How to lie with data, part 2, or Unvaccinated Covid patients are contagious for less time than those vaxxed or boosted

Irina Truong
j-bennet codes
Published in
7 min readSep 3, 2022


Nick Fewings on Unsplash,

The story begins

One day my aunt, who is 75 years old and spends her days watching videos on TikTok, told me that this is, of course, none of her business, but she thinks that I’m not doing my kids a favor by vaccinating them against Covid-19, and as for herself, although she is eligible for her next booster, she doesn’t believe she needs it. I asked what makes her think that. She said she saw a doctor on TikTok claiming that vaccinated people, if they get sick with Covid-19, actually stay contagious longer than unvaccinated people.

She didn’t know which doctor this was, or if it was even a real doctor. So I had to do some Googling.

I still don’t know which TikTok doctor it was (a Russian-speaking one), but the original source of misinformation appeared to be this article in the New England Journal of Medicine, called “Duration of Shedding of Culturable Virus in SARS-CoV-2 Omicron (BA.1) Infection”.

The numbers behind the story

The study looks at a small sample of 66 people, infected with either Delta (32) or Omicron (34), and gives them PCR and culture tests on the days following their first positive PCR test (or the onset of symptoms, whichever happened earlier). After 5, 10 and 15 days, some people still test positive:

| Days | Unvacc. | Vacc. | Boost. | Vacc. + boost. |
| Day 1 | 16 | 37 | 13 | 50 |
| After 5 days | 14 | 34 | 11 | 45 |
| After 10 days | 5 | 26 | 8 | 34 |
| After 15 days | 1 | 8 | 1 | 9 |

If we convert the absolute numbers to percentages, here is the result:

| Days | Unvacc. | Vacc. | Boost. | Vacc. + boost. |
| Day 1 | 100.00% | 100.00% | 100.00% | 100.00% |
| After 5 days | 87.50% | 91.89% | 84.62% | 90.00% |
| After 10 days | 31.25% | 70.27% | 61.54% | 68.00% |
| After 15 days | 6.25% | 21.62% | 7.69% | 18.00% |

Multiple other publications, such as this one, made their own conclusions based on these numbers. You see, after 10 days of being sick, 68% of vaccinated or boosted people still have a positive PCR test, while this number is much lower for unvaccinated people — only 31%. After 15 days, 18% of vaccinated or boosted people still have a positive PCR test, versus only 6% of unvaccinated people. Clearly, vaccinated people took longer to recover, right? And so The National Pulse article states:

When the data was separated into the categories “unvaccinated,” “vaccinated,” and “boosted,” individuals who did not receive a COVID-19 vaccine were contagious for a shorter period of time.

There are at least two problems with this statement:

  1. Having a positive PCR test is not the same as being contagious. PCR tests are very accurate, because they detect the presence of genetic virus material, but it’s not necessarily a live virus. Even after the virus is dead, PCR test may still detect fragments of its DNA that produce a positive result.
  2. The article in The National Pulse completely omits the second set of the metric that the original study looks at: time to culture conversion, i.e. how long it took for the participants to show a negative culture test. A viral culture test is a better metric than a PCR test to determine whether someone is contagious. Still not perfect though, because viral load — the quantity of the virus — is important.

There are also problems with the study itself, such as the small sample size. With such a sample, the confidence interval becomes very large, and the margin of error increases. The National Pulse article converts those small numbers to percentages, which is usually a bad idea, because it’s misleading. If you were told that in one study, 66% of people had a large nose, would this sound like a large number? Yes. But if you were told that the total sample size was three people, would your perception change?

However the two problems with the statement above are the most important.

The original study looks at two metrics — time to PCR conversion and time to culture conversion. The National Pulse only cites the first one. Let’s take a look at the second one, time to culture conversion :

| Days | Unvacc. | Vacc. | Boost. | Vacc. + boost. |
| Day 1 | 16 | 37 | 13 | 50 |
| After 5 days | 13 | 27 | 9 | 36 |
| After 10 days | 5 | 8 | 5 | 13 |
| After 15 days | 0 | 1 | 1 | 2 |

Same data, converted to percentages:

| Days | Unvacc. | Vacc. | Boost. | Vacc. or boost. |
| Day 1 | 100.00% | 100.00% | 100.00% | 100.00% |
| After 5 days | 81.25% | 72.97% | 69.23% | 72.00% |
| After 10 days | 31.25% | 21.62% | 38.46% | 26.00% |
| After 15 days | 0.00% | 2.70% | 7.69% | 4.00% |

We see that after 10 days, 26% of people in the vaccinated or boosted group still have live virus that can be cultured, while for the unvaccinated group, this number is higher — 31%. After 15 days, all of the unvaccinated people are in the clear though, and the vaccinated and boosted group still has a couple of stragglers. But is this table as convincing as the first one? Not really, and this is probably why The National Pulse didn’t use this metric, instead conflating contagiousness with a positive PCR test.

The authors of the study themselves make a different conclusion:

There were no appreciable between-group differences in the time to PCR conversion or culture conversion according to vaccination status, although the sample size was quite small, which led to imprecision in the estimates.

The interpretations and the consequences

Reuters fact-checked the article in The National Pulse, giving great analysis, and proving it wrong. They also requested more information from the study co-authors. One of them (Siedner) said:

The median time of viral culture positivity in the three groups (unvaccinated, vaccinated, and boosting) was seven days, six days and six days, respectively.

If anything, these numbers give a slight advantage to the vaccinated and boosted people (although they are not statistically significant).

But the damage has already been done. It’s still being done, because not that many people read past the headline. The headline was picked up and spread around countless Twitter, Facebook and TikTok posts. Here is one:


Complete with a large headline and a striking graphic, calculated for the maximum impact, the tweet definitely makes an impression. At the point of writing this article, it collected 14K retweets, 37.6K likes, and was quoted 905 times. The comments are mixed — a lot of people agree and thank the tweet author for the “honest information”, while a lot of people followed through to find the original study, and pointed out the flaws in both the study and the interpretation.

The doctor that posted this tweet is a psychiatric physician. He has over 170K followers on Twitter — not bad! — I have less than 200. He wrote a book called “The New Abnormal: The Rise of the Biomedical Security State”. Here is the book on Amazon:

This is the book summary:

The coronavirus pandemic conferred enormous power on certain government officials. They have no intention of giving it up.

In the space of a few weeks in early 2020, Americans witnessed the imposition of previously unimagined social controls by the biomedical security state — the unelected technocrats who suddenly enjoyed nearly absolute power to incarcerate, isolate, and medicate the entire population. In this chilling new book, a dissident scientist reveals

* the people and organizations that form the biomedical security state

* its role in the origin of the pandemic and shaping the government response

* why it is a threat to science, public health, and individual freedom

* what can be done to confront and defeat this new Leviathan

I wonder why this doctor would be promoting Covid misinformation… Do you?

Unfortunately, there are way too many people like my 75 years old aunt, who believe these doctors, their tweets, their books, and their articles.


Today’s lesson on how to lie with data was:

  • Cherry-pick a metric that tells your story, from the point beneficial to you. If there are other metrics, omit them, or gloss over them.
  • Conflate, conflate, conflate. People are not going to look behind the storefront of big words like “contagion”. They will quickly believe, like, retweet, subscribe, etc.

Oh yes, so was I able to convince my 75 year old aunt? Not really. I showed her the original study, explained the numbers and the included charts, and she said: “I believe you’re very smart, child, but this is too complicated. In any case, I’ll have this last booster just to please you, so be happy about that”.

That’s it for now. In case you missed Part 1, here is the link: