What if the ‘sky-is-falling’ coronavirus models are wrong?
As Carl Cannon, Washington bureau chief and executive editor of RealClearPolitics, recently wrote, political bias and social “wokeness” infect everything. From news, sports, weather and entertainment to the food we eat, everything is politicized — even, sadly but not surprisingly, science and medicine and even something as frightening and life-disrupting as the COVID-19 coronavirus, as we saw this past week when the Senate and then the House fought over the terms of a relief package for a nation in virtual lockdown.
With regard to the virus itself, however, the only things that can help us deal with it effectively are facts, truths and evidence, which, unfortunately, seem to be in as short supply as ventilators, face masks and other emergency material.
Indeed, much of the problem in determining the best responses — medically, socially, financially and otherwise — is that we still don’t know enough about COVID-19 beyond its apparent high mortality rate for older people, especially those with underlying medical conditions. Yet is there another side to the “sky-is-falling” models that are driving much of our responses? Are we not allowed to explore the arguments from acclaimed experts in the field without being accused of being partisan hacks or science deniers?
Logic and simple survival would seem to suggest that we all would celebrate if the world-is-ending models were proved to be dramatically wrong. And it seems that a few brave souls indeed are questioning some of the conventional wisdom.
In an article in the Los Angeles Times, Nobel laureate and Stanford biophysicist Michael Levitt throws a hope-inducing bucket of cold water on the nonstop alarmism being repeated by some in the media and in public office. Levitt says unnecessary panic has been created by focusing on the relentless increase in the cumulative number of cases and spotlighting celebrities who contract the virus. “What we need is to control the panic,” he writes. “We’re going to be fine.”
Levitt studied the number of COVID-19 cases worldwide in January and correctly calculated that China would get through the worst of its outbreak long before many health experts predicted it would. He now predicts a similar outcome for the United States and the rest of the world.
As we are reminded constantly by some media, many health experts predict that months or even more than a year of social distancing will be necessary and that the virus will cause millions of deaths. Levitt, on the other hand, states that his data do not support that doom-and-gloom outcome — just the opposite, in fact.
Months ago, before the pandemic sky fell around us, many people rightfully doubted or scoffed at computer models that predicted, say, where a hurricane would make landfall or who was guaranteed to win a presidential election. The people of Florida and the supporters of Hillary Clinton might happily tell the experts behind those predictions what they should do with their computer models.
It was a world-is-ending projection two weeks ago of as many as 500,000 dead in the United Kingdom and as many as 2.2 million dead in the United States, offered up by professor Neil Ferguson and his team at Imperial College London, that fired up the media’s panic machine. However, overlooked in the hyper-reaction was that this was an unlikely worst-case scenario based on nothing being done to stop the virus’s spread. And Ferguson (who reportedly contracted the virus himself) subsequently cut the projected number of British deaths in half as the government there ramped up its response — and has since drastically scaled it back yet again, to fewer than 20,000 deaths in Britain. As the National Review correctly points out, “Models like this will always turn out to be wrong in some way or other, because they rely on very strong assumptions about aspects of the disease we haven’t thoroughly studied yet. If nothing else, the original Imperial model will be obsolete soon.”
In the 1960s, during the glory days of NASA, trailblazing astronauts said of faulty predictions from human-programmed computers, “Garbage in, garbage out.” Computer-generated models and predictions may have their place but, when dealing with a pandemic that shuts down the globe, nothing substitutes for firsthand analysis utilizing patients in affected areas.
That is the point of another Stanford professor of medicine and epidemiology, John Ioannidis. In an article for Stat, Ioannidis breaks down why our governments are making decisions without reliable data or based upon flawed models.
The Hoover Institution’s Richard Epstein also waves a flag of caution regarding the COVID-19 dashboards that many news networks and online sites now prominently feature. Epstein’s analysis shows that COVID-19 deaths in the U.S. and worldwide will be dramatically fewer than many have predicted — possibly even fewer than the Hong Kong flu of 1968, the swine flu pandemic of 2009-2010 or seasonal influenza, which can claim hundreds of lives a day.
What if Levitt, Ioannidis and Epstein are correct? Could the COVID-19 pandemic end more quickly than anticipated or result in dramatically fewer deaths than have been predicted?
Let’s hope and pray that these three and the other pragmatic analysts now joining them are indeed correct about the outcome of all this, particularly because the draconian measures now in place could create another health catastrophe if lost jobs and bankruptcies lead to poverty, hopelessness and increased suicides.
Whatever the correct projections turn out to be, tens of thousands of people are likely to die, and millions more are paying an unimaginable price. Politics and partisanship should play no role in this — only truth and indisputable, real evidence.
Douglas MacKinnon, a political and communications consultant, was a writer in the White House for Presidents Ronald Reagan and George H.W. Bush, and former special assistant for policy and communications at the Pentagon during the last three years of the Bush administration. He is the author of “The Forty Days: A Vision of Christ’s Lost Weeks.”
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