Covid math we didn’t learn

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Two and a half years after all our lives were upended by Covid-19 it is critical that we look forward and ask ourselves, “How will America respond to the next pandemic?” Because we “failed the math part of exam” so badly with Covid-19, I fear that we will do much worse the next time out. The anti-math contingent of Americans have really dug in their heels and have come out of this pandemic confidently holding on to all the wrong answers. Here are a few:

The Drunk Driving Fallacy

Most drunk drivers arrive home safely every night. Most heavy smokers die from something other than lung cancer. And most people have survived Covid-19. The Drunk Driving Fallacy is what convinces millions of Americans that they are “excellent drivers” even when they are tipsy, because they have yet to have an incident on the way home. That strategy works — until it doesn’t.

In percentage terms, “only” about 0.32% of the U.S. population has died from Covid-19. In a “drunk driving” sense, that is a very small number, and you hear it a lot from the mask and vaccine deniers. After all, they are still alive, over two years into this worldwide virus scare. I wrote a post about this fallacy very early in the pandemic.

The Drunk Driving Fallacy is similar to “Survivor Bias.” You are still alive, and so your prayers and your good looks must be the reason. Just don’t think about the theodicy (the “justice of God”) implications for those million people and their million families whose “thoughts and prayers” came to naught. And the fortunate people who survived a Covid hospitalization are crediting God for a miracle every Sabbath, while those who did not come home are not. In absolute terms, we are well over one million deaths, with millions more cases of “long Covid.” When it comes to human costs, percentages are often illusory. Absolute numbers are very real; there is a human face behind each number.

The real math is pretty simple. The odds of dying in a car accident for sober, safe drivers in good driving conditions (akin to basic Covid mitigations) drop to literally near “win the lottery” odds, while the death rate for drunk drivers is exponentially several “orders of magnitude” (powers of ten) higher. Susceptibility to the coronavirus brings several other health risk factors into the equation, but there is still a reason why those countries with a drunk driving cultural taboo (called “drink driving” in the U.K., an interesting quantity implication) and those countries who effectively implemented Covid mitigations continue to see far lower death rates from either cause than the United States continues to experience.

Covid risk of harm

Monkeypox and the denial of exponential spread

Early in March of 2020, when coronavirus detections in the U.S. were still below 20,000 cases (we are currently at over 90 million cases in the U.S.) and President Trump was predicting how quickly the virus would disappear, I posted a prediction for one week out, based on simple exponential math, saying that we would see within days cases triple or quadruple, somewhere within the orange and gray lines. Here is how that prediction worked out:

March Coronavirus prediction

My March 19th projection with actual results.

There was no “magic skill” here: the number of cases and deaths continued to rise at crazy exponential rates (that upward-bending curve) until first the basic mitigations, and then the vaccines, bent the curve back down to its still-ugly creep (still killing an average of almost 400 Americans daily, with over 5000 new daily hospitalizations). Because most good scientists work off what are called “Bayesian priors,” which is the best probabilistic knowledge obtained from prior mass infections, I could confidently predict the short-term path of the virus. By the same process, some of the early-proposed mitigations, such as decontamination of all surfaces, proved less effective for this virus than it was for prior infections. Other mitigations, such as high-quality masks, continue to prove to be effective deterrents, despite their “drunk driving” critics (see above). This is the scientific method in practice, with multiple studies always tweaking the probabilities, then to be fed into the next round of forecasts, as is done in making ever-changing, but also ever more accurate, hurricane forecasts.

Bayes Theorem

The Bayesian scientific process.

Other proposed mitigations with really bad “priors,” such as ivermectin (what are the prior odds that a horse de-wormer could be effective against a killer virus?), have subsequently been proven to be ineffective. Not surprisingly, there is a high correlation of those proposed treatments with notorious medical con-men out to make a buck.

As I frequently note, Mother Nature counts, not in a linear “Base 10” mode like humans do, rather in a logarithmic-appearing math in which things naturally grow on that upward-bending curve unless another natural countervailing force dampens the rate.

And now we get to the newest worldwide infection, monkeypox. This is a very different virus from the coronavirus, and because it is more similar to the near-eradicated smallpox virus (I still bear the scar of that vaccination as a child) it has a different set of “priors” when it comes to mitigations. Nonetheless, we have watched the numbers of cases again grow exponentially until the last couple of weeks, with the highest risk groups have been either modifying their infectious behavior or getting vaccinated, the two best mitigations for “pox” viruses.

The math of effective vaccines

That small smallpox vaccination scar on my arm that I obtained in my childhood meant that subsequent generations of people worldwide were far less likely to contract smallpox, a disease that killed and scarred millions of people in the generations before me. I was in the first generation to receive first the Salk polio vaccine injection, followed a few years later by the more effective Sabin oral polio vaccine, administered on a sugar cube. I did, however, come down with nasty case of chicken pox one memorable Easter morning as a child, but my own grandchildren escaped that one thanks to a vaccine. And a new version of a shingles vaccine (for a similar or the same virus as chickenpox) has exponentially lessened my chances of contracting that serious ailment.

These vaccines all share a common probability math profile that is a kind of bet. The vast majority of recipients will either gain immunity from the targeted disease of be subject to far lower levels of side effects from an infection. A tiny number, again usually near lottery-win levels of probability, will suffer more severe side effect from the vaccine itself, or even die. This is a bet that is very difficult to evaluate emotionally, and even scientifically, because we must actually “pull the trolley switch” to get the vaccine.

The Covid vaccine is a great case in point. My vaccinated/boosted spouse and I have yet to test positive from Covid, despite many tests and even some suspicious early-onset symptoms. Is it because we have been careful to use basic mitigations? (We have.) Or is it because we have never come into close enough contact with a coronavirus variant that could break through the vaccine barrier? (Possibly.) Or because we are excessively “godly” as compared to miscreant sinners who contracted Covid? (That would be a “no.”)

Especially with Covid, we really only know of “vaccine-adjacent” deaths, in other words, people who died within some arbitrary short period after receiving a vaccine. One well-recognized study found a vaccine-adjacent death rate of about 53 per million long-term care residents, with residents over 85 constituting over half of the deaths. But there is a significant overlapping base rate of “natural deaths” of nursing home residents over any one-week period from any cause complicating that count. And the same study cited a staggering 21.5% one-month death rate of unvaccinated nursing home residents who do contract Covid. They thus concluded that vaccination was the far better bet for the infirm elderly.

But this is a case of the tiny “bullet that you hear” (someone reported to be harmed from a vaccine, often amplified by social media) versus the very much bigger “bullet that you did not hear,” all those times you missed contracting and dying from the disease. Mathematically, the bet is an easy one to make. We are again talking about multiple “orders of magnitude” differences between deaths and hospitalizations of vaccinated people versus the unvaccinated. But emotionally, some people just can’t do it, especially if they are stoked by fear from irrational media voices, or if they fear the math more than the disease.

Math will not kill you. Viruses can. Fox News can.

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