Self reported

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Quantitative analysis of self-reported symptoms in COVID-19 positive patients on Twitter along with other clinical studies. First study to have utilized Twitter to curate symptoms posted by COVID-19-positive users
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 		32620975
(J Am Med Inform Assoc)
PMID
32620975
Date of Publishing: 2020 Aug 1
Title Self-reported COVID-19 symptoms on Twitter: an analysis and a research resource.
Author(s) nameSarker A, Lakamana S et al.
Journal J Am Med Inform Assoc
Impact factor
4.46
Citation count: 31

Quantitative analysis of self-reported symptoms in COVID-19 positive patients on Twitter along with other clinical studies. First study to have utilized Twitter to curate symptoms posted by COVID-19-positive users
✍
 		32620975
(J Am Med Inform Assoc)
PMID
32620975
Date of Publishing: 2020 Aug 1
Title Self-reported COVID-19 symptoms on Twitter: an analysis and a research resource.
Author(s) nameSarker A, Lakamana S et al.
Journal J Am Med Inform Assoc
Impact factor
4.46
Citation count: 31

Frequency distribution of various symptoms in 2,450,569 participants from the United Kingdom were evaluated and interpreted. The COVID Symptom Study smartphone-based app (previously known as COVID Symptom Tracker) was developed by Zoe Global, in collaboration with Kings College London and Massachusetts General Hospital, and was launched in the United Kingdom
✍
 		32393804
(Nat Med)
PMID
32393804
Date of Publishing: 2020 Jul
Title Real-time tracking of self-reported symptoms to predict potential COVID-19.
Author(s) nameMenni C, Valdes AM et al.
Journal Nat Med
Impact factor
22.66
Citation count: 506

Frequency distribution of various symptoms in 168,293 participants from the United States of America were evaluated and interpreted. The app collects data from both asymptomatic and symptomatic individuals and tracks in real time how the disease progresses by recording self-reported health information on a daily basis, including symptoms, hospitalization, reverse-transcription PCR (RT-PCR) test outcomes, demographic information and pre-existing medical conditions.
✍
 		32393804
(Nat Med)
PMID
32393804
Date of Publishing: 2020 Jul
Title Real-time tracking of self-reported symptoms to predict potential COVID-19.
Author(s) nameMenni C, Valdes AM et al.
Journal Nat Med
Impact factor
22.66
Citation count: 506

The Covid Symptoms tracking app aim to track the daily self-reported symptoms of users in UK. The app helps track the range of symptoms, identify hotspots and characteristics of people under risk. Additionally, the app has been distributed to twins to identify the reason behind the varying severity of the disease Another app, US Health Weather Map, developed by Kinsa Insights in collaboration with Oregon State University, is being used to track atypical illness levels in the US. Although not designed specifically for covid-19, it is hoped that this may help to monitor regional distribution and trends in the transmission of coronavirus.
✍
 		32220898
(BMJ)
PMID
32220898
Date of Publishing: 2020 Mar 27
Title Covid-19: Researchers launch app to track spread of symptoms in the UK
Author(s) name Mayor S.
Journal BMJ
Impact factor
30.22
Citation count: 20