Estimating SARS-CoV-2 Seroprevalence from Spent Blood Samples, January-March 2021

Background. Measuring SARS-CoV-2 antibody prevalence in spent samples at serial time points can determine seropositivity in a diverse pool of individuals to inform understanding of trends as vaccinations are implemented. Methods. Blood samples collected for clinical testing and then discarded ("spent samples") were obtained from the clinical laboratory of a medical center in Atlanta. A convenience sample of spent samples from both inpatients (medical/surgical floors, intensive care, obstetrics) and outpatients (clinics and ambulatory surgery) were collected one day per week from January-March 2021. Samples were matched to clinical data from the electronic medical record. In-house single dilution serological assays for SARSCoV-2 receptor binding domain (RBD) and nucleocapsid (N) antibodies were developed and validated using pre-pandemic and PCR-confirmed COVID-19 patient serum and plasma samples (Figure 1). ELISA optical density (OD) cutoffs for seroconversion were chosen using receiver operating characteristic analysis with areas under the curve for all four assays greater than 0.95 after 14 days post symptom onset. IgG profiles were defined as natural infection (RBD and N positive) or vaccinated (RBD positive, N negative). Single dilution serological assays for SARS-CoV-2 nucleocapsid antibodies were validated using pre-pandemic and PCR-confirmed COVID-19 patient serum and plasma samples. ELISA optical density (OD) cutoffs for seroconversion were chosen using receiver operating characteristic (ROC) analysis with areas under the curve (AUC) for all four assays greater than 0.95 after 14 days post symptom onset. Results. A total of 2406 samples were collected from 2132 unique patients. Median age was 58 years (IQR 40-70), with 766 (36%) ≥ 65 years. The majority were female (1173, 55%), and 1341 (63%) were Black. Median Elixhauser comorbidity index was 5 (IQR 2-9). 210 (9.9%) patients ever had SARS-CoV-2 detected by PCR, and 191 (9.0%) received a COVID-19 vaccine within the health system. Nearly half (1186/2406, 49.3%) of samples were collected from inpatient units, 586 (24.4%) from outpatient labs, 403 (16.8%) from the emergency department, and 231 (9.6%) from infusion centers. Overall, 17.0% had the IgG natural infection profile, while 16.2% had a vaccination profile. Prevalence estimates for IgG due to natural infection ranged from 24.0% in week 2 to 9.7% in week 5, and for IgG due to vaccine from 4.4% in week 2 to 32.0% in week 6 (Table, Figure 2). Conclusion. Estimated SARS-CoV-2 IgG seroprevalence among patients at a medical center from January-March 2021 was 17% by natural infection, and 16% by vaccination. Weekly trends likely reflect community spread and vaccine uptake.

An automated approach to determine antibody endpoint titers for COVID-19 by an enzyme-linked immunosorbent assay.

While a variety of therapeutic options continue to emerge for COVID-19 treatment, convalescent plasma (CP) has been used as a possible treatment option early in the pandemic. One of the most significant challenges with CP therapy, however, both when defining its efficacy and implementing its approach clinically, is accurately and efficiently characterizing an otherwise heterogenous therapeutic treatment. Given current limitations, our goal is to leverage a SARS antibody testing platform with a newly developed automated endpoint titer analysis program to rapidly define SARS-CoV-2 antibody levels in CP donors and hospitalized patients. A newly developed antibody detection platform was used to perform a serial dilution enzyme-linked immunosorbent assay (ELISA) for immunoglobulin (Ig)G, IgM, and IgA SARS-CoV-2 antibodies. Data were then analyzed using commercially available software, GraphPad Prism, or a newly developed program developed in Python called TiterScape, to analyze endpoint titers. Endpoint titer calculations and analysis times were then compared between the two analysis approaches. Serial dilution analysis of SARS-CoV-2 antibody levels revealed a high level of heterogeneity between individuals. Commercial platform analysis required significant time for manual data input and extrapolated endpoint titer values when the last serial dilution was above the endpoint cutoff, occasionally producing erroneously high results. By contrast, TiterScape processed 1008 samples for endpoint titer results in roughly 14 minutes compared with the 8 hours required for the commercial software program analysis. Equally important, results generated by TiterScape and Prism were highly similar, with differences averaging 1.26 ± 0.2 percent (mean ± SD). The pandemic has created unprecedented challenges when seeking to accurately test large numbers of individuals for SARS-CoV-2 antibody levels with a rapid turnaround time. ELISA platforms capable of serial dilution analysis coupled with a highly flexible software interface may provide a useful tool when seeking to define endpoint titers in a high-throughput manner. Immunohematology 2021;37:33-43.While a variety of therapeutic options continue to emerge for COVID-19 treatment, convalescent plasma (CP) has been used as a possible treatment option early in the pandemic. One of the most significant challenges with CP therapy, however, both when defining its efficacy and implementing its approach clinically, is accurately and efficiently characterizing an otherwise heterogenous therapeutic treatment. Given current limitations, our goal is to leverage a SARS antibody testing platform with a newly developed automated endpoint titer analysis program to rapidly define SARS-CoV-2 antibody levels in CP donors and hospitalized patients. A newly developed antibody detection platform was used to perform a serial dilution enzyme-linked immunosorbent assay (ELISA) for immunoglobulin (Ig)G, IgM, and IgA SARS-CoV-2 antibodies. Data were then analyzed using commercially available software, GraphPad Prism, or a newly developed program developed in Python called TiterScape, to analyze endpoint titers. Endpoint titer calculations and analysis times were then compared between the two analysis approaches. Serial dilution analysis of SARS-CoV-2 antibody levels revealed a high level of heterogeneity between individuals. Commercial platform analysis required significant time for manual data input and extrapolated endpoint titer values when the last serial dilution was above the endpoint cutoff, occasionally producing erroneously high results. By contrast, TiterScape processed 1008 samples for endpoint titer results in roughly 14 minutes compared with the 8 hours required for the commercial software program analysis. Equally important, results generated by TiterScape and Prism were highly similar, with differences averaging 1.26 ± 0.2 percent (mean ± SD). The pandemic has created unprecedented challenges when seeking to accurately test large numbers of individuals for SARS-CoV-2 antibody levels with a rapid turnaround time. ELISA platforms capable of serial dilution analysis coupled with a highly flexible software interface may provide a useful tool when seeking to define endpoint titers in a high-throughput manner. Immunohematology 2021;37:33­43.

Serum pooling for rapid expansion of anti-SARS-CoV-2 antibody testing capacity.

OBJECTIVES: Examine possible pooling strategies designed to expand SARS-CoV-2 serological testing capacity. METHODS: Negative pools were assessed to determine optimal optical density (OD) cutoffs, followed by spiking weak or strong positive samples to assess initial assay performance. Samples were then randomly subjected to pool and individual testing approaches. RESULTS: Single positive specimens consistently converted pools of 5, 10, or 20 into positive outcomes. However, weaker IgG-positive samples failed to similarly convert pools of 50 to a positive result. In contrast, a stronger individual positive sample converted all pools tested into positive outcomes. Finally, examination of 150 samples configured into pools of 5, 10, 20 or 50 accurately predicted the presence of positive or negative specimens within each pool. CONCLUSIONS: These results suggest that pooling strategies may allow expansion of serological testing capacity. While limitations exist, such strategies may aid in large-scale epidemiological screening or identification of optimal convalescent plasma donors.