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Additional file 3: Table S3. Logistic regression models for each blood and physiological measure tested separately in the KCH training cohort, for 14- and 3-day ICU/death.

Background Information is essential for growth; without it, little can be accomplished. Data gathering has seen significant changes throughout the previous few centuries because of certain transitory medium. The look and style of information transference are affected by the employment of new and emerging technologies, some of which are efficient, others are reliable, and many more are quick and effective, but a few were disappointing for various reasons. Aims This study aims at using TextBlob and VADER analyser with historical tweets, to analyse emotional responses to the corona virus pandemic (covid-19). It shows us how much of a sociological, environmental, and economic impact it has in Nigeria, among other things. This study would be a tremendous step forward for students, researchers, and scholars who want to advance in fields like data science, machine learning, and deep learning. Methodology The hashtag ‘covid-19' was used to collect 1,048,575 tweets from Twitter. The tweets were pre-processed with a twitter tokenizer, and Valence Aware Dictionary for Sentiment Reasoning (VADER) and TextBlob were used for sentiment and text mining, respectively. Topic modelling was done with Latent Dirichlet Allocation (LDA). The simulated subjects, on the other hand, were visualized using Multidimensional scaling (MDS). Results The result of the VADER sentiment returned 39.8%, 31.3% and 28.9%, positive, neutral, and negative sentiment respectively while the result of the TextBlob sentiment returned 46.0%, 36.7% and 17.3%, neutral, positive, and negative sentiment, respectively. Conclusion With all of this, information from social media may be used to help organizations, governments, and nations around the world make smart and effective decisions about how to restrict and limit the negative effects of covid-19. Also know the opinion and challenges of people, then deal with problem of misinformation. It is concluded that with popular belief a significant number of the populace regards covid-19 as a virus that has come to stay, some believe it will eventually be conquered.

The outbreak of the Covid-19 pandemic was not only a public health crisis of unprecedented proportions in recent times, it also triggered an economic and social crisis whose consequences will be felt in our societies and economies for years. The decision-making and implementation of the social, economic and fiscal measures in response to the pandemic challenged the economic and fiscal sustainability of states. and simultaneously has raised valid questions about the legitimacy of Covid-19-crisis management. Such concerns are particularly relevant for multilevel systems where (at least) two levels of government are responsible for these areas and decision-making is characterised by either divided or shared powers. This paper reviews existing studies, indexes and databases dealing with the design and effects of the social, fiscal and economic measures in multilevel systems. It addresses general issues around crisis management in multilevel systems general in terms as well as in relation to the social, economic and fiscal measures introduced during the pandemic. The paper also focuses on the role of domestic and transnational governance arrangements in dealing with Covid-19. The review provides an important source to examine policy responses in the context of our study of the legitimacy of social, economic and fiscal measures in multilevel systems.

Food and waterborne outbreaks data reported under the framework of Directive 2003/99/EC and in accordance with the update of the technical specifications for harmonised reporting of FBOs through the EU reporting system in accordance with Directive 2003/99/EC. This dataset includes the number of outbreaks, as well as the number of human cases, hospitalisations and deaths, per causative agent. In addition, other information can include data on causative agents, food vehicles, and the factors in food preparation and handling that contributed to the food-borne outbreaks. Reporting countries can also provide information on the nature of the evidence supporting the suspicion of the food vehicle. This evidence can be epidemiological, microbiological, descriptive environmental, or based on product tracing investigations. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: PubliFBO2020_20211109: >> EU; csv; zoonoses_support@efsa.europa.eu

Abstract Background Community-acquired pneumonia (CAP) is the most frequent infection diagnosis in hospitals. Antimicrobial therapy for CAP is depicted in clinical practice guidelines, but adherence data and effect of antibiotic stewardship measures are lacking. Methods A dedicated antibiotic team pointed out CAP as a potential target for antimicrobial stewardship (AMS) measures at a 1.000-bed, tertiary care, teaching university hospital in Norway from March until May for the years 2016 throughout 2021. The aim of the AMS program was to increase diagnostic and antimicrobial therapy adherence to national clinical practice guideline recommendations through multiple and continuous AMS efforts. Descriptive statistics were retrospectively used to delineate antimicrobial therapy for CAP. The primary outcomes were proportions that received narrow-spectrum beta-lactams, and broad-spectrum antimicrobial therapy. Results 1.112 CAP episodes were identified. The annual proportion that received narrow-spectrum beta-lactams increased from 56.1 to 74.4% (p = 0.045). Correspondingly, the annual proportion that received broad-spectrum antimicrobial therapy decreased from 34.1 to 17.1% (p = 0.002). Trends were affected by the coronavirus pandemic. Mortality and 30-day readmission rates remained unchanged. De-escalation strategies were frequently unutilized, and overall therapy duration exceeded clinical practice guideline recommendations substantially. Microbiologically confirmed CAP episodes increased from 33.7 to 56.2% during the study period. Conclusion CAP is a suitable model condition that is sensitive to AMS measures. A continuous focus on improved microbiological diagnostics and antimicrobial therapy initiation is efficient in increasing adherence to guideline recommendations. There is an unmet need for better antimicrobial de-escalation strategies.

Background:Anti-CD20 therapies induce pronounced B-cell depletion and blunt humoral responses to vaccines. Recovery kinetics of anti-CD20 therapy-mediated cellular and humoral effects in people with multiple sclerosis (pwMS) are poorly defined.Objective:To investigate the duration of the anti-CD20 treatment-induced effects on humoral responses to COVID-19 vaccines.Methods:This retrospective observational study included pwMS who had discontinued anti-CD20 therapy for ⩾12 months and remained without immunomodulation. We retrieved demographics and laboratory parameters including B-cell counts and immunoglobulin (IgG, IgM, IgA) levels prior to anti-CD20 commencement (baseline) and longitudinally after anti-CD20 treatment discontinuation from electronic medical records. Humoral responses to SARS-CoV-2 vaccines were compared with a population of 11 pwMS with ongoing anti-CD20 medication (control cohort).Results:A total of 24 pwMS had discontinued anti-CD20 therapy for a median of 34 months (range: 16–38 months). Antibody responses to COVID-19 vaccines were available in 17 (71%). Most individuals (n = 15, 88%) elicited a measurable antibody response [mean: 774 BAU/ml (±SD 1283 BAU/ml)] to SARS-CoV-2 immunization on average 22 months (range: 10–30 months) from the last anti-CD20 infusion, which was higher compared with the population with ongoing anti-CD20 therapy (n = 11, mean: 12.36 ± SD 11.94 BAU/ml; p 18 months after treatment discontinuation (19–24 months: n = 2, p = 0.013; 25–36 months: n = 9; p Conclusion:Anti-CD20-induced inhibition of humoral responses to COVID-19 vaccines is transient and antibody production was more pronounced >18 months after anti-CD20 treatment discontinuation. The immunological effect on B-cell counts appears to wane by the same time.

This datasets contains analysis of Austrian SARS-CoV-2 clusters with in-school transmissions between calendar week 36 and 45, in 2020 as of 22.12.2020. A cluster is defined as a group of at least two cases of SARS-CoV-2 infection, which were epidemiologically linked as an infector (i.e. source case) and an infectee (i.e. successive case). A school cluster includes at least one infectee generated by in-school transmission. The source case of the in-school transmission(s), a teacher-source case or a student-source case, occurs in any other setting, such as household, work place, leisure activity, or in an unknown setting. For identifying the source case and successive cases, we used information on disease onset and possibly contagious interactions within 14 days prior to disease onset. These data derived from standardised case-interviews performed by the responsible public health authorities. The data was used for calibrating an agent-based epidemiological model (Link). Datasets inlcuded are: cases_and_sources.csv: includes data on students and teachers (person_group) by schooltype: number of cluster source cases (n_source_cases) and number of cases (n_cases) age_asymptomatic.csv: includes data of students and teachers (person_group) by age: number of cases per age-group (n_cases) and number of asymptomatic cases per age-group (n_asymptomatic) cluster_size.csv: includes data on cluster size including the source case (cluster_size) by schooltype: number of clusters (n_clusters)

ZusammenfassungFür Patienten und Patientinnen mit Asthma wird eine Impfung gegen COVID-19 empfohlen. Dies gilt auch für Patienten und Patientinnen mit schwerem Asthma. Die Behandlung des schweren Asthmas mit einem Biologikum ist keine Kontraindikation für eine Impfung gegen COVID-19.