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  • Corona Virus Disease

  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Carr, Ewan; Bendayan, Rebecca; Bean, Daniel; Stammers, Matt; +44 Authors

    Additional file 5: Figure S1. Calibration (logistic and LOESS curves) of supplemented NEWS2 model for 3-day ICU/death model at validation sites.

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    Image . 2021
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Image . 2021
    License: CC BY
    Data sources: Datacite
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      Image . 2021
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Image . 2021
      License: CC BY
      Data sources: Datacite
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    Authors: Arakelyan, Arsen; Avetyan, Diana;

    Sequencing of SARS-CoV-2 provides essential information on viral evolution, transmission, and epidemiology. In this study, we performed whole-genome sequencing of SARS-CoV-2 using nanopore and Illumina short-read sequencing to describe the circulation of the virus lineage in Armenia. This dataset contains Nextstrain configuration files, the auspice JSON file, BEAST output logs, and trees files, and resulting log and tree files as well as R scripts and data files used in phylogenetic and functional analyses.

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: ZENODO
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    Authors: Carr, Ewan; Bendayan, Rebecca; Bean, Daniel; Stammers, Matt; +44 Authors

    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.

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    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      figshare
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Waagsbø, Bjørn; Tranung, Morten; Damås, Jan Kristian; Heggelund, Lars;

    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.

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    Collection . 2022
    License: CC BY
    Data sources: Datacite
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    Collection . 2022
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ figsharearrow_drop_down
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      Collection . 2022
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      Data sources: Datacite
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      Collection . 2022
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      Data sources: Datacite
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    Authors: Abayomi-Alli Adewumi Adebayo; Odeyinka Abiola; Arogundade Oluwasefunmi Tale; Misra Sanjah; +1 Authors

    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.

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: ZENODO
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    Authors: Lie-Nielsen, Anders;

    Denne masteroppgaven omhandler simuleringsprogramvaren Aimsun Next 20 og hvilke muligheter som finnes for fotgjengersimulering der. Den tar utgangspunkt i to simuleringsmetoder Aimsun Pedestrian Simulator og Fotgjengersimulering ved bruk av kjøretøymodellen i Aimsun og ser på hvordan disse kan brukes. Oppgaven består av to deler: Et litteraturstudie, som går inn i teorien og virkemåten som ligger bak modellene. Et casestudie, som ser på hvordan de to modellene fungerer i praksis, sentrert rundt vikepliktregulerte gangfelt. Litteraturstudien peker på flere viktige forskjeller i hvordan modellene virker teoretisk. Det at de to modellene er bygget med helt forskjellig formål, den ene for å simulere bare fotgjengere og den andre for å simulere kjøretøy, har en del å si for hvilke situasjoner de kan brukes i. Det er allikevel fullt mulig å bruke begge modellene til å simulere fotgjengeroppførsel i gangfelt. I casestudien ble det ikke funnet vesentlige forskjeller på hvordan modellene virket i praksis når det kom til påvirkning på kjøretøyene i trafikken. Begge klarte å simulere resultater som avviklet kjøretøyvolum og forsinkelse som lå tett opp mot observerte verdier. Det ble funnet svakheter i måten Aimsun Pedestrian Simulator simulerte interaksjonen mellom kjøretøy og fotgjengere i gangfeltet. Deteksjon av fotgjengere og oppbremsing fungerte ikke som det burde, og førte til mange situasjoner med unaturlige brå oppbremsinger for kjøretøy og fastlåste situasjoner der bilene ble stående fast midt på gangfeltet og blokkerte for fotgjengere. Disse problemene ble løst gjennom å utvikle en løsning som benytter virtuelle signalanlegg som styrer gangfeltene og bruker akturerte signaler til å etterligne vikepliktoppførsel. Dette fungerte svært bra. Denne oppgaven er skrevet under Covid-19-pandemien, og det er derfor en risiko for at observasjonene fra casestudien er representative for en normalsituasjon. This thesis regards the simulation software Aimsun Next 20 and the possibilities for pedestrian simulation within it. It considers two models, Aimsun Pedestrian Simulator and Pedestrian simulation using the vehicle model in Aimsun, and investigates how these can be used. The thesis consists of two parts: A Literature study, which investigates the theory and behavior behind the models. A Case study which looks at how the two models work in real life, centered around yield regulated pedestrian crossings. The literature study points to several important differences between how the models work theoretically. The fact that the models are built for completely different purposes, one to simulate only pedestrians, and the other to simulate vehicles has a lot to say for which situations they are applicable for. Still, it is possible to use both models to simulate pedestrian behavior in crossing areas. In the case study, there were found no big differences in the practical function of the models, simulating the interaction between pedestrians and vehicles in the crossing. Both managed to produce results like traffic flow, and delay, in good accordance with observed values. Some weaknesses in the way that Aimsun Pedestrian Simulator simulated interactions between vehicles and pedestrians were found. The detection of pedestrians and deceleration did not work as expected, and lead to a lot of abrupt breaking and locked situations where the cars got stuck in the middle of the crossing and blocked the movement of pedestrians. These problems were solved by developing a work-around solution using virtual traffic signals that regulate the crossings using actuated signals to mimic the yield behavior. This worked out great. This thesis is written during the Covid-19 pandemic, and the observations from the case study may therefore not be representative for a normal situation.

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    Authors: Hassen, Hanna Defar; Welde, Mengistu; Menebo, Mesay Moges;

    Additional file 1.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Hillewi Carnesten; Lena Wiklund Gustin; Karin Skoglund; Petra von Heideken Wågert;

    AbstractAimTo illuminate the meaning of newly graduated registered nurses' experiences of caring for patients in emergency departments during the COVID‐19 pandemic.DesignA phenomenological hermeneutical study guided by Lindseth and Norberg.MethodsIn‐depth one‐on‐one interviews with 14 nurses from five hospitals were conducted from March to November 2020 and analysed using thematic analysis. The consolidated criteria for reporting qualitative research (COREQ) were used as the reporting guideline.ResultsThe findings comprise one main theme Caring through barriers and three themes with sub‐themes. In the first theme, having intention to care, participants revealed their dedication to care for patients during the pandemic despite extensive stress, little experience and skills. The second theme, with tied hands in human suffering, illuminates experiences of being disconnected from the patient, overwhelmed by responsibility and unable to relieve suffering. The third theme, feeling inadequate, reveals experiences of lack of support and doubts meaning less space to develop into the nurse one wants to be.ConclusionFindings reveal a new understanding of new nurses' experiences during times of crisis. The essence of caring in the emergency department during the pandemic can be explained as mediated through spatial, temporal and emotional barriers preventing new nurses from providing holistic care.ImpactThe results may be used as anticipatory guidance for new nurses and inform targeted support interventions to support new nurses entering the profession in crisis conditions.Public ContributionThis study involved new nurses in semi‐structured interviews.

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    Journal of Advanced Nursing
    Article . 2023 . Peer-reviewed
    License: CC BY
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      Journal of Advanced Nursing
      Article . 2023 . Peer-reviewed
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    Authors: Signe Søvik; Andreas Barratt-Due; Trine Kåsine; Theresa Olasveengen; +12 Authors

    To determine the incidence and characteristics of superinfections in mechanically ventilated COVID-19 patients, and the impact of dexamethasone as standard therapy.This multicentre, observational, retrospective study included patients ≥ 18 years admitted from March 1155/156 patients (115 men, mean age 62 years, range 26-84 years) were included. 67 patients (43%) had 90 superinfections, pneumonia dominated (78%). Superinfections were associated with receiving dexamethasone (66% vs 32%, p0.0001), autoimmune disease (18% vs 5.7%, p0.016) and with longer ICU stays (26 vs 17 days, p0,001). Invasive fungal infections were reported exclusively in dexamethasone-treated patients [8/67 (12%) vs 0/88 (0%), p0.0001]. Unadjusted 90-day survival did not differ between patients with or without superinfections (64% vs 73%, p=0.25), but was lower in patients receiving dexamethasone versus not (58% vs 78%, p=0.007). In multiple regression analysis, superinfection was associated with dexamethasone use [OR 3.7 (1.80-7.61), p0.001], pre-existing autoimmune disease [OR 3.82 (1.13-12.9), p=0.031] and length of ICU stay [OR 1.05 p0.001].In critically ill COVID-19 patients, dexamethasone as standard of care was strongly and independently associated with superinfections.

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    Journal of Infection
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      Journal of Infection
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    Authors: Marleen A Slim; Brent Appelman; Hessel Peters-Sengers; Dave A Dongelmans; +24 Authors

    Abstract Background Large clinical trials on drugs for hospitalized coronavirus disease 2019 (COVID-19) patients have shown significant effects on mortality. There may be a discrepancy with the observed real-world effect. We describe the clinical characteristics and outcomes of hospitalized COVID-19 patients in the Netherlands during 4 pandemic waves and analyze the association of the newly introduced treatments with mortality, intensive care unit (ICU) admission, and discharge alive. Methods We conducted a nationwide retrospective analysis of hospitalized COVID-19 patients between February 27, 2020, and December 31, 2021. Patients were categorized into waves and into treatment groups (hydroxychloroquine, remdesivir, neutralizing severe acute respiratory syndrome coronavirus 2 monoclonal antibodies, corticosteroids, and interleukin [IL]-6 antagonists). Four types of Cox regression analyses were used: unadjusted, adjusted, propensity matched, and propensity weighted. Results Among 5643 patients from 11 hospitals, we observed a changing epidemiology during 4 pandemic waves, with a decrease in median age (67–64 years; P < .001), in in-hospital mortality on the ward (21%–15%; P < .001), and a trend in the ICU (24%–16%; P = .148). In ward patients, hydroxychloroquine was associated with increased mortality (1.54; 95% CI, 1.22–1.96), and remdesivir was associated with a higher rate of discharge alive within 29 days (1.16; 95% CI, 1.03–1.31). Corticosteroids were associated with a decrease in mortality (0.82; 95% CI, 0.69–0.96); the results of IL-6 antagonists were inconclusive. In patients directly admitted to the ICU, hydroxychloroquine, corticosteroids, and IL-6 antagonists were not associated with decreased mortality. Conclusions Both remdesivir and corticosteroids were associated with better outcomes in ward patients with COVID-19. Continuous evaluation of real-world treatment effects is needed.

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    Open Forum Infectious Diseases; NARCIS
    Article . 2022 . Peer-reviewed
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      Open Forum Infectious Diseases; NARCIS
      Article . 2022 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Carr, Ewan; Bendayan, Rebecca; Bean, Daniel; Stammers, Matt; +44 Authors

    Additional file 5: Figure S1. Calibration (logistic and LOESS curves) of supplemented NEWS2 model for 3-day ICU/death model at validation sites.

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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Authors: Arakelyan, Arsen; Avetyan, Diana;

    Sequencing of SARS-CoV-2 provides essential information on viral evolution, transmission, and epidemiology. In this study, we performed whole-genome sequencing of SARS-CoV-2 using nanopore and Illumina short-read sequencing to describe the circulation of the virus lineage in Armenia. This dataset contains Nextstrain configuration files, the auspice JSON file, BEAST output logs, and trees files, and resulting log and tree files as well as R scripts and data files used in phylogenetic and functional analyses.

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    ZENODO
    Dataset . 2022
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      ZENODO
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      ZENODO
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    Authors: Carr, Ewan; Bendayan, Rebecca; Bean, Daniel; Stammers, Matt; +44 Authors

    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.

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    Dataset . 2021
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    Dataset . 2021
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    Authors: Waagsbø, Bjørn; Tranung, Morten; Damås, Jan Kristian; Heggelund, Lars;

    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.

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    Collection . 2022
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