Within months of SARS-CoV-2‘s emergence as a global catastrophe it was becoming clear that many who spread the disease did so unwittingly, experiencing not so much as a tickle in their throat to alert them of the danger within.
Distinguishing those who are truly asymptomatic from those who are simply yet to show signs of the virushas made it hard to calculate a precise figure on the risks of succumbing to the illness.
Early estimates ranged from just 4 percent of infections being asymptomatic, all the way up to 81 percent. Even as the pandemicensued, figures conservatively estimated fewer than 20 percent of people might be infectious without showing any signs.
Confidently nailing down a number is harder than it might seem. Without the fever, loss of smell, sore throat, aches, and cough to encourage a trip to a clinic, few people bother lining up for a test.
One of the simplest ways to capture the true spread of infection is to conduct a cross-sectional survey, randomly sampling a population to detect the presence of the virus regardless of the subject’s health.
There’s just one problem with this approach. Anybody who’s feeling well on the day they’re tested can potentially fall sick hours or days later, making ‘no symptoms’ look the same like ‘no symptoms… yet’.
To make the challenge even harder, SARS-CoV-2 can produce a variety of symptoms, some of which we’re still learning about late in the game. Going back through the literature to identify those who might have been symptomatic after all is no easy task.
It’s not that scientists haven’t tried. But according to the researchers who published this most recent effort, most either don’t account for the bias of symptomatic individuals seeking tests more than people without symptoms, or didn’t include enough longitudinal data to capture those who might have fallen ill later.
The result is likely to be an under-appreciation of the true extent of asymptomatic cases.
To address these limitations, the team systematically conducted two separate meta-analyses of existing COVID-19 studies that reported on laboratory-confirmed infections.
The first was limited to studies that included a substantial follow-up period to clear those who experienced some kind of effect from the virus later. The results of this particular analysis suggest 35.1 percent of people who might receive a positive laboratory result won’t personally suffer any consequences of their infection.
The second included studies that both distinguished silent infections at the time of testing as well as conducting a follow-up analysis. The number here was 36.9 percent.
The figures are close enough to convince the researchers that their method has merit, reinforcing speculations that many of our best guesses have been too low. Even taking into account index cases that could be biasing calculations, their figures are at least one in every four cases being silent ones.
Without looking at the development of symptoms at a later date, around 40 percent of individuals with a positive COVID result were feeling well at the time of their test.
In time, more studies might add data that skew these figures further. Long COVID – the residual symptoms that cling long after the initial period of illness subsides – came as a bit of a surprise to epidemiologists, so future work might yet uncover a few symptoms we missed.
Still, the take-home-message from the research remains clear. Many of us, more than we might think, can carry the virus in spite of feeling on top of the world.
With vaccines limiting symptoms while still leaving gaps for the virus to replicate, appreciating the ability for COVID-19 to tread silently through our midst is more important than ever.
This research was published in PNAS.