Educated elites bemoaning the return to power of Donald Trump would do well to ask how they contributed to this outcome. Trust in institutions is down, perhaps especially for those institutions charged with helping the public discern the truth. Observers often blame the “information ecosystem”—in particular, the internet—but elites have also undermined public faith by allowing science and the wider pursuit of truth to be politicized. The incoming administration presents the opportunity for a reset.
To that end, Trump should nominate Stanford University’s Dr. Jay Bhattacharya to lead the National Institutes of Health. Bhattacharya exemplifies qualities that were lacking in our nation’s scientific leadership during the pandemic. The ostracism and condemnation he faced for his dissenting views provides a vivid illustration of elite failures to live up to their own deepest values.
In the early months of the pandemic, deep uncertainty prevailed. We knew people were dying in frightening numbers in China’s Hubei Province, the north of Italy, and then in New York City. Early projections of mortality rates from the World Health Organization and mathematical modelers in Britain were alarming. The World Health Organization announced that the case fatality rate—the percentage of deaths among known cases—was 3.4 percent. But we also knew that early projections of morbidity in pandemics tend to be far too high, because at that early stage, the “cases” we see are people showing up sick at hospitals and clinics. That was the situation in February and March 2020. We didn’t know how many people had contracted the novel coronavirus with mild illness or without getting sick.
“That was just the tip of the iceberg of Covid uncertainty.”
That was just the tip of the iceberg of Covid uncertainty. We didn’t know how or by whom the disease was principally transmitted, how far the disease had spread, or what long-term health consequences it might entail.
Very early in the pandemic, Bhattacharya set out to gather vital information and to question what had too soon become settled assumptions. First, he joined with colleagues to ascertain what is known as “seroprevalence,” meaning to find out how many people in the population had been exposed to the novel coronavirus. Such studies are essential to gauging the real danger of a novel pathogen and discerning which segments of the population are most vulnerable. Bhattacharya, his collaborators, and others working on this problem quickly found that the infection fatality rate—the percentage of deaths among all who had been infected by the virus—was much lower than the early dire projections, and that risk of death was concentrated among the elderly.
In addition, Bhattacharya and other colleagues drew attention to the tremendous collateral damage of trying to stop the spread of the virus by locking down societies. He argued that most such measures were unnecessary, as most of the population was at low risk of serious illness. In October 2020, he co-authored a very brief document, the Great Barrington Declaration. He has called it the least original thing he has ever written, given how closely it hewed to pre-Covid public-health precepts.
He and his co-authors—Martin Kulldorff and Sunetra Gupta, professors at Harvard and Oxford, respectively—argued for a strategy of “focused protection” concentrating precautions on the vulnerable parts of the population, while letting most others go about their business with reasonable but non-draconian restrictions in place. Even though by fall 2020, evidence had accumulated that non-pharmaceutical interventions were enormously costly and of doubtful effectiveness, very few experts were willing to publicly question the consensus.
The Great Barrington Declaration should have been treated as a serious attempt by distinguished scholars to interrogate assumptions and debate the costs and benefits of a highly questionable policy consensus resting on shaky evidence. Instead, leading public-health officials—led by the then-director of the National Institutes of Health, Francis Collins—dismissed Bhattacharya and his co-authors as “fringe epidemiologists.”
The attempt to suppress discussion of the trade-offs entailed by pandemic-containment measures was another indication of the orthodoxy that had set in by the fall of 2020. Why didn’t the NIH and the Centers for Disease Control and Prevention launch seroprevalence studies in March of that year, as Bhattacharya and his colleagues had? Why didn’t the NIH commission quality studies to find out more about whether masks work to slow viral transmission in the population, or whether school closures were really reducing deaths and serious illness from the virus? Why didn’t public-health officials attend to the obvious fact that business closures, school lockdowns, and disruptions to the normal functioning of societies around the world would cause tremendous collateral damage?
Rather than acknowledge how little they knew, public-health leaders too often doubled down and insisted that they already had the answers. The mantra was “follow the science”: a slogan that often seemed to defy the basic scientific—and liberal—imperative to respect criticism, tolerate dissenters, and be open to revising one’s views. The result was an insistence on poorly justified policies and a series of bewildering flip-flops in public-health messaging on matters like masking, airborne transmission, the lab-leak hypothesis, and whether vaccines prevent infection. A decline of trust in health agencies was an inevitable consequence.
Everyone is fallible. In March 2020 Bhattacharya and another Stanford health-policy professor, Eran Bendavid, speculated in a Wall Street Journal op-ed that Covid might turn out to cause fewer deaths than a typical seasonal flu. It was a reasonable warning, given that other novel pathogens initially perceived as having pandemic potential, such as 2009’s H1N1 virus, had turned out to be less dangerous than seasonal flu. In the case of Covid, however, the suggestion proved far too optimistic. Nevertheless, their “bottom line” was clear and correct: Determining the true infection rate in the United States was vital, because “universal quarantine may not be worth the costs it imposes on the economy, community and individual mental and physical health.”
If the country had had more scientific leaders like Dr. Jay Bhattacharya—and more who were willing to listen to him—our policymaking could have been based more on evidence and less on hubris. During the pandemic democracy’s “truth-seeking” institutions were infected by politics, partisanship, and dogmatism. What we need now is a strong dose of fresh thinking and institutional reform from experts prepared to challenge the reigning consensus and renew our commitment to the basic values of science and liberalism.