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AbstractCOVID-19 pandemic has burdened healthcare systems, necessitating the development of mortality prediction scores to guide clinical decisions and resource allocation. 4C ISARIC mortality score was developed and validated on a British cohort.ObjectivesExternal validation of the score in the setting of a large Saudi Arabian ICU.MethodRetrospective chart review of COVID-19 patients admitted to ICU of King Saud Medical City, Riyadh, Saudi Arabia. Collecting data to calculate the score, then fitting a ROC curve against known patients’ outcome.ResultsCohort included 1493 patients with 38% mortality, AUC of the score was 0.81 (95% CI: 0.79 – 0.83, p < 0.001), correctly classifying 72.67% of the cohort. Cut-off value of > 9 had sensitivity of 70.5% (95% CI: 66.6 – 74.3), specificity 73.97% (95% CI: 71 – 76.8), positive predictive value 62.4% (95% CI: 59.5 – 65.2), and negative predictive value 80.2% (95% CI: 78.2 – 82.4).Conclusion4C ISARIC mortality risk score performed well with a good discriminatory ability for critically ill patients admitted to ICU in our setting. Cut-off > 9 was the optimal criterion.

Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2, an emerging virus that utilizes host proteins ACE2 and TMPRSS2 as entry factors. Understanding the factors affecting the pattern and levels of expression of these genes is important for deeper understanding of SARS-CoV-2 tropism and pathogenesis. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci for both ACE2 and TMPRSS2, that vary in frequency across world populations. We find TMPRSS2 is part of a mucus secretory network, highly upregulated by type 2 (T2) inflammation through the action of interleukin-13, and that the interferon response to respiratory viruses highly upregulates ACE2 expression. IL-13 and virus infection mediated effects on ACE2 expression were also observed at the protein level in the airway epithelium. Finally, we define airway responses to common coronavirus infections in children, finding that these infections generate host responses similar to other viral species, including upregulation of IL6 and ACE2. Our results reveal possible mechanisms influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes. ACE2 and TMPRSS2 have received recent attention as entry factors for SARS-CoV-2. Here the authors analyze nasal airway transcriptome data from 695 children determining ACE2 and TMPRSS2 expression is induced by viral and type2 inflammation, respectively, and both exhibit eQTLs that vary across world populations.

Abstract BackgroundThe spread of virus via the blood stream has been suggested to contribute to extra pulmonary organ failure in Coronavirus disease 2019 (COVID-19). We assessed SARS-CoV-2 RNAemia (RNAemia) and the association between RNAemia and inflammation, organ failure and mortality in critically ill COVID-19 patients.MethodsIn a tertiary center we included all patients with PCR verified COVID-19 and consent admitted to ICU. SARS-CoV-2 RNA copies above 1000/ml measured by PCR in plasma was defined as RNAemia and used as surrogate for viremia.ResultsOf the 92 patients RNAemia was found in 31 (34%) and RNA in plasma was detected in 63 (58%). Hypertension and corticosteroid treatment was more common in patients with RNAemia . RNAemia levels were higher in patients with RAAS-inhibitor treatment or corticosteroid treatment than those without. Extra-pulmonary organ failure biomarkers and the extent of organ failure were similar in patients with and without RNAemia, but the former group had more renal replacement therapy and higher mortality (26 vs 16%; 35 vs 16%, respectively, p=0.04). RNAemia was not an independent predictor of death at 30 days after adjustment for age. ConclusionSARS-CoV2 RNA copies in plasma is a common finding in ICU patients with COVID-19. Although viremia was not associated with extra pulmonary organ failure it was more common in patients who did not survive to 30 days after ICU admission.Trial registrationClinicalTrials NCT04316884

ABSTRACTThe COVID-19 pandemic began in the city of Wuhan, China, at the end of 2019 and quickly spread worldwide. The disease is caused by contact with the SARS-CoV-2 virus, which probably jumped from an animal host to humans. SARS-CoV-2 infects various tissues in the body, notably the lungs, and patients usually die from respiratory complications. Mathematical models of the disease have been instrumental to guide the implementation of mitigation strategies aimed at slowing the spread of the disease. One of the key parameters of mathematical models is the basic reproduction ratio R0, which measures the degree of infectivity of affected individuals. The goal of mitigation is to reduce R0 as close or below 1 as possible, as it means that new infections are in decline. In the present work, we use the recursive least-squares algorithm to establish the stochastic variability of a time-varying R0(t) from eight different countries: Argentina, Belgium, Brazil, Germany, Italy, New Zealand, Spain, and the United States of America. The proposed system can be implemented as an online tracking application providing information about the dynamics of the pandemic to health officials and the public at large.

AbstractThe present study has investigated the role of regional meteorology and air quality parameters in the outbreak pattern of COVID-19 pandemic in India. Using the remote sensing based dataset of 12 environmental variables we correlated infective case counts at a district level in India. Our investigation carried out on the circumstantial data from more than 300 major affected districts in India and found that air quality parameters are playing very crucial role in this outbreak. Among the air pollutants, O3 was better correlating with infection counts followed by AOD, CO, NO2, BC and SO2. We also observed that among the weather parameters air temperature, incoming shortwave radiation, wind speed are positively and significantly associate with outbreak pattern and precipitation and humidity are negatively correlated with confirmed cases; only cloud cover has no significant relation. We noted that coastal districts in the both coast of India and districts located in the plain and low-lying areas have experienced bitter situation during this pandemic. Our study suggests that improving air quality with proper strict regulations and complete lockdown during the peak of pandemic could reduce the misfortune in all over India.

Abstract Coronavirus disease-2019 (COVID-19) was declared as a pandemic by WHO in March 2020. SARS-CoV-2 causes a wide range of illness from asymptomatic to life-threatening. There is an essential need to identify biomarkers to predict disease severity and mortality during the earlier stages of the disease, aiding treatment and allocation of resources to improve survival. The aim of this study was to identify at the time of SARS-COV-2 infection patients at high risk of developing severe disease associated with low survival using blood parameters, including inflammation and coagulation mediators, vital signs, and pre-existing comorbidities. This cohort included 89 multi-ethnic COVID-19 patients recruited between July 14th and October 20th 2020 in Doha, Qatar. According to clinical severity, patients were grouped into severe (n = 33), mild (n = 33) and asymptomatic (n = 23). Common routine tests such as complete blood count (CBC), glucose, electrolytes, liver and kidney function parameters and markers of inflammation, thrombosis and endothelial dysfunction including complement component split product C5a, Interleukin-6, ferritin and C-reactive protein were measured at the time COVID-19 infection was confirmed. Correlation tests suggest that C5a is a novel predictive marker of disease severity and mortality, in addition to 40 biological and physiological parameters that were found statistically significant between survivors and non-survivors. Survival analysis showed that. high C5a levels, hypoalbuminemia, lymphopenia, elevated procalcitonin, neutrophilic leukocytosis, acute anemia along with increased acute kidney and hepatocellular injury markers were associated with a higher risk of death in COVID-19 patients. Altogether, we created a prognostic classification model, the CAL model (C5a, Albumin, and Lymphocyte count) to predict severity with significant accuracy. Stratification of patients using the CAL model could help the identification of patients likely to develop severe symptoms in advance so that treatments can be targeted accordingly.

AbstractBackgroundThe Covid-19 pandemic is a public health crisis which may cause unintended additional societal costs such as child maltreatment. Considerable concern is raised as to whether the pandemic has led to an increase in violence and sexual abuse against children.ObjectiveThe present study objective is to provide rates of violence and sexual abuse against adolescents the year before the pandemic compared to one year into the pandemic.Participants and settingTwo samples of Norwegian 12-16-year-olds were approached. A representative pre-pandemic sample of 9240 adolescents (M age= 14.11), and a sample recruited one year into the pandemic resulting in 3540 responses (M age (SD) = 14.5).MethodsAn online survey was administered during school hours including established measures of violence and sexual abuse exposure. Sociodemographic characteristics were assessed.ResultsThere was 1.4 percentage point increase in sexual abuse by an adult, and a 3.9 percentage point decrease in psychological violence by a parent during the pandemic compared to the year before the pandemic. Otherwise, violence and sexual abuse rates remained stable across these two time periods. Risk factors for violence and sexual abuse were amplified during the pandemic.ConclusionNorway, a high-income welfare state, imposed measures to counteract the burden of the pandemic mitigation actions for adolescents. This might partly explain the absence of the feared increase in violence towards adolescents. The disproportionate risk for violence and sexual abuse for some groups of adolescents is however concerning, and should be followed up over time.

Suspension of face-to-face instruction in schools during the COVID-19 pandemic has led to concerns about consequences for students’ learning. So far, data to study this question have been limited. Here we evaluate the effect of school closures on primary school performance using exceptionally rich data from The Netherlands (n ≈ 350,000). We use the fact that national examinations took place before and after lockdown and compare progress during this period to the same period in the 3 previous years. The Netherlands underwent only a relatively short lockdown (8 wk) and features an equitable system of school funding and the world’s highest rate of broadband access. Still, our results reveal a learning loss of about 3 percentile points or 0.08 standard deviations. The effect is equivalent to one-fifth of a school year, the same period that schools remained closed. Losses are up to 60% larger among students from less-educated homes, confirming worries about the uneven toll of the pandemic on children and families. Investigating mechanisms, we find that most of the effect reflects the cumulative impact of knowledge learned rather than transitory influences on the day of testing. Results remain robust when balancing on the estimated propensity of treatment and using maximum-entropy weights or with fixed-effects specifications that compare students within the same school and family. The findings imply that students made little or no progress while learning from home and suggest losses even larger in countries with weaker infrastructure or longer school closures.