JOURNAL ARTICLE

Pfizer-BioNTech Coronavirus Disease 2019 Vaccine Effectiveness Against Severe Acute Respiratory Syndrome Coronavirus 2 Infection Among Long-term Care Facility Staff With and Without Prior Infection in New York City, January–June 2021.

  • Published In: Journal of Infectious Diseases, 2023, v. 227, n. 4. P. 533 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Peebles, Kathryn; Arciuolo, Robert J; Romano, Anthony S; Sell, Jessica; Greene, Sharon K; Lim, Sungwoo; Mulready-Ward, Candace; Ternier, Alexandra; Badenhop, Brittan; Blaney, Kathleen; Real, Joseph E; Spencer, Magdalene; McPherson, Tristan D; Ahuja, Shama Desai; Meissner, Jeanne Sullivan; Zucker, Jane R; Rosen, Jennifer B 3 of 3

Abstract

This article evaluates the effectiveness of the Pfizer-BioNTech COVID-19 vaccine among long-term care facility (LTCF) staff in New York City with and without prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Using weekly SARS-CoV-2 testing data from January to June 2021 and vaccination records, the study found that full vaccination reduced the risk of SARS-CoV-2 infection by approximately 80% among persons without prior infection and increased protection to over 82% among those previously infected, compared with unvaccinated persons without prior infection. Additionally, prior infection alone reduced infection risk by about 55%, but vaccination after infection provided significantly greater protection. These findings support public health recommendations that all eligible individuals, regardless of prior infection status, receive COVID-19 vaccination.

Additional Information

  • Source:Journal of Infectious Diseases. 2023/02, Vol. 227, Issue 4, p533
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2023
  • ISSN:0022-1899
  • DOI:10.1093/infdis/jiac448
  • Accession Number:161937388
  • Copyright Statement:Copyright of Journal of Infectious Diseases is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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