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Background: Preexisting antibodies to influenza, shaped by early infection and subsequent exposures, may impact responses to influenza vaccination.Methods: We enrolled 72 children (aged 7-17 years) in 2015-2016; all received inactivated influenza vaccines. Forty-one were also vaccinated in 2014-2015, with 12 becoming infected with A(H3N2) in 2014-2015. Thirty-one children did not have documented influenza exposures in the prior 5 seasons. Sera were collected pre- and postvaccination in both seasons. We constructed antibody landscapes using hemagglutination inhibition antibody titers against 16 A(H3N2) viruses representative of major antigenic clusters that circulated between 1968 and 2015.Results: The breadth of the antibody landscapes increased with age. Vaccine-induced antibody responses correlated with boosting of titers to previously encountered antigens. Postvaccination titers were the highest against vaccine antigens rather than the historic A(H3N2) viruses previously encountered. Prevaccination titers to the vaccine were the strongest predictors of postvaccination titers. Responses to vaccine antigens did not differ by likely priming virus. Influenza A(H3N2)-infected children in 2014-2015 had narrower antibody landscapes than those uninfected, but prior season infection status had little effect on antibody landscapes following 2015-2016 vaccination.Conclusions: A(H3N2) antibody landscapes in children were largely determined by age-related immune priming, rather than recent vaccination or infection. [ABSTRACT FROM AUTHOR]

Background We compared effects of prior vaccination and added or lost protection from current season vaccination among those previously vaccinated. Methods Our analysis included data from the US Flu Vaccine Effectiveness Network among participants ≥9 years old with acute respiratory illness from 2012–2013 through 2017–2018. Vaccine protection was estimated using multivariate logistic regression with an interaction term for effect of prior season vaccination on current season vaccine effectiveness. Models were adjusted for age, calendar time, high-risk status, site, and season for combined estimates. We estimated protection by combinations of current and prior vaccination compared to unvaccinated in both seasons or current vaccination among prior vaccinated. Results A total of 31 819 participants were included. Vaccine protection against any influenza averaged 42% (95% confidence interval [CI], 38%–47%) among those vaccinated only the current season, 37% (95% CI, 33–40) among those vaccinated both seasons, and 26% (95% CI, 18%–32%) among those vaccinated only the prior season, compared with participants vaccinated neither season. Current season vaccination reduced the odds of any influenza among patients unvaccinated the prior season by 42% (95% CI, 37%–46%), including 57%, 27%, and 55% against A(H1N1), A(H3N2), and influenza B, respectively. Among participants vaccinated the prior season, current season vaccination further reduced the odds of any influenza by 15% (95% CI, 7%–23%), including 29% against A(H1N1) and 26% against B viruses, but not against A(H3N2). Conclusions Our findings support Advisory Committee on Immunization Practices recommendations for annual influenza vaccination. Benefits of current season vaccination varied among participants with and without prior season vaccination, by virus type/subtype and season. [ABSTRACT FROM AUTHOR]

Background Improving appropriate antibiotic use is crucial for combating antibiotic resistance and unnecessary adverse drug reactions. Acute respiratory illness (ARI) commonly causes outpatient visits and accounts for ~41% of antibiotics used in the United States. We examined the influence of influenza vaccination on reducing antibiotic prescriptions among outpatients with ARI. Methods We enrolled outpatients aged ≥6 months with ARI from 50–60 US clinics during 5 winters (2013–2018) and tested for influenza with RT-PCR; results were unavailable for clinical decision making and clinical influenza testing was infrequent. We collected antibiotic prescriptions and diagnosis codes for ARI syndromes. We calculated vaccine effectiveness (VE) by comparing vaccination odds among influenza-positive cases with test-negative controls. We estimated ARI visits and antibiotic prescriptions averted by influenza vaccination using estimates of VE, coverage, and prevalence of antibiotic prescriptions and influenza. Results Among 37 487 ARI outpatients, 9659 (26%) were influenza positive. Overall, 36% of ARI and 26% of influenza-positive patients were prescribed antibiotics. The top 3 prevalent ARI syndromes included: viral upper respiratory tract infection (47%), pharyngitis (18%), and allergy or asthma (11%). Among patients testing positive for influenza, 77% did not receive an ICD-CM diagnostic code for influenza. Overall, VE against influenza-associated ARI was 35% (95% CI, 32–39%). Vaccination prevented 5.6% of all ARI syndromes, ranging from 2.8% (sinusitis) to 11% (clinical influenza). Influenza vaccination averted 1 in 25 (3.8%; 95% CI, 3.6–4.1%) antibiotic prescriptions among ARI outpatients during influenza seasons. Conclusion s Vaccination and accurate influenza diagnosis may curb unnecessary antibiotic use and reduce the global threat of antibiotic resistance. [ABSTRACT FROM AUTHOR]

Observational studies have consistently shown that influenza vaccine effectiveness (VE) is lower for H3N2 relative to H1N1pdm09 and type B, and this is not entirely explained by antigenic match. The triad of virus, vaccine, and host immunity provides a framework to examine contributing factors. Antigenic evolution facilitates H3N2 immune escape, and increasing glycosylation of the hemagglutinin shields antigenic sites from antibody binding. Egg passage adaptation of vaccine viruses generates mutations that alter glycosylation, impair the neutralizing antibody response, and reduce VE. Complex host immune factors may also influence H3N2 VE, including early childhood imprinting and repeated vaccination, but their role is uncertain. Of the triad of contributing factors, only changes to the vaccine are readily achievable. However, it is unclear whether current licensed non–egg-based vaccines generate superior protection against H3N2. The optimal strategy remains to be defined, but newer vaccine technology platforms offer great potential. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background Statin medications have immunomodulatory effects. Several recent studies suggest that statins may reduce influenza vaccine response and reduce influenza vaccine effectiveness (VE). Methods We compared influenza VE in statin users and nonusers aged ≥45 years enrolled in the US Vaccine Effectiveness Network study over 6 influenza seasons (2011–2012 through 2016–2017). All enrollees presented to outpatients clinics with acute respiratory illness and were tested for influenza. Information on vaccination status, medical history, and statin use at the time of vaccination were collected by medical and pharmacy records. Using a test-negative design, we estimated VE as (1 – OR) × 100, in which OR is the odds ratio for testing positive for influenza virus among vaccinated vs unvaccinated participants. Results Among 11692 eligible participants, 3359 (30%) were statin users and 2806 (24%) tested positive for influenza virus infection; 78% of statin users and 60% of nonusers had received influenza vaccine. After adjusting for potential confounders, influenza VE was 36% (95% confidence interval [CI], 22%–47%) among statin users and 39% (95% CI, 32%–45%) among nonusers. We observed no significant modification of VE by statin use. VE against influenza A(H1N1)pdm09, A(H3N2), and B viruses were similar among statin users and nonusers. Conclusions In this large observational study, influenza VE against laboratory-confirmed influenza illness was not affected by current statin use among persons aged ≥45 years. Statin use did not modify the effect of vaccination on influenza when analyzed by type and subtype. [ABSTRACT FROM AUTHOR]

Self‐reported influenza vaccination is generally accurate for the current season, but the accuracy of self‐report for vaccination in prior seasons is largely unknown. This study evaluated the accuracy of self‐report for current and prior season influenza vaccination among patients with medically attended acute respiratory illness enrolled in a study of influenza vaccine effectiveness during the 2014‐15 influenza season. It demonstrates there is a greater potential for exposure misclassification when prior season vaccinations are ascertained by self‐report. Percent agreement between self‐report and final status was high for both current and prior season vaccination: 97.7% and 93.2%, respectively. [ABSTRACT FROM AUTHOR]

Background. In the 2015-2016 season, quadrivalent live attenuated influenza vaccine (LAIV) and both trivalent and quadrivalent inactivated influenza vaccine (IIV) were available in the United States. Methods. This study, conducted according to a test-negative case-control design, enrolled children aged 2-17 years presenting to outpatient settings with fever and respiratory symptoms for <5 days at 8 sites across the United States between 30 November 2015 and 15 April 2016. A nasal swab was obtained for reverse-transcriptase polymerase chain reaction (RT-PCR) testing for influenza, and influenza vaccination was verified in the medical record or vaccine registry. Influenza vaccine effectiveness (VE) was estimated using a logistic regression model. Results. Of 1012 children retained for analysis, most children (59%) were unvaccinated, 10% received LAIV, and 31% received IIV. Influenza A (predominantly antigenically similar to the A/California/7/2009 strain) was detected in 14% and influenza B (predominantly a B/Victoria lineage) in 10%. For all influenza, VE was 46% (95% confidence interval [CI], 7%-69%) for LAIV and 65% (48%-76%) for IIV. VE against influenza A(H1N1)pdm09 was 50% (95% CI, -2% to 75%) for LAIV and 71% (51%-82%) for IIV. The odds ratio for vaccine failure with RT-PCR-confirmed A(H1N1)pdm09 was 1.71 (95% CI, 0.78-3.73) in LAIV versus IIV recipients. Conclusions. LAIV and IIV demonstrated effectiveness against any influenza among children aged 2-17 years in 2015-2016. When compared to all unvaccinated children, VE against influenza A(H1N1)pdm09 was significant for IIV but not LAIV. [ABSTRACT FROM AUTHOR]

Background: Human papillomavirus (HPV) vaccine coverage rates remain low. This is believed to reflect parental hesitancy, but few studies have examined how changes in parents' attitudes impact HPV vaccine uptake. This study examined the association between changes in parents' vaccine attitudes and HPV vaccine receipt in their adolescent children.Methods: A baseline and 1-year follow-up survey of HPV vaccine attitudes was administered to parents of 11-17 year olds who had not completed the HPV vaccine series. Changes in attitudinal scores (barriers, harms, ineffectiveness, and uncertainties) from the Carolina HPV Immunization Attitudes and Beliefs Scale were assessed. Two outcomes were measured (in parents' adolescent children) over an 18-month period and analyzed using multivariable regression; receipt of next scheduled HPV vaccine dose and 3-dose series completion.Results: There were 221 parents who completed the baseline survey (11% response rate) and 164 with available follow-up data; 60% of their adolescent children received a next HPV vaccine dose and 38% completed the vaccine series at follow-up. Decrease in parents' uncertainties was a significant predictor of vaccine receipt, with each 1-point reduction in uncertainties score associated with 4.9 higher odds of receipt of the next vaccine dose. Higher baseline harms score was the only significant predictor of lower series completion.Conclusions: Reductions in parents' uncertainties appeared to result in greater likelihood of their children receiving the HPV vaccine. Only baseline concerns about vaccine harms were associated with lower series completion rate. Education for parents should emphasize the HPV vaccine's safety profile. [ABSTRACT FROM AUTHOR]

Background: Recent studies suggest that statin use may reduce influenza vaccine effectiveness (VE), but laboratory-confirmed influenza was not assessed.Methods: Patients ≥45 years old presenting with acute respiratory illness were prospectively enrolled during the 2004-2005 through 2014-2015 influenza seasons. Vaccination and statin use were extracted from electronic records. Respiratory samples were tested for influenza virus.Results: The analysis included 3285 adults: 1217 statin nonusers (37%), 903 unvaccinated statin nonusers (27%), 847 vaccinated statin users (26%), and 318 unvaccinated statin users (10%). Statin use modified VE and the risk of influenza A(H3N2) virus infection (P = .002) but not 2009 pandemic influenza A(H1N1) virus (A[H1N1]pdm09) or influenza B virus infection (P = .2 and .4, respectively). VE against influenza A(H3N2) was 45% (95% confidence interval [CI], 27%-59%) among statin nonusers and -21% (95% CI, -84% to 20%) among statin users. Vaccinated statin users had significant protection against influenza A(H1N1)pdm09 (VE, 68%; 95% CI, 19%-87%) and influenza B (VE, 48%; 95% CI, 1%-73%). Statin use did not significantly modify VE when stratified by prior season vaccination. In validation analyses, the use of other cardiovascular medications did not modify influenza VE.Conclusions: Statin use was associated with reduced VE against influenza A(H3N2) but not influenza A(H1N1)pdm09 or influenza B. Further research is needed to assess biologic plausibility and confirm these results. [ABSTRACT FROM AUTHOR]

Background Recent mumps outbreaks among 2-dose measles mumps rubella (MMR) vaccine recipients have raised questions regarding the potential benefits of a third dose of vaccine (MMR3). If MMR3 provides a sustained elevation in mumps antibody, it may be beneficial for certain at-risk groups or as an outbreak control measure. Methods Sera were collected immediately prior to MMR3 and at 1 month and 1 year post-MMR3 from 656 healthy adults aged 18–28 years in a nonoutbreak setting. Immunoglobulin G (IgG) was measured by enzyme-linked immunosorbent assay (ELISA) using whole mumps virus (commercial ELISA), hemagglutinin (HN; major neutralizing target), and nucleoprotein (NP; immunodominant) antigens. ELISA measurements were compared with in vitro plaque reduction neutralization (PRN) titers, and baseline antibody was compared with post-MMR3 levels. Results There were modest but statistically significant (P <.05) increases in mumps antibody at 1 month post-MMR3 by all 3 ELISA methods and by PRN titer. At 1 year post-MMR3, mumps antibody declined toward baseline but remained elevated (P <.05). The correlation between PRN titers and ELISA measurements was poor (r 2 =.49), although sera with the highest amount of HN IgG also had the highest PRN titers. Conclusions Individuals with the lowest baseline PRN titers had the largest increase in frequency of samples that became positive for HN and NP by ELISA. A third dose of MMR may benefit certain individuals with a low level of mumps virus–neutralizing antibody, especially in the context of an outbreak or other high-risk setting. Additionally, poor correlation among serologic tests does not allow effective prediction of PRN titer by ELISA. [ABSTRACT FROM AUTHOR]

Objective: Local reactions are the most common vaccine-related adverse event. There is no specific diagnosis code for local reaction due to vaccination. Previous vaccine safety studies used non-specific diagnosis codes to identify potential local reaction cases and confirmed the cases through manual chart review. In this study, a natural language processing (NLP) algorithm was developed to identify local reaction associated with tetanus-diphtheria-acellular pertussis (Tdap) vaccine in the Vaccine Safety Datalink.Methods: Presumptive cases of local reactions were identified among members ≥ 11 years of age using ICD-9-CM codes in all care settings in the 1-6 days following a Tdap vaccination between 2012 and 2014. The clinical notes were searched for signs and symptoms consistent with local reaction. Information on the timing and the location of a sign or symptom was also extracted to help determine whether or not the sign or symptom was vaccine related. Reactions triggered by causes other than Tdap vaccination were excluded. The NLP algorithm was developed at the lead study site and validated on a stratified random sample of 500 patients from five institutions.Results: The NLP algorithm achieved an overall weighted sensitivity of 87.9%, specificity of 92.8%, positive predictive value of 82.7%, and negative predictive value of 95.1%. In addition, using data at one site, the NLP algorithm identified 3326 potential Tdap-related local reactions that were not identified through diagnosis codes.Conclusion: The NLP algorithm achieved high accuracy, and demonstrated the potential of NLP to reduce the efforts of manual chart review in vaccine safety studies. [ABSTRACT FROM AUTHOR]

Background To address public concern about the safety of the childhood immunization schedule, the Institute of Medicine recommended observational studies comparing adverse health outcomes of fully vaccinated children to children under-vaccinated due to parental choice. Misclassification of vaccination status could bias such studies. Objective To assess risk of misclassification of vaccination status within the Vaccine Safety Datalink (VSD). Design/methods A retrospective cohort study was conducted in three phases. In phase 1, electronic health record (EHR) data were used to identify patterns of under-vaccination during the first 24 months of life potentially due to parental choice. In phase 2, a random sample of records of under-vaccinated children was manually reviewed. In phase 3, a separate sample of parents were surveyed to assess whether EHR data accurately reflected their child’s vaccination status. Phases 1 and 2 were conducted at 6 VSD sites, phase 3 at 1 site. Results The study cohort included 361,901 children born 2004 through 2012. By 24 months of age, 198,249 (54.8%) were fully vaccinated with no delays, 84,698 (23.4%) experienced delays but were fully vaccinated by 24 months of age, 4865 (1.3%) received no vaccines, 3789 (1.0%) delayed starting vaccination until ≥4 months of age, 4781 (1.3%) had consistent vaccine-limiting (≤2 vaccines per visit), and the remaining 65,519 (18.1%) were missing vaccine series or doses. When a diagnosis code for vaccine refusal was present in EHR data, encounter notes confirmed vaccine refusal as the reason for under-vaccination for nearly 100% of sampled records. Parent surveys confirmed these findings. Parents of under-vaccinated children were more likely to report visiting an alternative medical provider than parents of fully vaccinated children. Conclusions Specific groups of children, under-vaccinated due to parental choice, can be identified with relatively low likelihood of misclassification of vaccination status using EHR-based vaccine data and diagnosis codes. [ABSTRACT FROM AUTHOR]