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01 · ABSTRACT

Abstract

Background: The updated Moderna, Pfizer-BioNTech, and Novavax COVID-19 vaccines containing the SARS-CoV-2 omicron XBB.1.5 strain have replaced their predecessors in the United States and in other countries since the fall of 2023. The clinical impact of these vaccines on currently circulating variants was unknown.

Aims: We aimed to assess the effectiveness of the updated XBB.1.5 vaccines against currently circulating omicron subvariants.

Methods: We examined data on the administration of XBB.1.5 vaccines and the incidence of COVID-19 between September 11 and November 27, 2023 for approximately 2 million persons by linking records from the Nebraska Electronic Disease Surveillance System and the Nebraska State Immunization Information System. We used Cox regression to estimate the effects of XBB.1.5 vaccines on the risk of COVID-19, as a function of time elapsed since vaccination, while adjusting for demographic factors, previous infection history, and previous vaccination history.

Results: The effectiveness (i.e., proportionate reduction of risk) for XBB.1.5 vaccines against SARS-CoV-2 infection was 63.0% (95% confidence interval [CI], 48.6 to 73.4) 4 weeks after vaccination and 67.1% (95% CI, 49.9 to 78.4) 6 weeks after vaccination; vaccine effectiveness started to decline after 6 weeks. Vaccine effectiveness was broadly similar across subgroups defined by age, sex, race and ethnicity, socioeconomic status, and previous immunity status.

Conclusion: XBB.1.5 vaccines were effective against currently circulating variants, regardless of age, sex, race and ethnicity, socioeconomic status, or previous immunity status. These findings can be used to develop effective prevention strategies against COVID-19.

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02 · PUBLICATION RECORD

Article details

JournalMedical Research Archives
IssueVol 12 No 8 (2024): Vol 12 No 8 (2024): August ISSUE, Issue 8, VOl.12
SectionResearch Articles
Published30 August 2024
DOI10.18103/mra.v12i8.5740
ISSN2375-1924
03 · RIGHTS & REUSE

Rights & reuse

This article is published under a Creative Commons Attribution License (CC BY 3.0) and may be shared or distributed by anyone as long as attribution is given to the journal.

Authors & affiliations

DL

Dan-Yu Lin, Ph.D.

Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

YD

Yi Du, Ph.D.

Division of Public Health, Nebraska Department of Health and Human Services, Lincoln, NE 68509, USA; Department of Epidemiology, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA.

YX

Yangjianchen Xu, B.S.

Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

SP

Sai Paritala, Pharm.D.

Division of Public Health, Nebraska Department of Health and Human Services, Lincoln, NE 68509, USA; Department of Epidemiology, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA.

MD

Matthew Donahue, M.D.

Division of Public Health, Nebraska Department of Health and Human Services, Lincoln, NE 68509, USA.

PM

Patrick Maloney, Ph.D.

Division of Public Health, Nebraska Department of Health and Human Services, Lincoln, NE 68509, USA; Department of Epidemiology, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA.

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