Here is the full transcript of Bob Rauner’s talk titled “Where We Went Wrong With The COVID-19 Pandemic” at TEDxOmaha 2023 conference.
Listen to the audio version here:
TRANSCRIPT:
Tough Decisions in the Face of Uncertainty
Leaders are sometimes faced with tough decisions in the face of uncertainty that can affect the lives of thousands or even millions of people. This really recently played out in the worst pandemic in a century that killed more than a million of our fellow Americans. How did we do? Unfortunately, not very well.
If we had performed more like Canada, we would have had closer to 440,000 deaths, or like Germany, closer to 670,000 deaths. Our underperformance compared to these other developed countries led to the deaths of more Americans than all of our combat deaths in World War II.
So what went wrong and what went right? A lot has been said about technical mistakes like our failures in testing, but I think our bigger problem was failures in decision-making due to falling for false narratives, not knowing who the real experts were, and not following the data.
The Beginning of the Pandemic
Soren Kierkegaard was famous for saying, “Life can only be understood backwards, but it must be lived forwards.” So let’s go back to the beginning of the pandemic for me.
Picture yourself as a physician with a public health background on the school board at Lincoln Public Schools. It’s an emergency meeting in March of 2020. I’m sitting next to Dr. Steve Joel, our superintendent of public schools, and he asked me, “How serious is this?” And unfortunately, I really couldn’t tell him.
The information is conflicting and confusing, and there’s no clear recommendations coming from any layer of government. He tells me about a presentation that the Omaha area superintendents had by Dr. James Lawler that apparently really concerned them, and I said, “Is there any chance you’d get me a copy of that presentation?” And he did.
So the next morning, in my email inbox, is his presentation, and I’m looking at his slides, and I stop on this slide. What James was doing is looking at ranges of uncertainty based on our moderate or severe projections of the pandemic: how many hospitalizations and deaths. In my day job, I do a lot of work with health data, and so, of course, I started running the numbers myself.
I started adding ranges of uncertainty and some of the new information coming out of Italy and Spain, and I had a new reaction: “Oh, shit.” We’re looking at anywhere from hundreds to over 1,000 dead just in Lincoln, Nebraska. So now it’s the next week. It’s spring break, and we’ve got a tough decision to make.
The Decision to Close Schools
Do we bring the kids back to school or not? It’s not an easy decision. If we don’t bring 42,000 kids back to school for a few weeks, that’s a lot of parents scrambling for childcare. That’s a lot of employers who aren’t going to have their employees coming to work.
If we cause this degree of disruption in the community, then if the numbers are overblown, we are going to look pretty bad. On the other hand, if these numbers are right and we bring the kids back, we could contribute to the deaths of hundreds of people in our community. So what would you do? In public health, we’re taught to follow something called the precautionary principle.
What that means is that, let’s say you’ve got a wide range of uncertainty, 100 deaths on one side, one on the other; you have to act as if the 100 is true and to have good information that the one side is true. I’m happy to say that we chose caution, and we didn’t bring the kids back to school. Our decision, combined with that of many others across the country, likely saved the lives of tens of thousands to hundreds of thousands of people in the United States.
We did not have enough testing, and our hospitals were woefully underprepared. Now in August of 2020, on the other hand, we had reasonably good information that we could bring back the kids to school safely, and we did in Nebraska, leading to a lot less learning loss. So what went wrong, I think, can be summed up in this quote by H.L. Mencken: “For every complex problem, there is an answer that is clear, simple, and wrong.”
The Great Barrington Declaration
People are sometimes tempted by these false narratives, especially when they confirm what they want to believe. One of the worst of those false narratives was something called the Great Barrington Declaration. What that was, was a policy proposal written and promoted by three academics who had no real-world experience managing pandemics.
The people fell for those theories. It was based on some new ideas and concepts, a new theory called “natural herd immunity,” the idea that we could somehow protect the vulnerable from the less vulnerable, and the hope that coronavirus would be like measles, a one-and-done disease, where if you get the infection once, you wouldn’t get it again. Unfortunately, all three turned out to be either unworkable or incorrect.
Compounding that, some prominent physicians from Stanford and Johns Hopkins also backed the declaration, but these were physicians from the wrong fields, fields like neuroradiology and endocrine surgery. They didn’t have the right training. A way to explain this is, if you’re going to build a large school and you needed someone to wire the main electrical panel, would you have the painter, the tile guy, or the electrician? All three are in construction, but only one has the right expertise.
Not Following the Data
The same is true in healthcare. Some have the expertise; some don’t. Adding to the problem, they didn’t follow the data. They had bought into the theories too much so that when new data came in that didn’t back their theories, they wouldn’t change their minds, something summed up by the old adage, “In for a penny, in for the pound,” or what the psychologists call the “sunk cost fallacy.”
What did this look like?
If you Google the words “CDC excess deaths,” you’ll land on a website with this graph. What this is, the vertical blue lines, those are the number of people who died that week in the United States going back more than five years. The orange line is the average number of deaths that happened based on looking at death certificates going back decades. The red line is when significantly more deaths are happening than you’d expect. Every blue line that goes above that has a red plus sign above it.
You may have heard the false narrative, “Oh, those people are going to die anyway.” We knew how many people were going to, quote, “die anyway.” It was obvious within weeks there were far more people dying than were going to, quote, “die anyway.” You may have heard the false narrative that “COVID was no worse than the flu.”
COVID Misconceptions
Influenza typically kills 10 to 50,000 a year, and the last bad flu year was about four years ago, and I’ve labeled that to the left. That was about 40,000 deaths. It was obvious within weeks that coronavirus was far worse than a bad flu year. You might have heard a narrative that COVID was a seasonal virus and didn’t spread in the summer.
Some fell for that, especially in the south, and they took off their masks and got rid of precautions. And the summer wave that I’ve labeled there went through and killed over 100,000 Americans. Then the Great Barrington Declaration people said, “We’ve reached natural herd immunity based on those first two waves. Tell everybody the good news that we can go back to life as normal.”
And the alpha wave came through and killed over 200,000 Americans. And then they came back again and they said, “Well, maybe we jumped the gun last time. Now we’re at natural herd immunity.” And things were a little quiet for a while, but those of us who were following the data internationally could see the delta wave coming. Many still fell for the narrative. They didn’t get vaccinated. They didn’t take recommended treatments like Paxlovid, and the delta wave killed another 200,000 Americans.
And before the delta wave was even done, the Omicron wave was coming. You may have heard people claim that Omicron had evolved to be a milder virus, and some of them were even claiming it was, quote, “nature’s vaccine.” And people fell for the narrative, didn’t take their booster shots, didn’t take Paxlovid, and another 200,000 Americans died from the Omicron wave.
And then in the third year of the pandemic, people started claiming, “Oh, we’re in the endemic phase. We don’t have to worry anymore.” People who didn’t even know what “endemic” meant. And unfortunately, people didn’t get their boosters, didn’t take recommended treatments like Paxlovid, and close to 100,000 Americans died in the third year just from the Omicron subvariants.
So what went right? One of my pet peeves during the pandemic was people saying, “Who could have predicted something like this?” Well, actually, quite a few people had predicted something like this. Right here in Omaha, Nebraska, the dean of our College of Public Health, Ali Khan, wrote a book in 2016 titled “The Next Pandemic.” He discussed infections that he’d worked with in his career and the likelihood of a next pandemic, probably due to influenza or coronavirus.
The other expert I mentioned earlier, Dr. James Lawler, he was part of the team during the Bush administration that wrote a pandemic response plan on how we should respond to a pandemic like this.
Spreading Expertise
Unfortunately, many didn’t pull out those recommendations and didn’t read them and didn’t follow them. But thankfully, leaders like Drs. Khan and Lawler spread their ideas widely to anyone who would listen. It was Dr. Lawler’s presentation that tipped me off and led to our better decisions in Lincoln.
Another problem we had is we didn’t actually have a way to track pandemic data like this. The CDC had no centralized system. But a lot of volunteer journalists actually stepped up, and they started loading into a GitHub site every state’s infection rates down to the county level.
If during the pandemic you followed dashboards on Johns Hopkins, New York Times, or the Washington Post websites, that’s the data that they were pulling from. One of my colleagues, Ted Frazier, was able to access the site as well, and we created a Tableau visual and put it on our website for Nebraska. Within weeks, we had thousands of people checking those numbers.
We got a thank-you note from the middle of the state. Some people running a community were using it for contingency planning. They only had three people who could run the water plant, and if all three were sick at the same time, that community would have no clean drinking water. Another problem we had was with communications.
Best Volunteer Sources
One of my favorite volunteer sources was Dr. Katelyn Jetelina. She was an epidemiologist from the University of Texas. She started writing a newsletter for all her fellow faculty members that everybody started sharing widely, so she put it on a Facebook page and eventually on a blog site.
This was followed by tens of thousands of people across the country. She had a knack for creating good visuals, and she also wrote from the perspective of a young mother, which was really helpful with a lot of women struggling with what to do with their kids during the pandemic. It was one of the best sites I’ve followed, and I still follow it today. Some people stepped up, volunteered their time, and helped some of us lead to better decisions.
What did this look like? This is a map of the United States with the standardized death rates for coronavirus adjusted for health condition and age.
Metro Nebraska vs. Non-Metro Nebraska
You notice that Nebraska actually did better than those around us and far better than Arizona, which did the worst. Unfortunately, it wasn’t all of Nebraska. It was mostly metro Nebraska, Lincoln specifically, and to some extent Omaha. Non-metro Nebraska didn’t always follow the recommendations as well and had a mortality rate twice as high.
Arizona, which was fully into the Great Barrington Declaration, had a mortality rate three times as high. I’ve also put those original projections that Dr. Lawler made in March of 2020. You’ll notice if you followed the recommendations, you had numbers closer to his moderate rates, and if you ignored them, you’re in the severe. It turned out the expert was pretty accurate.
Colin Powell’s 40-70 Rule
So what next? I think one of the best lessons we can learn in a situation like this is Colin Powell’s 40-70 rule for tough decisions in the face of uncertainty. What the 40-70 rule is, is you wait for at least 40% of the information to come in so that you’re making a moderately informed decision and not shooting from the hip. You may have to make a decision before you have 70% of the information because time may be of the essence and you may miss a window of opportunity.
We saw that some people on one end of the political spectrum bought into the Great Barrington Declaration with far less than 40% of the information, and then paradoxically, when we had far better than 70% information, would not buy into masks, vaccines, and Paxlovid. On the other end of the political spectrum, we had people that closed schools on a timely basis but then failed to reopen their schools later on, especially on the coasts, leading to a lot more learning loss. For this 40-70 rule to work, we need to get four things right next time.
Four Things to Get Right Next Time
Number one, we need to acknowledge that our first theory is a working theory. Acknowledge what you know, acknowledge what you don’t know, and note what data is going to change your mind. When I used to teach family medicine residents, I used to tell them, “Don’t marry your first diagnosis.” Your first hunch might be right, but it might be wrong. As new information comes in, be honest with your patient about why you’re changing your mind, and they’ll appreciate it.
Second, we need to be able to follow the data. Unfortunately, a lot of the dashboards that were built are being taken down. We should build on and refine these dashboards so they’re ready to go next time.
Third, we need to know who the real experts are. Just being a governmental employee does not make you an expert. We need to make sure that people in key decision-making positions have the background in statistics and epidemiology to know what the data means, but just as important, what it doesn’t mean.
And last, we need to do a much better job of communications. We need to push out things that are vetted by experts in a non-partisan way so the public will accept it and have the right information. And we need to get it right, because next time might be coming sooner than you think. With eight billion people in this world, and modern airline travel, disease can spread from any continent in the world to your community in less than 48 hours.