Researchers have used data from millions of people to devise a chart that shows a person’s risk of being hospitalised with COVID.
The data is taken from the Zoe COVID Symptom Study app, where users give their location and other personal details alongside whether they have been tested for COVID and any symptoms they may be experiencing.
Researchers then use the data to determine which symptoms are likely to indicate COVID, and to give an estimate of who has the disease.
Now researchers at King’s College London have used the data of symptoms – including a loss of smell and sudden confusion – to create a chart that will show who is most likely to become severely ill with COVID.
Users detailed their symptoms to the app and reported if they needed oxygen treatment in hospital.
Dr Claire Stevens, who led the research, found that counting up the number of symptoms experienced across the first five days of becoming ill, along with sex and age, could be used to predict whether someone is likely to end up needing oxygen support.
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Using colour codes, the chart shows an increased level of risk for people in the various categories.
The research shows that a 50-year-old man with two symptoms in their first week of illness has a less than 25% chance of needing hospital treatment, compared to a more than 75% chance for a 60-year-old woman with 10 different symptoms in their first week.
The Zoe app also lists 15 main symptoms of the disease:
Loss of smell
High temperature (fever)
Severe tiredness (fatigue)
Severe shortness of breath
New confusion (delirium)
Researchers say anyone who finds themselves in the red or dark red zone of the chart should contact their doctor for more advice.
The Zoe data comes as data released by the Office for National Statistics (ONS) found that In England, the percentage of people testing positive for coronavirus remained high but decreased slightly in the week ending 16 January, 2021.
The ONS estimates that 1,023,700 people in England had COVID during the period, equating to around 1 in 55 people.
The data also found that in the period between 12 and 17 January, the highest COVID rates were in London and the North East of England, while the lowest rates were seen in Yorkshire and the Humber.
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