The relationship between mental health, sleep quality and the immunogenicity of COVID-19 vaccinations.

Sleep modulates the immune response, and sleep loss can reduce vaccine immunogenicity; vice versa, immune responses impact sleep. We aimed to investigate the influence of mental health and sleep quality on the immunogenicity of COVID-19 vaccinations and, conversely, of COVID-19 vaccinations on sleep quality. The prospective CoVacSer study monitored mental health, sleep quality and Anti-SARS-CoV-2-Spike IgG titres in a cohort of 1082 healthcare workers from 29 September 2021 to 19 December 2022. Questionnaires and blood samples were collected before, 14 days, and 3 months after the third COVID-19 vaccination, as well as in 154 participants before and 14 days after the fourth COVID-19 vaccination. Healthcare workers with psychiatric disorders had slightly lower Anti-SARS-CoV-2-Spike IgG levels before the third COVID-19 vaccination. However, this effect was mediated by higher median age and body mass index in this subgroup. Antibody titres following the third and fourth COVID-19 vaccinations ("booster vaccinations") were not significantly different between subgroups with and without psychiatric disorders. Sleep quality did not affect the humoral immunogenicity of the COVID-19 vaccinations. Moreover, the COVID-19 vaccinations did not impact self-reported sleep quality. Our data suggest that in a working population neither mental health nor sleep quality relevantly impact the immunogenicity of COVID-19 vaccinations, and that COVID-19 vaccinations do not cause a sustained deterioration of sleep, suggesting that they are not a precipitating factor for insomnia. The findings from this large-scale real-life cohort study will inform clinical practice regarding the recommendation of COVID-19 booster vaccinations for individuals with mental health and sleep problems.

Heterologous and homologous COVID-19 mRNA vaccination schemes for induction of basic immunity show similar immunogenicity regarding long-term spike-specific cellular immunity in healthcare workers.

Healthcare workers (HCWs) are recommended to receive at least three spike-antigen exposures to generate basic immunity and to mediate herd protection of vulnerable patients. So far, less attention has been put on the cellular immune response induced by homologous (three BTN162b2mRNA doses) or heterologous (mRNA-1273 as third dose building on two BTN162bmRNA doses) and the immunological impact of breakthrough infections (BTIs). Therefore, in 356 vaccinated HCWs with or without BTIs the Anti-SARS-CoV-2-Spike-IgG concentrations and avidities and B- and T-cell-reactivity against SARS-CoV-2-Spike-S1- and Nucleocapsid-antigens were assessed with Interferon-gamma-ELISpot and by flow-cytometry. HCWs who had hybrid immunity due to BTIs exhibited strong T-cell-reactivity against the Spike-S1-antigen. A lasso regression model revealed a significant reduction in T-cell immune responses among smokers (p < 0.0001), with less significant impact observed for age, sex, heterologous vaccination, body-mass-index, Anti-Nucleocapsid T-cell reactivity, days since last COVID-19-immunization, and Anti-SARS-CoV-2-Spike-IgG. Although subgroup analysis revealed higher Anti-SARS-CoV-2-Spike-IgG after heterologous vaccination, similar cellular reactivity and percentages of Spike-reactive T- and B-cells were found between homologous and heterologous vaccination. Anti-SARS-CoV-2-Spike-IgG concentrations and avidity significantly correlated with activated T-cells. CD4 + and CD8 + responses correlated with each other. A strong long-term cellular immune response should be considered as baseline for recommendations of booster doses in HCWs with prioritization of smokers. HCWs presented significant T-cellular reactivity towards Spike-S1-antigen with particularly strong responses in hybrid immunized HCWs who had BTIs. HCWs without BTI presented similar percentages of Spike-specific B- and T-cells between homologous or heterologous vaccination indicating similar immunogenicity for both mRNA vaccines, BNT162b2mRNA and mRNA-1273.

Differentiating patients admitted primarily due to coronavirus disease 2019 (COVID-19) from those admitted with incidentally detected severe acute respiratory syndrome corona-virus type 2 (SARS-CoV-2) at hospital admission: A cohort analysis of German hospital records.

OBJECTIVE: The number of hospitalized patients with severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) does not differentiate between patients admitted due to coronavirus disease 2019 (COVID-19) (ie, primary cases) and incidental SARS-CoV-2 infection (ie, incidental cases). We developed an adaptable method to distinguish primary cases from incidental cases upon hospital admission. DESIGN: Retrospective cohort study. SETTING: Data were obtained from 3 German tertiary-care hospitals. PATIENTS: The study included patients of all ages who tested positive for SARS-CoV-2 by a standard quantitative reverse-transcription polymerase chain reaction (RT-PCR) assay upon admission between January and June 2022. METHODS: We present 2 distinct models: (1) a point-of-care model that can be used shortly after admission based on a limited range of parameters and (2) a more extended point-of-care model based on parameters that are available within the first 24-48 hours after admission. We used regression and tree-based classification models with internal and external validation. RESULTS: In total, 1,150 patients were included (mean age, 49.5±28.5 years; 46% female; 40% primary cases). Both point-of-care models showed good discrimination with area under the curve (AUC) values of 0.80 and 0.87, respectively. As main predictors, we used admission diagnosis codes (ICD-10-GM), ward of admission, and for the extended model, we included viral load, need for oxygen, leucocyte count, and C-reactive protein. CONCLUSIONS: We propose 2 predictive algorithms based on routine clinical data that differentiate primary COVID-19 from incidental SARS-CoV-2 infection. These algorithms can provide a precise surveillance tool that can contribute to pandemic preparedness. They can easily be modified to be used in future pandemic, epidemic, and endemic situations all over the world.