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ABSTRACT
Background SARS-CoV-2 serologic surveys estimate the proportion of the population with antibodies against historical variants which nears 100% in many settings. New analytic approaches are required to exploit the full information in serosurvey data. Method Using a SARS-CoV-2 anti-Spike (S) protein chemiluminescent microparticle assay, we attained a semi-quantitative measurement of population IgG titres in serial cross-sectional monthly samples of routine blood donations across seven Brazilian state capitals (March 2021-November 2021). In an ecological analysis (unit of

analysis:

age-city-calendar month) we assessed the relative contributions of prior attack rate and vaccination to antibody titre in blood donors. We compared blood donor anti-S titre across the seven cities during the growth phase of the Delta variant of concern (VOC) and use this to predict the resulting age-standardized incidence of severe COVID-19 cases. Results On average we tested 780 samples per month in each location. Seroprevalence rose to >95% across all seven capitals by November 2021. Driven proximally by vaccination, mean antibody titre increased 16-fold over the study. The extent of prior natural infection shaped this process, with the greatest increases in antibody titres occurring in cities with the highest prior attack rates. Mean anti-S IgG was a strong predictor (adjusted R2 =0.89) of the number of severe cases caused by the Delta VOC in the seven cities. Conclusions Semi-quantitative anti-S antibody titres are informative about prior exposure and vaccination coverage and can inform on the potential impact of future SARS-CoV-2 variants. Summary In the face of near 100% SARS-CoV-2 seroprevalence, we show that average semi-quantitative anti-S titre predicted the extent of the Delta variant’s spread in Brazil. This is a valuable metric for future seroprevalence studies.
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Full text: Available Collection: Preprints Database: medRxiv Main subject: COVID-19 Language: English Year: 2022 Document Type: Preprint

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Full text: Available Collection: Preprints Database: medRxiv Main subject: COVID-19 Language: English Year: 2022 Document Type: Preprint