COVID Symptom Study
|Operating system||Android, iOS|
The COVID Symptom Study, formerly the COVID Symptom Tracker, is a COVID-19 epidemiological research mobile app developed in the United Kingdom that runs on Android and iOS. It is a collaboration between King's College London, Guy's and St Thomas' Hospitals and Zoe Global Limited, with funding granted by the UK government. The purpose of the app is to track symptoms and other salient data in a large number of people to enable epidemiological results to be calculated.
The idea for an app to track the spread of COVID-19 came from professor Tim Spector, an epidemiologist at King's College London. In the early months of 2020 he used his startup company ZOE Global Limited to build the Covid Symptom Tracker app in collaboration with King's College London and Guy's and St Thomas' hospitals. Initially the project was UK-based, where there is open membership. In the United States at a later date various cohorts from existing studies were added, including from the Nurses' Health Study; this research was in collaboration with Massachusetts General Hospital. The project website states that "The app is and always will be free, and any data you provide will not be used for commercial purposes."
The app was released as a trial for 5,000 twins, using patients involved in other Zoe research projects. It was later expanded for use by non-twins. The app entered the UK App Store and Play Store on 24 March, and the US App and Play stores on 29 March.
In August 2020, the UK government made a grant of £2 million to support data collection by the project, and by August 2021, government funding amounted to £5m. In May 2021, the associated company name was changed from Zoe Global Limited to Zoe Limited.
Within 24 hours of being available in the UK, the app had been downloaded over 1 million times. A paper using data collected in the four weeks up to 21 April 2020 analysed symptoms from 2.45 million people in the UK and 168,000 in the US. As of May 2020, the app had been downloaded by over 3 million people, including 2 million Britons. By 17 July the number exceeded 4 million.
The number of active app users is not published. In late October 2020, Spector said that a million users were reporting symptoms most days. Researchers who analysed data collected in the last three months of 2020 said they used more than 65 million health reports from 1.76 million users. By July 2021, the app had been used by 4.6 million people in Britain and about a quarter of that number continued to self-report every day.
The COVID Symptom Study requires users to give their location. Users give personal information including age, gender and location, and report if they have any underlying chronic conditions. They also answer questions related to common COVID-19 symptoms, and input any illness or symptoms that they have, as well as stating whether they have been tested for COVID-19. Beginning in May 2020, a random sample of users is selected (on the first day they report symptoms) for a swab test. Researchers then use statistical analysis to determine which symptoms are likely to indicate COVID-19, rather than the common cold or seasonal influenza. The app does not have any contact tracing functionality.
Based on the data inputted into the app, researchers estimated that when cases peaked on 1 April 2020, 2.1 million people in the UK aged between 20 and 69 may have had COVID-19, and that as of 23 May 2020, 280,000 people in that age range currently had symptoms consistent with COVID-19. The study also estimates the risk level to health workers, compared with the general public. Research based on the app was described in papers in Science on 5 May 2020 and in Nature on 11 May 2020. Using data from the app, researchers were able to identify six distinct types of COVID-19 and forecast which initial symptoms were more likely to lead to severe illnesses.
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- Menni, Cristina; Valdes, Ana M.; Freidin, Maxim B.; Sudre, Carole H.; Nguyen, Long H.; Drew, David A.; Ganesh, Sajaysurya; Varsavsky, Thomas; Cardoso, M. Jorge; El-Sayed Moustafa, Julia S.; Visconti, Alessia; Hysi, Pirro; Bowyer, Ruth C. E.; Mangino, Massimo; Falchi, Mario; Wolf, Jonathan; Ourselin, Sebastien; Chan, Andrew T.; Steves, Claire J.; Spector, Tim D. (11 May 2020). "Real-time tracking of self-reported symptoms to predict potential COVID-19". Nature Medicine. 26 (7): 1037–1040. doi:10.1038/s41591-020-0916-2. ISSN 1546-170X. PMC 7751267. PMID 32393804. S2CID 218572997.
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- Drew, David A.; Nguyen, Long H.; Steves, Claire J.; Menni, Cristina; Freydin, Maxim; Varsavsky, Thomas; Sudre, Carole H.; Cardoso, M. Jorge; Ourselin, Sebastien; Wolf, Jonathan; Spector, Tim D.; Chan, Andrew T. (5 May 2020). "Rapid implementation of mobile technology for real-time epidemiology of COVID-19". Science. 368 (6497): 1362–1367. Bibcode:2020Sci...368.1362D. doi:10.1126/science.abc0473. PMC 7200009. PMID 32371477.
- Sudre, Carole H.; Lee, Karla; Ni Lochlainn, Mary; Varsavsky, Thomas; Murray, Benjamin; Graham, Mark S.; Menni, Cristina; Modat, Marc; Bowyer, Ruth C.E.; Nguyen, Long H.; Drew, David Alden (16 June 2020). "Symptom clusters in Covid19: A potential clinical prediction tool from the COVID Symptom study app". Science Advances. 7 (12). doi:10.1126/sciadv.abd4177. PMC 7978420. S2CID 219700229.
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