Corpus overview


Overview

MeSH Disease

Human Phenotype

Falls (59)

Fever (6)

Hypertension (5)

Cough (4)

Pneumonia (4)


Transmission

Seroprevalence
    displaying 1 - 10 records in total 59
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    Prediction of Covid-19 Infections MESHD Through December 2020 for 10 US States Using a Two Parameter Transmission TRANS Model Incorporating Outdoor Temperature and School Re-Opening Effects

    Authors: Ty A Newell

    doi:10.1101/2020.08.06.20169896 Date: 2020-08-07 Source: medRxiv

    Covid-19 infection MESHD case predictions (total cases) are made for August through December 2020 for 10 US States (NY, WA, GA, IL, MN, FL, OH, MI, CA, and NC). A two-parameter model based on social distance index (SDI) and disease MESHD transmission TRANS efficiency (G) parameters is used to characterize SARS-CoV-2 disease MESHD disease spread TRANS spread. Current lack of coherent and coordinated US policy causes the US to follow a linear infection MESHD growth path with a limit cycle behavior that modulates the US between accelerating and decaying infection MESHD growth on either side of a linear growth path boundary. Four prediction cases are presented: 1) No school re-openings; fall HP season temperature effect 2) No school re-openings; no fall HP season temperature effect 3) School re-openings; fall HP season temperature effect 4) School re-openings; no fall HP season temperature effect Fall HP outdoor temperatures, in contrast to the 1918 pandemic, are predicted to be beneficial for dampening SARS-CoV-2 transmission TRANS in States as they pass through swing season temperature range of 70F to 50F. Physical re-opening of schools in September are predicted to accelerate infections MESHD. States with low current infectious case numbers (eg, NY) are predicted to be minimally impacted while States with high current infectious case numbers (eg, CA and FL) will be significantly impacted by school re-openings. Updated infection MESHD predictions will be posted monthly (Sept, Oct, Nov, Dec) with adjustments based on actual trends in SDI and G. Assessments related to outdoor temperature impact, school re-openings, and other public gathering re-openings will be discussed in updated reports.

    The effect of school closures and reopening strategies on COVID-19 infection MESHD dynamics in the San Francisco Bay Area: a cross-sectional survey and modeling analysis

    Authors: Jennifer R Head; Kristin Andrejko; Qu Cheng; Philip A Collender; Sophie Phillips; Anna Boser; Alexandra K Heaney; Christopher M Hoover; Sean L Wu; Graham R Northrup; Karen Click; Robert Harrison; Joseph A Lewnard; Justin V Remais

    doi:10.1101/2020.08.06.20169797 Date: 2020-08-07 Source: medRxiv

    Background Large-scale school closures have been implemented worldwide to curb the spread of COVID-19. However, the impact of school closures and re-opening on epidemic dynamics remains unclear. Methods We simulated COVID-19 transmission TRANS dynamics using an individual-based stochastic model, incorporating social- contact data TRANS of school- aged TRANS children TRANS during shelter-in-place orders derived from Bay Area (California) household surveys. We simulated transmission TRANS under observed conditions and counterfactual intervention scenarios between March 17-June 1, and evaluated various fall HP 2020 K-12 reopening strategies. Findings Between March 17-June 1, assuming children TRANS <10 were half as susceptible to infection MESHD as older children TRANS and adults TRANS, we estimated school closures averted a similar number of infections MESHD (13,842 cases; 95% CI: 6,290, 23,040) as workplace closures (15,813; 95% CI: 9,963, 22,617) and social distancing measures (7,030; 95% CI: 3,118, 11,676). School closure effects were driven by high school and middle school closures. Under assumptions of moderate community transmission TRANS, we estimate that fall HP 2020 school reopenings will increase symptomatic illness among high school teachers (an additional 40.7% expected to experience symptomatic infection MESHD, 95% CI: 1.9, 61.1), middle school teachers (37.2%, 95% CI: 4.6, 58.1), and elementary school teachers (4.1%, 95% CI: -1.7, 12.0). Results are highly dependent on uncertain parameters, notably the relative susceptibility and infectiousness of children TRANS, and extent of community transmission TRANS amid re-opening. The school-based interventions needed to reduce the risk to fewer than an additional 1% of teachers infected varies by grade level. A hybrid-learning approach with halved class sizes of 10 students may be needed in high schools, while maintaining small cohorts of 20 students may be needed for elementary schools. Interpretation Multiple in-school intervention strategies and community transmission TRANS reductions, beyond the extent achieved to date, will be necessary to avoid undue excess risk associated with school reopening. Policymakers must urgently enact policies that curb community transmission TRANS and implement within-school control measures to simultaneously address the tandem health crises posed by COVID-19 and adverse child TRANS health and development consequences of long-term school closures.

    Who is Left Behind? Altruism of Giving, Happiness and Mental Health during the Covid-19 Period in the UK

    Authors: Eleftherios Giovanis; Oznur Ozdamar

    doi:10.21203/rs.3.rs-53072/v1 Date: 2020-08-03 Source: ResearchSquare

    The UK government has decided to implement lockdown measures in the end of March 2020 as a response to the outbreak and spread of the Covid-19 pandemic. As a consequence, households have experienced job losses and a significant drop in their finances and living standards. During these unprecedented and difficult times, people provide financial assistance to those who are in need and have to cope with falls HP in their living standards. In this study we are interested to investigate the subjective well-being (SWB), which is expressed by mental health and components of general happiness, of the givers rather than of receivers. We apply a difference-in-differences (DiD) framework to investigate the impact of altruism on the givers’ SWB in the UK. Altruism is denoted by transfers made to adult TRANS children TRANS, parents TRANS, siblings, and friends TRANS. Using the DiD estimator and the estimated coefficient of the household income we calculate the implicit willingness-to-pay (WTP) for altruism. We perform various regressions by gender TRANS and racial-ethnic background using data from the UK Household Longitudinal Study (UKHLS). The analysis shows that altruistic behaviours impact different domains of SWB between men and women, as well as, among people with different racial-ethnic background. 

    Fighting COVID-19 spread among nursing home residents even in absence of molecular diagnosis: a retrospective cohort study.

    Authors: Alessio Strazzulla; Paul Tarteret; Maria Concetta Postorino; Marie Picque; Astrid de Pontfarcy; Nicolas Vignier; Catherine Chakvetadze; Coralie Noel; Cecile Drouin; Zine Eddine Benguerdi; Sylvain Diamantis

    doi:10.21203/rs.3.rs-51305/v1 Date: 2020-07-30 Source: ResearchSquare

    Background Access to molecular diagnosis was limited out-of-hospital in France during the 2020 coronavirus disease MESHD 2019 (COVID-19) epidemic. This study describes the evolution of COVID-19 outbreak in a nursing home in absence of molecular diagnosis. Methods A monocentric prospective study was conducted in a French nursing home from March 17th, 2020 to June 11th, 2020. Because of lack of molecular tests for severe acute respiratory syndrome MESHD 2 (SARS-Cov2) infection MESHD, probable COVID-19 cases were early identified considering only respiratory and not-respiratory symptoms and therefore preventing measures and treatments were enforced. Once available, serology tests were performed at the end of the study.A chronologic description of new cases and deaths MESHD was made together with a description of COVID-19 symptoms. Data about personal characteristics and treatments were collected and the following comparisons were performed: i) probable COVID-19 cases vs asymptomatic TRANS residents; ii) SARS-Cov2 seropositive residents vs seronegative residents. Results Overall, 32/66 (48.5%) residents and 19/39 (48.7%) members of health-care personnel were classified as probable COVID-19 cases. A total of 34/61 (55.7%) tested residents resulted seropositive. Death MESHD occurred in 4/66 (6%) residents. Diagnosis according to symptoms had 65% of sensitivity SERO, 78% of specificity, 79% of positive predictive value SERO and 64% of negative predictive value SERO.In resident population, the following symptoms were registered: 15/32 (46.8%) lymphopenia MESHD lymphopenia HP, 15/32 (46.8%) fever MESHD fever HP, 8/32 (25%) fatigue MESHD fatigue HP, 8/32 (25%) cough MESHD cough HP, 6/32 (18.8%) diarrhoea, 4/32 (12.5%) severe respiratory distress HP requiring oxygen therapy, 4/32 (12.5%) fall HP, 3/32 (9.4%) conjunctivitis MESHD conjunctivitis HP, 2/32 (6.3%) abnormal pulmonary noise at chest examination and 2/32 (6,25%) abdominal pain MESHD abdominal pain HP. Probable COVID-19 cases were older (81.3 vs 74.9; p=0.007) and they had higher prevalence SERO of atrial fibrillation MESHD atrial fibrillation HP (8/32, 25% vs 2/34, 12%; p=0.030); insulin treatment (4/34, 12% vs 0, 0%; p=0.033) and positive SARS-Cov2 serology (22/32, 69% vs 12/34, 35%; p=0.001) than asymptomatic TRANS residents. Seropositive residents had lower prevalence SERO of diabetes (4/34, 12% vs 9/27, 33%; p=0.041) and angiotensin-converting-enzyme inhibitors’ intake (1/34, 1% vs 5/27, 19%; p=0.042). Conclusions During SARS-Cov2 epidemic, early detection of respiratory and not-respiratory symptoms allowed to enforce extraordinary measures. They achieved limiting contagion and deaths MESHD among nursing home residents, even in absence of molecular diagnosis.

    Unemployment of Unskilled Labor due to COVID-19 led Restriction on Migration and Trade

    Authors: Biswajit Mandal; Saswati Chaudhuri; Alaka Shree Prasad

    doi:10.21203/rs.3.rs-45853/v1 Date: 2020-07-20 Source: ResearchSquare

    To combat COVID-19 the entire world has resorted to global lockdown implying restriction on international labor migration and trade. This paper aims to check the effect of such restrictions on the unemployment of unskilled labor in the source country. In competitive general equilibrium framework with three goods and four factors restriction on migration raises unemployment for given factor intensity. The results remain same even in a slightly different structure of the economy. In case of trade restriction, however, the rise or fall HP in unemployment depends on both the structure of the economy and the factor intensity assumption.

    The Impact of the COVID-19 Epidemic on Patterns of Attendance at Emergency MESHD Departments in Two Large London Hospitals: An Observational Study

    Authors: Michaela A C Vollmer; Sreejith Radhakrishnan; Mara D Kont; Seth Flaxman; Samir J Bhatt; Ceire Costelloe; Kate Honeyford; Paul Aylin; Graham Cooke; Julian Redhead; Alison Sanders; Helen Mangan; Peter J White; Neil Ferguson; Katharina Hauck; Shevanthi Nayagam; Pablo N Perez-Guzman

    doi:10.21203/rs.3.rs-45465/v1 Date: 2020-07-18 Source: ResearchSquare

    Background Hospitals in England have undergone considerable change to address the surge in demand imposed by the COVID-19 epidemic. The impact of this on emergency MESHD department (ED) attendances is unknown, especially for non-COVID-19 related emergencies MESHD.Methods We calibrated auto-regressive integrated moving average time-series models of ED attendances to Imperial College Healthcare NHS Trust (ICHNT) using historic (2015–2019) data. Forecasted trends were compared to present year ICHNT data for the period between March 12 (when England implemented the first COVID-19 public health measure) and May 31. We compared ICHTN trends with publicly available regional and national data. Lastly, we compared emergency MESHD admissions and in-hospital mortality at ICHNT during the present year to a historic 5-year average.Results ED attendances at ICHNT decreased by 35%, in keeping with the trend for ED attendances across all England regions, which fell HP by approximately 50%. For ICHNT, the decrease in attendances was mainly amongst those aged < 65 years and those arriving by their own means (e.g. personal or public transport). Increasing distance from postcode of residence to hospital was a significant predictor of reduced attendances. Non-COVID related emergency MESHD admissions to hospital after March 12 fell HP by 48%; there was an indication of a non-significant increase in non-COVID-19 crude mortality risk (RR 1.13, 95%CI 0.94–1.37, p = 0.19).Conclusions Our study finds strong evidence that emergency MESHD healthcare seeking has drastically changed across the population in England. At ICHNT, we find that a larger proportion arrived by ambulance and that hospitalisation outcomes of non-COVID patients did not differ from previous years. The extent to which these findings relate to ED avoidance behaviours compared to having sought alternative emergency MESHD health services outside of hospital remains unknown. National analyses and strategies to streamline emergency MESHD services in England going forward are urgently needed.

    Probabilistic Neighbourhood Component Analysis: Sample Efficient Uncertainty Estimation in Deep Learning

    Authors: Ankur Mallick; Chaitanya Dwivedi; Bhavya Kailkhura; Gauri Joshi; T. Yong-Jin Han

    id:2007.10800v1 Date: 2020-07-18 Source: arXiv

    While Deep Neural Networks (DNNs) achieve state-of-the-art accuracy in various applications, they often fall HP short in accurately estimating their predictive uncertainty and, in turn, fail to recognize when these predictions may be wrong. Several uncertainty-aware models, such as Bayesian Neural Network (BNNs) and Deep Ensembles have been proposed in the literature for quantifying predictive uncertainty. However, research in this area has been largely confined to the big data regime. In this work, we show that the uncertainty estimation capability of state-of-the-art BNNs and Deep Ensemble models degrades significantly when the amount of training data is small. To address the issue of accurate uncertainty estimation in the small-data regime, we propose a probabilistic generalization of the popular sample-efficient non-parametric kNN approach. Our approach enables deep kNN classifier to accurately quantify underlying uncertainties in its prediction. We demonstrate the usefulness of the proposed approach by achieving superior uncertainty quantification as compared to state-of-the-art on a real-world application of COVID-19 diagnosis from chest X-Rays. Our code is available at https://github.com/ankurmallick/sample-efficient-uq

    FIREBall-2: The Faint Intergalactic Medium Redshifted Emission Balloon Telescope

    Authors: Erika Hamden; D. Christopher Martin; Bruno Milliard; David Schiminovich; Shouleh Nikzad; Jean Evrard; Gillian Kyne; Robert Grange; Johan Montel; Etienne Pirot; Keri Hoadley; Donal O'Sullivan; Nicole Melso; Vincent Picouet; Didier Vibert; Philippe Balard; Patrick Blanchard; Marty Crabill; Sandrine Pascal; Frederi Mirc; Nicolas Bray; April Jewell; Julia Blue Bird; Jose Zorilla; Hwei Ru Ong; Mateusz Matuszewski; Nicole Lingner; Ramona Augustin; Michele Limon; Albert Gomes; Pierre Tapie; Xavier Soors; Isabelle Zenone; Muriel Saccoccio

    id:2007.08528v1 Date: 2020-07-16 Source: arXiv

    The Faint Intergalactic Medium Redshifted Emission Balloon (FIREBall) is a mission designed to observe faint emission from the circumgalactic medium of moderate redshift (z~0.7) galaxies for the first time. FIREBall observes a component of galaxies that plays a key role in how galaxies form and evolve, likely contains a significant amount of baryons, and has only recently been observed at higher redshifts in the visible. Here we report on the 2018 flight of the FIREBall-2 Balloon telescope, which occurred on September 22nd, 2018 from Fort Sumner, New Mexico. The flight was the culmination of a complete redesign of the spectrograph from the original FIREBall fiber-fed IFU to a wide-field multi-object spectrograph. The flight was terminated early due to a hole in the balloon, and our original science objectives were not achieved. The overall sensitivity SERO of the instrument and telescope was 90,000 LU, due primarily to increased noise from stray light. We discuss the design of the FIREBall-2 spectrograph, modifications from the original FIREBall payload, and provide an overview of the performance SERO of all systems. We were able to successfully flight test a new pointing control system, a UV-optimized, delta-doped and coated EMCCD, and an aspheric grating. The FIREBall-2 team is rebuilding the payload for another flight attempt in the Fall HP of 2021, delayed from 2020 due to COVID-19.

    How does stock market reflect the change in economic demand? A study on the industry-specific volatility spillover networks of China's stock market during the outbreak of COVID-19

    Authors: Fu Qiao; Yan Yan

    id:2007.07487v1 Date: 2020-07-15 Source: arXiv

    Using the carefully selected industry classification standard, we divide 102 industry securities indices in China's stock market into four demand-oriented sector groups and identify demand-oriented industry-specific volatility spillover networks. The "deman-oriented" is a new idea of reconstructing the structure of the networks considering the relationship between industry sectors and the economic demand their outputs meeting. Networks with the new structure help us improve the understanding of the economic demand change, especially when the macroeconomic is dramatically influenced by exogenous shocks MESHD shocks HP like the outbreak of COVID-19. At the beginning of the outbreak of COVID-19, in China's stock market, spillover effects from industry indices of sectors meeting the investment demand to those meeting the consumption demands rose significantly. However, these spillover effects fell HP after the outbreak containment in China appeared to be effective. Besides, some services sectors including utility, transportation and information services have played increasingly important roles in the networks of industry-specific volatility spillovers as of the COVID-19 out broke. By implication, firstly, being led by Chinese government, the COVID-19 is successfully contained and the work resumption is organized with a high efficiency in China. The risk of the investment demand therefore was controlled and eliminated relatively fast. Secondly, the intensive using of non-pharmaceutical interventions (NPIs) led to supply restriction in services in China. It will still be a potential threat for the Chinese economic recovery in the next stage.

    COVID-Track: World and USA SARS-COV-2 Testing and COVID-19 Tracking

    Authors: Ye Emma Mariam Zohner; Jeffrey S Morris

    doi:10.21203/rs.3.rs-41444/v1 Date: 2020-07-13 Source: ResearchSquare

    Background The COVID-19 pandemic has caused major health and socio-economic disruptions worldwide. Accurate investigation of emerging data is crucial to inform policy makers as they construct viral mitigation strategies. Complications such as variable testing rates and time lags in counting cases, hospitalizations and deaths MESHD make it challenging to accurately track and identify true infectious surges from available data, and requires a multi-modal approach that simultaneously considers testing, incidence, hospitalizations, and deaths MESHD. Although many websites and applications report a subset of these data, none of them provide graphical displays capable of comparing different states or countries on all these measures as well as various useful quantities derived from them. Here we introduce a freely available graphical application that allows the user to simultaneously assess time trends in these measures and compare various states or countries, equipping them with a tool to investigate the potential effects of the different mitigation strategies and timelines used by various jurisdictions. Findings COVID-TRACK is a Python based web-application that provides a platform for tracking testing, incidence, hospitalizations, and deaths MESHD related to COVID-19 along with various derived quantities. Our application makes the comparison across states or countries in the world easy to explore, with useful transformation options including per capita, log scale, and/or moving averages. We illustrate its use by assessing various viral trends in the USA and Europe. Conclusion The COVID-TRACK web-application is a user-friendly analytical tool to compare data and trends related to the COVID-19 pandemic across areas in the United States and worldwide. Our tracking tool provides a unique platform where trends can be monitored across geographical areas in the coming months to watch how the pandemic waxes and wanes throughout the summer and into a potential second wave in the fall HP.

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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