When the World Health Organization declared Covid-19 a global pandemic in March 2020, very little was known about the raging infection. Testing capability was limited and data sparse. Yet one citizen science project managed to gather and process real-time information and insights faster than most, propelling the power of people-led science combined with technology to the fore.
As the UK entered its first-ever national lockdown, Tim Spector, a professor of genetic epidemiology at King’s College London, while cycling home through London, had what turned out to be a game-changing idea. To garner on-the-ground information, he decided to survey the more than 14,000 participants of Twins UK, a study he set up in the 1990s, about their experiences of coronavirus.
Seeing the potential of simple surveys to gather data at pace, Spector enlisted the team and technology behind ZOE, a precision nutrition app, of which he is the scientific founder, to launch the survey nationwide. Within days the Covid Symptom Study app was born. Twenty-four hours later it had more than a million users, and by July four million, making it the largest citizen science project ever.
The project, which a year later still has over a million loyal contributors, is now supporting the government to understand the efficacy of its vaccine strategy. Most notably, however, it has become a model of how citizen science, with the right technology, can transform public health and medical research approaches, reducing both costs and timeframes.
The Covid Symptom Study app asks people to log daily whether they feel ‘normal’ or have one of 19 symptoms. Test results are also recorded and by the end of April the app had collected around 60,000, including 10,000 positive results. Using machine learning and artificial intelligence, researchers at King’s College London looked at symptoms that clustered with the positive test results, against those clustered with negative results and trained an algorithm, with an 80 per cent predictive ability, to determine whether a person has Covid-19 depending on their symptoms. Researchers extrapolate this data across the population to create an estimated daily nationwide and local figure for people with symptomatic Covid-19.
This data was particularly useful when there was limited community testing during the first lockdown, which, according to Spector, enabled them to determine where outbreaks were occurring up to 10 days before the government did (which incidentally rattled the government and saw them nearly shut the study down).
Through their work, the researchers were also among the first to identify lack of smell and taste as a key predictor of the disease, publishing a paper in Nature.
“I’ve been doing studies for 30 years and never got a result in less than six months,” says Spector. “Yet, with the app, we included a question on loss of smell and taste, and we had the answer in a week. It’s an incredibly fast and agile tool.”
Overall, data from the app has informed over 315 scientific papers, assisted the government’s testing programme by sending out thousands of tests to app users, as well as home stool and blood collection kits for research into long Covid.
With public funding, the researchers are now monitoring vaccine efficacy and side effects, something the government is keen to understand, Spector says, given its “bold” approach allowing a 12-week window between both shots. The first paper, published in The Lancet, found up to 74 per cent protection with a single shot and low side-effects.
“We are directly impacting policy; if our daily reports had shown 30 per cent efficacy and lots of post-vaccine infections, the government probably would have changed its 12-week policy,” says Spector.
The study, he adds, will show faster than anything else the emergence of vaccine-resistant variants and identify groups that need a booster.
‘I’ve been doing studies for 30 years and never got a result in less than six months. Yet, with the app, we included a question on loss of smell and taste, and we had the answer in a week. It’s an incredibly fast and agile tool.’Tim Spector, King’s College London
The dictionary defines citizen science as “scientific work undertaken by members of the general public, often in collaboration with or under the direction of professional scientists and institutions”.
The practice has typically been used for tracking nature, such as migration and population levels. Though not completely new to medical science – biobank studies that collect samples from healthy people are essentially citizen science in their approach – however, technology is providing new ways to run studies.
In March, researchers at the Centre for Psychedelic Research at Imperial College London published the results of its ‘self-blinding citizen science’ study, which they say is the largest placebo-controlled trial on psychedelics to date, comprising 190 people (the second had 86).
The participants, who were already micro-dosing with LSD, implemented their own placebo-control measures at home, following PDF instructions. This required them to buy and prepare two batches of gel capsules – one filled with a micro-dose and empty ones – putting them into zip-bags, and undertaking a specially devised shuffling process, that involved generating random numbers with QR codes. Through this process the researchers knew what the capsules contained but the micro-dosers didn’t.
Throughout the month-long study participants were asked to guess what they were taking – a placebo or micro-dose – and from the findings the researchers determined that what mattered most about people’s experience was not what they were actually consuming but what they thought they were taking.
Balázs Szigeti, lead author and a research associate at the Centre for Psychedelic Research at Imperial College London, says the study demonstrates the power of the self-blinding method, which has never been tried before.