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Pasteurizing the Conclusions of an Anti-Vaxxer – Article by Zach Richardson

Pasteurizing the Conclusions of an Anti-Vaxxer – Article by Zach Richardson

Zach Richardson


I had an unfortunate encounter with a friend of a U.S. Transhumanist Party member who was conducting on his page what I call an “anti-vaxxer drive-by”: shooting out some quick chart with poorly interpreted data that seemingly supports the idea that vaccines make you sick / don’t work / are Bill Gates microchips, etc.

The graphic in question was this one:

The chart in question shows a rise in infection at equal rates from those who got both vaccines, and those who did not receive a vaccine at all. The green bar shows amount of cases where no vaccine was received, and the blue bar amount of cases who again tested positive two weeks after the vaccine. What is the implied conclusion, then? The creator of this graphic wants to convey the message: “Why even get the vaccine, if the rates of infection are just as high 20 days after getting it as they are if you don’t get one at all?”

This post is about why his conclusion is wrong, why his analysis is wrong, and why his ilk are not to be trusted.

I was very lucky to find myself with several free hours of time today, as digging into this took some time. I had to type the source link into the browser a few characters at a time, since it was from an image, and the site itself was in Hebrew. I was pleased to find though, that the site did have the data available for download in a CSV format, which is easily importable into Google Sheets.

The data showed weekly stats on 9 age groups, and how many cases there were in three time periods: one to six days from vaccination, seven to thirteen days from vaccination, thirteen to twenty days from vaccination, and cases from vaccinations more than twenty days ago. This sequence is repeated for cases after dose two of the vaccine. Here is the spreadsheet:

I’ve included the last two weeks in this screenshot, and would like to direct the reader to notice a few things that should stick out sorely after a few moments’ study.

1. For the age range 0-19, the number of youths who reported cases was forty times as high as those who did not.

– Were children perhaps just 40 times as susceptible to infection? This would have been interesting for the person looking at the chart to know.

2. The age range 0-19 actually makes up one-half of the total amount of cases reported.

– Maybe it was just that those who signed up for this study all happened to be children who needed pocket money? That can’t be right…

3. For week the week of June 27 (2021-06-27), excepting the youth group for vaccine 1, not a single case was reported during the weeks 1-20 for any group. The next week never had more than five cases for an age group.

– Ah, good news! Perhaps the vaccine was super effective, if only for 20 weeks.

4. It is not reported how many people total got the vaccine who were NOT sick after 20 days.

-Perhaps the data account for all cases, and all those in the study eventually got reinfected?

There are some big problems with this chart, and the first is that this is a HUGE instance of what we call “self-selection bias”.

Unlike lab rats who have no choice in the matter, humans get to choose whether to participate in studies or not. Adults can easily choose to not report when they are sick; people had to voluntarily “select” themselves to be included in this dataset. Children have less choice. Children are in school, and vaccine testing can be conducted just the same way standardized knowledge testing is: get all the students in the same building, line them up, assign each a number, and have every single one tested. I think this is why youth aged 0-19 outnumber those aged 20-90 combined.

Even more important than that, we do not know how many people got the vaccine who did NOT get sick vs those who did not get the vaccine and did not get sick. Assuming Israel gives out 9,000 inoculations a day, the 30-39 year olds in week 07/04 could have been 248 vaccinated people infected out of tens of thousands who received the vaccine. We don’t have a way of knowing and don’t have that data.

The real plot twist though, comes after one digs into the “README” file attached to the study data right next to the CSV file. Here is the relevant excerpt Google translated:

vaccination_without_positive_Sum – number of verified people detected per week and age group Relevant, and who did not receive any vaccine dose. It should be noted that vaccinated who received the vaccine dose The first on the same day that a positive result was obtained are included in this column.”

What does this mean? It means that the “unvaccinated” group were those who ran to the doctor after they got sick, got the vaccine themselves, and were only THEN added into the dataset. They got the vaccine too!

The charlatan that made that chart was trying to make it seem like he was comparing data from two groups in a randomized controlled trial, and concluding that the data showed you were equally as likely to get sick when taking the vaccine as not. What the data really showed is that it is very easy to test children who are stuck doing what their teachers tell them for eight hours a day, and also that when the chips are down and the unvaccinated finally do get sick, they change their mind and run to the doctor to get the vaccine anyway.

As Director of Publication for the USTP, I would like to reaffirm the Transhumanist Party’s strongly-held pro-vaccine stance. There is far too much of this junk science flying around, and I certainly can’t spend the better part of the afternoon each day playing “debunker”, but you can be sure to expect a series of pro-vaccine material to be republished under the Infinity Banner.

Zach Richardson is Director of Publication for the U.S. Transhumanist Party.