‘Long Covid’ was just one of the many nasty surprises that came with the COVID-19 pandemic. While symptoms of Covid-19 generally last a week or so in most people (comparable to influenza), some have been left with lasting symptoms that persist for months or years. Neurological symptoms such as difficulty concentrating, memory difficulties and fatigue are commonly reported in long Covid. We’ve previously covered studies suggesting that people who have had Covid score worse on average in multiple cognitive tests when compared to controls.
Needless to say that long lasting cognitive impairment is a pretty bad thing and that most of us would like to avoid it. We need to know the level of risk so as to make informed choices about what is an acceptable exposure to potential infection. Unfortunately, we still don’t really know the probability that someone will get lasting symptoms from a given infection, and ascertaining this information has proven difficult. Many studies place the risk of long covid following infection at 10% or more, yet others put the estimate at a mere 1-2%.
Why is there so much variation? A recently published paper argues that many studies, especially those that appeared earlier in the pandemic, were flawed and that long Covid may be much less common than we initially thought. Though not all scientists agree with that conclusion, the paper provides some interesting commentary on how the rush to produce data concerning long Covid may actually have made things worse.
One of the reasons there’s still a lot of uncertainty around this subject is that long Covid is not easy to objectively measure. Unlike the initial Covid infection, there are no long Covid testing kits. Instead, most studies rely on self-reporting. Some early studies measured what percentage of participants continued to report symptoms months after their initial infection, and used this to estimate the incidence of long Covid. Yet for some reason, many of these studies did not include a control group composed of people who had never had Covid. This is a major design flaw because some of the most common symptoms of long Covid (such as fatigue) are often reported by people who have never had Covid.
To make matters worse, many early studies only asked participants whether they had had Covid, but did not actually confirm these cases with any form of test. This means that some of the people reporting long Covid symptoms may never even have had Covid to begin with! These studies may have effectively been measuring health anxiety in addition to genuine long Covid. As a result, early studies produced alarming figures that caused panic and possibly contributed to more overreporting of long Covid symptoms.
These flaws might sound easy to resolve at first glance: simply conduct a study that measures long Covid symptoms in people with confirmed Covid, and compare them to a sample of the general population who have never been infected. However, such studies must still be carefully designed to avoid selection bias. By recruiting participants with a confirmed Covid infection, a study can inadvertently select a group that is inherently different and potentially less healthy than the control group. In particular, less healthy people who are more vulnerable to Covid are more likely to get a case of Covid confirmed, since they are more likely to make a hospital visit. Many studies failed to adequately account for such biases and confounders.
It is possible to control for some of this with a well designed study. For example, instead of recruiting people who were already confirmed to have had Covid, the UK Office for National Statistics (ONS) asked a large sample to carry out regular Covid tests and report symptoms, regardless of whether they tested positive or not. They found that 5% of people had long Covid symptoms that persisted 3-4 months post-infection, but so did 3.4% of uninfected people, suggesting that only around 1.6% had genuine long Covid.
Despite the problems with early studies and the trend towards lower estimates, it’s important to highlight that this is still an ongoing area of research. Even good quality studies still disagree about how common it really is. This study from Iceland, for example, attempted to match their control group to the infected group so as to minimise confounding factors. They estimated that the incidence of genuine long Covid symptoms 8 months post-infection was 13%. Long Covid is still less than four years old, and it’s going to take time to determine its impact. We should also remember that the risk of long Covid is likely to vary according to many factors like vaccination status, age and so on.
Title image by Fusion Medical Animation, Upslash
How methodological pitfalls have created widespread misunderstanding about long COVID http://dx.doi.org/10.1136/bmjebm-2023-112338
Physical and cognitive impact following SARS-CoV-2 infection in a large population-based case-control study https://doi.org/10.1038/s43856-023-00326-5
Technical article: Updated estimates of the prevalence of post-acute symptoms among people with coronavirus (COVID-19) in the UK: 26 April 2020 to 1 August 2021 https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/articles/technicalarticleupdatedestimatesoftheprevalenceofpostacutesymptomsamongpeoplewithcoronaviruscovid19intheuk/26april2020to1august2021