Superspreading events shaped the Coronavirus Disease 2019 (COVID-19) pandemic, and their rapid identification and containment are essential for disease control. Here we provide a national-scale analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) superspreading during the first wave of infections in Austria, a country that played a major role in initial virus transmissions in Europe. Capitalizing on Austria’s well-developed epidemiological surveillance system, we identified major SARS-CoV-2 clusters during the first wave of infections and performed deep whole-genome sequencing of more than 500 virus samples. Phylogenetic-epidemiological analysis enabled the reconstruction of superspreading events and charts a map of tourism-related viral spread originating from Austria in spring 2020. Moreover, we exploited epidemiologically well-defined clusters to quantify SARS-CoV-2 mutational dynamics, including the observation of a low-frequency mutation that progressed to fixation within the infection chain. Time-resolved virus sequencing unveiled viral mutation dynamics within individuals with COVID-19, and epidemiologically validated infector-infectee pairs enabled us to determine an average transmission bottleneck size of 103 SARS-CoV-2 particles. In conclusion, this study illustrates the power of combining epidemiological analysis with deep viral genome sequencing to unravel the spread of SARS-CoV-2, and to gain fundamental insights into mutational dynamics and transmission properties.
CD8+ T cell immunity to SARS-CoV-2 has been implicated in COVID-19 severity and virus control. Here, we identified nonsynonymous mutations in MHC-I-restricted CD8+ T cell epitopes after deep sequencing of 747 SARS-CoV-2 virus isolates. Mutant peptides exhibited diminished or abrogated MHC-I binding in a cell-free in vitro assay. Reduced MHC-I binding of mutant peptides was associated with decreased proliferation, IFN-γ production and cytotoxic activity of CD8+ T cells isolated from HLA-matched COVID-19 patients. Single cell RNA sequencing of ex vivo expanded, tetramer-sorted CD8+ T cells from COVID-19 patients further revealed qualitative differences in the transcriptional response to mutant peptides. Our findings highlight the capacity of SARS-CoV-2 to subvert CD8+ T cell surveillance through point mutations in MHC-I-restricted viral epitopes.
AbstractWe comparatively assessed sensitivities and specificities of 4 commercial enzyme-linked immunosorbent assays (ELISAs) and 2 rapid tests in 77 patients with polymerase chain reaction–confirmed severe acute respiratory syndrome coronavirus 2 infection, grouped by interval since symptom onset. Although test sensitivities were low (<40%) within the first 5 days after disease onset, immunoglobulin (Ig) M, IgA, and total antibody ELISAs increased in sensitivity to >80% between days 6 and 10 after symptom onset. The evaluated tests (including IgG and rapid tests) provided positive results in all patients at or after the 11th day after onset of disease. The specificities of the ELISAs were 83% (IgA), 98% (IgG), and 97% (IgM and total antibody).
Aim
To assess predictors of in‐hospital mortality in people with prediabetes and diabetes hospitalized for COVID‐19 infection and to develop a risk score for identifying those at the greatest risk of a fatal outcome.
Materials and Methods
A combined prospective and retrospective, multicentre, cohort study was conducted at 10 sites in Austria in 247 people with diabetes or newly diagnosed prediabetes who were hospitalized with COVID‐19. The primary outcome was in‐hospital mortality and the predictor variables upon admission included clinical data, co‐morbidities of diabetes or laboratory data. Logistic regression analyses were performed to identify significant predictors and to develop a risk score for in‐hospital mortality.
Results
The mean age of people hospitalized (n = 238) for COVID‐19 was 71.1 ± 12.9 years, 63.6% were males, 75.6% had type 2 diabetes, 4.6% had type 1 diabetes and 19.8% had prediabetes. The mean duration of hospital stay was 18 ± 16 days, 23.9% required ventilation therapy and 24.4% died in the hospital. The mortality rate in people with diabetes was numerically higher (26.7%) compared with those with prediabetes (14.9%) but without statistical significance (
P
= .128). A score including age, arterial occlusive disease, C‐reactive protein, estimated glomerular filtration rate and aspartate aminotransferase levels at admission predicted in‐hospital mortality with a C‐statistic of 0.889 (95% CI: 0.837‐0.941) and calibration of 1.000 (
P
= .909).
Conclusions
The in‐hospital mortality for COVID‐19 was high in people with diabetes but not significantly different to the risk in people with prediabetes. A risk score using five routinely available patient variables showed excellent predictive performance for assessing in‐hospital mortality.
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