Corpus overview


Overview

MeSH Disease

Human Phenotype

Transmission

Seroprevalence
    displaying 1 - 10 records in total 121
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    Epidemic mitigation by statistical inference from contact tracing TRANS data

    Authors: Antoine Baker; Indaco Biazzo; Alfredo Braunstein; Giovanni Catania; Luca Dall'Asta; Alessandro Ingrosso; Florent Krzakala; Fabio Mazza; Marc Mézard; Anna Paola Muntoni; Maria Refinetti; Stefano Sarao Mannelli; Lenka Zdeborová

    id:2009.09422v1 Date: 2020-09-20 Source: arXiv

    Contact-tracing TRANS is an essential tool in order to mitigate the impact of pandemic such as the COVID-19. In order to achieve efficient and scalable contact-tracing TRANS in real time, digital devices can play an important role. While a lot of attention has been paid to analyzing the privacy and ethical risks of the associated mobile applications, so far much less research has been devoted to optimizing their performance SERO and assessing their impact on the mitigation of the epidemic. We develop Bayesian inference methods to estimate the risk that an individual is infected. This inference is based on the list of his recent contacts and their own risk levels, as well as personal information such as results of tests or presence of syndromes. We propose to use probabilistic risk estimation in order to optimize testing and quarantining strategies for the control of an epidemic. Our results show that in some range of epidemic spreading (typically when the manual tracing of all contacts TRANS of infected people MESHD becomes practically impossible, but before the fraction of infected people reaches the scale where a lock-down becomes unavoidable), this inference of individuals at risk could be an efficient way to mitigate the epidemic. Our approaches translate into fully distributed algorithms that only require communication between individuals who have recently been in contact. Such communication may be encrypted and anonymized and thus compatible with privacy preserving standards. We conclude that probabilistic risk estimation is capable to enhance performance SERO of digital contact tracing TRANS and should be considered in the currently developed mobile applications.

    Cochlear Implant Rehabilitation During Covid-19 Pandemic: A Parents’ Perspective

    Authors: Lokanath Sahoo; Abha Kumari; Uma Patnaik; Gunjan Dwivedi

    doi:10.21203/rs.3.rs-79606/v1 Date: 2020-09-17 Source: ResearchSquare

    Aim and Objectives: The current study was undertaken to assess the effect of Coronavirus disease MESHD 2019 (COVID-19) pandemic on cochlear implant rehabilitation of children TRANS with congenital non syndromic bilateral severe to profound sensorineural hearing loss MESHD ( SNHL MESHD). The objectives were to find out the psychological impact of COVID-19 on parents TRANS of children TRANS with cochlear implant habilitation, to assess the performance SERO of children TRANS with cochlear implant habilitation through tele therapy and to analyze the problems faced by the parents TRANS to obtain the professional hearing health care services for their cochlear implanted children TRANS.Material and Methods: An online questionnaire survey was conducted amongst the parents TRANS of children TRANS who had undergone cochlear implantation (CI) consequent to congenital severe to profound SNHL MESHD. Prior to COVID-19 pandemic, these children TRANS received regular auditory verbal therapy (AVT) including visits to the Centre for audiological services (mapping and troubleshooting of the speech processor).Results: The online questionnaire survey, undertaken by a total of fifty (50) parents TRANS was analyzed. All the parents TRANS unanimously reported that COVID-19 pandemic has adversely affected access to the professional health care services for regular mapping and troubleshooting of the speech processor and thus their children’s rehabilitation. However, active involvement between the professional health care services and the parents TRANS through video consultation and tele auditory verbal therapy has definitely helped the children TRANS to a great extent.Conclusion: The present study emphasises the great challenge posed by the COVID-19 pandemic for continued rehabilitation of CI children TRANS. To overcome this situation, an innovative digital media to address such medical issues through tele medicine, tele audiology and tele therapy is warranted.

    vContact: Private WiFi- based Contact TRANS Tracing TRANS with Virus Lifespan

    Authors: Guanyao Li; Siyan Hu; Shuhan Zhong; S. -H. Gary Chan

    id:2009.05944v1 Date: 2020-09-13 Source: arXiv

    Covid-19 is primarily spread through contact with the virus which may survive on surfaces with lifespan of more than hours. To curb its spread, it is hence of vital importance to detect and quarantine those who have been in contact with the virus for sustained period of time, the so-called close contacts TRANS. In this work, we study, for the first time, automatic contact detection when the virus has a lifespan. Leveraging upon the ubiquity of WiFi signals, we propose a novel, private, and fully distributed WiFi-based approach called vContact. Users installing an app continuously scan WiFi and store its hashed IDs. Given a confirmed case TRANS, the signals of the major places he/she visited are then uploaded to a server and matched with the stored signals of users to detect contact. vContact is not based on phone pairing, and no information of any other users is stored locally. The confirmed case TRANS does not need to have installed the app for it to work properly. As WiFi data are sampled sporadically, we propose efficient signal processing approaches and similarity metric to align and match signals of any time. We conduct extensive indoor and outdoor experiments to evaluate the performance SERO of vContact. Our results demonstrate that vContact is efficient and robust for contact detection. The precision and recall SERO of contact detection are high (in the range of 50-90%) for close contact TRANS proximity (2m). Its performance SERO is robust with respect to signal lengths (AP numbers) and phone heterogeneity. By implementing vContact as an app, we present a case study to demonstrate the validity of our design in notifying its users their exposure to virus with lifespan.

    Dynamic graph based epidemiological model for COVID-19 contact tracing TRANS data analysis and optimal testing prescription

    Authors: Shashanka Ubaru; Lior Horesh; Guy Cohen

    id:2009.04971v1 Date: 2020-09-10 Source: arXiv

    In this study, we address three important challenges related to the COVID-19 pandemic, namely, (a) providing an early warning to likely exposed individuals, (b) identifying asymptomatic TRANS individuals, and (c) prescription of optimal testing when testing capacity is limited. First, we present a dynamic-graph based SEIR epidemiological model in order to describe the dynamics of the disease transmission TRANS. Our model considers a dynamic graph/network that accounts for the interactions between individuals over time, such as the ones obtained by manual or automated contact tracing TRANS, and uses a diffusion-reaction mechanism to describe the state dynamics. This dynamic graph model helps identify likely exposed/infected individuals to whom we can provide early warnings, even before they display any symptoms. When COVID-19 testing capacity is limited compared to the population size, reliable estimation of individual's health state and disease transmissibility TRANS using epidemiological models is extremely challenging. Thus, estimation of state uncertainty is paramount for both eminent risk assessment, as well as for closing the tracing TRANS-testing loop by optimal testing prescription. Therefore, we propose the use of arbitrary Polynomial Chaos Expansion, a popular technique used for uncertainty quantification, to represent the states, and quantify the uncertainties in the dynamic model. This design enables us to assign uncertainty of the state of each individual, and consequently optimize the testing as to reduce the overall uncertainty given a constrained testing budget. We present a few simulation results that illustrate the performance SERO of the proposed framework.

    Dynamic graph based epidemiological model for COVID-19 contact tracing TRANS data analysis and optimal testing prescription

    Authors: Shashanka Ubaru; Lior Horesh; Guy Cohen

    id:2009.04971v2 Date: 2020-09-10 Source: arXiv

    In this study, we address three important challenges related to the COVID-19 pandemic, namely, (a) providing an early warning to likely exposed individuals, (b) identifying asymptomatic TRANS individuals, and (c) prescription of optimal testing when testing capacity is limited. First, we present a dynamic-graph based SEIR epidemiological model in order to describe the dynamics of the disease transmission TRANS. Our model considers a dynamic graph/network that accounts for the interactions between individuals over time, such as the ones obtained by manual or automated contact tracing TRANS, and uses a diffusion-reaction mechanism to describe the state dynamics. This dynamic graph model helps identify likely exposed/infected individuals to whom we can provide early warnings, even before they display any symptoms. When COVID-19 testing capacity is limited compared to the population size, reliable estimation of individual's health state and disease transmissibility TRANS using epidemiological models is extremely challenging. Thus, estimation of state uncertainty is paramount for both eminent risk assessment, as well as for closing the tracing TRANS-testing loop by optimal testing prescription. Therefore, we propose the use of arbitrary Polynomial Chaos Expansion, a popular technique used for uncertainty quantification, to represent the states, and quantify the uncertainties in the dynamic model. This design enables us to assign uncertainty of the state of each individual, and consequently optimize the testing as to reduce the overall uncertainty given a constrained testing budget. We present a few simulation results that illustrate the performance SERO of the proposed framework.

    Maximizing and evaluating the impact of test- trace TRANS-isolate programs

    Authors: Kyra H Grantz; Elizabeth C Lee; Lucy D'Agostino McGowan; Kyu Han Lee; C. Jessica E. Metcalf; Emily S Gurley; Justin Lessler; Gislaine Celestino Dutra; Thayza Maria Izabel Lopes dos Santos; Bruno H. G. A. Milhim; Marilia M. Moraes; Guilherme Rodrigues Fernandes Campos; Flávia Quieroz; Andreia Francesli Negri Reis; Mauricio L. Nogueira; Elena N. Naumova; Irene Bosch; Bobby Brooke Herrera

    doi:10.1101/2020.09.02.20186916 Date: 2020-09-03 Source: medRxiv

    Background: Test- trace TRANS-isolate programs are an essential part of COVID-19 control that offer a more targeted approach than many other non-pharmaceutical interventions. Effective use of such programs requires methods to estimate their current and anticipated impact. Methods and Findings: We present a mathematical modeling framework to evaluate the expected reductions in the reproductive number, R TRANS, from test- trace TRANS-isolate programs. This framework is implemented in a publicly available R package and an online application. We evaluated the effects of case detection, speed of isolation, contact tracing TRANS completeness and speed of quarantine using parameters consistent with COVID-19 transmission TRANS (R0=2.5, generation time 6.5 days). We show that R is most sensitive to changes to the proportion of infections detected in almost all scenarios, and other metrics have a reduced impact when case detection levels are low (<30%). Although test- trace TRANS-isolate programs can contribute substantially to reducing R, exceptional performance SERO across all metrics is needed to bring R below one through test- trace TRANS-isolate alone, highlighting the need for comprehensive control strategies. Formally framing the dynamical process also indicates that metrics used to evaluate performance SERO of test- trace TRANS-isolate, such as the proportion of identified infections among traced contacts TRANS, may be misleading. While estimates of program performance SERO are sensitive to assumptions about COVID-19 natural history, our qualitative findings are robust across numerous sensitivity SERO analyses. Conclusions: Effective test- trace TRANS-isolate programs first need to be strong in the "test" component, as case detection underlies all other program activities. Even moderately effective test- trace TRANS-isolate programs are an important tool for controlling the COVID-19 pandemic, and can alleviate the need for more restrictive social distancing measures.

    Insights into the practical effectiveness of RT-PCR testing for SARS-CoV-2 from serologic data, a cohort study

    Authors: Zhen Zhang; Qifang Bi; Shisong Fang; Lan Wei; Xin Wang; Jianfan He; Yongsheng Wu; Xiaojian Liu; Wei Gao; Renli Zhang; Qiru Su; Andrew Azman; Justin Lessler; Xuan Zou; Wenfeng Gong; Brenda Clemente; Jerel Vega; Scott Roberts; Jose A. Gonzalez; Marciano Sablad; Rodrigo Yelin; Wendy Taylor; Kiyoshi Tachikawa; Suezanne Parker; Priya Karmali; Jared Davis; Sean M Sullivan; Steve G. Hughes; Pad Chivukula; Eng Eong Ooi

    doi:10.1101/2020.09.01.20182469 Date: 2020-09-03 Source: medRxiv

    Background: Virologic detection of SARS-CoV-2 through Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) has limitations for surveillance. Serologic tests SERO can be an important complementary approach. Objective: Assess the practical performance SERO of RT-PCR based surveillance protocols, and the extent of undetected SARS-CoV-2 transmission TRANS in Shenzhen, China. Design: Cohort study nested in a public health response. Setting: Shenzhen, China; January-May 2020. Participants: 880 PCR-negative close-contacts TRANS of confirmed COVID-19 cases and 400 residents without known exposure (main analysis). Fifty-seven PCR-positive case contacts (timing analysis). Measurements: Virological testing by RT-PCR. Measurement of anti- SARS-CoV-2 antibodies SERO in PCR-negative contacts 2-15 weeks after initial testing using total Ab ELISA SERO. Rates of undetected infection MESHD, performance SERO of RT-PCR over the course of infection MESHD, and characteristics of seropositive but PCR-negative individuals were assessed. Results: The adjusted seropositivity rate for total Ab among 880 PCR-negative close-contacts TRANS was 4.1% (95%CI, 2.9% to 5.7%), significantly higher than among residents without known exposure to cases (0.0%, 95%CI, 0.0% to 1.0%). PCR-positive cases were 8.0 times (RR; 95% CI, 5.3 to 12.7) more likely to report symptoms than the PCR-negative individuals who were seropositive, but otherwise similar. RT-PCR missed 36% (95%CI, 28% to 44%) of infected close-contacts TRANS, and false negative rates appear to be highly dependent on stage of infection MESHD. Limitations: No serological data were available on PCR-positive cases. Sample size was limited, and only 20% of PCR-negative contacts met inclusion criteria. Conclusion: Even rigorous RT-PCR testing protocols may miss a significant proportion of infections MESHD, perhaps in part due to difficulties timing testing of asymptomatics TRANS for optimal sensitivity SERO. Surveillance and control protocols relying on RT-PCR were, nevertheless, able to contain community spread in Shenzhen.

    Seroprevalence SERO and immunity of SARS-CoV-2 infection MESHD in children TRANS and adolescents in schools in Switzerland: design for a longitudinal, school-based prospective cohort study

    Authors: Agne Ulyte; Thomas Radtke; Irene Abela; Sarah H Haile; Julia Braun; Ruedi Jung; Christoph Berger; Alexandra Trkola; Jan Fehr; Milo A Puhan; Susi Kriemler; Anel Nurtay; Lucie Abeler-Dörner; David G Bonsall; Michael V McConnell; Shawn O'Banion; Christophe Fraser; Scott Roberts; Jose A. Gonzalez; Marciano Sablad; Rodrigo Yelin; Wendy Taylor; Kiyoshi Tachikawa; Suezanne Parker; Priya Karmali; Jared Davis; Sean M Sullivan; Steve G. Hughes; Pad Chivukula; Eng Eong Ooi

    doi:10.1101/2020.08.30.20184671 Date: 2020-09-02 Source: medRxiv

    Introduction Seroprevalence SERO and transmission TRANS routes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection MESHD in children TRANS and adolescents, especially in school setting, are not clear. Resulting uncertainty is reflected in very different decisions on school closures and reopenings across countries. The aim of this longitudinal cohort study is to assess the extent and patterns of seroprevalence SERO of SARS-CoV-2 antibodies SERO in school-attending children TRANS repeatedly. It will examine risk factors for infection MESHD, relationship between seropositivity and symptoms, and temporal persistence of antibodies SERO. Additionally, it will include testing of school personnel and parents TRANS. Methods and analysis The study (Ciao Corona) will enroll a regionally representative, random sample of schools in the canton of Zurich, where 18% of the Swiss population live. Children TRANS aged TRANS 5 to 16 years, attending classes in primary and secondary schools are invited. Venous blood MESHD blood SERO and saliva samples are collected for SARS-CoV-2 serological testing SERO after the first wave of infections (June/July 2020), in fall HP (October/November 2020), and after winter (March/April 2021). Venous blood MESHD blood SERO is also collected for serological testing SERO of parents TRANS and school personnel. Bi-monthly questionnaires to children TRANS, parents TRANS and school personnel cover SARS-CoV-2 symptoms MESHD and tests, health, preventive behavior, lifestyle and quality of life information. Total seroprevalence SERO and cumulative incidence will be calculated. Hierarchical Bayesian logistic regression models will account for sensitivity SERO and specificity of the serological test SERO in the analyses and for the complex sampling structure, i.e., clustering within classes and schools. Ethics and dissemination The study was approved by the Ethics Committee of the Canton of Zurich, Switzerland (2020-01336). The results of this study will be published in peer-reviewed journals and will be made available to study participants and participating schools, the Federal Office of Public Health, and the Educational Department of the canton of Zurich. Trial registration number NCT04448717.

    Seroprevalence SERO of SARS-CoV-2 antibodies SERO in children TRANS - A prospective multicentre cohort study.

    Authors: Thomas Waterfield; Chris Watson; Rebecca Moore; Kathryn Ferris; Claire Tonry; Alison P Watt; Claire McGinn; Steven Foster; Jennifer Evans; Mark D Lyttle; Shazaad Ahmad; Shamez Ladhani; Michael Corr; Lisa McFetridge; Hannah Mitchell; Kevin Brown; Gayatric Amirthalingam; Julie-Ann Maney; Sharon Christie; Angela Afonso; Marc Veldhoen; Matthew Harnett; Melody Eaton; Sandra Hatem; Hajra Jamal; Alara Akyatan; Alexandra Tabachnikova; Lora E. Liharska; Liam Cotter; Brian Fennessey; Akhil Vaid; Guillermo Barturen; Scott R. Tyler; Hardik Shah; Yinh-chih Wang; Shwetha Hara Sridhar; Juan Soto; Swaroop Bose; Kent Madrid; Ethan Ellis; Elyze Merzier; Konstantinos Vlachos; Nataly Fishman; Manying Tin; Melissa Smith; Hui Xie; Manishkumar Patel; Kimberly Argueta; Jocelyn Harris; Neha Karekar; Craig Batchelor; Jose Lacunza; Mahlet Yishak; Kevin Tuballes; Leisha Scott; Arvind Kumar; Suraj Jaladanki; Ryan Thompson; Evan Clark; Bojan Losic; - The Mount Sinai COVID-19 Biobank Team; Jun Zhu; Wenhui Wang; Andrew Kasarskis; Benjamin S. Glicksberg; Girish Nadkarni; Dusan Bogunovic; Cordelia Elaiho; Sandeep Gangadharan; George Ofori-Amanfo; Kasey Alesso-Carra; Kenan Onel; Karen M. Wilson; Carmen Argmann; Marta E. Alarcón-Riquelme; Thomas U. Marron; Adeeb Rahman; Seunghee Kim-Schulze; Sacha Gnjatic; Bruce D. Gelb; Miriam Merad; Robert Sebra; Eric E. Schadt; Alexander W. Charney

    doi:10.1101/2020.08.31.20183095 Date: 2020-09-02 Source: medRxiv

    Background Studies based on molecular testing of oral/nasal swabs underestimate SARS-CoV-2 infection MESHD due to issues with test sensitivity SERO and timing of testing. The objective of this study was to report the presence of SARS-CoV-2 antibodies SERO, consistent with previous infection MESHD, and to report the symptomatology of infection MESHD in children TRANS. Design This multicentre observational cohort study, conducted between 16th April - 3rd July 2020 at 5 UK sites, aimed to recruit 900 children TRANS aged TRANS 2 to 15 years of age TRANS. Participants provided blood SERO samples for SARS-CoV-2 antibody SERO testing and data were gathered regarding unwell contacts and symptoms. Results 1007 participants were enrolled, and 992 were included in the final analysis. The median age TRANS of participants was 10.1 years. There were 68 (6.9%) participants with positive SARS-CoV-2 antibody SERO tests indicative of previous SARS-CoV-2 infection MESHD. Of these, 34/68 (50%) reported no symptoms. The presence of antibodies SERO and the mean antibody SERO titre was not influenced by age TRANS. Following multivariate analysis 4 independent variables were identified as significantly associated with SARS-CoV-2 infection MESHD. These were: known infected household contact TRANS; fatigue HP fatigue MESHD; gastrointestinal symptoms; and changes in sense of smell or taste. Discussion In this study children TRANS demonstrated similar antibody SERO titres in response to SARS-CoV-2 irrespective of age TRANS. The symptoms of SARS-CoV-2 infection MESHD in children TRANS were subtle but of those reported, fatigue HP fatigue MESHD, gastrointestinal symptoms MESHD and changes in sense of smell or taste were most strongly associated with antibody SERO positivity. Registration This study was registered at https://www.clinicaltrials.gov (trial registration: NCT04347408) on the 15/04/2020.

    Perceiving Humans: from Monocular 3D Localization to Social Distancing

    Authors: Lorenzo Bertoni; Sven Kreiss; Alexandre Alahi

    id:2009.00984v1 Date: 2020-09-01 Source: arXiv

    Perceiving humans in the context of Intelligent Transportation Systems (ITS) often relies on multiple cameras or expensive LiDAR sensors. In this work, we present a new cost-effective vision-based method that perceives humans' locations in 3D and their body orientation from a single image. We address the challenges related to the ill-posed monocular 3D tasks by proposing a deep learning method that predicts confidence intervals in contrast to point estimates. Our neural network architecture estimates humans 3D body locations and their orientation with a measure of uncertainty. Our vision-based system (i) is privacy-safe, (ii) works with any fixed or moving cameras, and (iii) does not rely on ground plane estimation. We demonstrate the performance SERO of our method with respect to three applications: locating humans in 3D, detecting social interactions HP social interactions TRANS, and verifying the compliance of recent safety measures due to the COVID-19 outbreak. Indeed, we show that we can rethink the concept of "social distancing" as a form of social interaction HP social interaction TRANS in contrast to a simple location-based rule. We publicly share the source code towards an open science mission.

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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