Prediction models for neutralization activity against emerging SARS-CoV-2 variants: A cross-sectional study

Area of Science:

• Virology
• Immunology
• Public Health

Background:

• Extensive COVID-19 vaccination campaigns have been implemented globally.
• Emerging SARS-CoV-2 variants, such as Omicron (BA.1 and BA.2), pose a threat due to potential antibody escape.
• Understanding neutralizing activity against these variants is crucial for public health strategies.

Purpose of the Study:

• To evaluate the 50% neutralizing activity (NT50) against SARS-CoV-2 D614G, Delta, Omicron BA.1, and BA.2 variants.
• To develop prediction models for assessing infection risk in the general Japanese population.
• To compare the performance of prediction models for Omicron BA.1 and BA.2.

Main Methods:

• A population-based cross-sectional survey was conducted in Yokohama City, Japan.
• Samples from 1,277 participants were analyzed, with a focus on 123 individuals aged 20-74 who had received two vaccine doses.
• Neutralizing activity (NT50) against SARS-CoV-2 variants and spike protein immunoglobulin G (SP-IgG) levels were measured.

Main Results:

• Neutralizing activity was substantially lower against Omicron BA.1 (geometric mean NT50: 14.9) and BA.2 (12.9) compared to D614G (65.5) and Delta (34.3).
• Prediction models for Omicron BA.1 and BA.2 showed moderate predictive ability.
• The prediction model for Omicron BA.1 demonstrated superior performance compared to the BA.2 model in both initial analysis and validation.

Conclusions:

• In a highly vaccinated Japanese population, neutralizing antibody activity against Omicron BA.1 and BA.2 was significantly reduced.
• The developed prediction models offer moderate utility for assessing Omicron infection risk.
• The Omicron BA.1 prediction model exhibited better performance, highlighting potential differences in immune response or variant characteristics.