Predicting SARS-CoV-2 Variant Spread in a Completely Seropositive Population Using Semi-Quantitative Antibody...

Area of Science:

• Immunology
• Epidemiology
• Public Health

Background:

• Existing SARS-CoV-2 serologic surveys often provide limited quantitative data on population immunity.
• High seroprevalence (>95%) was observed across Brazilian capitals by November 2021.
• New methods are needed to better utilize serosurvey data for understanding population immunity and predicting disease impact.

Purpose of the Study:

• To develop and apply a semi-quantitative assay for measuring population IgG antibody titers against SARS-CoV-2.
• To assess the influence of prior infection rates and vaccination on antibody titers.
• To evaluate the correlation between antibody titers and severe COVID-19 incidence during the Delta variant surge.

Main Methods:

• Utilized a SARS-CoV-2 anti-Spike (S) protein chemiluminescent microparticle assay.
• Analyzed serial cross-sectional blood donation samples from seven Brazilian state capitals (March-November 2021).
• Conducted ecological analyses to correlate antibody titers with attack rates, vaccination, and severe COVID-19 cases.

Main Results:

• Mean anti-S IgG antibody titers increased 16-fold over the study period, primarily driven by vaccination.
• Cities with higher prior infection rates showed the greatest increases in antibody titers post-vaccination.
• A strong correlation (adjusted R2 = 0.89) was found between mean anti-S IgG titers and the incidence of severe COVID-19 cases caused by the Delta variant.

Conclusions:

• Semi-quantitative anti-S IgG antibody titers provide valuable insights into population exposure and vaccination coverage.
• Antibody titer measurements can help predict the potential impact of new SARS-CoV-2 variants on severe disease incidence.
• This approach offers a more nuanced understanding of population immunity beyond simple seroprevalence.