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Background: Although the Pfizer-BioNTech (BNT162b2), Oxford-AstraZeneca (ChAdOx1 nCoV-19), Sinopharm (BBIBP-CorV), and Sputnik V coronavirus disease 2019 (COVID-19) vaccines have been granted emergency approval in many nations, their safety has never been studied and compared in one community-based study. This study aimed to investigate and compare the incidence, nature, severity, and predictors of adverse events following immunization (AEFIs) with COVID-19 vaccines., Method: This was a prospective observational study conducted in Jordan between 1 January and 21 September 2021. A team of pharmacists and nurses (n = 407) collected the local and systemic AEFIs of four COVID-19 vaccines by prospectively contacting participants registered in the national vaccination program platform. A red-flag technology was inserted to classify and track rare and serious AEFIs., Results: This study included 658,428 participants who were vaccinated with 1,032,430 doses; 610,591, 279,606, 140,843, and 1390 participants received the first and second doses of the BNT162b2, BBIBP-CorV, ChAdOx1 nCoV-19, and Sputnik V vaccines, respectively. The overall incidence of AEFIs was 28.8%, and the overall rates of systemic, local, and immediate hypersensitivity AEFIs were 22.2%, 18.8%, and 0.5%, respectively. The highest proportions of immediate hypersensitivity AEFIs and systemic AEFIs were reported after administration of the Sputnik V vaccine and ChAdOx1 nCoV-19 first dose, respectively. The most severe AEFIs were reported after ChAdOx1 nCoV-19 first dose and BNT162b2 second dose. The hospitalization and mortality rates after vaccination were 20 in 10,000 and 1 in 10,000, respectively. Based on red-flag tracking, the top three outcome events were lymphadenopathy (157.9/100,000), anxiety disorders (136.6/100,000), and lower respiratory tract infection (100.9/100,000), with Guillain-Barré syndrome (1.8/100,000), vasculitis (3.0/100,000), and myopericarditis (4.8/100,000) being the least common., Conclusion: The incidence rates of local, systemic, and immediate hypersensitivity AEFIs of four COVID-19 vaccines occur frequently. High incidence rates of rare and serious AEFIs were reported in this study. Younger participants, females, those who had previously had COVID-19, and smokers were more likely to encounter AEFIs., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: The upper respiratory tract (URT) is the portal of entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and SARS-CoV-2 likely interacts with the URT microbiome. However, understanding of the associations between the URT microbiome and the severity of coronavirus disease 2019 (COVID-19) is still limited., Objective: Our primary objective was to identify URT microbiome signature/s that consistently changed over a spectrum of COVID-19 severity., Methods: Using data from 103 adult participants from two cities in the United States, we compared the bacterial load and the URT microbiome between five groups: 20 asymptomatic SARS-CoV-2-negative participants, 27 participants with mild COVID-19, 28 participants with moderate COVID-19, 15 hospitalized patients with severe COVID-19, and 13 hospitalized patients in the ICU with very severe COVID-19., Results: URT bacterial load, bacterial richness, and within-group microbiome composition dissimilarity consistently increased as COVID-19 severity increased, while the relative abundance of an amplicon sequence variant (ASV), Corynebacterium _unclassified.ASV0002, consistently decreased as COVID-19 severity increased., Conclusions: We observed that the URT microbiome composition significantly changed as COVID-19 severity increased. The URT microbiome could potentially predict which patients may be more likely to progress to severe disease or be modified to decrease severity. However, further research in additional longitudinal cohorts is needed to better understand how the microbiome affects COVID-19 severity., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Shilts, Rosas-Salazar, Strickland, Kimura, Asad, Sehanobish, Freeman, Wessinger, Gupta, Brown, Boone, Patel, Barbi, Bottalico, O’Neill, Akbar, Rajagopala, Mallal, Phillips, Turner, Jerschow and Das.)

Background: Anosmia and ageusia are symptoms commonly associated with COVID-19, but the relationship with disease severity, onset and recovery are unclear., Objective: To examine factors associated with anosmia and ageusia and the recovery from these symptoms in an ethnically diverse cohort., Methods: Individuals tested for SARS-CoV-2 between March and April 2020 were eligible for the study. Randomly selected participants answered a telephone questionnaire on COVID-19 symptoms with a focus on anosmia and ageusia. Additionally, relevant past medical history and data on the COVID-19 clinical course were obtained from electronic medical records. 486 patients were in the COVID-19 group and 103 were COVID-19-negative., Results: Patients who were younger were more likely to report anosmia and/or ageusia (odds ratio (OR) for anosmia per 1-year increase in age: 0·98, 95%CI:0-97-0·99, p  = 0·003; for ageusia: 0·98, 95%CI:0·97-0·99, p  = 0·005) as were patients with lower eosinophil counts (OR for anosmia per 0.1-K/μL increase in eosinophils: 0·02, 95%CI:0·001-0·46, p  = 0·01, for ageusia 0·10, 95%CI:0·01-0·97, p  = 0·047). Male gender was independently associated with a lower probability of ageusia (OR:0·56, 95%CI:0·38-0·82, p  = 0·003) and earlier sense of taste recovery (HR:1·44, 95%CI:1·05-1·98, p  = 0·02). Latinos showed earlier sense of taste recovery than white patients (HR:1·82, 95%CI:1·05-3·18, p  = 0·03)., Conclusion: Anosmia and ageusia were more common among younger patients and those with lower blood eosinophil counts. Ageusia was less commonly reported among men, and time to taste recovery was earlier among both men and Latinos.

COVID-19 and SARS are epidemics which have influenced the largest global economic crisis in recent years. This research reveals that both SARS and COVID-19 have led to fluctuations in the prices of gold and the US dollar index; however, there is no direct causal relationship be-tween COVID-19 and the price of bitcoin. The USD index saw a significant increase during the SARS outbreak, while gold prices surged during the COVID-19 pandemic. The notion that cryptocurrency will surpass the value of gold or traditional currencies seems improbable, given the lack of evidence linking bitcoin prices to COVID-19. Gold is expected to maintain its value in the long term, offering lower risk compared to other currencies. [ABSTRACT FROM AUTHOR]

Background: There is a scarcity of evidence regarding the real-world effectiveness of coronavirus disease 2019 (COVID-19) vaccines. This was the first study to evaluate the effectiveness of four types of vaccines against asymptomatic and symptomatic infection, and COVID-19 outcomes among the general population. Methods: This was a matched comparison group quasi-experimental study conducted in Jordan between 1 January and 29 August 2021. In the first part of the study, 1200 fully vaccinated individuals were matched with 1200 unvaccinated control participants. In order to measure vaccine effectiveness, the infection rates of both vaccinated and unvaccinated groups were calculated. The second part of the study included measuring specific anti-SARS CoV-2 immune cells and antibodies. Results: BNT162b2 (Pfizer, New York, NY, USA) showed a significantly higher effectiveness against asymptomatic COVID-19 infection (91.7%) and hospitalization (99.5%) than BBIBP-CorV (Sinopharm, Beijing, China) (88.4% and 98.7%, respectively) and ChAdOx1 nCoV-19 (AstraZeneca, Cambridge, UK) (84.3%, and 98.9%, respectively). The effectiveness rates of the Sputnik V (Gamaleya Research Institute, Moscow, Russia) vaccine against asymptomatic, symptomatic, and hospitalization were 100%, 100%, and 66.7%, respectively. The highest median anti-spike (S) IgG values were seen in individuals who received BNT162b2 (2.9 AU/mL) and ChAdOx1 nCoV-19 (2.8 AU/mL) vaccines. The levels of anti-S IgG were significantly decreased after 7 months of vaccination with BNT162b2 and BBIBP-CorV. There were significant decreases in the median number of neutralizing antibodies one month and seven months after receiving BNT162b2 (from 88.5 to 75.2 4 Bioequivalent Allergen Unit per milliliter/mL), BBIBP-CorV (from 69.5 to 51.5 BAU/mL), and ChAdOx1 nCoV-19 (from 69.2 to 58.BAU/mL) vaccines. The highest percentage of T cells specific to COVID-19 vaccine was found in individuals who received BNT162b2 (88.5%). Conclusion: All four vaccines evaluated in this study showed effectiveness against asymptomatic COVID-19 infection, symptomatic infection, hospitalization, and death. Furthermore, BNT162b2, BBIBP-CorV, and ChAdOx1 nCoV-19 induced high levels of immunology markers within one month of vaccination. [ABSTRACT FROM AUTHOR]

Background It's critical to identify COVID-19 patients with a higher death risk at early stage to give them better hospitalization or intensive care. However, thus far, none of the machine learning models has been shown to be successful in an independent cohort. We aim to develop a machine learning model which could accurately predict death risk of COVID-19 patients at an early stage in other independent cohorts. Methods We used a cohort containing 4711 patients whose clinical features associated with patient physiological conditions or lab test data associated with inflammation, hepatorenal function, cardiovascular function, and so on to identify key features. To do so, we first developed a novel data preprocessing approach to clean up clinical features and then developed an ensemble machine learning method to identify key features. Results Finally, we identified 14 key clinical features whose combination reached a good predictive performance of area under the receiver operating characteristic curve 0.907. Most importantly, we successfully validated these key features in a large independent cohort containing 15 790 patients. Conclusions Our study shows that 14 key features are robust and useful in predicting the risk of death in patients confirmed SARS-CoV-2 infection at an early stage, and potentially useful in clinical settings to help in making clinical decisions. [ABSTRACT FROM AUTHOR]