Beginning in late February, government officials and the press began to predict a massive outbreak of a contagious disease known as COVID-19 in the United States. Using math models, they were convinced that anywhere between 100,000 to 200,000 deaths would occur.
The governor of California even went so far as to say 25.5 million Californians might contract the disease. As of mid-April, there were a total of 26,182 positive cases in California.
This set in motion a series of decisions that closed almost all commercial enterprises and denied millions of people their constitutional rights of freedom of movement and assembly.
From The Wall Street Journal on April 9: “The good news on lower expected virus mortality arrived at Wednesday’s White House coronavirus task force briefing. Here’s an excerpt from the official transcript:
“Question: Last week, your top experts were saying that we should expect 100,000 to 240,000 deaths in this country. You’ve been talking about how it looks like maybe things are plateauing. Are these numbers now being revised downward? I know you don’t want people to stop social distancing and that sort of thing, but what can you tell us about the numbers? Are they being revised down?”
President Donald Trump deferred to Dr. Deborah Birx who said: “I know many of you are watching the Act Now model and the IHME model from … and they have consistently decreased the number, the mortality from over almost 90,000 or 86,000, down to 81,000 and now down to 61,000. That is modeled on what America is doing. That’s what’s happening.”
So, how could our political leaders have gotten it so wrong? I can’t excuse the media reporting; they relied on and dramatized the information they were fed instead of seeking out facts.
Managing risk is a tricky business. First you must establish what could cause loss of life, serious injury, or a significant monetary loss. Then you must determine what measures are necessary to reduce or totally mitigate the risk. Then you must make recommendations based on several options including a “no action” option.
I say that this is “tricky business” because how you establish the severity of action or inaction is based on reliable information. The goal is always minimize, monitor, and control the probability or impact.
So, how does this relate to early predictions of 100,000 to 240,000 COVID-19 deaths in this country?
Reliable computer models are based on the information that forms the basis of the predicted outcome. In the case of the COVID-19 data, it appears that researchers were relying of unverifiable information being fed to them from China. This produced an enormous and unacceptable risk factor.
As more models were being produced by different research organizations, their results differed dramatically.
The decision makers at all levels of government were faced with a serious dilemma: How do we plan for a catastrophe of the magnitude being predicted by the scientific/medical community? Their response was a series of actions that resulted an unheard-of loss of civil liberties in modern memory.
Then, as actual data from reliable and verifiable sources in the United States, Canada, and northern Europe began to be plugged into the models, the predicted risk was significantly reduced.
In matters like this, hindsight is 20/20. The policy in place to manage the assumed risk was to “flatten the curve,” however some were suggesting “net zero”—meaning no new cases or deaths—was the safe way to go.
Here are some facts from the Centers for Disease Control: In 2019 there were 2.8 fatalities nationwide; that means that means that an average of 7,903 people passed away each day from a variety of causes. For example, an average of 1,773 passed away each day from heart disease; 1,641 from cancer; and 465 from accidents.
Recently the director of the Santa Barbara County Public Health Department was suggesting that the current restrictions may need to remain in place for several more months.
A couple of days later, Dr. Henning Ansorg, county public health officer, said during a daily press briefing, “We continue to see an increase in confirmed cases across the county of Santa Barbara, however, the increase is following a linear pathway and has not evolved into an exponential pattern [characterized by or being an extremely rapid increase as in size or extent], which we initially were worried about.”
That sounds like exactly what health officials were initially hoping for—a “flattening of the curve” and should signal a return to normal. But will it?
Gov. Gavin Newsom recently laid out his administration’s benchmarks for reopening the state; they appear designed to achieve zero risk. Considering the testing needed to achieve development of “therapeutics to meet the demand” and the “ability to prevent infection in people who are at risk,” these goals appear to be unachievable in the foreseeable future.
In the meantime, we are left with the aftermath produced by early predictive models based on unverified information. Politicians, who were responsible for creating the policies that resulted in this chaos, are faced with even more difficult challenges associated with admitting they made decisions based on a faulty risk analysis.
Will they be willing to give up these new powers? Based on Gov. Newsom’s plan to reopen the state, it doesn’t look like it.
Ron Fink writes to the Sun from Lompoc. Send your thoughts, comments, and opinionated letters to letters@santamariasun.com.
This article appears in Apr 23-30, 2020.