Computer models compiled by scientists, statisticians and public health experts to predict the number of deaths resulting from COVID-19 have been drastically scaled back this past week. This is hopeful news, but has wider implications. There also should be a serious look-back, given the wildly inflated early predictions of numbers of deaths in the United States.

Computer models are only as good as the assumptions built into them. If the inputs are faulty, the predictions will have shown to be flawed based on real life outcomes. This is playing out with the coronavirus models, and wreacking economic havoc worldwide. This modeling problem has ample precedent.

Flawed computer models have long been rampant in predicting planetary global warming for at least the last 30 years, even as they continue to influence public policy. Perhaps the most famous falsehood was the “hockey stick” prediction of rapid warming of the Earth beginning in the late 19th century after centuries in which the average global temperature was shown—erroneously—to be flat-lined, thereby ignoring prior warming periods.

Demonstrably false climate predictions by the biggest charlatan of our time, former Vice President Al Gore, alone could fill a hard drive, and have regularly been documented by CFACT (e.g., here and here).  The classic response from climate alarmists following a prediction shown to be wrong is to move the goalposts.

Global warming predictions then and now have been so flawed, the label itself has been renamed to “climate change,” which was clever since climate always is changing, so the drumbeat goes on. Unrecognized by man-made global warming proponents is that changes to climate are influenced by a variety of natural factors and always will be, no matter how many trillions of dollars are spent on a “Green New Deal.” Accordingly, it is folly to upend the economy and livelihoods for pretentious climate models.

In a much more compressed timespan, computer model predictions for the number of deaths from COVID-19 are now showing the death toll to be equivalent of a bad flu season rather than the six-figure or seven-figure projections made just days and weeks earlier.

The White House Coronavirus Task Force has been relying on the COVID-19 model produced by the University of Washington (State) Institute for Health Metrics and Evaluation. In just one week, from April 2nd, the Institute reduced the number of projected deaths from the virus from approximately 93,500 to 60,000 – an astounding 36 percent decline.

As many as 60,000 deaths from COVID-19, or related to this virus, is still substantial and tragic. However, if that number pans out in the months ahead, it would be lower than the 61,000 deaths in America from influenza in the 2017-18 period.

The Institute’s computer model also has quickly scaled back the projected number of hospital beds, intensive care unit beds and ventilators. During the first week in April, projections for needed hospital beds precipitously dropped from about 262,000 to 95,000.

The lower projected number of deaths is due in part to social distancing to the point of shutting down the “non-essential” areas of the private economy; otherwise, the death rate from the more contagious COVID-19 likely would have exceeded a bad flu season. Thousands of businesses have closed and 17 million people are now unemployed. The once bustling streets of New York, New Orleans, Los Angeles and countless other places are near empty.

There is more going on with the declining death rate predictions from coronavirus than social distancing – especially since the recent virus computer model predictions already assumed distancing measures. Increasingly, the computer model assumptions are being seriously challenged, along with the necessity of shutting down so much of the economy to the detriment of millions of Americans.

One reason for the sharp drop of projected deaths from coronavirus is that many Americans already may have had the virus long before the public health emergency was declared in March, particularly in California and Washington State, without being reported as such. Outbreaks of influenza were reported in California around the New Year, which likely spread from the thousands of Chinese traveling daily into the state throughout the winter, which subsequently provided residents some degree of “herd immunity” to COVID-19.

The rapid decline in projected COVID-19 deaths does not mean U.S. residents are out of the woods. New York City, Detroit and other hot spots remain in crisis. But the diminishing public health impact of the coronavirus heightens the need for the federal government and states to re-open the private economy sooner rather than later. Doing so would preclude further economic catastrophe, while maintaining social distancing measures and protecting vulnerable populations.


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  • Peter Murphy

    Peter Murphy is Senior Fellow at CFACT. He has researched and advocated for a variety of policy issues, including education reform and fiscal policy, both in the non-profit sector and in government in the administration of former New York Governor George Pataki. He previously wrote and edited The Chalkboard weblog for the NY Charter Schools Association, and has been published in numerous media outlets, including The Hill, New York Post, Washington Times and the Wall Street Journal. Twitter: @PeterMurphy26 Website: