Article

Key predictors of attending hospital with COVID19: An association study from the COVID Symptom Tracker App in 2,618,948 individuals

2020-04-29

Abstract excerpt

<h4>Objectives</h4> We aimed to identify key demographic risk factors for hospital attendance with COVID-19 infection. <h4>Design</h4> Community survey <h4>Setting</h4> The COVID Symptom Tracker mobile application co-developed by physicians and scientists at King’s College London, Massachusetts General Hospital, Boston and Zoe Global Limited was launched in the UK and US on 24 th and 29 th March 2020 respectively....

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 5c1bdbcf-2cc9-58f2-9d7c-dfe58044ebcb
DOI: 10.1101/2020.04.25.20079251

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Key predictors of attending hospital with COVID19: An association study from the COVID Symptom Tracker App in 2,618,948 individualsDOI 10.1101/2020.04.25.20079251Read

Age-dependent and Independent Symptoms and Comorbidities Predictive of COVID-19 HospitalizationSemantic proximity Read

Characteristics of post-acute COVID-19 presentations and healthcare use in Australian general practice and comparisons to those with acute COVID-19 and upper respiratory tract infectionSemantic proximity Read

Symptoms associated with a COVID-19 infection in the general population of ViennaSemantic proximity Read

COVID-19 susceptibility and severity risks in a survey of over 500,000 individualsSemantic proximity Read

Estimating excess 1- year mortality from COVID-19 according to underlying conditions and age in England: a rapid analysis using NHS health records in 3.8 million adultsSemantic proximity Read

Symptoms and risk factors for hospitalization of COVID-19 presented in primary careSemantic proximity Read

Prevalence, Risk Factors and Characterisation of Individuals with Long COVID Using Electronic Health Records in Over 1.5 Million COVID Cases in EnglandSemantic proximity Read

Geo-social gradients in predicted COVID-19 prevalence and severity in Great Britain: results from 2,266,235 users of the COVID-19<i>Symptoms Tracker app</i>Semantic proximity Read

Passive Monitoring of Physiological Data and Self-reported Symptoms to Detect Clusters of People with COVID-19Semantic proximity Read

Cancer and risk of COVID-19 through a general community surveySemantic proximity Read

Predicting COVID-19 related death using the OpenSAFELY platformSemantic proximity Read

Seek COVER: Development and validation of a personalized risk calculator for COVID-19 outcomes in an international networkSemantic proximity Read