Vaccine Effectiveness Against Influenza Hospitalization and Emergency Department Visits in 2 A(H3N2) Dominant Influenza Seasons Among Children &amp;lt;18 Years Old—New Vaccine Surveillance Network 2016–2017 and 2017–2018

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Abstract

Studies have shown egg-adaptive mutations in influenza vaccine strains that might have impaired protection against circulating A(H3N2) influenza viruses during the 2016–2017 and 2017–2018 seasons. We used the test-negative design and multivariable models to assess vaccine effectiveness against influenza-associated hospitalization and emergency department visits among children (<18 years old) during the 2016–2017 and 2017–2018 seasons. Effectiveness was 71% (95% confidence interval, 59%–79%), 46% (35%–55%), and 45% (33%–55%) against A(H1N1)pdm09, A(H3N2), and B viruses respectively, across both seasons. During high-severity seasons with concerns for vaccine mismatch, vaccination offered substantial protection against severe influenza outcomes requiring hospitalization or emergency department visits among children.

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The phenomenon of separation or monotone likelihood is observed in the fitting process of a logistic model if the likelihood converges while at least one parameter estimate diverges to +/- infinity. Separation primarily occurs in small samples with several unbalanced and highly predictive risk factors. A procedure by Firth originally developed to reduce the bias of maximum likelihood estimates is shown to provide an ideal solution to separation. It produces finite parameter estimates by means of penalized maximum likelihood estimation. Corresponding Wald tests and confidence intervals are available but it is shown that penalized likelihood ratio tests and profile penalized likelihood confidence intervals are often preferable. The clear advantage of the procedure over previous options of analysis is impressively demonstrated by the statistical analysis of two cancer studies. Copyright 2002 John Wiley & Sons, Ltd.

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Variable influenza vaccine effectiveness by subtype: a systematic review and meta-analysis of test-negative design studies.

Edward A Belongia, Melissa D. Simpson, Jennifer P. King … (2016)

Influenza vaccine effectiveness (VE) can vary by type and subtype. Over the past decade, the test-negative design has emerged as a valid method for estimation of VE. In this design, VE is calculated as 100% × (1 - odds ratio) for vaccine receipt in influenza cases versus test-negative controls. We did a systematic review and meta-analysis to estimate VE by type and subtype.

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Contemporary H3N2 influenza viruses have a glycosylation site that alters binding of antibodies elicited by egg-adapted vaccine strains

Seth Zost, Kaela Parkhouse, Megan E. Gumina … (2017)

Significance The majority of influenza vaccine antigens are prepared in chicken eggs. Human vaccine strains grown in eggs often possess adaptive mutations that increase viral attachment to chicken cells. Most of these adaptive mutations are in the hemagglutinin protein, which functions as a viral attachment factor. Here, we identify a hemagglutinin mutation in the current egg-adapted H3N2 vaccine strain that alters antigenicity. We show that ferrets and humans exposed to the current egg-adapted H3N2 vaccine strain produce antibodies that poorly neutralize H3N2 viruses that circulated during the 2016–2017 influenza season. These studies highlight the challenges associated with producing influenza vaccine antigens in eggs, while offering a potential explanation of why there was only moderate vaccine effectiveness during the 2016–2017 influenza season.

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Author and article information

Contributors

Rangaraj Selvarangan: (View ORCID Profile)

Journal

Title: The Journal of Infectious Diseases

Publisher: Oxford University Press (OUP)

ISSN (Print): 0022-1899

ISSN (Electronic): 1537-6613

Publication date Created: July 01 2022

Publication date Created: August 12 2022

Publication date Created: December 24 2021

Publication date Other: July 01 2022

Publication date (Print): August 12 2022

Publication date (Electronic): December 24 2021

Volume: 226

Issue: 1

Pages: 91-96

Article

DOI: 10.1093/infdis/jiab624

SO-VID: 28fd7e5d-70ca-4b6a-847b-734dfdb78395

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