Corpus overview


Overview

MeSH Disease

Infections (554)

Disease (464)

Death (402)

Coronavirus Infections (276)

Pneumonia (109)


Human Phenotype

Pneumonia (113)

Fever (109)

Cough (88)

Fatigue (28)

Hypertension (20)


Transmission

Seroprevalence
    displaying 41 - 50 records in total 1146
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    Isolation Considered Epidemiological Model for the Prediction of COVID-19 Trend in Tokyo, Japan

    Authors: Motoaki Utamura; Makoto Koizumi; Seiichi Kirikami

    doi:10.1101/2020.07.31.20165829 Date: 2020-07-31 Source: medRxiv

    Background: Coronavirus Disease MESHD 2019 (COVID19) currently poses a global public health threat. Although no exception, Tokyo, Japan was affected at first by only a small epidemic. Medical collapse nevertheless nearly happened because no predictive method existed for counting patients. A standard SIR epidemiological model and its derivatives predict susceptible, infectious, and removed (recovered/ deaths MESHD) cases but ignore isolation of confirmed cases TRANS. Predicting COVID19 trends with hospitalized and infectious people in field separately is important to prepare beds and develop quarantine strategies. Methods: Time-series COVID19 data from February 28 to May 23, 2020 in Tokyo were adopted for this study. A novel epidemiological model based on delay differential equation was proposed. The model can evaluate patients in hospitals and infectious cases in the field. Various data such as daily new cases, cumulative infections MESHD, patients in hospital, and PCR test positivity ratios were used to examine the model. This approach derived an alternative formulation equivalent to the standard SIR model. Its results were compared quantitatively with those of the present isolation model. Results: The basic reproductive number TRANS, inferred as 2.30, is a dimensionless parameter composed of modeling parameters. Effects of intervention to mitigate the epidemic spread were assessed a posteriori. An exit policy of how and when to release a statement of emergency MESHD was also assessed using the model. Furthermore, results suggest that the rapid isolation of infectious cases has a large potential to effectively mitigate the spread of infection MESHD and restores social and economic activities safely. Conclusions: A novel mathematical model was proposed and examined using COVID19 data for Tokyo. Results show that shortening the period from infection MESHD to hospitalization is effective against outbreak without rigorous public health intervention and control. Faster and precise case cluster detection and wider and quicker introduction of testing measures are strongly recommended.

    The Effect of Temperature Upon Transmission TRANS Of COVID-19 Australia And Egypt Case Study.

    Authors: Adly Anis

    doi:10.21203/rs.3.rs-51746/v1 Date: 2020-07-31 Source: ResearchSquare

    BackgroundSeveral previous studies have recognized the effect of air temperature on the survival and transmission TRANS of viruses and germs. The current study investigated the effect of air temperature on the transmission TRANS of coronavirus covid-19 by monthly temperature averages maps analyzing.MethodsThe study demonstrated the relationship between temperature and transmission TRANS speed of Covid-19 virus, It confirmed that the most appropriate average temperature for virus activity and transmission TRANS ranges between 13-24 ° C, by analyzing the maps of monthly temperature averages in Egypt and Australia.ResultsThe study reached, through cartographic analysis, to confirm the relationship between temperature and increase in the number of confirmed cases TRANS of covid-19, This study confirmed that the most appropriate average temperature for virus activity and transmission TRANS ranges between 13-24 ° C, by analyzing the maps of monthly temperature averages in Egypt and Australia. But the effect of the climate does not prevent the virus from being transmitted from one person to another through close contact TRANS or use of personal tools infected with the Corona virus, or crowding in air-conditioned places.Therefore, failure of individuals to follow the instructions for social distance and wearing a mask will lead to the transmission TRANS of the virus, even in hot climates.ConclusionsResults support that the most appropriate average temperature for the survival transmission TRANS of COVID-19 ranges between 13-24 ° C. Australia and Egypt are models to confirm the relationship between temperature and COVID-19 activity and spread.

    Neonatal COVID-19: a clinical case report from the Democratic Republic of Congo (DRC)

    Authors: Serge ZIGABE; Etienne Kajibwami; Guy-Quesney Mateso; Benjamin Ntaligeza

    doi:10.21203/rs.3.rs-51061/v1 Date: 2020-07-30 Source: ResearchSquare

    COVID-19 started as a cluster of pneumonia MESHD pneumonia HP cases in Wuhan City, the Province of Hubei, China, in December 2019. It spread to many regions of China, outside of China and was declared a pandemic by the World Health Organization (WHO) on March 11th, 2020. Initially Africa had no case and now the continent is reporting an increasing number of confirmed cases TRANS in an exponential manner (1,2).

    The effective reproductive number TRANS (Rt) of COVID-19 and its relationship with social distancing

    Authors: Lucas Jardim Sr.; Jose Alexandre Diniz-Filho Sr.; Thiago Fernando Rangel Sr.; Cristiana Maria Toscano II

    doi:10.1101/2020.07.28.20163493 Date: 2020-07-29 Source: medRxiv

    The expansion of the new coronavirus disease MESHD (COVID-19) triggered a renewed public interest in epidemiological models and on how parameters can be estimated from observed data. Here we investigated the relationship between average number of transmissions TRANS though time, the reproductive number TRANS Rt, and social distancing index as reported by mobile phone data service inloco, for Goias State, Brazil, between March and June 2020. We calculated Rt values using EpiEstim package in R-plataform for confirmed cases TRANS incidence curves. We found a correlation equal to -0.72 between Rt values for confirmed cases TRANS and isolation index at a time lag of 8 days. As the Rt values were paired with center of the moving window of 7 days, the delay matches the mean incubation period TRANS of the virus. Our findings reinforce that isolation index can be an effective surrogate for modeling and epidemiological analyses and, more importantly, can be an useful metrics for anticipating the need for early interventions, a critical issue in public health.

    Children TRANS with COVID-19 like symptoms in Italian Pediatric Surgeries: the dark side of the coin

    Authors: Gianfranco Trapani; Vassilios Fanos; Enrico Bertino; Giulia Maiocco; Osama Al Jamal; Michele Fiore; VIncenzo Bembo; Domenico Careddu; Lando Barberio; Luisella Zanino; Giuseppe Verlato

    doi:10.1101/2020.07.27.20149757 Date: 2020-07-29 Source: medRxiv

    BACKGROUND: Symptoms of SARS-CoV-2 infection MESHD in children TRANS are nonspecific and shared with other common acute viral illnesses ( fever MESHD fever HP, respiratory or gastrointestinal symptoms, and cutaneous signs), thus making clinical differential diagnosis tricky. In Italy, first line management of pediatric care is handed over to Primary Care Pediatricians (PCPs), who were not allowed to directly perform diagnostic tests during the recent COVID-19 outbreak. Without a confirmatory diagnosis, PCPs could only collect information on ''COVID-19 like symptoms'' rather than identify typical COVID-19 symptoms. AIM: To evaluate the prevalence SERO of COVID-19 like symptoms in outpatient children TRANS, during Italian lockdown. To provide PCPs a risk score to be used in clinical practice during the differential diagnosis process. METHODS: A survey was submitted to 50 PCPs (assisting 47,500 children TRANS) from 7 different Italian regions between the 4th of March and the 23rd of May 2020 (total and partial lockdown period). COVID-19 like symptoms in the assisted children TRANS were recorded, as well as presence of confirmed/suspected cases in children TRANS's families, which was taken as proxy of COVID-19. Multivariable logistic regression was accomplished to estimate the risk of having suspected/ confirmed cases TRANS in families, considering symptoms as potential determinants. RESULTS: 2,300 children TRANS (4.8% of overall survey population) fell HP ill with COVID-19 like symptoms, 3.1% and 1.7% during total and partial lockdown period respectively. The concurrent presence of fatigue MESHD fatigue HP, cough MESHD cough HP, and diarrhea MESHD diarrhea HP in children TRANS, in absence of sore throat/ earache MESHD and abnormal skin signs, represents the maximum risk level of having a suspected/ confirmed case TRANS of COVID-19 at home. CONCLUSIONS: The percentage of children TRANS presenting COVID-19 like symptoms at home has been remarkable also during the total lockdown period. The present study identified a pattern of symptoms which could help, in a cost-effective perspective, PCPs in daily clinical practice to define priorities in addressing children TRANS to the proper diagnostic procedure.

    Novel uses of three-parameter logistic models and first-derivative models for the Coronavirus Disease MESHD (COVID-19) epidemic in the United States, in three distinct scenarios

    Authors: Bishoy T. Samuel

    doi:10.21203/rs.3.rs-50739/v1 Date: 2020-07-29 Source: ResearchSquare

    Background: Forecasting the current coronavirus disease MESHD (COVID-19) epidemic in the United States necessitates novel mathematical models for accurate predictions. This paper examines novel uses of three-parameter logistic models and first-derivative models through three distinct scenarios that have not been examined in the literature as of July 14, 2020.Methods: Using publicly available data, statistical software was used to conduct a non-linear least-squares estimate to generate a three-parameter logistic model, with a subsequently generated first-derivative model. In the first scenario a logistic model was used to examine the natural log of COVID-19 cases as the dependent variable (versus day number), on July 11 and May 1. Independent t-test analyses were used to test comparative coefficient differences across models. In the second scenario, a first-derivative model was derived from a base three-parameter logistic model for April 27, examining time to peak mortality and decrease in case fatality rate. In the third scenario, a first-derivative model of mortality through July 11 as the dependent variable, versus confirmed cases TRANS, was generated to look at case fatality rate relative to increasing cases.Results: All models generated were statistically significant with R2 > 99%. The logistic models in the first scenario best predicted time to growth deceleration in the natural log of cases in the U.S. (slowing of exponential growth), estimated at March 11, 2020. For the May 1 data, independent t-test analyses of comparative coefficients across models were useful to track improvements from implemented public health measures. The first-derivative model in the second scenario on April 27, when the epidemic was more controlled, showed peak mortality around April 12-13, with a case fatality rate of < 1,000 deaths MESHD and trending down. The first-derivative model in the third scenario estimated a near-zero case fatality rate to occur at 4 million confirmed cases TRANS. It has not been affected by fluctuations in mortality from June 29 through July 11.Conclusion: Three-parameter logistic models and first-derivative models have utility in predicting time to growth deceleration, and case fatality rates relative to cases. They can objectively assess improvements of implemented epidemiologic measures and have applicable public health safety implications.

    Close-range exposure to a COVID-19 carrier TRANS: transmission TRANS trends in the respiratory tract and estimation of infectious dose

    Authors: Saikat Basu

    doi:10.1101/2020.07.27.20162362 Date: 2020-07-29 Source: medRxiv

    How respiratory physiology and airflow therein proceed to impact SARS-CoV-2 transmission TRANS, leading to the initial infection MESHD, is an open question. An answer can help determine the susceptibility of an individual on exposure to a COVID-2019 carrier TRANS and can also quantify the still-unknown infectious dose for the disease MESHD. Combining computational fluid mechanics-based tracking of respiratory transport in anatomic domains with sputum assessment data from hospitalized patients and earlier measurements of ejecta size distribution during regular speech - this study shows that targeted deposition at the initial nasopharyngeal infection MESHD sites peaks over the droplet size range of 2.5 - 19 , and reveals that the number of virions that can establish the infection MESHD is at most of O(100).

    A Retrospective Study on Efficacy and Safety of Guduchi Ghan Vati for Covid-19 Asymptomatic TRANS Patients

    Authors: Abhimanyu Kumar; Govind Prasad; Sanjay Srivastav; Vinod Kumar Gautam; Neha Sharma

    doi:10.1101/2020.07.23.20160424 Date: 2020-07-29 Source: medRxiv

    Background Coronavirus disease MESHD 2019 (Covid-19) has been declared global emergency MESHD with immediate safety, preventative and curative measures to control the spread of virus. Confirmed cases TRANS are treated with clinical management as they are diagnosed but so far, there is no effective treatment or vaccine yet for Covid-19. Ayurveda has been recommended by preventative and clinical management guidelines in India and several clinical trials are ongoing. But there is no study to assess impact of Ayurveda on Covid-19. Methods Objective of present study was to evaluate the clinical outcome in Covid-19 confirmed asymptomatic TRANS to mild symptomatic patients who had received Ayurveda and compare with control (who has not received Ayurveda or any support therapy). Patients having Ayurveda intervention (Guduchi Ghan Vati-extract of Tinospora cordifolia) were included from Jodhpur Covid Care Centre and non-recipients were taken from Jaipur Covid Care Centre between May 15 to June 15, 2020. Total 91 patients, who were asymptomatic TRANS at the time of hospital admission and between 18 -75 years of age TRANS, were included in the study to analyse retrospectively. Results In control group, 11.7% developed mild symptoms after average 1.8 days and none in Ayurveda group reported any symptoms. Significant difference was reported between the group of patients taking Guduchi Ghan Vati (n=40) and patients in standard care (n=51) in terms of virologic clearance at day-7 (97.5% vs 15.6% respectively; p=0.000), at day 14 (100% vs 82.3%) days to stay in hospital ( 6.4 vs 12.8 respectively; p< 0.0001) . Conclusion Results of the study suggest that Guduchi Ghan Vati, a common and widely used Ayurveda preparation, could benefit treating asymptomatic TRANS Covid-19 patients. Larger, randomised controlled Trials are required to confirm the findings. Keywords: Ayurveda, Guduchi Ghan

    A Comprehensive Evaluation of Early Predictors of Disease Progression MESHD in Patients with COVID-19: A Case Control Study

    Authors: Qiang Tang; Yanwei Liu; Yingfeng Fu; Ziyang Di; Kailiang Xu; Bo Tang; Hui Wu; Maojun Di

    doi:10.21203/rs.3.rs-50527/v1 Date: 2020-07-29 Source: ResearchSquare

    Background: The 2019 coronavirus disease MESHD (COVID-19) has become an unprecedented public health crisis with nearly 16 million confirmed cases TRANS and 630,000 deaths MESHD worldwide. Methods: We retrospectively investigated the demographic, clinical, laboratory, radiological and treatment data of COVID-19 patients consecutively enrolled from January 18 to May 15, 2020, in Taihe and Jinzhou central hospital. Results: Of all 197 patients, the median age TRANS was 66.5 years (IQR 7-76), and 120 (60.9%) patients were males TRANS. We identified 88 (44.7%) of 197 COVID-19 patients as the disease progression MESHD (aggravation) cases. The aggravation cases tend to have more medical comorbidity: hypertension MESHD hypertension HP (34.1%), diabetes (30.7%), and presented with dyspnea MESHD dyspnea HP (34.1%), neutrophilia HP (60.2%), and lymphocytopenia (73.9%), compared with those without. And the patients with disease progression MESHD showed significantly higher level of Fibrinogen (Fbg), D-dimer, IL-6, C-reactive protein (CRP), procalcitonin (PCT), and serum SERO ferritin, and were more prone to develop organ damage in the liver, kidney, and heart (P<0.05). Multivariable regression showed that advanced age TRANS, comorbidities, lymphopenia MESHD lymphopenia HP, and elevated level of Fbg, lactate dehydrogenase (LDH), Cardiac troponin (CTnI), IL-6, serum SERO ferritin were the significant predictors of disease progression MESHD. Further, we investigated antibody SERO responses to SARS-CoV-2 and found that the levels of IgM and IgG were significantly higher in the disease progression MESHD cases compared to non-progression cases from 3 weeks after symptom onset TRANS. In addition, the disease progression MESHD group tended to peak later and has a more vigorous IgM/IgG response against SARS-CoV-2. Further, we performed Kaplan-Meier analysis and found that 61.6% of patients had not experienced ICU transfer or survival from hospital within 25 days from admission.Conclusions: Investigating the potential factors of advanced age TRANS, comorbidities and elevated level of IL-6, serum SERO ferritin and Kaplan-Meier analysis enables early identification and management of patients with poor prognosis. Detection of the dynamic antibody SERO may offer vital clinical information during the course of SARS-CoV-2 and provide prognostic value for patients infection MESHD.  

    Deep Learning Models for Early Detection and Prediction of the spread of Novel Coronavirus (COVID-19)

    Authors: Devante Ayris; Kye Horbury; Blake Williams; Mitchell Blackney; Celine Shi Hui See; Syed Afaq Ali Shah

    id:2008.01170v1 Date: 2020-07-29 Source: arXiv

    SARS-CoV2, which causes coronavirus disease MESHD (COVID-19) is continuing to spread globally and has become a pandemic. People have lost their lives due to the virus and the lack of counter measures in place. Given the increasing caseload and uncertainty of spread, there is an urgent need to develop machine learning techniques to predict the spread of COVID-19. Prediction of the spread can allow counter measures and actions to be implemented to mitigate the spread of COVID-19. In this paper, we propose a deep learning technique, called Deep Sequential Prediction Model (DSPM) and machine learning based Non-parametric Regression Model (NRM) to predict the spread of COVID-19. Our proposed models were trained and tested on novel coronavirus 2019 dataset, which contains 19.53 Million confirmed cases TRANS of COVID-19. Our proposed models were evaluated by using Mean Absolute Error and compared with baseline method. Our experimental results, both quantitative and qualitative, demonstrate the superior prediction performance SERO of the proposed models.

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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