Corpus overview


Overview

MeSH Disease

Human Phenotype

Pneumonia (1024)

Fever (631)

Cough (507)

Hypertension (349)

Anxiety (277)


Transmission

age categories (2567)

Transmission (2371)

gender (1183)

fomite (1083)

contact tracing (854)


Seroprevalence
    displaying 5881 - 5890 records in total 12533
    records per page




    Quantifying the Immediate Effects of the COVID-19 Pandemic on Scientists

    Authors: Kyle R. Myers; Wei Yang Tham; Yian Yin; Nina Cohodes; Jerry G. Thursby; Marie C. Thursby; Peter E. Schiffer; Joseph T. Walsh; Karim R. Lakhani; Dashun Wang

    id:2005.11358v2 Date: 2020-05-22 Source: arXiv

    The COVID-19 pandemic has undoubtedly disrupted the scientific enterprise, but we lack empirical evidence on the nature and magnitude of these disruptions. Here we report the results of a survey of approximately 4,500 Principal Investigators (PIs) at U.S.- and Europe-based research institutions. Distributed in mid-April 2020, the survey solicited information about how scientists' work changed from the onset of the pandemic, how their research output might be affected in the near future, and a wide range of individuals' characteristics. Scientists report a sharp decline in time spent on research on average, but there is substantial heterogeneity with a significant share reporting no change or even increases. Some of this heterogeneity is due to field-specific differences, with laboratory-based fields being the most negatively affected, and some is due to gender TRANS, with female TRANS scientists reporting larger declines. However, among the individuals' characteristics examined, the largest disruptions are connected to a usually unobserved dimension: childcare. Reporting a young dependent is associated with declines similar in magnitude to those reported by the laboratory-based fields and can account for a significant fraction of gender TRANS differences. Amidst scarce evidence about the role of parenting TRANS in scientists' work, these results highlight the fundamental and heterogeneous ways this pandemic is affecting the scientific workforce, and may have broad relevance for shaping responses to the pandemic's effect on science and beyond.

    Advice from a systems-biology model of the Corona epidemics

    Authors: Hans V. Westerhoff; Alexey N. Kolodkin

    doi:10.21203/rs.3.rs-31144/v1 Date: 2020-05-22 Source: ResearchSquare

    Using standard systems biology methodologies a 14-compartment dynamic model was developed for the Corona virus epidemic. The model predicts that: (i) it will be impossible to limit lockdown intensity such that sufficient herd immunity develops for this epidemic to die down, (ii) the death MESHD toll from the SARS-CoV-2 virus decreases very strongly with increasing intensity of the lockdown, but (iii) the duration of the epidemic increases at first with that intensity and then decreases again, such that (iv) it may be best to begin with selecting a lockdown intensity beyond the intensity that leads to the maximum duration, (v) an intermittent lockdown strategy should also work and might be more acceptable socially and economically, (vi) an initially intensive but adaptive lockdown strategy should be most efficient, both in terms of its low number of casualties and shorter duration, (vii) such an adaptive lockdown strategy offers the advantage of being robust to unexpected imports of the virus, e.g. due to international travel TRANS, (viii) the eradication strategy may still be superior as it leads to even fewer deaths MESHD and a shorter period of economic, but should have the adaptive strategy as backup in case of unexpected infection MESHD imports (ix) earlier detection of infections MESHD is the most effective way in which the epidemic can be controlled, whilst waiting for vaccines.

    Exploring the spread dynamics of COVID-19 inMorocco

    Authors: Mohamed NAJI

    doi:10.1101/2020.05.18.20106013 Date: 2020-05-22 Source: medRxiv

    Despite some similarities of the dynamic of COVID-19 spread in Morocco and other countries, the infection MESHD, recovery and death MESHD rates remain very variable. In this paper, we analyze the spread dynamics of COVID-19 in Morocco within a standard susceptible-exposed-infected-recovered- death MESHD (SEIRD) model. We have combined SEIRD model with a time-dependent infection MESHD rate function, to fit the real data of i) infection MESHD counts and ii) death MESHD rates due to COVID-19, for the period between March 2nd and Mai 15th 2020. By fitting the infection MESHD rate, SEIRD model placed the infection MESHD peak on 04/24/2020 and could reproduce it to a large extent on the expense of recovery and death MESHD rates. Fitting the SEIRD model to death MESHD rates gives rather satisfactory predictions with a maximum of infections MESHD on 04/06/2020. Regardless of the low peak position, the peak position, confirmed cases TRANS and transmission TRANS rate were well reproduced.

    Co- infection MESHD of COVID-19 and Influenza A in A Hemodialysis Patient: A Case Report

    Authors: Ran Jing; Rama R Vunnam; Elizabeth Schnaubelt; Chad Vokoun; Allison Cushman-Vokoun; David Goldner; Srinivas R Vunnam

    doi:10.21203/rs.3.rs-31135/v1 Date: 2020-05-22 Source: ResearchSquare

    Background: Coronavirus disease MESHD 2019 (COVID-19) is caused by SARS-CoV-2, a novel coronavirus that was first discovered in Wuhan, China in December 2019. With the growing numbers of community spread cases worldwide, the World Health Organization (WHO) declared the COVID-19 outbreak as a pandemic on March 11. Like influenza viruses, SARS-CoV-2 is thought to be transmitted by contact, droplets, and fomites, and COVID-19 has a similar disease MESHD presentation to influenza. Here we present a case of influenza A and COVID-19 co- infection MESHD in a 60-year-old man with end-stage renal disease MESHD (ESRD) on hemodialysis.Case presentation: A 60-year-old man with ESRD on hemodialysis (HD) presented for worsening cough MESHD cough HP, shortness of breath, and diarrhea MESHD diarrhea HP. The patient first developed a mild fever MESHD fever HP (100 °F) during hemodialysis three days prior to presentation and has been experiencing worsening flu-like symptoms, including fever MESHD fever HP of up to 101.6 °F, non- productive cough HP cough MESHD, generalized abdominal pain MESHD abdominal pain HP, nausea MESHD nausea, vomiting HP, vomiting MESHD, and liquid green diarrhea MESHD diarrhea HP. He lives alone at home with no known sick contacts and denies any recent travel TRANS or visits to healthcare facilities other than the local dialysis center. Rapid flu test was positive for influenza A. Procalcitonin was elevated at 5.21 ng/mL with a normal white blood SERO cell (WBC) count. Computed tomography (CT) chest demonstrated multifocal areas of consolidation and extensive mediastinal and hilar adenopathy concerning for pneumonia MESHD pneumonia HP. He was admitted to the biocontainment unit of Nebraska Medicine for concerns of possible COVID-19 and was started on oseltamivir for influenza and vancomycin/cefepime for the probable bacterial cause of his pneumonia MESHD pneumonia HP and diarrhea MESHD diarrhea HP. GI pathogen panel and C. diff toxin assay were negative. On the second day of admission, initial nasopharyngeal swab came back positive for SARS-CoV-2 by RT-PCR. The patient received supportive care and resumed bedside hemodialysis in strict isolation, and eventually fully recovered from COVID-19.Conclusions: Our case demonstrated that co- infection MESHD of influenza and SARS-CoV-2 can occur in patients with no known direct exposure to COVID-19. The possibility of SARS-CoV-2 co- infection MESHD should not be overlooked even when other viruses including influenza can explain the clinical symptoms.

    A previously uncharacterized gene in SARS-CoV-2 illuminates the functional dynamics and evolutionary origins of the COVID-19 pandemic

    Authors: Chase W. Nelson; Zachary Ardern; Tony L. Goldberg; Chen Meng; Chen-Hao Kuo; Christina Ludwig; Sergios-Orestis Kolokotronis; Xinzhu Wei

    doi:10.1101/2020.05.21.109280 Date: 2020-05-22 Source: bioRxiv

    Understanding the emergence of novel viruses requires an accurate and comprehensive annotation of their genomes. Overlapping genes (OLGs) are common in viruses and have been associated with the origins of pandemics, but are still widely overlooked. We identify ORF3c, a novel OLG in SARS-CoV-2 that is also present in Guangxi pangolin-CoVs but not more closely related pangolin-CoVs (Guangdong) or bat-CoVs (RaTG13 and RmYN02). We then document evidence of translation from ribosome profiling and conduct an evolutionary analysis at three levels: between-species (n=21 betacoronavirus genomes), between-host (n=3,978 SARS-CoV-2 consensus sequences), and within-host (401 deeply sequenced SARS-CoV-2 samples). ORF3c has been independently identified and shown to elicit a strong antibody SERO response in COVID-19 patients. However, it has been misclassified as ORF3b, an unrelated gene in other SARS-related betacoronaviruses, leading to confusion MESHD confusion HP and unfounded functional inferences. Our results liken ORF3c to other viral accessory genes and stress the importance of studying OLGs.

    Reduced child TRANS maltreatment prevention service case openings during COVID-19

    Authors: Kelly Whaling; Alissa Der Sarkissian; Natalie A. Larez; Jill D. Sharkey; Michael A. Allen; Karen Nylund-Gibson

    doi:10.21203/rs.3.rs-30930/v1 Date: 2020-05-21 Source: ResearchSquare

    Severe acute respiratory syndrome MESHD coronavirus 2 (SARS-CoV-2; COVID-19), is a novel virus that has swept the world causing illness and death MESHD. Youth are at a heightened risk of experiencing increased rates of abuse given necessary measures required to slow the spread of the virus (e.g., indefinite school closures). We analyzed data from New York City’s Administration for Children’s Services (ACS) to investigate the frequency of child TRANS maltreatment prevention service case openings during this time of unprecedented stress. Two descriptive investigations were conducted. An examination of trend lines demonstrated that for 2013-2019, New York City’s new prevention case openings have consistently peaked in the month of March, for all seven years. New prevention case service openings in March 2020 do not peak, as they do in the preceding seven years. An independent samples t-test indicated that the frequency of case openings of March 2020 is significantly different than the frequency of case openings in March 2013-2019. Further, a Poisson regression model estimated that the odds of opening a new child TRANS maltreatment prevention case post-COVID-19 are 179% lower than opening a new child TRANS maltreatment case pre-COVID-19 (OR = -0.79, p < .001). These findings highlight the necessity of future research and innovation regarding child TRANS maltreatment prevention and intervention services during a global pandemic. This study has important implications for identification, prevention, and documentation for current support, and recommendations for local governments, community members, and practitioners are provided.

    Coswara -- A Database of Breathing, Cough MESHD Cough HP, and Voice Sounds for COVID-19 Diagnosis

    Authors: Neeraj Sharma; Prashant Krishnan; Rohit Kumar; Shreyas Ramoji; Srikanth Raj Chetupalli; Nirmala R.; Prasanta Kumar Ghosh; Sriram Ganapathy

    id:2005.10548v1 Date: 2020-05-21 Source: arXiv

    The COVID-19 pandemic presents global challenges transcending boundaries of country, race, religion, and economy. The current gold standard method for COVID-19 detection is the reverse transcription polymerase chain reaction (RT-PCR) testing. However, this method is expensive, time-consuming, and violates social distancing. Also, as the pandemic is expected to stay for a while, there is a need for an alternate diagnosis tool which overcomes these limitations, and is deployable at a large scale. The prominent symptoms of COVID-19 include cough MESHD cough HP and breathing difficulties. We foresee that respiratory sounds MESHD, when analyzed using machine learning techniques, can provide useful insights, enabling the design of a diagnostic tool. Towards this, the paper presents an early effort in creating (and analyzing) a database, called Coswara, of respiratory sounds MESHD, namely, cough MESHD cough HP, breath, and voice. The sound samples are collected via worldwide crowdsourcing using a website application. The curated dataset is released as open access. As the pandemic is evolving, the data collection and analysis is a work in progress. We believe that insights from analysis of Coswara can be effective in enabling sound based technology solutions for point-of-care diagnosis of respiratory infection MESHD, and in the near future this can help to diagnose COVID-19.

    A Machine Learning Solution Framework for Combatting COVID-19 in Smart Cities from Multiple Dimensions

    Authors: Ibrahim Abaker Targio Hashem; Absalom E Ezugwu; Mohammed A. Al-Garadi; Idris N. Abdullahi; Olumuyiwa Otegbeye; Queeneth O Ahman; Godwin C. E. Mbah; Amit K Shukla; Haruna Chiroma

    doi:10.1101/2020.05.18.20105577 Date: 2020-05-21 Source: medRxiv

    The spread of COVID-19 across the world continues as efforts are being made from multi-dimension to curtail its spread and provide treatment. The COVID-19 triggered partial and full lockdown across the globe in an effort to prevent its spread. COVID-19 causes serious fatalities with United States of America recording over 3,000 deaths MESHD within 24 hours, the highest in the world for a single day. In this paper, we propose a framework integrated with machine learning to curtail the spread of COVID-19 in smart cities. A novel mathematical model is created to show the spread of the COVID-19 in smart cities. The proposed solution framework can generate, capture, store and analyze data using machine learning algorithms to detect, prevent the spread of COVID-19, forecast next epidemic, effective contact tracing TRANS, diagnose cases, monitor COVID-19 patient, COVID-19 vaccine development, track potential COVID-19 patients, aid in COVID-19 drug discovery and provide better understanding of the virus in smart cities. The study outlined case studies on the application of machine learning to help in the fight against COVID-19 in hospitals in smart cities across the world. The framework can provide a guide for real world execution in smart cities. The proposed framework has the potential for helping national healthcare systems in curtailing the COVID-19 pandemic in smart cities.

    Who should we test for COVID-19?A triage model built from national symptom surveys

    Authors: Saar Shoer; Tal Karady; Ayya Keshet; Smadar Shilo; Hagai Rossman; Amir Gavrieli; Tomer Meir; Amit Lavon; Dmitry Kolobkov; Iris Kalka; Anastasia Godneva; Ori Cohen; Adam Kariv; Ori Hoch; Mushon Zer-Aviv; Noam Castel; Carole Sudre; Anat Ekka Zohar; Angela Irony; Timothy Spector; Benjamin Geiger; Dorit Hizi; Varda Shalev; Ran Balicer; Eran Segal

    doi:10.1101/2020.05.18.20105569 Date: 2020-05-21 Source: medRxiv

    The gold standard for COVID-19 diagnosis is detection of viral RNA in a reverse transcription PCR test. Due to global limitations in testing capacity, effective prioritization of individuals for testing is essential. Here, we devised a model that estimates the probability of an individual to test positive for COVID-19 based on answers to 9 simple questions regarding age TRANS, gender TRANS, presence of prior medical conditions, general feeling, and the symptoms fever MESHD fever HP, cough MESHD cough HP, shortness of breath, sore throat and loss of taste or smell, all of which have been associated with COVID-19 infection MESHD. Our model was devised from a subsample of a national symptom survey that was answered over 2 million times in Israel over the past 2 months and a targeted survey distributed to all residents of several cities in Israel. Overall, 43,752 adults TRANS were included, from which 498 self-reported as being COVID-19 positive. We successfully validated the model on held-out individuals from Israel where it achieved a positive predictive value SERO (PPV) of 46.3% at a 10% sensitivity SERO and demonstrated its applicability outside of Israel by further validating it on an independently collected symptom survey dataset from the U.K., U.S. and Sweden, where it achieved a PPV of 34.7% at 10% sensitivity SERO. Moreover, evaluating the model's performance SERO on this latter independent dataset on entries collected one week prior to the PCR test and up to the day of the test we found the highest performance SERO on the day of the test. As our tool can be used online and without the need of exposure to suspected patients, it may have worldwide utility in combating COVID-19 by better directing the limited testing resources through prioritization of individuals for testing, thereby increasing the rate at which positive individuals can be identified and isolated.

    Symptom extraction from the narratives of personal experiences with COVID-19 on Reddit

    Authors: Curtis Murray; Lewis Mitchell; Jonathan Tuke; Mark Mackay

    id:2005.10454v1 Date: 2020-05-21 Source: arXiv

    Social media discussion of COVID-19 provides a rich source of information into how the virus affects people's lives that is qualitatively different from traditional public health datasets. In particular, when individuals self-report their experiences over the course of the virus on social media, it can allow for identification of the emotions each stage of symptoms engenders in the patient. Posts to the Reddit forum r/COVID19Positive contain first-hand accounts from COVID-19 positive patients, giving insight into personal struggles with the virus. These posts often feature a temporal structure indicating the number of days after developing symptoms the text refers to. Using topic modelling and sentiment analysis, we quantify the change in discussion of COVID-19 throughout individuals' experiences for the first 14 days since symptom onset TRANS. Discourse on early symptoms such as fever MESHD fever HP, cough MESHD cough HP, and sore throat was concentrated towards the beginning of the posts, while language indicating breathing issues peaked around ten days. Some conversation around critical cases was also identified and appeared at a roughly constant rate. We identified two clear clusters of positive and negative emotions associated with the evolution of these symptoms and mapped their relationships. Our results provide a perspective on the patient experience of COVID-19 that complements other medical data streams and can potentially reveal when mental health issues might appear.

The ZB MED preprint Viewer preVIEW includes all COVID-19 related preprints from medRxiv and bioRxiv, from ChemRxiv, from ResearchSquare, from arXiv and from Preprints.org and is updated on a daily basis (7am CET/CEST).

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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