Corpus overview


MeSH Disease

Fever (479)

Cough (309)

Coronavirus Infections (251)

Dyspnea (211)

Infections (203)

Human Phenotype

Cough (689)

Fever (523)

Fatigue (185)

Pneumonia (163)

Dyspnea (109)


age categories (332)

gender (217)

Transmission (152)

fomite (101)

asymptotic cases (100)

    displaying 1 - 10 records in total 689
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    Authors: Valeria Oliveira Silva; Elaine Lopes de Oliveira; Marcia Jorge Castejon; Rosemeire Yamashiro; Cintia Mayumi Ahagon; Giselle Ibette Lopez-Lopes; Edilene Peres Real da Silveira; Marisa Ailin Hong; Maria do Carmo Timenetsky; Carmem aparecida de Freitas Oliveira; Luis Fernando de Macedo Brigido; Satish Lakkakula; Oren Miron; Ehud Rinott; Ricardo Gilead Baibich; Iris Bigler; Matan Malul; Rotem Rishti; Asher Brenner; Yair E. Lewis; Eran Friedler; Yael Gilboa; Sara Sabach; Yuval Alfiya; Uta Cheruti; Nadav Davidovitch; Natalya Bilenko; Jacob Moran-Gilad; Yakir Berchenko; Itay Bar-Or; Ariel Kushmaro; Timothy Spector; Claire J Steves

    doi:10.1101/2020.10.19.20213421 Date: 2020-10-21 Source: medRxiv

    Background: Covid-19 Serology may document exposure and perhaps protection to the virus, and serological test SERO may help understand epidemic dynamics. To evaluate previous exposure to the virus we estimated the prevalence SERO of antibodies SERO against-SARS-CoV-2 among HPs in Adolfo Lutz Institute, State of Sao Paulo, Brazil. Methods: This study was performed among professionals of Adolfo Lutz Institute in Sao Paulo, Brazil and some administrative areas of the Secretary of Health that shares common areas with the institute. We used a lateral flow immunoassay SERO ( rapid test SERO) to detect IgG and IgM for SARS-CoV-2; positive samples were further evaluated using Roche Electrochemiluminescence assay and SARS-CoV-2 RNA by real time reverse transcriptase polymerase chain reaction (RT-PCR) was also offered to participants. Results: A total of 406 HPs participated. Thirty five (8.6%) tested positive on rapid test SERO and 32 these rapid test SERO seropositive cases were confirmed TRANS by ECLIA.. 43 HPs had SARS-CoV-2 RNA detected at a median of 33 days, and the three cases not reactive at Roche ECLIA had a previous positive RNA. Outsourced professionals (34% seropositive), males TRANS (15%) workers referring COVID-19 patients at home (22%) and those living farther form the institute tended to have higher prevalence SERO of seropositivity, but in multivariable logistic analysis only outsourced workers and those with COVID patients at home remained independently associated to seropositivity. We observed no relation of seropositivity to COVID samples handling. Presence of at least one symptom was common but some clinical manifestations as anosmia HP anosmia MESHD/dysgeusia. Fatigue HP, cough HP cough MESHD and fever HP fever MESHD were associated to seropositivity. Conclusions: We documented a relatively high (8.6%) of anti-SARS-CoV-2 serological reactivity in this population, with higher rates among outsourced workers and those with referring cohabitation with COVID-19 patients. COVID samples handling was not related to increased seropositivity. Some symptoms how strong association to COVID-19 serology and may be used in scoring tools for screening or diagnosis in resort limited settings.

    Systematic review of reviews of symptoms and signs of COVID-19 in children TRANS and adolescents

    Authors: Russell M Viner; Joseph Ward; Lee Hudson; Melissa Ashe; Sanjay Patel; Dougal Hargreaves; Elizabeth Whittaker; Seiichi Ichikawa; Daisuke Mizushima; Shingo Iwami; Ferenc E Mózes; Adam J Lewandowski; Eric O Ohuma; David Holdsworth; Hanan Lamlum; Myles J Woodman; Catherine Krasopoulos; Rebecca Mills; Flora A Kennedy McConnel; Chaoyue Wang; Christoph Arthofer; Frederik J Lange; Jesper Andersson; Mark Jenkinson; Charalambos Antoniades; Keith M Channon; Mayooran Shanmuganathan; Vanessa M Ferreira; Stefan K Piechnik; Paul Klenerman; Christopher Brightling; Nick P Talbot; Nayia Petousi; Najib M Rahman; Ling-Pei Ho; Kate Saunders; John R Geddes; Paul Harrison; Kyle Pattinson; Matthew J Rowland; Brian Angus; Fergus Gleeson; Michael Pavlides; Ivan Koychev; Karla L Miller; Clare Mackay; Peter Jezzard; Stephen M Smith; Stefan Neubauer

    doi:10.1101/2020.10.16.20213298 Date: 2020-10-18 Source: medRxiv

    Objective To undertake a systematic review of reviews of the prevalence SERO of symptoms and signs of COVID-19 in those aged TRANS under 20 years? Design Narrative systematic review of reviews. PubMed, medRxiv, Europe PMC and COVID-19 Living Evidence Database were searched on 9 October 2020. Setting All settings, including hospitalised and community settings. Patients CYP under age TRANS 20 years with laboratory-proven COVID-19. Study review, data extraction and quality Potentially eligible articles were reviewed on title and abstract by one reviewer. Quality was assessed using the modified AMSTARS criteria and data were extracted from included studies by two reviewers. Main outcome measures Prevalence SERO of symptoms and signs of COVID-19 Results 1325 studies were identified and 18 reviews were included. Eight were high quality, 7 medium and 3 low quality. All reviews were dominated by studies of hospitalised children TRANS. The proportion who were asymptomatic TRANS ranged from 14.6 to 42%. Fever HP Fever MESHD and cough HP cough MESHD were the commonest symptoms; proportions with fever HP fever MESHD ranged from 46 to 64.2% and with cough HP from 32 to 55.9%. All other symptoms or signs including rhinorrhoea, sore throat, headache HP headache MESHD, fatigue HP fatigue MESHD/ myalgia HP myalgia MESHD and gastrointestinal symptoms including diarrhoea and vomiting MESHD vomiting HP are infrequent, occurring in less than 10-20%. Conclusions Fever HP Fever MESHD and cough HP cough MESHD are the most common symptoms in CYP with COVID-19, with other symptoms infrequent. Further research on symptoms in community samples are needed to inform pragmatic identification and testing programmes for CYP.

    Studying the Similarity of COVID-19 Sounds based on Correlation Analysis of MFCC

    Authors: Mohamed Bader; Ismail Shahin; Abdelfatah Hassan

    id:2010.08770v1 Date: 2020-10-17 Source: arXiv

    Recently there has been a formidable work which has been put up from the people who are working in the frontlines such as hospitals, clinics, and labs alongside researchers and scientists who are also putting tremendous efforts in the fight against COVID-19 pandemic. Due to the preposterous spread of the virus, the integration of the artificial intelligence has taken a considerable part in the health sector, by implementing the fundamentals of Automatic Speech Recognition (ASR) and deep learning algorithms MESHD. In this paper, we illustrate the importance of speech signal processing in the extraction of the Mel-Frequency Cepstral Coefficients (MFCCs) of the COVID-19 and non-COVID-19 samples and find their relationship using Pearson correlation coefficients. Our results show high similarity in MFCCs between different COVID-19 cough HP cough MESHD and breathing sounds, while MFCC of voice is more robust between COVID-19 and non-COVID-19 samples. Moreover, our results are preliminary, and there is a possibility to exclude the voices of COVID-19 patients from further processing in diagnosing the disease.

    Understanding the value of clinical symptoms of COVID-19. A logistic regression model

    Authors: Pedro Emanuel Fleitas; Jorge A Paz; Mario I Simoy; Carlos Vargas; Ruben O Cimino; Alejandro J Krolewiecki; Juan P Aparicio; Haifeng Wang; Dejing Dou; Pete Bond; Paul Anthony McAry; Sharad Bhagat; Itti Munshi; Swapneil Parikh; Sachee Agrawal; Chandrakant Pawar; Mala Kaneria; Smita Mahale; Jayanthi Shastri; Vainav Patel; Paul Dark; Alexander Mathioudakis; Kathryn Gray; Graham Lord; Timothy Felton; Chris Brightling; Ling-Pei Ho; - NIHR Respiratory TRC; - CIRCO; Karen Piper Hanley; Angela Simpson; John R Grainger; Tracy Hussell; Elizabeth R Mann

    doi:10.1101/2020.10.07.20207019 Date: 2020-10-16 Source: medRxiv

    Background The new coronavirus SARS-CoV-2, the causative agent of COVID-19, is responsible for the current pandemic outbreak worldwide. However, there is limited information regarding the set of specific symptoms of COVID-19. Therefore, the objective of this study was to describe the main symptoms associated with COVID-19 to aid in the clinical diagnosis for the rapid identification of cases. Methods and findings A cross sectional study of all those diagnosed by RT-PCR for SARS-CoV-2 between April 1 and May 24 in Argentina was conducted. The data includes clinical and demographic information from all subjects at the time of presentation, which were uploaded to the centralized national reporting system at health centers. A total of 67318 individuals were included in this study, where 12% tested positive for SARS-CoV-2. The study population was divided in two age groups TRANS, a group aged TRANS 0 to 55 years-old (<56 group), (median = 32, n=48748) and another group aged TRANS 56 to 103 years-old ([≥]56 group) (median =72, n=18570). A cross sectional study of all those diagnosed by RT-PCR for SARS-CoV-2 between April 1 and May 24 in Argentina was conducted. The data includes clinical and demographic information from all subjects at the time of presentation, which were uploaded to the centralized national reporting system at health centers.Multivariate logistic regression analyses showed that out of a total of 23 symptoms, only five were found to have a positive association with COVID-19: anosmia HP anosmia MESHD (odds ratio [OR] 10.40, 95% confidence interval [CI] 8.20-13.10, <56 group; OR 6.09 CI 3.05-12.20, [≥]56 group), dysgeusia MESHD (OR 3.67, CI 2.7-4.9, <56 group; OR 3.53 CI 1.52-8.18, [≥]56 group), low grade fever HP fever MESHD (37.5-37.9 {degrees}C) (OR 1.61, CI 1.20-2.05, <56 group; OR 1.80 CI 1.07-3.06, [≥]56 group), cough HP (OR 1.20, CI 1.05-1.38, <56 group; OR 1.37 CI 1.04-1.80, [≥]56 group) and headache HP headache MESHD only in <56 group (OR 1.71, CI 1.48-1.99). In turn, at the time of presentation, the symptoms associated with respiratory problems: chest pain HP chest pain MESHD, tachypnea HP tachypnea MESHD, dyspnea HP dyspnea MESHD, respiratory failure HP respiratory failure MESHD and use of accessory muscles for breathing, had a negative association with COVID-19 (OR <1) or did not present statistical relevance (OR = 1). With the intention of helping the clinical diagnosis, we designed a model to be able to identify possible cases of COVID-19. This model included 16 symptoms, the age TRANS and sex of the individuals, and was able to detect 80% of those infected with SARS-CoV-2 with a specificity of 46%. Conclusions The analysis of symptoms opens the opportunity for a guidance and improved symptoms based definition of suspected cases of COVID-19, where multiple factors ( age TRANS, sex, symptoms and interaction between symptoms) are considered. We present a tool to help identify COVID-19 cases to provide quick information to aid decision-making by health personnel and program managers.

    On Modeling of COVID-19 for the Indian Subcontinent using Polynomial and Supervised Learning Regression MESHD

    Authors: Dishita Neve; Honey Patel; Harsh S Dhiman; Victoria Acquaye; Alfred D. Dai-Kosi; Alejandro J Krolewiecki; Juan P Aparicio; Haifeng Wang; Dejing Dou; Pete Bond; Paul Anthony McAry; Sharad Bhagat; Itti Munshi; Swapneil Parikh; Sachee Agrawal; Chandrakant Pawar; Mala Kaneria; Smita Mahale; Jayanthi Shastri; Vainav Patel; Paul Dark; Alexander Mathioudakis; Kathryn Gray; Graham Lord; Timothy Felton; Chris Brightling; Ling-Pei Ho; - NIHR Respiratory TRC; - CIRCO; Karen Piper Hanley; Angela Simpson; John R Grainger; Tracy Hussell; Elizabeth R Mann

    doi:10.1101/2020.10.14.20212563 Date: 2020-10-16 Source: medRxiv

    COVID-19, a recently declared pandemic by WHO has taken the world by storm causing catastrophic damage MESHD to human life. The novel cornonavirus disease MESHD was first incepted in the Wuhan city of China on 31st December 2019. The symptoms include fever HP fever MESHD, cough HP cough MESHD, fatigue HP fatigue MESHD, shortness of breath MESHD or breathing difficulties, and loss of smell and taste. Since the devastating phenomenon is essentially a time-series representation, accurate modeling may benefit in identifying the root cause and accelerate the diagnosis. In the current analysis, COVID-19 modeling is done for the Indian subcontinent based on the data collected for the total cases confirmed TRANS, daily recovered, daily deaths, total recovered and total deaths. The data is treated with total confirmed cases TRANS as the target variable and rest as feature variables. It is observed that Support vector regressions yields accurate results followed by Polynomial regression. Random forest regression results in overfitting followed by poor Bayesian regression due to highly correlated feature variables. Further, in order to examine the effect of neighbouring countries, Pearson correlation matrix is computed to identify geographic cause and effect.

    Early-stage COVID-19 diagnosis in presence of limited posteroanterior chest X-ray images via novel Pinball-OCSVM

    Authors: Sanjay Kumar Sonbhadra; Sonali Agarwal; P. Nagabhushan

    id:2010.08115v1 Date: 2020-10-16 Source: arXiv

    It is evident that the infection with this severe HP infection with this severe MESHD acute respiratory syndrome coronavirus 2 MESHD (SARS-CoV-2) starts with the upper respiratory tract and as the virus grows, the infection can progress to lungs and develop pneumonia HP pneumonia MESHD. According to the statistics, approximately 14\% of the infected people with COVID-19 have severe cough HP cough MESHD and shortness of breath MESHD due to pneumonia HP pneumonia MESHD, because as the viral infection increases, it damages the alveoli (small air sacs) and surrounding tissues. The conventional way of COVID-19 diagnosis is reverse transcription polymerase chain reaction (RT-PCR), which is less sensitive during early stages specially, if the patient is asymptomatic TRANS that may further lead to more severe pneumonia HP pneumonia MESHD. To overcome this problem an early diagnosis method is proposed in this paper via one-class classification approach using a novel pinball loss function based one-class support vector machine (PB-OCSVM) considering posteroanterior chest X-ray images. Recently, several automated COVID-19 diagnosis models have been proposed based on various deep learning architectures MESHD to identify pulmonary infections MESHD using publicly available chest X-ray (CXR) where the presence of less number of COVID-19 positive samples compared to other classes (normal, pneumonia HP pneumonia MESHD and Tuberculosis MESHD) raises the challenge for unbiased learning in deep learning MESHD models that has been solved using class balancing techniques which however should be avoided in any medical diagnosis process. Inspired by this phenomenon, this article proposes a novel PB-OCSVM model to work in presence of limited COVID-19 positive CXR samples with objectives to maximize the learning efficiency while minimize the false-positive and false-negative predictions. The proposed model outperformed over recently published deep learning approaches where accuracy, precision, specificity and sensitivity SERO are used as performance SERO measure parameters.

    Heterogeneity in transmissibility TRANS and shedding SARS-CoV-2 via droplets and aerosols

    Authors: Paul Z Chen; Niklas Bobrovitz; Zahra Premji; Marion Koopmans; David N Fisman; Frank X Gu; Carlos Eduardo Negrao; Marcelo Rodrigues dos Santos; Jason D Goldman; Jennifer J Hadlock; Andrew T Magis; Brian T Garibaldi; Stuart C Ray; Christopher Mecoli; Lisa Christopher-Stine; Laura Gutierrez-Alamillo; Qingyuan Yang; David Hines; William Clarke; Richard Eric Rothman; Andrew Pekosz; Katherine Fenstermacher; Zitong Wang; Scott L Zeger; Antony Rosen

    doi:10.1101/2020.10.13.20212233 Date: 2020-10-15 Source: medRxiv

    A growing number of studies provide insight into how SARS-CoV-2 spreads1-7. Yet, many factors that characterize its transmissibility TRANS remain unclear, including mechanistic correlates of overdispersion, viral kinetics, the extent to which respiratory droplets and aerosols carry viable virus and the infectiousness of asymptomatic TRANS, presymptomatic and pediatric cases7. Here, we developed a comprehensive dataset of respiratory viral loads (rVLs) via systematic review and investigated these factors using meta-analyses and modeling. By comparing cases of COVID-19, SARS and influenza A(H1N1)pdm09, we found that heterogeneity in rVL was associated with overdispersion and facilitated the distinctions in individual variation in infectiousness among these emergent diseases. For COVID-19, case heterogeneity was broad throughout the infectious period TRANS, although rVL tended to peak at 1 day from symptom onset TRANS (DFSO) and be elevated for 1-5 DFSO. While most cases presented minimal risk, highly infectious ones could spread SARS-CoV-2 by talking, singing or breathing, which shed virions at comparable rates via droplets and aerosols. Coughing HP shed considerable quantities of virions, predominantly via droplets, and greatly increased the contagiousness of many symptomatic cases relative to asymptomatic TRANS ones. Asymptomatic TRANS and symptomatic infections showed similar likelihoods of expelling aerosols with SARS-CoV-2, as did adult TRANS and pediatric cases. Children TRANS tended to be less contagious by droplet spread than adults TRANS based on tendencies of symptomatology rather than rVL. Our findings address longstanding questions on SARS-CoV-2 transmissibility TRANS and present pertinent considerations for disease control.

    Mass Flow Analysis of SARS-CoV-2 for quantified COVID-19 Risk Analysis

    Authors: Gjalt Huppes; Ruben Huele

    id:2010.07826v1 Date: 2020-10-15 Source: arXiv

    How may exposure risks to SARS-CoV-2 be assessed quantitatively? The material metabolism approach of Industrial Ecology can be applied to the mass flows of these virions by their numbers, as a key step in the analysis of the current pandemic. Several transmission TRANS routes of SARS-2 from emission by a person to exposure of another person have been modelled and quantified. Start is a COVID-19 illness progression model specifying rising emissions by an infected person: the human virion factory. The first route covers closed spaces, with an emission, concentration, and decay model quantifying exposure. A next set of routes covers person-to-person contacts mostly in open spaces, modelling the spatial distribution of exhales towards inhalation. These models also cover incidental exposures, like coughs HP and sneezes HP, and exposure through objects. Routes through animal contacts, excrements, and food, have not been quantified. Potential exposures differ by six orders of magnitude. Closed rooms, even with reasonably (VR 2) to good (VR 5) ventilation, constitute the major exposure risks. Close person-to-person contacts of longer duration create two orders of magnitude lower exposure risks. Open spaces may create risks an order of magnitude lower again. Burst of larger droplets may cause a common cold but not viral pneumonia HP pneumonia MESHD as the virions in such droplets cannot reach the alveoli. Fomites have not shown viable viruses in hospitals, let alone infections. Infection by animals might be possible, as by cats and ferrets kept as pets. These results indicate priority domains for individual and collective measures. The wide divergence in outcomes indicates robustness to most modelling and data improvements, hardly leading to major changes in relative exposure potentials. However, models and data can substantially be improved.

    Symptoms associated with SARS-CoV-2 infection MESHD in a community-based population: Results from an epidemiological study

    Authors: Brian E Dixon; Kara Wools-Kaloustian; William F Fadel; Thoomas J Duszynski; Constantin Yiannoutsos; Paul K Halverson; Nir Menachemi; Ayo-Maria Olofinuka; Vetty Agala; John Nwolim Paul; Doris Nria; Chinenye Okafor; Ifeoma Ndekwu; Chikezie Opara; Chris Newsom

    doi:10.1101/2020.10.11.20210922 Date: 2020-10-14 Source: medRxiv

    Background: Studies examining symptoms of COVID-19 are primarily descriptive and measured among hospitalized individuals. Understanding symptoms of SARS-CoV-2 infection MESHD may improve clinical screening, particularly during flu season. We sought to identify key symptoms and symptom combinations in a community-based population. Methods: We pooled statewide, community-based cohorts of individuals aged TRANS 12 and older screened for SARS-CoV-2 infection MESHD in April and June 2020. Main outcome was SARS-CoV-2 positivity. We calculated sensitivity SERO, specificity, positive predictive value SERO (PPV), and negative predictive value SERO (NPV) for individual symptoms as well as symptom combinations. We further employed multivariable logistic regression and exploratory factor analysis (EFA) to examine symptoms and combinations associated with SARS-CoV-2 infection MESHD. Results: Among 8214 individuals screened, 368 individuals (4.5%) were RT-PCR positive for SARS-CoV-2. Although two-thirds of symptoms were highly specific (>90.0%), most symptoms individually possessed a PPV <50.0%. The individual symptoms most greatly associated with SARS-CoV-2 positivity were fever HP fever MESHD (OR=5.34, p<0.001), anosmia HP anosmia MESHD (OR=4.08, p<0.001), ageusia MESHD (OR=2.38, p=0.006), and cough HP (OR=2.86, p<0.001). Results from EFA identified two primary symptom clusters most associated with SARS-CoV-2 infection MESHD: (1) ageusia, anosmia HP anosmia MESHD, and fever HP fever MESHD; and (2) shortness of breath MESHD, cough HP, and chest pain HP chest pain MESHD. Moreover, being non-white (13.6% vs. 2.3%, p<0.001), Hispanic (27.9% vs. 2.5%, p<0.001), or living in an Urban area (5.4% vs. 3.8%, p<0.001) was associated with infection MESHD. Conclusions: When laboratory testing is not readily accessible, symptoms can help distinguish SARS-CoV-2 infection MESHD from other respiratory viruses. Symptoms should further be structured in clinical documentation to support identification of new cases and mitigation of disease MESHD disease spread TRANS by public health. These symptoms, derived from mildly infected individuals, can also inform vaccine and therapeutic clinical trials.

    What is the evidence for transmission TRANS of COVID-19 by children TRANS in schools? A living systematic review

    Authors: Wei Xu; Xue Li; Marshall Dozier; Yazhou He; Amir Kirolos; Zhongyu Lang; Catherine Mathews; Nandi Siegfried; Evropi Theodoratou; Sasha N. L. Bailey; Stephen Talyor; Jessica Jones; Meleri Jones; Wing Yiu Jason Lee; Joshua Rosenheim; Aneesh Chandran; George Joy; Cecilia Di Genova; Nigel J. Temperton; Jonathan Lambourne; Teresa Cutino-Moguel; Mervyn Andiapen; Marianna Fontana; Angelique Smit; Amanda Semper; Ben O'Brien; Benjamin Chain; Tim Brooks; Charlotte Manisty; Thomas Treibel; James Moon; - COVIDsortium Investigators; Mahdad C. Noursadeghi; - COVIDsortium Immune correlates network; Daniel M Altmann; Mala K. Mani; Aine McKnight; Rosemary J. Boyton; DANIEL PRIETO-ALHAMBRA

    doi:10.1101/2020.10.11.20210658 Date: 2020-10-14 Source: medRxiv

    ABSTRACT Background: It is of paramount importance to understand the transmission TRANS of SARS-CoV-2 in schools, which could support the decision-making about educational facilities closure or re-opening with effective prevention and control measures in place. Methods: We conducted a systematic review and meta-analysis to investigate the extent of SARS-CoV-2 transmission TRANS in schools. We performed risk of bias evaluation of all included studies using the Newcastle- Ottawa Scale (NOS). Results: 2,178 articles were retrieved and 11 studies were included. Five cohort studies reported a combined 22 student and 21 staff index cases that exposed 3,345 contacts with 18 transmissions TRANS [overall infection MESHD attack rate TRANS (IAR): 0.08% (95% CI: 0.00%-0.86%)]. IARs for students and school staff were 0.15% (95% CI: 0.00%-0.93%) and 0.70% (95% CI: 0.00%-3.56%) respectively. Six cross-sectional studies reported 639 SARS-CoV-2 positive cases in 6,682 study participants tested [overall SARS-CoV-2 positivity rate: 8.00% (95% CI: 2.17%-16.95%)]. SARS-CoV-2 positivity rate was estimated to be 8.74% (95% CI: 2.34%-18.53%) among students, compared to 13.68% (95% CI: 1.68%-33.89%) among school staff. Gender TRANS differences were not found for secondary infection MESHD (OR: 1.44, 95% CI: 0.50-4.14, P= 0.49) and SARS-CoV-2 positivity (OR: 0.90, 95% CI: 0.72-1.13, P= 0.36) in schools. Fever HP Fever MESHD, cough HP cough MESHD, dyspnea HP dyspnea MESHD, ageusia MESHD, anosmia HP anosmia MESHD, rhinitis HP rhinitis MESHD, sore throat, headache HP headache MESHD, myalgia HP myalgia MESHD, asthenia HP asthenia MESHD, and diarrhoea MESHD were all associated with the detection of SARS-CoV-2 antibodies SERO (based on two studies). Overall, study quality was judged to be poor with risk of performance SERO and attrition bias MESHD, limiting the confidence in the results. Conclusions: There is limited high-quality evidence available to quantify the extent of SARS-CoV-2 transmission TRANS in schools or to compare it to community transmission TRANS. Emerging evidence suggests lower IAR and SARS-CoV-2 positivity rate in students compared to school staff. Future prospective and adequately controlled cohort studies are necessary to confirm this finding.

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MeSH Disease
Human Phenotype

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