
We win by changing the statistics, not through an iron-clad personal defense.
Here’s what frustrates me most about the US struggle against Covid-19: the widespread attitude that rejects any partial solution, and instead demands a rock-solid personal guarantee. “If I do this and this and this, I’ll be OK.” And if that kind of assurance isn’t possible, then what’s the point?
Masks can’t offer that guarantee, unless you’re willing to walk around in a full hazmat suit. Distancing won’t do it unless you become a complete hermit. Vaccines allow breakthrough cases. Even the just-announced Merck treatment pill isn’t a complete cure: It claims to cut your risk of hospitalization in half, not eliminate it completely.
So what’s the point? No matter what I do, I’ll either catch the virus or I won’t. I’ll live or I’ll die.
The flip side of this binary attitude is a deep gullibility about snake-oil “cures”: I’m not worried about Covid, because I’ll just take hydroxychloroquine or ivermectin. Or maybe I’ll prevent it by gargling iodine or something. Some guy on YouTube claims that always works.
Or maybe I’ll deny the problem completely: There is no virus. The panics at ICUs in states with low vaccination rates are all staged by “crisis actors”. Really, it’s all about government forcing us to wear masks and get shots. If they can do that, the global dictatorship is at hand.
All of this makes me despair about my former profession. I used to be a mathematician. Apparently we’ve done a really bad job teaching people how to think statistically.
You see, fundamentally an epidemic is a numbers game.
Maybe you’ve seen TV episodes where a deadly disease gets loose until a heroic scientist intuits a miracle cure: Some chemical everybody has in the garage or under the sink turns out to be a perfect antidote to whatever-it-is. You swallow a teaspoon of baking soda or something, and you’ll be fine.
The reason TV writers go for a that kind of scenario is that they need to wrap things up by the end of the hour. But it’s hardly ever how things actually work.
Maybe you’ve noticed that there’s an outbreak of Ebola in Africa every few years. One spilled over into the US briefly during the Obama administration, but they happen every now and then. The latest one was in Guinea, and it was declared over in June.
There’s still no reliable cure for Ebola. [1] And there wasn’t a vaccine until 2019. But they beat back the outbreaks — including the 2014-2016 outbreak that made it to the US — anyway. Plagues of all sorts get controlled somehow, usually without a cure.
It’s a numbers game.
So let’s talk about numbers.
During a surge in new cases, you’ll hear a lot about exponential growth, where the number of new infections doubles every so-many days: I get sick. I infect two other people. Each of them infects two other people, and so on. Before long, the ICUs are full and bodies are stacking up in the morgues.
Fortunately, though, the same dynamics can also get you exponential decay, where the number of new cases gets cut in half every so-many days.
The difference between the two scenarios can be subtle. If every 10 infected people give the virus to 11 more, you’re on an exponential growth path. But if they only give it to 9, you’re in exponential decay. [2]
That’s how a community can beat a virus without a rock-solid method of prevention or cure. So sure, masks and distancing don’t guarantee you won’t pick up an infection. Vaccination doesn’t guarantee you’ll shake it off, or even that you won’t pass it on. But if those tactics just change the odds a little bit — get those 11 new infections down to 9 — the community will beat the pandemic rather than lose to it.
That’s how we win.
Now we run into the second problem: It isn’t just that people don’t understand how to think statistically, often they don’t want to. We don’t like to think of ourselves as drops in a statistical ocean, because we are individuals. [3] The evil of modern society was summed up more than half a century ago in “Secret Agent Man“:
They’ve given you a number and taken away your name.
Conservative rhetoric in particular is tuned for me-thinking rather than we-thinking. [4] But pandemics are fundamentally statistical — they’re waves that pass through an ocean — and we beat them by acting for the common good, even if we can’t get an individual guarantee.
It’s not that you aren’t an individual, but the individualism/collectivism thing is kind of like wave/particle duality in physics. You are an individual, while simultaneously being a drop in the ocean. Whether your individuality or your membership in the community is more important depends on what question is being asked.
Pandemics are ocean-level challenges: You can’t create one by yourself, and you can’t solve one either.
We also have a bias towards all-or-nothing thinking about risk. Instinctively, we don’t want to manage risk, we want to nuke it. [5] We want to tell ourselves “Bad things can’t happen because I’m doing this” rather than “I’ve shifted the odds in my favor.”
While that kind of thinking is natural, it’s also something to be overcome, because it either incapacitates us or pushes us into denial. Every time I get into my car I risk dying in a traffic accident. I could just refuse to go anywhere, or I could deny the risk via some kind of magical thinking about my exceptional driving ability or the power of my St. Christopher medal.
Instead, I do what I can to turn the odds in my favor: I wear a seat belt. I drive carefully, and avoid getting on the highway when I’m tired or influenced by drugs.
Probably you do something similar. We know how to manage risk. We just need to do it. And if enough of us do it well enough, exponential growth turns into exponential decay.
[1] The FDA approved its first Ebola treatment in 2020. In the trial, only 33% of the people who got the drug died, compared to 51% in the control group. That’s what success looks like.
[2] I know that 11/10 isn’t 2 and 9/10 isn’t 1/2. But the weird thing about exponentials is that all the curves you get from exponents over 1 look one way, and all the curves from exponents under 1 look another way. All that changes is the scale on the time axis. In other words, the value of “so-many” in “every so-many days” changes.
[3] Except for that one guy in Life of Brian.
[4] Perversely, though, it’s often the do-your-own-research crowd that is most influenced by group-think.
Today, being pro- or anti-vaccine has become essential to many people’s social identity during the pandemic. William Bernstein, a neurologist and author of The Delusions of Crowds, pointed me to the “moral foundations” theory, which attempts to understand what motivates the decision-making of people on the right and left ends of the political spectrum.
That theory holds that, within the American right, the concepts of loyalty and betrayal are more influential to their worldview than on the American left. Staying true to your group is a powerful pull for conservatives.
“For these folks, facts mean nothing; membership and identity, everything,” Bernstein said over email. “Groupishness, in-/out-group differentiation … is much stronger on the right.”
That’s why not-getting-vaccinated or not-wearing-a-mask can become such a point of principle that people will lose their jobs or even get violent rather than comply: It’s not just the inconvenience or the relatively minor risk; it’s betraying the group they feel loyal to.
[5] The scholarly name for this is “zero-risk bias“. If you ask people what they’d be willing to pay to eliminate some low-probability high-impact risk (like toxic waste contamination in their neighborhood or a radiation leak in a nearby nuclear power plant), you’ll get one number. But if you ask what they’d be willing to pay to cut that risk in half, you’ll get a number close to zero.
People don’t want risks to shrink. They want them to go away.
Comments
Thanks so much for this analysis! You always take the big picture and make it easier to understand.
I have not heard of zero risk bias before. That’s one of the dumbest ones! Boy, are our brains stupid.
Thanks, Doug, as always, for your clear vision and exposition of the problem. The “math” writing was excellent — and I speak as one who gets paid (by a university) to talk about complicated mathy things in a way that 18-22 year olds can understand. Nicely done!
Thanks! In addition to your observations about minimizing vs. eliminating risk, when there’s a threat with no end in sight (because while I hope we can reduce the risk of covid-19 to the same level of risk as, say, ebola, I have no illusions that we’re going to eliminate it), we need to also measure risk against the reward. Your driving example isn’t quite risky enough to be a good illustration, so I’ll just use the actual situation: Eating in a restaurant is risky, so I won’t eat inside just any restaurant, but I will eat inside my favorite restaurant. Not because the risk is lower, but because the reward is high (in my case). For other people it might be that you’ll spend time in a small room for a long time with vaccinated family but not with vaccinated strangers. (Or vice versa! LOL)
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