One of the fundamental pillars of the Hysteric Brigade is an absolute faith in authoritative sources. “Quality” of the sources is rarely measured, and, often, the very act of criticizing a source on its merits is considered heresy. The Hysterics have invented new terms, or at least transmuted old terms, to define this act of skepticism: misinformation, disinformation, and malinformation. Inevitably, those who use these terms are devoid of the tool kits necessary to even assess quality, but their faith is unbending, so long as the conclusions align with their prejudices.
The past two years have been dominated by typical Hysterics — television virologists, TikTok nurses, and Twitter doctors — who cite studies that make tenuous assumptions using opaque data without any consideration for the strength of the evidence. But the hyper-dissemination of content rather than substance is an old problem taken to its’ natural extremes.
Before even examining the problem, we need to understand what we are truly facing. I recommend going to the COVID-19 early treatment website and looking around for yourself. It really gets to the point of this post and it is also a wonderful resource worth checking out. While the site owners generally do an excellent job pointing out data quality errors, one thing that sticks out like a broken thumb is how basically everything seems to be effective against COVID-19.
On the surface, that may seem reasonable. Why would researchers perform research on drugs that they did not think would have a benefit in treatment?
Then again, many of the most “promising” drugs are poorly studied, and the variance among some drugs is wildly out of proportion or based on small samples and limited data. Surely, one would imagine, if some of these repurposed drugs were so effective, there would be more interest in them?
But what if there has been. How can we be sure?
Molnupiravir is a perfect example. We know that at least two randomized control trials have been halted due to a lack of efficacy. The results were never released and would not be seen on a site like COVID-19 early treatments. We also know that the Merck trials appear to have been gamed, something I have repeatedly pointed out since the results were released. There are other drugs on the list, such as Paxlovid, which are in similar circumstances. Pfizer released the results of the EPIC-High Risk trials, but where are the results for the EPIC-Standard Risk trial, which was on pace to have statistically insignificant results?
Nor is this a new phenomenon. Tamiflu is another perfect example. Countries spent billions of dollars stockpiling a drug that does not work based on recommendations from the Food and Drug Administration, who knew it did not work. There were eight, yes, EIGHT unpublished studies that showed conclusively that it did not work compared to the one weak study claiming it did. Other agencies like the Center for Disease Control were happy to hop on board, reminding us of the old adage: “Do not believe your own propaganda”.
The opportunities for Type I errors to dominate the narrative, as Rosenthal pointed out when he initially outlined the “file drawer problem”, are incredible when researchers refuse to publish negative results. Unfortunately, there are many reasons why researchers would refuse to publish their results including difficulty getting published, conflicts of interest, or concerns over reprisal from pharmaceutical companies. Added to the list these days is the fear of being labelled a conspiracy theorist. For example, there are probably not many negative results about Ivermectin left unpublished, but there may be a few positive results.
This is made only worse when the Hysterics tell us we cannot question the results of obviously poorly run studies like the hundreds of test-negative case control studies used to promote vaccines despite the assumptions of that study design being violated from the beginning.
I guess my point is that blind obedience to authoritative sources is not just “anti-science”, but it is also a surefire way to kill ones credibility. If the results seem too good to be true, they probably are: check the methodology, check the assumptions, check the data, but, most of all, check for missing studies.
That was one of my first lessons about big pharma years ago. I collected data for a major drug, company, and their product did not perform as hypothesized. The study was not published.
The free capitalist market does not want scientific breakthroughs which cannot be monopolised, trademarked and controlled - it wants the profits for the next quarter to look better than the last.
One does not need to adopt the folly of marxism to understand why capitalist logic cannot be implied or applied as a universally intrinsically good (factual and normative) principle. More profit in shorter time for lesser cost at lower risk trumps all other considerations. If one uses that logic as a tool to understand, the decisionmaking process also becomes understandable:
Most of what helps alleviate Covid are well-known already in use methods and medicines. Low profit margin, no monopoly and full liability. Bad for business, but good for people.
(Anyone wanting to confuse or equate criticism of the failures of capitalism as support for marxism is welcome to do so, at their own peril. I suspect such a person has zero real-life experience of communism or socialism put into practice. I do, so I would never endorse those systems any more than I endorse a corporate capitalist one.)