Stephen McKeever


There are growing suggestions emerging from some quarters, including the White House, that the current social distancing measures that are being urged across the United States are overkill, and that more people will die because of the economic and social impact than will die from COVID-19. To support this view, it is claimed that more people have died from seasonal flu in the U.S. than have died from COVID-19.

In the 2018-2019 flu season, the CDC estimates that 61,200 people died of seasonal flu and 42.9 million people were infected, a fatality rate of 0.14%. The fatality rate for COVID-19 is yet to be defined, but as more and more data are generated, the fatality rate seems to be hovering around 4.5%.

If we took no more precautions about COVID-19 than we do about seasonal flu, and if the infection rates were about the same (42.9 million infected) this would mean that approximately 2 million people would die from COVID-19 in the U.S. alone.

However, COVID-19 is a much more infectious disease than seasonal flu and there is no vaccine for COVID-19. (There is no “COVID shot” in the same way that there is a “flu shot.”)

Therefore, there is every reason to believe the number of infections would be much higher than flu infections, and the 2 million COVID-19 deaths is likely to be a lower limit.

The only reason deaths from flu are larger than deaths for COVID-19 currently is because flu arrived in the U.S. many months ago (October) whereas COVID-19 arrived only recently (late February). Also, it is important to remember that the 4.5% fatality rate is averaged over the whole population. For those 70-80 years old, the rate is almost 10% and for those over 80 the rate is 18%.

Infectious diseases spread “exponentially.” This mathematical term means that the rate of infection is proportional to the number of people affected.

On March 21, 53 people were officially infected in Oklahoma. This means that the rate of infection at that time was proportional to 53. The following day the number had increased to 67, meaning that the rate of infection just one day later had now risen by about 25%, meaning that the on the next day the infection number could be predicted to be more than 80. It was 81.

If this trend continues, and if conditions stay the same, by the end of the month (only a few days away) the estimated number of infected people in Oklahoma will be considerably more than 500.

The current conditions in Oklahoma indicate that for every approximately three people infected, one new person is infected, every day.

Similar considerations nationally predict that, by the end of the month, the U.S. will see well over 300,000 people infected, assuming conditions remain the same.

However, there is hope that conditions will not remain the same. Since the infection has an incubation period of about one week (that is it is about one week after infection before symptoms are seen) the current conditions are affected by how things were more than a week ago.

There has been considerable social distancing taking place since then and so the rate of infection should fall below the current 1 infected person for every 3 infected. Even a small reduction in the number will see a drastic reduction in the projected number of infected people. However, if the opposite occurs, if social distancing restrictions are eased, the infection numbers will increase dramatically.

For example, a modest increase from one new infection for every three people infected nationally, to one new infection for every 2½ people infected, increases the number of infections to about 1 million people in the U.S. — by the end of March alone.

This accelerating rate will continue through the following months. The infection numbers noted above for flu are not far-fetched, and neither are the estimated numbers of COVID-19 deaths.

Social distancing precautions must not be eased.

Stephen McKeever is emeritus regents professor of physics at Oklahoma State University and former state secretary of science and technology. McKeever notes that his figures were made earlier this week and don’t use the latest data.

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