In May, the CDC started to practice a form of "off the books accounting" (Here's a page describing creative accounting principles). In the U.S., we now have two sets of books when it comes to counting Covid-19 cases.

On May 1, the CDC introduced a new definition for "breakthrough cases." Breakthrough cases are cases that are found among the vaccinated people. Prior to May 1, all PCR-positive cases, including mild and asymptomatic cases, were counted as breakthrough if they occurred at least 14 days after the single J&J shot or the second mRNA shot. After May 1, only PCR-positive cases **that result in hospitalizations and deaths** within that case-counting window are counted as "breakthrough cases".

Because of the revised definition, the U.S. now has two tallies of cases among the vaccinated: one count includes mild and asymptomatic cases while the other count excludes them. (No such distinction is made for unvaccinated Americans.)

So if you ask how many Covid-19 cases there are in the U.S., there are two possible answers. The reality is even messier because each state may be reporting one or both counts to the national database.

That statement from the CDC implies that one of the two counts (the one including mild and asymptomatic cases for vaccinated Americans) is incomplete.

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Consider media statements such as "95% of Covid-19 cases in the U.S. are now in the unvaccinated."

This statement is meaningless unless you're told which set of books was consulted. Were mild and asympotomatic cases in fully vaccinated Americans included in the total, or only CDC-approved breakthrough cases? (A separate but still pertinent issue is whether sufficient fully vaccinated people are tested to measure mild and asymptomatic infections.)

It appears likely that a data analyst computes the number of cases in the unvaccinated population by subtracting the number of breakthrough cases from the total number of reported cases. The total number of reported cases is typically the number of positive PCR test results, and therefore it should include all cases, including mild and asymptomatic, and regardless of vaccination status.

Now, pay attention to the following types of cases:

a) Mild and asymptomatic cases among the vaccinated that were reported at least 2 weeks after the last prescribed vaccine shot

b) Mild and asymptomatic cases among the vaccinated that were reported prior to 2 weeks after the last shot

c) Hospitalizations and death among the vaccinated that were reported prior to 2 weeks after the last shot.

CDC does not qualify these cases as "breakthrough cases" but all of these produced PCR-positive test results. The first statement means these cases are not counted as vaccinated cases while the second statement says they are counted as unvaccinated cases - if the analyst subtracts the breakthrough cases from the total cases.

Imagine that! Someone who is hospitalized two days after receiving the second Pfizer shot is counted as an unvaccinated case in this math. Someone who has mild disease a month after receiving the second Pfizer shot is also counted as an unvaccinated case.

What happens if the data analyst recognizes this problem, and wants to fix the math? You'd have to create a third bucket to hold all those cases - which are neither cases in the fully vaccinated nor cases in the unvaccinated. In the business world, this is known as "off the books accounting". You simply disappear these cases into the nether world.

In a follow-up post, I will estimate the scale of this off-the-books accounting using real-world data. Stay tuned.

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