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9,674 results for “COVID-19”
COVID-19 Data
<p>COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University</p>
Data for manuscript "Prevalence in News Media of two Competing Hypotheses about COVID-19 Origins"
<p>The Covid-19 pandemic has been one of the most disruptive and painful phenomena of the last few decades. As of July 2021, the origins of the SARS-CoV-2 virus that caused the outbreak remain a mystery. This work analyzes the prevalence in news media articles of two popular hypotheses about SARS-CoV-2 virus origins: the natural emergence and the lab-leak hypotheses. </p> <p>This data set contains frequency counts of target words in news and opinion articles from 12 popular news media outlets. The target words are listed in the associated manuscript and are mostly words associated with the Covid-19 pandemic. </p> <p>The list of compressed files in this data set is listed next:</p> <p>targetWordsInArticlesCounts.rar contains counts of target words in outlets articles as well as total counts of words in articles</p> <p>targetWordsFrequencies.rar daily, weekly, monthly word frequencies</p> <p>wordEmbeddingModels.rar monthly embedding models of news outlets content</p> <p>analysisScripts.rar analysis notebooks</p> <p>The textual content of news and opinion articles from the outlets is available in the outlet's online domains and/or public cache repositories such as Google cache, The Internet Wayback Machine, and Common Crawl. We used derived word frequency counts from these sources. Textual content included in our analysis is circumscribed to articles headlines and main body of text of the articles and does not include other article elements such as figure captions.</p> <p>Targeted textual content was located in HTML raw data using outlet specific XPath expressions. Tokens were lowercased prior to estimating frequency counts. </p> <p>Yearly frequency usage of a target word in an outlet in any given temporal interval ( daily, weekly, monthly) was estimated by dividing the total number of occurrences of the target word in all articles of a given temporal interval by the number of all words in all articles of that temporal interval. This method of estimating frequency accounts for variable volume of total article output over time.</p> <p>In a small percentage of articles, outlet specific XPath expressions might fail to properly capture the content of the article due to the heterogeneity of HTML elements and CSS styling combinations with which articles text content is arranged in outlets online domains. As a result, the total and target word counts metrics for a small subset of articles are not precise. In a random sample of articles and outlets, manual estimation of target words counts overlapped with the automatically derived counts for over 90% of the articles. Most of the incorrect frequency counts are minor deviations from the actual counts such as for instance counting a word in an article footnote encouraging article readers to find related articles and that the XPath expression might mistakenly include as the content of the article main text. Some additional outlet-specific inaccuracies that we could identify occurred in the WSJ where in less than 5% of the articles XPath expressions failed to capture the article's main text content. Other outlets articles samples sizes might not be comprehensive but, to the best of our knowledge, they are representative and include tens of thousands of articles per outlet/year. To conclude, in a data analysis of over 1.5 million articles, we cannot manually check the correctness of frequency counts for every single article and hundred percent accuracy at capturing articles’ content is elusive due to the small number of difficult to detect boundary cases such as incorrect HTML markup syntax in online domains. Overall however, we are confident that our frequency metrics are representative of word prevalence in print news media content (see Figure 1 of main manuscript for supporting evidence).</p> <p> </p> <p> </p>
How Did the COVID-19 Crisis Affect Different Types of Workers in the Developing World?
<p>Video presentation of paper submission 15 for the Data for Policy 2021 Conference with the main results of "HOW DID THE COVID-19 CRISIS AFFECT DIFFERENT TYPES OF WORKERS IN THE DEVELOPING WORLD?" research paper emanating from the JobsWatch World Bank project to monitor labor market outcomes across 40 developing countries in real time identifying women, youth, less educated and urban workers as bearing the brunt of the burden of the pandemic job and wage losses.</p>
SARS-CoV-2 viral loads across the upper and lower respiratory tract, sex, disease severity and age groups for adult and pediatric COVID-19
<p>This dataset shows SARS-CoV-2 respiratory viral loads (viral RNA concentration in the respiratory tract) in the upper and lower respiratory tract for age, sex and COVID-19 severity groups. The data were obtained from a systematic review. The model outputs show the Weibull distributions, case percentiles, and sensitivity & specificity when using SARS-CoV-2 viral load (URT or LRT) as a prognostic indicator. See our paper for more information.</p>
Clinical outcome prediction in COVID-19 patients by lymphocyte subsets analysis and monocytes' iTNF-α expression
<p>Raw Box & Whiskers plot related to a manuscript submitted to "Biology" journal - MDPI - https://www.mdpi.com/journal/biology - https://doi.org/10.3390/biology10080735</p> <p><strong>Manuscript Title</strong>: Clinical outcome prediction in COVID-19 patients by lymphocyte subsets analysis and monocytes’ iTNF-α expression</p> <p><strong>Authors: G</strong>abriele Madonna <sup>1†</sup>, Silvia Sale <sup>2†</sup>, Mariaelena Capone <sup>1</sup>, Chiara De Falco <sup>2</sup>, Valentina Santocchio <sup>2</sup>, Tiziana Di Matola <sup>2</sup>, Giuseppe Fiorentino <sup>3</sup>, Caterina Pirozzi <sup>2</sup>, Anna D’Antonio <sup>2</sup>, Rocco Sabatino <sup>2</sup>, Lidia Atripaldi<sup>4</sup>, Umberto Atripaldi <sup>4</sup>, Marcello Raffone <sup>5</sup>, Marcello Curvietto<sup> 1</sup>, Antonio Maria Grimaldi <sup>1</sup>, Vito Vanella <sup>1</sup>, Lucia Festino <sup>1</sup>, Luigi Scarpato <sup>1</sup>, Marco Palla <sup>1</sup>, Michela Spatarella <sup>6</sup>, Francesco Perna <sup>7</sup>, Pellegrino Cerino <sup>8</sup>, Gerardo Botti <sup>9</sup>, Roberto Parrella <sup>10</sup>, Vincenzo Montesarchio <sup>11</sup>, Paolo Antonio Ascierto <sup>1††* </sup>and Luigi Atripaldi <sup>2††</sup></p> <p><strong>Affiliations:</strong></p> <p>1 Melanoma, Cancer Immunotherapy and Development Therapeutics Unit, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale, Napoli, Italy</p> <p>2 UOC Biochimica Clinica, AORN Ospedali dei Colli - Monaldi – Cotugno - CTO, Napoli, Italy</p> <p>3 UOC Fisiopatologia e Riabilitazione respiratoria, AORN Ospedali dei Colli - Monaldi – Cotugno - CTO, Napoli, Italy</p> <p>4 University of Campania "Luigi Vanvitelli", Naples, Italy</p> <p>5 UOC Microbiologia e Virologia, AORN Ospedali dei Colli - Monaldi – Cotugno - CTO, Napoli, Italy</p> <p>6 UOSD di Farmacia, AORN Ospedali dei Colli - Monaldi – Cotugno - CTO, Napoli, Italy</p> <p>7 Università degli Studi di Napoli "Federico II", Naples, Italy.</p> <p>8 Istituto Zooprofilattico Sperimentale del Mezzogiorno, Portici (Na), Italy.</p> <p>9 Scientific Direction, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale, Napoli, Italy</p> <p>10 UOC Malattie Infettive ad Indirizzo Respiratorio, AORN Ospedali dei Colli - Monaldi – Cotugno -CTO, Napoli, Italy</p> <p>11 UOC Oncologia, AORN Ospedali dei Colli - Monaldi – Cotugno - CTO, Napoli, Italy</p> <p>†These authors have contributed equally to this work and share first authorship</p> <p>††These authors have contributed equally to this work and share senior authorship</p> <p>*Correspondence:</p> <p><strong>Abstract of submitted Manuscript:</strong> T</p> <p>In December 2019 a novel coronavirus, “SARS-CoV-2”, was recognized as the cause of Coronavirus disease-2019 (COVID-19-disease). Several studies have explored the changes and the role of inflammatory cells and cytokines in the immunopathogenesis of disease, but until today the results have been controversial. Based on these premises, we carried out a retrospective assessment of monocytes’ intracellular TNF-α expression (iTNF-α) and on frequencies of lymphocyte sub-populations in twenty-five patients with moderate/severe COVID-19-disease. We found lymphopenia in all COVID-19 infected subjects compared with healthy subjects. On initial observation, in patients with favorable outcome we detected high absolute eosinophils count and high CD4+/CD8+ T lymphocytes ratio, while in the exitus group we observed high neutrophils and CD8+ T lymphocytes counts. During infection, in patients with favorable outcome we observed a rise in lymphocyte count, in monocytes and in Treg lymphocytes counts, in CD4+ and in CD8+ T lymphocytes count but a reduction in CD4+/CD8+ T lymphocytes ratio. Instead, in the exitus group we observed a reduction in Treg lymphocytes counts and a decrease in iTNF-α expression. Our preliminary findings point to a modulation of the different cellular mediators of immune system, which probably have a key role in the outcome of the COVID-19-disease.</p> <p><strong>Funding:</strong> This work was supported by Grants from “Regione Campania” through “POR FESR CAMPANIA 2014-2020”, CUP H64I20000300002.</p> <p><strong>Cite</strong>: Madonna, G.; Sale, S.; Capone, M.; De Falco, C.; Santocchio, V.; Di Matola, T.; Fiorentino, G.; Pirozzi, C.; D’Antonio, A.; Sabatino, R.; Atripaldi, L.; Atripaldi, U.; Raffone, M.; Curvietto, M.; Grimaldi, A.M.; Vanella, V.; Festino, L.; Scarpato, L.; Palla, M.; Spatarella, M.; Perna, F.; Cerino, P.; Botti, G.; Parrella, R.; Montesarchio, V.; Ascierto, P.A.; Atripaldi, L. Clinical Outcome Prediction in COVID-19 Patients by Lymphocyte Subsets Analysis and Monocytes’ iTNF-α Expression. <em>Biology</em> <strong>2021</strong>, <em>10</em>, 735. doi: <a href="https://doi.org/10.3390/biology10080735">10.3390/biology10080735</a></p> <p> </p>
COV-BHP - Psychological Impact of the COVID-19 Outbreak on Health Professionals
<p>The COVID-19 pandemic had a massive impact on health care systems,<br> increasing the risks of psychological distress in health professionals. This database includes data from a study which assessed the prevalence of burnout and psychopathological conditions in health professionals working in a health institution in the Northern Italy, and identified socio-demographic, work-related and psychological predictors of burnout. Health professionals working in the hospitals of the Istituto Auxologico Italiano were asked to participate to an online anonymous survey investigating socio-demographic data, COVID-19 emergency-related work and psychological factors, state anxiety, psychological distress, post-traumatic symptoms and burnout.</p>
Intragenerational Social Mobility and Preventive Behaviors regarding COVID-19: A Case Study of the Slum and Non-Slum Peoples in Dhaka City
<p>Social Mobility and Preventive Behaviors regarding COVID-19 among the Slum and Non-Slum Peoples in Dhaka City</p>
SGLT2-Inhibition reverts urinary peptide changes associated with severe COVID-19: an in-silico proof-of-principle of proteomics-based drug repurposing
<p>Severe COVID-19 is reflected by significant changes in urine peptides. Based on this observation, a clinical test predicting COVID-19 severity, CoV50, was developed and registered as in vitro diagnostic in Germany. We have hypothesized that molecular changes displayed by CoV50, likely reflective of endothelial damage, may be reversed by specific drugs. Such an impact by a drug could indicate potential benefits in the context of COVID-19. To test this hypothesis, urinary peptide data from patients without COVID-19 prior to and after drug treatment were collected from the human urinary proteome database. The drugs chosen were selected based on availability of sufficient number of participants in the dataset (n>20) and potential value of drug therapies in the treatment of COVID-19 based on reports in the literature. In these participants without COVID-19, spironolactone did not demonstrate a significant impact on CoV50 scoring. Empagliflozin treatment resulted in a significant change in CoV50 scoring, indicative of a potential therapeutic benefit. The study serves as a proof-of-principle for a drug repurposing approach based on human urinary peptide signatures. The results support the initiation of a randomised control trial testing a potential positive effect of empagliflozin for severe COVID-19, possibly via endothelial protective mechanisms.</p>
Environmental Education During the COVID-19 Pandemic Dataset
<p>Data files that support the capstone thesis <em>Environmental Education during the COVID-19 Pandemic</em> by Margaret Janz.</p> <p> </p> <p>The COVID-19 pandemic that hit the United States in March 2020 quickly caused the entire nation to rethink how we work and how we approach education. Informal environmental education in particular faced unique challenges during this time yet found ways to adapt their educational programming. This thesis will explore the questions: How did organizations alter and adapt their programming to meet public health guidelines during the pandemic? and What successes and challenges did organizations face in offering these programs? To answer these questions, a survey was distributed to organizations that offer environmental education programs. Results echo and expand on the existing literature on pandemic education. Organizations offered many virtual programs both synchronously and asynchronously and also found new ways to offer in person events. Programs that involved some interaction with other people and those that took place in person or outdoors were most successful, while asynchronous virtual materials were considered less so. Organizations faced many challenges in offering programming including financial barriers, technology troubles, and difficulty staying current on public health recommendations. Despite the difficulties and learning losses, respondents felt there may have been some benefits to the changes in their programming and many will continue to offer their adapted programs in the future.</p>
T cell dysregulation associated with COVID-19 severity and progression
<p>The dataset refers to a study the objective of which was to retrospectively investigate the immune dysregulation associated with COVID-19 severity and clinical course in hospitalised patients. Immunophenotyipc analyses were performed by multi-colour flow cytometry on whole blood samples, the systemic concentration of selected cytokines was determined in serum samples.</p> <p>The dataset contains de-identified demographic and clinical information, as well as experimental raw data.</p>
Covid19Dynamics/2ndSurges: Ascertaining the initiation of COVID-19 second surges in Europe and the Northeast United States
<p>First release of data used in ascertaining the initiation of COVID-19 second surges in Europe and the Northeast United States</p>
IMC dataset: duodenal biopsies of COVID-19 and Control patients
<p>An Imaging Mass Cytometry dataset containing .mcd files of duodenal biopsies from COVID-19 and Control patients. The peer-reviewed publication for this dataset has been published in Mucosal Immunology, and can be accessed here: https://www.nature.com/articles/s41385-021-00437-z. Please cite this when using the dataset.</p>
Data from: Fear of infection and the common good: COVID-19 and the first Italian lockdown
<p>The Excel file contains the data for the paper "Fear of infection and the common good: COVID-19 and the first Italian lockdown". This paper is currently under review. The original data came from the paper "Flesia L, Monaro M, Mazza C, Fietta V, Colicino E, Segatto B, et al. Predicting Perceived Stress Related to the Covid-19 Outbreak through Stable Psychological Traits and Machine Learning Models. J Clin Med. 2020;9(10)."</p>
Artificial Intelligence and COVID-19 using chest CT scan and chest X-ray images: Machine Learning and Deep Learning Approaches for Diagnosis and Treatment
<p>We uploaded the Table of included articles in the systematic review "Artificial Intelligence and COVID-19 using chest CT scan and chest X-ray images: Machine Learning and Deep Learning Approaches for Diagnosis and Treatment"</p>
Nudging healthcare professionals to improve treatment of COVID-19: a narrative review
<p>The dataset is a complete description of all included and excluded studies in a narrative review synthesizing the available literature 2010-2020 on how nudging techniques can be used to affect the behavior of HCPs in clinical settings in order to see if these can be useful in the prevention and treatment of COVID-19. </p>
Early warning signal reliability varies with COVID-19 waves
<p><strong>Abstract</strong></p> <p>Early warning signals (EWSs) aim to predict changes in complex systems from phenomenological signals in time series data. These signals have recently been shown to precede the emergence of disease outbreaks, offering hope that policy makers can make predictive rather than reactive management decisions. Here, using a novel, sequential analysis in combination with daily COVID-19 case data across 24 countries, we suggest that composite EWSs consisting of variance, autocorrelation, and skewness can predict non-linear case increases, but that the predictive ability of these tools varies between waves based upon the degree of critical slowing down present. Our work suggests that in highly monitored disease time series such as COVID-19, EWSs offer the opportunity for policy makers to improve the accuracy of urgent intervention decisions but best characterise hypothesised critical transitions.</p> <p><strong>Dataset</strong></p> <p>The deposited dataset contains scripts used in the early warning signal and generalised additive model analysis, the generation of figures, and the custom R functions underpinning the work. Raw COVID-19 case data is also provided if users prefer to access files directly rather than sourcing from the host repositories (all credit is provided to the original publishers).</p>
Saudi scholars' contribution to the COVID-19 literature: A bibliometric study
<p>This study aims to explore Saudi researchers' academic performance on the topic of COVID-19. In addition, the paper attempts to find the contribution of Saudi Arabia in the area and how Saudi Arabia is doing compared to other Arab countries. The study results are expected to help understand the current role of Saudi Arabia in fighting COVID-19.</p>
University students' adherence and vaccination attitude during the COVID-19 pandemic
<p>Data on university students' adherence and vaccination attitudes, accompanying the manuscript a manuscript (in press). </p> <p>Data collection took place between November 23rd and December 21st, 2020.</p> <p>The sample consists of German-speaking university students, recruited at Innsbruck Universities.</p> <p> </p> <p>Scale Sources: <br> Reactance - COSMO COVID-19 Snapshot Monitoring <br> Betsch, C., Korn, L., Felgendreff, L., Eitze, S., Schmid, P., Sprengholz, P., Wieler, L., Schmich, P., Stollorz, V., Ramharter, M., Bosnjak, M., Omer, S., Thaiss, H., Bock, F. de, & Rüden, U. von (2020). <em>Covid-19 Snapshot Monitoring (COSMO Germany) - Welle 27</em>. PsychArchives. https://doi.org/10.23668/PSYCHARCHIVES.4381</p>
Efecto de las contribuciones sobre COVID-19 en el factor de impacto de las revistas médicas latinoamericanas
<p>Se muestra el efecto de las citas provenientes de documentos COVID en el factor de impacto de las revistas médicas latinoamericanas. </p>
Comparative analysis of health authorities spokesperson and health influencer during the COVID-19 pandemic: A case in Indonesia
<p><span><strong>Background</strong>: </span><span>Concerns over an infodemic following a surge in health misinformation circulating on social media sets out the government's priority for Indonesia. Given the urgent work on the coronavirus disease 2019 (COVID-19) response, the government collaborated with health-related spokespersons and influencers with a medical background by starting a COVID-19 public education campaign on social media. A collaborative initiative involved health spokespersons from government and non-government to clarify misinformation about COVID-19.</span></p> <p><span><strong>Methods</strong>: </span><span>The primary purpose of this research is to compare government and non-government spokespersons by examining their role in educating about the COVID-19 vaccine and health services. This study employed comparative factor analysis and non-participatory observation toward the media activity of spokespersons in Indonesia. Using a questionnaire, this study examines the dimensions of public campaigns, risk communication, health and emergency, leadership, and communication from Indonesian spokespersons. The data collection was conducted in two stages. The first stage was a pilot study that collected data from 102 respondents, the second stage collected data from 276 respondents.</span></p> <p><span><strong>Results</strong>: </span><span>Findings show that utilizing the spokesperson is important due to its capabilities of reaching diverse audiences, and improving public engagement, trustworthiness, and credibility.</span></p> <p><span><strong>Conclusions</strong>: </span><span>With the combination of health authorities spokespersons and health influencers in Indonesia, this study provides valuable insights for communication management in developing and supporting the role of health authorities from the government, non-government as well as medical sectors.</span></p>
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