Influenza Vaccine Effectiveness in Households With Children During the 2012-2013 Season: Assessments of Prior Vaccination and Serologic Susceptibility

Ohmit, Suzanne E.; Petrie, Joshua G.; Malosh, Ryan E.; Fry, Alicia M.; Thompson, Mark G.; Monto, Arnold S.

doi:10.1093/infdis/jiu650

Cited by 90 publications

(126 citation statements)

References 20 publications

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“…Eighteen studies met the eligibility criteria [4,13,[16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31]. Of these, one study was restricted to hospitalized patients and was therefore excluded from the meta-analysis [31].…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Repeated annual influenza vaccination and vaccine effectiveness: review of evidence

Belongia

Skowronski

McLean

et al. 2017

Expert Review of Vaccines

233

185

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Introduction: Studies in the 1970s and 1980s signaled concern that repeated influenza vaccination could affect vaccine protection. The antigenic distance hypothesis provided a theoretical framework to explain variability in repeat vaccination effects based on antigenic similarity between successive vaccine components and the epidemic strain. Areas covered: A meta-analysis of vaccine effectiveness studies from 2010-11 through 2014-15 shows substantial heterogeneity in repeat vaccination effects within and between seasons and subtypes. When negative effects were observed, they were most pronounced for H3N2, especially in 2014-15 when vaccine components were unchanged and antigenically distinct from the epidemic strain. Studies of repeated vaccination across multiple seasons suggest that vaccine effectiveness may be influenced by more than one prior season. In immunogenicity studies, repeated vaccination blunts the hemagglutinin antibody response, particularly for H3N2. Expert commentary: Substantial heterogeneity in repeated vaccination effects is not surprising given the variation in study populations and seasons, and the variable effects of antigenic distance and immunological landscape in different age groups and populations. Caution is required in the interpretation of pooled results across multiple seasons, since this can mask important variation in repeat vaccination effects between seasons. Multi-season clinical studies are needed to understand repeat vaccination effects and guide recommendations. ARTICLE HISTORY

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Section: Resultsmentioning

confidence: 99%

“…Another study at the University of Michigan found blunting of the H3N2 vaccine response in a cohort study with 321 households (1426 members) during the 2012-2013 season [21]. Subjects with any vaccine exposure had higher titers than those who were unvaccinated in both 2012-2013 and the prior season.…”

Section: Michigan Household Cohort Studymentioning

confidence: 97%

Repeated annual influenza vaccination and vaccine effectiveness: review of evidence

Belongia

Skowronski

McLean

et al. 2017

Expert Review of Vaccines

233

185

View full text Add to dashboard Cite

show abstract

“…Current season influenza VE has been suggested to vary by prior season influenza vaccine history [34][35][36]. Our study would benefit from having taken prior season influenza vaccination into account in the analysis, however, sample size for stratification by receipt of previous season vaccination is still small despite the five year pooling.…”

Section: Discussionmentioning

confidence: 99%

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?

Kissling¹,

et al. 2016

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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.

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“…Patient-derived samples of influenza A virus were collected as part of the Household Influenza Vaccine Effectiveness (HIVE) study (39,40) and kindly provided by Arnold S. Monto and colleagues at the University of Michigan School of Public Health. The HIVE study was approved by the Institutional Review Board at the University of Michigan, and all subjects provided informed consent.…”

Section: Methodsmentioning

confidence: 99%

Measurements of Intrahost Viral Diversity Are Extremely Sensitive to Systematic Errors in Variant Calling

McCrone

Lauring

2016

J Virol

115

164

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With next-generation sequencing technologies, it is now feasible to efficiently sequence patient-derived virus populations at a depth of coverage sufficient to detect rare variants. However, each sequencing platform has characteristic error profiles, and sample collection, target amplification, and library preparation are additional processes whereby errors are introduced and propagated. Many studies account for these errors by using ad hoc quality thresholds and/or previously published statistical algorithms. Despite common usage, the majority of these approaches have not been validated under conditions that characterize many studies of intrahost diversity. Here, we use defined populations of influenza virus to mimic the diversity and titer typically found in patient-derived samples. We identified single-nucleotide variants using two commonly employed variant callers, Deep-SNV and LoFreq. We found that the accuracy of these variant callers was lower than expected and exquisitely sensitive to the input titer. Small reductions in specificity had a significant impact on the number of minority variants identified and subsequent measures of diversity. We were able to increase the specificity of DeepSNV to >99.95% by applying an empirically validated set of quality thresholds. When applied to a set of influenza virus samples from a household-based cohort study, these changes resulted in a 10-fold reduction in measurements of viral diversity. We have made our sequence data and analysis code available so that others may improve on our work and use our data set to benchmark their own bioinformatics pipelines. Our work demonstrates that inadequate quality control and validation can lead to significant overestimation of intrahost diversity. IMPORTANCEAdvances in sequencing technology have made it feasible to sequence patient-derived viral samples at a level sufficient for detection of rare mutations. These high-throughput, cost-effective methods are revolutionizing the study of within-host viral diversity. However, the techniques are error prone, and the methods commonly used to control for these errors have not been validated under the conditions that characterize patient-derived samples. Here, we show that these conditions affect measurements of viral diversity. We found that the accuracy of previously benchmarked analysis pipelines was greatly reduced under patientderived conditions. By carefully validating our sequencing analysis using known control samples, we were able to identify biases in our method and to improve our accuracy to acceptable levels. Application of our modified pipeline to a set of influenza virus samples from a cohort study provided a realistic picture of intrahost diversity and suggested the need for rigorous quality control in such studies. Many viral pathogens are thought to exist as a cloud of closely related mutants within an infected individual (1). Until recently, our understanding of intrahost viral dynamics and the impact of viral diversity on evolution and pathogenesis has been li...

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Influenza Vaccine Effectiveness in Households With Children During the 2012-2013 Season: Assessments of Prior Vaccination and Serologic Susceptibility

Abstract: Prior vaccination appears to modify VE by both residual protection and reduced vaccine response.

Cited by 90 publications

References 20 publications

Repeated annual influenza vaccination and vaccine effectiveness: review of evidence

Repeated annual influenza vaccination and vaccine effectiveness: review of evidence

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?

Measurements of Intrahost Viral Diversity Are Extremely Sensitive to Systematic Errors in Variant Calling

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