Cellular and humoral immune response to a third dose of BNT162b2 COVID-19 vaccine - a prospective observational study (preprint)

Background Since the introduction of various vaccines against SARS-CoV-2 at the end of 2020, rates of infection have continued to climb worldwide. This led to the establishment of a third dose vaccination in several countries, known as a booster. To date, there has been little real-world data about the immunological effect of this strategy. Methods We compared the humoral- and cellular immune response before and after the third dose of BioNTech/Pfizer vaccine BNT162b2, following different prime-boost regimes. Humoral immunity was assessed by determining anti-SARS-CoV-2 binding antibodies using a standardized quantitative assay. In addition, neutralizing antibodies were measured using a commercial surrogate ELISA-assay. Interferon-gamma release was measured after stimulating blood-cells with SARS-CoV-2 specific peptides using a commercial assay to evaluate the cellular immune response. Results The median antibody level increased significantly after the third dose to 2663.1 BAU/ml vs. 101.4 BAU/ml (p < 0.001) before administration of the boosting dose. This was also detected for neutralizing antibodies with a binding inhibition of 99.68% {+/-} 0.36% vs. 69.06% {+/-} 19.88% after the second dose (p < 0.001). 96.3% of the participants showed a detectable T-cell-response after the third dose with a mean interferon-gamma level of 2207.07 mIU/ml {+/-} 1905 mIU/ml. Conclusion This study detected a BMI-dependent increase after the third dose of BNT162b2 following different vaccination protocols, whereas all participants showed a significant increase of their immune response. This, in combination with the limited post-vaccination-symptoms underlines the potential beneficial effect of a BNT162b2-boosting dose.

Short-term drop in antibody titer after the third dose of SARS-CoV-2 BNT162b2 vaccine in adults (preprint)

Little is known about the longevity of antibodies after a third dose of BNT162b2 (BioNTech/Pfizer). Therefore, the serum antibody levels were evaluated after the third dose of BNT162b2 which dropped significantly within 11 weeks from 4155.59 {+/-} 2373.65 BAU/ml to 2389.10 {+/-} 1433.90 BAU/ml, p-value <0.001 but remained higher than after the second dose. These data underline the positive effect of third dose of BNT162b2 but shows a rapid and significant drop of antibodies within a short span of time.

Persistence of immune response in health care workers after two doses BNT162b2 in a longitudinal observational study (preprint)

Background The mRNA-based vaccine BNT162b2 of BioNTech/Pfizer has shown high efficacy against SARS-CoV-2 infection and a severe course of the COVID-19 disease. However, little is known about the long-term durability of the induced immune response resulting from the vaccination. Methods In a longitudinal observational study in employees at a German hospital we compared the humoral and cellular immune response in 184 participants after two doses of the BioNTech/Pfizer vaccine (BNT162b2) with a mid-term follow-up after 9 months. Anti-SARS-CoV-2 binding antibodies were determined using both a quantitative and a semi-quantitative assay. For a qualitative assessment of the humoral immune response, we additionally measured neutralizing antibodies. Cellular immune response was evaluated by measuring Interferon-gamma release after stimulating blood-cells with SARS-CoV-2 specific peptides using a commercial assay. Results In the first analysis, a 100% humoral response rate was described after two doses of BNT162b2 vaccine with a mean antibody ratio of 8.01 ± 1.00. 9 months after the second dose of BNT162b2, serological testing showed a significant decreased mean antibody ratio of 3.84 ± 1.69 (p < 0.001). Neutralizing antibodies were still detectable in 96% of all participants, showing an average binding inhibition value of 68.20% ± 18.87%. Older age, (p < 0.001) and obesity (p = 0.01) had a negative effect on the antibody persistence. SARS-CoV-2 specific cellular immune response was proven in 75% of individuals (mean IFN-gamma release: 579.68 mlU/ml ± 705.56 mlU/ml). Conclusion Our data shows a declining immune response 9 months after the second dose of BNT162b2, supporting the potentially beneficial effect of booster vaccinations, the negative effect of obesity and age stresses the need of booster doses especially in these groups.

SARS-CoV-2-antibody response in health care workers after vaccination or natural infection in a longitudinal observational study (preprint)

Background Following a year of development, several vaccines have been approved to contain the global COVID-19 pandemic. Real world comparative data on immune response following vaccination or natural infection are rare. Methods We conducted a longitudinal observational study in employees at a secondary care hospital affected by the COVID-19 pandemic. Comparisons were made about the presence of anti-SARS-CoV-2 immunglobulin G (IgG) antibody ratio after natural infection, or vaccination with one or two doses of BioNTech/Pfizer (BNT162b2), or one dose of AstraZenca (Vaxzevria) vaccine. Results We found a 100% humoral response rate in participants after 2 doses of BNT162b2 vaccine. The antibody ratio in participants with one dose BNT162b2 and Vaxzevria did not differ significantly to those with previous PCR-confirmed infection, whereas this was significantly lower in comparison to two doses of BioNTech/Pfizer. We could not identify a correlation with previous comorbidities, obesity or age within this study. Smoking showed a negative effect on the antibody response (p=0.006) Conclusion Our data provide an overview about humoral immune response after natural SARS-CoV-2 infection or following vaccination, and supports the usage of booster vaccinations, especially in patients after a natural SARS-CoV-2 infection.

Half year longitudinal seroprevalence of SARS-CoV-2-antibodies and rule compliance in German hospital employees (preprint)

Introduction COVID-19, caused by SARS-CoV-2, is an occupational health risk especially for healthcare employees. This study was designed to determine the longitudinal seroprevalence of specific immunglobolin-G (IgG)-antibodies in employees in a hospital setting. Methods All employees including healthcare and non-healthcare workers in a secondary care hospital were invited to participate in this single-center study. After an initial screening, a 6 months follow-up was done which included serological examination for SARS-CoV-2-IgG-antibodies and a questionnaire for self-reported symptoms, self-perception and thoughts about the local and national hygiene and pandemic plans. Results The seroprevalence of SARS-CoV-2-IgG-antibodies was 0.74% among 406 hospital employees (95% confidence interval) (0.75% in healthcare workers, 0.72% in non-healthcare workers), initially recruited in April 2020, in their follow-up blood specimen in October 2020. In this study, 30.54% of the participants reported using the official German corona mobile application and the majority were content with the local and national rules in relation to Coronavirus restrictions. Discussion At the 6 months follow-up, the 0.74% seroprevalence was below the reported seroprevalence of 1.35% in the general German population. The prevalence in healthcare workers in direct patient care compared with those without direct patient contact did not differ significantly.

Changing case fatality risk for COVID-19 over time in selected European countries (preprint)

Objectives To illustrate the development of the case fatality risk (CFR) for COVID-19 over time using different assumptions for calculating the CFR. Design Observational study. Setting Selected European countries, 28 January to October 29 2020. Participants Laboratory-confirmed COVID-19 cases and deaths due to COVID-19 Main outcome measure case fatality risk (CFR) Results We show that the CFR has considerably decreased over time. This seems to be driven not only by increased testing but also by a reduced CFR among cases older than 60 years. Our data also confirm a significantly higher fatality risk for men than for women. The decline in the CFR is even more pronounced when only cases and deaths occurring in a specified time window are considered. This alternative estimation method has the advantage that early data where the bias due to the incomplete ascertainment of cases was arguably largest do not affect CFR estimates later on. We find similar results for other European countries. Conclusion CFR estimates vary considerably depending on the underlying assumptions concerning their calculation. Reliable CFR estimates should not be based on cumulative numbers from the beginning of the pandemic but rather be based on more recent data only.

The Role of Age Distribution, Time Lag Between Reporting and Death and Healthcare System Capacity in Case Fatality Estimates of COVID-19 (preprint)

Background: European countries report large differences in coronavirus disease (COVID-19) case fatality risk (CFR). CFR estimates depend on demographic characteristics of the cases, time lags between reporting of infections and deaths and infrastructural characteristics, such as healthcare and surveillance capacities. Methods: We used publicly available data from official reports of the national health authorities of Germany, Italy, France, and Spain on COVID-19. These include age-specific numbers of cases and deaths for different dates, which we used to compute age-standardized CFR ratios using a standard European population for standardization. Moreover, we investigated the impact of different potential time lags on the estimation of the CFR using data published by the European Centre for Disease Prevention and Control (ECDC). Finally, we described the association between case fatality and the intensive care bed capacity.Results: We found that age-standardized CFR estimates increased from the beginning of March to mid-May 2020 in all included European countries. In Germany, CFRs are lower than in other countries. However, the differences are much larger when comparing the crude risks rather than the age-adjusted risks. Thus, the different age distribution of the cases account for a major proportion of the reported differences. Case fatality estimates using time lags of 1-10 days converged in all countries over time, however, there is no optimal time lag to assess the CFR during the pandemic. Time lags that provided the most constant estimates and approach best the observed CFR after the pandemic ranged from 5-10 days in different countries and at different time points during the pandemic. For the association between intensive care bed capacity and fatality we found that days with a high need for intensive care beds were positively correlated with daily hospitalization fatality in France, Italy, and Spain, but not in Germany.  Conclusions: Our results highlight that cross-country comparisons of crude CFR estimates can be misleading and should be avoided. However, to adjust for potential sources of bias more disaggregated data and information on surveillance and health care capacities are needed. Filling these gaps and harmonizing data across European countries will facilitate further analysis. 

The role of age distribution, time lag between reporting and death and healthcare system capacity on case fatality estimates of COVID-19 (preprint)

European countries report large differences in coronavirus disease (COVID-19) case fatality risk (CFR). CFR estimates depend on demographic characteristics of the cases, time lags between reporting of infections and deaths and infrastructural characteristics, such as healthcare and surveillance capacities. We discuss the impact of these factors on the CFR estimates for Germany, Italy, France, and Spain for the COVID-19 pandemic from early March to mid-April, 2020. We found that, first, a large proportion of the difference in CFRs can be attributed to different age structures of the cases. Second, lags of 5-10 days between day of case report and death should be used, since these provide the most constant estimates. Third, for France, Italy, and Spain, intensive care beds occupied by COVID-19 patients were positively associated with fatality risks of hospitalized cases. Our results highlight that cross-country comparisons of crude CFR estimates can be misleading and should be avoided.