Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic in 2020. Testing is crucial for mitigating public health and economic effects. Serology is considered key to population-level surveillance and potentially individual-level risk assessment. However, immunoassay performance has not been compared on large, identical sample sets. We aimed to investigate the performance of four high-throughput commercial SARS-CoV-2 antibody immunoassays and a novel 384-well ELISA. Methods We did a head-to-head assessment of SARS-CoV-2 IgG assay (Abbott, Chicago, IL, USA), LIAISON SARS-CoV-2 S1/S2 IgG assay (DiaSorin, Saluggia, Italy), Elecsys Anti-SARS-CoV-2 assay (Roche, Basel, Switzerland), SARS-CoV-2 Total assay (Siemens, Munich, Germany), and a novel 384-well ELISA (the Oxford immunoassay). We derived sensitivity and specificity from 976 pre-pandemic blood samples (collected between Sept 4, 2014, and Oct 4, 2016) and 536 blood samples from patients with laboratory-confirmed SARS-CoV-2 infection, collected at least 20 days post symptom onset (collected between Feb 1, 2020, and May 31, 2020). Receiver operating characteristic (ROC) curves were used to assess assay thresholds. Findings At the manufacturers' thresholds, for the Abbott assay sensitivity was 92·7% (95% CI 90·2–94·8) and specificity was 99·9% (99·4–100%); for the DiaSorin assay sensitivity was 95·0% (92·8–96·7) and specificity was 98·7% (97·7–99·3); for the Oxford immunoassay sensitivity was 99·1% (97·8–99·7) and specificity was 99·0% (98·1–99·5); for the Roche assay sensitivity was 97·2% (95·4–98·4) and specificity was 99·8% (99·3–100); and for the Siemens assay sensitivity was 98·1% (96·6–99·1) and specificity was 99·9% (99·4–100%). All assays achieved a sensitivity of at least 98% with thresholds optimised to achieve a specificity of at least 98% on samples taken 30 days or more post symptom onset. Interpretation Four commercial, widely available assays and a scalable 384-well ELISA can be used for SARS-CoV-2 serological testing to achieve sensitivity and specificity of at least 98%. The Siemens assay and Oxford immunoassay achieved these metrics without further optimisation. This benchmark study in immunoassay assessment should enable refinements of testing strategies and the best use of serological testing resource to benefit individuals and population health. Funding Public Health England and UK National Institute for Health Research.

Identification of protective T cell responses against SARS-CoV-2 requires distinguishing people infected with SARS-CoV-2 from those with cross-reactive immunity to other coronaviruses. Here we show a range of T cell assays that differentially capture immune function to characterise SARS-CoV-2 responses. Strong ex vivo ELISpot and proliferation responses to multiple antigens (including M, NP and ORF3) are found in 168 PCR-confirmed SARS-CoV-2 infected volunteers, but are rare in 119 uninfected volunteers. Highly exposed seronegative healthcare workers with recent COVID-19-compatible illness show T cell response patterns characteristic of infection. By contrast, >90% of convalescent or unexposed people show proliferation and cellular lactate responses to spike subunits S1/S2, indicating pre-existing cross-reactive T cell populations. The detection of T cell responses to SARS-CoV-2 is therefore critically dependent on assay and antigen selection. Memory responses to specific non-spike proteins provide a method to distinguish recent infection from pre-existing immunity in exposed populations.

The trajectories of acquired immunity to severe acute respiratory syndrome coronavirus 2 infection are not fully understood. We present a detailed longitudinal cohort study of UK healthcare workers prior to vaccination, presenting April-June 2020 with asymptomatic or symptomatic infection. Here we show a highly variable range of responses, some of which (T cell interferon-gamma ELISpot, N-specific antibody) wane over time, while others (spike-specific antibody, B cell memory ELISpot) are stable. We use integrative analysis and a machine-learning approach (SIMON - Sequential Iterative Modeling OverNight) to explore this heterogeneity. We identify a subgroup of participants with higher antibody responses and interferon-gamma ELISpot T cell responses, and a robust trajectory for longer term immunity associates with higher levels of neutralising antibodies against the infecting (Victoria) strain and also against variants B.1.1.7 (alpha) and B.1.351 (beta). These variable trajectories following early priming may define subsequent protection from severe disease from novel variants.

Over the last few decades, computer-aided diagnosis systems have become a part of clinical practice. They have the potential to assist clinicians in daily diagnostic tasks. The image processing techniques are fast, repeatable, and robust, which helps physicians to detect, classify, segment, and measure various structures. The recent rapid development of computer methods for high-frequency ultrasound image analysis opens up new diagnostic paths in dermatology, allergology, cosmetology, and aesthetic medicine. This paper, being the first in this area, presents a research overview of high-frequency ultrasound image processing techniques, which have the potential to be a part of computer-aided diagnosis systems. The reviewed methods are categorized concerning the application, utilized ultrasound device, and image data-processing type. We present the bridge between diagnostic needs and already developed solutions and discuss their limitations and future directions in high-frequency ultrasound image analysis. A search was conducted of the technical literature from 2005 to September 2022, and in total, 31 studies describing image processing methods were reviewed. The quantitative and qualitative analysis included 39 algorithms, which were selected as the most effective in this field. They were completed by 20 medical papers and define the needs and opportunities for high-frequency ultrasound application and CAD development.