nonrandomized RWE studies. A systematic literature review of RWE studies evaluating the absolute or relative VE of aIIV was conducted. Identified studies were assessed by evaluators for risk of bias (RoB) by means of the ROBINS-I (Reduction of Bias In Non-randomized Studies of Interventions) tool to inform evidence-based medicine deliberations. Differences in evaluator assessments were resolved by consensus. The literature review yielded 14 follow-up studies, seven test-negative case-control (TNCC) studies, five traditional case-control studies, and one cluster-randomized clinical trial. Most follow-up studies and three TNCC studies were judged at low RoB. Issues increasing RoB included inadequate control of confounding, selection of controls, and reliance on recall of vaccination. The concerns identified in any of the designs could be mitigated with straightforward revisions to design or implementation. 17 of 27 nonrandomized studies of adjuvanted influenza-vaccine effectiveness, some from each of four study designs, were judged at low risk of material bias. These studies merit credence in assessing aIIV effectiveness relative to other influenza vaccines.

Influenza Vaccine Effectiveness and Test-Negative Study Design Within the Department of Defense.

Test-negative observational studies are routinely used to assess vaccine effectiveness. This test method consistently shows lower annual vaccine effectiveness in the highly vaccinated U.S. military compared to the general population. Incorporating other test designs and broader impact measures may better estimate influenza vaccine benefits in highly vaccinated groups.

Investigating confounding in network-based test-negative design influenza vaccine effectiveness studies-Experience from the DRIVE project.

Establishing a large study network to conduct influenza vaccine effectiveness (IVE) studies while collecting appropriate variables to account for potential bias is important; the most relevant variables should be prioritized. We explored the impact of potential confounders on IVE in the DRIVE multi-country network of sites conducting test-negative design (TND) studies. We constructed a directed acyclic graph (DAG) to map the relationship between influenza vaccination, medically attended influenza infection, confounders, and other variables. Additionally, we used the Development of Robust and Innovative Vaccines Effectiveness (DRIVE) data from the 2018/2019 and 2019/2020 seasons to explore the effect of covariate adjustment on IVE estimates. The reference model was adjusted for age, sex, calendar time, and season. The covariates studied were presence of at least one, two, or three chronic diseases; presence of six specific chronic diseases; and prior healthcare use. Analyses were conducted by site and subsequently pooled. The following variables were included in the DAG: age, sex, time within influenza season and year, health status and comorbidities, study site, health-care-seeking behavior, contact patterns and social precautionary behavior, socioeconomic status, and pre-existing immunity. Across all age groups and settings, only adjustment for lung disease in older adults in the primary care setting resulted in a relative change of the IVE point estimate >10%. Our study supports a parsimonious approach to confounder adjustment in TND studies, limited to adjusting for age, sex, and calendar time. Practical implications are that necessitating fewer variables lowers the threshold for enrollment of sites in IVE studies and simplifies the pooling of data from different IVE studies or study networks.

Effects of Confounding Bias in Coronavirus Disease 2019 (COVID-19) and Influenza Vaccine Effectiveness Test-Negative Designs Due to Correlated Influenza and COVID-19 Vaccination Behaviors.

BackgroundThe test-negative design is commonly used to estimate influenza and coronavirus disease 2019 (COVID-19) vaccine effectiveness (VE). In these studies, correlated COVID-19 and influenza vaccine behaviors may introduce a confounding bias where controls are included with the other vaccine-preventable acute respiratory illness (ARI). We quantified the impact of this bias on VE estimates in studies where this bias is not addressed.MethodsWe simulated study populations under varying vaccination probabilities, COVID-19 VE, influenza VE, and proportions of controls included with the other vaccine-preventable ARI. Mean bias was calculated as the difference between estimated and true VE. Absolute mean bias in VE estimates was classified as low (<10%), moderate (10% to <20%), and high (≥20%).ResultsWhere vaccination probabilities are positively correlated, COVID-19 and influenza VE test-negative studies with influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ARI controls, respectively, underestimate VE. For COVID-19 VE studies, mean bias was low for all scenarios where influenza represented ≤25% of controls. For influenza VE studies, mean bias was low for all scenarios where SARS-CoV-2 represented ≤10% of controls. Although bias was driven by the conditional probability of vaccination, low VE of the vaccine of interest and high VE of the confounding vaccine increase its magnitude.ConclusionsWhere a low percentage of controls is included with the other vaccine-preventable ARI, bias in COVID-19 and influenza VE estimates is low. However, influenza VE estimates are likely more susceptible to bias. Researchers should consider potential bias and its implications in their respective study settings to make informed methodological decisions in test-negative VE studies.

Using capture-recapture methods to estimate influenza hospitalization incidence rates.

BackgroundAccurate population estimates of disease incidence and burden are needed to set appropriate public health policy. The capture–recapture (C‐R) method combines data from multiple sources to provide better estimates than is possible using single sources.MethodsData were derived from clinical virology test results and from an influenza vaccine effectiveness study from seasons 2016–2017 to 2018–2019. The Petersen C‐R method was used to estimate the population size of influenza cases; these estimates were then used to calculate adult influenza hospitalization burden using a Centers for Disease Control and Prevention (CDC) multiplier method.ResultsOver all seasons, 343 influenza cases were reported in the clinical database, and 313 in the research database. Fifty‐nine cases (17%) reported in the clinical database were not captured in the research database, and 29 (9%) cases in the research database were not captured in the clinical database. Influenza hospitalizations were higher among vaccinated (58%) than the unvaccinated (35%) in the current season and were similar among unvaccinated (51%) and vaccinated (49%) in the previous year. Completeness of the influenza hospitalization capture was estimated to be 76%. The incidence rates for influenza hospitalizations varied by age and season and averaged 307–309 cases/100,000 adult population annually.ConclusionUsing C‐R methods with more than one database, along with a multiplier method with adjustments improves the population estimates of influenza disease burden compared with relying on a single‐data source.

Agreement among sources of adult influenza vaccination in the age of immunization information systems

IntroductionMany vaccination studies rely on self-reported vaccination status, with its inherent biases. Accuracy of influenza vaccination self-report has been evaluated periodically, typically using the medical record as the gold standard. The burgeoning of electronic medical records (EMRs) and immunization information systems (IISs) and the rise of adult vaccine administration in community pharmacies suggest the need for a reevaluation of self-reported vaccination status. MethodsVaccination data from self-report, the state IIS, the health system EMR and other sources were compared for participants in outpatient and inpatient influenza vaccine effectiveness studies for four seasons (2016–2017 to 2019–2020). Agreement among the sources was calculated along with sensitivity and specificity. Tests for trend assessed changes in completeness of the Pennsylvania - Statewide IIS (PA-SIIS) data over time. ResultsWith self-report as the gold standard, agreement with the local EMR, PA-SIIS, and all sources was 62%, 77% and 85%, respectively. Sensitivity of the EMR was 42% (95% CI = 41, 43) and specificity was 91% (90, 92). With PA-SIIS-as the gold standard, agreement with the local EMR and all sources was 77% and 78%, respectively. Sensitivity of all sources combined was 96% (95, 97) and specificity was (63% (62, 64). Capture of influenza vaccinations in the IIS has not consistently improved over time, with a significant increase among children (P = 0.001), no change among working-age adults and a decrease among older adults (P = 0.004). However, PA-SIIS provided the largest percentage of verified vaccines (69.3%) compared with EMR (43.3%) and other sources (12.4%). ConclusionBoth self-report and PA-SIIS are good estimates of actual vaccine uptake. When high accuracy data are required, such as for vaccine effectiveness studies, triangulation using multiple sources should be conducted.

Influence function methods to assess the effectiveness of influenza vaccine with survey data.

To examine a robust relative risk (RR) estimation for survey data analysis with ideal inferential properties under various model assumptions. We employed secondary data from the Household Component of the 2000-2016 US Medical Expenditure Panel Survey (MEPS). We investigate a broad range of data-balancing techniques by implementing influence function (IF) methods, which allows us to easily estimate the variability for the RR estimates in the complex survey setting. We conduct a simulation study of seasonal influenza vaccine effectiveness to evaluate these approaches and discuss techniques that show robust inferential performance across model assumptions. Demographic information, vaccine status, and self-administered questionnaire surveys were obtained from the longitudinal data files. We linked this information with medical condition files and medical event to extract the disease type and associated expenditures for each medical visit. We excluded individuals who were 18 years or younger at the beginning of each panel. Under various model assumptions, the IF methods show robust inferential performance when the data-balancing procedures are incorporated. Once IF methods and data-balancing techniques are implemented, contingency table-based RR estimation yields a comparable result to the generalized linear model approach. We demonstrate the applicability of the proposed methods for complex survey data using 2000-2016 MEPS data. When employing these methods, we find a significant, negative association between vaccine effectiveness (VE) estimates and influenza-incurred expenditures. We describe and demonstrate a robust method for RR estimation and relevant inferences for influenza vaccine effectiveness using MEPS data. The proposed method is flexible and can be extended to weighted data for survey data analysis. Hence, these methods have great potential for health services research, especially when data are nonexperimental and imbalanced.

Agreement between state registry, health record, and self-report of influenza vaccination

BackgroundDocumentation of influenza vaccination, including the specific product received, is critical to estimate annual vaccine effectiveness (VE). MethodsWe assessed performance of the Michigan Care Improvement Registry (MCIR) in defining influenza vaccination status relative to documentation by provider records or self-report among subjects enrolled in a study of influenza VE from 2011 through 2019. ResultsThe specificity and positive predictive value of MCIR were high; however, >10% of vaccinations were identified only by other sources each season. The proportion of records captured by MCIR increased from a low of 67% in 2013–2014 to a high of 89% in 2018–2019, largely driven by increased capture of vaccination among adults. ConclusionsState vaccine registries, such as MCIR, are important tools for documenting influenza vaccination, including the specific product received. However, incomplete capture suggests that documentation from other sources and self-report should be used in combination with registries to reduce misclassification.

Role of Age in the Spread of Influenza, 2011-2019: Data From the US Influenza Vaccine Effectiveness Network.

Intraseason timing of influenza infection among persons of different ages could reflect relative contributions to propagation of seasonal epidemics and has not been examined among ambulatory patients. Using data from the US Influenza Vaccine Effectiveness Network, we calculated risk ratios derived from comparing weekly numbers of influenza cases prepeak with those postpeak during the 2010-2011 through 2018-2019 influenza seasons. We sought to determine age-specific differences during the ascent versus descent of an influenza season by influenza virus type and subtype. We estimated 95% credible intervals around the risk ratios using Bayesian joint posterior sampling of weekly cases. Our population consisted of ambulatory patients with laboratory-confirmed influenza who enrolled in an influenza vaccine effectiveness study at 5 US sites during 9 influenza seasons after the 2009 influenza A virus subtype H1N1 (H1N1) pandemic. We observed that young children aged <5 years tended to more often be infected with H1N1 during the prepeak period, while adults aged ≥65 years tended to more often be infected with H1N1 during the postpeak period. However, for influenza A virus subtype H3N2, children aged <5 years were more often infected during the postpeak period. These results may reflect a contribution of different age groups to seasonal spread, which may differ by influenza virus type and subtype.

Investigating the procurement system for understanding seasonal influenza vaccine brand availability in Europe.

Timely knowledge of which influenza vaccine brands are procured and where is of interest to inform site-selection for brand-specific influenza vaccine effectiveness (VE) studies. Vaccine procurement is a key determinant of brand availability. We therefore sought to understand how the procurement for seasonal influenza vaccine in Europe is organized, how this drives brand availability and how procurement data could enable to determine brand availability pre-season. Structured telephone interviews were conducted with 15 experts in 16 European countries between 2017 and 2019 to collect information on the influenza vaccine procurement systems. Sources of (brand-specific) procurement data were identified and assessed on public accessibility. Vaccine type and brand availability and timelines were determined for the 2019-20 season to understand how procurement systems drive brand availability and diversity. Four main types of procurement systems for seasonal influenza vaccination campaigns were identified: national public tenders (Croatia, Denmark, Finland, Ireland, Lithuania, Netherlands, Norway, Scotland, Slovenia), regional public tenders (Italy, Spain, Sweden), direct purchase of vaccines by GPs (England, Wales) or pharmacies (Belgium, France, Germany, Greece) from manufacturers or wholesalers. National public tender outcomes are publicly available and timely; brand availability at clinic level can generally be deduced or narrowed down to two brands. Regional tender outcomes are more difficult to find, known very late or not available. In Italian and Spanish regions tenders may be awarded only a few weeks before the seasonal campaign. No public procurement information is available for countries with direct purchase. At the country-level, brand diversity is generally lower for countries with national public tenders than for countries with regional public tenders or direct purchase. In only a few countries, procurement data at the brand level is both publicly available and timely. Therefore the usefulness of procurement data for prospective site-selection for brand-specific VE studies is limited.

Underlying cardiopulmonary conditions as a risk factor for influenza and respiratory syncytial virus infection among community-dwelling adults aged≥65 years in Thailand: Findings from a two-year prospective cohort study.

BackgroundAdults with cardiopulmonary conditions may be at increased risk of influenza and respiratory syncytial virus (RSV) infection, but it is not well‐established and few data are available from middle‐income countries.MethodsUsing data from a prospective cohort study of influenza vaccine effectiveness, we estimated and compared the incidences of influenza and RSV between community‐dwelling Thai adults aged ≥ 65 years with and without cardiopulmonary conditions. During May 2015‐May 2017, older adults in a rural province in Thailand were followed‐up with weekly surveillance for acute respiratory illness (ARI), defined broadly as new onset or worsening of cough with or without fever, and hospitalized ARI. When ill, nasal self‐swabs and/or nasopharyngeal swabs were collected for reverse‐transcription polymerase chain reaction testing. We used Poisson regression to calculate incidence rate ratios (IRR), adjusting for age, sex, current smoking, number of hospital visits, weekly influenza activity, and influenza vaccination.ResultsOverall, 3220 adults with a median age of 71 years (IQR 68‐76) were enrolled; 1324 (41.1%) were male; and 313 (9.7%) had ≥1 underlying cardiopulmonary condition, most commonly chronic obstructive pulmonary disease (131; 41.2%) or asthma (73; 23.3%). Participants with cardiopulmonary conditions had higher incidences of ARI, influenza, and RSV than those without (Adjusted IRR: 1.84, 95% CI 1.64‐2.07; 1.86, 95% CI 1.07‐3.26; 2.04, 95% CI 1.11‐3.76, respectively).ConclusionOlder adults in rural Thailand with cardiopulmonary conditions have increased rates of ARI, influenza, and RSV infections. Our findings support efforts to ensure this population has access to influenza vaccines and other respiratory illness prevention measures.

Challenges and Adaptation of a European Influenza Vaccine Effectiveness Study Platform in Response to the COVID-19 Emergence: Experience from the DRIVE Project.

The Development of Robust and Innovative Vaccine Effectiveness (DRIVE) project is a public–private partnership aiming to build capacity in Europe for yearly estimation of brand-specific influenza vaccine effectiveness (IVE). DRIVE is a five-year project funded by IMI (Innovative Medicines Initiative). It was initiated as a response to the guidance on influenza vaccines by EMA (European Medicines Agency), which advised vaccine manufacturers to work with public health institutes to set up a joint IVE study platform. The COVID-19 pandemic reached Europe in February 2020 and overlapped with the 2019/2020 influenza season only in the last weeks. However, several elements of the DRIVE study network were impacted. The pandemic specifically affected the study sites’ routines and the subsequent assessment of the 2019/20 influenza season. Moreover, the current social distancing measures and lockdown policies across Europe are expected to also limit the circulation of influenza for the 2020/21 season, and therefore the impact of COVID-19 will be higher than in the season 2019/20. Consequently, DRIVE has planned to adapt its study platform to the COVID-19 challenge, encompassing several COVID-19 particularities in the study procedures, data collection and IVE analysis for the 2020/21 season. DRIVE will study the feasibility of implementing these COVID-19 components and establish the foundations of future COVID-19 vaccine effectiveness studies.

Evaluating the Effectiveness of Influenza Vaccine in People With At-Risk Medical Conditions: A Test-Negative Design Case-Control Study for the Seasonal Influenza Vaccine Effectiveness II (SIVE II) Project

Background: Seasonal trivalent inactivated influenza (TIV) vaccine effectiveness (VE) against laboratory confirmed influenza in adults with at-risk medical conditions is not well established. Previous studies have been hampered by small sample sizes to assess VE for each at-risk medical condition recommended for vaccination. Larger better powered studies investigating how influenza VE varied in those with specific risk factors associated with poor influenza outcomes is therefore required. Methods: A test-negative design case-control study of influenza VE was carried out in adults with at-risk medical conditions in Scotland between 2010/11 to 2015/16. We used individual patient-level health administrative data from 223 primary care practices linked with hospital and laboratory data (n=10275 swabs from n=9147 individuals). Generalised additive logistic regression was used to provide adjusted VE estimates between adults (aged >18 years) with laboratory-confirmed influenza compared to those with a negative test for influenza. Findings: Significant positive VE was found for all adults with chronic heart disease (31%; 95% confidence interval [CI]: 10 to 48), diabetes (34%; 95%CI: 12 to 51), impaired immune function (51%; 95%CI: 13 to 72), chronic kidney disease (40%; 95%CI: 17 to 57) and Body Mass Index (BMI) >30 to <40 kg/m2 (62%; 95%CI: 26 to 81). Significant VE was demonstrated for impaired immune function amongst most age groups including younger adults (18-54 years; 68%; 95%CI: 17 to 88) and those aged 85 years and over (42%; 95%CI: 4 to 65). The oldest adults aged 85 years and over had a significant positive VE for chronic respiratory disease (20%; 95%CI: 3 to 34), diabetes (34%; 95%CI: 11 to 51), and impaired immune function (42%; 95%CI: 4 to 65). Non-significant VE was found for those with chronic neurological disease (18%; 95%CI: -16 to 43). Interpretation: The amount of vaccine protection against laboratory-confirmed influenza varied amongst adults with at-risk medical conditions in different age groups. Seasonal influenza vaccination programmes should additionally consider those with BMI >30 to <40 kg/m2. Available alternate vaccines which aim to improve immune response should be considered for at-risk groups with consistently low TIV VE (e.g. neurological disease). Funding Statement: National Institute for Health Research Health Technology Assessment Programme (project number 13/34/14), Health Data Research UK, Asthma UK Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: The Privacy Advisory Committee of the Information Services Division, NSS, approved the linkage and the statistical analysis of the anonymised data used in this study. Ethical permission was granted from the National Research Ethics Service Committee, West Midlands - Edgbaston [15/WM/0035].

Comparison of Parental Report of Influenza Vaccination to Documented Records in Children Hospitalized With Acute Respiratory Illness, 2015-2016.

Parent-reported influenza vaccination history may be valuable clinically and in influenza vaccine effectiveness (VE) studies. Few studies have assessed the validity of parental report among hospitalized children. Parents of 2597 hospitalized children 6 months-17 years old were interviewed from November 1, 2015 to June 30, 2016, regarding their child's sociodemographic and influenza vaccination history. Parent-reported 2015-2016 influenza vaccination history was compared with documented vaccination records (considered the gold standard for analysis) obtained from medical records, immunization information systems, and providers. Multivariable logistic regression analyses were conducted to determine potential factors associated with discordance between the 2 sources of vaccination history. Using a test-negative design, we estimated VE using vaccination history obtained through parental report and documented records. According to parental report, 1718 (66%) children received the 2015-2016 influenza vaccine, and of those, 1432 (83%) had documentation of vaccine receipt. Percent agreement was 87%, with a sensitivity of 96% (95% confidence interval [CI], 95%-97%) and a specificity of 74% (95% CI, 72%-77%). In the multivariable logistic regression, study site and child's age 5-8 years were significant predictors of discordance. Adjusted VE among children who received ≥1 dose of the 2015-2016 influenza vaccine per parental report was 61% (95% CI, 43%-74%), whereas VE using documented records was 55% (95% CI, 33%-69%). Parental report of influenza vaccination was sensitive but not as specific compared with documented records. However, VE against influenza-associated hospitalizations using either source of vaccination history did not differ substantially. Parental report is valuable for timely influenza VE studies.

Silent Transmission of SARS-CoV-2 Among Ambulatory Influenza Like Illness (ILI) Patients

Background: The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China in December 2019 has led to a pandemic. Influenza and coronaviruses are known to show cross-reactive immunity. Therefore, we hypothesized that influenza vaccination may provide a protective effect against SARS-CoV-2.Methods: We investigated the presence of SARS-CoV-2 in flu vaccinated and unvaccinated ILI cases by real time PCR, followed by confirmation of evolutionary and spatial relationships using next generation sequencing (NGS).Results: Out of 739 nasopharyngeal specimens collected from November 2019 to March 2020, we found 37 samples were positive for SARS-CoV-2 RNA mostly during February 2020. We observed that the overall incidence of ILI cases during 2019-2020 influenza season was considerably higher than previous years and was gradually replaced with SARS-CoV-2 which indicated a slow transmission among ambulatory patients. NGS data confirmed independent introductions and transmission earlier than previously thought. Phylogenetic reconstruction of representative isolates showed clustering in the GH clade which is characterized by two amino acid changes in spike gene (D614G) and NS3 (Q57H). Shortness of breath was significantly lower (p = 0.04) in the ILI cases with the history of influenza vaccination suggesting a protective effect of the influenza vaccine, at least in part, on COVID-19 disease outcomes.Conclusions: The detection of SARS-CoV-2 among ILI patients shows the importance of flu vaccination and ILI surveillance system and warrants their further strengthening to mitigate the ongoing transmission of SARS-CoV-2 and to guide policy makers to optimize public health interventions.Funding Statement: This work was supported by the Research Center at King Fahad Medical city (Grant No 20- 066).Declaration of Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.Ethics Approval Statement: The study was approved by the Institutional Review Board at King Fahad Medical City (IRB Log No. 19-477 approved on 25 September 2019) for influenza vaccine effectiveness study, started from 7 November 2019. When COVID-19 pandemic started, the collection of samples stopped on the 2nd of March 2020. To screen those samples for SARS-CoV-2, we applied for another IRB (Log No. 20-161 approved on 23 March 2020).

Incorporating Real-time Influenza Detection Into the Test-negative Design for Estimating Influenza Vaccine Effectiveness: The Real-time Test-negative Design (rtTND).

With rapid and accurate molecular influenza testing now widely available in clinical settings, influenza vaccine effectiveness (VE) studies can prospectively select participants for enrollment based on real-time results rather than enrolling all eligible patients regardless of influenza status, as in the traditional test-negative design (TND). Thus, we explore advantages and disadvantages of modifying the TND for estimating VE by using real-time, clinically available viral testing results paired with acute respiratory infection eligibility criteria for identifying influenza cases and test-negative controls prior to enrollment. This modification, which we have called the real-time test-negative design (rtTND), has the potential to improve influenza VE studies by optimizing the case-to-test-negative control ratio, more accurately classifying influenza status, improving study efficiency, reducing study cost, and increasing study power to adequately estimate VE. Important considerations for limiting biases in the rtTND include the need for comprehensive clinical influenza testing at study sites and accurate influenza tests.

Assessment of the benefits of seasonal influenza vaccination: Elements of a framework to interpret estimates of vaccine effectiveness and support robust decision-making and communication.

Systematic reviews and meta‐analyses confirm that influenza vaccination reduces the risk of influenza illness by between about 40% and 60% in seasons when circulating influenza stains are well matched to vaccine strains. Influenza vaccine effectiveness (IVE) estimates, however, are often discordant and a source of confusion for decision makers. IVE assessments are increasingly publicized and are often used by policy makers to make decisions about the value of seasonal influenza vaccination. But there is limited guidance on how IVE should be interpreted or used to inform policy. There are several limitations to the use of IVE for decision‐making: (a) IVE studies have methodological issues that often complicate the interpretation of their value; and (b) the full impact of vaccination will almost always be greater than the impact assessed by a point estimate of IVE in specific populations or settings. Understanding the strengths and weaknesses of study methodologies and the fundamental limitations of IVE estimates is important for the accuracy of interpretations and support of policy makers’ decisions. Here, we review a comprehensive set of issues that need to be considered when interpreting IVE and determining the full benefits of influenza vaccination. We propose that published IVE values should be assessed using an evaluative framework that includes influenza‐specific outcomes, types of VE study design, and confounders, among other factors. Better interpretation of IVE will improve the broader assessment of the value of influenza vaccination and ultimately optimize the public health benefits in seasonal influenza vaccination.

Influenza vaccine effectiveness studies in Europe: SWOT analysis of DRIVE collaborating sites

Abstract Background DRIVE is a European public-private partnership that aims at creating a network that works on high quality, brand-specific effectiveness estimates for all influenza vaccines used in the EU each season. The SWOT analysis aims at assessing the quality and feasibility of DRIVE operational model after its implementation, i.e. the operations of the study site network as applied in DRIVE. Methods The SWOT analysis was conducted through two meetings held among 2 of 14 partners participating in the DRIVE studies in the first season, with clinicians, nurses, data managers and lab technicians from the sites in the network. We collected data on two identified axes (1.organizational and 2.logistical, practical, and laboratory aspects), containing more than one SWOT objective. For each item classified under Strength (S), Weakness (W), Opportunity (O) or Threat (T), experts assigned a 1-5 score, meant to reflect the impact of each listed item on reaching the objectives. Results The most common topics, reported by both Italian and Finnish sites collaborators, were the opportunities related to the training and development of the network; funding concerns; opportunities and challenges in training the personnel; management issues due to the project practical organization (e.g. for lack of dedicated personnel, including administrative and for data entry). The scores attributed to the single items appeared skewed to the top, showing how the researchers perceived the majority of the topics as relevant for their day-to-day work. Conclusions The SWOT exercise was welcomed as a useful means to compare issues and practices among local study sites, but also as a chance for exchange with both peers and project lead. The results highlight the great value of communication and discussion between study groups, albeit the geographical distance. Such exercise should be included as a routine opportunity for discussion aiming at improving both collaboration and governance model in large projects. Key messages One of the main challenges of large public-private consortiums is building a shared governance model; opportunities for collective sharing and collaboration should be promoted in this setting. This SWOT analysis was a useful exercise that should inform the prosecution of the programming of DRIVE operational model, allowing a comparison of issues and practices among local study sites.