Abstract

Expansion of the SARS-CoV-2 BA.4 and BA.5 Omicron subvariants in populations with prevalent immunity from prior infection and vaccination, and associated burden of severe COVID-19, has raised concerns about epidemiologic characteristics of these lineages including their association with immune escape or severe clinical outcomes. Here we show that BA.4/BA.5 cases in a large US healthcare system had at least 55% (95% confidence interval: 43–69%) higher adjusted odds of prior documented infection than time-matched BA.2 cases, as well as 15% (9–21%) and 38% (27–49%) higher adjusted odds of having received 3 and ≥4 COVID-19 vaccine doses, respectively. However, after adjusting for differences in epidemiologic characteristics among cases with each lineage, BA.4/BA.5 infection was not associated with differential risk of emergency department presentation, hospital admission, or intensive care unit admission following an initial outpatient diagnosis. This finding held in sensitivity analyses correcting for potential exposure misclassification resulting from unascertained prior infections. Our results demonstrate that the reduced severity associated with prior (BA.1 and BA.2) Omicron lineages, relative to the Delta variant, has persisted with BA.4/BA.5, despite the association of BA.4/BA.5 with increased risk of breakthrough infection among previously vaccinated or infected individuals.

Continuous monitoring of SARS-CoV-2 variant properties is important for public health planning. Here, the authors use data from the United States and show that Omicron BA.4/5 subvariants, which became dominant in mid-2022, have stronger immune escape properties, but are no more severe, than the previously dominant BA.2.

Details

Title
Association of SARS-CoV-2 BA.4/BA.5 Omicron lineages with immune escape and clinical outcome
Author
Lewnard, Joseph A. 1   VIAFID ORCID Logo  ; Hong, Vennis 2 ; Kim, Jeniffer S. 2 ; Shaw, Sally F. 2   VIAFID ORCID Logo  ; Lewin, Bruno 2 ; Takhar, Harpreet 2 ; Tartof, Sara Y. 3   VIAFID ORCID Logo 

 University of California, Berkeley, Division of Epidemiology, School of Public Health, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); University of California, Berkeley, Division of Infectious Diseases & Vaccinology, School of Public Health, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); University of California, Berkeley, Center for Computational Biology, College of Engineering, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878) 
 Kaiser Permanente Southern California, Department of Research & Evaluation, Pasadena, USA (GRID:grid.280062.e) (ISNI:0000 0000 9957 7758) 
 Kaiser Permanente Southern California, Department of Research & Evaluation, Pasadena, USA (GRID:grid.280062.e) (ISNI:0000 0000 9957 7758); Kaiser Permanente Bernard J. Tyson School of Medicine, Department of Health Systems Science, Pasadena, USA (GRID:grid.19006.3e) (ISNI:0000 0000 9632 6718) 
Pages
1407
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2786732978
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.