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?:abstract
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Background SARS-CoV-2 serology is used to identify prior infection at individual and at population level. Extended longitudinal studies with multi-timepoint sampling to evaluate dynamic changes in antibody levels are required to identify the time horizon in which these applications of serology are valid, and to explore the longevity of protective humoral immunity. Methods Health care workers were recruited to a prospective cohort study from the first SARS-CoV-2 epidemic peak in London, undergoing weekly symptom screen, viral PCR and blood sampling over 16-21 weeks. Serological analysis (n=12,990) was performed using semi quantitative Euroimmun IgG to viral spike S1 domain and Roche total antibody to viral nucleocapsid protein (NP) assays. Comparisons were made to previously reported pseudovirus neutralising antibody measurements. Findings A total of 157/729 (21.5%) participants developed positive SARS-CoV-2 serology by one or other assay, of whom 31.0% were asymptomatic and there were no deaths. Peak Euroimmun anti-S1 and Roche anti-NP measurements correlated (r=0.57, p<0.0001) but only anti S1 measurements correlated with near contemporary pseudovirus neutralising antibody titres (measured at 16-18 weeks, r=0.57, p<0.0001). By 21 weeks of follow-up, 31/143 (21.7%) anti S1 and 6/150 (4.0%) anti-NP measurements reverted to negative. Mathematical modelling suggested faster clearance of anti-S1 compared to anti NP (median half-life of 2.5 weeks versus 4.0 weeks), earlier transition to lower levels of antibody production (median of 8 versus 13 weeks), and greater reductions in relative antibody production rate after the transition (median of 35% versus 50%). Interpretation Mild SARS CoV 2 infection is associated with heterogenous serological responses in Euroimmun anti-S1 and Roche anti-NP assays. Anti-S1 responses showed faster rates of clearance, more rapid transition from high to low level production rate and greater reduction in production rate after this transition. The application of individual assays for diagnostic and epidemiological serology requires validation in time series analysis.
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