Corpus overview


MeSH Disease

Human Phenotype

Pneumonia (302)

Fever (236)

Cough (195)

Hypertension (140)

Respiratory distress (91)


age categories (701)

Transmission (451)

gender (363)

fomite (294)

asymptotic cases (154)

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    Comparison of Renin–Angiotensin–Aldosterone System Inhibitors with Other Antihypertensives in Association with Coronavirus Disease MESHD-19 Clinical Outcomes: Systematic Review and Meta-Analysis

    Authors: Yihienew M. Bezabih; Alemayehu Bezabih; Endalkachew Admassie; Gregory M. Peterson; Woldesellassie Bezabhe

    id:10.20944/preprints202005.0392.v1 Date: 2020-05-24 Source:

    Since the effects of renin–angiotensin–aldosterone system (RAAS) inhibitors on the clinical outcomes of coronavirus disease MESHD-19 (COVID-19) have been conflicting in different studies, we performed this meta-analysis. A systematic search of published articles was performed in PubMed and EMBASE from January-May 5, 2020. Studies that reported the clinical outcomes of patients with COVID-19, stratified by the class of concomitant antihypertensive drug therapy, were included. The Mantel-Haenszel random effects model was used to estimate pooled odds ratio (OR). A total of 6,997 hypertensive patients with COVID-19 were included. The overall risk of poor patient outcomes (severe COVID-19 or death MESHD) was lower in patients taking RAAS inhibitors (OR=0.84, 95% CI: [0.73, 0.96]; P=0.017) compared with those receiving non-RAAS inhibitor antihypertensives. Patients taking angiotensin-I-converting enzyme inhibitors (ACEIs) were less likely to experience poor clinical outcomes (OR=0.73, 95% CI: [0.58-0.92]; P=0.01) compared with those receiving angiotensin-II receptor blockers (ARBs). Compared to all other antihypertensives, ACEIs decreases the risk poor COVID-19 outcomes (OR=0.77, 95% CI: [0.63-0.93]) while ARBs did not (OR=1.13, 95% CI: [0.95-1.35]). The risk of poor patient outcomes from COVID-19 was lower in patients who received RAAS inhibitors compared with those who took non-RAAS inhibitors. Unlike ARBs, ACEIs might help in decreasing the severity and mortality of COVID-19.

    Intention to Vaccinate Against the Novel 2019 Coronavirus Disease MESHD: The Role of Health Locus of Control and Religiosity

    Authors: Ayokunle Olagoke; Olakanmi Olagoke; Ashley M. Hughes

    doi:10.21203/ Date: 2020-05-24 Source: ResearchSquare

    The urgency to develop a vaccine against the 2019 coronavirus (COVID-19) has waxed stronger in speed, scale, and scope. However, wisdom dictates that we take a vantage position and start to examine the demographic predictors of COVID-19 vaccine hesitancy. The objective of this study was to examine the role of health locus of control (HLOC) in the relationship between religiosity and COVID-19 vaccination intention. In a cross-sectional survey (N=501), we found a significantly negative association between religiosity and COVID-19 vaccination intention. This relationship was partially mediated by external HLOC. Collaborative efforts with religious institutions may influence COVID-19 vaccine uptake.

    Unravelling the Social Network of COVID-19 in India from 30 January to 6 April 2020

    Authors: Sarita Azad; Sushma Devi

    id:10.20944/preprints202005.0382.v1 Date: 2020-05-24 Source:

    Social network analysis is an essential means to uncover and examine infectious contact relations between individuals. This paper aims to investigate the spread of coronavirus disease MESHD (COVID-19) from international to the national level and find a few super spreaders which played a central role in the transmission TRANS of disease MESHD in India. Our network metrics calculated from 30 January to 6 April 2020 revealed that the maximum numbers of connections were established from Dubai (degree-144) and UK (degree-64). These two countries played a crucial role in diffusing the disease MESHD in Indian states. The eigenvector centrality of Dubai is found to be the highest, and this marked it the most influential node. However, based on the modularity class, we found that the different clusters were formed across Indian states which demonstrated the forming of a multi-layered social network structure.A significant increase in the confirmed cases TRANS was reported during the first lockdown 1.0 (22 March 2020) primarily attributed to a gathering in Delhi Religious Conference (DRC) known as Tabliqui Jamaat. As of 6 April 2020, the overall structure of the network has encompassed local transmission TRANS, and it was significantly seen in the states like Gujarat, Rajasthan, and Karnataka. An important conclusion drawn from the presented social network reveals that the COVID-19 spread till 6 April was mainly due to the local transmission TRANS across Indian states. The timely quarantine of infected cases in DRC has not led it to spread at the level of community transmission TRANS.

    Importations of COVID-19 into African countries and risk of onward spread

    Authors: Haoyang Sun; Borame Lee Dickens; Alex Richard Cook; Hannah Eleanor Clapham

    doi:10.1101/2020.05.22.20110304 Date: 2020-05-24 Source: medRxiv

    Background The emergence of a novel coronavirus (SARS-CoV-2) in Wuhan, China, at the end of 2019 has caused widespread transmission TRANS around the world. As new epicentres in Europe and America have arisen, of particular concern is the increased number of imported coronavirus disease MESHD 2019 (COVID-19) cases in Africa, where the impact of the pandemic could be more severe. We aim to estimate the number of COVID-19 cases imported from 12 major epicentres in Europe and America to each African country, as well as the probability of reaching 10,000 infections MESHD in total by the end of March, April, and May following viral introduction. Methods We used the reported number of cases imported from the 12 major epicentres in Europe and America to Singapore, as well as flight data, to estimate the number of imported cases in each African country. Under the assumption that Singapore has detected all the imported cases, the estimates for Africa were thus conservative. We then propagated the uncertainty in the imported case count estimates to simulate the onward spread of the virus, until 10,000 infections MESHD are reached or the end of May, whichever is earlier. Specifically, 1,000 simulations were run separately under two scenarios, where the reproduction number TRANS under the stay-at-home order was assumed to be 1.5 and 1.0 respectively. Findings We estimated Morocco, Algeria, South Africa, Egypt, Tunisia, and Nigeria as having the largest number of COVID-19 cases imported from the 12 major epicentres. Based on our 1,000 simulation runs, Morocco and Algeria's estimated probability of reaching 10,000 infections MESHD by end of March was close to 100% under both scenarios. In particular, we identified countries with less than 100 cases in total reported by end of April whilst the estimated probability of reaching 10,000 infections MESHD by then was higher than 50% even under the more optimistic scenario. Conclusion Our study highlights particular countries that are likely to reach (or have reached) 10,000 infections MESHD far earlier than the reported data suggest, calling for the prioritization of resources to mitigate the further spread of the epidemic.

    Conditions for a second wave of COVID-19 due to interactions between disease MESHD dynamics and social processes

    Authors: Sansao A Pedro; Frank T Ndjomatchoua; Peter Jentsch; Jean M Tcheunche; Madhur Anand; Chris T Bauch

    doi:10.1101/2020.05.22.20110502 Date: 2020-05-24 Source: medRxiv

    In May 2020, many jurisdictions around the world began lifting physical distancing restrictions against the spread of severe acute respiratory syndrome MESHD coronavirus 2 (SARS-CoV-2), giving rise to concerns about a possible second wave of coronavirus disease MESHD 2019 (COVID-19). These restrictions were imposed as a collective population response to the presence of COVID-19 in communities. However, lifting restrictions is also a population response to their socio-economic impacts, and is expected to increase COVID-19 cases, in turn. This suggests that the COVID-19 pandemic exemplifies a coupled behaviour- disease MESHD system. Here we develop a minimal mathematical model of the interaction between social HP interaction between social TRANS support for school and workplace closure and the transmission TRANS dynamics of SARS-CoV-2. We find that a second wave of COVID-19 occurs across a broad range of plausible model input parameters, on account of instabilities generated by behaviour- disease MESHD interactions. We conclude that second waves of COVID-19--should they materialize--can be interpreted as the outcomes of nonlinear interactions between disease MESHD dynamics and population behaviour.

    COVID-19 pandemic brings a sedentary lifestyle: a cross-sectional and longitudinal study

    Authors: Chen ZHENG; Wendy Yajun HUANG; Sinead SHERIDAN; Cindy Hui-Ping SIT; Xiang-Ke CHEN; Stephen Heung-Sang WONG

    doi:10.1101/2020.05.22.20110825 Date: 2020-05-24 Source: medRxiv

    Objectives: The coronavirus disease MESHD 2019 (COVID-19) pandemic continues to pose profound challenges on society. Governments around the world have managed to mitigate its spread through strategies including social distancing; however, this may result in the adoption of sedentary lifestyle. This study aimed to investigate: 1) physical activity (PA) levels, sedentary behavior (SB) and sleep among young adults TRANS during COVID-19 epidemic, and 2) the change in these behaviors before and during the pandemic. Methods: A total of 631 young adults TRANS (38.8% males TRANS) participated in the cross-sectional study and completed an online survey that included five components: general information, COVID-19 related issues, PA, SB, and sleep. For longitudinal study, PA, SB, and sleep data collected from 70 participants before and during COVID-19 pandemic were analyzed. Results: Participants reported engaging in low PA, high SB and long sleep duration during COVID-19 pandemic. Females TRANS had greater concern for COVID-19 related issues and engaged in more prevention strategies than males TRANS. Moreover, a significant decline in PA while increase in both times spent in SB and sleep were determined after COVID-19 outbreak. Conclusion: The results of this study demonstrated a sedentary lifestyle in young adults TRANS in responses to social distancing during the COVID-19 pandemic, which will assist health policy makers and practitioners in the development of population specific health education and behavior interventions during this pandemic and for other future events.

    Ethnics and economics in COVID-19: Meta-regression of data from countries in the New York metropolitan area

    Authors: Hisato Takagi; Toshiki Kuno; Yujiro Yokoyama; Hiroki Ueyama; Takuya Matsushiro; Yosuke Hari; Tomo Ando

    doi:10.1101/2020.05.22.20110791 Date: 2020-05-24 Source: medRxiv

    Ethnics and economics may affect prevalence SERO and case fatality of Coronavirus disease MESHD 2019 (COVID-19). To determine whether COVID-19 prevalence SERO and fatality are modulated by ethnics and economics, meta-regression of data from the countries in the New York metropolitan area were herein conducted. We selected 31 countries in the New York metropolitan area. 1) Prevalence SERO and case-fatality rates of confirmed COVID-19 cases on May 20, 2020 and 2) income and poverty estimates were obtained in each country. We performed random-effects meta-regression using OpenMetaAnalys. The covariates included 1) black (%), 2) Hispanic or Latino (%), 3) poverty rates (%), and 4) median household income ($). Statistically significant (P < .05) covariates in the univariable model were together entered into the multivariable model. A slope (coefficient) of the univariable meta-regression line for COVID-19 prevalence SERO was not significant for household income (P = .639), whereas the coefficient was significantly positive for black (coefficient, 0.021; P = .015), Hispanic/Latino (0.033; P < .001), and poverty (0.039; P = .02), which indicated that COVID-19 prevalence SERO increased significantly as black, Hispanic/Latino, and poverty increased. The multivariable model revealed that the slope was significantly positive for only Hispanic/Latino (P < .001). The coefficient in the univariable model for COVID-19 fatality, however, was not significant for all the covariate. In conclusion, black, Hispanic/Latino, and poverty (not household income), especially Hispanic/Latino independently, may be associated with COVID-19 prevalence SERO. There may be no association of black, Hispanic/Latino, poverty, and household income with COVID-19 fatality.

    In silico Proteome analysis of Severe acute respiratory syndrome MESHD coronavirus 2 (SARS-CoV-2)

    Authors: Chittaranjan Baruah; Papari Devi; Dhirendra K Sharma

    doi:10.1101/2020.05.23.104919 Date: 2020-05-24 Source: bioRxiv

    Severe acute respiratory syndrome MESHD coronavirus 2 (SARS-CoV-2) (2019-nCoV), is a positive-sense, single-stranded RNA coronavirus. The virus is the causative agent of coronavirus disease MESHD 2019 (COVID-19) and is contagious through human-to-human transmission TRANS. The present study reports sequence analysis, complete coordinate tertiary structure prediction and in silico sequence-based and structure-based functional characterization of full SARS-CoV-2 proteome based on the NCBI reference sequence NC_045512 (29903 bp ss-RNA) which is identical to GenBank entry MN908947 and MT415321. The proteome includes 12 major proteins namely orf1ab polyprotein (includes 15 proteins), surface glycoprotein, ORF3a protein, envelope protein, membrane glycoprotein, ORF6 protein, ORF7a protein, orf7b, ORF8, Nucleocapsid phosphoprotein and ORF10 protein. Each protein of orf1ab polyprotein group has been studied separately. A total of 25 polypeptides have been analyzed out of which 15 proteins are not yet having experimental structures and only 10 are having experimental structures with known PDB IDs. Out of 15 newly predicted structures six (6) were predicted using comparative modeling and nine (09) proteins having no significant similarity with so far available PDB structures were modeled using ab-initio modeling. Structure verification using recent tools QMEANDisCo 4.0.0 and ProQ3 for global and local (per-residue) quality estimates indicate that the all-atom model of tertiary structure of high quality and may be useful for structure-based drug designing targets. The study has identified nine major targets (spike protein, envelop protein, membrane protein, nucleocapsid protein, 2-O-ribose methyltransferase, endoRNAse, 3-to-5 exonuclease, RNA-dependent RNA polymerase and helicase) for which drug design targets could be considered. There are other 16 nonstructural proteins (NSPs), which may also be percieved from the drug design angle. The protein structures have been deposited to ModelArchive. Tunnel analysis revealed the presence of large number of tunnels in NSP3, ORF 6 protein and membrane glycoprotein indicating a large number of transport pathways for small ligands influencing their reactivity.

    Computed Tomography and Clinical Features Differentiating Coronavirus Disease MESHD 2019 from Seasonal Influenza Pneumonia MESHD Pneumonia HP

    Authors: Shuang Zhao; Zixing Huang; Hanjiang Zeng; Zhixia Chen; Fengming Luo; Chongwei Zhang; Bin Song

    doi:10.21203/ Date: 2020-05-23 Source: ResearchSquare

    Objectives: To investigate computed tomography (CT) and clinical features could help differentiate coronavirus disease MESHD 2019 (COVID-19) from seasonal influenza pneumonia MESHD pneumonia HP.Methods: We retrospectively evaluated the clinical features and chest CT findings of Chinese patients with COVID-19 and seasonal influenza pneumonia MESHD pneumonia HP treated during the same period. Results: The 24 patients with COVID-19 (mean age TRANS, 41 years; 13 men) and 79 patients with seasonal influenza pneumonia MESHD pneumonia HP (mean age TRANS, 41 years; 50 men) differed significantly in mean temperature, respiratory rate, and systolic blood SERO pressure; in central-peripheral, superior-inferior, and anterior-posterior distribution but not lateral distribution of pulmonary lesions; and patchy ground-glass opacity (GGO), GGO nodules, vascular enlargement in GGO, air bronchogram, bronchiolectasis HP in GGO or consolidation, interlobular septal thickening, and crazy-paving pattern. Separate regression models were developed with clinical features, CT features (including anatomical distributions), and a combined model informed by the first two. The combined model had the best diagnostic performance SERO for identifying COVID-19: a cut-off value of 0.38 was 74% sensitive and 100% specific and had an area under the receiver operating characteristics curve of 0.94. This model was based on sputum production, vascular enlargement in GGO, and central-peripheral distribution (random vs subpleural). Conclusions: The combination of sputum production, vascular enlargement in GGO, and central-peripheral distribution should be extremely helpful in the differential diagnosis of COVID-19. 

    Coronavirus: Comparing COVID-19, SARS and MERS in the eyes of AI

    Authors: Anas Tahir; Yazan Qiblawey; Amith Khandakar; Tawsifur Rahman; Uzair Khurshid; Farayi Musharavati; M. T. Islam; Serkan Kiranyaz; Muhammad E. H. Chowdhury

    id:2005.11524v4 Date: 2020-05-23 Source: arXiv

    Novel Coronavirus disease MESHD (COVID-19) is an extremely contagious and quickly spreading Coronavirus disease MESHD. Severe Acute Respiratory Syndrome MESHD (SARS)-CoV, Middle East Respiratory Syndrome MESHD (MERS)-CoV outbreak in 2002 and 2011 and current COVID-19 pandemic all from the same family of Coronavirus. The fatality rate due to SARS and MERS were higher than COVID-19 however, the spread of those were limited to few countries while COVID-19 affected more than two-hundred countries of the world. In this work, authors used deep machine learning algorithms along with innovative image pre-processing techniques to distinguish COVID-19 images from SARS and MERS images. Several deep learning algorithms were trained, and tested and four outperforming algorithms were reported: SqueezeNet, ResNet18, Inceptionv3 and DenseNet201. Original, Contrast limited adaptive histogram equalized and complemented image were used individually and in concatenation as the inputs to the networks. It was observed that inceptionv3 outperforms all networks for 3-channel concatenation technique and provide an excellent sensitivity SERO of 99.5%, 93.1% and 97% for classifying COVID-19, MERS and SARS images respectively. Investigating deep layer activation mapping of the correctly classified images and miss-classified images, it was observed that some overlapping features between COVID-19 and MERS images were identified by the deep layer network. Interestingly these features were present in MERS images and 10 out of 144 images were miss-classified as COVID while only one out of 423 COVID-19 images was miss-classified as MERS. None of the MERS images was miss-classified to SARS and only one COVID-19 image was miss-classified as SARS. Therefore, it can be summarized that SARS images are significantly different from MERS and COVID-19 in the eyes of AI while there are some overlapping feature available between MERS and COVID-19.

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MeSH Disease
Human Phenotype

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