Due to urgency and demand, numerous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoassays are rapidly being developed and placed on the market with limited validation on clinical samples. Thorough validation of serological tests are required to facilitate their use in the accurate diagnosis of SARS-CoV-2 infection, confirmation of molecular results, contact tracing, and epidemiological studies. This study evaluated the sensitivity and specificity of nine commercially available serological tests. These included three enzyme-linked immunosorbent assays (ELISAs) and six point-of-care (POC) lateral flow tests. The assays were validated using serum samples from: i) SARS-CoV-2 PCR-positive patients with a documented first day of disease; ii) archived sera obtained from healthy individuals before the emergence of SARS-CoV-2 in China;iii) sera from patients with acute viral respiratory tract infections caused by other coronaviruses or noncoronaviruses; and iv) sera from patients positive for dengue virus, cytomegalovirus and Epstein Barr virus.The results showed 100% specificity for the Wantai SARS-CoV-2 Total Antibody ELISA, 93% for the Euroimmun IgA ELISA, and 96% for the Euroimmun IgG ELISA with sensitivities of 90%, 90%, and 65%, respectively. The overall performance of the POC tests according to manufacturer were in the rank order of AutoBio Diagnostics > Dynamiker Biotechnology = CTK Biotech > Artron Laboratories > Acro Biotech ≥ Hangzhou Alltest Biotech. Overall, these findings will facilitate selection of serological assays for the detection SARS-CoV-2-specific antibodies towards diagnosis as well as sero-epidemiological and vaccine development studies.

Severe acute respiratory syndrome coronavirus 2 has caused a pandemic in humans. Farmed mink ( Neovison vison ) are also susceptible. In Denmark, this virus has spread rapidly among farmed mink, resulting in some respiratory disease. Full-length virus genome sequencing revealed novel virus variants in mink. These variants subsequently appeared within the local human community.

The Omicron SARS-CoV-2 variant of concern (VOC lineage B.1.1.529), which became dominant in many countries during early 2022, includes several subvariants with strikingly different genetic characteristics. Several countries, including Denmark, have observed the two Omicron subvariants: BA.1 and BA.2. In Denmark the latter has rapidly replaced the former as the dominant subvariant. Based on nationwide Danish data, we estimate the transmission dynamics of BA.1 and BA.2 following the spread of Omicron VOC within Danish households in late December 2021 and early January 2022. Among 8,541 primary household cases, of which 2,122 were BA.2, we identified a total of 5,702 secondary infections among 17,945 potential secondary cases during a 1-7 day follow-up period. The secondary attack rate (SAR) was estimated as 29% and 39% in households infected with Omicron BA.1 and BA.2, respectively. We found BA.2 to be associated with an increased susceptibility of infection for unvaccinated individuals (Odds Ratio (OR) 2.19; 95%-CI 1.58-3.04), fully vaccinated individuals (OR 2.45; 95%-CI 1.77-3.40) and booster-vaccinated individuals (OR 2.99; 95%-CI 2.11-4.24), compared to BA.1. We also found an increased transmissibility from unvaccinated primary cases in BA.2 households when compared to BA.1 households, with an OR of 2.62 (95%-CI 1.96-3.52). The pattern of increased transmissibility in BA.2 households was not observed for fully vaccinated and booster-vaccinated primary cases, where the OR of transmission was below 1 for BA.2 compared to BA.1. We conclude that Omicron BA.2 is inherently substantially more transmissible than BA.1, and that it also possesses immune-evasive properties that further reduce the protective effect of vaccination against infection, but do not increase its transmissibility from vaccinated individuals with breakthrough infections.

We have generated Artificial Neural Networks (ANN) capable of performing sensitive, quantitative predictions of peptide binding to the MHC class I molecule, HLA-A*0204. We have shown that such quantitative ANN are superior to conventional classification ANN, that have been trained to predict binding vs non-binding peptides. Furthermore, quantitative ANN allowed a straightforward application of a 'Query by Committee' (QBC) principle whereby particularly information-rich peptides could be identified and subsequently tested experimentally. Iterative training based on QBC-selected peptides considerably increased the sensitivity without compromising the efficiency of the prediction. This suggests a general, rational and unbiased approach to the development of high quality predictions of epitopes restricted to this and other HLA molecules. Due to their quantitative nature, such predictions will cover a wide range of MHC-binding affinities of immunological interest, and they can be readily integrated with predictions of other events involved in generating immunogenic epitopes. These predictions have the capacity to perform rapid proteome-wide searches for epitopes. Finally, it is an example of an iterative feedback loop whereby advanced, computational bioinformatics optimize experimental strategy, and vice versa.