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X. C. Dopico, L. Hanke, D. Sheward, M. Christian, Sandra, Muschiol, N. Grinberg, M. Ádori, L. P. Vidakovics, Changil Kim, S. Khoenkhoen, P. Pushparaj, Ainhoa Moliner Morro, M. Mandolesi, M. Forsell, J. Coquet, M. Corcoran, J. Rorbach, S. Aleman, G. Bogdanovic, G. McInerney, T. Allander, C. Wallace, Ben, Murrell, J. Albert, G. K. Hedestam
2 2020.

Antibody phenotypes and probabilistic seroprevalence estimates during the emergence 1 of SARS-CoV-2 in Sweden 2

Serological studies are critical for understanding pathogen-specific immune responses and 30 informing public health measures 1,2 . Here, we evaluate tandem IgM, IgG and IgA responses in 31 a cohort of individuals PCR+ for SARS-CoV-2 RNA ( n= 105) representing different categories 32 of disease severity, including mild and asymptomatic infections. All PCR+ individuals 33 surveyed were IgG-positive against the virus spike (S) glycoprotein. Elevated Ab levels were 34 associated with hospitalization, with IgA titers, increased circulating IL-6 and strong 35 neutralizing responses indicative of intensive care status. Additional studies of healthy blood 36 donors ( n =1,000) and pregnant women ( n =900), sampled weekly during the initial outbreak in 37 Stockholm, Sweden (weeks 14-25, 2020), demonstrated that anti-viral IgG titers differed over 38 1,000-fold between seroconverters, highlighting the need for careful evaluation of assay cut- 39 offs for individual measurements and accurate estimates of seroprevalence (SP). To provide a 40 solution to this, we developed probabilistic machine learning approaches to assign likelihood 41 of past infection without setting an assay cut-off, allowing for more quantitative individual and 42 population-level Ab measures. Using these tools, that considered responses against both S and 43 RBD, we report SARS-CoV-2 S-specific IgG in 6.8% of blood donors and pregnant women 44 two months after the peak of spring COVID-19 deaths, with the SP curve and country death 45 rate following similar trajectories. 46

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