NYU Dataset

Emergence and dissemination of SARS-CoV-2 XBB.1.5 in New York

UID: 10695
* Corresponding Author
Description

This study compared SARS-CoV-2 sequences that were collected from infected patients (n=2,397) who were seen at NYU Langone Health facilities and globally (n=24,060 sequences in GISAID) between August 1, 2022, and February 4, 2023 to understand the proliferation of Omicron strain XBB.1.5. Active SARS-CoV-2 infection was confirmed with positive real-time (RT)-qPCR testing. To assess the association between patients' vaccination statuses, infection statuses, and detected strains, patients were categorized into the following groups:

  1. Unvaccinated: Individuals who had not received a COVID-19 vaccine at the time of SARS-CoV-2 infection, and reported no prior SARS-CoV-2 infections.
  2. Partially vaccinated: Individuals who contracted SARS-CoV-2 infection between the first vaccine shot and less than 14 days after completing their primary vaccination series.
  3. Primary series: Individuals who completed their primary vaccination series at least 14 days ago. (I.e., after the second dose of BNT162b2 (Pfizer/BioNTech) or mRNA-1273 (Moderna) vaccines, or the single-dose COVID-19 Janssen vaccine.)
  4. Boosted: Individuals who had received at least one additional COVID-19 shot (any vaccine) after completing the primary vaccination series.
  5. Re-infected: Individuals who were infected with SARS-CoV-2 infection after having had a previous SARS-CoV-2 infection, regardless of their vaccination status and variant. This group included patients with multiple infections.

The viral genomes collected from patients at NYU Langone were also compared with 'background' SARS-CoV-2 sequences available in GISAID to estimate and compare the introduction and dispersal dynamics of the XBB.1.5 variant.

Timeframe
2022 - 2023
Geographic Coverage
New York (State) - New York City
Subject of Study
Subject Domain
Keywords

Access

Restrictions
Free to All
Instructions
De-identified data, shapefiles, and code generated through this study are available in GitHub. Metadata, including identifiers, for the 'background' GISAID sequences utilized in study analyses can also be found in the GitHub repository.
Access via GitHub

Data, code, and shapefiles

Associated Publications
Data Type
Software Used
bcl2fastq2 v2.20
BEAST v1.10.4
IQ-TREE v2.2.0
Nextclade
Pangolin v3.1.20
Recombination Detection Program (RDP) v4.101
TreeTime v0.8.6
Study Type
Observational
Dataset Format(s)
TSV, FASTQ
Grant Support
G098321N/Research Foundation - Flanders
F.4515.22/Fonds National de la Recherche Scientifique
874850/European Union Horizon 2020
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