We’ve never successfully controlled an airborne virus, cured or developed an effective vaccine for a coronavirus or the flu, or even successfully modeled anything as complex as a spreading, mutating virus, and yet we still continue to persist in the fantasy we can, despite all evidence.
As the Delta surge continues and public health experts consider additional measures to slow the spread, now is the perfect time to consider the insane hubris that underlying our response from the beginning. The concept of “hubris” comes to us from the ancient Greeks, describing an outrage against the gods or the natural order of things, usually driven by pride or overconfidence in a person’s abilities. Hubris is the mechanism that underlies much of Greek tragedy. For example, Arachne was a skilled young weaver that claimed she had more talent than the goddess Athena, who promptly transformed her into a spider so she could weave for all eternity. Icarus is a daredevil who flew too close to the sun on wings made of wax, only to perish in the sea when the wax melted.
The idea captured a simple reality: Humans, for all of their intellectual gifts and accomplishments, are only capable of so much. Whether in ancient Greece or 21st century America, there is a point beyond which we cannot reach and when we try, tragedy ensues. Hubris has been a topic on my mind since practically day one of the coronavirus pandemic, when it seemed clear to me that despite our advanced technology, models, medical treatments, vaccines, etc. a virus simply cannot be controlled in the manner assumed. If you step back and look at the underlying impetus for everything we’ve done to date, it starts with the assumption that we can precisely predict the behavior of microbe so small we cannot even conceive the size and, armed with those predictions, we can change that behavior like we would Photoshop an image.
In this analogy the models themselves are the picture we are editing and the variables the model’s use are the things we can change with a slider, measures like masks, social distancing, limits on gatherings, closures of certain businesses, closures of certain areas in certain businesses, restrictions on certain goods or activities, etc. Ultimately, the belief is that if only we dial in a little more of this and a little less of that, presto, the spread is controlled and the virus can be stopped. Two assumptions are baked into this, but are rarely mentioned: First, that the models themselves are accurately describing the behavior of the virus. Here, it’s important to understand that the models aren’t actually considering what the virus does on a molecular level. Instead, we’re reducing the billions of interactions the virus has within our bodies and other bodies to a set of assumptions about how quickly it spreads and under what conditions. Second, even these assumptions are subject to debate and not based on reliable data.
For comparison’s sake, consider one of the crown jewels of scientific achievement, the Standard Model of Particle Physics. The Standard Model describes the behavior of three out four fundamental forces, the electromagnetic, and the weak and strong nuclear force. Armed with it, we can near perfectly model the behavior of subatomic particles and by, near perfect, I mean accurate out past 6 or 7 decimal points. The Standard Model, however, comes with a catch: The model includes at least 19 parameters that are set entirely by experiment, meaning their values are not described by the model itself and why these parameters take the values they do is completely unknown. We only know the values ourselves with a high degree of precision after decades of experimentation and observation. If you were to go back in time, and teach the Standard Model to Sir Isaac Newton without specifying those parameters, it would be entirely useless to him because he would have no means to calculate their value.
Circling back to the pandemic, the models used to predict the behavior of the virus are not nearly as accurate as the Standard Model of Particle Physics, nor have we had decades of time to properly set the parameters. Instead, the parameters themselves are preliminary observations and assumptions, subject to change without notice. Even worse, the parameters aren’t nearly as granular either. For example, SIR is a popular model to calculate the spread of an infection over time. It contains just four variables, the initial number of susceptible subjects, the initial number of removed subjects (those immune to the disease or those who have had it), the size of the population, and the rate at which the virus spreads. That’s it. Two of those variables are composites of hundreds if not thousands of factors, the rate of spread and the removed subjects, and neither of them could possibly be known with any certainty early in the pandemic. Plus, the value of these variables like the rate at which the virus spreads, RO, changes over time.
The potential number of deaths was then calculated by applying the case fatality rate to the SIR model’s output of the spread of infections, even as estimates for the case fatality rate occupied a broad range. Initially, some experts put the fatality rate as high as 3%, resulting in predictions of millions of people dead in the United States in just three months. The Imperial College of London for example claimed 2.2 million dead in that short a span, a number that was immediately seized upon for public policy despite a poor track record of similar predictions from the same group. The current confirmed case fatality rate in the United States is 1.7%, but even that is deceptive as the number is notoriously difficult to calculate. You arrive at 1.7% simply by taking the number of confirmed deaths and dividing by the number of confirmed cases, but in reality experts estimate the number of cases to be at least several times higher. The fatality rate could be .4% or likely even lower. We might not ever know the actual number except as an estimate, but some number is used in the model regardless.
This simplicity, variability, and lack of specificity across all these models didn’t prevent a media and public health expert obsession with the output, as if the experts producing these models were oracles and seers in ancient Greece, and a corresponding belief that we might slow the spread. Of course, the plan to slow the spread itself was based on an equally simplistic model, an idea originally conceived by a then 14-year old, Laura M. Glass, for a high school science experiment. Ms. Glass created a computer simulation to describe how people interact and how much. She determined that school kids come in contact with 140 people per day, more than any other group. She applied that finding to a hypothetical town of 10,000 people and showed that 5,000 would be infected in a pandemic if schools were open, but since students interacted with more people, only 500 would be affected if they were closed. Again, that’s it. Reduce the number of interactions per day on a slider, and lockdowns are an instant success story.
The real world, of course, is a lot messier and, as a result, the models have been consistently wrong. Even a year later and armed with much more data, we are still unable to predict the various waves in advance with any precision or even when a wave in motion might subside. Hence, in March and April while cases were collapsing for a still unknown reason, the experts were convinced “impending doom” was imminent, but then in May they suddenly became optimistic and relaxed the mask mandate. By July, this optimism had completely taken hold, prompting President Biden to declare victory over the virus on Independence Day, only to reimplement the mask mandate before the month was even over because the latest Delta surge caught us completely by surprise.
None of this should’ve been remotely surprising, however: Our ability to model and predict complex systems has always been limited for obvious reasons. In fact, there’s not a single complex system in existence that we can model with anything approaching the near-perfect accuracy of the Standard Model of Particle Physics or the General Theory of Relativity. Do you trust the 10-day weather report? Do you rely on a computer to determine which stocks to buy and trust it to accurately predict changes in the economy? If not, why would anyone trust what some model says about deaths that might or might not occur three months from now?
And yet the inability of our coronavirus models to predict the behavior of the virus in the real world is rarely identified as a potential concern for relying on the model in the future. Instead, we just move onto the next prediction, rapidly forgetting the errors in all prior cases. Perhaps even worse, we institute policies based on these predictions as if the real world can truly be edited via a Photoshop slider without any unintended consequences or unwanted side effects. Both public health experts and most of the mainstream media continue to insist that the lockdowns were both necessary and effective, while continually dismissing the obvious collateral damage. What model predicted 6.8 million jobs lost? The 27% spike in drug overdoses? The increase in domestic violence and suicide? The rapid increase in violent crime, especially concentrated in cities, overall? How about thousands of students who simply disappeared from online learning, never to be seen again as far as we can tell? Or the millions of lost educational hours? None of them, of course, but it still happened in the real world, the fallout from which we will be dealing with for years to come.
Now, we find ourselves confronted with yet another surge of the virus, a renewed mask mandate, and accompanying calls to reimplement restrictions on social gatherings and social distancing. Masks in particular have become almost a religious talisman, assumed to grant the same protection as a hazmat suit. What goes entirely unsaid, even though it’s entirely obvious: Cloth masks and cheap plastic ones bought in drugstores offer very limited protection. Dr. Anthony Fauci said it privately in an email in February 2020, and now Dr. Michael Osterholm said it publicly just this week. “We know today that many of the face coverings people wear are not effective in reducing any of the virus movement in and out.” There isn’t much that can be more obvious than that, and yet instead of recognizing the absurdity that millions of lives could’ve been saved over centuries if humanity simply adopted wrapping their mouth in a scarf, Dr. Osterholm doubles down, “We need to talk about better masking. We need to talk about N95 respirators.” He says this even as the politicians ordering these mandates often go unmasked themselves.
The latest surge, cases up hundreds of percent in just a few weeks, is occurring even after the development and rollout of a vaccine in record time, an achievement that was widely believed to be the ultimate endpoint in the pandemic. Once again, however, we’re being taught an object lesson that nature doesn’t readily conform to our wishes: The vaccine isn’t as effective against the Delta variant as the original strain, and breakthrough infections are becoming increasingly more common, meaning coronavirus will continue to spread no matter what we do. In Kentucky, for example, about 20% of new infections are occuring in vaccinated people and about 11% of deaths. Anecdotal information puts the number even higher, with an outbreak in Massachusetts where 74% of the infected were vaccinated and 80% of those hospitalized, or the spread among Texas Democrats traveling to DC, or now Senator Lindsey Graham announcing he tested positive just this week.
One would think numbers like this might cause a little introspection and consideration that perhaps our ability to deal with a new, fast spreading infectious disease isn’t absolute or unlimited, the experts not actually oracles who pronounce truth from on high. If the vaccine is less effective against the Delta variant and no model predicted the Delta variant itself, what about the next variant or the next? Lamda is out there as well, circulating now, perhaps prompting another surge, perhaps not. Instead, frustrated that our plans and predictions don’t work as advertised, we lash out at one another, blaming those who are not yet vaccinated and claiming they have blood on their hands, as if all our troubles will be over if a few more people would get the shot.
Ultimately, none of our failures to contain or eliminate the virus should be remotely surprising. We have never successfully defeated any coronavirus or influenza virus, whether by vaccine or therapeutic. There has never actually been a coronavirus vaccine before, ever. Indeed, both strains of virus and other diseases have plagued humanity for centuries, but suddenly, for completely unjustified and largely unsaid reasons, we’ve somehow convinced ourselves we’ve found the answer, both to permanently stop it with a vaccine and, in the interim, to control it with other measures. When these measures fail or generate limited results or unintended consequences, we run the entire thing again, as if doing the same thing is going to generate an entirely different result. This time, yes, this time, we’ll control a force of nature and stop a virus from spreading.
What is this other than an insane hubris that would make the Ancient Greeks blush?
Some may say this is a defeatist call to surrender to the virus, but I don’t see it that way. There is no doubt that we’ve done amazing things, in record time. In addition to a vaccine that offers significant protection, we’ve developed new therapeutics, adapted old ones, and ultimately saved a lot of lives that would’ve been lost without the miracles of modern technology. We should continue to focus on all of the above, but we should also acknowledge and accept that humans have limitations and one of them is an imperfect control over the forces of nature. We should also acknowledge the reality that humanity has always been plagued by illness and nothing is likely to change that. Finally, we should embrace the idea that humans need to live and be free to prosper, even in an uncertain world of illness and death, as we have always tried to do before.
They say pride comes before a fall. The worst possible fall of all would be humanity under continual, sporadic lockdown, continuing to hide in their homes anytime a virus or some other calamity rears its head, waiting for someone to control life and death, and hoping some scientist truly does arrive as a modern Oracle at Delphi. I can assure you it ’ s not going to happen whatever we may wish.