Validation of neutralizing antibody titers for estimating vaccine effectiveness for the Omicron SARS-CoV-2 variant, BA.1
Abstract
Background
The emergence of new virus variants, including the Omicron variant (B.1.1.529) of SARS-CoV-2, can lead to immune escape and reduced vaccine effectiveness. Neutralizing antibody titers could be used to quickly estimate vaccine effectiveness (VE), because they can be easily measured following the emergence of a new virus variant and have been shown to be a correlate of protection for SARS-CoV-2 and other pathogens. However, few studies have examined VE-neutralizing antibody titer relationships with multiple virus variants, and none have validated relationships for immune evasive variants.
Methods
We leveraged variation among vaccines and virus variants to estimate VE-neutralizing antibody titer relationships across a 54-fold range of neutralizing antibody titers for two endpoints for COVID-19: symptomatic disease, and hospitalization. We predicted VEs for Omicron three days after the first neutralizing antibody titer became available. We tested these predictions using subsequently collected observational VE data.
Findings
For two mRNA vaccines (mRNA-1273, BNT162b2), fitted models predicted that infection with the BA.1 Omicron variant would increase the risk of hospitalization 2.8-4.4-fold and increase the risk of symptomatic disease 1.7-4.2-fold compared to the Delta variant. However, a third vaccine dose was predicted to restore protection. Out-of-sample validation data indicated that model predictions were quite accurate, with all predictions being within 10% of observed VE estimates, and all empirical estimates fell within the model prediction intervals.
Interpretation
These analyses demonstrate that models using neutralizing antibody titers can provide rapid VE estimates which can inform vaccine design and selection.
Funding
California Department of Health, National Science Foundation
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