Are COVID-19 Antibody Results Overly Optimistic?
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There is a lot of interest in the results emerging from antibody testing in hopes that these might reflect the true range of severity and be able to nail down just how many people might have been infected already and have some immunity.
But first we need to know that the tests can tell the difference between someone who has had COVID-19 and someone who has had one of the other betacoronaviruses. Getting this wrong is bad for understanding immunity in the population, and it’s disastrous for an individual.
If you think you have a good test, as Dylan Morris has said, the way to use that test to learn about population immunity is to go somewhere where there has been a lot of disease and a large proportion has been infected. Think Lombardy or New York City; Wuhan is now small potatoes.
That assures you of something important: that there will have been enough exposure for a random sample to capture people who were asymptomatic, mildly ill, or severely ill (and let’s not forget the dead) in numbers large enough that we can accurately estimate the proportion of each.
In contrast, smaller studies in places currently with little COVID-19 activity, like California, will struggle because the signal is expected to be weaker in the first place. Smaller numbers are hard to estimate accurately. Biased sampling through social media won’t help either.
Also, if your sample is nonrandom, then you’re probably not doing useful science directed at understanding this question. You are keeping the people who do the real work busy at the pipettes.
There’s a simple smell test here. We know that outbreaks of this virus result in severe strain to healthcare. If a study reports large amounts of population immunity without much disease, we’ve got to ask why the pandemic is magically different there versus in other places.
Continued
Finally, we cannot escape the fact that the poorly designed studies and the way they are reported all skew in one direction, the one which says there is more immunity in the population for less cost in lives. This is dangerous. I don’t know what the reasons for that are. Maybe it’s wishful thinking. But the virus will carry on regardless. It doesn’t care about your study, whether it is well designed or not. Remember: Nature cannot be fooled.
I believe that there are quite huge numbers of uncounted cases and much mild disease. I just do not think it’s as much as these studies claim. There is a real answer out there, and we are still waiting for it. #Serosurveynow. But make it a good one.
Bill Hanage is an associate professor at the Center for Communicable Disease Dynamics in the Department of Epidemiology at the Harvard T. H. Chan School of Public Health. He specializes in pathogen evolution. Follow him on Twitter.
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