SARS-CoV-2 seroprevalence among patients with severe mental illness: A cross-sectional study.

Patients with severe mental illness (SMI) i.e. schizophrenia, schizoaffective disorder, and bipolar disorder are at increased risk of severe outcomes if infected with coronavirus disease 2019 (COVID-19). Whether patients with SMI are at increased risk of COVID-19 is, however, sparsely investigated. This important issue must be addressed as the current pandemic could have the potential to increase the existing gap in lifetime mortality between this group of patients and the background population. The objective of this study was to determine whether a diagnosis of schizophrenia, schizoaffective disorder, or bipolar disorder is associated with an increased risk of COVID-19. A cross-sectional study was performed between January 18th and February 25th, 2021. Of 7071 eligible patients with schizophrenia, schizoaffective disorder, or bipolar disorder, 1355 patients from seven psychiatric centres in the Capital Region of Denmark were screened for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies. A total of 1258 unvaccinated patients were included in the analysis. The mean age was 40.5 years (SD 14.6), 54.3% were female. Fifty-nine of the 1258 participants had a positive SARS-CoV-2 antibody test, corresponding to a adjusted seroprevalence of 4.96% (95% CI 3.87-6.35). No significant difference in SARS-CoV-2-risk was found between female and male participants (RR = 1.32; 95% CI 0.79-2.20; p = .290). No significant differences in seroprevalences between schizophrenia and bipolar disease were found (RR = 1.12; 95% CI 0.67-1.87; p = .667). Seroprevalence among 6088 unvaccinated blood donors from the same region and period was 12.24% (95% CI 11.41-13.11). SARS-CoV-2 seroprevalence among included patients with SMI was significantly lower than among blood donors (RR = 0.41; 95% CI 0.31-0.52; p < .001). Differences in seroprevalences remained significant when adjusting for gender and age, except for those aged 60 years or above. The study is registered at ClinicalTrails.gov (NCT04775407). https://clinicaltrials.gov/ct2/show/NCT04775407?term=NCT04775407&draw=2&rank=1.

Epidemiological characterisation of the first 785 SARS-CoV-2 Omicron variant cases in Denmark, December 2021.

By 9 December 2021, 785 SARS-CoV-2 Omicron variant cases have been identified in Denmark. Most cases were fully (76%) or booster-vaccinated (7.1%); 34 (4.3%) had a previous SARS-CoV-2 infection. The majority of cases with available information reported symptoms (509/666; 76%) and most were infected in Denmark (588/644; 91%). One in five cases cannot be linked to previous cases, indicating widespread community transmission. Nine cases have been hospitalised, one required intensive care and no deaths have been registered.

Quantifying SARS-CoV-2 nucleocapsid antigen in oropharyngeal swabs using single molecule array technology.

This study aimed to develop a highly sensitive SARS-CoV-2 nucleocapsid antigen assay using the single molecule array (Simoa) technology and compare it with real time RT-PCR as used in routine clinical practice with the ambition to achieve a comparative technical and clinical sensitivity. Samples were available from 148 SARS-CoV-2 real time RT-PCR positive and 73 SARS-CoV-2 real time RT-PCR negative oropharyngeal swabs. For determination of technical sensitivity SARS-CoV-2 virus culture material was used. The samples were treated with lysis buffer and analyzed using both an in-house and a pre-commercial SARS-CoV-2 nucleocapsid antigen assay on Simoa. Both nucleocapsid antigen assays have a technical sensitivity corresponding to around 100 SARS-CoV-2 RNA molecules/mL. Using a cut-off at 0.1 pg/mL the pre-commercial SARS-CoV-2 nucleocapsid antigen assay had a sensitivity of 96% (95% CI 91.4-98.5%) and specificity of 100% (95% CI 95.1-100%). In comparison the in-house nucleocapsid antigen assay had sensitivity of 95% (95% CI 89.3-98.1%) and a specificity of 100% (95% CI 95.1-100%) using a cut-off at 0.01 pg/mL. The two SARS-CoV-2 nucleocapsid antigen assays correlated with r = 0.91 (P < 0.0001). The in-house and the pre-commercial SARS-CoV-2 nucleocapsid antigen assay demonstrated technical and clinical sensitivity comparable to real-time RT-PCR methods for identifying SARS-CoV-2 infected patients and thus can be used clinically as well as serve as a reference method for antigen Point of Care Testing.

Daily monitoring of viral load measured as SARS-CoV-2 antigen and RNA in blood, IL-6, CRP and complement C3d predicts outcome in patients hospitalized with COVID-19.

OBJECTIVES: We hypothesized that the amount of antigen produced in the body during a COVID-19 infection might differ between patients, and that maximum concentrations would predict the degree of both inflammation and outcome for patients. METHODS: Eighty-four hospitalized and SARS-CoV-2 PCR swab-positive patients, were followed with blood sampling every day until discharge or death. A total of 444 serial EDTA plasma samples were analyzed for a range of biomarkers: SARS-CoV-2 nuclear antigen and RNA concentration, complement activation as well as several inflammatory markers, and KL-6 as a lung marker. The patients were divided into outcome groups depending on need of respiratory support and death/survival. RESULTS: Circulating SARS-CoV-2 nuclear antigen levels were above the detection limit in blood in 65 out of 84 COVID-19 PCR swab-positive patients on day one of hospitalization, as was viral RNA in plasma in 30 out of 84. In all patients, complete antigen clearance was observed within 24 days. There were definite statistically significant differences between the groups depending on their biomarkers, showing that the concentrations of virus RNA and antigen were correlated to the inflammatory biomarker levels, respiratory treatment and death. CONCLUSIONS: Viral antigen is cleared in parallel with the virus RNA levels. The levels of antigens and SARS-CoV-2 RNA in the blood correlates with the level of IL-6, inflammation, respiratory failure and death. We propose that the antigens levels together with RNA in blood can be used to predict the severity of disease, outcome, and the clearance of the virus from the body.