It's never been obvious just what "the science" is, or why anyone would speak of science as a single truth, but the role it plays is quite clear. It's the modern equivalent of the Oracle of Delphi, that mysterious font of guidance that Greek leaders consulted during wars and other crises. However foolish or sensible the advice may be, the oracle gives leaders an excuse to duck responsibility for decisions — and their consequences.
Why, for instance, was the upstate New York economy shut down for more than two months, despite the small number of cases of Covid-19 in rural counties? Why, as some offices and barber shops and other upstate businesses were finally about to reopen at the end of May, did Governor Andrew Cuomo infuriate local officials by suddenly announcing that this decision could not be made by them — or even by himself?
"We'll give the experts all the data," he explained. "And if they say we should move forward, we move forward." Everyone's fate now rests with the new oracles.
By "the experts," Cuomo meant the consultants brought in to oversee the state's reopening: an epidemiologist from the University of Minnesota and a statistician from Imperial College in London. When he introduced them at a press conference in mid-May, he explained that reopening was "not a political exercise."
"This is about facts and science and data," he said. "It's math and there's a liberation in that."
It may be liberating for politicians to blame economic devastation on someone else, but it's ridiculous to pretend that epidemiologists and statisticians have magical formulae for determining the costs and benefits of the shutdown. They can estimate how quickly the virus is spreading, but they don't know exactly what effect the various lockdown measures have on viral spread, let alone on people's lives and livelihoods.
The "metrics" now ruling New York's policy sound reassuringly precise, like the requirement that a region must have 30 percent of its hospital beds free in order to enter the next phase of the reopening — as upstate counties were finally allowed to do on May 29, once the oracles had reviewed the data. New York City did not qualify then because only 28 percent of its hospital beds were free.
How do the experts know that 28 percent is too little and 30 percent is enough? They don't. They've made a guess. It's an educated guess, because it's informed by their profession, but it's also biased by their profession. Their careers depend on stopping the spread of the virus, not on making sure that children can learn or adults can work.
So when these experts ponder trade-offs, they err on the side of their profession. It would be much easier for restaurants and other businesses to operate if customers had to stay just three feet apart, in line with the World Health Organization's recommendation of one-meter social distancing. But public-health authorities would rather play it safe by doubling the distance. They don't know how many lives this will save, and they certainly don't know how many businesses will be bankrupted by it. That's not their job.
However scientific they try to be, they're swayed by some of the same irrational biases and perverse incentives that afflict politicians and journalists. In creating their models and presenting their data, they're rewarded for skewing negative, because scary predictions will bring them more attention, more funding, and more power. Their worst-case scenario may be utterly implausible, but it's newsworthy, and it guarantees that no one will blame them for not anticipating every possible death from the virus.
The side effects of the lockdowns across America may already be deadlier than the pandemic itself, as Scott Atlas of the Hoover Institution and other researchers have concluded. They estimate that the consequences of unemployment, missed doctors' visits, and other factors during the two-month lockdowns will lead to so many extra deaths that Americans will lose a cumulative 1.5 million years of life, nearly twice the total lost so far to Covid-19. Those deaths don't show up in the media's daily Covid-19 tally, so they don't figure into the "science and data" guiding Cuomo and other politicians.
Cuomo prefers to rely on his chosen consultants, and he doesn't seem troubled by their limitations — or by their track record. One, Samir Bhatt, is a member of the Covid-19 Response team at Imperial College, which produced the much-quoted (and much-criticized) model projecting, under its worst-case scenario, that more than 2 million Americans could die from the virus. That projection was never realistic, and its chief author had made wild overestimates during previous pandemics, but Cuomo and others relied on the Imperial College model, among others, to guide their decisions.
In March, Cuomo looked at the numbers and warned that New York State would soon need 110,000 hospital beds for Covid patients at the pandemic's peak — more than twice the available capacity. In reality, the number of beds occupied at the peak, in April, turned out to be below 20,000, less than half of capacity. But state officials were so afraid of running short that they ordered hospitals to free up beds by transferring Covid patients to nursing homes. To avert a projected disaster, they created a real one by allowing the virus to spread rapidly in nursing homes, killing thousands of people.
Yet Cuomo's faith in the experts remained unshaken, as he explained at the recent press conference introducing the state's consultants. He conceded that the computer modeling hadn't been "100 percent accurate" — quite an understatement, considering that the projected peak of 110,000 hospitalized Covid patients was off by more than 90,000. But never mind. We must continue to entrust our fate to the new oracles.
"At a time of such division in politics and elections and all this garbage," Cuomo said, "this is an exercise in science and math." It does involve science and math, but it's also an exercise in passing the buck.
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