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Herd Immunity from COVID-19 and the Rate of Vaccinations

In my last blog post, I projected that if everything continues to go well with the increase in vaccinations and the decrease of new cases, we could potentially reach herd immunity from COVID-19 in the United States by mid-May. After looking at the latest numbers on fully vaccinated people through yesterday, March 22nd, I am revising my forecast to mid-June. The issue is the vaccine rollout. The trend was ramping up last week, but is now just slightly faster than a linear trend. Not everyone needs to be immune for the spread of COVID-19 to slow to a very low level and not re-surge. This level is termed her immunity. The value varies based on multiple factors, the most important of which is the how easily a disease spreads. The level for COVID-19 seems to imply a herd immunity of approximately 75%.

Approximately 91 million are believed to have contracted COVID-19 to date. If you assume all these people are now immune (which may not be true), we need approximately 160 million people to be fully vaccinated in order to achieve herd immunity. Looking at the graph below, which is a simple second-degree polynomial extrapolation from actuals between January 19th and March 22nd, it appears that the number of fully vaccinated people which reach the required level by the end of May. It takes another two weeks for the antibodies to build up in the immune system, which leads to a best-case forecast of mid-June.

This forecast is an optimistic scenario, as it assumes people who have had COVID cannot get reinfected, that people who are vaccinated are immune from the new variants of COVID now spreading in the United States, and that people will get vaccinated as soon as possible.

2 thoughts on “Herd Immunity from COVID-19 and the Rate of Vaccinations”

  1. Dr. Smart, thanks for posting. I am curious on the source of the data and the statement “it is believed 91 million people have contracted COVID-19 to date.” This has to be estimated and subject to assumptions and measurement error. For example, it is policy in New York city that if a person tests positive for COVID and then gets a second test to confirm, it is recorded as two positive cases even though it was the same person. There was a large incentive to inflate the rates for political reasons. Therefore, ascertaining the actual number of cases is very difficult because the underlying data is flawed. Concur?

    1. Eric, thanks for the comment. There are approximately 30 million confirmed cases of COVID-19 in the U.S. to date. However, we know the true number is higher. Some of the best modelers and forecasters of COVID-19 cases have based their analysis on death data, which is more reliable (although still not perfect). There are approximately 540,000 deaths due to the novel coronavirus in the U.S. to date, and scientists estimate the infection fatality rate due to COVID-19 is 0.6%, so you can use those two pieces of information to estimate that the true number of cumulative U.S. COVID-19 cases is 91 million. That avoids the issue with multiple tests conducted on the same person.

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