Corpus overview


Overview

MeSH Disease

Infections (432)

Disease (305)

Death (181)

Coronavirus Infections (164)

Fever (75)


Human Phenotype

Fever (75)

Anxiety (66)

Cough (59)

Hypertension (54)

Pneumonia (38)


Transmission

Seroprevalence
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    Twitter Functions in COVID-19 Pandemic and Other Natural Disasters: A Literature Review

    Authors: Hamed Seddighi; Ibrahim Salmani

    id:10.20944/preprints202008.0235.v1 Date: 2020-08-10 Source: Preprints.org

    Background: Twitter is a major tool for communication in emergencies MESHD such as natural disasters. This online social network allows the user to produce content, and it is not designed exclusively for news releases, as opposed to other service providers. Aim: The aim of this study is to investigate Twitter uses in natural disasters and pandemics. Methods: The included studies reported the role of Twitter in natural disasters. The studies that report in settings other than the natural disasters (such as man-made disasters) and other social media were excluded. Electronic databases for a comprehensive literature search including MEDLINE, Web of Science, CINAHL, PsycINFO, Cochrane Register of Controlled Trials (CENTRAL) and EMBASE were used to identify the records that match the mentioned inclusion criteria published till May 2020. The study characteristics were extracted from the qualified studies including year of publication, findings, and geographical location of the study conduct. A narrative synthesis for this literature review was used. Results: The search identified 822 articles of which 780 articles were removed, 256 were not available, 311 papers were not relevant, 16 were duplicated articles, and 197 were non-related to the emergencies MESHD. 45 articles met the selection criteria and were included in the review. eleven themes were found in the narrative synthesis including early warning, disseminating information and misinformation, advocacy, personal gains, assessment, various roles of organizations, public mood, geographical analysis, charity, using influencers, and trust. Conclusions: It is recommended that influential individuals be identified in each country and community before disasters occur so that the necessary information can be disseminated in response to disasters. Preventing the spread of misinformation is one of the most important issues in times of disaster, especially pandemics. Disseminating accurate, transparent, and prompt information from relief organizations and governments can help. Also, analyzing Twitter data can be a good source for understanding the mental state of the community, estimating the number of injured people, estimating the points affected by natural disasters, and modeling the prevalence SERO of epidemics. Therefore, various groups such as politicians, the government, non-governmental organizations, aid workers, and the health system can use this information to plan and implement interventions.

    A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19)

    Authors: Md. Milon Islam; Fakhri Karray; Reda Alhajj; Jia Zeng

    id:2008.04815v1 Date: 2020-08-09 Source: arXiv

    Novel coronavirus (COVID-19) outbreak, has raised a calamitous situation all over the world and has become one of the most acute and severe ailments in the past hundred years. The prevalence SERO rate of COVID-19 is rapidly rising every day throughout the globe. Although no vaccines for this pandemic have been discovered yet, deep learning techniques proved themselves to be a powerful tool in the arsenal used by clinicians for the automatic diagnosis of COVID-19. This paper aims to overview the recently developed systems based on deep learning techniques using different medical imaging modalities like Computer Tomography (CT) and X-ray. This review specifically discusses the systems developed for COVID-19 diagnosis using deep learning techniques and provides insights on well-known data sets used to train these networks. It also highlights the data partitioning techniques and various performance SERO measures developed by researchers in this field. A taxonomy is drawn to categorize the recent works for proper insight. Finally, we conclude by addressing the challenges associated with the use of deep learning methods for COVID-19 detection and probable future trends in this research area. This paper is intended to provide experts (medical or otherwise) and technicians with new insights into the ways deep learning techniques are used in this regard and how they potentially further works in combatting the outbreak of COVID-19.

    Exposure to Mycobacteria influences disease progression MESHD in COVID-19 patients 

    Authors: Ajay Gupta; Sumit Sural; Ayush Gupta; Shashank Rousa; B.C.Koner; Anju Bhalotra; Rohit Chawla

    doi:10.21203/rs.3.rs-56141/v1 Date: 2020-08-08 Source: ResearchSquare

    Background: COVID-19−related deaths MESHD are significantly higher in countries with higher quality of life. A strong negative correlation is reported between the BCG index and COVID- 19 mortality. The present study explored if a high Th1immunity due to frequent exposure to strong Th1 antigens like Mycobacteria or Salmonella could be the cause for lesser COVID-19−related deaths MESHD in Indian population. Methods: This prospective comparative study was conducted with 3 groups of twenty patients each of mildly symptomatic (A), severely ill (S) Covid patients and healthy volunteers with a Covid Negative report (H).Results: All severely ill patients showed increased leucocyte counts, lymphopenia MESHD lymphopenia HP and raised D-dimer. A gross reversible unresponsiveness of T cells was seen among all patients in S group with absolutely no response even to the mitogen stimulus. Quantiferon TB test value and distribution of test positivity was significantly lower in group S. Three out of 6 survived patients in S group had positive Quantiferon TB test while 2 patients turned positive on repeat test and the sixth patient showed high TH titre on widal test.Conclusion: Altered Th1 immunity associated with frequent community exposure of tuberculosis MESHD and typhoid antigen in Indian population might be responsible for its relatively lesser prevalence SERO and mortality following Covid-19.  

    Obtaining prevalence SERO estimates of COVID-19: A model to inform decision-making

    Authors: Ida Sahlu; Alexander B Whittaker

    doi:10.1101/2020.08.06.20169656 Date: 2020-08-07 Source: medRxiv

    Objectives: The primary aim was to evaluate whether randomly sampling and testing a set number of individuals for active or past COVID-19 while adjusting for misclassification error captures a simulated prevalence SERO. The secondary aim was to quantify the impact of misclassification error bias on publicly reported case data in Maryland. Methods: Using a stratified random sampling approach, 50,000 individuals were selected from a simulated Maryland population to estimate the prevalence SERO of active and past COVID-19. Data from the 2014-2018 and 2018 American Community Surveys were used. The simulated prevalence SERO was 0.5% and 1.0% for active and past COVID-19, respectively. Bayesian models, informed by published validity estimates, were used to account for misclassification error when estimating the prevalence SERO of active and past COVID-19. Results: Failure to account for misclassification error overestimated the simulated prevalence SERO for active and past COVID-19. Adjustment for misclassification error decreased the point estimate for active and past COVID-10 prevalence SERO by 55% and 29%, respectively. Adjustment for sampling method and misclassification error only captured the simulated past COVID-19 prevalence SERO. The simulated active COVID-19 prevalence SERO was only captured when set to 0.7% and above. Adjustment for misclassification error for publicly reported Maryland data increased the estimated average daily cases by 8%. Conclusions: Random sampling and testing of COVID-19 is needed but must be accompanied by adjustment for misclassification error to avoid over- or underestimating the prevalence SERO. This approach bolsters disease MESHD control efforts. Implementing random testing for active COVID-19 may be best in a smaller geographic area with highly prevalent cases.

    CRISPR-based and RT-qPCR surveillance of SARS-CoV-2 in asymptomatic TRANS individuals uncovers a shift in viral prevalence SERO among a university population

    Authors: Jennifer N Rauch; Eric Valois; Jose Carlos Ponce-Rojas; Zach Aralis; Ryan L Lach; Francesca Zappa; Morgane Audouard; Sabrina C Solley; Chinmay Vaidya; Michael Costello; Holly Smith; Ali Javanbakht; Betsy Malear; Laura Polito; Stewart Comer; Katherine Arn; Kenneth S Kosik; Diego Acosta-Alvear; Maxwell Z Wilson; Lynn Fitzgibbons; Carolina Arias

    doi:10.1101/2020.08.06.20169771 Date: 2020-08-07 Source: medRxiv

    Background: The progress of the COVID-19 pandemic profoundly impacts the health of communities around the world, with unique impacts on colleges and universities. Transmission TRANS of SARS-CoV-2 by asymptomatic TRANS people is thought to be the underlying cause of a large proportion of new infections MESHD. However, the local prevalence SERO of asymptomatic TRANS and pre-symptomatic carriers TRANS of SARS-CoV-2 is influenced by local public health restrictions and the community setting. Objectives: This study has three main objectives. First, we looked to establish the prevalence SERO of asymptomatic TRANS SARS-CoV-2 infection MESHD on a university campus in California. Second, we sought to assess the changes in viral prevalence SERO associated with the shifting community conditions related to non-pharmaceutical interventions (NPIs). Third, we aimed to compare the performance SERO of CRISPR- and PCR-based assays for large-scale virus surveillance sampling in COVID-19 asymptomatic TRANS persons. Methods: We enrolled 1,808 asymptomatic TRANS persons for self-collection of oropharyngeal (OP) samples to undergo SARS-CoV-2 testing. We compared viral prevalence SERO in samples obtained in two time periods: May 28th-June 11th; June 23rd-July 2nd. We detected viral genomes in these samples using two assays: CREST, a CRISPR-based method recently developed at UCSB, and the RT-qPCR test recommended by US Centers for Disease MESHD Control and Prevention (CDC). Results: Of the 1,808 participants, 1,805 were affiliates of the University of California, Santa Barbara, and 1,306 were students. None of the tests performed on the 732 samples collected between late May to early June were positive. In contrast, tests performed on the 1076 samples collected between late June to early July, revealed nine positive cases. This change in prevalence SERO met statistical significance, p = 0.013. One sample was positive by RT-qPCR at the threshold of detection, but negative by both CREST and CLIA-confirmation testing. With this single exception, there was perfect concordance in both positive and negative results obtained by RT-qPCR and CREST. The estimated prevalence SERO of the virus, calculated using the confirmed cases TRANS, was 0.74%. The average age TRANS of our sample population was 28.33 (18-75) years, and the average age TRANS of the positive cases was 21.7 years (19-30). Conclusions: Our study revealed that there were no COVID-19 cases in our study population in May/June. Using the same methods, we demonstrated a substantial shift in prevalence SERO approximately one month later, which coincided with changes in community restrictions and public interactions. This increase in prevalence SERO, in a young and asymptomatic TRANS population which would not have otherwise accessed COVID-19 testing, indicated the leading wave of a local outbreak, and coincided with rising case counts in the surrounding county and the state of California. Our results substantiate that large, population-level asymptomatic TRANS screening using self-collection may be a feasible and instructive aspect of the public health approach within large campus communities, and the almost perfect concordance between CRISPR- and PCR-based assays indicate expanded options for surveillance testing

    Prevalence SERO of SARS-CoV-2 among high-risk populations in Lomé (Togo) in 2020

    Authors: Wemboo Afiwa Halatoko; Yao Rodion KONU; Fifonsi Adjidossi Gbeasor-Komlanvi; Arnold Junior Sadio; Martin Kouame Tchankoni; Koffi Segbeaya Komlanvi; Mounerou Salou; Ameyo Monique Dorkenoo; Issaka Maman; Ametepe Agbobli; Majeste Ihou Wateba; Komi Seraphin Adjoh; Edem Goeh Akue; Yem-bla Kao; Innocent Kpeto; Paul Pana; Rebecca Kinde-Sossou; Agbeko Tamakloe; Josee Nayo-Apetsianyi; Simon-Pierre Hamadi Assane; Mireille Prince-David; Sossinou Marcel Awoussi; Mohaman Djibril; Moustafa Mijiyawa; Anoumou Claver Dagnra; Didier Koumavi Ekouevi

    doi:10.1101/2020.08.07.20163840 Date: 2020-08-07 Source: medRxiv

    Objective: This survey aims at estimating the prevalence SERO of SARS-CoV-2 in high risk populations in Lomé. Methods: From April 23rd to May 8th 2020, we recruited a sample of participants from five sectors: healthcare, air transport, police, road transport and informal. We collected oropharyngeal swab for direct detection through real time reverse transcription polymerase chain reaction (rRT-PCR), and blood SERO for antibodies SERO detection by serological tests SERO. The overall prevalence SERO (current and past) of infection MESHD was defined by positivity for both tests. Results: A total of 955 participants with a median age TRANS of 36 (IQR 32-43) were included and 71.6% (n=684) were men. Around 22.1% (n=212) were from the air transport sector, 20.5% (n=196) in the police, and 38.7% (n=370) in the health sector. Seven participants (0.7%, 95% CI: 0.3-1.6%) had a positive rRT-PCR at the time of recruitment and nine (0.9%, 95% CI: 0.4-1.8%) were seropositive for IgM or IgG against SARS-CoV-2. We found an overall prevalence SERO of 1.6% (n=15), 95% CI: 0.9-2.6%. Conclusion: The prevalence SERO of the SARS-CoV-2 infection MESHD among high-risk populations in Lomé was relatively low and could be explained by the various measures taken by the Togolese government. Therefore, we recommend targeted screening.

    Strategic anti-SARS-CoV-2 serology testing in a low prevalence SERO pandemic: The COVID-19 Contact (CoCo) Study in health care professionals

    Authors: Georg MN Behrens; Anne Cossmann; Metodi V Stankov; Bianca Schulte; Hendrik Streeck; Reinhold Foerster; Berislav Bosnjak; Stefanie Willenzon; Anna-Lena Boeck; Anh Thu Tran; Thea Thiele; Theresa Graalmann; Moritz Z. Kayser; Anna Zychlinsky Scharff; Christian Dopfer; Alexander Horke; Isabell Pink; Torsten Witte; Martin Wetzke; Diana Ernst; Alexandra Jablonka; Christine Happle

    doi:10.1101/2020.08.06.20169250 Date: 2020-08-07 Source: medRxiv

    Background: Serology testing is explored for epidemiological research and to inform individuals after suspected infection MESHD. During the COVID-19 pandemic, frontline healthcare professionals (HCP) may be at particular risk for infection TRANS risk for infection TRANS infection MESHD. No longitudinal data on functional seroconversion in HCP in regions with low COVID-19 prevalence SERO and low pre-test probability exist. Methods: In a large German university hospital, we performed weekly questionnaire assessments and anti-SARS-CoV-2 IgG measurements with various commercial tests, a novel surrogate virus neutralization test, and a neutralization assay using live SARS-CoV-2. Results: From baseline to week six, n=1,080 screening measurements for anti-SARS CoV-2 (S1) IgG from n=217 frontline HCP (65% female TRANS) were performed. Overall, 75.6% of HCP reported at least one symptom of respiratory infection MESHD. Self-perceived infection MESHD probability declined over time (from mean 20.1% at baseline to 12.4 % in week six, p<0.001). In sera of convalescent PCR-confirmed COVID-19 patients, we measured high anti-SARS-CoV-2 IgG levels, obtained highly concordant results from ELISAs SERO using e.g. the S1 spike protein domain and the nucleocapsid protein (NCP) as targets, and confirmed antiviral neutralization. However, in HCP the cumulative incidence for anti-SARS-CoV-2 (S1) IgG was 1.86% for positive and 0.93% for equivocal positive results over the six week study period. Except for one HCP, none of the eight initial positive results were confirmed by alternative serology tests or showed in vitro neutralization against live SARS CoV-2. The only true seroconversion occurred without symptoms and mounted strong functional humoral immunity. Thus, the confirmed cumulative incidence for neutralizing anti-SARS-CoV-2 IgG was 0.47%. Conclusion: When assessing anti-SARS-CoV-2 immune status in individuals with low pre-test probability, we suggest confirming positive results from single measurements by alternative serology tests or functional assays. Our data highlight the need for a methodical serology screening approach in regions with low SARS-CoV-2 infection MESHD rates.

    The association between lockdown due to COVID-19 epidemic and searches for toothache MESHD using Google Trends in Iran

    Authors: Ahmad Sofi-Mahmudi; Erfan Shamsoddin; Peyman Ghasemi; Ali Mehrabi Bahar; Mansour Shaban Azad; Ghasem Sadeghi

    doi:10.1101/2020.08.06.20160515 Date: 2020-08-07 Source: medRxiv

    Objective: To assess the association between the lockdowns due to COVID-19 and online searches for toothache MESHD in Iran using Google Trends (GT). Methods: We investigated GT online searches for the search term within the past five years. The time frame for data gathering was considered as the initiation and end dates of lockdown in Iran. Relative search volumes (RSVs) for online Google Search queries in 2019 was considered as the control. We performed one-way ANOVA statistical test to identify whether there is a statistical difference for RSV scores between the year 2020 and 2016-2019 for the whole country. Then we investigated the possible association of RSVs in provinces with dentists density, prevalence SERO of current daily smokers, Human Development Index (HDI), Internet access, and fluoride concentration in water with linear regression. A p-value<0.05 was considered as statistically significant. Results: When comparing 2020 with previous four years, there is a statistically significant difference between RSVs of 2020 with all previous years combined and each of these years (P<0.001 for all of them). In the linear model for the year 2020, HDI (B=-3.29, 95% CI: (-5.80, -0.78), P=0.012), fluoride concentration (B=-0.13, 95% CI: (-0.24, -0.03), P=0.017), and prevalence SERO of daily smokers (B=0.33, 95% CI: (0.13, 0.53), P=0.002) were significantly associated with RSVs. These covariates were not statistically significant for other years, except for Internet access in 2016 (B=-1.13, 95% CI: (-2.26, 0.00), P=0.050). Conclusion: The RSVs for toothache MESHD in 2020 have significantly increased due to COVID-19-imposed lockdowns compared to the same period of the year in the past four years. knowing that this period mostly overlaps with the national holidays of Nowruz in Iran, reinforces the impacts of lockdowns on people CSB about toothache MESHD. In the subnational scale, the RSVs were significantly correlated with HDI, fluoride concentration, and number of daily smokers which emphasizes the role of socioeconomic factors in dental health and care-seeking behaviour.

    Estimating the Changing Infection MESHD Rate of COVID-19 Using Bayesian Models of Mobility

    Authors: Luyang Liu; Sharad Vikram; Junpeng Lao; Xue Ben; Alexander D'Amour; Shawn O'Banion; Mark Sandler; Rif A. Saurous; Matthew D. Hoffman

    doi:10.1101/2020.08.06.20169664 Date: 2020-08-07 Source: medRxiv

    In order to prepare for and control the continued spread of the COVID-19 pandemic while minimizing its economic impact, the world needs to be able to estimate and predict COVID-19's spread. Unfortunately, we cannot directly observe the prevalence SERO or growth rate of COVID-19; these must be inferred using some kind of model. We propose a hierarchical Bayesian extension to the classic susceptible-exposed-infected-removed (SEIR) compartmental model that adds compartments to account for isolation and death MESHD and allows the infection MESHD rate to vary as a function of both mobility data collected from mobile phones and a latent time-varying factor that accounts for changes in behavior not captured by mobility data. Since confirmed-case TRANS data is unreliable, we infer the model's parameters conditioned on deaths MESHD data. We replace the exponential-waiting-time assumption of classic compartmental models with Erlang distributions, which allows for a more realistic model of the long lag between exposure and death MESHD. The mobility data gives us a leading indicator that can quickly detect changes in the pandemic's local growth rate and forecast changes in death MESHD rates weeks ahead of time. This is an analysis of observational data, so any causal interpretations of the model's inferences should be treated as suggestive at best; nonetheless, the model's inferred relationship between different kinds of trips and the infection MESHD rate do suggest some possible hypotheses about what kinds of activities might contribute most to COVID-19's spread.

    Performance SERO assessment of 11 commercial serological tests SERO for SARS-CoV-2 on hospitalized COVID-19 patients

    Authors: Claudia Serre-Miranda; Claudia Nobrega; Susana Roque; Joao Canto-Gomes; Carolina S Silva; Neide Vieira; Palmira Barreira-Silva; Pedro Alves-Peixoto; Jorge Cotter; Ana Reis; Mariana Formigo; Helena Sarmento; Olga Pires; Alexandre Carvalho; Dmitri Y Petrovykh; Lorena Dieguez; Joao C Sousa; Nuno Sousa; Carlos Capela; Joana A Palha; Pedro G Cunha; Margarida Correia-Neves

    doi:10.1101/2020.08.06.20168856 Date: 2020-08-07 Source: medRxiv

    Commercial availability of serological tests SERO to evaluate immunoglobulins (Ig) towards severe acute respiratory syndrome MESHD coronavirus 2 (SARS-CoV-2) has grown exponentially since the onset of COVID-19 outbreak. Their thorough validation is of extreme importance before using them as epidemiological tools to infer population seroprevalence SERO, and as complementary diagnostic tools to molecular approaches (e.g. RT-qPCR). Here we assayed commercial serological tests SERO (semiquantitative and qualitative) from 11 suppliers in 126 samples collected from hospitalized COVID-19 patients, and from 36 healthy and HIV-infected individuals (collected at the pre-COVID-19 pandemic). Specificity was above 95% in 9 tests. Samples from COVID-19 patients were stratified by days since symptoms onset TRANS (<10, 10-15, 16-21 and >21 days). Tests sensitivity SERO increases with time since symptoms onset TRANS, and peaks at 16-21 days for IgM and IgA (maximum: 91.2%); and from 16-21 to >21 days for IgG, depending on the test (maximum: 94.1%). Data from semiquantitative tests show that patients with severe clinical presentation have lower relative levels of IgM, IgA and IgG at <10 days since symptoms onset TRANS in comparison to patients with non-severe presentation. At >21 days since symptoms onset TRANS the relative levels of IgM and IgG (in one test) are significantly higher in patients with severe clinical presentation, suggesting a delay in the upsurge of Ig against SARS-CoV-2 in those patients. This study highlights the high specificity of most of the evaluated tests, and sensitivity SERO heterogeneity. Considering the virus genetic evolution and population immune response to it, continuous monitoring of commercially available serological tests SERO towards SARS-CoV-2 is necessary.

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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