JOURNAL ARTICLE

Potential Benefits of Expanded Palivizumab in American Indian Children Under the Age of 2 Years.

  • Published In: Journal of the Pediatric Infectious Diseases Society, 2023, v. 12, n. 9. P. 522 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Close, Ryan M; Palmer, Alvin S; McAuley, James B 3 of 3

Abstract

This article focuses on a quality improvement program at the Whiteriver Service Unit (WRSU) in Eastern Arizona that expanded palivizumab (PVZ) prophylaxis to all children under 2 years of age to reduce respiratory syncytial virus (RSV) infections and hospitalizations in a rural American Indian community. The expanded PVZ administration from October 2022 to February 2023 was associated with significant reductions in RSV infections and hospitalizations among both high-risk and non-high-risk children, with an absolute risk reduction of 8.4% for RSV hospitalization among recipients. Despite these positive outcomes, uptake was limited, with only 13.8% of eligible children receiving PVZ. The study acknowledges limitations due to its retrospective design and potential selection bias but suggests that broader RSV prophylaxis could benefit American Indian and Alaska Native populations. The article also notes upcoming RSV prevention strategies, including the long-acting monoclonal antibody nirsevimab, which is recommended for young children including AI/AN populations.

Additional Information

  • Source:Journal of the Pediatric Infectious Diseases Society. 2023/09, Vol. 12, Issue 9, p522
  • Document Type:Article
  • Subject Area:Environmental Sciences
  • Publication Date:2023
  • ISSN:2048-7193
  • DOI:10.1093/jpids/piad063
  • Accession Number:172362028
  • Copyright Statement:Copyright of Journal of the Pediatric Infectious Diseases Society 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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