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July 23, 2020 Reading Time: 4 minutes

Most of the United States entered into a tepid reopening from the COVID lockdowns in mid-May. Although the reopening process has advanced through an interminable succession of bureaucratic phases with most of the country remaining under varying degrees of restriction as of mid-July, the reopening process has remained under sustained criticism from the media and a segment of the epidemiology profession since the moment it started.

Back on May 24th the epidemiology team at Imperial College London (ICL) published a study that expanded on their now-notorious COVID-19 model. Donald Trump and UK Prime Minister Boris Johnson both cited the apocalyptic projections of this report and its lead author Neil Ferguson back in March to justify their decisions to lock everything down.

The follow-up ICL paper from May attempted to model the effects of reopening in 5 US states: New York, Massachusetts, California, Washington, and Florida. In all five cases, the Imperial College team predicted an aggressive rebound of COVID-19 fatalities under even the most modest relaxation of stay-at-home policies and practices.

To illustrate this pattern, the ICL team presented three scenarios based on the expected change in human mobility in each state after the lifting of lockdown restrictions. The first scenario kept the lockdowns in place, assuming that mobility would remain constant at its severely reduced post-lockdown rate. Under the other two scenarios, the ICL team assumed a 20% and 40% increase of mobility corresponding with the reopening process.

In both of these reopening scenarios, the model depicted a catastrophic rebound of COVID-19 fatalities. As the ICL team itself put it, their model “illustrate[s] the potential consequences of increasing mobility across the general population: in almost all cases, after 8 weeks, a 40% return to baseline [mobility] leads to an epidemic larger than the current wave.” Media reports at the time touted the study’s dire warnings as reasons to stall the reopening process – even at its sluggish pace of recurring 2-week delays and extensions.

More than 8 weeks have passed since the publication of the ICL team’s warnings against reopening, meaning we can now see how their model performed.

As with other examples of ICL COVID modeling, their attempt to predict the effects of a US reopening can only be described as an embarrassing scientific failure.

The image below shows the three modeled scenarios from May, as depicted in the ICL report for the five states under consideration. Note that even under the “constant mobility” scenario of remaining under lockdown, their model predicted an increase in COVID deaths for every state except New York, which had already peaked. Under the reopening scenarios where mobility increased 20% and 40% respectively from its lockdown state, all five states were predicted to surge into apocalyptic territory by the middle of July. Under the 40% scenario, this even entailed upper boundaries of more than 4,000 deaths per day (the bands represent the 95% confidence interval). Massachusetts and New York, two of the hardest-hit states from the first wave back in March and April, would easily match or exceed their previous COVID-19 daily death records.

To see how these predictions held up, I indicated the daily death totals for each state for July 20th with a small red dot on the graphs above. As you can see, the actual totals are below the ICL model’s predictions in every scenario. In Massachusetts, the current daily death totals are even falling below the lower boundary of the ICL model’s projections for both its 20% and 40% mobility increase scenarios.

Coronavirus cases and deaths have spiked in two of the modeled states, Florida and California. As of the week of July 20th, both are averaging between roughly 100 and 150 deaths per day. Yet even with this “second wave” spike, Florida and California are only showing about one-tenth of the projected deaths that the Imperial College modelers predicted for this time back in May.

In New York, Washington, and Massachusetts, daily death counts have dropped to the low double-digits and remain a tiny fraction of the ICL predictions for mid-July.

Although all five states remain under COVID-19 restrictions of varying degrees, even partial reopening has increased mobility at levels that match or exceed the ICL’s modeled scenarios. The main Google mobility indicators for Massachusetts are depicted below for reference, and show a clear upward trend since the time of the ICL predictions in mid-May.

These patterns confirm that US mobility trends are increasing as lockdown restrictions are slowly lifted, and as society moves toward reopening. They therefore show that the ICL model correctly anticipated one effect of relaxing the lockdowns.

At the same time though, the ICL model severely overstated the projected mortality associated with reopening in all five states. Actual data do not map onto any of their scenarios, including the broadest of the three predictions for reopening. States that peaked back in March and April show no signs of a resurgence, let alone the predicted resurgence that would surpass the first wave. And states that are undergoing later surges are still well below the ICL team’s predictions – so far below that they barely even register on the graphs.

As with other predictions from the ICL team, the May paper likely faltered due to a fundamental error in its underlying code. These flawed ICL models begin with an unproven assumption, namely that lockdowns are effective at combating the coronavirus. The models are therefore automatically calibrated to produce a sharp spike in deaths after the removal of lockdowns or any move toward reopening. 

As we’re now seeing in actual data however, that assumption is grossly exaggerated. As a result, the predictive ability of Imperial College’s COVID epidemiology modeling amounts to little more than an exercise in statistical astrology.

Phillip W. Magness

Phil Magness

Phillip W. Magness is Senior Research Faculty and Director of Research and Education at the American Institute for Economic Research. He is also a Research Fellow at the Independent Institute. He holds a PhD and MPP from George Mason University’s School of Public Policy, and a BA from the University of St. Thomas (Houston). Prior to joining AIER, Dr. Magness spent over a decade teaching public policy, economics, and international trade at institutions including American University, George Mason University, and Berry College. Magness’s work encompasses the economic history of the United States and Atlantic world, with specializations in the economic dimensions of slavery and racial discrimination, the history of taxation, and measurements of economic inequality over time. He also maintains an active research interest in higher education policy and the history of economic thought. In addition to his scholarship, Magness’s popular writings have appeared in numerous venues including the Wall Street Journal, the New York Times, Newsweek, Politico, Reason, National Review, and the Chronicle of Higher Education.

Selected Publications

“How pronounced is the U-curve? Revisiting income inequality in the United States, 1917-1960” Co-authored with Vincent Geloso, Philip Schlosser, and John Moore. The Economic Journal (March 2022) “The Great Overestimation: Tax Data and Inequality Measurements in the United States, 1913-1943.” Co-authored with Vincent Geloso. Economic Inquiry (April 2020). “The anti-discriminatory tradition in Virginia school public choice theory.” Public Choice. James M. Buchanan Centennial Issue. (March 2020). “John Maynard Keynes, H.G. Wells, and a Problematic Utopia.” Co-authored with James Harrigan. History of Political Economy (Spring 2020) “Detecting Historical Inequality Patterns: A Replication of Thomas Piketty’s Wealth Concentration Estimates for the United Kingdom.” Social Science Quarterly (Summer 2019) “James M. Buchanan and the Political Economy of Desegregation,” Co-authored with Art Carden and Vincent Geloso. Southern Economic Journal (January 2019) “Lincoln’s Swing State Strategy: Tariff Surrogates and the Pennsylvania Election of 1860” Pennsylvania Magazine of History and Biography, (January 2019) “Are Adjuncts Exploited?: Some Grounds for Skepticism.” Co-authored with Jason Brennan. Journal of Business Ethics. (Spring 2017). “Estimating the Cost of Adjunct Justice: A Case Study in University Business Ethics.” Co-authored with Jason Brennan. Journal of Business Ethics. (January, 2016) “The American System and the Political Economy of Black Colonization.” Journal of the History of Economic Thought, (June 2015). “The British Honduras Colony: Black Emigrationist Support for Colonization in the Lincoln Presidency.” Slavery & Abolition, 34-1 (March 2013) “Morrill and the Missing Industries: Strategic Lobbying Behavior and the Tariff of 1861.” Journal of the Early Republic, 29 (Summer 2009).  

Books by Phillip W. Magness

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