Because Covid-19 testing in many countries is skewed towards testing only those with the worst symptoms, some argue official fatality rates are misleadingly high. They wonder what would happen if the virus was allowed to run wild.
At this stage we don’t know the long term effects of Covid-19. Beyond the obvious short term impact on lungs, it appears to affect endothelial cells throughout the body, impacting the lymphatic system, heart, kidneys, intestine and other organs. T-cells, part of the immune system, seem to be affected too. In time we might discover that the disease has broader, possibly lasting effects on the body. Perhaps it doesn’t. At this stage we don’t know.
How many would die if Covid-19 was left to run wild infecting everyone?
This is a subject of much debate. One key challenge, given limited testing, is pinning down how many people have already been infected. Countries with high fatality rates are likely to be missing many mild or asymptomatic cases from their infection numbers, inflating their fatality rates.
A significant number of studies suggest for every symptomatic patient there is at least one other with negligible or no symptoms. For example, 52% of those testing positive on the Diamond Princess cruise ship were asymptomatic, and 43% of those testing positive in the quarantined town of Vo in Italy had no symptoms either. A recent report from China suggests 59% with the disease could be asymptomatic.
Seroprevalence testing for Covid-19 antibodies
Seroprevalence tests that look for antibodies are being used to estimate actual infection rates. Two studies, one in Santa Clara in the US, and one in a village in Germany suggest infection rates far higher than official figures – 50 to 85 times in the Santa Clara study. But there is much uncertainty, especially around the issue of false positives in these studies.
A peer review of the Santa Clara study finds it is statistically possible that all of the study’s positives are false. In addition, those recruited for the study came via Facebook adverts. This might have drawn in a large number of people who thought they were infected but failed to get a swab test, skewing the sample towards a highly infected minority.
If more statistically certain tests in the future support these results it would be good news, assuming Covid-19 has no long term impact on the health of those who have had it. But given the high uncertainty around false positives and sampling it feels too soon to draw conclusions from these studies.
Using South Korea’s thorough testing to estimate fatality rate
There are countries with thorough testing, tracking and tracing systems that have captured many mild and asymptomatic cases in their official figures. In South Korea, people are tested if they have had any close contact with an infected person, regardless of whether they show symptoms or not. South Korea has tested 584,000 people and has a positivity rate of 1.8% – this is the rate of positives across all tests.
A low positivity rate indicates the testing net has been spread wide. By contrast, the UK has a positivity rate of 23.7%. The Swiss rate is 12.5%, somewhere in the middle.
Age adjusting
Another factor driving fatality rates is the age of those infected. Older people are more likely to die if infected. If more older people get it more will die and the overall fatality rate will be higher. To calculate a meaningful estimate of a population-wide fatality rate it is vital to adjust for age.
The outcome-based death rate in South Korea is currently 2.8%. When this is age-adjusted in line with the total population it drops to 2.4%. On this basis, if the virus was left to run wild and 100% of South Korea’s population was infected the death toll could reach 1.3 million.
Is this figure reliable? Possibly. Possibly not. A big question is: what percentage of total asymptomatic cases South Korea’s testing has picked up?
Applying South Korea’s experience to Switzerland’s population results in an age adjusted fatality rate of 3.1% and a potential death toll of 270,000, assuming the virus was left to run wild and 100% of the population was infected. The higher rate of 3.1% reflects Switzerland’s relatively older population.
But how accurate is it to apply a rate from one population to another? Different underlying health, environmental factors and genetics could produce a misleading result. For example, obesity appears to be a risk factor and rates of obesity are higher in Switzerland than in South Korea – 42% of Switzerland’s adult population is overweight (11% obese). The same figure in Korea is 30% (4% obese).
Herd immunity
Might herd immunity kick in at some point before everyone caught it and reduce the death toll? Possibly. But big questions remain regarding natural immunity. To reflect this uncertainty, South Korea has refrained from describing patients as recovered. Instead it refers to released patients.
Shielding the vulnerable
If the most vulnerable were shielded from the virus while it ran wild would the death toll be lower? In theory yes. But attempts to do this haven’t worked particularly well in Europe so far. Older people in Italy, France, UK, Belgium and Spain have been hard hit. Germany and Switzerland have done better and this is reflected in their lower fatality rates.
In any case, we don’t yet know if Covid-19 has any long term effects. Other viruses that appear harmless initially can cause problems further down the line. This is a new pathogen and the body is a complicated thing.
What might happen if everyone caught it remains a minefield of unanswered questions.
More on this:
Infection and testing data (in English)
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