[Screening of Mothers in a COVID-19 Low-Prevalence Region: Determination of SARS-CoV-2 Antibodies in 401 Mothers from Rostock by ELISA and Confirmation by Immunofluorescence]

Systematic review of seroprevalence of SARS-CoV-2 antibodies and appraisal of evidence, prior to the widespread introduction of vaccine programmes in the WHO European Region, January-December 2020

OBJECTIVES

Systematic review of SARS-CoV-2 seroprevalence studies undertaken in the WHO European Region to measure pre-existing and cumulative seropositivity prior to the roll out of vaccination programmes.

DESIGN

A systematic review of the literature.

DATA SOURCES

We searched MEDLINE, EMBASE and the preprint servers MedRxiv and BioRxiv in the WHO 'COVID-19 Global literature on coronavirus disease' database using a predefined search strategy. Articles were supplemented with unpublished WHO-supported Unity-aligned seroprevalence studies and other studies reported directly to WHO Regional Office for Europe and European Centre for Disease Prevention and Control.

ELIGIBILITY CRITERIA

Studies published before the widespread implementation of COVID-19 vaccination programmes in January 2021 among the general population and blood donors, at national and regional levels.

DATA EXTRACTION AND SYNTHESIS

At least two independent researchers extracted the eligible studies; a third researcher resolved any disagreements. Study risk of bias was assessed using a quality scoring system based on sample size, sampling and testing methodologies.

RESULTS

In total, 111 studies from 26 countries published or conducted between 1 January 2020 and 31 December 2020 across the WHO European Region were included. A significant heterogeneity in implementation was noted across the studies, with a paucity of studies from the east of the Region. Sixty-four (58%) studies were assessed to be of medium to high risk of bias. Overall, SARS-CoV-2 seropositivity prior to widespread community circulation was very low. National seroprevalence estimates after circulation started ranged from 0% to 51.3% (median 2.2% (IQR 0.7-5.2%); n=124), while subnational estimates ranged from 0% to 52% (median 5.8% (IQR 2.3%-12%); n=101), with the highest estimates in areas following widespread local transmission.

CONCLUSIONS

The low levels of SARS-CoV-2 antibody in most populations prior to the start of vaccine programmes underlines the critical importance of targeted vaccination of priority groups at risk of severe disease, while maintaining reduced levels of transmission to minimise population morbidity and mortality.

A Multiple-Target Simultaneous Detection Method for Immunosorbent Assay and Immunospot Assay

Enzyme-linked immunosorbent assay (ELISA) is one of the most common methods in biological studies, and enzyme-linked immunospot (ELISpot) is a method to measure specific cell numbers by detecting protein secretion at a single-cell level. However, these two current methods can only detect one signal at one time and the sensitivity is not high enough to test low-concentration samples, which are major shortcomings in systematically analyzing the samples of interest. Herein, we demonstrated fluorescence-based oligo-linked immunosorbent assay (FOLISA) and fluorescence-based oligo-linked immunospot (FOLISPOT), which utilized DNA-barcoded antibodies to provide a highly multiplexed method with signal amplification. Signal amplification and simultaneous multiple-target detection were achieved by DNA complementary pairing and modular orthogonal DNA concatemers. By comparing FOLISA with traditional ELISA and comparing FOLISPOT with traditional ELISPOT, we found that the detection sensitivities of FOLISA and FOLISPOT are much higher than those of traditional ELISA and ELISPOT. The detection limit of ELISA is around 3 pg/mL, and the detection limit of FOLISA is below 0.06 pg/mL. FOLISPOT can detect more spots than ELISPOT and can detect targets that are undetectable for ELISPOT. Furthermore, FOLISA and FOLISPOT allowed sequential detection of multiple targets by using a single dye or multiple dyes in one round and sequential detection in multiple rounds. Thus, FOLISA and FOLISPOT enabled simultaneous detection of a large number of targets, significantly improved the detection sensitivity, and overcame the shortcomings of ELISA and ELISPOT. Overall, FOLISA and FOLISPOT presented effective and general platforms for rapid and multiplexed detection of antigens or antibodies with high sensitivity, either in laboratory tests or potentially in clinic tests.

Fcγ-Receptor-Based Enzyme-Linked Immunosorbent Assays for Sensitive, Specific, and Persistent Detection of Anti-SARS-CoV-2 Nucleocapsid Protein IgG Antibodies in Human Sera

Sensitive and specific serological tests are mandatory for epidemiological studies evaluating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prevalence as well as coronavirus disease 2019 (COVID-19) morbidity and mortality rates. The accuracy of results is challenged by antibody waning after convalescence and by cross-reactivity induced by previous infections with other pathogens. By employing a patented platform technology based on capturing antigen-antibody complexes with a solid-phase-bound Fcγ receptor (FcγR) and truncated nucleocapsid protein as the antigen, two SARS-CoV-2 IgG enzyme-linked immunosorbent assays (ELISAs), featuring different serum and antigen dilutions, were developed. Validation was performed using a serum panel comprising 213 longitudinal samples from 35 COVID-19 patients and a negative-control panel consisting of 790 pre-COVID-19 samples from different regions of the world. While both assays show similar diagnostic sensitivities in the early convalescent phase, ELISA 2 (featuring a higher serum concentration) enables SARS-CoV-2 IgG antibody detection for a significantly longer time postinfection (≥15 months). Correspondingly, analytical sensitivity referenced to indirect immunofluorescence testing (IIFT) is significantly higher for ELISA 2 in samples with a titer of ≤1:640; for high-titer samples, a prozone effect is observed for ELISA 2. The specificities of both ELISAs were excellent not only for pre-COVID-19 serum samples from Europe, Asia, and South America but also for several challenging African sample panels. The SARS-CoV-2 IgG FcγR ELISAs, methodically combining antigen-antibody binding in solution and isotype-specific detection of immune complexes, are valuable tools for seroprevalence studies requiring the (long-term) detection of anti-SARS-CoV-2 IgG antibodies in populations with a challenging immunological background and/or in which spike-protein-based vaccine programs have been rolled out.

Bayes Lines Tool (BLT): a SQL-script for analyzing diagnostic test results with an application to SARS-CoV-2-testing

The performance of diagnostic tests crucially depends on the disease prevalence, test sensitivity, and test specificity. However, these quantities are often not well known when tests are performed outside defined routine lab procedures which make the rating of the test results somewhat problematic. A current example is the mass testing taking place within the context of the world-wide SARS-CoV-2 crisis. Here, for the first time in history, laboratory test results have a dramatic impact on political decisions. Therefore, transparent, comprehensible, and reliable data is mandatory. It is in the nature of wet lab tests that their quality and outcome are influenced by multiple factors reducing their performance by handling procedures, underlying test protocols, and analytical reagents. These limitations in sensitivity and specificity have to be taken into account when calculating the real test results. As a resolution method, we have developed a Bayesian calculator, the Bayes Lines Tool (BLT), for analyzing disease prevalence, test sensitivity, test specificity, and, therefore, true positive, false positive, true negative, and false negative numbers from official test outcome reports. The calculator performs a simple SQL (Structured Query Language) query and can easily be implemented on any system supporting SQL. We provide an example of influenza test results from California, USA, as well as two examples of SARS-CoV-2 test results from official government reports from The Netherlands and Germany-Bavaria, to illustrate the possible parameter space of prevalence, sensitivity, and specificity consistent with the observed data. Finally, we discuss this tool's multiple applications, including its putative importance for informing policy decisions.

Bayes Lines Tool (BLT): a SQL-script for analyzing diagnostic test results with an application to SARS-CoV-2-testing

The performance of diagnostic tests crucially depends on the disease prevalence, test sensitivity, and test specificity. However, these quantities are often not well known when tests are performed outside defined routine lab procedures which make the rating of the test results somewhat problematic. A current example is the mass testing taking place within the context of the world-wide SARS-CoV-2 crisis. Here, for the first time in history, laboratory test results have a dramatic impact on political decisions. Therefore, transparent, comprehensible, and reliable data is mandatory. It is in the nature of wet lab tests that their quality and outcome are influenced by multiple factors reducing their performance by handling procedures, underlying test protocols, and analytical reagents. These limitations in sensitivity and specificity have to be taken into account when calculating the real test results. As a resolution method, we have developed a Bayesian calculator, the Bayes Lines Tool (BLT), for analyzing disease prevalence, test sensitivity, test specificity, and, therefore, true positive, false positive, true negative, and false negative numbers from official test outcome reports. The calculator performs a simple SQL (Structured Query Language) query and can easily be implemented on any system supporting SQL. We provide an example of influenza test results from California, USA, as well as two examples of SARS-CoV-2 test results from official government reports from The Netherlands and Germany-Bavaria, to illustrate the possible parameter space of prevalence, sensitivity, and specificity consistent with the observed data. Finally, we discuss this tool's multiple applications, including its putative importance for informing policy decisions.

Bayes Lines Tool (BLT): a SQL-script for analyzing diagnostic test results with an application to SARS-CoV-2-testing

The performance of diagnostic tests crucially depends on the disease prevalence, test sensitivity, and test specificity. However, these quantities are often not well known when tests are performed outside defined routine lab procedures which make the rating of the test results somewhat problematic. A current example is the mass testing taking place within the context of the world-wide SARS-CoV-2 crisis. Here, for the first time in history, laboratory test results have a dramatic impact on political decisions. Therefore, transparent, comprehensible, and reliable data is mandatory. It is in the nature of wet lab tests that their quality and outcome are influenced by multiple factors reducing their performance by handling procedures, underlying test protocols, and analytical reagents. These limitations in sensitivity and specificity have to be taken into account when calculating the real test results. As a resolution method, we have developed a Bayesian calculator, the Bayes Lines Tool (BLT), for analyzing disease prevalence, test sensitivity, test specificity, and, therefore, true positive, false positive, true negative, and false negative numbers from official test outcome reports. The calculator performs a simple SQL (Structured Query Language) query and can easily be implemented on any system supporting SQL. We provide an example of influenza test results from California, USA, as well as two examples of SARS-CoV-2 test results from official government reports from The Netherlands and Germany-Bavaria, to illustrate the possible parameter space of prevalence, sensitivity, and specificity consistent with the observed data. Finally, we discuss this tool's multiple applications, including its putative importance for informing policy decisions.

Transmission of SARS-CoV-2 through breast milk and breastfeeding: a living systematic review

The pandemic of coronavirus disease 2019 (COVID-19) is caused by infection with a novel coronavirus strain, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). At present, there is limited information on potential transmission of the infection from mother to child, particularly through breast milk and breastfeeding. Here, we provide a living systematic review to capture information that might necessitate changes in the guidance on breast milk and breastfeeding given the uncertainty in this area. Our search retrieved 19,414 total records; 605 were considered for full-text eligibility and no ongoing trials were identified. Our review includes 340 records, 37 with breast milk samples and 303 without. The 37 articles with analyzed breast milk samples reported on 77 mothers who were breastfeeding their children; among them, 19 of 77 children were confirmed COVID-19 cases based on RT-PCR assays, including 14 neonates and five older infants. Nine of the 68 analyzed breast milk samples from mothers with COVID-19 were positive for SARS-CoV-2 RNA; of the exposed infants, four were positive and two were negative for COVID-19. Currently, there is no evidence of SARS-CoV-2 transmission through breast milk. Studies are needed with longer follow-up periods that collect data on infant feeding practices and on viral presence in breast milk.

[COVID-19: epidemiology and clinical facts]

Until July 31, 2020, about 17.6 million SARS-CoV‑2 infections and 680,000 deaths from COVID-19 were reported. SARS-CoV‑2 is most likely transmitted by droplets and probably by aerosols. Patients become infectious 2-3 days before the onset of symptoms, and persons with asymptomatic infections are also infectious. COVID-19 affects the upper respiratory tract, lungs (pneumonia, acute respiratory distress syndrome [ARDS]), heart, liver, gastrointestinal tract, and other organs. SARS-CoV‑2 uses ACE2 a receptor to enter host cells. Vasculitis, endothelial damage, thromboembolic events and organ failure are accompanied by a massive cytokine response. Elderly people and those with pre-existing diseases are particularly vulnerable. An efficient antiviral therapy is not yet available. Severely ill patients may benefit from dexamethasone and early treatment of complications. Candidate vaccines are currently being tested in clinical studies.