The latest findings of the world’s biggest study into ‘Long Covid’ in children and young people (CYP) – the CLoCk study from University College London – have been published as a pre-print.
Surveying 11 to 17 year-olds who tested positive for COVID-19 in England between September and March, the researchers found that the condition is not common in children and young people. This is in line with other studies into Long Covid.
As with earlier studies, symptoms were prevalent in those who tested negative as well as those who tested positive, complicating the picture of the condition which the authors acknowledge lacks clear definition.
Further confusion was sown by the fact that reported symptoms increased rather than decreased after three months, leaving the authors puzzling over the explanation.
Three months after the SARS-CoV-2 test, the presence of physical symptoms was higher than at the time of testing. This finding emphasises the importance of having a comparison group to objectively interpret the findings and derive prevalence estimates. Although 64.6% of test-positives reported no symptoms at time of testing (compared to 91.7% of test-negatives), they did not continue to remain asymptomatic, with only 33.5% of test-positives (and 46.7% of test-negatives) reporting no symptoms at three months. This finding warrants further exploration and could be due to self-selection into the study because they were experiencing on-going symptoms, recall bias, external factors relating to the pandemic such as returning to school and exposure to other sources of infection, and the actual trajectory of the illness, although this wouldn’t explain the high prevalence among test-negative CYP.
In terms of physical symptoms – tiredness, headaches, shortness of breath, loss of smell, and so on – the researchers found there was a somewhat elevated prevalence of these among the test-positive compared to the test-negative, though both had increased over the three month period.
Three months after the SARS-CoV-2 test, the presence of physical symptoms was higher than at baseline in both groups; 66.5% of test-positives and 53.4% of test-negatives had any symptoms whilst 30.3% of test-positives and 16.2% of test-negatives had 3+ symptoms. The symptom profile did not vary by age: for both 11-15 year-olds and 16-17 year-olds the most common symptoms among test-positives were tiredness, headache and shortness of breath and, among test-negatives, tiredness, headache and the unspecified category of “other”. Again, the prevalence of tiredness and headache was consistently higher in the test positives, 39.0% and 23.2% versus 24.4% and 14.2% in negatives, respectively. Prevalence was higher for 16-17 year-olds; for example, 46.4% of test-positives reported being tired compared to 29.6% of test-negatives.
The 14% difference reported here between the 30% of test-positives and the 16% of test-negatives who had three or more symptoms at three months is likely to be the study’s most accurate estimate of the prevalence of Long Covid in the sample population.
However, as the BBC’s Nick Triggle notes, the low response rate and selection bias towards the unwell in the survey may mean the true prevalence of Long Covid is more like 2%.
Only 13% of those asked to respond to the survey did so.
Researchers believe those who are suffering ongoing symptoms would be more likely to complete the survey than those who are not.
If all those with long Covid were to do so among those who did so, that would suggest their actual number was just 4,000 or fewer than 2%.
This lower figure is almost identical to the estimate of 2.3% from a study based on the ZOE Covid Symptom Study app published in Nature in March.
In terms of mental health, the study found “no difference in the distribution of mental health scores… and well-being… between test positives and negatives, overall or in either age-group”. Similarly, fatigue “showed no substantial differences between positives… and negatives”.
Despite these findings suggesting a very limited prevalence of Long Covid in children and young people, Professor Sir Terence Stephenson, the lead author of the study, told BBC Radio 4 that “we can’t trivialise this”. He said his study “provides some data” that allows policymakers “to make judgements and policy decisions” on issues such as school safety or the vaccination of children “on hard evidence, rather than speculation”.
While he acknowledged there was “no difference” in mental health between those who contracted Covid and those who didn’t, he added there was also “no difference” with young people surveyed over the last ten years. It seems young people’s mental health is “bearing up well” in the pandemic, he says.
This is a quite incredible statement in a week when it was revealed that prescriptions of antidepressants to children hit record highs in 2020, with 231,791 prescriptions issued to children aged between five and 16. In America, a new CDC report found that emergency hospital attendances for attempted suicide for children aged 12-17 were up by 39% between February 21st and March 20th of 2021 compared to the same period in 2019. There were significant differences by sex, and the most extreme increase was in females in the winter of 2021, which was up 51% on winter 2019. It is disappointing that Professor Stephenson would spin his study’s results to exaggerate the impact of Long Covid – with a nod to the vaccine rollout – and trivialise the impact of lockdowns and restrictions on the mental health of children and young people.
One of the most curious statistics in the study was of a 3.5-fold increase in young people dying in the test-negative group compared to the test-positive group. Those who died were excluded from the study, but in setting out their exclusions the researchers tell us there were six test-positive individuals who died out of 102,402, and 37 test-negative individuals who died out of 147,561. This translates to a mortality rate of six per 100,000 in the test-positives and 21 per 100,000 in the test-negatives, which makes not catching Covid increase a young person’s risk of death by 250%! No explanation is offered for this strange statistic. It is presumably because the population testing negative is at higher risk of death (from all causes) than the population testing positive. Is this because young people at higher risk of death are subject to more routine testing? Other suggestions welcome.