The Centre for Epidemiology and Biostatistics, led by epidemiologist Professor Tony Blakely, in an article in the Medical Journal of Australia, has offered support for the idea that permanent masks in public in Victoria may be the best way of preventing deaths from Covid: “The net impact of mask wearing will vary according to the levels of other interventions, including vaccination rates. Nevertheless, our findings suggest that consistently higher mask wearing rates across all ages would reduce the cumulative infection and mortality burden in Victoria.” However, as critics have pointed out, the study is a computer simulation study, that was based upon the claim that cloth masks reduce transmission by 53 percent and respirators reduced it by 80 percent. But, the issue of the effectiveness of mask is controversial and there are major studies that see masks as totally ineffective for preventing Covid transmission, or that this is inconclusive. The principle here is garbage in, garbage out.
Will a new mask policy be based upon such “research”?
https://off-guardian.org/2023/07/27/this-pro-mask-study-is-why-you-should-never-trust-the-science/
“Last week it was reported that the Australian state of Victoria may be considering “permanent” facemask mandates to achieve “zero-Covid”.
Now, we don’t need to get into the personal liberty implications of such a law, or the near-infinite supply of evidence that masks don’t work to prevent the transmission of respiratory disease.
They don’t work, they never worked. Mandating them was a political move designed to make the fake Covid “pandemic” appear real, and their continued use is a symptom of brainwashing or a by-product of chronic virtue signalling.
The mask debate, such as it was, is over.
No, the only aspect of this development worth talking about is the “evidence” used to support the position – and trust me, the quotes are entirely justified.
The “study” which claims to demonstrate the benefits of permanent masking was published in the Medical Journal of Australia last week and titled “Consistent mask use and SARS‐CoV‐2 epidemiology: a simulation modelling study”.
“Simulation modelling study” is very much the key phrase there. For those who don’t know, “simulation modelling studies” involve feeding data into a computer programme, then asking it to form conclusions.
Clearly, they are only as reliable and useful as the data you use. In fact, you can very easily make them produce any result you want by feeding in the “right” (bad) data.
In this particular modelling study they started out by telling the computer that cloth masks reduce transmission by 53% and respirators reduced it by 80%:
Odds ratios for the relative risk of infection for people exposed to an infected person (wearing a mask v not wearing a mask) were set at 0.47 for cloth and surgical masks and 0.20 for respirators
Essentially, they told their computer that masks prevent disease…and then said “ok, computer, since you now know masks prevent disease – what would happen if everybody wore them all the time?”
The computer then told them – obviously – that nobody would get sick.
Because they made it logically impossible for it to say anything else.
But there’s a bit more to it.
The next layer of interest is where they got their input data from.
After all there have been dozens of studies done on masks over the years, 98% of which say masks don’t work.
So, did our guys they choose a peer-reviewed real-time control trial relying on lab-tested double-blind results?
Perhaps one of the dozen or so such trials listed in our 40 facts article?
Did they maybe average the results of multiple studies?
No, they used a phone survey.
One phone survey.
This phone survey, published last year and conducted in late 2021.
In this *ahem* “scientific study”, they had people randomly call up those who had recently been tested for “Covid”, ask them “did you wear a mask?” and then published the conclusion – “masks reduce transmission by 53%” – as if they meant something.
Interestingly, if you scroll down to the “affiliations” section you can see that one of the authors is a Pfizer grant recipient.
Rather more troublingly – and for some reason not mentioned as a conflict of interest – is that the whole study was produced by the California Board of Public Health.
California had already had a mask mandate in place for almost a year before this “study” was even started.
What we have here is not “science” it’s a computer model based on the results of a subjective phone survey conducted by a government agency with a vested interest. It is entirely meaningless, and yet is published in journals and cited by “experts”, perhaps even used as the basis of introducing new laws.
This is how “The ScienceTM” works. And, although Covid has maybe opened many people’s eyes to this issue, it is far from unique to “Covid”. You are just as likely to find this kind of “research” published on any topic – especially those that serve a political purpose – and have been for years if not decades.
Stanford Professor of evidence-based medicine, John Ioannidis wrote a paper called “Why Most Published Research Findings Are False”, and that was back in 2005.
This has nothing to do with the “pandemic”, and everything to do with the difference between science and “The Science”. So let’s examine that distinction.
“Science” is an approach to the world. A rational method for gathering information, testing new ideas and forming evidence-based conclusions.
“The Science” is a self-sustaining industry of academics who need jobs and owe favours.
An ongoing quid pro quo relationship between the researchers – who want honors and knighthoods and tenure and book deals and research grants and to be the popular talking head explaining complex ideas to the multitudes on television – and the corporations, governments and “charitable foundations” who have all of those things in their gift.
This system doesn’t produce research intended to be read, it creates headlines for celebrities to tweet, links for “journalists” to embed, sources for other researchers to cite.
An illusion of solid substantiation that comes apart the moment you actually read the words, examine the methodology or analyse the data.
Self-reporting surveys, manipulated data, “modelling studies” that spit-out pre-ordained results. Affiliated-authors paid by the state or corporate interests to provide “evidence” that supports highly profitable or politically convenient assumptions.
This mask study is the perfect example of that.
Interlacing layers of nothing designed to create the impression of something.
That’s why they want you to trust it, rather than read it.”