Articles: sars-cov-2.
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COVID-19 superspreader events have occurred when symptomatic individuals without wearing face masks boarded buses. ⋯ Strict nonpharmacological preventive interventions substantially reduced the risk of COVID-19 super-spreader events in buses boarded by presymptomatic individuals.
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On 8 December 2020 NHS England administered the first COVID-19 vaccination. ⋯ The NHS rapidly delivered mass vaccination. In this study a data-monitoring framework was deployed using publicly auditable methods and a secure in situ processing model, using linked but pseudonymised patient-level NHS data for 57.9 million patients. Targeted activity may be needed to address lower vaccination coverage observed among certain key groups.
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The coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus and is responsible for nearly 6 million deaths worldwide in the past 2 years. Machine learning (ML) models could help physicians in identifying high-risk individuals. ⋯ ML and GAs provided adequate models to predict COVID-19 outcomes in patients with different severity grades.
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Rev Assoc Med Bras (1992) · Jan 2022
Thorax computed tomography findings and anti-SARS-CoV-2 immunoglobulin G levels in polymerase chain reaction-negative probable COVID-19 cases.
This study aimed to evaluate the SARS-CoV-2 immunoglobulin G (IgG) levels after 6 months of polymerase chain reaction (PCR) negative but assumed to be COVID-19 positive cases to investigate the relationship between IgG levels and thoracic computed tomography (CT) findings. ⋯ This study is valuable because increasing severity (≥5%) of lung involvement appears to be associated with high and persistent IgG antibody titers. In probable cases of COVID-19, even if the PCR test is negative, high IgG titers 6 months after discharge can predict the rate of lung parenchymal involvement.
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We aimed to characterize biochemical and cardiovascular predictors of the paediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2 (PIMS-TS) risk based on the data from the LATE-COVID-Kids study. ⋯ It is the first data on the possible predictors of PIMS-TS risk in the Long-COVID period. These results need to be further validated to next create the PIMS SCORE algorithm, which might enable the effective prediction of children with the risk of PIMS-TS occurrence after COVID-19 recovery.