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Abstract Background In recent influenza seasons, the effectiveness of inactivated influenza vaccines against circulating A(H3N2) virus has been lower than against A(H1N1)pdm09 and B viruses, even when circulating viruses remained antigenically similar to vaccine components. Methods During the 2016–2017 influenza season, vaccine effectiveness (VE) across age groups and vaccine types was examined among outpatients with acute respiratory illness at 5 US sites using a test-negative design that compared the odds of vaccination among reverse transcription polymerase chain reaction–confirmed influenza positives and negatives. Results Among 7083 enrollees, 1342 (19%) tested positive for influenza A(H3N2), 648 (9%) were positive for influenza B (including B/Yamagata, n = 577), and 5040 (71%) were influenza negative. Vaccine effectiveness was 40% (95% confidence interval [CI], 32% to 46%) against any influenza virus, 33% (95% CI, 23% to 41%) against influenza A(H3N2) viruses, and 53% (95% CI, 43% to 61%) against influenza B viruses. Conclusions The 2016–2017 influenza vaccines provided moderate protection against any influenza among outpatients but were less protective against influenza A(H3N2) viruses than B viruses. Approaches to improving effectiveness against A(H3N2) viruses are needed. The 2016–2017 influenza vaccines provided moderate protection against any influenza among outpatients but were less protective against influenza A(H3N2) viruses than B viruses.

Many 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. Vaccination 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. With 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%). Both 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.

Background Influenza vaccination is recommended for all US residents aged ≥6 months. Vaccine effectiveness (VE) varies by age, circulating influenza strains, and the presence of high‐risk medical conditions. We examined site‐specific VE in the US Influenza VE Network, which evaluates annual influenza VE at ambulatory clinics in geographically diverse sites. Methods Analyses were conducted on 27 180 outpatients ≥6 months old presenting with an acute respiratory infection (ARI) with cough of ≤7‐day duration during the 2011‐2016 influenza seasons. A test‐negative design was used with vaccination status defined as receipt of ≥1 dose of any influenza vaccine according to medical records, registries, and/or self‐report. Influenza infection was determined by reverse‐transcription polymerase chain reaction. VE estimates were calculated using odds ratios from multivariable logistic regression models adjusted for age, sex, race/ethnicity, time from illness onset to enrollment, high‐risk conditions, calendar time, and vaccination status‐site interaction. Results For all sites combined, VE was statistically significant every season against all influenza and against the predominant circulating strains (VE = 19%‐50%) Few differences among four sites in the US Flu VE Network were evident in five seasons. However, in 2015‐16, overall VE in one site was 24% (95% CI = −4%‐44%), while VE in two other sites was significantly higher (61%, 95% CI = 49%‐71%; P = .002, and 53%, 95% CI = 33,67; P = .034). Conclusion With few exceptions, site‐specific VE estimates aligned with each other and overall VE estimates. Observed VE may reflect inherent differences in community characteristics of the sites and highlights the importance of diverse settings for studying influenza vaccine effectiveness.

Background While it is known that acute respiratory illness (ARI) is caused by an array of viruses, less is known about co-detections and the resultant comparative symptoms and illness burden. This study examined the co-detections, the distribution of viruses, symptoms, and illness burden associated with ARI between December 2012 and March 2013. Methods Outpatients with ARI were assayed for presence of 18 viruses using multiplex reverse transcriptase polymerase chain reaction (MRT-PCR) to simultaneously detect multiple viruses. Results Among 935 patients, 60% tested positive for a single virus, 9% tested positive for ≥1 virus and 287 (31%) tested negative. Among children (<18 years), the respective distributions were 63%, 14%, and 23%; whereas for younger adults (18–49 years), the distributions were 58%, 8%, and 34% and for older adults (≥50 years) the distributions were 61%, 5%, and 32% ( P  < 0.001). Co-detections were more common in children than older adults ( P  = 0.01), and less frequent in households without children ( P  = 0.003). Most frequently co-detected viruses were coronavirus, respiratory syncytial virus, and influenza A virus. Compared with single viral infections, those with co-detections less frequently reported sore throat ( P  = 0.01), missed fewer days of school (1.1 vs. 2 days; P  = 0.04), or work (2 vs. 3 days; P  = 0.03); other measures of illness severity did not vary. Conclusions Among outpatients with ARI, 69% of visits were associated with a viral etiology. Co-detections of specific clusters of viruses were observed in 9% of ARI cases particularly in children, were less frequent in households without children, and were less symptomatic (e.g., lower fever) than single infections.

Abstract Background A clinical informatics algorithm (CIA) was developed to systematically identify potential enrollees for a test-negative, case-control study to determine influenza vaccine effectiveness, to improve enrollment over manual records review. Further testing may enhance the CIA for increased efficiency. Methods The CIA generated a daily screening list by querying all medical record databases for patients admitted in the last 3 days, using specified terms and diagnosis codes located in admission notes, emergency department notes, chief complaint upon registration, or presence of a respiratory viral panel charge or laboratory result (RVP). Classification and regression tree analysis (CART) and multivariable logistic regression were used to refine the algorithm. Results Using manual records review, 204 patients (<4/day) were approached and 144 were eligible in the 2014–2015 season compared with 3531 (12/day) patients who were approached and 1136 who were eligible in the 2016–2017 season using a CIA. CART analysis identified RVP as the most important indicator from the CIA list for determining eligibility, identifying 65%–69% of the samples and predicting 1587 eligible patients. RVP was confirmed as the most significant predictor in regression analysis, with an odds ratio (OR) of 4.9 (95% confidence interval [CI], 4.0–6.0). Other significant factors were indicators in admission notes (OR, 2.3 [95% CI, 1.9–2.8]) and emergency department notes (OR, 1.8 [95% CI, 1.4–2.3]). Conclusions This study supports the benefits of a CIA to facilitate recruitment of eligible participants in clinical research over manual records review. Logistic regression and CART identified potential eligibility screening criteria reductions to improve the CIA’s efficiency. A clinical informatics algorithm (CIA) was developed to systematically identify potential enrollees for an influenza vaccine effectiveness study that improved enrollment efficiency over manual record review. Classification and Regression Tree analysis indicated modifications to further increase the CIA’s efficiency.

Abstract Background Evidence establishing effectiveness of influenza vaccination for prevention of severe illness is limited. The US Hospitalized Adult Influenza Vaccine Effectiveness Network (HAIVEN) is a multiyear test-negative case-control study initiated in 2015–2016 to estimate effectiveness of vaccine in preventing influenza hospitalization among adults. Methods Adults aged ≥18 years admitted to 8 US hospitals with acute respiratory illness and testing positive for influenza by polymerase chain reaction were cases; those testing negative were controls. Vaccine effectiveness was estimated with logistic regression adjusting for age, comorbidities, and other confounding factors and stratified by frailty, 2-year vaccination history, and clinical presentation. Results We analyzed data from 236 cases and 1231 controls; mean age was 58 years. More than 90% of patients had ≥1 comorbidity elevating risk of influenza complications. Fifty percent of cases and 70% of controls were vaccinated. Vaccination was 51% (95% confidence interval [CI], 29%–65%) and 53% (95% CI, 11%–76%) effective in preventing hospitalization due to influenza A(H1N1)pdm09 and influenza B virus infection, respectively. Vaccine was protective for all age groups. Conclusions During the 2015–2016 US influenza A(H1N1)pdm09–predominant season, we found that vaccination halved the risk of influenza-association hospitalization among adults, most of whom were at increased risk of serious influenza complications due to comorbidity or age. During the 2015–2016 US influenza A(H1N1)pdm09–predominant season, we found that vaccination halved the risk of influenza-association hospitalization among adults, most of whom were at increased risk of serious influenza complications due to comorbidity or age.

Background. Little is known about vaccine intention behavior among patients recovering from a medically attended acute respiratory infection. Methods. Adults ≥ 18 years old with an acute respiratory infection in the 2014-2015, 2015-2016, and 2016-2017 influenza seasons were tested for influenza and completed surveys. Across seasons, unvaccinated participants were grouped into those who intended to receive the influenza vaccine in the following season (vaccine intention) and those who did not (no vaccine intention). In 2016-2017, participants were asked the reasons for their vaccination behavior. Results. Of the 837 unvaccinated participants, 308 (37%) intended to be vaccinated the next season. The groups did not differ in demographic or overall health factors. In logistic regression, non-Whites, those reporting wheezing or nasal congestion, and those receiving an antiviral prescription were more likely to be in the vaccine intention group. That group was significantly more likely to cite perceived behavioral control reasons for not being vaccinated (forgot), while the no vaccine intention group was significantly (p < .001) more likely to report knowledge/attitudinal reasons (side effects). Conclusion. Because influenza vaccine is given annually, adults must make a conscious decision to receive the vaccine each year. Understanding the factors related to vaccination behavior and intent can help shape interventions to improve influenza vaccination rates. A medical visit at the time of an acute respiratory illness, especially one in which the provider suspects influenza, as evidenced by an antiviral prescription, is an ideal opportunity to recommend influenza vaccine in the next season, to prevent a similar experience.