Comparative hospitalization risk for SARS-CoV-2 Omicron and Delta variant infections, by variant predominance periods and patient-level sequencing results, New York City, August 2021-January 2022

Influenza Other Respir Viruses. 2023 Jan;17(1):e13062. doi: 10.1111/irv.13062. Epub 2022 Oct 31.

Abstract

Background: Comparing disease severity between SARS-CoV-2 variants among populations with varied vaccination and infection histories can help characterize emerging variants and support healthcare system preparedness.

Methods: We compared COVID-19 hospitalization risk among New York City residents with positive laboratory-based SARS-CoV-2 tests when ≥98% of sequencing results were Delta (August-November 2021) or Omicron (BA.1 and sublineages, January 2022). A secondary analysis defined variant exposure using patient-level sequencing results during July 2021-January 2022, comprising 1-18% of weekly confirmed cases.

Results: Hospitalization risk was lower among patients testing positive when Omicron (16,025/488,053, 3.3%) than when Delta predominated (8268/158,799, 5.2%). In multivariable analysis adjusting for demographic characteristics and prior diagnosis and vaccination status, patients testing positive when Omicron predominated, compared with Delta, had 0.72 (95% CI: 0.63, 0.82) times the hospitalization risk. In a secondary analysis of patients with sequencing results, hospitalization risk was similar among patients infected with Omicron (2042/29,866, 6.8%), compared with Delta (1780/25,272, 7.0%), and higher among the subset who received two mRNA vaccine doses (adjusted relative risk 1.64; 95% CI: 1.44, 1.87).

Conclusions: Hospitalization risk was lower among patients testing positive when Omicron predominated, compared with Delta. This finding persisted after adjusting for prior diagnosis and vaccination status, suggesting intrinsic virologic properties, not population-based immunity, explained the lower severity. Secondary analyses demonstrated collider bias from the sequencing sampling frame changing over time in ways associated with disease severity. Representative data collection is necessary to avoid bias when comparing disease severity between previously dominant and newly emerging variants.

Keywords: COVID-19; SARS-CoV-2; epidemiology; hospitalization; informatics; public health; selection bias; whole genome sequencing.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • COVID-19* / diagnosis
  • COVID-19* / epidemiology
  • Hospitalization
  • Humans
  • New York City / epidemiology
  • SARS-CoV-2* / genetics

Supplementary concepts

  • SARS-CoV-2 variants