Early Covid-19 symptoms vary from men to women, age groups

Wednesday 04th August 2021 08:27 EDT
 
 

Symptoms for early Covid-19 infection differ across age groups and gender. The differences are most notable between younger age groups 16 to 59 years, as compared to older age groups 60 to 80 years. The symptoms also differed from men to women. The paper, published in the Lancet Digital Health, led by researchers from King's College London analysed data from the ZOE COVID Symptom Study app between April 20 to October 15, 2020.

The scientists modelled the early signs of Covid-19 infection and successfully detected 80 per cent of cases when using three days of self-reported symptoms. Researchers compared the ability to predict early signs of Covid-19 infection using current National Health Service UK diagnostic criteria and a Hierarchical Gaussian Process model, a type of machine learning.

The machine learning model was able to incorporate some characteristics about the person affected, such as age, sex, and health conditions, and showed that symptoms of early Covid-19 infection are different among various groups.

Lead author, Claire Steves, Reader at King's College London said, “Its important people know the earliest symptoms are wide-ranging and may look different for each member of a family or household. Testing guidance could be updated to enable cases to be picked up earlier, especially in the face of new variants which are highly transmissible. This could include using widely available lateral flow tests for people with any of these non-core symptoms.”

The most important symptoms for the earliest detection of Covid-19 overall included loss of smell, chest pain, persistent cough, abdominal pain, blisters on the feet, eye soreness, and unusual muscle pain.

Dr Liane dos Santos Canas, first author from King's College London, said, “Currently, in the UK, only a few symptoms are used to recommend self-isolation and further testing. Using a larger number of symptoms and only after a few days of being unwell, using AI, we can better detect COVID-19 positive cases. We hope such a method is used to encourage more people to get tested as early as possible to minimise the risk of spread.”


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