Corpus overview


MeSH Disease

HGNC Genes

SARS-CoV-2 proteins

ProteinS (1608)

ProteinN (451)

NSP5 (379)

ComplexRdRp (215)

ProteinE (121)


SARS-CoV-2 Proteins
    displaying 21901 - 21910 records in total 22092
    records per page

    Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus ( COVID-19 MESHD)

    Authors: Ruiyun Li; Sen Pei; Bin Chen; Yimeng Song; Tao Zhang; Wan Yang; Jeffrey Shaman

    doi:10.1101/2020.02.14.20023127 Date: 2020-02-17 Source: medRxiv

    Background Estimation of the fraction and contagiousness of undocumented novel coronavirus ( COVID-19 MESHD) infections is critical for understanding the overall prevalence and pandemic potential of this disease. Many mild infections are typically not reported and, depending on their contagiousness, may support stealth transmission and the spread of documented infection. Methods Here we use observations of reported infection and spread within China in conjunction with mobility data, a networked dynamic metapopulation model and Bayesian inference, to infer critical epidemiological characteristics associated with the emerging coronavirus, including the fraction of undocumented infections and their contagiousness. Results We estimate 86% of all infections were undocumented (95% CI: [82%-90%]) prior to the Wuhan travel shutdown (January 23, 2020). Per person, these undocumented infections were 52% as contagious as documented infections ([44%-69%]) and were the source of infection for two-thirds of documented cases. Our estimate of the reproductive number (2.23; [1.77-3.00]) aligns with earlier findings; however, after travel restrictions and control measures were imposed this number falls considerably. Conclusions A majority of COVID-19 MESHD infections were undocumented prior to implementation of control measures on January 23, and these undocumented infections substantially contributed to virus transmission. These findings explain the rapid geographic spread of COVID-19 MESHD and indicate containment of this virus will be particularly challenging. Our findings also indicate that heightened awareness of the outbreak, increased use of personal protective measures, and travel restriction have been associated with reductions of the overall force of infection; however, it is unclear whether this reduction will be sufficient to stem the virus spread.

    Optimizing diagnostic strategy for novel coronavirus pneumonia, a multi-center study in Eastern China

    Authors: Jing-Wen Ai; Hao-Cheng Zhang; Teng Xu; Jing Wu; Mengqi Zhu; Yi-Qi Yu; Han-Yue Zhang; Zhongliang Shen; Yang Li; Xian Zhou; Guo-Qing Zang; Jie Xu; Wen-Jing Chen; Yong-Jun Li; De-Sheng Xie; Ming-Zhe Zhou; Jing-Ying Sun; Jia-Zhen Chen; Wen-Hong Zhang

    doi:10.1101/2020.02.13.20022673 Date: 2020-02-17 Source: medRxiv

    COVID-19 MESHD caused by a novel coronavirus SARS-CoV-2 emerged in Wuhan, Hubei province since December 2019, and caused a rapid outbreak throughout China and globally. Cities outside Hubei are also facing great challenge and require implementing of effective and feasible strategy in precision diagnosing novel coronavirus pneumonia MESHD ( NCP PROTEIN). We described a multicenter prospective study on diagnostic strategy of suspected NCP PROTEIN patients from January 22nd to February 9th, 2020 in Eastern China cities. Nasopharyngeal swabs were collected from the patients. The epidemiological characteristics, clinical symptoms, laboratory assessments, and computed tomographic (CT) scans were obtained. Pathogen screen were performed including RT-PCR, multiplex PCR, rapid flu antigen tests and mNGS. We enrolled 53 suspected NCP PROTEIN patients, among whom 20 were laboratory-confirmed. Fourteen (70%) and 3 (15%) patients were positive for the first and second SARS-CoV-2 RT-PCR test, respectively. All NCP PROTEIN patients were positive for mNGS. Chest CT images and the symptoms of early stage NCP PROTEIN patients were similar to other viral pneumonia MESHD patients. We identified 11 of 20 co-infections MESHD in NCP PROTEIN cases, including regular respiratory virus, fungi and bacteria synchronously. Genomic analysis showed that 8 of 10 cases had no mutation in virus genome, while 2 cases had only one single mutation in N gene PROTEIN. Our study discovered that a combination of chest CT, SARS-CoV-2 RT-PCR and multi-plex PCR is recommended in regions outside Hubei province. Co-infection MESHD of other pathogens with SARS-CoV-2 exists and should be acknowledged. Repeated sampling, change of specimen type or metagenomics sequencing could further facilitate during critical clinical cases.

    A simple laboratory parameter facilitates early identification of COVID-19 MESHD patients

    Authors: Qilin Li; Xiuli Ding; Geqing Xia; Zhi Geng; Fenghua Chen; Lin Wang; Zheng Wang

    doi:10.1101/2020.02.13.20022830 Date: 2020-02-17 Source: medRxiv

    The total number of COVID-19 MESHD patients since the outbreak of this infection in Wuhan, China has reached 40000 and are still growing. To facilitate triage or identification of the large number of COVID-19 MESHD patients from other patients with similar symptoms in designated fever clinics, we set to identify a practical marker that could be conveniently utilized by first-line health-care workers in clinics. To do so, we performed a case-control study by analyzing clinical and laboratory findings between PCR-confirmed SARS-CoV-2 positive patients (n=52) and SARS-CoV-2 negative patients (n=53). The patients in two cohorts all had similar symptoms, mainly fever MESHD and respiratory symptoms. The rates of patients with leukocyte counts (normal or decreased number) or lymphopenia MESHD (two parameters suggested by current National and WHO COVID-19 MESHD guidelines) had no differences between these two cohorts, while the rate of eosinopenia (decreased number of eosinophils) in SARS-CoV-2 positive patients (79%) was much higher than that in SARS-CoV-2 negative patients (36%). When the symptoms were combined with eosinopenia, this combination led to a diagnosis sensitivity and specificity of 79% and 64%, respectively, much higher than 48% and 53% when symptoms were combined with leukocyte counts (normal or decreased number) and/ or lymphopenia MESHD. Thus, our analysis reveals that eosinopenia may be a potentially more reliable laboratory predictor for SARS-CoV-2 infection MESHD than leukocyte counts and lymphopenia MESHD recommended by the current guidelines.

    Estimating the Efficacy of Traffic Blockage and Quarantine for the Epidemic Caused by 2019-nCoV ( COVID-19 MESHD)

    Authors: Deqiang Li; Zhicheng Liu; Qinghe Liu; Zefei Gao; Junkai Zhu; Junyan Yang; Qiao Wang

    doi:10.1101/2020.02.14.20022913 Date: 2020-02-17 Source: medRxiv

    Background: Since the 2019-nCoV ( COVID-19 MESHD) outbreaks in Wuhan, China, the cumulative number of confirmed cases is increasing every day, and a large number of populations all over the world are at risk. The quarantine and traffic blockage can alleviate the risk of the epidemic and the infections, henceforth evaluating the efficacy of such actions is essential to inform policy makers and raise the public awareness of the importance of self-isolation and quarantine. Method: We collected confirmed case data and the migration data, and introduced the quarantine factor and traffic blockage factor to the Flow-SEIR model. By varying the quarantine factor and traffic blockage factor, we simulated the change of the peak number and arrival time of infections, then the efficacy of these two intervation measures can be analyzed in our simulation. In our study, the self-protection at home is also included in quarantine. Results: In the simulated results, the quarantine and traffic blockage are effective for epidemic control. For Hubei province, the current quarantine factor is estimaed to be 0.405, which means around 40.5% of suceptibles who are close contacting with are in quarantine, and the current traffic blockage factor is estimaed to be 0.66, which indicates around 34% of suceptibles who had flowed out from Hubei. For the other provinces outside Hubei, the current quarantine factor is estimated to be 0.285, and the current traffic blockage factor is estimated to be 0.26. With the quarantine and traffic blockage factor increasing, the number of infections decrease dramatically. We also simulated the start dates of quarantine and traffic blockage at four time points, the simulated results show that the early of warning is also effective for epidemic containing. However, provincial level traffic blockage can only alleviate 21.06% - 22.38% of the peak number of infections. In general, the quarantine is much more effective than the traffic blockage control. Conclusion: Both of quarantine and traffic blockage are effective ways to control the spread of COVID-19 MESHD. However, the eff icacy of quarantine is found to be much stronger than that of traffic blockage. Considering traffic blockage may also cause huge losses of economy, we propose to gradually deregulate the traffic blockage, and improve quarantine instead. Also, there might be a large number of asymptomatic carriers of COVID-19 MESHD, the quarantine should be continued for a long time until the epidemic is totally under control.

    A deep learning algorithm using CT images to screen for Corona Virus Disease ( COVID-19 MESHD)

    Authors: Shuai Wang; Bo Kang; Jinlu Ma; Xianjun Zeng; Mingming Xiao; Jia Guo; Mengjiao Cai; Jingyi Yang; Yaodong Li; Xiangfei Meng; Bo Xu

    doi:10.1101/2020.02.14.20023028 Date: 2020-02-17 Source: medRxiv

    Background: The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 MESHD (SARS-COV-2) has caused more than 2.5 million cases of Corona Virus Disease MESHD ( COVID-19 MESHD) in the world so far, with that number continuing to grow. To control the spread of the disease, screening large numbers of suspected cases for appropriate quarantine and treatment is a priority. Pathogenic laboratory testing is the gold standard but is time-consuming with significant false negative results. Therefore, alternative diagnostic methods are urgently needed to combat the disease. Based on COVID-19 MESHD radiographical changes in CT images, we hypothesized that Artificial Intelligence's deep learning methods might be able to extract COVID-19 MESHD's specific graphical features and provide a clinical diagnosis ahead of the pathogenic test, thus saving critical time for disease control. Methods and Findings: We collected 1,065 CT images of pathogen-confirmed COVID-19 MESHD cases (325 images) along with those previously diagnosed with typical viral pneumonia MESHD (740 images). We modified the Inception transfer-learning model to establish the algorithm, followed by internal and external validation. The internal validation achieved a total accuracy of 89.5% with specificity of 0.88 and sensitivity of 0.87. The external testing dataset showed a total accuracy of 79.3% with specificity of 0.83 and sensitivity of 0.67. In addition, in 54 COVID-19 MESHD images that first two nucleic acid test results were negative, 46 were predicted as COVID-19 MESHD positive by the algorithm, with the accuracy of 85.2%. Conclusion: These results demonstrate the proof-of-principle for using artificial intelligence to extract radiological features for timely and accurate COVID-19 MESHD diagnosis.

    Artificial Intelligence Forecasting of Covid-19 MESHD in China

    Authors: Zixin Hu; Qiyang Ge; Shudi Li; Li Jin; Momiao Xiong

    id:2002.07112v2 Date: 2020-02-17 Source: arXiv

    BACKGROUND An alternative to epidemiological models for transmission dynamics of Covid-19 MESHD in China, we propose the artificial intelligence (AI)-inspired methods for real-time forecasting of Covid-19 MESHD to estimate the size, lengths and ending time of Covid-19 MESHD across China. METHODS We developed a modified stacked auto-encoder for modeling the transmission dynamics of the epidemics. We applied this model to real-time forecasting the confirmed cases of Covid-19 MESHD across China. The data were collected from January 11 to February 27, 2020 by WHO. We used the latent variables in the auto-encoder and clustering algorithms to group the provinces/cities for investigating the transmission structure. RESULTS We forecasted curves of cumulative confirmed cases of Covid-19 MESHD across China from Jan 20, 2020 to April 20, 2020. Using the multiple-step forecasting, the estimated average errors of 6-step, 7-step, 8-step, 9-step and 10-step forecasting were 1.64%, 2.27%, 2.14%, 2.08%, 0.73%, respectively. We predicted that the time points of the provinces/cities entering the plateau of the forecasted transmission dynamic curves varied, ranging from Jan 21 to April 19, 2020. The 34 provinces/cities were grouped into 9 clusters. CONCLUSIONS The accuracy of the AI-based methods for forecasting the trajectory of Covid-19 MESHD was high. We predicted that the epidemics of Covid-19 MESHD will be over by the middle of April. If the data are reliable and there are no second transmissions, we can accurately forecast the transmission dynamics of the Covid-19 MESHD across the provinces/cities in China. The AI-inspired methods are a powerful tool for helping public health planning and policymaking.

    Clinical Characteristics of 2019 Novel Infected Coronavirus Pneumonia:A Systemic Review and Meta-analysis

    Authors: Kai Qian; Yi Deng; Yonghang Tai; Jun Peng; Hao Peng; Lihong Jiang

    doi:10.1101/2020.02.14.20021535 Date: 2020-02-17 Source: medRxiv

    Background:A Novel pneumonia MESHD associated with the 2019 coronavirus infected pneumonia MESHD (NCIP) suddenly broke out in Wuhan, China in December 2019. 37287 confirmed cases and 813 death MESHD case in China (Until 8th/Feb/2019) have been reported in just fortnight. Although this risky pneumonia MESHD with high infection rates and high mortality rates need to be resolved immediately, major gaps in our knowledge of clinical characters of it were still not be established. The aim of this study is to summaries and analysis the clinical characteristics of 2019-nCoV pneumonia MESHD. Methods: Literature have been systematically performed a search on PubMed, Embase, Web of Science, GreyNet International, and The Cochrane Library from inception up to February 8, 2020. The Newcastle-Ottawa Scale was used to assess quality, and publication bias MESHD was analyzed by Egger test. In the single-arm meta-analysis, A fix-effects model was used to obtain a pooled incidence rate. We conducted subgroup analysis according to geographic region and research scale. Results: A total of nine studies including 356 patients were included in this study, the mean age was 52.4 years and 221 (62.1%) were male. The pooled incidences rate of symptoms as follows: pharyngalgia (12.2%, 95% CI: 0.087-0.167), diarrhea MESHD (9.2%, 95% CI: 0.062-0.133) and headache MESHD (8.9%, 95% CI: 0.063-0.125). Meanwhile, 5.7% (95% CI: 0.027-0.114) of patients were found without any symptoms although they were diagnosed by RT-PCR. In the terms of CT imaging examination, the most of patients showed bilateral mottling or ground-glass opacity, 8.6% (95% CI: 0.048-0.148) of patients with crazy-paving pattern, and 11.5% (95% CI: 0.064-0.197) of patients without obvious CT imaging presentations. The pooled incidence of mortality was 8.9% (95% CI: 0.062-0.126). Conclusions: To our knowledge, this is the first evidence-based medicine research to further elaborate the clinical characteristics of NCIP, which is beneficial to the next step of prevention and treatment.

    The Efficacy of Contact Tracing for the Containment of the 2019 Novel Coronavirus ( COVID-19 MESHD).

    Authors: Matt J Keeling; T. Deirdre Hollingsworth; Jonathan M Read

    doi:10.1101/2020.02.14.20023036 Date: 2020-02-17 Source: medRxiv

    Contact tracing is a central public health response to infectious disease outbreaks, especially in the early stages of an outbreak when specific treatments are limited. Importation of novel Coronavirus ( COVID-19 MESHD) from China and elsewhere into the United Kingdom highlights the need to understand the impact of contact tracing as a control measure. Using detailed survey information on social encounters coupled to predictive models, we investigate the likely efficacy of the current UK definition of a close contact (within 2 meters for 15 minutes or more) and the distribution of secondary cases that may go untraced. Taking recent estimates for COVID-19 MESHD transmission, we show that less than 1 in 5 cases will generate any subsequent untraced cases, although this comes at a high logistical burden with an average of 36.1 individuals (95th percentiles 0-182) traced per case. Changes to the definition of a close contact can reduce this burden, but with increased risk of untraced cases; we estimate that any definition where close contact requires more than 4 hours of contact is likely to lead to uncontrolled spread.

    The role of absolute humidity on transmission rates of the COVID-19 MESHD outbreak

    Authors: Wei Luo; Maimuna S Majumder; Dianbo Liu; Canelle Poirier; Kenneth D Mandl; Marc Lipsitch; Mauricio Santillana

    doi:10.1101/2020.02.12.20022467 Date: 2020-02-17 Source: medRxiv

    A novel coronavirus ( COVID-19 MESHD) was identified in Wuhan, Hubei Province, China, in December 2019 and has caused over 40,000 cases worldwide to date. Previous studies have supported an epidemiological hypothesis that cold and dry (low absolute humidity) environments facilitate the survival and spread of droplet-mediated viral diseases, and warm and humid (high absolute humidity) environments see attenuated viral transmission (i.e., influenza). However, the role of absolute humidity in transmission of COVID-19 MESHD has not yet been established. Here, we examine province-level variability of the basic reproductive numbers of COVID-19 MESHD across China and find that changes in weather alone (i.e., increase of temperature and humidity as spring and summer months arrive in the North Hemisphere) will not necessarily lead to declines MESHD in COVID-19 MESHD case counts without the implementation of extensive public health interventions.

    Evaluating the Traditional Chinese Medicine (TCM) Officially Recommended in China for COVID-19 MESHD Using Ontology-Based Side-Effect Prediction Framework (OSPF) and Deep Learning

    Authors: Zeheng Wang; Liang Li; Jing Yan; Yuanzhe Yao

    id:10.20944/preprints202002.0230.v1 Date: 2020-02-17 Source:

    Ethnopharmacological relevance: Novel coronavirus disease MESHD ( COVID-19 MESHD) outbroke in Wuhan has imposed a huge influence onto the society in term of the public heath and economy. However, so far, no effective drugs or vaccines have been developed. Whereas, the Traditional Chinese Medicine (TCM) has been considered as a promising supplementary treatment for the disease owing to its clinically proven performance on many diseases MESHD even like severe acute respiratory syndrome MESHD (SARS). Meanwhile, many side-effect ( SE MESHD) reports suggest the SE MESHD of the TCM prescriptions cannot be ignored in curing the COVID-19 MESHD, especially because COVID-19 MESHD always simultaneously leads to dramatic degradation of the patients’ physical condition. How to evaluate the TCM regarding to their latent SE MESHD is a urgent challenge. Aim of the study: In this study, we use an ontology-based side-effect prediction framework (OSPF) developed in our previous work and Artificial Neural Network (ANN)-based deep learning to evaluate the TCM prescriptions that are officially recommended in China for novel coronavirus ( COVID-19 MESHD). Materials and methods: Firstly, we adopted the OSPF developed in our previous work, where an ontology-based model separate all the ingredients in a TCM prescription into two categories: hot and cold. Then, we established a database by converting each TCM prescription into a vector containing the ingredient dosage and the according hot/cold attribution as well as the safe/unsafe label. And, we trained the ANN model using this database, after which a safety indicator (SI), as the complementary percentage of side-effect ( SE MESHD) possibility, is then given for each TCM prescription. According to the proposed SI from high to low, we re-organize the recommended prescription list. Secondly, by using this method, we also evaluate the safety indicators of some other famous TCM prescriptions that are not in the recommended list but are used traditionally to cure flu-like diseases for extending the potential treatments. Results: Based on the SI generated in the ANN model, FTS HGNC, PMSP, and SF are the safest ones in recommended list, which all own a more-than-0.8 SI. Whereas, JHQG, LHQW, SFJD, XBJ, and SHL are the prescriptions that are most likely unsafe, where the indicators are all below 0.2. In the extra list, the indicators of XC, XQRS, CC, and CHBX are all above 0.8, and at the meantime, XZXS, SJ, QW, and KBD’s indicators are all below 0.2. Conclusions: In total, there are seven TCM prescriptions which own the indicators more than 0.8, suggesting these prescriptions should be considered firstly in curing COVID-19 MESHD, if suitable. We believe this work will provide a reasonable suggestion for the society to choose proper TCM as the supplementary treatment for COVID-19 MESHD. Besides, this work also introduces a pilot and enlightening method for creating a more reasonable recommendation list of TCM to other diseases.

The ZB MED preprint Viewer preVIEW includes all COVID-19 related preprints from medRxiv and bioRxiv, from ChemRxiv, from ResearchSquare, from arXiv and from and is updated on a daily basis (7am CET/CEST).
The web page can also be accessed via API.



MeSH Disease
HGNC Genes
SARS-CoV-2 Proteins

Export subcorpus as...

This service is developed in the project nfdi4health task force covid-19 which is a part of nfdi4health.

nfdi4health is one of the funded consortia of the National Research Data Infrastructure programme of the DFG.