Researchers have revealed the three different 'types' of long Covid that the public needs to keep an eye out for.
Experts at King's College London believe there are three 'subtypes' of Covid infection which all come with their own different sets of symptoms. As part of the Zoe health study, researchers looked at 1,459 people living with long Covid where they have been suffering symptoms for at least 84 days following infection.
The NHS notes that it may take longer for some people to recover from Covid-19. While many people will feel better in a few days or weeks, with a full recovery expected within 12 weeks, it can take longer for some people to shake off symptoms, even those who first experienced a mild infection.
Read more: Greater Manchester's latest Covid rates as cases remain high despite fall
The pre-print of the study, published on medRxiv, claims that people with long Covid can effectively be split into three main groups. It includes the following:
- Those with neurological symptoms, including fatigue, brain fog and headache which are most commonly found in those infected with the alpha and delta strains.
- Those with respiratory symptoms such as chest pain and shortness of breath. People in this group were also found to more commonly be infected during the first wave of the virus.
- Those experiencing a diverse range of symptoms such as heart palpitations, muscle ache and pain, as well as changes in skin and hair.
However, researchers pointed out that these three subtypes were found in infections from all variants of the virus. Clinical lead author Dr Claire Steves, from King’s College London, said: “These data show clearly that post-Covid syndrome is not just one condition, but appears to have at several subtypes.
“Understanding the root causes of these subtypes may help in finding treatment strategies. Moreover, these data emphasise the need for long Covid services to incorporate a personalised approach sensitive to the issues of each individual.”
First author Dr Liane Canas, from King’s College London, added: “These insights could aid in the development of personalised diagnosis and treatment for these individuals.”
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