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Thursday, Jun 30, 2022

Doti on COVID-19 Data

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I love teaching statistics. The basic principle that undergirds this remarkable science is the normal curve. Teaching how the normal curve explains why the mean of all the sample means equals the population mean fills with joy. The beauty and power of the normal curve is indeed a wonder to behold. It’s even inspired me to turn wood bowls to emulate the graceful lines of a normal curve. (see photo)

Doti Bowl #69

A statistician by the name of William Farr was similarly inspired by the normal curve. While that inspiration didn’t lead to the creation of a Farr Bowl, it did lead to Farr’s Law. That law was used by Farr in 1840 to show how a smallpox epidemic followed a bell-shaped or symmetrical pattern. Since then, this pattern has been used to explain the infection rate of other diseases, including most strains of flu that rise in the fall, peak in the winter, and decline in the spring.

In a column that I wrote in this Business Journal last week, I argued that the number of new COVID-19 cases would not follow the geometric increases projected by Governor Newsom. That argument has been supported by recent data that show the number of new COVID-19 cases has fallen far short of his projections.

The daily rate of new COVID-19 cases in California has recently hit 1,371—not the 7,100 level implicit in the Governor’s projection. More dramatically, Gov. Newsom’s call for an Armageddon-like geometric increase to 23,000 by next week seems ludicrous in light of daily rates that hovered in a narrow range of 1,029 to 1,372 over the last week. (see Chart 1)

Although I’m not an epidemiologist, I do believe that similar to other flu strains, the incidence of COVID-19 will be consistent with Farr’s Law and follow my beloved normal curve.

While it may be too early to conclude that the number of new COVID-19 infections has peaked or may even be on the downside slope of a normal curve, the data points in that direction. Chart 2 shows a three-day moving average of new COVID-19 cases in California overlain by a normal curve.

This chart points to COVID-19 rising over a three-week period, peaking in early April and then dropping to less than 200 new daily cases in about three weeks towards the end of this month.

While I know an ending of this year’s COVID-19 season so soon may seem improbable, the rise and subsequent fall of new COVID-19 infections in China followed very similar patterns. (see Trends and Prediction in the Daily Incidence of Novel Coronavirus Infection in China, Hubei Province, and Wuhan City: An Application of Farr (sic) Law by Jie Xu et al in MedRxiv.)

If the actual COVID-19 number of new infection follows the normal curve as shown in Chart 2, the total number of infections in California would hit about 35,000 cases—not the 25 million projected by Gov. Newsom.

While it’s certainly possible that the 35,000 total case count may be low, I believe there is sufficient evidence to suggest that plans need to be put into place to restart the California economy post haste. In many respects, after all the human costs of lost payrolls and businesses, restarting the state’s economy will present even more challenges than shutting down.

Thankfully, free-market forces will do most of the work. But rational public policy initiatives at the state level will help grease the wheels.

Jim Doti is president emeritus and professor of economics at Chapman University.

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