It is being proclaimed on lawn signs and social media memes, on T-shirts and in PSAs. From sea to shining sea, the message is clear: Trust the Science! This is the mantra chanted by pro-vaccine portions of the population to encourage us to do our part. Getting the jab is no longer a matter of debate. There is only one sensible choice: vaccinate or be condemned to the anti-science movement that denies the horrors of polio and remains entrenched in a flat-earth delusion.
Scientists Do Not “Trust The Science”
I have a message for all you “science trusters”: scientists don’t trust the science. Scientists are the most skeptical of the science because they know that science is always changing. That is why our understanding evolves, and why we trust the scientists to begin with.
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Scientists trust the scientific method, which is an entirely different thing. In order to do the systematic measurement, experimentation, observation and reformulation of hypotheses, the scientific method demands that we approach what is happening with an open mind, so that all possibilities are on the table to begin with. It is their unbiased approach to examining what is that instills credibility to their opinion.
Unless you are a scientist yourself, it is very hard to understand what the scientists are actually saying. Trusting the science is not the same thing as trusting what the media is telling you what the science says. This is becoming more and more evident as MSM sources continue to distort and oversimplify nuanced and complicated subjects into sound bites, tweets and headlines. In this article I attempt to explain how to critically examine content published in Mainstream Media that attempts to explain “the science”.
“Lab Origins” Was Always The Scientific Position
Perhaps the biggest example of the enormous amount of Mainstream media distortion around scientific matters is the recent acknowledgement that the SARS-COV2 virus was most likely engineered in a laboratory. Of course no new evidence emerged recently. The evidence pointing to lab origins was available 15 months ago, but it was portrayed as an absurd notion unworthy of any consideration by any legitimate news source. Nevertheless, Collective Evolution covered it here nearly three months ago.
How Do We Know If The Vaccine Is Proving Effective ?
The arguments for universal vaccination have been starting to shift now that hundreds of millions of people have been vaccinated. Is the vaccine making an impact on the spread of Covid-19? That is an extremely difficult question to answer. Unless we have access to clear data that demonstrates the rate of infection in the unvaccinated compared to the vaccinated we can only guess. Why don’t we have those numbers now? It’s because we haven’t completed Phase III trials of the first vaccines that were formulated. That’s why we do the trials and why we generally wait for them to be completed before giving the vaccine to anyone.
The best data I have seen has come from Israel and published in the New England Journal of Medicine on February 24, 2021. They matched nearly 600,000 vaccinated individuals with unvaccinated ones and observed them over 42 days. At the end of that period approximately 10,000 documented cases of Covid-19 resulted, the unvaccinated outnumbered the vaccinated by about 5 to 4. To be precise, 57% of the people who got documented Covid-19 in this examination were not vaccinated. What this means is that vaccine efficacy over the entire period of observation is:
On the other hand, the vaccine seemed to be more effective (over 91%) as time went on. This is of course encouraging and is more representative of what the vaccine’s efficacy really is. However, if we compare the incidence of the disease in the unvaccinated to the vaccinated after 35 days we are now dealing with a much smaller pool of subjects. At that point there were 47 unvaccinated people that contracted the disease compared to 4 that were vaccinated. The vaccines may prove to be that effective as time goes on.
Perhaps what is more telling is that at the end of the study period only about 1% of the people got Covid-19. Of those, 43% were vaccinated. This means the absolute risk reduction of vaccination is just over 0.1%. In other words, in order to prevent 1 case, 1000 people need to be vaccinated. If the vaccine continues to demonstrate a 91% efficacy then 110 vaccinations would prevent a single case in the long run. The point here is that unless one is willing to look more closely it is very easy to come to unsound conclusions, especially around the true impact of the vaccine.
The Washington Post Used Circular Reasoning To Make False Claims
The Washington Post has built an interactive Covid-19 data tracking page called “The Unseen Covid-19 Risk for Unvaccinated People” on May 21, 2021. This page was cited by a member of my social media community as proof that the vaccines were very effective and, based on the title of their page, the unvaccinated were facing a risk “unseen”. This person was quite convinced that remaining unvaccinated was irrational if not unconscionable and the data proved it. After all, it was in the Washington Post, a publication with a long history of balanced and rigorous inquiry.
The page demonstrates rates of infection among unvaccinated compared to the total population over time. From the day that vaccines began, it seemed (from the dozens of graphs presented) that the rate of infection in the total population began to drop faster than that of the unvaccinated. This was demonstrated in a number of selected states and not the country as a whole. Could they be cherry picking data? Of course. Nevertheless, I was surprised to see such a marked effect of the vaccines in any given population, cherry picked or not.
However, upon closer inspection something was missing. Where was the plot showing the rate of infection among the vaccinated? It wasn’t shown. The graphs only plotted total rates compared to unvaccinated rates. The mystery deepens…
Numbers of unvaccinated and vaccinated people with infection were not counted
If you searched for the raw data (the numbers of people who got covid who were vaccinated and unvaccinated), you won’t find it. So how are they able to tell us the rate of infection in the unvaccinated? They weren’t telling us that at all. Instead they created a variable which they call “Rate adjusted for Unvaccinated”. To see how they arrive at this “rate” you must read their methodology section at the bottom. In it they demonstrate their deception. They assume that 85% of all people vaccinated could not contribute to the total number of cases. They make that assumption based on a small study from the CDC involving about 4,000 people (one tenth that of the Pfizer study). They then apply this to all the states in their plots.
This is a big assumption. Although the authors cite the study upon which this assumption is made in at the bottom of the article in the “methodology” section, the assumed efficacy of the vaccine (85%) is never explicitly stated in the body of the article. Perhaps the vaccine will turn out to be that good. The point here is that there is no consensus on what the vaccine efficacy is (Phase III trials are yet to be completed), and they buried their assumptions in the methodology section.
Let’s go back to the basics. These are the proper scientific definitions:
Total Case rate = Total Number of Cases/Total Population
Vaccinated rate = Number of Cases in Vaccinated/Number of Vaccinated
Unvaccinated rate = Number of Cases in Unvaccinated/Number of Unvaccinated
Hopefully that was straightforward and logical. The Washington Post then introduces this term:
Rate adjusted for Unvaccinated = Total Cases/(Total Population – 0.85 x Vaccinated)
What is wrong with this? Nothing–as long as they know that only 15% of the vaccinated are contributing to the number of cases. But they don’t know this, they are assuming this in order to make their graphs. To casual Washington Post readers (numbering in the millions), it would be easy to look at the graphs and believe that that is what is being reported while in fact that is what the graphs would look like if their assumption were true.
They are taking out 85% of the vaccinated people from the total population to calculate the new “rate” and calling that the Rate of Unvaccinated. This would in fact be true if they actually measured every population in each plot and confirmed that 85% of the vaccinated people were not contributing to the case count. But that is not what they did. They assumed that was the case, drew their plots and “demonstrated” that the rates in unvaccinated people were much worse than the vaccinated. This is pure circular reasoning.
Notice that in their formula for “Rate adjusted for Unvaccinated” the denominator is the difference between the Total Population and 85% of the vaccinated. What do you suppose happens to the adjusted unvaccinated rate as more people get vaccinated? Before answering, “it gets bigger!” notice that it depends. It depends on “Total Cases” which had also been dropping day after day. However in every graph they compare Total Case rate and Rate adjusted for Unvaccinated. A quick glance at the formulas above should lead you to the conclusion that “Rate adjusted for Unvaccinated” will always be larger than Total Case rate as more and more people get vaccinated. That is what every graph they published demonstrated. They are not introducing another artifact; it is the direct result of their assumption that in every geographical area plotted 85% of the vaccinated are protected.
They deepen the deception by subsequently referring to their “Rate adjusted for the unvaccinated” as “case rate for the unvaccinated” by subtly removing the word “adjusted”. As explained and defined above, the unvaccinated case rate requires that the actual number of unvaccinated individuals who are infected were counted. This is pure manipulation. What happened to the fact checkers?
They conclude the article by quoting Umair A. Shah, Washington State Secretary of health who makes this audacious claim:
“The people who are not vaccinated are the ones who are not wearing a mask or washing their hands. Those are the very people who oftentimes will socialize and be around similar like-minded people. You’re going to have the pandemic continue in those clusters.”
I wonder how Dr. Shah, an MD and epidemiologist was able to make this measurement? Did he survey unvaccinated people to see if they were wearing masks or washing their hands? Did he surveil them? This level of propaganda coming from the Washington Post or any other media platform is unconscionable yet continues to go unchecked.
The Washington Post is not the only culprit in this kind of manipulation. In this piece from CE, similar kinds of spin were apparent in the NYTimes in their effort to paint 5G naysayers as Russian apologists and citing articles that contradicted their own position. Are established, corporate funded publications given an enormous amount of latitude because of their reputation? Or is it because they contribute to a narrative that is accepted by their sponsors and “independent” fact-checkers? I believe it is both.
(This article was corrected on June 7, 2021 to clarify the efficacy results from the NEJM paper submitted 2/24/21)