AI Model Predicts 8 Out Of 10 Covid-19 Infections Without Tests

Monday, May 25, 2020

The study has been described in the paper "Real-time tracking of self-reported symptoms to predict potential COVID-19" published in Nature Medicine and an article by Tim Spector, Head of Department of Twin Research & Genetic Epidemiology at the King's College London.


  • AI model bases on data from the COVID Symptom Study app downloaded by 3.3 million people
  • The COVID Symptom Study smartphone-based app (previously COVID Symptom Tracker) was launched in the United Kingdom on 24 March 2020 and in the United States on 29 March 2020.
  • Researchers investigated whether loss of smell and taste is specific to COVID-19
  • They analyzed data donated by 2,618,862 individuals
  • Four key symptoms have been identified: loss of smell or taste, severe or persistent cough, fatigue and skipping meals
  • Among the 18,401 who had undergone a SARS-CoV-2 test, the proportion of participants who reported a loss of smell and taste was higher in those with a positive test result (65.03%) than in those with a negative test result (21.71%).
  • Researchers say this may provide help for populations where access to testing is limited.
  • Two clinical trials in the UK and the US are due to start shortly.
  • A significant limitation of the study is the self-report nature of the data included

Data source

More than 3.3 million people globally have downloaded the COVID Symptom Study app. They are using it to report daily on their health status, whether they feel well or have any new symptoms such as persistent cough, fever, fatigue, and loss of taste or smell (anosmia, also known as smell blindness).

In this study, the researchers analysed data gathered from just under 2.5 million people in the UK and US who had been regularly logging their health status in the app, around a third of whom had registered symptoms associated with COVID-19. Of these, 18,374 reported having had a test for coronavirus, with 7,178 people testing positive.

Anosmia more reliable predictor

The research team investigated which symptoms known to be associated with COVID-19 were most likely to be associated with a positive test. They found a wide range of symptoms compared to cold and flu, and warn against focusing only on fever and cough. Indeed, they found loss of taste and smell (anosmia) was particularly striking, with two-thirds of users testing positive for coronavirus infection reporting this symptom compared with just over a fifth of the participants who tested negative. The findings suggest that anosmia is a more reliable predictor of COVID-19 than fever, supporting anecdotal reports of loss of smell and taste as a common symptom of the disease.

The researchers then created a mathematical model that predicted with nearly 80% accuracy whether an individual is likely to have COVID-19 based on their age, sex, and a combination of four key symptoms: loss of smell or taste, severe or persistent cough, fatigue and skipping meals. Applying this model to the entire group of over 800,000 app users experiencing symptoms predicted that just under a fifth of those who were unwell (17.42%) were likely to have COVID-19 at that time.

Researchers suggest that combining this AI prediction with the widespread adoption of the app could help to identify those who are likely to be infectious as soon as the earliest symptoms start to appear, focusing tracking and testing efforts where they are most needed.

"Our results suggest that loss of taste or smell is a key early warning sign of COVID-19 infection and should be included in routine screening for the disease. We strongly urge governments and health authorities everywhere to make this information more widely known, and advise anyone experiencing a sudden loss of smell or taste to assume that they are infected and follow local self-isolation guidelines," says Professor Tim Spector from King's College London.