Our coronavirus response revealed the limits of scientific modeling in policymaking. There are lessons for the Green New Deal.
In mid March, as the global economy closed for business and the frightful and deadly phase of America’s coronavirus pandemic began in earnest, I started a daily email update to a list of friends and colleagues. I had a background in public relations, and in health-care policymaking in particular, and I had hoped to cut through the noise of hyper-politicized and sensationalized news coverage and provide people in the right-of-center policy orbit with a digest of credible public-health news and analysis.
As we approach 200 days of the “15 Days to Stop the Spread,” it’s clear now how wrong I — and everyone else — was about COVID-19. The data we had weren’t wrong; our analysis of them was. Certainly, we had all hoped that by Easter, the pandemic would be under control. As the public drained our nation’s supply chain of all its hand sanitizer and disinfectant wipes, we discovered that surfaces weren’t really great hosts for the virus; saliva droplets serve as coronavirus’s preferred mode of transmission. And many prominent health officials around the globe expressed skepticism about masking, warning that the public lacked proper knowledge to hygienically wear them and arguing that homemade face coverings weren’t effective at protecting people. Now, it is illegal in many states to be indoors or in public without one.
After six grueling months of shared sacrifices, with America’s children and businesses bearing so much of the burden of “life as usual” interrupted, better days are on the horizon. With the introduction of new therapeutics, the warp-speed production of vaccinations, greater knowledge from health-care providers, and growing immunity, we have reason to be optimistic that the pandemic’s wrath is slowing and may soon be under control.
With breathing room to analyze how our country and others handled COVID-19, the scientific community, government leaders, and the public will have the opportunity to examine both the promise and the limitations of basing far-reaching public policy on empirically tenuous theories and models. The massive failures of epidemiological modeling, in particular, and the significant damage their unreliability inflicted on the global economy and health, should make us especially wary of other efforts to make sweeping policy changes on the backs of ambitious abstractions.
I’m talking of course about the climate-change forecasts that, to date, have failed to live up to the doomsday scenarios that their most ardent defenders forewarned.
Climate-change maximalists’ doomsaying assume that models published by groups such as the United Nations’ Intergovernmental Panel on Climate Change (IPCC) are valid, sound, and sensitive enough to account for changes in inputs. But with the coronavirus, we have discovered how blind faith in modeling can be exceedingly treacherous, as the epidemiological assumptions that governments across the globe relied on when making their decisions over the past several months have been proven wrong time and time again.
In particular, prominent models about hospitalization, R0 curves (the virus’s rate of reproduction, and case fatalities were dramatically revised multiple times, typically downgrading experts’ previous catastrophic projections. These failures demonstrate just how far-reaching the prejudices of scientists may be. While their motivations aren’t always political, it’s clear that their instincts are to forecast the worst possible outcome, even when the likelihood of it occurring is infinitesimal and relies on negative variables remaining unchanged or worsening. When questioned about their accuracy, defenders of traditional epidemiological models guiding COVID-19 policy say that their charts can only assume that current variables remain constant.
Meanwhile, climate models are, if anything, far more complex and sensitive to confounders than epidemiological ones. It’s therefore reasonable to doubt that they can truly reflect reality. Climate scientists readily admit that, as with coronavirus modeling, changes in inputs cause complicated and unpredictable feedback loops. With this in mind, how can their projections accurately forecast much of anything as it concerns the future temperature of our planet?
Unfortunately, the failures of epidemiological modeling for COVID-19 inflicted tremendous human and economic costs on the U.S. and, indeed, much of the world. From the foolishly dangerous nursing-home policy of Governor Andrew Cuomo (D., N.Y.) to the widespread joblessness caused by preemptively shutting down the economy in places that had yet to see significant coronavirus spikes, an incorrect understanding of this virus — made worse by experts’ wrong predictions — resulted in huge losses to families and businesses.
The real-world consequences of coronavirus-modeling fiascos should give pause to climate scientists. Still, they insist that we enact their most radical policy prescriptions to protect the planet. They remain unconcerned with the efficacy of such measures, their human cost, or the real extent of the dangers we face. Even as Americans, locked down during the pandemic, involuntarily enacted drastic cuts in carbon-producing activities, climate-change alarmists insist that we all do more to stave off a climate catastrophe.
Worse still, climate scientists are so dogged in achieving their political goals that they won’t be deterred by facts that negate their narrative. According to one influential study in Nature Climate Change, global carbon emissions are expected to decrease by 4 to 7 percent in 2020. This is the largest decrease on record since World War II. This should be cause for celebration, but the study’s authors argue that even this level of economic and human pain is not enough to forestall the calamitous future they predict.
“These dramatic measures . . . begin to approximate the emissions cuts the world would need to make every year for a decade in order to meet the goals of the 2015 Paris climate agreement,” the authors explain, citing a 2019 United Nations report calling for a 7.6 percent annual reduction in emissions to reduce global temperatures by 1.5 degrees Celsius by 2100. For climate-change extremists, coronavirus-spurred economic destruction resulting in widespread joblessness, drug abuse, and suicide are not enough to reduce our world’s climate footprint.
Americans made tremendous sacrifices this year, forgoing family vacations and church attendance to stay locked in their homes for more than four months now. Millions have lost their jobs, while others shuttered their small businesses. Still, left-wing talking heads and their activist followers have relentlessly harassed people who, in their view, have not fully embraced all the austere restrictions imposed — at times arbitrarily — on their communities. Americans who raise questions about the changing coronavirus protocols (and they have changed frequently and even daily at times) have been called selfish, accused of being complicit in death, and depicted as scientifically illiterate ignoramuses more concerned with their individual liberties than with protecting the elderly and immunocompromised.
These same experts — elected officials, scientists, community leaders — lost all credibility when they neglected their own social-distancing recommendations to join huge crowds and engage in civic activities that aligned with their ideological priorities. Such hypocrisy brings to mind the Davos gathering focused on climate change last year: Record numbers of private planes flew to Switzerland, carrying thousands of climate-conscious “influencers” who apparently were more concerned with luxury and convenience than with they were practicing what they preached.
Science, especially on matters as serious as public health and climate, shouldn’t be biased. Scientists have a responsibility to provide accurate information that helps us make the best possible decisions, and they should make revisions when new data conflict with existing recommendations or narratives. Unfortunately, we know that the realms of science and propaganda overlap all too often today.