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Journal Article

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


Rorbach,  J.
Rorbach – Mitochondrial Gene Expression, External and Associated Groups, Max Planck Institute for Biology of Ageing, Max Planck Society;

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Dopico, X. C., Hanke, L., Sheward, D. J., Christian, M., Muschiol, S., Grinberg, N. F., et al. (2020). Antibody phenotypes and probabilistic seroprevalence estimates during the emergence of SARS-CoV-2 in Sweden. medRxiv, 2020.07.17.20155937. doi:10.1101/2020.07.17.20155937.

Cite as: https://hdl.handle.net/21.11116/0000-000B-3F3D-C
Serological studies are critical for understanding pathogen-specific immune responses and informing public health measures1,2. Here, we evaluate tandem IgM, IgG and IgA responses in a cohort of individuals PCR+ for SARS-CoV-2 RNA (n=105) representing different categories of disease severity, including mild and asymptomatic infections. All PCR+ individuals surveyed were IgG-positive against the virus spike (S) glycoprotein. Elevated Ab levels were associated with hospitalization, with IgA titers, increased circulating IL-6 and strong neutralizing responses indicative of intensive care status. Additional studies of healthy blood donors (n=1,000) and pregnant women (n=900), sampled weekly during the initial outbreak in Stockholm, Sweden (weeks 14-25, 2020), demonstrated that anti-viral IgG titers differed over 1,000-fold between seroconverters, highlighting the need for careful evaluation of assay cut-offs for individual measurements and accurate estimates of seroprevalence (SP). To provide a solution to this, we developed probabilistic machine learning approaches to assign likelihood of past infection without setting an assay cut-off, allowing for more quantitative individual and population-level Ab measures. Using these tools, that considered responses against both S and RBD, we report SARS-CoV-2 S-specific IgG in 6.8% of blood donors and pregnant women two months after the peak of spring COVID-19 deaths, with the SP curve and country death rate following similar trajectories.Competing Interest StatementThe authors have declared no competing interest.Funding StatementFunding for this work was provided by a Distinguished Professor grant from the Swedish Research Council (agreement 532 2017-00968) and NIH (agreement SUM1A44462-02). CW and NFG are funded by the Wellcome Trust (WT107881) and MRC (MC_UP_1302/5)Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Swedish Ethical Review Authority (registration no. 2020-01807).All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesData generated as part of the study, along with custom code for statistical analyses, is openly available via our GitHub repositories: https://github.com/MurrellGroup/DiscriminativeSeroprevalence/ and https://github.com/chr1swallace/seroprevalence-paper.