Serological Studies and Context

A hypothesis I have mooted here several times is that, given: (1) the contagiousness of the coronavirus (including from asymptomatic carriers), (2) the slow roll-out of testing for COVID-19, and (3) the fact that a significant plurality of the afflicted do not even realize they are infected; then the actual case count should be higher than the widely-reported figures, perhaps by an order of magnitude or more. This obviously has implications for herd immunity (if infection confers significant and long-lasting immunity) and both hospitalization and death rates. (For a simple example, if case numbers were an order of magnitude higher, those rates would be a tenth of what is being reported, assuming those numbers were otherwise accurate.) This is an important question for evaluating what to do about the virus, and that emphatically includes you and me, as individuals.

Preliminary serological results have come out recently, notably out of Los Angeles and Santa Clara County, California, that estimate under-reporting by a factor of 50-85. This is great news, if it holds up, but it may be too early to feel relief, as a story from NPR explains in part:

Refusing to confront a danger does not make it go away, to say the least. (Image by Caleb Woods, via Unsplash, license.)

The test [with] a specificity of 99%, which means it only falsely says a blood sample contains antibodies against the coronavirus 1% of the time. But despite that impressive statistic, a test like that is not 99% correct, and in fact in some circumstances could be much worse.

That's because of this counterintuitive fact: The validity of a test depends not only on the technology, but how common the disease is in the population you're sampling.

"It is kind of a strange thing," admits Dr. H. Gilbert Welch, a scientist at Brigham and Women's Hospital in Boston who studies issues surrounding tests and screening. "An antibody test is much more likely to be wrong in a population with very little COVID exposure."

This is a result of statistics, rather than the technology of any given test.

Here's a simple way to look at it. Say you are running a test that gives five falsely positive results in a group of 100 people. That doesn't sound too bad. But consider this. If 5% of those 100 people were actually infected with the coronavirus, you should get five correct test results (true positives), along with the five false positive results. [bold added]

In this light, the tests I mentioned earlier -- which indicated low single-digit percentage infection rates in the general population -- might not alone offer much reassurance that the above hypothesis is correct, as reasonable as it is. (The authors report a specificity of 99.5%, and at least one discussion raises concerns over sampling. Furthermore, the study has not yet been peer-reviewed.)

That said, the NPR piece indirectly raises another issue that should give us even more pause. "Flatten the curve," originally sold to the American public as a means of giving hospitals time to adjust to the pandemic has morphed into an excuse by government officials to impose indefinite universal lockdowns on the population. I seem to recall that Governor Newsom of California may be among those who expect everyone to hunker down until there is a vaccine. At most wildly optimistic best, this will take one or two years. More realistically, it's five or more years down the road. Even if it were not wrong to imprison people in their own homes, this would be a ridiculous amount of time to wait, even for a guaranteed result.

But, as NPR notes, "it's not clear whether someone who has antibodies to the coronavirus in their blood is actually immune." This puts the whole idea of herd immunity into question. And if herd immunity is in doubt, then so is the deus ex machina of a rapidly developed, perfectly safe, and completely effective vaccine.

Hell, there may never be a vaccine. Wouldn't we be better off resuming our lives as much as possible now -- with open eyes and thinking about how we manage the continued stalking presence of this disease -- than tolerating imprisonment and fantasizing about a salvation that may never come?

And too many people are lazily and dangerously relying on the tender mercies of government. Each of us should consider what, "Prepare for the worst, but hope for the best," means for ourselves as an individual, versus for a government official.

In the former case, it means exercising vigilance and carefully weighing things in a way one did not have to before the virus came along. This can be hard at first, but at least quality of life -- your one, irreplaceable life -- comes into play, too.  And, so long as you repect the rights of others, the only person who should have a say in that -- you -- gets to decide. A politician is motivated primarily by whether he will get reelected (so long as it's not a "safe" district, in which case, deuces wild), and as for bureaucrats, they just want to not be seen as wrong by their bosses.

-- CAV