People whose expertise has been questioned often respond in ways that further alienate the skeptics. A good illustration comes from Vanity Fair’s profile of Alex Berenson, a leading advocate of the view that lockdowns are too strict. Berenson was one of the first journalists to point out that the IHME model, on which so many states rely, drastically overestimated hospitalizations — even after multiple revisions, and even after taking the effect of lockdowns into account. Here is the response from Gregg Gonsalves, assistant professor of epidemiology at Yale School of Medicine, as quoted by Vanity Fair:
Models are not crystal balls. A modeler is giving you a range of potential outcomes. What he [Berenson] is doing is what a lot of people who don’t understand science do, they take the uncertainty built into a model and say, “Oh, well, it shows these people don’t know what they are talking about.” He is playing with scientific uncertainty in order to say, “See, I know what is right here.” He is somebody with a messianic complex. And to be clear, all of the models say this is going to be one of the worst epidemics we have ever faced.
Note the arrogant tone, the name-calling, and the argument from authority. This is how Professor Gonsalves intends to win over the skeptics? It’s not even clear what his point is. Yes, all predictive models have uncertainty, but it follows that the more uncertain the model, the less useful its predictions are. That should not be controversial.
Furthermore, IHME has underestimated its own uncertainty. Although I am a mere policy analyst, I do know that when IHME offers 95 percent prediction intervals, then the actual values are supposed to fall outside those intervals only 5 percent of the time. Applying that standard, critics investigated how the IHME model has performed on what should be one of its easiest tasks — predicting the number of deaths that will occur the very next day. They found that over a four-day period, the actual number of next-day deaths in each state fell outside the model’s 95 percent interval about two-thirds of the time. The failure is self-evident. One need not have a “messianic complex” to reject this model’s predictions.
Finally, even if “all of the models say this is going to be one of the worst epidemics,” that is hardly the end of the policy debate. It can be simultaneously true that we face a terrible epidemic and that full lockdowns are an overreaction. The real issue is how far our mitigation attempts can go before they are no longer worth the economic and social costs. Even people who “understand science” might conclude that those attempts have already gone too far.
Not to be outdone in the Vanity Fair piece, Dr. Joseph Vinetz chimes in on Berenson’s point that most hospitals are not overcrowded:
Why is this guy [Berenson] even getting any oxygen? People are under-using the system in terms of the regular catastrophic circumstances like heart attacks or strokes or elective procedures, so we don’t overwhelm the hospital system, so that’s why some medical workers are being laid off. The fear of getting COVID-19 [is] why people are not coming into the hospitals for other health issues and for elective surgeries. It’s to free up the facilities for COVID patients. He should stick to his novel writing. He should go back to school to learn some science.
Nothing from Dr. Vinetz’s quote conflicts with Berenson’s positions — most hospitals are far from overflowing, they have more flexibility than expected, and non-COVID-19 patients should be encouraged to return so that beds don’t go unused. Nevertheless, Dr. Vinetz felt the need to throw in not one, but two gratuitous insults.
Why react to skepticism with hostility rather than reason? Perhaps it’s just human nature. People become invested in their own work; they come to believe their critics are not just wrong but dangerous; and they end up lashing out in frustration. Still, if the goal is to bring skeptics to their side, this is exactly the wrong way to do it.