|D003141||Communicable Diseases NIH||0.07|
|D045169||Severe Acute Respiratory Syndrome NIH||0.04|
There is one clinical trial.
The Covid-19 viral pandemic has caused significant global losses and disruption to all aspects of society. One of the major difficulties in controlling the spread of this coronavirus has been the delayed and mild (or lack of) presentation of symptoms in infected individuals, and the insufficient Covid-19 testing capacity in the UK. This warrants the development of alternative diagnostic tools that reliably assess Covid-19 infection in the early stages of infection, while also being low- cost, low-burden, and easily administered to a wide proportion of the population. This study aims to validate machine learning models as a diagnostic tool that predicts infection with SARS-CoV-2 based on app-reported symptoms and phenotypic data, against the 'gold-standard' swab PCR-test. This study will take place within the Covid Symptom Study app, the free symptom tracking mobile application launched in March 2020.
Description: Likelihood of infection with Covid-19, based on app-reported symptomsMeasure: SARS-CoV-2 infection Time: 3 days
Description: Active infection with Covid-19 as assessed by PCR swab testMeasure: SARS-CoV-2 infection Time: 1 day
Data processed on January 01, 2021.
An HTML report was created for each of the unique drugs, MeSH, and HPO terms associated with COVID-19 clinical trials. Each report contains a list of either the drug, the MeSH terms, or the HPO terms. All of the terms in a category are displayed on the left-hand side of the report to enable easy navigation, and the reports contain a list of correlated drugs, MeSH, and HPO terms. Further, all reports contain the details of the clinical trials in which the term is referenced. Every clinical trial report shows the mapped HPO and MeSH terms, which are also hyperlinked. Related HPO terms, with their associated genes, protein mutations, and SNPs are also referenced in the report.Drug Reports MeSH Reports HPO Reports