Edging towards a year since the first coronavirus pandemic took Britain hostage, a voluminous amount of data has now been collated on the devastati
Edging towards a year since the first coronavirus pandemic took Britain hostage, a voluminous amount of data has now been collated on the devastating disease. Thus, a more nuanced observation of symptoms can be achieved.
Millions of people have shared their experience with Covid on the COVID-19 Symptom Study.
The not-for-profit organisation was launched in March 2020, and has been collecting information ever since.
This collection of data has been vigorously analysed by research staff at King’s College London.
The Covid Symptom Study – launched by health science company ZOE – asked participants who reported their symptoms in the first wave of the pandemic to take an antibody test.
The results demonstrate that one in four (25 percent) who didn’t have any of the classic triad of symptoms had Covid antibodies.
This means that they had been infected by SARS-CoV-2 – the coronavirus that causes the Covid disease, and displayed other non-classic signs of infection.
Looking more closely at the data, only one in five (20 percent) who reported no symptoms of the disease at all had tested positive for Covid.
Coronavirus variants have been causing alarm, with a new strain identified in Brazil.
Another, the super contagious B117 variant in the UK, contributed to the enforced national lockdown.
Thus, the more information collected on symptoms of each variant, the better our understanding of the viruses grow.
If you’d like to take part in the research, you can download the Covid Symptom Study app on a smartphone.
The investigation is led by ZOE co-founder Tim Spector, a professor of genetic epidemiology at King’s College London.
Anonymised data will be shared with Guys & St Thomas’ Hospitals, data scientists at ZOE Global Ltd and perhaps the UK National Health Service (NHS).
The aim of the Covid Symptom Study is to better understand symptoms of the disease, identify high risk areas in the country, and identify who is at most risk of the disease due to linked health conditions.