ABSTRACT
Background: Monitoring antibody response following SARS-CoV-2 vaccination is strategic, and neutralizing antibodies represent the gold standard. The neutralizing response to Beta and Omicron VOCs was evaluated versus the gold standard by a new commercial automated assay. Methods: Serum samples from 100 healthcare workers from the Fondazione Policlinico Universitario Campus Biomedico and the Pescara Hospital were collected. IgG levels were determined by chemiluminescent immunoassay (Abbott Laboratories, Wiesbaden, Germany) and serum neutralization assay as the gold standard. Moreover, a new commercial immunoassay, the PETIA test Nab (SGM, Rome, Italy), was used for neutralization evaluation. Statistical analysis was performed with R software, version 3.6.0. Results: Anti-SARS-CoV-2 IgG titers decayed during the first ninety days after the vaccine second dose. The following booster dose significantly (p < 0.001) increased IgG levels. A correlation between IgG expression and neutralizing activity modulation was found with a significant increase after the second and the third booster dose (p < 0.05. Compared to the Beta variant of the virus, the Omicron VOC was associated with a significantly larger quantity of IgG antibodies needed to achieve the same degree of neutralization. The best Nab test cutoff for high neutralization titer (≥1:80) was set for both Beta and Omicron variants. Conclusion: This study correlates vaccine-induced IgG expression and neutralizing activity using a new PETIA assay, suggesting its usefulness for SARS-CoV2 infection management.
ABSTRACT
BACKGROUND: Monitoring antibody response following SARS-CoV-2 vaccination is strategic, and neutralizing antibodies represent the gold standard. The neutralizing response to Beta and Omicron VOCs was evaluated versus the gold standard by a new commercial automated assay. METHODS: Serum samples from 100 healthcare workers from the Fondazione Policlinico Universitario Campus Biomedico and the Pescara Hospital were collected. IgG levels were determined by chemiluminescent immunoassay (Abbott Laboratories, Wiesbaden, Germany) and serum neutralization assay as the gold standard. Moreover, a new commercial immunoassay, the PETIA test Nab (SGM, Rome, Italy), was used for neutralization evaluation. Statistical analysis was performed with R software, version 3.6.0. RESULTS: Anti-SARS-CoV-2 IgG titers decayed during the first ninety days after the vaccine second dose. The following booster dose significantly (p < 0.001) increased IgG levels. A correlation between IgG expression and neutralizing activity modulation was found with a significant increase after the second and the third booster dose (p < 0.05. Compared to the Beta variant of the virus, the Omicron VOC was associated with a significantly larger quantity of IgG antibodies needed to achieve the same degree of neutralization. The best Nab test cutoff for high neutralization titer (≥1:80) was set for both Beta and Omicron variants. CONCLUSION: This study correlates vaccine-induced IgG expression and neutralizing activity using a new PETIA assay, suggesting its usefulness for SARS-CoV2 infection management.
ABSTRACT
Introduction COVID-19 (Coronavirus Disease 19) has rapidly spread all around the world. Vaccination represents one of the most promising counter-pandemic measures. There is still little specific evidence in literature on how to safely and effectively program access and flow through specific healthcare settings to avoid overcrowding in order to prevent SARS-CoV-2 transmission. Literature regarding appointment scheduling in healthcare is vast. Unpunctuality however, especially when targeting healthcare workers during working hours, is always possible. Therefore, when determining how many subjects to book, using a linear method assuming perfect adhesion to scheduled time could lead to organizational problems. Methods This study proposes a “Queuing theory” based approach. A COVID-19 vaccination site targeting healthcare workers based in a teaching hospital in Rome was studied to determine real-life arrival rate variability. Three simulations using Queueing theory were performed. Results Queueing theory application reduced subjects queueing over maximum safety requirements by 112 in a real-life based vaccination setting, by 483 in a double-sized setting and by 750 in a mass vaccination model compared with a linear approach. In the 3 settings, respectively, the percentage of station's time utilization was 98.6, 99.4 and 99.8%, while the average waiting time was 27.2, 33.84, and 33.84 min. Conclusions Queueing theory has already been applied in healthcare. This study, in line with recent literature developments, proposes the adoption of a Queueing theory base approach to vaccination sites modeling, during the COVID-19 pandemic, as this tool enables to quantify ahead of time the outcome of organizational choices on both safety and performance of vaccination sites.