Long Covid: the numbers don’t add up, so why do we keep collecting them?

How common is Long Covid?  Top of the range, with estimates of nearly 40% of people who’ve had Covid still being symptomatic 12 weeks later, come the REACT-2 study and a recently-published analysis from a US database. In the basement come estimates of 0% from a follow up study of children in Melbourne who had recovered from mild or asymptomatic infection, 2.3% at 12 weeks (the Zoe survey), 4% from a study of schoolchildren in Zurich, and 5% for symptoms at 12-16 weeks from a recent ONS survey. And other estimates in between…

Why is there so much variation? There are the usual suspects – results may be influenced by differences in the samples in terms of age, gender, BMI, vaccination status and so on. Many of the symptoms reported are non-specific (such as fatigue, aches and pains, difficulties with concentration) and endorsement is likely to depend upon exactly how they are asked about and whether an attribution to Covid infection is required. Response rates varied greatly – only 13% in a substantial UCL UCL study of young people and 20% in an ONS study of school children. Some attempt to adjust is possible but response bias and confounding can’t be entirely discounted.

Maybe there’s an issue of reporting threshold – the higher estimates coming from counting relatively minor experiences while the lower estimates count only more severe symptoms. Certainly there seems to be an inverse relationship between number of symptoms and prevalence, but severity (intensity, intrusiveness) is harder to gauge from readily available reports. An ONS survey from earlier this year suggested that only about 1 in 10 respondents was limited a lot by their experiences. An intriguing finding from a study of NHS general practice records suggests that GPs are recording very few cases by comparison with those reported from research surveys – in fact about 100^th of the numbers, with a quarter of GPs using NHS codes for Long Covid to describe no cases at all in the study period. The headline of the Guardian’s report of the study this article was amended after publication. An earlier version said that GPs in England were “failing to recognise thousands of long Covid cases”. The headline was changed to indicate that the research concluded that “long Covid coding in primary care is low compared with early reports of long Covid prevalence”.” An acknowledgement that at least one possible explanation is that GPs are applying a clinical-severity filter not recognized by researchers.

Another way to ask about the significance of “Long Covid” symptoms is to consider the prevalence of the same sort of symptoms in the general population. For example persistent fatigue is reported by between 10 and 20% of the general population and something like 50% of people with an identified physical disorder. Not many Long Covid studies collect data from comparison groups, but one ONS survey suggested 3.4% of non-Covid respondents had the same symptoms as the Covid+ respondents and the UCL study found a figure of 16%. In both studies the Covid respondents had more symptoms than the non-Covid respondents, but between-study differences raise again the question of why so much variation – no doubt it’s down to sampling, how the questions were asked, and response rates.

So … what is the value, and what is the likely outcome, of collecting not-very-accurate information on underspecified populations of people who have had a Covid infection and who for the most part have non-specific symptoms that are common in the general population? It may be that the result will be a better understanding of the nature of longer-term problems attributable (or attributed) to Covid infection, but it isn’t clear that these surveys are the most efficient way of getting there. And there are potential pitfalls – Long Covid manifestly isn’t a single condition and it is difficult not to see, in the current approach to researching it, the process that Ian Hacking called Making Up People – the bringing into being of a new category of people with what may turn out to be a transient illness (transient as a medical category that is, not for the individual) – in ways that are not beneficial to anybody concerned.

A start would surely be to stop using the term Long Covid. It’s unlikely we’ll convince the media or pressure groups to drop it, but a move in the right direction would be if researchers and clinicians started using more specific terminology to describe exactly what it is they are studying and why.