Difference between revisions of "Application for Secular/Religious Exemption from Mask/Vaccine Mandate - Section Two, The Evidence"
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[https://media.mercola.com/ImageServer/Public/2021/November/PDF/covid-jab-reduces-all-cause-death-pdf.pdf Dr. Joseph Mercola] summarizes Berenson's analysis, adding the analyses of [https://twitter.com/RepThomasMassie/status/1454372068338900998?s=20 Rep. Thomas Massie], [https://twitter.com/MartinKulldorff/status/1454302176772333572?s=20 Martin Kulldorff, Ph.D.,] professor of medicine at Harvard Medical School and a
[https://media.mercola.com/ImageServer/Public/2021/November/PDF/covid-jab-reduces-all-cause-death-pdf.pdf Dr. Joseph Mercola] summarizes Berenson's analysis, adding the analyses of [https://twitter.com/RepThomasMassie/status/1454372068338900998?s=20 Rep. Thomas Massie], [https://twitter.com/MartinKulldorff/status/1454302176772333572?s=20 Martin Kulldorff, Ph.D.,] professor of medicine at Harvard Medical School and a
biostatistician and epidemiologist in the Division of Pharmacoepidemiology and Pharmacoeconomics at Brigham and Women's Hospital, along with his own observations.
biostatistician and epidemiologist in the Division of Pharmacoepidemiology and Pharmacoeconomics at Brigham and Women's Hospital, along with his own observations.
==Vaccines Kill More than they Cure==
==Vaccines Kill More than they Cure==
Revision as of 08:17, 26 September 2022
Continued from Application_for_Religious/Secular_Exemption_from_Mask_Vaccine_&_testing_Mandates Section One: The Religious Basis
This article was started by Dave Leach R-IA Bible Lover-musician-grandpa (talk) 02:25, 1 October 2021 (UTC)
Please interact! To interact with any particular point made here, simply click "edit", then right after that point, type four dashes (to create a horizontal line), hit "enter" to start on the next line typing your response, then close with four tildes which will leave your real name, time etc.; then on the last line, four more dashes.
To vote, Like, rate, argue, change your past comment, add a section with a heading that appears in the Table x`of Contents, start a new article, use colors, write in Greek, etc. find suggestions and codes at Begin!
“Are you tired of masks yet?” I found out that if that’s how I begin the subject with doctors and nurses, I am likely to hear “Oh, I’ve hated masks from day one!” Then the door cracks open for me to share the research I have read proving that masks offer zero provable protection, while causing clear harms.
This works much better than “Have you read the Bangladesh and Denmark studies showing masks don’t slow covid?” That word combination seems to trigger eye rolling like tapping a knee cap with a rubber hammer. It makes them defensive, which I had mistaken for apathy. How can I be so old and still have so much to learn?!
Humans are complicated. Statistics math is complicated. Put the two together and you have a mess. Besides being complicated, humans are not always entirely honest. If humans were scrupulously honest and life were simple, this article would be a lot shorter.
And less interesting.
None of the many doctors and nurses I have asked over the past two years have heard of the Bangladesh and Denmark mask studies. Even when my concerns reach hospital administrators, who should be able to find who on their staff knows the research, their answers to me include no response to, or concern for, evidence! Who can I interact with to get corrected if I am wrong, or about getting their harmful hospital mandate corrected if I am right?
I should be able to walk up to any information desk in any hospital, ask “can you show me the evidence that these masks which you require reduces covid infection, in the face of the Bangladesh and Denmark RCT’s which find they don’t?” and the receptionist should be able to hand me a stack of research as she says “Sure!”
I am their patient: aren’t doctors used to summarizing research for patients to help them understand treatment options? Why no “informed consent” for any patient who asks about an intervention not just offered but imposed on every patient?
I mean, nowhere is such information available. Not on the hospital website. Not from any doctor I have talked with, though it should be available from any doctor, since every doctor enforces it. Not even from hospital administrators confronted with the questions.
Evidence challenging a nation-wide, hospital-wide mandate, triggers no discussion. Only apathy. This apathy is turning me, in the company of many others, into an extremist. What distinguishes modern medicine from the cocaine-laced “snake oil” sold by the buckets in “medicine shows” a century ago? Isn’t it attention to research? To the extent hospitals ignore research, and not on some obscure intervention [treatment] but an intervention that affects everybody, what is happening to modern medicine? How many other interventions have no rational basis, even before you consider alarming side effects? What will be left of modern medicine for my grandchildren?
Let’s begin with a summary of what the research shows.
Then, before jumping into a detailed review of the research, with explanations of technical terms which any voter or lawmaker will be able to understand, you “just gotta see” how much confusion and fraud poisons modern medicine just over two terms in statistics math, which are previewed in the above graphs. There are standards for peer-reviewed research requiring both terms to be honestly reported, but there is peer-reviewed research showing that at least a quarter of peer-reviewed research violates these standards, in the company of 100% of advertisers.
You will be completely confused by seemingly contradictory research until you understand these two terms. The premiere example in the mask research world is the Bangladesh mask study of a third of a million people which reports that masks reduce covid by 10%, while the Denmark mask study of 6,000 people reports that the Actual Risk Reduction from wearing masks was so close to zero that it is uncertain whether there is any benefit at all or if masks actually cause covid.
Yet nearly identical results were experienced in both Bangladesh and Denmark. The difference was not in the Sick Rate Reductions, but in the spin.
Denmark honestly reported the Actual Risk Reduction: 2.1% of nomaskers got sick, and 1.8% of maskers. The difference: 0.3%. That’s the Actual Risk Reduction gained by wearing masks all the time. But probability estimates that the range of results that others should expect crosses into negative territory. It is “inconclusive” whether masks help at all, or actually harm.
Bangladesh fraudulently reported that 0.76% of nomaskers got sick, and only 0.68% of maskers. The reduction: 10%! (At one point they said 10%, at another, 9%. The calculation without rounding, which they don’t report, is 9.5%.) The comparison of the two sick rates with each other, without the context of how small a percent they both are of the whole group, 99% of which never got sick, is called by others the Relative Risk Reduction. I find that a very confusing term, so I call it the Sick Rate Reduction. Bangladesh never mentions the difference between the two sick rates: 0.8% is the Actual Risk Reduction gained by wearing masks all the time. Even worse than in Denmark. Neither does Bangladesh mention that its own probability calculations warn that we can be 95% certain that the covid reduction could be as low as zero.
- 1 Part 1 - Masks Clearly Reduce Covid: Disproved
- 1.1 Preview of Research Results Reviewed Below
- 1.2 Terms that Deceive: ARR v RRR
- 1.2.1 SRR = Sick Rate Reduction. ARR = Actual Risk Reduction
- 1.2.2 Violations of ARR v RRR Standards in Peer-reviewed Studies
- 1.2.3 RRR v. ARR Explanations by Others
- 1.2.4 Pill Peddlers
- 1.2.5 Truth In Advertising Laws
- 1.2.6 One More Example
- 1.3 Parachute use to prevent death and major trauma when jumping from aircraft: randomized controlled trial
- 1.4 Nearly identical results, nearly opposite spin in the Only Two Mask&Covid RCT's
- 1.4.1 Denmark and Bangladesh: nearly identical results, nearly opposite spin
- 1.4.2 CATO: Only 2 High Quality RCT's - Bangladesh and Denmark - No Benefit Proved
- 1.4.3 DENMARK: What the Study Showed
- 1.4.4 BANGLADESH ARR’s v. RRR’s: Research Fraud
- 220.127.116.11 CATO on Bangladesh: a Tenth of One Percent Benefit
- 18.104.22.168 250% Inflation: Maybe results indicate not just 0.08% protection, but a whole 0.2%!
- 22.214.171.124 750% Inflation: Maybe results support not just 0.2% protection but 1.5%!
- 126.96.36.199 Doubling Down on Failure: results, 0.08% protection. Claim, 9%!
- 188.8.131.52 NNT: Number Needed to Treat: 35,001 maskers needed to prevent one covid death!
- 184.108.40.206 Bangladesh and Probability: probable protection, 0.14% to zero
- 220.127.116.11 CDC's Inflation of Bangladesh Stats
- 18.104.22.168 Cato on Bangladesh: A Tenth of One Percent
- 22.214.171.124 Bangladesh: Masking Reduces Covid Risk 0.09%, MAYBE
- 126.96.36.199 "No adverse events were reported"?
- 1.4.5 CDC: Miracle Masks
- 1.5 Other Mask Studies
- 1.5.1 July 8, 2022 North Dakota Schools study
- 1.5.2 CDC Report: No Statistically Significant Benefit from School Masks
- 1.5.3 State Mask Mandates Ineffective
- 1.5.4 Non-Covid, yet Relevant, Mask Studies
- 1.5.5 Surgical masks and N95 masks perform about the same
- 1.5.6 "No evidence" masks prevent transmission of flu in hospital setting
- 1.5.7 No significant reduction in flu transmission when used in community setting
- 1.5.8 Risk reduction may be due to chance
- 1.5.9 "No evidence" that universal masking prevents COVID-19
- 1.5.10 Mask or no mask, same difference
- 1.5.11 Fauci's Flip Flops, listed by Congressman Jordan
- 2 Part 2 - Masks Dangerously Reduce Oxygen: PROVED
- 2.1 Harm to children from masks
- 2.2 More masks, more deaths in Europe
- 2.3 Hospital mask mandates impose masks most on those most harmed by masks
- 2.4 German Study: Is a Mask Free of Potential Hazards?
- 2.5 Masks Don’t Reduce Oxygen?
- 2.6 Study where masks reduced oxygen & raised CO2 reported as "Face masks DON'T restrict oxygen or..."
- 2.7 Masks violate OSHA standards
- 2.8 Masks DON’T Violate OSHA Standards?
- 2.9 "Evidence that masks help is lacking. Their harms are established."
- 2.9.1 The effects of less oxygen
- 2.9.2 More medical conditions from lowered oxygen
- 2.9.3 Not just lowered oxygen: more germs, poisons, heat
- 2.9.4 Stress to heart and lungs
- 2.9.5 Surgeons’ 4x more headaches, faster heartrate, lower oxygen levels
- 2.9.6 List of potential medical harms
- 2.9.7 Tiny germs, wide open spaces
- 2.9.8 So how did masks come to be mandated all over the world?
- 2.9.9 Cloth masks most dangerous
- 2.10 Reduced Communication with Patients
- 2.11 Children Struggle to Recognize Mask Wearers
- 3 Part 3 - PCR tests, most trusted of Covid tests: Unreliable
- 4 Part 4 Vaccines Kill
- 4.1 Steve Kirsch Review of Evidence
- 4.2 Higher Death Rate among the Vaccinated
- 4.3 LOWER Death Rate among the Vaccinated
- 4.4 Covid vs. Other Vaccines: UNSAFE
- 4.5 Covid Vaccines: Safer than Natural Immunity! says CDC
- 4.6 Vaccines Kill More than they Cure
- 4.6.1 Fifth Largest Life Insurance Company Reports a “Catastrophic” 40% increase in deaths in 2021
- 4.6.2 Vaccines Kill 1 in 800 in Netherlands and England
- 4.6.3 17,000 doctors: Stop the Jabs!
- 4.6.4 Toddlers Getting Seizures from Vaccinations
- 4.6.5 Total American deaths up 40% among vaccinated
- 4.6.6 Studies documenting vaccine deaths
- 4.6.7 60 times more deaths from covid vaccines than all other vaccines combined, even though thousands of reports are being deleted
- 4.6.8 Vaccination Doubles the Death Rate
- 4.6.9 German Vaccines Correlated with Higher Deaths
- 4.6.10 $1,000,000 offer for anyone who will debate
- 4.6.11 68 Countries, 2947 counties: The more vaccinations, the more Covid
- 4.6.12 "All Cause Mortality" up, implicating vaccines
- 4.6.13 A Statistician's Evidence that Death Rates Increase as Vaccinations Increase
- 4.6.14 Grossly Exaggerated Covid Deaths
- 4.6.15 Grossly Underreported Vaccine Deaths
- 4.6.16 Grossly Exaggerating the Death Toll
- 4.6.17 How to Make 13% effectiveness look like 90% effectiveness
- 4.6.18 Heart Problems
- 5 Censorship
- 5.1 Worldwide Censorship: Dr. Malone explains how it's done
- 5.2 Dr. Malone response to Twitter suspension
- 5.3 Pfizer data saying one person was saved from covid, says 4 died of heart attacks
- 5.4 Just Plain Ignoring Evidence: Fauci & Birx
- 5.5 Censorship Stories
- 5.6 Facebook Censoring Jokes
- 5.7 Deliberately Manipulating Statistics
- 5.8 Government Coverup
Part 1 - Masks Clearly Reduce Covid: Disproved
Featured in Part 1:
Preview of Research Results Reviewed Below (next)
Terms that Deceive: ARR v RRR Actual Risk Reductions, not just Sick Rate Reductions that seem 100 times higher, are supposed to be reported in peer-reviewed studies. Yet at least a quarter of them don't.
Nearly_identical_results,_nearly_opposite_spin_in_the_Only_Two_Mask&Covid_RCT's This is the same kind of info as in the "preview.." above, but with more detail including more math.
Preview of Research Results Reviewed Below
Evidence can’t be forever ignored. Research establishes that masks cause much harm, German study, 4/21/21, while it is impossible to prove any benefit because the results of the only two mask RCT’s, (RCT’s are called “the gold standard” of medical research), in Bangladesh and Denmark can’t rule out the possibility that the impact of masks is zero. The Denmark results were that the impact might even be negative: masks might cause covid.
Even the CDC admits that the Bangladesh results include zero. See l. (“Table: Summary of Studies...” admits the study found that the average percentage of covid cases that mask wearers will experience, compared to the sick rate of those without masks, lies somewhere between 82% and 100%. Here is how this fact is admitted, in a table at the bottom of the page just above the footnotes, in language unfamiliar to most voters and lawmakers: “(adjusted prevalence ratio 0.91, 95% CI 0.82-1.00)”
This meets the definition in statistics of “statistically insignificant”, since “A relative risk is considered statistically significant when the value of 1.0 is not in the 95% confidence interval.”
Unfortunately the statistical insignificance of the Bangladesh results was not admitted in plain language by either the Bangladesh researchers or the CDC. Neither did either admit the context of their claimed “9%” fewer cases counted among Bangladesh maskers than among nomaskers: the fact that only three quarters of a percent of nomaskers got sick. 0.76%. 9% fewer cases than that are a 0.68% sick rate. That isn’t even a one tenth of a percent reduction of the sick rate experienced by maskers. The Denmark researchers honestly admitted their similar findings in plain language.
Wearing a mask all the time reduces the risk of getting covid by one tenth of one percent. (Actual Risk Reduction, ARR, is easy to understand: it is simply the difference between the sick rates of those wearing, and not wearing, masks. Subtract the percentage of maskers who got sick – 0.68% in Bangladesh, from the percentage of nomaskers who got sick – 0.76%. The answer: 0.08% in Bangladesh – LESS than 0.1%. That’s the ARR: how much masks reduce your risk of covid. [Others have ARR stand for Absolute Risk Reduction. They also call it the “Risk Difference”. The Denmark researchers called it the “Between-group difference.” I think “Actual Risk Reduction” most clearly describes what it is.]) That is, 0.1%. In Bangladesh the result was even less: 0.08%. The figure looks even worse if you write it without the % sign: 0.0008. You reduce your chance of getting covid by 0.0008 if you wear a mask all the time. THAT MEANS:
One thousand people need to wear masks all the time to prevent one person from catching covid. (That number is called the Number Needed to Treat (NNT.) If the death rate is 1% of those infected (without comorbidities – other serious conditions equally responsible for death) THEN:
100,000 people need to wear masks all the time to prevent one covid death. (If we can trust that 0.1% is outside the margin of error. But we can’t. More about that later.)
By contast, the chance of being struck by lightning during your life is one in 15,300, and one in ten who are struck by lightning die therefrom, but government doesn’t make us all wear rubber suits our whole lives to reduce that risk. (Yet.)
Maybe every 100,000 maskers save TWO lives. Probability calculations indicate that 100,000 people, wearing masks all the time, might prevent as many as TWO covid deaths. Maybe 100,000 people wearing masks all the time, will prevent 200 people from getting covid, which would prevent two covid deaths.
There is an equal chance that they don’t save anyone from anything. Probability calculations leave it uncertain whether wearing masks makes any difference at all in the number of people who get covid, and who die. It is almost as probable that masks kill! (The “Confidence Interval” on the 0.1% Denmark ARR stretches between a 46% reduction in sickness and a 23% increase!)
These statistics are from the only two RCT’s that measured actual covid transmission with real people, in Denmark and Bangladesh. Their covid reduction rates are nearly identical. So said the Cato Institute in its analysis of many mask studies. So said Martin Kulldorff, director of the Brownstone Institute. 0.1% benefit, maybe; maybe zero. So said the Denmark researchers.
Yet the Bangladesh researchers said their virtually identical percentages prove masks slash the risk of covid by 10%! One hundred times more than Denmark’s measly 0.1%!
“Masks reduced the sick rate by 10%!” Doesn’t that make you thank God for masks? “The percentage of maskers that got sick was 10% lower than the percentage of nomaskers that got sick!”
But here is some context: “Masks reduced the sick rate by 10%. But since 99.24% of those not wearing masks remained healthy, and only 0.76% got sick, that 10% Sick Rate Reduction only reduced the sick rate of those wearing masks down from 0.76% to 0.68%. The difference, 0.08%, is the Actual Risk Reduction that people wearing masks all the time earned for themselves. Those without masks have a risk of 0.76% of getting covid. Wearing masks drops that risk down to 0.68%. Less than a tenth of a percent.”
You won’t see that context in a TV ad! You won’t see “Masks reduced the risk of getting covid by only one tenth of one percent.” You will see the 10% claim! 100 times more impressive!
What a difference that makes in whether patients will buy your drugs! Researchers “found that the framing of benefit or risk in relative versus absolute terms [Sick Rate Reduction v. Actual Risk Reduction] may have a major influence on patient preference. The medication whose benefits were expressed in relative terms [SRR] was chosen by 56.8% of patients, whereas 14.7% chose the medication whose benefit was expressed in absolute terms. [ARR] Malenka DJ, Baron JA, Johansen S, et al. The framing effect of relative and absolute risk. J Gen Intern Med 1993;10:543–8.”
Doesn’t it help you understand how much masks benefit, to know how many get sick without them? (Comparing the sick rates of the maskers and nomaskers, without telling what either sick rate is, is a calculation I call the “Sick Rate Reduction” but which others call the “Relative Risk Reduction”. It tells you only the risk rate reduction of maskers relative only to the risk rate of nomaskers. It leaves out the fact that 99% of nomaskers ever got sick, leaving the risk of covid for nomaskers at less than 1%, making it mathematically impossible for their risk to be reduced more than a fraction of 1%.
(“Sick rate” is not an official term. I made it up myself. I wanted an explanation of RRR’s and ARR’s so simple that even I could have understood it the first time I read about them. By “sick rate” I mean the percentage of the people in the group that got sick. The sick rate of Bangladesh nomaskers was 0.76%. 0.76% of the nomaskers got sick. The sick rate of maskers was 0.68%. The Actual Risk Reduction is simply the difference between those two percentages. Subtract 0.76% minus 0.68% = 0.08% That is how much you reduce your risk by wearing a mask, from not wearing a mask. The Sick Rate Reduction is the percentage that that difference [ARR] is of the nomask [control, or untreated] percentage. Divide that difference [ARR] into the nomask percentage. 0.76% divided by 0.08% = 9.5%. Over 100 times greater!
(What a difference it makes whether you subtract or divide!
(When the sick rate is high, the SRR can be useful. But when the sick rate of “controls” - those not being treated; those not wearing masks – is not even 1%, the Relative Risk Reduction can easily be 100 times higher than the actual risk reduction, which is grossly misleading when reported without the ARR.
(But grossly misleading is good, if you are a mask salesman.
(Another way to describe the difference between ARR and SRR: The SRR compares the sick rate of maskers with only the sick rate of nomaskers. The ARR compares the sick rate of maskers with the sick rate of nomaskers, and compares both sick rates in the context of the health rates – the percentage of people who never got sick.
(You can see how it is possible to have a reasonably impressive Sick Rate Reduction, ie 10% fewer maskers got sick than nomaskers, while ignoring the 99%+ of both groups who never got sick, which shows that your actual ARR, Actual Reduction, is a tiny fraction of one percent.)
That is the spin that the CDC quoted.
CDC: In villages receiving mask interventions, symptomatic [where there are symptoms] seroprevalence [where covid infection is confirmed by blood tests] of SARS-CoV-2 was reduced by approximately 9% relative to comparison villages. In villages randomized to receive surgical masks, symptomatic seroprevalence of SARS-CoV-2 was significantly lower (relative reduction 11.1% overall). The results of this study show that even modest increases in community use of masks can effectively reduce symptomatic SARS-CoV-2 infections.
Yet in another place the Bangladesh researchers posted a calculation not far from a 0.1% ARR: they figured it would take 35,001 people wearing masks to prevent one covid death!
There is enough confusion about these calculations that entire peer-reviewed articles examine them. Peer-reviewed published studies find that nearly half of other peer-reviewed studies fail to meet standards for peer-reviewed studies requiring that abstracts – the summaries that always begin the studies – honestly report the ARR (Actual Risk Reduction, which in Bangladesh was 0.08%, plus or minus 0.08% - reduced risk of getting covid by wearing masks all the time) and not just the misleading SRR (The difference between sick rates, divided into the highest sick rate, tells how many % the lower sick rate is than the higher sick rate. 10%, in Bangladesh.)
Terms that Deceive: ARR v RRR
Featured in this section:
SRR = Sick Rate Reduction. ARR = Actual Risk Reduction (Next) The more I stare at the standard terms, the more I think the terms themselves are a large part of the problem. I propose terms more understandable to voters and to lawmakers, as well as to doctors, all of whom need easy and reasonable access to this information.
Violations of ARR v RRR Standards in Peer-reviewed Studies Peer-reviewed studies say at least a quarter of peer-reviewed studies violate standards for peer-reviewed studies calling for honest reporting of ARR's.
How Pfizer used RRR’s to Fraudulently Inflate its Success An illustration of misuse of RRR's without mentioning ARR's to deceive our nation, from the Pfizer trials, analyzed by a peer-reviewed researcher.
500 Doctors Want to Know It isn't just voters, lawmakers, and people seeing TV ads for meds that are confused by misuse of RRR's. Doctors are, according to these reports. In fact, lawmakers should consider adding honest ARR reports for meds to "Truth In Advertising" laws.
SRR = Sick Rate Reduction. ARR = Actual Risk Reduction
The more I stare at the standard terms, the more I think the terms themselves are a large part of the problem. RRR, Relative Risk Reduction, and ARR, Absolute Risk Reduction, are certainly confusing enough that the average voter and lawmaker has no idea what they mean, and how they differ, without explanation; and without quite a lot of explanation, and continual explanation, because even after explanation, the word choices do not easily match what they are.
It is much easier to give examples showing to what the terms refer, than to extract that meaning from the terms themselves.
Relative? Absolute? I have spent many hours reading explanations of these terms, and trying to distill them into an explanation into which the terms “relative” and “absolute” flow naturally, and I still can’t do it, and haven’t read where others could. I don’t recall an explanation of ARR that had the word “absolute” as part of the explanation. “Relative” is a little easier to wrestle with: the RRR is the reduction experienced by the treated group relative to only the control group, but I doubt if anyone unfamiliar with the subject could make sense of that explanation either.
The closest I can come to justification for the terms is to note that “Relativism” is a religion that believes there is no “absolute” truth, or “right and wrong” in any absolute sense, but only “your religion may be right for you, but my religion is right for me”. “Relativists” apply this to objective Truths as defined by the Bible about how to live and behave. But when it comes to making a phone app work, or the rules of a video game, they believe in objective truth like the rest of us.
The connection between Relativity and the use of the terms RELATIVE Risk Reduction and ABSOLUTE Risk Reduction is remote, but one commonality is their mutual use to justify fraud. Both promote evil, and call it good. Isaiah 5:20 Woe unto them that call evil good, and good evil; that put darkness for light, and light for darkness; that put bitter for sweet, and sweet for bitter!
Outside their misuse by Relativity and in the terms Relative Risk Reduction and Absolute Risk Reduction, the words “relative” and “absolute” are useful, valuable terms. They just don’t belong here.
The RRR should not have the word “risk” in it because it is at best an indirect measure of actual risk, and at worst has a prolific record of misleading people about actual risk, including doctors and even peer-reviewed researchers. The word “risk” in both the RRR and the ARR creates mental pressure in the uninitiated to understand in what sense the RRR “risk” is different than the ordinary meaning of the word “risk”, an understanding not present in the word “relative”. What it is “relative” to requires too much explanation, and once explained, is too hard to remember.
I think “Sick Rate Reduction” is a term that makes sense to voters and lawmakers with almost no explanation. It is a “rate” reduction, meaning a specific mathematical relationship whose significance will be affected by a factual or mathematical context, as opposed to being stand-alone information of value without further context. A “rate” is clearly distinct from “risk”. “Risk” means a fully processed conclusion ready to warn average readers and patients, with no further mathematical context.
I still haven’t figured out what “absolute” means in this context, where it is tasked with distinguishing itself from an RRR. But “Actual” has a clear meaning to anyone, and further distinguishes the ARR’s superior value in providing an honest grasp of risk. This word substitution allows the abbreviation to be retained with its current meaning, and will only replace “absolute” with “actual” to make it understandable. Sick Rate Reduction, SRR, is a term with only 9 Google returns, only one of which was in medicine, unless you count sick pigs in which case there were two. The term was not capitalized, indicating it was not recognized as a recognizable term with probable idiomatic additional meanings but was used for its clarity and simplicity of meaning. It is thus a term that won’t be confused with some other meaning. As for the abbreviation SRR, the other uses of that abbreviation I found at abbreviations.com all have meanings in narrow fields, none of which is medicine.
Violations of ARR v RRR Standards in Peer-reviewed Studies
The source of these excerpts: “Relative risk versus absolute risk: one cannot be interpreted without the other”, by Marlies Noordzij, Merel van Diepen, Fergus C. Caskey, Kitty J. Jager, Nephrology Dialysis Transplantation, Volume 32, Issue suppl_2, April 2017 [www.academic.oup.com/ ndt/article/32/suppl_2/ii13/3056571#64437158 Oxford Academic].
“In 1996, the first version of the Consolidated Standards of Reporting Trials (CONSORT) statement was published to improve the quality of the reporting of the results of RCTs. A second update of the guideline—published in 2010—recommends that both the relative effect and the absolute effect should be reported with their confidence intervals, as neither the relative nor the absolute measure alone gives a complete picture of the effect and its implications. In addition, the study group recommends that ‘for binary outcomes, the denominators or event rates should be reported so that readers can understand how risk ratios and risk differences are calculated’. So, results should not be presented solely as summary measures, such as relative risks.
“The ‘Strengthening the Reporting of Observational studies in Epidemiology’ (STROBE) statement for the reporting of results from observational studies such as cohort studies and case-control studies was published in 2007 [16, 17]. This guideline recommends ‘to consider translating estimates of relative risk into absolute risk if this is possible’. Although these two widely accepted and applied statements for the reporting of studies give clear recommendations about the reporting of relative and absolute measures of risk, it seems that not all their recommendations are very well adopted in practice. This was confirmed by a recent study by Rao et al. showing continuing deficiencies in the reporting of STROBE items and their sub-criteria in cohort studies focusing on chronic kidney disease. Their study demonstrated weak evidence of improvement in the overall reporting quality of cohort studies in nephrology between the period before and after publication of the STROBE statement.”
The authors summarize the issue: “When the outcome is rare in the general population, a large relative risk may not be so important for public health.”
They give an illustration from news headlines: “in 2013 newspapers reported a ‘70% increase in cancer risk’ among females exposed as infants to the Fukushima Daiichi nuclear disaster in Japan in 2011. This relative risk was drawn from statistics showing that about 1.25 out of every 100 girls (1.25%) in the area developed thyroid cancer due to the radiation exposure, instead of the natural rate of about 0.75%. Indeed, this is an increase of almost 70%. However, experts from the World Health Organization correctly emphasized that due to the low baseline rates of thyroid cancer, even a large relative increase represents a small absolute increase in risks of 0.50%.”
Violations of standards have been cataloged: “In 2011, Hochman and McCormick published a systematic review on endpoint selection and relative versus absolute risk reporting in published medication trials. For this purpose they analysed all randomized medication trials published in the six highest impact general medicine journals between June 2008 and September 2010 and determined the percentage of papers reporting results in the abstract [the introductory summary] only in relative terms.
“Of the 316 identified trials, 157 reported positive and statistically significant findings. Nevertheless, 69 (44%) of these positive trials reported only relative and no absolute measures of risk in their abstract.
“Similar findings were reported by Schwartz et al., who performed a survey of abstracts [the introductory summary] of 222 articles published in leading medical journals. They found that this problem was even larger in observational studies than in RCTs; in 62% of abstracts of randomized trials both relative and absolute risk measures were given, while this was only the case in 21% of abstracts of cohort studies.”
Missing Placebos, Missing Alternative Treatment
Neither the Denmark nor the Bangladesh studies had a placebe group; just a “control” (untreated) and a Treatment group. Nor did either study compare masks with any alternative way to address covid risk.
Normally a proper RCT (Randomized Controlled Trial) has a placebo group. The best RCT’s also compare a treatment with alternatives. So observes ValueInHealthJournal.com:
“The main difficulty in the comparison of different treatments lies in the fact that they are almost never compared, in a preplanned study, against each other. Instead, most studies compare the new treatment with a placebo.” ValueInHealthJournal.com
Placebo pills are easy. Patients have no way to tell what is inside the pill they are given. But how do you pass out placebo masks? How do patients not know if a mask is phony?
Well, there are actually masks sold which promise not to restrict the air flow at all, but only to fool mask checkers at hospital doors. I haven’t seen and felt them, so I have no sense of whether their use as placebos could fool anybody. Especially now that almost everyone in the world has worn paper or cloth masks. Perhaps the placebo group could be told they are testing a new mask with greater air flow but with special properties that zaps germs.
Gosh, do I actually hear myself suggesting to doctors how to trick people?!
How Pfizer used RRR’s to Fraudulently Inflate its Success
“The RCT method was applied to the Pfizer-BioNTech vaccine trials. The investigators randomly assigned 21,720 subjects 16 years and older to receive two doses of the new vaccine, and 21,728 subjects to receive two doses of placebo. They followed the subjects for a median of two months after the intervention.
“The trial compared the case numbers in the vaccinated vs control (placebo) groups where a case of COVID-19 was defined as an individual who experienced symptoms and had a positive test for SARS-CoV-2 infection. This is arguably a weak endpoint, as incidence of severe disease and death, the very outcomes one would hope the vaccine prevents, were not considered. Other data was collected, including the incidence of serious side effects.
“The trial reported eight cases of COVID-19 (as defined above) among the immunized group and 162 in the placebo group. So, the risk of COVID-19 in the immunized group was 8/21,720 = 0.037%, and the risk in the unimmunized group was 162/21,728 = 0.745%. The ARR is defined simply as the difference in risk between the two groups. In this case it would be = 0.745% – 0.037% = 0.708%; we will round it to 0.7%. The RRR is the ARR expressed as a percentage of the absolute risk of disease in the unvaccinated. [In other words, the percentage the vaccinated suffer, of the sickness that is suffered by the unvaccinated?] In this case, it is = 0.708/0.745 = 95%. [CER-EER/CER] This RRR is what is reported (this is standard practice) as the “efficacy” of the vaccine.
“The vaccine appeared to reduce the relative risk of COVID-19 (as defined by Pfizer) by an estimated 95% over the short duration of the trial, but the interpretation of that number is not that simple.
“Firstly we must understand the role of statistics here. If you toss a coin 10 times you would expect to get 50% heads and 50% tails on average. In practice, however, it would not be too surprising to obtain 7 heads and 3 tails in any 10 tosses of the coin. There are similar considerations that apply to any medical trial. Although the headline figure here is a 95% relative risk reduction, how confident are we that this figure is close to the truth? If we had run the trial at another time, might we have only recorded a value of 90% for the RRR? So any quoted reduction must also come with some indication of how “good” that number is. While the Pfizer trail had 40000+ participants, relatively few were infected with COVID, leaving the conclusions to be based on small numbers.
“In order to determine if the administration of the vaccine to the population is really beneficial, we also need to consider the actual risk of disease in those who did not receive the intervention. To illustrate with an exaggerated example, if the risk of acquiring a disease is only one in a million, reducing it by half, to one in 2 million is not a big deal. If, however, the risk of acquiring a disease is 30%, reducing the risk to 15% is very significant. If our proposed experimental treatment caused side effect deaths at a rate of one in a million we would be hesitant to recommend it in the above example, but we would be much more likely to recommend it for the latter.
“[Pfizer’s result] appears to be an impressive result, as there are more cases in the placebo group RELATIVE to the vaccinated group. But note the Y axis only goes to 2.5% – so that in total 2.3% of placebo patients became ill versus .3% of vaccinated patients. If we look at the ABSOLUTE RISK of each group, the results look far less impressive....
“...whilst we want to save lives, we also recognize that the vaccines, like all medical interventions, are not free from serious side effects. Even though only a small percentage suffer such effects, we must weigh this against the fact that we are also dealing with mostly small percentages of people (depending on personal risk factors) who die from COVID-19. The ARR and RRR are both important parameters that help us in addressing these complex issues.
“This illustrates why considering the ARR may be helpful. In the Pfizer clinical trial mentioned above, the risk of COVID-19 = 0.75%; so, reducing this risk by 95% does not seem like a very impressive effect.
“Whilst it is important to determine whether the vaccines are effective at reducing infection, it is equally important to know whether they improve health outcomes overall – is the benefit sufficient to justify the potential risk? For example, in the vaccine trial discussed above, there were 262 serious adverse events noted in the vaccinated group and 172 serious adverse events noted in the placebo group (which admittedly seems odd as one wouldn’t expect a saline injection to produce any adverse events). [Actually placebo groups often report side effects. Interesting.] Given that, for the vast majority, COVID-19 is not a serious illness, adverse events arising during the trials should also factor into our decision about overall suitability of the proposed measure.
“The logical conclusion is that the RRR and ARR of an intervention (in this case a vaccine) reported in a RCT should be interpreted carefully when making decisions about the desirability of implementing the intervention in the general population. It is not sound public health practice to say: ‘This vaccine is 95% effective, so let’s give it to everyone’.”
Another Analysis of ARR/RRR Misuse
"Relative risk reduction and absolute risk reduction measures in the evaluation of clinical trial data are poorly understood by health professionals and the public. The absence of reported absolute risk reduction in COVID-19 vaccine clinical trials can lead to outcome reporting bias that affects the interpretation of vaccine efficacy....[Pfzier reports 95.1% efficacy, Moderna reports 94.1% efficacy.]...Unreported absolute risk reduction measures of 0.7% and 1.1% for the Pfzier/BioNTech and Moderna vaccines, respectively, are very much lower than the reported relative risk reduction measures. Reporting absolute risk reduction measures is essential to prevent outcome reporting bias in evaluation of COVID-19 vaccine efficacy."
This the abstract from "Outcome Reporting Bias in COVID-19 mRNA Vaccine Clinical Trials" by Ronald Brown, February 26, 2021.
CDC Perversion of Reality
“A 2018 review of 52 randomized trials for influenza vaccines that studied over 80,000 healthy adults reported an overall influenza vaccine EER [experimental event rate] of 0.9% and a 2.3% CER, [control event rate] which calculates to a RRR of 60.8%. This vaccine efficacy is consistent with a 40% to 60% reduction in influenza reported by the Centers for Disease Control and Prevention (CDC).
“However, critically appraising data from the 2018 review shows an overall ARR of only 1.4%, which reveals vital clinical information that is missing in the CDC report. A 1.4% ARR works out to a NNV [number needed to vaccinate] of approximately 72 people, meaning that 72 individuals need to be vaccinated to reduce one case of influenza. By comparison, Figure 2 of the present article shows that the NNV for the Pfzier-BioNTech and Moderna vaccines are 142 (95% CI 122 to 170) and 88 (95% CI 76 to 104), respectively.”
This is the study that is the subject of “500 doctors want to know” below.
RRR v. ARR Explanations by Others
Dr. Phillip Lee Miller
writes, “I am always waiting for that ‘aha moment”’when you understand how relative risk management is chicanery. It is used to sell you product. To amplify, inflate or conflate results.” He says most doctors just read “an abstract of the results of the study. And so frequently that is all you will see and believe. Because most people, including even most physicians, will not read or analyze the paper. We are too busy.”
He quotes from a book he recommends. He says “The relative risk reduction looks more impressive than absolute risk reduction. Relative risks are larger numbers than absolute risk and therefore suggest higher benefits than really exist.”
He explains the difference between ARR (Absolute Risk Reduction) and RRR (Relative Risk Reduction) and concludes “This is how they fool you. The relative risk reduction is independent of the sample size.”
RRR's Mislead Patients
“The framing of benefit or risk in relative versus absolute terms [RRR v. ARR] may have a major influence on patient preference. The medication whose benefits were expressed in relative terms was chosen by 56.8% of patients, whereas 14.7% chose the medication whose benefit was expressed in absolute terms.” That was the finding of Malenka DJ, Baron JA, Johansen S, et al. The framing effect of relative and absolute risk. J Gen Intern Med 1993;10:543–8. I found the stat at article/S1098-3015(10)60033-2/pdf?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS1098301510600332%3Fshowall%3Dtrue ValueInHealthJournal.com.
Should you wear a rubber suit to protect yourself from lightning?
This illustration of the difference between ARR’s and RRR’s is posted at Straight2Point. This is my summary:
Extreme examples often help explain technical ideas.
The Acme Rubber Company made hooded rubber suits to protect people who are struck by lighting. They advertised that “our suits slash your risk of dying, when you are struck by lightning by 100 to 1! For every 100 deaths by lightning in non-suit wearers there is only one death in suit wearers!” That is the RRR, the Relative Risk Reduction. Who wouldn’t want to reduce their risk of dying, while being struck by lightning, to 1% of the death rate of non-rubberized citizens? The suits are a hundred times more effective!
But your chance of being struck by lightning during your lifetime is one in 15,300. And only one in ten who are struck by lightning are killed by it, so your chance of being killed by lightning drops to one in 153,000.
There are about 27 lightning fatalities a year in the U.S. So if your new rubber suit can slash your risk from one in 153,000 to one in 15,300,000, your ARR, the amount of risk you reduce by wearing a rubber suit all the time, is 0.0000065359% - 0.0000000653% = 0.0000064706%. (I think. Actually when I checked this on my calculator it shorted out.)
So you can see how much better a salesman you are to advertise that your rubber suit makes you 100 times safer when you are struck by lightning, than to say “our suits reduce you risk of death from being struck by lightning by 0.0000064706%!”
The ARR is a valuable measure of whether wearing a rubber suit, or wearing a mask, is worth doing. The SRR is a valuable sales tool for getting you to do it.
Bangladesh covid sick rates of both maskers and nomaskers were less than 1%. The difference between them, the ARR, was only a tenth of one percent. The researchers never reported that figure. The reported the SRR, the ratio between the two sick rates without the context of both of them being less than 1% out of the whole groups. The SRR was 100 times greater. The CDC likewise quoted the SRR, not the ARR, from Bangladesh. Denmark's research produced a nearly identical SRR and ARR but the researchers only reported the ARR and never mentioned the SRR. That caused a delay of several months before any peer reviewed journal would publish it, and it caused the CDC to not report its findings but only to denigrate them as "small" and "inconclusive".
500 Doctors Want to Know
A statistician [I guess that he was] blogged that 500 Doctors Want to Know if it is really true that reporting only the RRR is misleading. He said a doctor wrote to him about an article explaining how Pfizer covid vaccine reports mislead by reporting only the RRR: “What are your thoughts on this paper?....There are many of us MD’s who are quite foxed. If you blog about it, please don’t mention my name and just say a doctor on a 500-member listserv asked you about this. And send me the link to that blog article please. There are at least 500 of us doctors who would love to be enlightened.”
The paragraph asked about said a 2018 review of influenza vaccines by the CDC reported a 40-60% reduction in influenza, but that only compared the 2.3% sick rate for “controls” with the 0.9% rate for those vaccinated. The honest risk reduction was only 1.4%. “A 1.4% ARR works out to a NNV [number needed to vaccinate] of approximately 72 people, meaning that 72 individuals need to be vaccinated to reduce one case of influenza.” (A number of 20-50 is considered a good score.) “By comparison, ...the NNV for the Pfzier-BioNTech and Moderna vaccines are 142 (95% CI 122 to 170) [we can be 95% confident that the most people needed to vaccinate, to save one person from getting covid, is 170, and maybe it will only take 122] and 88 (95% CI 76 to 104), respectively. ”
The answer of the statistician concerns me more than that 500 doctors don’t know whether to be concerned that Pfizier and the CDC are fraudulently reporting RRR’s without ARR’s. He at least acknowledges that “Absolute risk does matter in some settings—for example, we wouldn’t be so article interested in a drug that prevents 50% of cases in a disease that only affects 2 people in the world.”
But he doesn’t seem to think that principle applies to mask studies where 99% of untreated people don’t get sick. Or, where 97.7% of them don’t get sick – he says the sick rate is 2.3%.
Well, wait: no, it’s not that he denies that rate is insignificant, but that he doesn’t believe that rate! He says “...coronavirus is not a rare disease. Presumably the rate of infection was so low in those studies only because the participants were keeping pretty careful, but the purpose of the vaccines is to give it to everyone so we don’t have to go around keeping so careful.”
What a reason to dismiss the results of a trial with thousands of participants, that is one of the mostly closely watched trials in medical history! (One of the “comments” posted after the Denmark study complained “This study received 90,000 tweets by 60,000 users within 4 days of publication. The majority of these tweets championed the study as evidence of the impotence of masks in the control of the COVID-19 pandemic.”)
He alludes to Wikipedia’s article. It says “Relative risk is commonly used to present the results of randomized controlled trials. This can be problematic if the relative risk is presented without the absolute measures, such as absolute risk, or risk difference. In cases where the base rate of the outcome is low, large or small values of relative risk may not translate to significant effects, and the importance of the effects to the public health can be overestimated. Equivalently, in cases where the base rate of the outcome is high, values of the relative risk close to 1 may still result in a significant effect, and their effects can be underestimated. Thus, presentation of both absolute and relative measures is recommended.”
I wish he gave an example of how RRR can cause an underestimation of benefit. It seems that the higher the sick rate, the less misleadibng RRR becomes. I can see how the RRR can be useful to compare multiple treatments. But not when there are only those treated and those not treated, and the sick rate is only 1%.
Posted here. “Statistical analyses of data and making sense of medical data have received much attention in the medical literature, but nevertheless have caused confusion among practitioners [over terms like] odds ratios, relative risk, relative risk reduction, absolute risk reduction, and the number needed to treat]....At the mention of the term ‘statistics’, most physicians react with a groan of confusion and annoyance.”
Researchers “found that the framing of benefit or risk in relative versus absolute terms may have a major influence on patient preference. The medication whose benefits were expressed in relative terms was chosen by 56.8% of patients, whereas 14.7% chose the medication whose benefit was expressed in absolute terms. Malenka DJ, Baron JA, Johansen S, et al. The framing effect of relative and absolute risk. J Gen Intern Med 1993;10:543–8.”
I talked to a woman whose previous job was answering doctors’ questions about what research showed about various drugs. At the time I was trying to understand “95% Confidence Intervals”, so I asked her about them. She had never heard of them. She was fuzzy about the difference between RRR’s and ARR’s. She said she skipped over the statistics math. Mostly she just read the abstracts.
Yet doctors trusted her.
Truth In Advertising Laws
Lawmakers could heal a lot of fraud and medical waste by simply requiring advertisers who make claims about rates of the reduction of sickness or other medical issues, to report the ARR as well as the RRR (SRR, I call it). The FTC already has a huge Truth In Advertising bureaucracy. It's Health wing goes to a lot of expense investigating claims of efficacy of supplements where there is no peer-reviewed research. A simple rule requiring ARR reporting would level the bias against alternative medicine by focusing on the exaggerated claims of alternative medicine [ignorance] while ignoring the exaggerated claims [fraud] of FDA approved medicine, without requiring expensive investigations.
One More Example
Suppose a researcher followed one million volunteers, half jabbed and half unjabbed, for one hour, and found that one jabbed volunteer and two unjabbed volunteers got sick during that hour. So the researcher told reporters, "put off the jab and you face a whopping 0.000004% chance, 2 in 500,000, of catching covid. But get the jab like a good little boy, and you slash your danger to a mere 0.000002% chance, 1 in 500,000, of catching covid. To put this in scientific terms, the difference between 0.000004% and 0.000002% is 0.000002%, which is how much better your odds are if you get jabbed. We call this the ARR, Absolute Risk Reduction."
The reporter says, "Not much difference, huh?" and starts to walk away.
The researcher shouts, "No wait! I just told you the facts. Now let me give you something you can quote: 'people who don't get jabbed are twice as likely to catch covid.'"
The puzzled reporter says "But you just said..."
The researcher explains, "Two people in the unjabbed group got sick, but only one in the jabbed group. Not getting jabbed doubles your risk! See, scientists call this the RRR, the Relative Risk Reduction, where we just compare the numbers from the jabbed and the unjabbed groups."
See? Both figures are true. The unjabbed are twice as likely to get sick, and jabbing increases your protection by 0.000002%.
WHICH FIGURE MOST HONESTLY MEASURES THE PROTECTION OFFERED BY JABS?
WHICH FIGURE MORE LIKELY PERSUADE THE PUBLIC TO GET JABBED?
WHICH FIGURE IS BEING REPORTED BY CDC, GOVERNMENT, AND MEDIA?
Parachute use to prevent death and major trauma when jumping from aircraft: randomized controlled trial
Bonus Article: Understanding RCT’s
What’s the big deal about an RCT? (Randomized Controlled Trial)? This trial is especially for readers who aren’t sure what an RCT is. After you read this one, then for the rest of your life, you will at least remember what an RCT is.
This trial is actually published by the BMJ Publishing Group Limited.
Here is the summary:
“Objective: To determine if using a parachute prevents death or major traumatic injury when jumping from an aircraft.
“Design: Randomized controlled trial.
“Setting: Private or commercial aircraft between September 2017 and August 2018.
“Participants: 92 aircraft passengers aged 18 and over were screened for participation. 23 agreed to be enrolled and were randomized.
“Intervention: Jumping from an aircraft (airplane or helicopter) with a parachute versus an empty backpack (unblinded).
“Main outcome measures: Composite of death or major traumatic injury (defined by an Injury Severity Score over 15) upon impact with the ground measured immediately after landing.
“Results: Parachute use did not significantly reduce death or major injury (0% for parachute v 0% for control; P>0.9). This finding was consistent across multiple subgroups. Compared with individuals screened but not enrolled, participants included in the study were on aircraft at significantly lower altitude (mean of 0.6 m for participants v mean of 9146 m for non-participants; P<0.001) and lower velocity (mean of 0 km/h v mean of 800 km/h; P<0.001).
“Conclusions: Parachute use did not reduce death or major traumatic injury when jumping from aircraft in the first randomized evaluation of this intervention. However, the trial was only able to enroll participants on small stationary aircraft on the ground, suggesting cautious extrapolation to high altitude jumps. When beliefs regarding the effectiveness of an intervention exist in the community, randomized trials might selectively enroll individuals with a lower perceived likelihood of benefit, thus diminishing the applicability of the results to clinical practice.”
The “study” goes on like that for several pages. Hilarity in every sentence. Read it. You won’t be sorry.
Nearly hidden among the jokes are some serious applications to medicine. “This could raise concerns for supporters of evidence-based medicine, because numerous medical interventions believed to be useful have ultimately failed to show efficacy when subjected to properly executed randomized clinical trials.”
The fact that no one jumped out of a plane higher than two feet off the ground – a young girl is shown jumping off the bottom wing of a parked biplane – is made a metaphor of - hmmm. I can't figure out what it is a metaphor of. But I am sure it is a very good metaphor of something.
There is a dig at studies with such a low “event rate” (sick rate) that their results are “statistically insignificant”. Insignificant results are no basis for national mandates. (Except that the reason the results were insignificant in this “study” was that both “event rates” were zero, because no one was in either “arm” of the trial.) “Discussion: We have performed the first randomized clinical trial evaluating the efficacy of parachutes for preventing death or major traumatic injury among individuals jumping from aircraft. Our groundbreaking study found no statistically significant difference in the primary outcome between the treatment and control arms. Our findings should give momentary pause to experts who advocate for routine use of parachutes for jumps from aircraft in recreational or military settings.”
The third paragraph of the discussion applies much better to masks than to parachutes: “Beliefs about the efficacy of commonly used, but untested, interventions often influence daily clinical decision making. These beliefs can expose patients to unnecessary risk without clear benefit and increase healthcare costs. Beliefs grounded in biological plausibility and expert opinion have been proven wrong by subsequent rigorous randomized evaluations.The PARACHUTE trial represents one more such historic moment.”
Nearly identical results, nearly opposite spin in the Only Two Mask&Covid RCT's
(A subsection of Part 1. Featured in this section:)
Denmark and Bangladesh: nearly identical results, nearly opposite spin The ARR’s and SRR’s (RRR’s) of both studies are very similar. But the ARR was focus of the Denmark report, while the Bangladesh report boasted about the SRR without mentioning the ARR or even making the calculation.
CATO: Only 2 High Quality RCT's - Bangladesh and Denmark The Cato Institute analyzed hundreds of mask studies, focusing on ARR’s, ignoring SRR’s (RRR’s). Result: masks don’t work.
DENMARK: What the Study Showed Among the details reported here but omitted in the preceding reviews are an explanation of probability statistics, which is critical to understanding why we can’t be sure that masks help even 0.1%. Maybe they harm, not just by reducing oxygen which contributes to many medical conditions, but by increasing covid infection. The CDC’s dismissal of the Denmark study as “small” and “inconclusive” is addressed. BANGLADESH ARR’s v. RRR’s: Research Fraud The researchers, though boasting of a 10% reduction of covid from wearing masks, betrayed their knowledge of the futility of masks by calculating that it takes 35,001 people wearing masks all the time to prevent one covid death! But their probability calcuation shows that may be optimistic. The covid reduction of masks might be zero. The CDC latches on to the 10% reduction claim in a breathtakingly simplistic and biased review.
CDC: Miracle Masks CDC director Walesky tweeted that masks reduce covid 80%! No evidence was linked as the source of that claim! I’ve not heard of even RRR’s claiming such a miracle!
Masks reduce covid by a tenth of a percent. 0.1%. That is, the percentage of mask wearers that got sick was 0.1% lower than the percentage of nomaskers that got sick, in both studies.
The Actual Risk Reduction you get from wearing a mask all the time, therefore, is 0.1%.
There have been only two RCT’s – Randomized Controlled Trials – on how well masks block covid: in Denmark, November 2020, and Bangladesh, April 2021. Their figures both show a risk reduction of one tenth of one percent.
Except that the authors of one of them claim that means masks reduce covid by 10% - 100 times higher! If they hadn’t done that, this article would be a lot shorter.
And less interesting.
But first let’s put some terminology through our BWG (Big Word Grinder). RCT’s. There have been many mask studies. Only two RCT’s. “Why does that matter?” you ask. “What’s so special about an RCT? Are they canceled out by other studies that aren’t RCT’s?”
RCT’s: “Gold Standard” of Research
Remember when the “pandemic” was young, March, 2020, and a few doctors actually lost their medical licenses for treating covid with hydroxychloroquine (HCQ)? Pharmacists wouldn’t even fill doctors’ prescriptions for HCQ, when they thought doctors prescribed it for covid. “But HCQ quickly cured all of our covid patients”, the doctors complained. “And look at all the studies showing HCQ cures covid!”
‘“Ah, but those studies aren’t RCT’s”, said the authorities who drove those doctors out of medicine. “Randomized Controlled Trials are the Gold Standard of research. All you have is anecdotal evidence. Good bye!”
RCT’s are studies with one large group receiving a treatment and a parallel large group not receiving anything, and maybe a third group receiving a placebo – something that looks like a treatment but doesn’t physically do anything. That’s the “Gold Standard” for measuring the benefits of a treatment.
Well, the only existing “Gold Standard” RCT’s on mask effectiveness tell us masks don’t help. The Cato Institute reviewed the evidence, and agrees. Here’s how Dr. Martin Kulldorff, senior scientific director of the Brownstone Institute, summarized the Cato study according to an Epoch Times report:
Kulldorff: “The truth is that there have been only two randomized trials of masks for COVID. One was in Denmark, which showed that they might be slightly beneficial, they might be slightly harmful, we don’t really know—the confidence interval kind of crossed zero,” he said. “And then there was another study from Bangladesh where they randomized villagers to masks or no masks. And the efficacy of the masks was for reduction of COVID was something between zero and 18 percent. So either no effect or very minuscule effect.”
Kulldorff had read the Bangladesh study itself – not just Cato’s review of it. Because the Cato review nowhere talks about a range of results that reaches all the way to 18%. All Cato says is that the Bangladesh study finds a 0.09% benefit.
Cato: “Researchers also reported results by mask type, finding that surgical masks reduced symptomatic seroprevalence [covid symptoms confirmed by blood tests] rates by 0.09% compared to controls (0.67% vs. 0.76%, P=0.043)”
An 18% benefit is 200 times greater than a 0.09% benefit. Kuldorff must have been referring to a Bangladesh claim that masks reduce covid 9%, and another claim that probability calculations stretch that 9% all the way from a possible 18% benefit back down to a 0% benefit. More about that below.
Denmark and Bangladesh: nearly identical results, nearly opposite spin
In Denmark, 22 of about 1,125 mask wearers – 2.0%, got sick. 53 of about 2,470 nomaskers – 2.1%, got sick. [2.1457%, to be exact.] The difference between 2.1% and 2.0% is 0.1%. That 0.1% is your “Actual Risk Reduction” (ARR).
To repeat: Your risk, if you never wear a mask, is 2.1%. 2.1% of nomaskers get sick. Your risk, if you wear a mask all the time, is 2.0%. If you wear a mask all the time, you reduce your risk by 0.1%.
One tenth of one percent. Well actually 0.15%.
(Actually there is a slight contradiction, probably due to rounding. We are told that the sick rate of the maskers was 2.0%, and that the difference between that and 2.1%, the nomasker sick rate, is 0.2%. On my calculator, which may be too old to understand “the new math”, 2.1 – 2.0 = .1, not .2.
(Here is the claim from the study: When the masker count “included only participants reporting wearing face masks ‘exactly as instructed,’ infection (the primary outcome) occurred in 22 participants (2.0%) in the face mask group and 53 (2.1%) in the control group (between-group difference, - 0.2 percentage point”.
(We aren’t told now many mask wearers wore “exactly as instructed”, but we are told that 22 of them got sick, which represents 2.0% of them. If it were exactly 2.0%, then there were 1100 total who wore “exactly as instructed.” Because 22 / 2.0% = 1100.
(Table 2 gives the actual number of nomaskers who got sick and who didn’t, so we can see that 2.1% is rounded from 2.1457%. If the precise unrounded sick rate of maskers who wore “exactly as instructed” was as low as 1.956%, then the difference between it and 2.1457% would be greater than 0.15% so the difference could correctly be rounded up to 0.2%.
(If exactly 1125 maskers wore “exactly as instructed”, then their sick rate would be precisely 1.956%. So the number must be at least 1126. But if the number were even four persons more, then the sick rate would be 1.948%, which should require rounding the masker sick rate down to 1.9%. So to qualify as a sick rate of 2.0%, and yet to have the difference between that and 2.1% be 0.2%, the number of maskers wearing “exactly as instructed” must have been between 1126 and 1129.
(That is why I will start reporting this difference as 0.15%. Not 0.2%, not 0.1%.
(It seems odd to me to report without explanation that the difference between 2.1% and 2.0% is 0.2%. But what do I know? I’m just a trumpet player.)
Before the 54% of maskers who didn’t wear their masks “exactly as instructed” were removed from the count, the Denmark researchers figured a risk reduction from masks of three tenths of one percent. “the between-group difference was 0.3%.” 2.1% of nomaskers (53 of 2,470), minus 1.8% of maskers (42 of about 2,392). Wearing masks “exactly as instructed” apparently reduced their effectiveness!
The Denmark researchers honestly admitted that their study could prove no benefit from mask wearing. That is, unless you count, as enough effectiveness to require masks for everyone, an approximately one tenth of one percent reduction of your risk, give or take a margin of error of two tenths of one percent: “... the findings were inconclusive and cannot definitively exclude a 46% reduction to a 23% increase in infection of mask wearers in such a setting.”
In Bangladesh, the ARR was even lower: only 0.08%. 1,142 out of 168,000 mask wearers – 0.68%, got sick. 1,277 out of 168,000 nomaskers – 0.76%, got sick. The difference between 0.76% and 0.68%: 0.08%. Your “Absolute Risk Reduction” (ARR) from wearing a mask all the time is 0.08%. Your risk, if you never wear a mask, is 0.76%. 0.76% of nomaskers get sick. If you wear a mask all the time, you reduce your risk by 0.08%. Except that the researchers claimed masks reduce covid by a whopping 10%!!! 100 times the measly tenth of one percent admitted in Denmark! How did they DO that?!!
CATO: Only 2 High Quality RCT's - Bangladesh and Denmark - No Benefit Proved
November 8, 2021: A Cato Institute Working Paper analyzes "the available clinical evidence of facemask efficacy": "sixteen identified randomized controlled trials" and "sixteen quantitative metaanalyses". (A "meta-analysis" is a critical review of most, if not all available, research published in peer-reviewed journals.)
The Cato abstract states: "...evidence of facemask efficacy is based primarily on observational studies that are subject to confounding [To cause to become confused or perplexed; To fail to distinguish; mix up] and on mechanistic studies [mechanical measurements by various contraptions] that rely on surrogate endpoints [substitute things measured, other than actual infection rates in real people with or without masks] (such as droplet dispersion) as proxies for disease transmission.
“The available clinical evidence of facemask efficacy is of low quality and the best available clinical evidence has mostly failed to show efficacy, with fourteen of sixteen identified randomized controlled trials comparing face masks to no mask controls failing to find statistically significant benefit in the intent-to-treat populations.
“Of sixteen quantitative metaanalyses, eight were equivocal or critical as to whether evidence supports a public recommendation of masks, and the remaining eight supported a public mask intervention on limited evidence primarily on the basis of the precautionary principle. [We have no evidence they help, but lets wear them because they might.] Although weak evidence should not preclude precautionary actions in the face of unprecedented events such as the COVID-19 pandemic, ethical principles require that the strength of the evidence and best estimates of amount of benefit be truthfully communicated to the public."
Notice that the alleged existence of "weak evidence" does not mean there is any proof of any benefit at all. The authors aren't actually saying there is any evidence, but they use the phrase to hypothetically say "even though the evidence is weak to zero, it is OK to err on the side of safety, but we should be honest." There is zero proof, in Kulldorf's assessment, with which my own reading of the studies agrees.
Here is how Cato analyzes Denmark study - its analysis of Bangladesh is farther below:
Cato on Denmark: No "Statistically Significant" Benefit
“One study of 4862 participants in Denmark (“DANMASK”) who reported being outside the home for more than 3 hours per day found no statistically significant difference [enough difference to be certain of any difference; a difference greater than the "margin of error"] between a group receiving a recommendation to wear a surgical mask when outside the home and the control group (1.8% (n=42) of the masked intervention group became infected vs. 2.1% (n=53) of the control group). [“n” means this is the actual number of people.] The DANMASK study relied on self-reported adherence [to wearing their masks], was not designed to test the efficacy of masks as source control, and did not consider whether COVID-19 positive participants were infected in the home, among other limitations.
(My comment so far: being unmasked at home is an appropriate element of the research since virtually nobody, I hope, wears masks in their own home! Calling these elements "limitations of the study" is not an accusation of negligence on the part of the researchers, since it is not clear what could have been done differently to avoid these "limitations". Perhaps the point about catching covid at home was thought necessary because that point was in one of the responses from other researchers included in the "comments" after the study. The point was not thought worth mentioning in the Bangladesh study, even though in that study no one was even asked to wear masks inside their homes. To the contrary, they were instructed, the study stated: "Adult household members were asked to wear masks whenever they were outside their house and around other people")
DENMARK: What the Study Showed
In late October, 2020, there was an article about how long this peer-reviewed study has waited for publication. It contained hints about the nature of the study results, such as "This study will be published as soon as a journal is brave enough." That article must have shaken something loose, because three weeks later, November 18, it was published. The study indeed seriously challenges the assumptions supporting public mask wearing.
3030 participants wore surgical masks, of whom 42 (1.8%) got sick. 2994 didn't, of whom 53 (2.1%) got sick. That difference is not "statistically significant".
Here is the math they offer to explain the statistical insignificance of that 0.3% difference: "The between-group difference was −0.3 percentage point (95% CI, −1.2 to 0.4 percentage point; P = 0.38) (odds ratio, 0.82 [CI, 0.54 to 1.23]; P = 0.33). Multiple imputation accounting for loss to follow-up yielded similar results. Although the difference observed was not statistically significant, the 95% CIs are compatible with a 46% reduction to a 23% increase in infection."
That means that masks might reduce infection by 46%, or they might increase infection by 23%, for all these numbers tell us. Later the numbers were presented as: "the findings were inconclusive and cannot definitively exclude a 46% reduction to a 23% increase in infection of mask wearers in such a setting. " The researchers had expected to prove a 50% reduction in infection from mask wearing. That didn't happen.
The study summarized previous mask studies:
A systematic review of observational studies reported that mask use reduced risk for SARS, Middle East respiratory syndrome, and COVID-19 by 66% overall, 70% in health care workers, and 44% in the community (12).
However, surgical and cloth masks were grouped [not tested separately as in this study which used only "high-quality surgical masks with a filtration rate of 98%"] in preventive studies, and none of the 3 included non–health care studies related directly to COVID-19. Another systematic review (18) and American College of Physicians recommendations (19) concluded that evidence on mask effectiveness for respiratory infection prevention is stronger in health care than community settings.
Here is a surprising finding that makes little sense: "A total of 52 participants in the mask group and 39 control participants reported COVID-19 in their household. Of these, 2 participants in the face mask group and 1 in the control group developed SARS-CoV-2 infection, suggesting that the source of most observed infections was outside the home." !!!
The participants contracted other viruses. 9 who wore masks, 11 who did not. However, the study was not "powered" to [focused on] accurately measure that.
Conclusion: "...a recommendation to wear a surgical mask when outside the home among others did not reduce, at conventional levels of statistical significance, incident SARS-CoV-2 infection compared with no mask recommendation."
Now watch this careful wording: "The findings, however, should not be used to conclude that a recommendation for everyone to wear masks in the community would not be effective in reducing SARS-CoV-2 infections, because the trial did not test the role of masks in source control of SARS-CoV-2 infection." In other words, all that was proved was that wearing a mask won't protect YOU. The study doesn't indicate if it protects others FROM you.
(How could you measure such a thing? You would have to take 3,000 people coughing and sneezing with covid, put masks on them, expose them to tens of thousands of healthy people who can't possibly catch covid from anyone else, and see how many they infect?)
The authors theorize that perhaps there is so little difference between wearing or not wearing masks because the droplets carrying covid measure billionths of an inch after all, (aerosols), rather than the millionths of an inch that masks can stop: "How SARS-CoV-2 is transmitted—via respiratory droplets, aerosols, or (to a lesser extent) fomites—is not firmly established. Droplets are larger and rapidly fall to the ground, whereas aerosols are smaller (≤5 μm) and may evaporate and remain in the air for hours (39). Transmission of SARS-CoV-2 may take place through multiple routes. It has been argued that for the primary route of SARS-CoV-2 spread—that is, via droplets—face masks would be considered effective, whereas masks would not be effective against spread via aerosols, which might penetrate or circumnavigate a face mask (37, 39). Thus, spread of SARS-CoV-2 via aerosols would at least partially explain the present findings."
Denmark, Probability, and Plain Misunderstanding
"Fact checker” Jessica McDonald’s attempt to minimize the Denmark study makes a great illustration of how ignorance of probability stats, combined with ignorance of the difference between ARR’s and RRR’s, combined with the usual cornucopia of caveats that scientists include to stave off lawsuits, supply liberal news reporters with as much power to indulge every naughty fantasy as that of a child inheriting a candy factory.
“Danish Study Doesn’t Prove Masks Don’t Work Against the Coronavirus” was her headline at factcheck.org, posted on November 25, 2020. She wrote:
“Q: Did a recent study in Denmark show that face masks are useless for COVID-19? “A: No. The study found that face masks did not have a large protective effect for wearers — not that masks provide no protection at all or don’t offer benefits to others. ….even the authors of the study say the results shouldn’t be interpreted to mean masks shouldn’t be worn.”
Well yeah that’s what they said to avoid lawsuits, but neither did they say masks do any good at all.
“The study didn’t identify a statistically significant protective effect for wearers, but the trial was only designed to detect a large effect of 50% or more.”
Well, 50% Actual Risk Reduction is what they expected. But that doesn’t mean the study was NOT designed to verify a SMALL effect. Their conclusion was very precise, statistically: the effect was a little on either side of zero. Maybe an infinitesimal benefit, maybe an infinitesimal harm. Benefit or harm, can’t be sure. Infinitesimal, we can be sure.
“And the study didn’t weigh in on the ability of masks to prevent spread of the virus from wearers to others, or what’s known as source control, which is thought to be the primary way that masks work.”
Well that might be because such a test is impossible, unless you take a thousand coughing, sneezing covid sufferers in a population where no covid exists, and see how many get sick. But the fact that is impossible is probably the Machiavellian reason the CDC says that is the primary way masks work; it’s a way to allege a benefit which no one can disprove. No evidence exists to indicate your mask protects others from you. It is a claim made without evidence, made safely since the claim has eluded a test design.
But it is hard to imagine anything about masks that would stop virus from going through them one direction but not the other. The size of the virus compared to the size of holes in masks has been compared to flies going through a chain link fence. After they find a way through, what stops them from turning around and coming back through from the other direction?
“As a result, the most that can be said is that this particular study, under the conditions at the time in Denmark, didn’t find that the face mask intervention had a large protective effect for wearers — not that masks provide no protection at all or don’t offer benefits to others. ”
Obviously this author did not read the study.
“Another post inaccurately described the results as ‘conclusive,’ despite the fact that the authors specifically wrote that their findings were ‘inconclusive.’”
Well, the authors said that, but only in the context of whether the infinitesimal impact of masks was beneficial or harmful. There was nothing inconclusive about the fact that the impact of masks is infinitesimal. “Yet another from Sharyl Attkisson, who has previously spread misinformation about vaccines, misleadingly states that there was ‘no statistically significant difference when it comes to wearing a mask or not outside the home to prevent Covid-19 spread.’”
But that is precisely what the study concluded. Obviously this author did not read the study. Wait, look what she quotes next from the study:
“Given the observed number of infections in each group, the plausible effect of the mask intervention ranged all the way from a 46% decrease in infection to a 23% increase. “It’s this negative result that some have interpreted to mean that masks are ineffective. But that’s not how the authors frame their findings.”
“Bundgaard, et al.: Our results suggest that the recommendation to wear a surgical mask when outside the home among others did not reduce, at conventional levels of statistical significance, the incidence of SARS-CoV-2 infection in mask wearers in a setting where social distancing and other public health measures were in effect, mask recommendations were not among those measures, and community use of masks was uncommon. Yet, the findings were inconclusive and cannot definitively exclude a 46% reduction to a 23% increase in infection of mask wearers in such a setting. It is important to emphasize that this trial did not address the effects of masks as source control or as protection in settings where social distancing and other public health measures are not in effect.”
It is unclear to me how Jessica imagines some manner of “framing” the results by the authors somehow cancels the fact that the results show masks may actually spread more covid. But if the hope she sees for masks is in that 46% reduction in infection, then let’s go over the numbers she glosses over.
The numbers below show that the actual infection in people without masks was only 2.1% of the 2470 nomaskers – 53 people. 2417 remained healthy. Dropping infections 46% lower than 2.1% is mathematically impossible.
The possible 46% reduction is in the sick rate. That is, 46% x 2.1% = 1.13%. The sick rate, 2.1%, is already so low that a 46% reduction of it will be microscopic. Those odds in Denmark allow for the sick rate to drop from 2.1% all the way down to 1.13%. In other words, those odds say an Actual Risk Reduction of almost one percent is possible – 0.97%. If the odds are in your favor, wearing a mask all the time will reduce your actual risk of getting covid by almost one percent.
However, if the odds are against you, wearing a mask all the time might actually INCREASE your risk of getting covid, by 0.48%. That is, your Actual Risk Reduction will be a negative number: – 0.48%, because that possible outcome would not be a “reduction” but an increase.
Jessica quoted from the next to last paragraph of the study. Here is the first paragraph from the study which gives that information with a little more detail:
“Results: A total of 3030 participants were randomly assigned to the recommendation to wear masks, and 2994 were assigned to control; 4862 completed the study. Infection with SARS-CoV-2 occurred in 42 participants recommended masks (1.8%) and 53 control participants (2.1%). The between-group difference was −0.3 percentage point (95% CI, −1.2 to 0.4 percentage point; P = 0.38) (odds ratio, 0.82 [CI, 0.54 to 1.23]; P = 0.33). Multiple imputation accounting for loss to follow-up yielded similar results. Although the difference observed was not statistically significant, the 95% CIs are compatible with a 46% reduction to a 23% increase in infection.”
How many news reporters are prepared to process all that stuff about percentage points and CI’s and P’s? But “46% reduction to a 23% increase in infection” SOUNDS like something anyone can understand, right?
But the 46% reduction v. 23% increase is of the sick rate. Not of the 'risk'.
The sick rate of “controls” (those not treated; those without masks) was 2.1%. Out of about 2400 other nomaskers, 98% of whom never got sick. Only 2.1% got sick. The sick rate of “maskers” was 1.8%, according to this paragraph. (Later those not wearing masks “exactly as instructed” were removed from the count, and the sick rate rose to 2.0%.) So, this paragraph says, the difference between the two sick rates was 0.3%. That’s how much 2400 people reduced their risk of getting covid by wearing masks all the time when they were away from home. 0.3%. Whoopee.
0.3% is 18% of 2.1%, so what statisticians call the RRR, Relative Risk Reduction, is 18%. This is the ratio reported in TV commercials: This pill reduced pimples by 18%. Well, the RRR is a term whose words don’t well match its meaning. All it is, is the Sick Rate Reduction. The sick rate, only 2.1%, was reduced by 18%, all the way down to 1.8%. But the Actual Risk Reduction, considering the very low risk since 98% of the group never got sick, was only 0.3%.
(Actually there is a lot of rounding in these figures, so if you try to run them on your calculator, your results won’t quite match. Here are the numbers with four places added:
Table 2 says that out of 2470 nomaskers, 53 got sick. Their sick rate is: 53 / 2470 = 2.1457%
Out of 2392 maskers, 42 got sick. Their sick rate is: 42 / 2392 = 1.7558%The Actual Risk Reduction, ARR, is the difference: 2.1457 – 1.7558 = 0.3899%
0.3899% is the Actual Risk Reduction, meaning if you wear a mask all the time you will slash your risk of getting covid from a whopping 2.1457% down to a scant 1.7558% risk – an ARR of 0.3899%.
But if you are a mask salesman, you won’t want anything to do with the ARR, the Actual Risk Reduction. No ho, you will want to quote the SRR, the Sick Rate Reduction. You want to quote the percent of reduction there was, from the sick rate of those not wearing masks, to the sick rate of those wearing masks. You get that by dividing the “between-group difference” (the study’s term for the Actual Risk Reduction) by the sick rate for the nomaskers: .3899 / 2.1457 = 18.17%
That is what I call the Reduced Sick Rate, RSR. The standard name for it is the RRR, Relative Risk Reduction, which I believe is misleading and confusing because it is not a direct measure of risk and what it is “relative” to takes too much explanation. But it is literally the sick rate which was reduced by wearing masks.
The SRR, Sick Rate Reduction: 18.17%
The inverse of this, .82, is called the Odds Ratio.
The paragraph further explains, “The between-group difference was −0.3 percentage point (95% CI, −1.2 to 0.4 percentage point; P = 0.38) (odds ratio, 0.82 [CI, 0.54 to 1.23]; P = 0.33).”
The first half of that parenthesis means that we can be 95% Confident that the Interval [CI means “Confidence Interval”] within which future mask wearers will reduce their sick rate is between 1.2% lower than 2.1, the sick rate for nomaskers, to 0.4% higher.
A sick rate 1.2% lower than 2.1% is 0.9%. A sick rate 0.4% higher is 2.5%.
2.1 – 1.2 = 0.9. 2.1 + .04 = 2.5.
That means if Lady Luck exists and loves maskers, something rather unlikely, the sick rate among maskers might drop all the way down to 0.9% in some future group, although it dropped only to 1.8% in Denmark. But if Lady Luck is having a bad day, the sick rate for maskers might actually 'rise to 2.5%'.
Here is the next stat:
(95% CI, −1.2 to 0.4 percentage point; P = 0.38)
(odds ratio, 0.82 [CI, 0.54 to 1.23]; P = 0.33).”
P = 38 means there is a 38% probability, or chance, that there would have been a Sick Rate Reduction of 18% from chance alone, even if there were no physical connection between masks and sickness.
Next: (odds ratio, 0.82 [CI, 0.54 to 1.23]; P = 0.33). This is the source of the figures that confused Jessica.
The “Odds Ratio” (OR) of .82, means there is an 82% probability that the sickness experienced by the nomaskers will be experienced by the maskers. It is the inverse of the 18% that others call the RRR, Relative Risk Reduction, and that I call the SRR, The OR is calculated by dividing the maskers sick rate by the nomaskers sick rate.
Maskers sick rate: 42 sick maskers / 2392 healthy maskers = .017558
Nomaskers sick rate: 53 sick nomaskers / healthy nomaskers 2470 = .021457
OR: .017558 maskers sick rate / nomaskers sick rate .021457 = 0.81828
Review of calculations – how to calculate ARR, SRR, and OR:
Actual Risk Reduction (ARR) subtract masker sick rate from nomasker sick rate.
Sick Rate Reduction (SRR or RRR) divide nomasker sick rate by ARR.
Odds Ratio (OR) divide masker sick rate by nomasker sick rate.
The last statistic in the study’s string of statistics is “(0.54 – 1.23)” which means a 46% reduction (the inverse of 0.54) of that 2.1% nomasker sick rate, or maybe a 23% increase
“Yet, the findings were inconclusive and cannot definitively exclude a 46% reduction to a 23% increase in infection of mask wearers in such a setting.”
A 46% reduction from 2.1 is .54 x 2.1 = 1.13, ARR 0.97%
A 23% increase in infection from 2.1 is 1.23 x 2.1 = 2.58 ARR = – 0.48% 2.1
WHAT was “inconclusive”? That paragraph begins: “Our results suggest that the recommendation to wear a surgical mask when outside the home among others did not reduce, at conventional levels of statistical significance, the incidence of SARS-CoV-2 infection in mask wearers...” In other words, since probability determines whether maskers get sicker or healthier, what is “inconclusive” is whether the microscopic impact of masks is beneficial or harmful. What is conclusive is that the impact of masks is microscopic.
So the study was unable to prove any degree of benefit for maskers as a whole. How about for certain categories of maskers? Such as old folks? Could there be any category of people that would be more likely to benefit from masks?
No. “In the third post hoc analysis, which investigated constellations of patient characteristics, we did not find a subgroup where face masks were effective at conventional levels of statistical significance.”
CDC's Strange Dismissal of Denmark Study
Here is how the CDC dismissed the preceding major study May 7, 2021:
“Two studies have been improperly characterized by some sources as showing that surgical or cloth masks offer no benefit. A community-based randomized control trial in Denmark during 2020 assessed whether the use of surgical masks reduced the SARS-CoV-2 infection rate among wearers (personal protection) by more than 50%. Findings were inconclusive, most likely because the actual reduction in infections was lower. The study was too small (i.e., enrolled about 0.1% of the population) to assess whether masks could decrease transmission from wearers to others (source control). (Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, et al. Effectiveness of Adding a Mask Recommendation to Other Public Health Measures to Prevent SARS-CoV-2 Infection in Danish Mask Wearers : A Randomized Controlled Trial. Ann Intern Med. Nov 18 2020;doi:10.7326/M20-6817)”
The findings were not inconclusive. The formal conclusion was that the difference between infections among mask wearers vs. those without masks was “statistically insignificant”.
(The authors didn’t call the results “insignificant”, but “statistically insignificant”. They didn’t call it “statistically insignificant” because the benefit of masks is "insignificant", as voters and lawmakers would define the term, but for another reason: it was within what pollsters call “the margin of error”, leaving researchers uncertain whether masks help or harm: “... the findings were inconclusive and cannot definitively exclude a 46% reduction to a 23% increase in infection of mask wearers in such a setting.” Had they proved masks definitely protect from covid one millionth of a percent all the time, they would not have called it “statistically insignificant”.)
Though not a doctor, I have read dozens of studies and this is the first time I have heard a study of just under 6,000 people in each leg of the study called "small". It is also the first time I have heard a study denigrated because it involved less than one percent of the population of the nation! (Denmark's population is just under six million.)
The Denmark study measured whether wearing a mask protects the mask wearer. The Denmark study made no attempt to directly measure whether wearing a mask protects others. The CDC insinuates criticism of the study for being "too small" to measure something it made no attempt to measure, in order to justify the CDC's judgment that the study has been "improperly characterized by some sources as showing that surgical or cloth masks offer no benefit." No, that is exactly what the study showed.
The CDC sows further confusion by observing that the Denmark study "assessed whether the use of surgical masks reduced the...infection rate among wearers...by more than 50%. Findings were inconclusive...." Those two sentences, correct separately, are fraudulently misleading out of their contexts. Together, out of context, they sound like it was inconclusive whether masks cut infections in half. It was very conclusive that infections were not cut anywhere near in half! What was inconclusive was whether infections were cut at all!
But yes, the authors of the study wrote that when they began the study they expected to prove that masks cut infection by a huge margin. Their failure to prove masks reduce infection at all was a big surprise and was a huge obstacle to getting published in a peer-reviewed journal; publication was delayed several months.
The CDC speculated why the "Findings were inconclusive". It is "most likely because the actual reduction in infections was lower." There are two ways I can think of to take this statement. The first way is not true. The second way makes no sense.
(1) Not true: No, the "actual reduction in infections", at least the actual reduction, the ARR, was higher, not lower than in the Bangladesh study which the CDC's same article praised. In Denmark the ARR was actually 0.15%, counting only the maskers who wore "exactly as instructed", though the report rounded it to 0.2%. Before those not wearing the mask correctly were removed from the count, the ARR was reported as 0.3%, rounded down from 0.38%. In Bangladesh the ARR was much lower: a microscopic 0.08% Actual Risk Reduction.
(2) Makes no sense: Although the Denmark and Bangladesh ratios were almost identical, their reports to the public were nearly opposite, because Bangladesh reported only the SRR of 10% and Denmark reported only the ARR of 0.3%. Maybe the CDC confused the REPORTED reduction in infections with the ACTUAL reduction in infections. Certainly Denmark's reported reduction was lower. But if that is what the CDC thinks, it makes no sense that the CDC would admit that masks reduced covid that much less in Denmark than in Bangladesh, and on that basis, dismiss Denmark's finding as "inconclusive". If they realized the result in Denmark wildly contradicted the result in Bangladesh, wouldn't they want to find some other reason to dismiss the difference than that there was a difference? So that they could continue bragging that "Bangladesh's result proves how fantabulous masks work, and Denmark's opposite finding is explained by ____?"
It is hard to imagine how the misleading selectivity of this CDC report could be accidental. The arrangement of out-of-context quotes to achieve the greatest possible misrepresentation shows too much craft.
As for indirectly measuring whether wearing a mask protects others, I wrote above: "How could masks protect others from wearers, while unable to protect wearers from others? Their inability to protect wearers from others shows masks do not significantly block germs traveling from others, through the masks, to wearers. How does that not also show masks do not significantly block germs traveling from wearers, through the masks, to others? There is nothing about masks that permits only one way travel. If germs can travel through one way, they can also travel the other way."
Did the CDC address the Denmark study at any other time? I don't know; its search bar doesn't stick to the search terms entered, at least when I tried. I found this mention by accident.
DENMARK: Multiple journals rejected THE ONLY major Covid mask study as of Oct 23, 2021)
Update: the study was published 3 weeks after this story was published. See details below.
October 23 JustTheNews A major study out of Denmark that sought to examine the efficacy of face masks at limiting the spread of COVID-19 has reportedly been rejected by multiple academic journals amid hints that the study found face coverings are not effective in protecting individuals from the coronavirus.
The team of Danish scientists earlier this year carried out a major randomized controlled trial study to determine how effective masks might be at stopping COVID transmission. The study, begun in April, involved around 6,000 Danish citizens, half of whom wore face coverings during "normal behavior" and the other half of whom went without them.
The study concluded in June. Yet the Copenhagen newspaper Berlingske reported this week that it has been rejected by at least three elite medical journals so far — the Lancet, the New England Journal of Medicine, and JAMA, the Journal of the American Medical Association. "They all said no,"
The researchers are ethically bound to not publicly announce their findings until it is published in a peer-reviewed medical journal, so all we have, months after their study was completed - the ONLY major study of mask effectiveness specifically for Covid - is hints dropped by the extremely frustrated researchers.
Hints that the study finds masks are ineffective.
Hints like "(Results will be published) as soon as a journal is brave enough."
Or, "its results may run against the grain of current public orthodoxy on mask usage."
Or, asked by the paper if the study's results could be considered "controversial," another researcher said: "That's how I want to interpret it."
The research was ready for publication 5 months ago.
Although its authors feel ethically bound to refrain from self-publishing their results, critics have managed to view the paper and have published their criticism of it, yet without fully revealing its findings, and without the researchers having a chance to defend themselves. Their criticism offers us more hints: they say inherent design flaws in the study — including possible noncompliance factors within both the control and study groups — could unfairly skew the results in favor of non-mask usage.
The study "poses a serious risk of mistranslation" due to concerns that "null or too-small effects will be misinterpreted to mean that masks are ineffective," the writers stated. The academics warned policy-makers against "interpreting the results of this trial as being anything other than artifacts of weak design."
DENMARK: Two Analyses of this study: "Masks DO work", and "Masks DON'T work"!
Masks DO work: Bangor Daily News is mad at people who read, in this study, that masks don't work! The study "did not find that masks don’t work in slowing the spread of COVID-19." Well, no, it did not positively even test whether wearing a mask might protect others from you, but it certainly threw cold water on your hope that wearing a mask will protect you from others.
Plus, this article points out, at the time of the Danish study, most Danes were not wearing masks. IF wearing a mask DOES protect others from you, (a theory awaiting evidence), then if everyone wears a mask, that protects you too! So MAYBE masks work after all! Although that theory awaits clear evidence, this article points out that the CDC called the theory "likely".
“The relationship between source control and personal protection is likely complementary and possibly synergistic, so that individual benefit increases with increasing community mask use,” the CDC concluded earlier this month.
Masks DON'T work!
Business World is mad at people who read, in this study, that masks still might work. "One would think the study’s findings would encourage greater scrutiny on the efficacy of mandatory mask mandates, considering the absurd burden it places on individuals and businesses, not to mention the likely violation of civil liberties."
BW says the context of this study is "study after study showing that masks in the public setting do tend to be ineffective. And a CDC Report of Sept. 11, 2020, which found that amongst those infected by COVID-19, 85% 'always' or 'often' wore masks, while 70% of those actually hospitalized for COVID-19 'always' wore masks."
BW complains about the flip flopping mask mandates: "up to March 2020, the advice had nearly always been: 'don’t wear masks' Yet, suddenly, mask proponents, imposed an about-face. It became 'yes wear it publicly because it protects you.' Then it changed to: 'no, actually it doesn’t protect you but it protects others.' The current manifestation seems to be: 'well, wear it to raise awareness of COVID-19.' The foregoing is bizarrely contradicted by CDC Director Robert Redfield’s Sept. 16 statement: A 'face mask is more guaranteed to protect me against COVID than when I take a COVID vaccine.' Which in turn weirdly contradicted the CDC’s own Sept. 11 Report (particularly in an e-mail to Health Feedback), which stated that it 'clearly stated that wearing a mask is intended to protect other people in case the mask wearer is infected. At no time has CDC guidance suggested that masks were intended to protect the wearers.'”
"Note that an Oct. 23 study (Dhaval Adjodah, et al), published on medRxiv, had to be retracted when it claimed that mask mandates resulted in reducing COVID-19 cases, only to find infections in the subject areas rose after the study was released."
BW argues that asymptomatic spread is disproven, so why mandate mask wearing for people without symptoms, if masks are supposedly only useful to protect others from you?
"Then, finally, there is this: a study (Shiyi Cao, et al) published Nov. 20, described 'a city-wide SARS-CoV-2 nucleic acid screening program between May 14 and June 1, 2020 in Wuhan. There were no positive tests [no one tested positive] amongst 1,174 close contacts of asymptomatic cases.' In short, and if true: asymptomatic spread is not real. And if that is the case, with nearly 98-99% of COVID-19 cases being asymptomatic or mild, what could then justify mandatory mask wearing?"
Therefore, "if the science on public mask wearing shows that such is useless or doesn’t work...or at the very least uncertain, then for the government to make public mask wearing a mandatory requirement is arbitrary, capricious, and even perhaps despotic."
Another perspective of the fact that this study disproved any SIGNIFICANT benefit from masks, for wearers: How could masks protect others from wearers, while unable to protect wearers from others? Their inability to protect wearers from others shows masks do not significantly block germs traveling from others, through the masks, to wearers. How does that not also show masks do not significantly block germs traveling from wearers, through the masks, to others? There is nothing about masks that permits only one way travel. If germs can travel through one way, they can also travel the other way.
The inability of masks to block germs traveling from wearers to others, through masks, was graphically demonstrated by a doctor who exhaled vape "smoke" through different masks. (See description above.) Vape droplets are larger than the largest droplets theorized to carry covid, yet the droplets passed through almost as easily as they passed around the masks. The masks affected the direction and speed of exhaled breath, but not quantity.
In fact, if masks COULD actually TRAP large droplets and keep them from going into the room, wouldn't they become soggy after a couple of minutes? Doesn't the fact that they remain dry for hours prove they don't block droplets?
BANGLADESH ARR’s v. RRR’s: Research Fraud
Denmark’s mask research is a model of standards established for peer reviewed research to avoid falsely inflating the effectiveness of treatments, by honestly reporting ARR’s. In fact, they never mention SRR's (called by others "RRR's").
Bangladesh’s mask research illustrates how to violate them, by reporting only SRR’s. (Which others call “RRR’s”.) In fact, they never mentioned ARR's. (That is, the ARR to prevent covid infection. They did try to calculate the microscopic ARR to prevent a covid death, an even more microscopic percentage.)
Bangladesh’s noncompliance does not stand out. There is even peer-reviewed research on how much peer-reviewed research violates these standards.
About half of those reporting positive results. Along with 100% of medical advertisements.
But first let’s review what they did in Bangladesh. They reported that masks reduce covid infection by 10%! Significant indeed!
CATO on Bangladesh: a Tenth of One Percent Benefit
But imagine my surprise when I read the Cato Institute's analysis of the Bangladesh math, concluding that 10% is a hundred times more covid reduction than the numbers tell us:
Cato: “Researchers also reported results by mask type, finding that surgical masks reduced symptomatic seroprevalence rates by 0.09% compared to controls (0.67% vs. 0.76%, P=0.043)”
(Translation of the numbers: 67 out of every 10,000 maskers got sick, while 76 out of every 10,000 nomaskers got sick. The “probability value”: on a scale from 0 to 1, there is a 0.043 probability, or a 4.3% chance, that these results could have occurred even if there were no connection between masks and sickness. That “probability” is just barely within what is called “statistically significant”. A “P” of greater than 0.05 (a 5% chance that these differences could have occurred just by chance, classifies a number as “statistically insignificant”.)
Why the hundred-fold discrepancy? The Bangladesh researchers compared the sick rates of the “controls” vs. the “treatment” group – 0.68% and 0.76%, with each other, without the context of the 99% who never got sick. 0.76% is 10% more than 0.68%. Viola! Wearing a mask all the time reduces your covid risk by 10%!
The microscopic 0.08% has to be inflated over 100 times to reach 10%.
The researchers gave the percentages of maskers vs. nomaskers – 0.68% and 0.76%, but never mentioned that their difference is only 0.08%, or that this difference is the Actual Risk Reduction – the amount of risk of infection that is reduced by wearing a mask all the time.
Neither did they give the exact number remaining in the mask wearing group after 60.5% of them were removed from the count after they had a few covid symptoms but refused to let their blood be tested so doctors could see if they really had covid.
We are only told that 336,010 began the study – five times as many as in Denmark. Their Table S1 says 174,776 of them wore masks; 161,234 didn’t. Table S3 says only 40.2% of maskers consented to blood tests. 40.2% x 174,776 = 70,260 maskers.
Table S3 says 39.3% of nomaskers gave their consent. 39.3% x 161,234 = 63,365 nomaskers.
478 maskers got sick. Out of 70,260. 0.68%.
482 nomaskers got sick. Out of 63,365. 0.76%.
10 times that many had complained of covid symptoms. 8.6% of the 161,234 nomaskers, and 7.63% of the 174,776 maskers. After 60% of them were removed from the count after they refused blood tests, that should have left around 3% of them with confirmed covid, had all who complained been confirmed by their blood tests. Yet the rates dropped all the way down to 0.76% and 0.68%. The reason for the drop is not articulated, that I can find. But that drop is consistent with the possibility that only 22% of those claiming covid symptoms, actually had covid according to blood tests.
Masks caused an Actual Risk Reduction of 0.08%. Not 100 times greater: not 10%.
250% Inflation: Maybe results indicate not just 0.08% protection, but a whole 0.2%!
What a shame the researchers didn’t ask the study participants, before the study began, if they would permit blood tests.
But because they didn’t, the true infection rate among 60% of those with symptoms can’t be proved. If we assume their rate is the same as the rate of those who were tested, then the “between-group difference”, or ARR, or Actual Risk Reduction, would be 2½ times greater. But that would still only be 0.2%. The researchers didn’t do much with that possibility because it can’t be proved. The researchers probably didn’t care anyway; they were only going to report the SRR, (Sick Rate Reduction, that others call the RRR), the comparison between the mask sickness rate and the nomask sickness rate without the context of the total group size, and the SRR would stay the same if both covid groups jumped 250%. The jump would only affect the ARR.
750% Inflation: Maybe results support not just 0.2% protection but 1.5%!
The Bangladesh doctors even point out that their “10%” reduction is achieved with an increase of only 29% in mask wearing; imagine how many more lives would be saved with 100% mask wearing, they say! (“Our intervention induced 29 more people out of every 100 to wear masks, with 42% of people wearing masks in total. The total impact with near-universal masking – perhaps achievable with alternative strategies or stricter enforcement – may be several times larger than our 10% estimate.”) Hmmm. “Proper mask-wearing increased from 13.3% in the control group to 42.3% in the intervention arm.” Tripling masks produced a claimed 10% covid reduction. So would a 7.5-fold increase, to 100%, produce a 23% covid reduction?
Significant, indeed! Table S31 assumes making the whole Bangladesh population of 166 million wear masks all the time would reduce covid deaths 26%.
That great a Risk Reduction indeed is the rule on Planet Fauci, but I can’t remain there long. Not enough oxygen. On Planet Reality, the Absolute (actual) Risk Reduction is 0.08%, inflated to 0.2% if we assume the true infection rate among blood test refuseniks was the same as those actually tested. And here let us inflate it another 750% to project how much risk might be reduced if everyone wore masks all the time. An ARR of 1.5%. At the most – this was not proved but maybe – wearing a mask all the time will reduce your risk of getting covid by 1.5%.
Not 10%. Not 26%. 1.5%.
But all that was proved was 0.08%.
Even 0.08% is sky high in the opinion of the Bangladesh researchers, if we are to believe it wasn’t a typo when they said in Table S31 that to prevent one covid death, 30,001 people must wear masks all the time, because the ARR has mysteriously fallen to “2.86E-05” (0.00286%). 0.08% is 28 times higher than “2.86E-05” (0.00286%). More about that later.
Doubling Down on Failure: results, 0.08% protection. Claim, 9%!
Yet the Bangladesh doctors reported: “we estimate a roughly 9% decline in” covid cases confirmed by blood tests, among mask wearers, and “We find clear evidence that surgical masks [as opposed to cloth masks] lead to a relative reduction...of 11.1%. And still later, “Our results should not be taken to imply that mask-wearing can prevent only 10% of COVID-19 cases...”]
Guess which figure the CDC reports? Here in its entirety is the CDC’s breathtakingly superficial, biased summary of the Bangladesh research:
CDC: In villages receiving mask interventions, symptomatic [where there are symptoms] seroprevalence [where covid infection is confirmed by blood tests] of SARS-CoV-2 was reduced by approximately 9% relative to comparison villages. In villages randomized to receive surgical masks, symptomatic seroprevalence of SARS-CoV-2 was significantly lower (relative reduction 11.1% overall). The results of this study show that even modest increases in community use of masks can effectively reduce symptomatic SARS-CoV-2 infections (COVID-19).
But the Cato Institute agrees with my reading of the Bangladesh stats that the result was covid reduction of less than a tenth of one percent! Without betraying a critical spirit by suggesting the Bangladesh researchers misled anyone, Cato simply reported the numbers and ignored the inflated claims about them:
Cato: “Researchers also reported results by mask type, finding that surgical masks reduced symptomatic seroprevalence rates by 0.09% compared to controls (0.67% vs. 0.76%, P=0.043)”
Translation of the numbers: 67 out of every 10,000 maskers got sick, while 76 out of every 10,000 nomaskers got sick. The “probability value”: on a scale from 0 to 1, there is a 0.043 probability, or a 4.3% chance, that these results could have occurred even if there were no connection between masks and sickness. That “probability” is just barely within what is called “statistically significant”. A “P” of greater than 0.05 (a 5% chance that these differences could have occurred just by chance, classifies a number as “statistically insignificant”.
(The Cato figures don’t exactly match the Bangladesh study. The Bangladesh figure is 0.68% vs. 0.76%, not 0.67% vs. 0.76%. That apparent typo favors mask wearing by one hundredth of one percent: not just 0.08% less risk, but masks make you 0.09% safer.)
NNT: Number Needed to Treat: 35,001 maskers needed to prevent one covid death!
Another way the Bangladesh researchers admitted, to inquiring minds, how little masks help, is by discussing the NNT, the Number Needed to Treat, not just to save from covid sickness but to save from covid deaths. For example, if masks really did reduce covid 10%, then the NNT, the Number of people you would Need to Treat would be 10. On average, for every 10 people you treat, one of those 10 will be saved from covid.
The Bangladesh doctors even point out that their “10%” reduction is achieved with an increase of only 29% in mask wearing; imagine how many more lives would be saved with 100% mask wearing, they say! (“Our intervention induced 29 more people out of every 100 to wear masks, with 42% of people wearing masks in total. The total impact with near-universal masking – perhaps achievable with alternative strategies or stricter enforcement – may be several times larger than our 10% estimate.”) Hmmm. “Proper mask-wearing increased from 13.3% in the control group to 42.3% in the intervention arm.” Tripling masks produced a claimed 10% covid reduction. So would a 7.5-fold increase, to 100%, produce a 23% covid reduction? Significant, indeed!
A 26.41% reduction is their expectation on their Table S31, where in one column they list death rates and the next column they list how much lower they expect the rate to fall with everyone masking up. (They don’t state that percentage, but that is the ratio between the two columns.) But hey, 26.41% and 23% are close.
If masks reduce covid 26.41%, then wouldn’t the NNT be 4? 4 people wearing masks would save one life? So that 71,936 maskers would have prevented all 17,984 covid deaths?
Not according to Table S31, which says 35,001 must wear masks just to save ONE life! In fact even if all 166 million Bangladesh citizens wear masks, that save rate, or NNT, (35,001) would only save 4,751 lives!
(17,984 reported covid deaths, minus the 13,323 deaths that would supposedly remain even with the whole population wearing masks according to the table, leaves 4,751 lives saved. The table doesn’t specify that the scenario is the whole Bangladesh population wearing masks all the time, but 4751, the lives saved, x 35,001, the number needed to wear masks to save one life, = 166,289,751, which is the whole population of Bangladesh at the time of the study.)
So how does a NNT grow from an alleged 4 to an alleged 35,001 in the same population with the same set of factors? The study doesn’t say, so I will try to guess.
If masks really reduced covid sickness by 26%, would that reduce covid deaths by the same rate? (Not the same amount, but the same rate.) No. Because only about 1% of those who get covid die from it. So to prevent covid deaths, you have to prevent 100 times that many covid illnesses.
The population of Bangladesh was 166,000,000 at the time of the study. The government reported that infections “reached 15,000 per day in during our study period”. That comes out to about 1,800,000 infections during four months. The government reported 17,984 covid deaths over 4 months in 2021 That’s pretty close to 1% of the population getting covid during those four months.. That’s one death per one hundred infections. 1%.
1% of the population got infected. 1% of those who were infected died. 1% of 1% is one in ten thousand. The Actual Risk Reduction was less than 0.1%, which means 1,000 people would have to wear masks all the time to prevent one covid infection. And if 100 infections have to be prevented to prevent one covid death, then 100,000 people would have to wear masks all the time to prevent one covid death.
But what if masks really could cut covid 25%? Then if 40,000 wear masks, infections among them will drop 25% from 400 to 300. With 100 fewer infections, there will be one less covid death. 40,000 people wearing masks all the time would prevent one covid death – assuming masks cut covid infections by 25%.
Except that the infection rate for nomaskers reported in this study is 0.76%. So if 35,001 wear masks, 266 would be infected if no one wore masks, but with a reduction of 26% for maskers, only 195 would get covid, with all 35,001 people wearing masks. A difference of 71. But it takes a reduction of 100 infections to save one life, so 30,000 masking up would save only 71% of a life.
Running the same numbers on 50,000 maskers finally saves one life. (50,000 x .0076 = 380; 380 x .7359 [the inverse of 26,41%] = 279.6. 380 - 279.6 = a hair over 100 fewer infections.)
One life saved.
50,000 people wearing masks all the time. One life saved. IF everyone wearing masks would reduce covid infections by 26.41%.
But then why doesn’t Table S31 say 50,000 maskers are needed to save one life? Why "only" 35,001?
Maybe because a 26.41% risk reduction with masks, with a 0.76% infection rate without masks, is mathematically impossible. The researchers can’t change the government’s covid death count of 17,984. And they are determined that universal masking would reduce actual risk by 26.41%. That limits them to promising that 4,751 lives would be saved, reducing the death toll to 13,233. Once it is established that 4,751 lives is how many we are supposed to save, we have to calculate how many maskers it will take to save that many. We can’t put down 50,000, because 4,751 x 50,000 = 237,550,000. That’s how many people would have to wear masks all the time, to save 4,751 lives. At an infection reduction rate of 26.41%, and an infection rate without masks of 0.76%.
Does anyone see the problem with that?
The population of Bangladesh is only about 167 million.
Suppose we wanted to calculate how many maskers could be squeezed out of that 167 million, per life saved of those 4,751? That is, if we want to get as close to 50,000 maskers per life saved as possible, x 4,751, how many are available out of the whole population? That is, what is the whole population divided by 4,751?
Did you guess it?
Shake your hand if you guessed it’s the number the researchers put down as necessary to save that many lives. 35,001 is the maximum possible number of people available to mask up, because 4,751 x 35,001 = 166,289,751 which was just about exactly the total population of Bangladesh at the time of the study.
A little number juggling appears to have been necessary.
But on Planet Reality, that 26.41% is only the difference between two miniscule sick rates. It is irrelevant to determining how many need to be treated to save one life. If the difference between the sickness rates of “control” and “treatment” were not just one being 26% lower than the other, (SRR) but were 26% of the whole group lower, (ARR), then treating four people would prevent one infection, and treating 400 would prevent 100 infections which would save one life. The NNT would be 400. Not 50,000. Or 35,001.
The only time the ARR or the NTT is mentioned in the whole study is in this table, S31, where it is given as “2.86E-05” (0.00286%) and 35,001.
There are two other calculations on Table S31 of the rate, should covid be responsible for way more deaths than officially acknowledged. The more of the death rate it is postulated might be caused by covid, the lower the NNT goes and the higher the ARR goes. Should covid turn out to be responsible for 94,209 deaths – not only those deaths officially attributed to covid but also to 100% of all “excess deaths” (more than the death rate average over the past few years), then the ARR would shoot up to “1.50E-04” (0.0150%). One fifth of 0.08%. And the NNT would drop to 6,682. But instead of driven by any physical benefit from masks, the NNT is always as high as it can get without requiring more people to mask up than there are people. The NNT is always the total population divided by whatever death stat is postulated, while the ARR is derived from the NNT. (The NNT is 1, divided by the ARR.)
I didn’t know an ARR could jump up and down to match the mathematical need.
What should be very clear is that the Bangladesh stats do not support a remotely impressive success rate for masks. The stats agree with Denmark’s, though the claims are wildly opposite. Other than that, I’m tired. I’m going to bed.
(Yawn.) OK. I can’t sleep. Were the NNT derived from the true ARR, 0.08%, it would be 1250. (Not to prevent covid deaths but just covid infections.) 1,250 people is the Number Needed to Treat (to force to wear masks all the time) to save one person, on average, from covid infection. And since there is about one death per hundred cases, it would take 125,000 people wearing masks all the time to save one person from a covid death. The NNT would be 125,000.
“Usually a NNT between 20 and 50 is considered as a ndt/article/32/suppl_2/ii13/3056571#64437158 good score.” () An NNT of 125,000 is not a good score! Neither is 35,001!
Bangladesh and Probability: probable protection, 0.14% to zero
The best two mask trials, Denmark and Bangladesh, were the only ones worth mentioning according to Dr. Martin Kulldorff, senior scientific director of the Brownstone Institute, summarizing the Cato study according to an Epoch Times report.
Kulldorff: “The truth is that there have been only two randomized trials of masks for COVID. One was in Denmark, which showed that they might be slightly beneficial, they might be slightly harmful, we don’t really know—the confidence interval kind of crossed zero,” he said. “And then there was another study from Bangladesh where they randomized villagers to masks or no masks. And the efficacy of the masks was for reduction of COVID was something between zero and 18 percent. So either no effect or very minuscule effect.”
Kulldorff must be referring to a Bangladesh claim that “we estimate a roughly 9% decline in symptomatic seroprevalence [covid infection, confirmed both by symptoms and by blood tests] in the treatment group (adjusted prevalence ratio (aPR) = 0.91 [0.82, 1.00]).”
The PR, Prevalence Ratio, means .91 (91%) of the maskers got covid, as the number of nomaskers who did. A 9.1% decline. But in the brackets are the probability on either side – the range of results that others will likely face: wearing a mask might make you only .82 times (82%) as likely to get covid! An 18% risk reduction! Or, on the other side, you might be 1.0 (100%) as likely to get covid. No difference at all. As Kulldorff said, “reduction of COVID was something between zero and 18 percent. So either no effect or very minuscule effect.”
But why would Kulldorff call an 18% reduction “very miniscule”?
Presumably because Kulldorff understood that while an 18% reduction of a huge risk is wonderful, that much reduction of a risk that is already less than 1% isn’t a headline grabber. 18% less than a 0.76% risk is a 0.62% risk. The actual reduction of risk is only 0.14%. At most, if you wear a mask all the time, you will reduce your risk of getting covid by 0.14% compared to never wearing a mask.
Then again, there is an equal chance that you will reduce your risk by zero.
Kulldorff knew that the claimed 18% reduction had to be just the sick rate of maskers compared to the sick rate of nomaskers, without the context of the 99%+ of each group that never got sick, because there isn’t enough room below a 1% risk to reduce your risk another 18%.
If 50% of nomaskers got covid, then a reduction of 18% would at least be mathematically possible. But when less than 1% of nomaskers get covid, the most reduction of covid that is mathematically possible is a tiny fraction of a percent.
0.76% of nomaskers in Bangladesh got covid. That percentage is called their “risk”. 0.68% of maskers got covid. 0.76% minus 0.68% is 0.08%. That is how much less risk of covid you have from wearing a mask all the time. Plus or minus 0.08%. Your risk drops somewhere between 0.62% and zero. “Very miniscule.” That is called the “Actual Risk Reduction”, ARR. It is also called the “Risk Difference”. The Denmark researchers called it the “Between-group difference.”
The alleged 9% reduction, give or take 9%, is the sick rate of maskers compared to the sick rate of nomaskers, without the context of the 99%+ of each group that never got sick. Divide 0.08%, the “risk difference”, (ARR), into the nomask (the “controls”) risk, 0.76%, and you get just over 9%. 9% more nomaskers got sick, than maskers. That is called the “Sick Rate Reduction”, the SRR (which others call the RRR). Sick Rate Reduction tells you by how much the treatment reduced the risk of bad outcomes relative to the control group who did not have the treatment. The relative risk reduction is independent of the size of the total “controls” and “treatment” groups.
CDC's Inflation of Bangladesh Stats
CDC, reporting the Bangladesh study, Updated Dec. 6, 2021:
A large, well-designed cluster-randomized trial in Bangladesh in late 2020 found that surgical or cloth mask distribution, role-modeling, and active mask promotion tripled mask use to 42.3% in intervention villages compared to 13.3% in comparison villages. In villages receiving mask interventions, symptomatic seroprevalence of SARS-CoV-2 was reduced by approximately 9% relative to comparison villages. In villages randomized to receive surgical masks, symptomatic seroprevalence of SARS-CoV-2 was significantly lower (relative reduction 11.1% overall). The results of this study show that even modest increases in community use of masks can effectively reduce symptomatic SARS-CoV-2 infections (COVID-19).37
Much ink and many watts have already been expended by meshowing what's misleading about the 9% and 11.1% claim, which I won't repeat here. But the beginning of this paragraph shows that about half the goal of the Bangladesh researchers was to figure out how to get more people to wear masks. That investment certainly biases the researchers towards finding some way to defend the wearing of masks as being beneficial.
Cato on Bangladesh: A Tenth of One Percent
Quotes from the Cato Institute’s analysis of the Bangladesh mask research, followed by my comments:
“A second, high-quality, cluster-randomized study of more than 342,000 adults spread across 600 villages in rural Bangladesh found that placement in the study’s intervention group increased mask-wearing by 28.8% (from 13.3 to 42.3%), with participants in control villages (n=13,893) [who didn't wear masks] reporting a 1% higher rate of symptoms of COVID-like illness than participants in intervention villages (n=13,273) (8.6% v. 7.6%; P=0.000).
(My comment: In other words, wearing a mask, in the experience of these researchers, reduced the chance of getting covid by 1%. This is called the ARR, the "Actual Risk Reduction". 8.6% of those without masks got covid, but "only" 7.6% of those with masks got it. Actually the study reported a rate of 7.63% for the mask wearers, so the actual benefit was just under 1% - 0.97%. Cato just rounded it up to 1%. Notice this is a “rate of symptoms”. In other words, this reports what patients told researchers that they suffered. When blood tests were run to confirm whether those reporting symptoms actually had covid, the difference shrank.)
“Similar relative rate differences were noted for the study’s primary outcome, [what the study measured] symptomatic seroprevalence [percentage of people being studied testing positive in blood tests] (positive blood test plus COVID-19 symptoms), with control [nomaskers] and intervention [maskers] prevalence rates of 0.80% and 0.71%, respectively(P=0.043). Researchers also reported results by mask type, finding that surgical masks reduced symptomatic seroprevalence rates by 0.09% compared to controls (0.67%vs. 0.76%, P=0.043), but that cloth masks did not offer a statistically significant rate reduction(cloth mask: 0.74%, control: 0.76%, P=0.540).
(My comment: In other words, while the paragraph before said wearing a mask reduced covid infection by 1%, based on what the volunteers told the researchers, this paragraph says when that diagnosis was confirmed by a blood test, the difference dropped to only 0.09% - not quite a tenth of a percent. Cloth masks achieved a reduction of only 0.02% which is a small enough difference for the researchers to admit the difference is "not statistically significant", meaning, too small to rule out chance as the reason.)
“A secondary endpoint [the thing measured] of symptoms [as reported by study participants] without serologic confirmation [blood testing] favored face masking generally, but this endpoint is highly bias susceptible and the difference in the cloth mask subgroup, although borderline statistically significant, was less than 1% (cloth mask group: 7.9% v. 8.6%, p=0.048). Communities assigned to masking may report symptoms differently, [different people report how sick they are differently] and the more rigorous endpoint of laboratory-confirmed [by blood testing] prior SARS-CoV-2 infection found no benefit.
(My comment: In other words, cloth masks seemed to reduce risk a whopping 0.7%, based on the less accurate self-diagnosis of participants. Cato researchers called that "borderline statistically significant", which was enough of a benefit, in their minds, to say that result "favored face masking generally". But when self diagnosis was tested by blood samples, the advantage dropped enough lower for CATO researchers to classify the difference as "no benefit".
(In my opinion, even if the actual difference were a whopping 1% greater risk of catching a disease of which about 1.4% die, that difference is not dramatic enough to justify any mask mandate anywhere, and especially when that is compared with the documented medical harms from masks as listed in two studies reviewed in this section!)
“The Bangladesh cluster RCT is applicable to the unique circumstances of the region. Natural immunity at the outset of the study was very low due to low case numbers,vaccination was largely absent, and children and schools were not included. Unfortunately, this trial is limited in its ability to inform regions with higher rates of natural immunity, higher rates of vaccination, or school policies.”
Bangladesh: Masking Reduces Covid Risk 0.09%, MAYBE
(This is the same Bangladesh study reviewed by CATO in the previous article. This article is my own notes on quotes from the study.)
0.1% Fewer Maskers get covid - or is it 11%?
The Bangladesh study, November 8, 2021, found that only one percent fewer mask wearers got sick compared with the maskless, when patients submitted their own reports, but that advantage dropped to a tenth of one percent when patient reports were double checked with blood tests.
"There were 178,322 individuals in the intervention group and 163,861 individuals in the control group." At least the study was not "small". Entire villages were masked v. unmasked. Nearly 600 villages. It seems impossible to imagine, after the uselessness of masks is proved by a study of this size, that any future study could establish it with any more certainty.
"The proportion of individuals with COVID-19–like symptoms was 7.63% (N = 12,784) in the intervention arm [maskers] and 8.60% (N = 13,287) in the control arm [nomaskers], an estimated 11.6% reduction after controlling for baseline covariates."
In other words, the N [number] of sick people - 12,784, divided by the total masked population - 178,322, tells us that 7.63% of maskers got sick in three months. (Except I got 7.17%.) 13,287 sick nomaskers divided by 163,861 total nomaskers gives 8.60%, the percentage of the nomaskers who got sick. (Except I got 8.11%.) The difference between 7.63% and 8.6% is 0.97% - the degree of risk reduced by scrupulous masking. 0.97% is the ARR, the Actual Risk Reduction. You will reduce your chances of getting covid by nearly 1% if you wear a mask all the time.
But mask effectiveness is much more impressive when you divide that 0.97% difference by the 8.60% who got sick, so you can say masks reduced infection 11.6%. (Except I got 11.3%.) That calculation is called the SRR, the Sick Rate Reduction. [Others call it the Relative Risk Reduction.]
"No adverse events were reported"?
"No adverse events were reported." Interesting observation. The study doesn't mention measures in place to process adverse event reports. One of the goals of the study was to develop ways to get more people to wear masks. That goal conflicts with the goal of encouraging full reports of adverse events. "An August 2020 phone survey in rural Kenya found that although 88% of respondents claim to wear masks in public, direct observation revealed that only 10% actually did."
Funny. The art of taking honest surveys includes phrasing questions to neutralize the tendency of people to adjust their answers to what they think the surveyer wants to hear. Especially when people think the surveyer might be linked to the government, as in the case of this study in which they got government authorities to help encourage masking. "Adult household members were asked to wear masks whenever they were outside their house and around other people. To emphasize the importance of mask-wearing, we prepared a brief video of notable public figures discussing why, how, and when to wear a mask. The video was shown to each household during the mask distribution visit and featured the Honorable Prime Minister of Bangladesh Sheikh Hasina, the head of the Imam Training Academy, and the national cricket star Shakib Al Hasan. "
"Although we did not directly assess harms in this study, there could be costs resulting from discomfort with increased mask-wearing, adverse health effects such as dermatitis or headaches, or impaired communication."
CDC: Miracle Masks
The CDC Needs Us to Follow Science but Offers None
“Masks can help reduce your chance of #COVID19 infection by more than 80%.” That’s what Dr. Rochelle Walensky, director of the CDC (U.S. Centers for Disease Control and Prevention)tweeted November 5.
She didn’t cite any evidence for her claim. It would be very helpful if she would because the best evidence fails to prove that masks help at all to prevent covid, while they are quite harmful to quite a lot of people.
She says in the accompanying short video, “the evidence is clear”. Her statement that the evidence is clear appears to be her evidence.
No study that Cato Institute researchers know about, (or trust) as of November 8, 2021, claims 80% reduction.
Even if Walesky is perverting numbers by confusing ARR's and RRR's - Absolute Risk Reduction v. Relative Risk Reduction, (I call them Actual Risk Reduction and Sick Rate Reduction), I have yet to see even RRR’s (SRR’s) stretched all the way up to a claimed 80% covid reduction!
"Women wear masks more often, but men respond more to the intervention."
"We generally find that the impact of the intervention is concentrated among individuals over age 50. In surgical mask villages, we observe a 22.8% decline in symptomatic seroprevalence among individuals aged 50 to 59 years (adjusted prevalence ratio = 0.77 [0.60, 0.95]) and a 35.3% decline among individuals ≥60 years old in our baseline specification (p = 0.000) (adjusted prevalence ratio = 0.65 [0.45, 0.85]).....we investigate more deeply in appendix N and find that the age gradient appears to be sensitive to how we deal with missing values."
"The intervention led to a 9.5% reduction in symptomatic SARS-CoV-2 seroprevalence (which corresponds to 105 fewer symptomatic seropositives) and an 11.6% reduction in the prevalence of COVID-19–like symptoms, corresponding to 1541 fewer people reporting these symptoms. If we assume that nonconsenting symptomatic individuals were seropositive at the same rate as consenting symptomatic individuals, the total estimated symptomatic seropositives prevented would be 354." (Elsewhere there was a dollar value placed on each life by the government.)
The following statement again alludes to the RRR, not the ARR:
"Our results should not be taken to imply that mask-wearing can prevent only 10% of COVID-19 cases, let alone 10% of COVID-19 mortality. Our intervention induced 29 more people out of every 100 to wear masks, with 42% of people wearing masks in total. The total impact with near-universal masking—perhaps achievable with alternative strategies or stricter enforcement—may be several times larger than our 10% estimate. Additionally, the intervention reduced symptomatic seroprevalence more when surgical masks were used and even more for the highest-risk individuals in our sample (23% for ages 50 to 59 years and 35% for ages ≥60 years)"
"Although surgical masks can break down into microplastics that can enter the environment if disposed of improperly, an analysis of waste generated in Bangladesh’s first lockdown finds that the mass of surgical mask waste was one-third that of polyethylene bags, which also break down into macro- and microplastics."
Oh goody. So raising the microplastic pollution of a nation by a scant third is harmless.
Other Mask Studies
July 8, 2022 North Dakota Schools study
"New Study Proves Again School Masks were Useless for Stopping Covid" By Admin Published on July 8, 2022
The new study in pre-print publication at Research Square focuses on North Dakota schools], but it reinforces the conclusions of more sweeping studies, such as one published at “The Lancet” in May. The researchers from the University of Southern California, University of California, Davis and Truth in Data, LLC, unpacked the school mask mandate data.
“School districts across the nation have implemented mask mandates for children in the hope of reducing COVID-19 transmission, but the impact of school-based mask mandates on COVID-19 transmission in children is not fully established,” the authors write. “While observational studies of school mask mandates have had conflicting results, randomized studies have failed to detect an impact of masking on participants under 50 years of age.”
“Here we report the results of a natural experiment in two large K-12 school districts in Fargo, North Dakota, Fargo Public Schools (FPS) and West Fargo Public Schools (WF), to estimate the association between school mask mandates and COVID-19 infections,” the authors continue. “Our study population is unique because the districts are adjacent to each other in the same county and have similar student demographics, COVID-19 mitigation policies and staff vaccination rates. At the start of the Fall 2021 semester, FPS mandated masks and WF did not. On January 17, 2022, FPS also moved to a mask optional policy, creating a unique natural experiment to study school-based mask mandates.” The authors' conclusions clearly demonstrate that there was no significant difference between the school districts.
“We observed no significant difference between student case rates while the districts had differing masking policies (IRR 0.99; 95% CI: 0.92 to 1.07) nor while they had the same mask policies (IRR 1.04; 95% CI: 0.92 to 1.16),” the concluded. ” The IRRs across the two periods were also not significantly different (p = 0.40). Our findings contribute to a growing body of literature which suggests school-based mask mandates have limited to no impact on the case rates of COVID-19 among K-12 students.”
Indeed, the mask mandate-less West Fargo district had a lower spike than the mandated Fargo Public School District. Lest someone believe this is a fluke, it jibes with findings from multiple datasets.
The CDC’s mask mandate was recently unpacked in research article entitled, “Revisiting Pediatric COVID-19 Cases in Counties With and Without School Mask Requirements—United States, July 1—October 20 2021.” The results were unfavorable for the CDC’s support of school mask mandates.
The researchers, Ambarish Chandra from the University of Toronto and Tracy Beth Høeg from the UC Cal-Davis, point out their methodology of examining the CDC’s mask mandate claims.
“Our study replicates a highly cited CDC study showing a negative association between school mask mandates and pediatric SARS-CoV-2 cases,” the authors state. “We then extend the study using a larger sample of districts and a longer time interval, employing almost six times as much data as the original study. We examine the relationship between mask mandates and per-capita pediatric cases, using multiple regression to control for differences across school districts.”
Emily Burns and Joshua Stevenson also used a national dataset to issue a study of their own that meshes with these findings.
“Burbio.com has been tracking weekly mask status for the 500 largest school districts, comprising approximately 40% of the nations ~51 million public school students,” they state.
“With these data in hand, the question is, ‘Is there a difference in the case rates between masked and un-masked districts?’”
“The result of that analysis is below,” they state. “As you can see, except for a slight edge in October, masked districts fare 2-4x worse than un-masked districts.”
“This pattern is remarkably similar to that visible in Emily Oster’s data from the 2020/21 school year, and analyzed by @boriquagato,” they add. “That is, un-masked schools showed higher case rates early in the year, around October, but later in the year, case rates in masked schools vastly outstripped them. According to Emily Oster, ‘We do not find any correlations with mask mandates’.”
The U.K.’s Health Security Agency (UKHSA) in January published data that showed children who “never” or “sometimes” wear masks at work or school were less likely compared to those who “always” wear them.
There is mounting evidence that public health officials’ response to Covid-19 was not only futile, but it did lasting damage to an entire generation of kids.
(The rest of this article summarizes the psychological and educational harm to students from "distance learning" and masks - not medical harm, but the hampered communication from the loss of facial expressions to supplement speech.
CDC Report: No Statistically Significant Benefit from School Masks
The CDC writes: “The 21% lower incidence [of covid] in schools that required mask use among students was not statistically significant compared with schools where mask use was optional.” May 28, 2021
Several things are incredible about this study.
The study doesn’t say whether even one person was actually sick. The study only counts “cases”, which as you know from the news includes people who test positive for covid even if they have no symptoms. (“Asymptomatic”.)
The CDC report explains the two tests relied on: the infamous PCR tests, and “rapid antigen” tests. CDC writes, “COVID-19 cases among staff members and students are defined as laboratory-confirmed reverse transcription–polymerase chain reaction or rapid antigen positive test results self-reported to the school by staff members and parents or guardians of students or by local public health officials.” The two tests, and their wide range of reliability, are explained by UC Davis Health.
This analysis will keep the word “cases” in quote marks to remind readers that the CDC uses the word very differently than the rest of America does. The rest of us assume a “case of Covid” means where a person is actually sick.
The study doesn’t say whether any students ever even tested positive. Case numbers among teachers, other staff, and students were combined. “Number includes both students and staff members with a case of COVID-19 during the study period.” If all the “cases” were among only the adults, that would be consistent with general reports that children are more resistant, but we will not find out from the CDC.
The failure to distinguish between students and adults in counting “cases” leaves the report unable to guess whether mask wearing by adults or by students is the reason adults reduced “cases” 37% in schools where students were ordered to mask up. “This finding might be attributed to higher effectiveness of masks among adults, who are at higher risk for SARS-CoV-2 infection but might also result from differences in mask-wearing behavior among students in schools with optional requirements.”
The relative general immunity of children also helps explain why the study found that covid “cases” among both students and staff were only about half what is experienced in the general population. CDC reports 3.08 “cases” of both staff and students per 500 students, while the general population experiences 5.28 “cases” “per 500 population”.
How is 21% reduction of “cases” under mask mandates not “statistically significant”? Look at the quote again, and consider how much better a headline the sentence would be in conservative news reports, by deleting that “21%”:
“The 21% lower incidence [of covid] in schools that required mask use among students was not statistically significant compared with schools where mask use was optional.”
Reporting the difference as a “21% lower incidence” certainly takes the edge off the finding that it is not “statistically significant”, which a skeptic might guess is the reason it was called a “21% lower incidence” rather than a half of a percent lower incidence, which truly is “statistically insignificant”. Try to be patient with a bunch of numbers.
A chart at the end of the report says that where masks were required for students, there were 2.44 cases per 500 students, or 0.488%.
(Watch out! Calling it “per 500 students” feeds the impression that those “cases” are among students. But as pointed out earlier, the report doesn’t say if any students tested positive, much less actually got sick.)
For schools where masks were optional, it was 4.42 cases per 500 students, or 0.884%. That is a whopping 70% higher number of “cases” where students faced mask mandates!
But it is only a 0.346% higher rate of “cases”.
But where does CDC get the 21% figure?
The chart reports mask mandated student cases as 2.44 (2.15–2.77) and optionally masked student cases as 3.81 (3.42–4.25). The numbers in parenthesis are “confidence intervals”, which the study “estimates” at 95%. That “means that if the same population is sampled on numerous occasions and interval estimates are made on each occasion, the resulting intervals would bracket the true population parameter in approximately 95% of the cases.”
Comparing 3.42, the minimum “cases” to expect without a mandate, is a 23% increase over 2.77, the maximum “cases” to expect with a mandate. In other words, “we can expect at least 23% more cases without a mask mandate.”
Well, 23% is close to 21%. That’s the best I can figure, in the absence of the CDC explaining where it got 21%.
Still unclear is how either a 21% increase, or 23%, is “statistically insignificant”. Or whether we should instead go by the 0.346% figure, which makes the difference seem truly negligible. How can we clear up this confusion?
Suppose you need your house painted, so you ask two painters to give you a bid. You hope you can get it done for $4,000.
One contractor offers to do it for $3,999. He will save you $1. The second says “I can save you twice as much as the other guy. I can do the job for a scant $3,998!”
Which figure gives you the most realistic view of your options? The fact that the difference is only 0.9997%? Or the fact that the second painter will save you twice as much?
State Mask Mandates Ineffective
“Mask mandate and use efficacy in state-level COVID-19 containment”. By Damian D. Guerra, Daniel J. Guerra. May 18, 2021
This study compared covid rates of states with mask mandates, with those of states without. This study is a “preprint”, not yet peer reviewed, and therefore not intended to be relied on as if it were. But in the absence of better information, it seems more useful than nothing.
Here are quotes from the study, selected by Redstate:
The study notes that “80% of US states mandated masks during the COVID-19 pandemic” and while “mandates induced greater mask compliance, [they] did not predict lower growth rates when community spread was low (minima) or high (maxima).” Among other things, the study—conducted using data from the CDC covering multiple seasons—reports that “mask mandates and use are not associated with lower SARS-CoV-2 spread among US states.”
“Our findings do not support the hypothesis that SARS-CoV-2 transmission rates decrease with greater public mask use,” notes the U of L report.
Researchers stated that “masks may promote social cohesion as rallying symbols during a pandemic, but risk compensation can also occur” before listing some observed risks that accompany mask wearing…
The study has more value than what the study itself establishes. A section of it summarizes a dozen previous relevant studies, with links.
Conclusions Mask mandates and use are not associated with slower state-level COVID-19 spread during COVID-19 growth surges.
...Prior studies have conflicted on whether masks reduce SARS-CoV-2 transmission. For USS Theodore Roosevelt crew, reported mask use was lower among COVID-19 cases (56% vs. 81%) . There were no infections for 47.9% of patrons of two hair stylists with COVID-19 with universal masking , but PCR tests were not obtained for the other 52.1% of patrons , and first wave COVID-19 hospitalizations were no higher in public schools (high density with minimal masking) than elsewhere in Sweden . A randomized controlled trial (RCT) of Danish volunteers found no protective benefit of medical masks against COVID-19 infection . In RCTs before COVID-19, viral infections were more common for Vietnamese clinicians with cloth masks than medical or no masks (which were indistinguishable from each other) , and N-95 respirators (but not medical masks) protected Beijing clinicians from bacterial and viral diseases compared to no masks . To be sure, mask use compliance in RCTs is not always clear . Mask use was 10% and 33% for Beijing households with and without intrahousehold COVID-19 transmission, respectively . This suggests greater mask use may reduce COVID-19 spread. Hence, our second objective was to assess whether COVID-19 case growth is negatively associated with mask use.
... We found little to no association between COVID-19 case growth and mask mandates or mask use at the state level. These findings suggest that statewide mandates and enhanced mask use did not detectably slow COVID-19 spread.
Non-Covid, yet Relevant, Mask Studies
A review with useful links, emailed to me by Bill Whatcott 9/30/2021.
In May 2020, a CDC journal named Emerging Infectious Diseases published a “systematic review” of 10 RCTs that “reported estimates of the effectiveness of face masks in reducing” the spread of the flu in community settings. A “pooled analysis” of their results found “no significant reduction in influenza transmission with the use of face masks,” regardless of whether they are “worn by the infected person” to protect others, or if they are worn by “uninfected persons” to protect themselves from people who are infected.
All of those flu RCTs are highly relevant to Covid-19 because:
• both diseases are transmitted by RNA viruses that produce respiratory tract infections.
• more than 87% of virus-laden respiratory particles exhaled by people with either disease are less than 1 micron in diameter. These can easily penetrate surgical and cloth masks because the average pore sizes of:
• surgical masks are at least 17 to 51 times larger than those particles.
• cloth masks are at least 80 to 500 times larger than those particles. (More details about this are provided below in the section on laboratory studies.)
The following mask studies, with links, were summarized 10/15/2021 by Joseph Mercola:
Surgical masks and N95 masks perform about the same
A 2009 study published in JAMA compared the effectiveness of surgical masks and N95 respirators to prevent seasonal influenza in a hospital setting; 24% of the nurses in the surgical mask group still got the flu, as did 23% of those who wore N95 respirators.
Cloth masks perform far worse than medical masks
A study published in 2015 found health care workers who wore cloth masks had the highest rates of influenza-like illness and laboratory-confirmed respiratory virus infections, when compared to those wearing medical masks or controls (who used standard practices that included occasional medical mask wearing).
Compared to controls and the medical mask group, those wearing cloth masks had a 72% higher rate of lab-confirmed viral infections. According to the authors:
"Penetration of cloth masks by particles was almost 97% and medical masks 44%. This study is the first RCT of cloth masks, and the results caution against the use of cloth masks … Moisture retention, reuse of cloth masks and poor filtration may result in increased risk of infection."
"No evidence" masks prevent transmission of flu in hospital setting
In September 2018, the Ontario Nurses Association (ONA) won its second of two grievances filed against the Toronto Academic Health Science Network's (TAHSN) "vaccinate or mask" policy. As reported by the ONA:
"After reviewing extensive expert evidence submitted … Arbitrator William Kaplan, in his September 6 decision, found that St. Michael's VOM policy is 'illogical and makes no sense' …
"In 2015, Arbitrator James Hayes struck down the same type of policy in an arbitration that included other Ontario hospitals across the province … Hayes found there was 'scant evidence' that forcing nurses to use masks reduced the transmission of influenza to patients …
"ONA's well-regarded expert witnesses, including Toronto infection control expert Dr. Michael Gardam, Quebec epidemiologist Dr. Gaston De Serres, and Dr. Lisa Brosseau, an American expert on masks, testified that there was … no evidence that forcing healthy nurses to wear masks during the influenza season did anything to prevent transmission of influenza in hospitals.
"They further testified that nurses who have no symptoms are unlikely to be a real source of transmission and that it was not logical to force healthy unvaccinated nurses to mask."
No significant reduction in flu transmission when used in community setting
A policy review paper published in Emerging Infectious Diseases in May 2020, which reviewed "the evidence base on the effectiveness of nonpharmaceutical personal protective measures … in non-healthcare settings" concluded, based on 10 randomized controlled trials, that there was "no significant reduction in influenza transmission with the use of face masks …"
Risk reduction may be due to chance
In 2019, a review of interventions for flu epidemics published by the World Health Organization concluded the evidence for face masks was slim, and may be due to chance:
"Ten relevant RCTs [the "gold standard" of research] were identified for this review and meta-analysis to quantify the efficacy of community-based use of face masks …
"In the pooled analysis, although the point estimates suggested a relative risk reduction in laboratory-confirmed influenza of 22% in the face mask group, and a reduction of 8% in the face mask group regardless of whether or not hand hygiene was also enhanced, the evidence was insufficient to exclude chance as an explanation for the reduced risk of transmission."
"No evidence" that universal masking prevents COVID-19
A 2020 guidance memo by the World Health Organization pointed out that:
"Meta-analyses in systematic literature reviews have reported that the use of N95 respirators compared with the use of medical masks is not associated with any statistically significant lower risk of the clinical respiratory illness outcomes or laboratory-confirmed influenza or viral infections …
"At present, there is no direct evidence (from studies on COVID- 19 and in healthy people in the community) on the effectiveness of universal masking of healthy people in the community to prevent infection with respiratory viruses, including COVID-19."
Mask or no mask, same difference
A meta-analysis and scientific review led by respected researcher Thomas Jefferson, cofounder of the Cochrane Collaboration, posted on the prepublication server medRxiv in April 2020, found that, compared to no mask, mask wearing in the general population or among health care workers did not reduce influenza-like illness cases or influenza.
In one study, which looked at quarantined workers, it actually increased the risk of contracting influenza, but lowered the risk of influenza-like illness. They also found there was no difference between surgical masks and N95 respirators.
Fauci's Flip Flops, listed by Congressman Jordan
Watch Rep. Jim Jordan, grilling Fauci: Jim Jordan Resumes Attacks On Dr. Fauci Over COVID-19 Origins, Mask Guidance. Posted July 28, 2021 by Forbes Breaking News; the hearing was the day before. Transcript of Jordan:
"When this virus came on the scene Dr. Fauci initially told the American people you don’t need to wear a mask, then later he said no, you need to wear a mask, then he said you need to wear two masks, then after that he said back to one mask, then of course he went to no masks, and no he talks about we need to wear a mask again.
"When it comes to the question of the origin of the virus, Dr. Fauci has had just as many positions. He initially said U.S. taxpayer money did not fund the Wuhan Institute of Neurology. He later changed that: no, no, we did fund it, but it was through a sub-grant. Then he subsequently said no, no, we funded it but we did no gain-of-function research. And then just last Sunday he said well, we funded it, it was gain-if-function research, but it was a sound scientific decision. "And then he said this: 'It would have been negligent to not fund the lab in China.' "I mean, talk about being all over the board. I’ll tell you what’s negligent: Dr. Fauci’s ever changing statements to the American people...."
Part 2 - Masks Dangerously Reduce Oxygen: PROVED
Research featured in this section:
German Study: Is a Mask Free of Potential Hazards? Children are the most vulnerable. There are problems with masks that should be obvious. Masks spread covid even more, by forcing the larger droplets exhaled by maskless people to be broken up by the mask to make them smaller, which then makes them airborne longer. People have to talk louder, further expelling fine droplets. We rebreathe the air we exhale even without masks, because not all that leaves our lungs makes it all the way out of our noses; masks double this “dead space volume”. Masks make us breather faster and makes lung muscles work harder.
Study where masks reduced oxygen & raised CO2 reported as "Face masks DON'T restrict oxygen or..." Actual reduced oxygen and raised CO2 was recorded, but the study only lasted half an hour! so the small differences were not judged “statistically significant”. Let’s have a longer study! Like, that goes 40 hours a week, for two years!
"Evidence that masks help is lacking. Their harms are established." the NIH published a review of 100+ mask studies January, 2021, which said “Although, scientific evidence supporting facemasks’ efficacy is lacking, adverse physiological, psychological and health effects are established.” It was retracted, but without giving any reason, which publication guidelines require.
More masks, more deaths in Europe More masking wearing correlated with more “excess” (higher than average) deaths in come countries and with more covid in others, but never with less of either.
Hospital mask mandates impose masks most on those most harmed by masks Heart and lung problems are among the most serious conditions of hospital patients. Along with overweight patients, patients with COPD and sleep apnea, they already suffer from low oxygen and high CO2 levels; their hearts and lungs are already under stress. Masks further lower oxygen and raise CO2 levels, tax lung muscles which have to breathe faster and overcome more resistance, which raises heart rates and blood pressure levels.
Harm to children from masks
From "Effects of Mask Mandates and School Closures", by Joseph Mercola, posted September 28, 2021 but removed two days later.
"Data from the first registry to record children's experiences with masks show physical, psychological and behavioral issues including irritability, difficulty concentrating and impaired learning
"A late 2020 and early 2021 retrospective [Research Square, 2021; doi.org/10.21203/rs.3.rs-124394/v2 study,] shows that children have experienced great psychological, behavioral and physical harm from the mandates and lockdowns handed down during the COVID-19 pandemic.
"...updated periodically through early 2021, [it] uses data from Germany's first registry showing the experience children are having wearing masks. Parents, doctors and others were allowed to enter their observations; the registry had recorded use by 20,353 people as of October 26, 2020.
"Editors have since added disclaimers to the text claiming "this study cannot demonstrate a causal relationship between mask wearing and the reported adverse effects in children," [but] as you can see, the data gathered on 25,930 children were specific and intriguing. The average time children were wearing a mask was 270 minutes each day.
[The consequences] '… included irritability (60%), headache (53%), difficulty concentrating (50%), less happiness (49%), reluctance to go to school/kindergarten (44%), malaise (42%), impaired learning (38%) and drowsiness or fatigue (37%).'
"Added to these concerning [psychological] symptoms, they also found 29.7% reported feeling short of breath, 26.4% being dizzy and 17.9% were unwilling to move or play. Hundreds more experienced "accelerated respiration, tightness in chest, weakness and short-term impairment of consciousness."
[Mercola's article next summarizes the Danish study which is described at the beginning of Section Two.] "The first randomized controlled trial evaluating the effectiveness of surgical face masks against SARS-CoV-2 was published in November 2020 in the Annals of Internal Medicine.
"During the trial, researchers evaluated more than 6,000 individuals and found that masks did not statistically significantly reduce the incidence of infection of COVID-19. Among the people who wore masks, 1.8% tested positive for SARS-CoV-2, compared to 2.1% among the control group.
[Next Mercola summarizes a study reported above, of covid incidence in mask mandate states vs. voluntary masking states.] "At the end of December 2020, researchers from Rational Ground revealed results of data analysis evaluating the use of masks from all 50 U.S. states.27 It was completed by data analysts, computer scientists and actuaries, who divided the information into states that had mask mandates and those that did not.
"They evaluated data from May 1, 2020, through December 15, 2020, and calculated how many cases per day occurred by population with and without mask mandates. Among states without a mask mandate, 5,781,716 cases were counted over 5,772 days, which worked out to:
"No mask mandates — 17 cases per 100,000 people per day
"Mask mandates — 27 cases per 100,000 people per day
More masks, more deaths in Europe
April 19, 2022, National Institutes of Health, PubMed.gov
"Correlation Between Mask Compliance and COVID-19 Outcomes in Europe" by Beny Spira
From the Abstract (Summary): "...countries with high levels of mask compliance did not perform better than those with low mask usage" according to "Data from 35 European countries on morbidity, mortality, and mask usage". In fact, "correlation...between mask usage and COVID-19 outcomes were either null or positive, depending on the subgroup of countries and type of outcome (cases or deaths)." In other words, depending on the country, more masks caused more covid in some places and more deaths in others, but never caused less of either.
Excerpts from the study: "the World Health Organization (WHO) as well as other public institutions, such as the IHME, from which the data on mask compliance used in this study were obtained, strongly recommend the use of masks as a tool to curb COVID-19 transmission [8,13]. These mandates and recommendations took place despite the fact that most randomised controlled trials carried out before and during the COVID-19 pandemic concluded that the role of masks in preventing respiratory viral transmission was small, null, or inconclusive."
..."studies, performed during the first months of the pandemic, comparing countries, states, and provinces before and after the implementation of mask mandates almost unanimously concluded that masks reduced COVID-19..." but that false impression may be because "mask mandates were normally implemented after the peak of COVID...at a time when the propagation of COVID-19 was already declining. Furthermore, the mask mandate was still in place in the subsequent autumn-winter wave of 2020-2021, but it did not help preventing the outburst of cases and deaths in Germany that was several-fold more severe than in the first wave".
"...the moderate positive correlation between mask usage and deaths in Western Europe also suggests that the universal use of masks may have had harmful unintended consequences."
"The positive correlation between mask usage and cases was not statistically significant (rho = 0.136, p = 0.436), while the correlation between mask usage and deaths was positive and significant (rho = 0.351, p = 0.039). The Spearman’s correlation between masks and deaths was considerably higher in the West than in East European countries: 0.627 (p = 0.007) and 0.164 (p = 0.514), respectively."
"Not statistically significant" means a difference too small to rule out chance; "statistically significant" means a difference great enough to be sure more masks definitely correlate to more deaths - but not necessarily enough more for laymen to think of it as significant.
"Spearman's Correlation is a measure of "the strength of the relationship between two variables....Rho values range from -1 to 1. A negative value of r indicates that the variables are inversely related, or when one variable increases, the other decreases. On the other hand, positive values indicate that when one variable increases, so does the other."
In other words, a rho of .351 indicates that deaths increase by about a third as much as mask use increases. This, the study calls a "moderate" correlation.
And the "p" value? "The p-value represents the chance of seeing our results if there was no actual relationship between our variables. A p-value less than or equal to 0.05 means that our result is statistically significant and we can trust that the difference is not due to chance alone."
In other words, the "p" of 0.039 means we can trust that the difference is not due to chance alone.
"Table 1" shows death rates and mask wearing rates for nine countries. Albania has the lowest death rate: 679 per million over the six months studied. Its covid rate: 40,990 per million. 53% of its population were "reporting always wearing a mask when leaving home." Hungary's death rate is 2,064 per million. Covid rate: 64,704 per million. 77% of its population always wore masks away from home. Hungary's mask rate is 145% of Albania's. Hungary's death rate is 300% of Albania's. Three times as high.
So, the study concludes, since the covid increases with mask use but not enough to even be sure about it, but deaths increase by about a third as much as mask use increases, the deaths are not covid deaths. It is not proved that the masks cause other deaths, but the correlation is pretty suspicious, especially in light of the German study that reviews the dozens of serious medical conditions that are contributed to by lowering of oxygen levels and the raising of carbon dioxide levels in the blood.
Hospital mask mandates impose masks most on those most harmed by masks
Heart and lung problems are among the most serious conditions of hospital patients. Along with overweight patients, patients with COPD and sleep apnea, they already suffer from low oxygen and high CO2 levels; their hearts and lungs are already under stress. Masks further lower oxygen and raise CO2 levels, tax lung muscles which have to breathe faster and overcome more resistance, which raises heart rates and blood pressure levels.
I am writing this in September, 2022, in Des Moines, where hospitals are the only institutions requiring masks for all patients.
The German study, next, lists peer-reviewed studies that document many minor and major medical conditions that are contributed to, if not caused by masks, among which are:
- increase in breathing dead space volume
- increase in breathing resistance
- increase in blood carbon dioxide
- decrease in blood oxygen saturation
- increase in heart rate
- increase in blood pressure
- decrease in cardiopulmonary capacity (heart and lung measurements, during exercise, looking for indicators for conditions that limit safe exercise. Measurements include Heart rate, EKG, Blood pressure, Oxygen saturation, Respiratory rate, Minute ventilation (amount of air that the patient breathes in a minute), Exhaled carbon dioxide concentration, Inhaled and exhaled oxygen concentration.
- increase in respiratory rate
- shortness of breath and difficulty breathing
The rest of the conditions on this particular list from the German study limit the ability of doctors and nurses, who are especially required to wear masks almost al the time, to provide the best quality care:
- feeling hot and clammy
- decreased ability to concentrate
- decreased ability to think
- decrease in empathy perception
- impaired skin barrier function
- acne, skin lesions and irritation
- overall perceived fatigue and exhaustion
These last conditions are not major medical issues by themselves, but they can have major consequences in patients who need to keep their minds sharp to understand doctors' instructions, and to care for themselves properly. They can also have major consequences when doctors and nurses are distracted by them from providing the best possible care for patients.
The study below headlined "Evidence that masks help is lacking. Their harms are established" likewise includes a section on “Stress to heart and lungs”. Even the study titled below “Study where masks reduced oxygen & raised CO2 headline: "Face masks DON'T restrict oxygen or contribute to carbon dioxide buildup" measures heart rate, showing that heart rates for patients with COPD raised from an average 86 beats per minute to 97, after only 30 minutes at rest, or after 6 minutes of walking, while wearing an N95 mask. (This detail is found at the study at [www.atsjournals.org/doi/full/ 10.1513/AnnalsATS.202007-812RL Annals of the American Thoracic Society)
German Study: Is a Mask Free of Potential Hazards?
The German study summarized here reaches several findings which Americans need to know, but which are stated in English that takes too much concentration, even for me. So I am going to “translate” several key paragraphs. In normal print will be my effort at simpler English, and below it, indented, the verbiage from the study.
The numbers in parenthesis are footnotes citing studies published in peer-reviewed medical journals. The study's 178 footnotes fill 14 pages, so I won't reprint them here. I leave those footnote numbers in these excerpts so that you can see that for each claim of a medical condition caused by or at least contributed to by masks, there are around a dozen studies of the link to just that condition. If you want to know the studies relating to a particular condition, look up that number in the online study itself. The title of the study: "Is a Mask That Covers the Mouth and Nose Free from Undesirable Side Effects in Everyday Use and Free of Potential Hazards?" Published online 2021 Apr 20. Paul B. Tchounwou, Academic Editor. Authors: Kai Kisielinski, Paul Giboni, Andreas Prescher, Bernd Klosterhalfen, David Graessel, Stefan Funken, Oliver Kempski, and Oliver Hirsch.
In this article: In normal print, my effort at simpler English. After it, indented, the verbiage from the study.
The CDC Needs Us to Follow Science but Offers None. “Neither the WHO (World Health Organization), CDC (U.S. Centers for Disease Control and Prevention), nor the European ECDC, nor the German RKL, offer sound scientific data that masks reduce Covid.
“...Neither higher level institutions such as the WHO or the European Centre for Disease Prevention and Control (ECDC) nor national ones, such as the Centers for Disease Control and Prevention, GA, USA (CDC) or the German RKI, substantiate with sound scientific data a positive effect of masks in the public (in terms of a reduced rate of spread of COVID-19 in the population) [2,4,5].”
My Translation of the following excerpt: Germans remember the last time German doctors surrendered their individual judgment to a central authority. The 1948 Geneva Declaration, driven by the memory of Hitler’s barbaric mandates based on the assumptions of his “Master Race” religion, places responsibility on the shoulders of every individual doctor to act in his OWN best judgment, and to resist authorities who rule contrary. To surrender individual judgment without limit to a central authority gives central authority a literally absolute power, and absolute power corrupts absolutely.
(Is there a limit to the atrocities which American doctors are willing to commit who surrender their personal convictions to the CDC? We already have the majority of doctors, along with Veterans Administration hospitals, imposing unhealthy mask mandates on hospital patients, and setting this example for all of society, while urging vaccines which kill more than they cure.)
“In addition to protecting the health of their patients, doctors should also base their actions on the guiding principle of the 1948 Geneva Declaration, as revised in 2017. According to this, every doctor vows to put the health and dignity of his patient first and, even under threat, not to use his medical knowledge to violate human rights and civil liberties.”
We pray authorities will pay attention to this evidence, and continually review whatever evidence they have that masks help, with this evidence that masks harm. Doctors should also use this list of established side effects. Virtually every diagnosis requires weighing risks v. benefits, a responsibility impossible with ignorance of risks. Some conditions more clearly than others merit deliverance from the harms of mask wearing.
“...All the scientific facts found in our work expand the knowledge base for a differentiated view of the mask debate. This gain can be relevant for decision makers who have to deal with the issue of mandatory mask use during the pandemic under constant review of proportionality as well as for physicians who can advise their patients more appropriately on this basis. For certain diseases, taking into account the literature found in this study, it is also necessary for the attending physician to weigh up the benefits and risks with regard to a mask obligation. With an overall strictly scientific consideration, a recommendation for mask exemption can become justifiable within the framework of a medical appraisal (Figure 5).”
Our recommendations, supported by the dozens of studies we have reviewed, comply with law, with medical best practices, and science, in contrast to the assumption-led, evidence-challenged mantra that obsessive mask wearing is great for everybody.
“Within the framework of these findings, we, therefore, propagate an explicitly medically judicious, legally compliant action in consideration of scientific factual reality [2,4,5,16,130,132,143,175,176,177] against a predominantly assumption-led claim to a general effectiveness of masks, always taking into account possible unwanted individual effects for the patient and mask wearer concerned, entirely in accordance with the principles of evidence-based medicine and the ethical guidelines of a physician.”
At the least, doctors should use this list of established side effects to compare with the conditions of each patient, and as appropriate, exempt patients from mask wearing whose illness is associated with mask wearing.
“The results of the present literature review could help to include mask-wearing in the differential diagnostic pathophysiological cause consideration of every physician when corresponding symptoms are present (MIES, Figure 4). In this way, the physician can draw on an initial complaints catalogue that may be associated with mask-wearing (Figure 2) and also exclude certain diseases from the general mask requirement (Figure 5).”
We are blissfully ignorant of what oxygen/carbon dioxide imbalance is doing to our bodies at the cellular level to degrade immunity and cause cancer. How long are we going to go on causing this imbalance on a national scale without bothering to find out?
“Basic research at the cellular level regarding mask-induced triggering of the transcription factor HIF with potential promotion of immunosuppression and carcinogenicity also appears to be useful under this circumstance. Our scoping review shows the need for a systematic review.”
Children are the most Vulnerable
Children are the most vulnerable to dangerous policies. Their consequences will be the longest, (because they have more years to live remaining than adults) and therefore the most profound.
“In our view, further research is particularly desirable in the gynecological (fetal and embryonic) and pediatric fields, as children are a vulnerable group that would face the longest and, thus, most profound consequences of a potentially risky mask use.”
Obvious Problems with Masks
(Under “4. Discussion:) Masks soaked with exhaled air accumulate bacteria, fungi, and viruses. Handling them contaminates hands.
“From an infection epidemiological point of view, masks in everyday use offer the risk of self-contamination by the wearer from both inside and outside, including via contaminated hands [5,16,88]. In addition, masks are soaked by exhaled air, which potentially accumulates infectious agents from the nasopharynx and also from the ambient air on the outside and inside of the mask. In particular, serious infection-causing bacteria and fungi should be mentioned here [86,88,89], but also viruses . The unusual increase in the detection of rhinoviruses in the sentinel studies of the German RKI from 2020  could be an indication of this phenomenon. Clarification through further investigations would therefore be desirable.”
Dizziness, vertigo (loss of balance), and shortness of breath should cause anyone to rip off his mask, at the least! Authorities who issue mandates should issue warnings, along with First Aid instruction.
“...the use of masks should be stopped immediately at the latest when shortness of breath, dizziness or vertigo occur [23,25]. From this aspect, it seems sensible for decision makers and authorities to provide information, to define instruction obligations and offer appropriate training for employers, teachers and other persons who have a supervisory or caregiving duty. Knowledge about first aid measures could also be refreshed and expanded accordingly in this regard.”
We want children in school so they can become smart, right? But masks impair thinking, decrease attention spans, along with dizziness, psychological and brain problems! And school bus drivers wearing masks are more likely to have accidents!
“...The proven mask-induced mild to moderate cognitive impairment with impaired thinking, decreased attention and dizziness [19,23,29,32,36,37,39,40,41,69], as well as the psychological and neurological effects , should be additionally taken into account when masks are compulsory at school and in the vicinity of both public and non-public transport, also regarding the possibility of an increased risk of accidents (see also occupational health side effects and hazards) [19,29,32,36,37].”
Indirect health hazard: 89 million masks are discarded every month. 7 polymers into which they degrade are a significant source of plastic particles polluting our water and infecting fish. The microbes (protozoa, bacteria, viruses, fungi) on them are an ominous threat. Their disposal is barely regulated even in western countries.
“3.15. Effects on the Environment. According to WHO estimates of a demand of 89 million masks per month, their global production will continue to increase under the Corona pandemic . Due to the composition of, e.g., disposable surgical masks with polymers such as polypropylene, polyurethane, polyacrylonitrile, polystyrene, polycarbonate, polyethylene and polyester , an increasing global challenge, also from an environmental point of view, can be expected, especially outside Europe, in the absence of recycling and disposal strategies . The aforementioned single use polymers have been identified as a significant source of plastic and plastic particles for the pollution of all water cycles up to the marine environment . A significant health hazard factor is contributed by mask waste in the form of microplastics after decomposition into the food chain. Likewise, contaminated macroscopic disposable mask waste—especially before microscopic decay—represents a widespread medium for microbes (protozoa, bacteria, viruses, fungi) in terms of invasive pathogens [86,87,88,89,142]. Proper disposal of bio-contaminated everyday mask material is insufficiently regulated even in western countries.”
Masks worn by the public are a greater risk than those worn by doctors because hospital rules can’t be followed by the general public.
“Masks, when used by the general public, are considered by scientists to pose a risk of infection because the standardized hygiene rules of hospitals cannot be followed by the general public .”
How Masks Make Covid Spread Even Worse
Masks cause covid virus to travel farther through the air, because the “droplets” (microscopic drops of water, as in mist and in clouds) driven through a mask are smaller than the droplets exhaled by mask-less people. [The volume of droplets is not necessarily less, because the same amount of air is forced through the masks as people normally breathe. If masks actually trapped large droplets, they would quickly become soggy, which proves they actually force large droplets through, making them smaller; and the smaller they are, the longer they are airborne.] This forcing of large droplets into becoming smaller droplets is called the “Nebulizer Effect”.
“On top of that, mask wearers (surgical, N95, fabric masks) exhale relatively smaller particles (size 0.3 to 0.5 μm) than mask-less people and the louder speech under masks further amplifies this increased fine aerosol production by the mask wearer (nebulizer effect) .”
Mask Reseach History
Masks didn’t achieve the hoped-for protection from the 1918 Spanish Flu, the influenzas of 1957–58, 1968, 2002 or 2009, or from SARS in 2004–2005. Masks are ineffective against viruses even in hospital use.
“The history of modern times shows that already in the influenza pandemics of 1918–1919, 1957–58, 1968, 2002, in SARS 2004–2005 as well as with the influenza in 2009, masks in everyday use could not achieve the hoped-for success in the fight against viral infection scenarios [67,144]. The experiences led to scientific studies describing as early as 2009 that masks do not show any significant effect with regard to viruses in an everyday scenario [129,145]. Even later, scientists and institutions rated the masks as unsuitable to protect the user safely from viral respiratory infections [137,146,147]. Even in hospital use, surgical masks lack strong evidence of protection against viruses .”
The Evidence is Clear
The evidence of harm isn't just documented in one little study. But in 42 peer-reviewed studies in medical journals. Each of the harms listed above are documented in several of those 42 studies. From the Conclusion:
“We were able to demonstrate a statistically significant correlation of the observed adverse effect of hypoxia and the symptom of fatigue with p < 0.05 in the quantitative evaluation of the primary studies. Our review of the literature shows that both healthy and sick people can experience Mask-Induced Exhaustion Syndrome (MIES), with typical changes and symptoms that are often observed in combination, such as an increase in breathing dead space volume [22,24,58,59], increase in breathing resistance [31,35,60,61], increase in blood carbon dioxide [13,15,17,19,21,22,23,24,25,26,27,28,29,30,35], decrease in blood oxygen saturation [18,19,21,23,28,29,30,31,32,33,34], increase in heart rate [23,29,30,35], increase in blood pressure [25,35], decrease in cardiopulmonary capacity , increase in respiratory rate [15,21,23,34,36], shortness of breath and difficulty breathing [15,17,19,21,23,25,29,31,34,35,60,71,85,101,133], headache [19,27,29,37,66,67,68,71,83], dizziness [23,29], feeling hot and clammy [17,22,29,31,35,44,71,85,133], decreased ability to concentrate , decreased ability to think [36,37], drowsiness [19,29,32,36,37], decrease in empathy perception , impaired skin barrier function [37,72,73] with itching [31,35,67,71,72,73,91,92,93], acne, skin lesions and irritation [37,72,73], overall perceived fatigue and exhaustion [15,19,21,29,31,32,34,35,69] (Figure 2, Figure 3 and Figure 4).”
The harms we document are “statistically significant”. That is, the difference in harm from wearing a mask compared with not wearing a mask is great enough to rule out chance. These harms are proved, and they are numerous. The disruption of normal breathing is unhealthy.
“In our work, we have identified scientifically validated and numerous statistically significant adverse effects of masks in various fields of medicine, especially with regard to a disruptive influence on the highly complex process of breathing and negative effects on the respiratory physiology and gas metabolism of the body (see Figure 2 and Figure 3). The respiratory physiology and gas excThe result of significant changes in blood gases in the direction of hypoxia (drop in oxygen saturation) and hypercapnia (increase in carbon dioxide concentration) through masks, thus, has the potential to have a clinically relevant influence on the human organism even without exceeding normal limits.hange play a key role in maintaining a health-sustaining balance in the human body [136,153]. ...”
"There were studies showing no negative effects from masks, which we did not take seriously, for various reasons. For example, some had no control groups. Some were too small too prove anything. Some should not be trusted because of conflicts of interest. Some didn’t even use masks! And even a well done study that mentions no negative effects doesn’t mean there were none – only that they weren’t mentioned, it not being the mission of the research to document them.
“For a compilation of studies with harmless results when using masks, reference must, therefore, be made to reviews with a different research objective, whereby attention must be paid to possible conflicts of interest there. Some of the studies excluded by us lacking negative effects have shown methodological weaknesses (small, non-uniform experimental groups, missing control group even without masks due to corona constraints, etc.) . In other words, if no negative concomitant effects were described in publications, it does not necessarily mean that masks have exclusively positive effects. It is quite possible that negative effects were simply not mentioned in the literature and the number of negative effects may well be higher than our review suggests.”
The famous N95 mask filters better than other masks, at the cost of greater airway resistance and more dead air space. That made the N95 mask great for our study because its negative effects are greater, making them easier to measure.
“The most commonly used personal particulate matter protective equipment in the COVID-19 pandemic is the N95 mask . Due to its characteristics (better filtering function, but greater airway resistance and more dead space volume than other masks), the N95 mask is able to highlight negative effects of such protective equipment more clearly than others (Figure 3). Therefore, a relatively frequent consideration and evaluation of N95 masks within the studies found (30 of the 44 quantitatively evaluated studies, 68%) is even advantageous within the framework of our research question”
How Masks Harm
Not all of the air we exhale leaves our body. Some of it doesn’t get clear of our throats and noses, and we breathe back in its carbon dioxide. We call this amount of re-breathed air “dead space volume”. Wearing a mask almost doubles this “dead space volume”, lowering the oxygen and raising the carbon dioxide in our blood.
“According to the studies we found, a dead space volume that is almost doubled by wearing a mask and a more than doubled breathing resistance (Figure 3) [59,60,61] lead to a rebreathing of carbon dioxide with every breathing cycle [16,17,18,39,83] with—in healthy people mostly—a subthreshold but, in sick people, a partly pathological increase in the carbon dioxide partial pressure (PaCO2) in the blood [25,34,58].”
This forces mask wearers to breathe faster. It makes lung muscles work harder. Mask training doesn’t change this.
“According to the primary studies found, these changes contribute reflexively to an increase in respiratory frequency and depth [21,23,34,36] with a corresponding increase in the work of the respiratory muscles via physiological feedback mechanisms [31,36]. Thus, it is not, as initially assumed, purely positive training through mask use. This often increases the subliminal drop in oxygen saturation SpO2 in the blood [23,28,29,30,32], which is already reduced by increased dead space volume and increased breathing resistance [18,31].
Oxygen drop increases heart and breathing rate, and blood pressure.
“The overall possible resulting measurable drop in oxygen saturation O2 of the blood on the one hand [18,23,28,29,30,32] and the increase in carbon dioxide (CO2) on the other [13,15,19,21,22,23,24,25,26,27,28] contribute to an increased noradrenergic stress response, with heart rate increase [29,30,35] and respiratory rate increase [15,21,23,34], in some cases also to a significant blood pressure increase [25,35].” Even when oxygen/carbon dioxide imbalance isn’t serious enough to cause measurable harm, or even enough to notice, it causes reactions in important control centers in the brain.
“Even subthreshold changes in blood gases such as those provoked when wearing a mask cause reactions in these control centers in the central nervous system. Masks, therefore, trigger direct reactions in important control centers of the affected brain via the slightest changes in oxygen and carbon dioxide in the blood of the wearer [136,154,155].”
Disturbed breathing increases hypertension and sleep apnea. It is the main trigger for the Sympathetic Stress Response.
“A link between disturbed breathing and cardiorespiratory diseases such as hypertension, sleep apnea and metabolic syndrome has been scientifically proven [56,57]. Interestingly, decreased oxygen/O2blood levels and also increased carbon dioxide/CO2 blood levels are considered the main triggers for the sympathetic stress response [38,136]. The aforementioned chemo-sensitive neurons of the nucleus solitarius in the medulla are considered to be the main responsible control centers [136,154,155]. Clinical effects of prolonged mask-wearing would, thus, be a conceivable intensification of chronic stress reactions and negative influences on the metabolism leading towards a metabolic syndrome. The mask studies we found show that such disease-relevant respiratory gas changes (O2 and CO2) [38,136] are already achieved by wearing a mask [13,15,18,19,21,22,23,24,25,26,27,28,29,30,31,32,33,34]. A connection between hypoxia, sympathetic reactions and leptin release is scientifically known .”
Psychological research links health-promoting breathing to positive emotion and drive. Masks impede good breathing.
“Additionally important is the connection of breathing with the influence on other bodily functions [56,57], including the psyche with the generation of positive emotions and drive . The latest findings from neuro-psychobiological research indicate that respiration is not only a function regulated by physical variables to control them (feedback mechanism), but rather independently influences higher-level brain centers and, thus, also helps to shape psychological and other bodily functions and reactions [153,157,158]. Since masks impede the wearer’s breathing and accelerate it, they work completely against the principles of health-promoting breathing [56,57] used in holistic medicine and yoga. According to recent research, undisturbed breathing is essential for happiness and healthy drive [157,159], but masks work against this.”
Oxygen/carbon dioxide doesn’t just affect organs. It affects cells. Not only cells, but genes. It inhibits stem cells, promotes tumor cells, and causes inflammation. How interesting all this is for researchers!
“According to the latest scientific findings, blood-gas shifts towards hypoxia and hypercapnia not only have an influence on the described immediate, psychological and physiological reactions on a macroscopic and microscopic level, but additionally on gene expression and metabolism on a molecular cellular level in many different body cells. Through this, the drastic disruptive intervention of masks in the physiology of the body also becomes clear down to the cellular level, e.g., in the activation of hypoxia-induced factor (HIF) through both hypercapnia and hypoxia-like effects . HIF is a transcription factor that regulates cellular oxygen supply and activates signaling pathways relevant to adaptive responses. e.g., HIF inhibits stem cells, promotes tumor cell growth and inflammatory processes . Based on the hypoxia- and hypercapnia-promoting effects of masks, which have been comprehensively described for the first time in our study, potential disruptive influences down to the intracellular level (HIF-a) can be assumed, especially through the prolonged and excessive use of masks. Thus, in addition to the vegetative chronic stress reaction in mask wearers, which is channeled via brain centers, there is also likely to be an adverse influence on metabolism at the cellular level. With the prospect of continued mask use in everyday life, this also opens up an interesting field of research for the future.”
As early as 1983 the WHO noted the harm from the carbon dioxide buildup indoors, compared to outdoors. Those harms overlap the harms experienced from masks. Since masks are required especially indoors, the buildup is multiplied.
“The fact that prolonged exposure to latently elevated CO2 levels and unfavorable breathing air compositions has disease-promoting effects was recognized early on. As early as 1983, the WHO described “Sick Building Syndrome” (SBS) as a condition in which people living indoors experienced acute disease-relevant effects that increased with time of their stay, without specific causes or diseases [161,162]. The syndrome affects people who spend most of their time indoors, often with subliminally elevated CO2 levels, and are prone to symptoms such as increased heart rate, rise in blood pressure, headaches, fatigue and difficulty concentrating [38,162]. Some of the complaints described in the mask studies we found (Figure 2) are surprisingly similar to those of Sick Building Syndrome . Temperature, carbon dioxide content of the air, headaches, dizziness, drowsiness and itching also play a role in Sick Building Syndrome. On the one hand, masks could themselves be responsible for effects such as those described for Sick Building Syndrome when used for a longer period of time. On the other hand, they could additionally intensify these effects when worn in air-conditioned buildings, especially when masks are mandatory indoors.”
People who are overweight, have COPD, or sleep apnea (in other words, many of the people who come to hospitals) already suffer elevated carbon dioxide levels, further multiplying the effects of masks and being indoors. Extended mask use for these people heightens the risk of serious diseases and death.
“The already often elevated blood carbon dioxide (CO2) levels in overweight people, sleep apnea patients and patients with overlap-COPD could possibly increase even further with everyday masks. Not only a high body mass index (BMI) but also sleep apnea are associated with hypercapnia during the day in these patients (even without masks) [19,163]. For such patients, hypercapnia means an increase in the risk of serious diseases with increased morbidity, which could then be further increased by excessive mask use [18,38].”
Masks don’t harm everyone, but we should expect long term exposure to even a very mild poison to generally cause long term disease.
“Wearing masks does not consistently cause clinical deviations from the norm of physiological parameters, but according to the scientific literature, a long-term pathological consequence with clinical relevance is to be expected owing to a longer-lasting effect with a subliminal impact and significant shift in the pathological direction.
Harms that all mask wearers consistently suffer are increase in carbon dioxide in the blood, increase in heart rate, and increase in respiratory rate. Long exposure to these effects obviously causes high blood pressure, arteriosclerosis, heart disease, and neurological (nerve) disease.
“For changes that do not exceed normal values, but are persistently recurring, such as an increase in blood carbon dioxide [38,160], an increase in heart rate  or an increase in respiratory rate [56,57], which have been documented while wearing a mask [13,15,17,19,21,22,23,24,25,26,27,28,29,30,34,35] (Figure 2), a long-term generation of high blood pressure [25,35], arteriosclerosis and coronary heart disease and of neurological diseases is scientifically obvious [38,55,56,57,160].”
The general principle, that even very low exposure to mild poisons but over a long period cause significant sickness, is a theme of environmental studies.
“This pathogenetic damage principle with a chronic low-dose exposure with long-term effect, which leads to disease or disease-relevant conditions, has already been extensively studied and described in many areas of environmental medicine [38,46,47,48,49,50,51,52,53,54].”
Our studies prove (as if it were not already obvious) that extended mask wearing harms the oxygen/carbon dioxide balance in the blood, induces a chronic sympathetic stress response, which reduces immunity along with diseases of the heart and nerves.
“Extended mask-wearing would have the potential, according to the facts and correlations we have found, to cause a chronic sympathetic stress response induced by blood gas modifications and controlled by brain centers. This in turn induces and triggers immune suppression and metabolic syndrome with cardiovascular and neurological diseases.”
We didn’t just establish long term consequences. Short term effects include headache, exhaustion, skin redness and itching, and germ colonies.
“We not only found evidence in the reviewed mask literature of potential long-term effects, but also evidence of an increase in direct short-term effects with increased mask-wearing time in terms of cumulative effects for: carbon dioxide retention, drowsiness, headache, feeling of exhaustion, skin irritation (redness, itching) and microbiological contamination (germ colonization) [19,22,37,66,68,69,89,91,92].”
Logically, these effects reach to individual cells, causing inflammation of cells and promoting cancer, contrasting with the level of health prior to wearing masks.
“...Theoretically, the mask-induced effects of the drop in blood gas oxygen and increase in carbon dioxide extend to the cellular level with induction of the transcription factor HIF (hypoxia-induced factor) and increased inflammatory and cancer-promoting effects  and can, thus, also have a negative influence on pre-existing clinical pictures.”
Masks Don’t Reduce Oxygen?
News reports are no more interested in citing evidence than CDC director Walesky was in her tweet I review under the heading “Miracle Masks” above.
Here is a report from a TV news broadcast, way back July 14, 2020, but still top ranking in internet searches.
It shows a doctor putting on 6 face masks with an oxygen sensor on his finger to “prove” masks don’t reduce oxygen levels.
Not even after a whole half a minute!
“C’mon, man!” (To quote our President.) And his first mask isn’t even on until the first 25 seconds of it? It is possible to hold your breath for 30 seconds without blood oxygen levels dipping on a finger meter. Studies showing oxygen drops don’t talk about minutes, but hours.
I notice that he has his mask far up on his nose, almost covering his eyes, without that little metal piece conforming the mask to the outline of the face, allowing plenty of air to go around the masks even if the masks were made of metal.
Anyway, this article is full of flat statements like
“According to the American Lung Association, there has been a tremendous amount of disinformation spreading regarding the use of masks. Dr. David G. Hill said masks “absolutely” do not cause lower oxygen levels. “We wear masks all day long in the hospital. The masks are designed to be breathed through and there is no evidence that low oxygen levels occur,” Hill said.
Then come the caveats.
“Hill said there is some evidence that prolonged use of N-95 masks in patients with preexisting lung disease could cause some build-up of carbon dioxide levels in the body. “People with preexisting lung problems should discuss mask wearing concerns with their health care providers,” Hill said.
Masks won’t cause a CO2 buildup if you are healthy, but if you have a lung condition, they will feel sorry for you and let the oxygen through. Ah, modern “science”. (The link to the American Lung Association is dated June 18, 2020. It just repeats the Dr. Hill quote.)
Study where masks reduced oxygen & raised CO2 reported as "Face masks DON'T restrict oxygen or..."
Face masks DON'T restrict oxygen or contribute to carbon dioxide buildup: study Fox News Published October 2, 2020 10:26am EDT
(The Denmark study was published a month later, the German review the following April. The German study did not address this one.)
“Effect of Face Masks on Gas Exchange in Healthy Persons and Patients with COPD,” which was published in the Annals of the American Thoracic Society
The small study included 15 military veterans with severe COPD, each with lung function under 50%, and 15 healthy participants. All participants wore masks for 30 minutes and were told to walk for six minutes while wearing the surgical masks. Researchers then gave each participant a blood test and discovered there were no differences in levels of oxygen or carbon dioxide. “This data find that gas exchange is not significantly affected by the use of surgical mask, even in subjects with severe lung impairment,” Campos said in the study.
Comment: Hmmm. A very small study. What is “significant” to these people?
Here’s the actual study.
“At 5 and 30 minutes, no major changes in end-tidal CO2 or oxygen saturation as measured by pulse oximetry of clinical significance were noted at any time point in either group at rest (Table 1). With the 6-minute walk, subjects with severe COPD decreased oxygenation as expected (with two qualifying for supplemental oxygen). However, as a group, subjects with COPD did not exhibit major physiologic changes in gas exchange measurements after the 6-minute walk test using a surgical mask, particularly in CO2 retention.
Table 1 shows that healthy physicians indeed experienced lower oxygen levels by a quarter of a percent (0.28%) but that didn’t count as “clinically significant” because that was within what the general population calls the “margin of error” but what statisticians call the “Confidence Interval”, or CI. 97.5% is the “baseline”, or the oxygen saturation rate before the test, so the drop was to 97.22%, but it would have had to drop to below 95% to escape the “margin of error” boundaries. Hence, news reporters say “no significance”.
How about a longer test?!!!
That drop occurred after only five minutes wearing a mask, while resting. No exercise. After 30 minutes of wearing a mask at rest oxygen had actually slightly increased a tenth of a percent over baseline, to 97.6%.
As for CO2 “baseline” [the measurement before the test started] was 36.2%. The rise was to 37.26%. The “Confidence Interval” [the range of results, higher and lower, which we can be 95% confident others will experience] reached up to 40%. After 30 minutes wearing a mask the rise was still up to 36.95%.
Breathing got a little faster. Baseline was 17.2 breaths per minute. After 5 masked minutes it rose to 17.72; after 30 minutes, 18.33. But CI reached up to 21.
For those with severe COPD, “baseline” for oxygen was 91.3% After 5 minutes their average was actually up to 91.65%. After 30 minutes at rest it was higher: to 92.17% But after 6 minutes of walking it dropped to 89.02%. The CI allowed a drop below 89% before calling it “statistically significant”.
CO2 levels dropped slightly at all three points: after 5 minutes, 30 minutes, and after 6 minutes of walking.
Breathing dropped slightly from 20.5 breaths per minute to 20.38 after 5 minutes, but rose to 21.53 after 30 minutes at rest, and to 23.8 after 6 minutes of walking. It could have risen to 35 without escaping the CI.
The study concludes, “our population offers a clear signal on the nil effect of surgical masks on relevant physiological changes in gas exchange under routine circumstances (prolonged rest, brief walking).”
Apparently “nil” doesn’t mean “zero” in the vocabulary of these researchers, because two sentences later they write “As shown, we observed a small drop in oxygen pressure/tension in this group, expected based on their disease severity, but not a rise in Pco2 [carbon dioxide tension/partial pressure ] after walking.”
In dictionaries, however, “nil” does mean “zero” and “nothing”. So the two claims clearly clash. However, contradictions in medical research offer the blessing of choice to news reporters.
The only thing this study proves to me is the need for a longer study than 30 minutes! Can 30 minutes measure the impact of masks after 30 months, of 40 hours a week? Which is 1,800 times longer than 30 minutes! I will expect a small change after 30 minutes to not be small after it germinates 1,800 times longer.
Masks violate OSHA standards
"Oxygen deficient atmosphere means an atmosphere with an oxygen content below 19.5% by volume." OSHA Carbon dioxide content of air that workers breathe must remain above 1,000 ppm (one part per thousand) or less. In other words, 0.1%.”
Obviously masks reduce oxygen and increase carbon dioxide, and the more so, the harder someone is breathing, such as during exercise. It can't take very much heavy breathing to push the 20.95% oxygen level in our atmosphere down below 19.5%, and to push the 0.04% carbon dioxide level up above 0.1%. (Wikipedia).
A video by Peggy Hall from The Healthy American shows that people wearing a mask are breathing oxygen levels below what OSHA defines as safe. Medical professionals often wear masks for hours during surgery or when taking care of individuals with immune deficiencies. But wearing a mask while standing or walking slowly puts much less dramatic strain on one's body than while exercising or working harder.
Joseph Mercola reports, "Some people have suffered dangerous and even lethal consequences from wearing a mask while exercising. When levels of carbon dioxide rise too high, it can initially trigger symptoms such as headaches, fatigue, poor concentration, nausea and breathing difficulties", according to the Wisconsin Department of Health Services. Mercola reported several cases of people dying from heavy exercise while wearing masks, but I don't trust the stories because they were all in China.
Masks DON’T Violate OSHA Standards?
This article is not dated, but it contains a July 21, 2020 tweet.
It is a “FALSE CLAIM”, CBIA.com says,
“that [OSHA’s] respiratory protection standard, its permit-required confined space standard, and its air contaminants standard apply to the issue of oxygen or carbon levels resulting from the use of medical masks or cloth face coverings in work settings under normal ambient air, such as healthcare settings, offices, retail, and construction.”
It is false, according to OSHA’s explanation, not because the lower oxygen levels that violate OSHA standards for ships and tanks have been discovered not to create health risks after all, but because they do not legally apply to wearing medical masks outside ships and tanks.
Um, who said they did?
The argument that masks are unhealthy as measured by the fact that they bring down oxygen levels below what OSHA classifies as healthy levels is not made out of concern that OSHA will fine you for wearing a mask, but is made out of concern that masks are unhealthy. Recognition of that fact by a federal agency that enforces its standard against businesses, even if it does so selectively, is a valuable point to make to lawmakers, hospital administrators, and courts. The inconsistency of OSHA, in endorsing masks in retail and other public settings, does not cancel its establishment of the level of lowered oxygen and increased CO2 that is unsafe. Because the needs of our physical bodies for oxygen do not change from when we are inside a ship or tank, or outside.
The article continues, stating the obvious which is irrelevant to health concerns, “”These standards do not apply to wearing medical masks or cloth face coverings in work settings in normal ambient air. These standards would only apply to work settings with known or suspected sources of chemicals, like manufacturing facilities, or where workers are required to enter into a potentially dangerous location, such as a large tank or vessel.”
Unfortunately OSHA’s concern for health in tanks and ships is not shared with the rest of us. It’s FAQ’s admit there is carbon dioxide buildup, but without links to any evidence, assumes it is “not at unsafe levels”.
Here is OSHA’s complete statement:
Does wearing a medical/surgical mask or cloth face covering cause unsafe oxygen levels or harmful carbon dioxide levels to the wearer?
No. Medical masks, including surgical masks, are routinely worn by healthcare workers throughout the day as part of their personal protective equipment (PPE) ensembles and do not compromise their oxygen levels or cause carbon dioxide buildup. They are designed to be breathed through and can protect against respiratory droplets, which are typically much larger than tiny carbon dioxide molecules. Consequently, most carbon dioxide molecules will either go through the mask or escape along the mask's loose-fitting perimeter. Some carbon dioxide MIGHT collect between the mask and the wearer's face, but not at unsafe levels.
Like medical masks, cloth face coverings are loose-fitting with no seal and are designed to be breathed through. In addition, workers may easily remove their medical masks or cloth face coverings periodically (and when not in close proximity with others) to eliminate any negligible build-up of carbon dioxide that might occur. Cloth face coverings and medical masks can help prevent the spread of potentially infectious respiratory droplets from the wearer to their co-workers, including when the wearer has COVID-19 and does not know it.
Some people have mistakenly claimed that OSHA standards (e.g., the Respiratory Protection standard, 29 CFR 1910.134; the Permit-Required Confined Space standard 29 CFR 1910.146; and the Air Contaminants standard, 29 CFR 1910.1000) apply to the issue of oxygen or carbon dioxide levels resulting from the use of medical masks or cloth face coverings in work settings with normal ambient air (e.g. healthcare settings, offices, retail settings, construction). These standards do not apply to the wearing of medical masks or cloth face coverings in work settings with normal ambient air. These standards would only apply [meaning, legally] to work settings where there are known or suspected sources of chemicals (e.g., manufacturing facilities) or workers are required to enter a potentially dangerous location (e.g., a large tank or vessel).
"Evidence that masks help is lacking. Their harms are established."
National Institutes of Health published a review of over 100 mask studies January, 2021, which had been earlier published online November 22, 2020. One of its conclusions, from its abstract (summary): “Although, scientific evidence supporting facemasks’ efficacy is lacking, adverse physiological, psychological and health effects are established.”
The study was “retracted” four months later, May 12, 2021] but the “retraction notice” gives no reason, even though the NIH Retraction Policy says "The notice should also clearly specify the reason that the article is invalid." The Notice identifies no error in the study or any other reason that would justify retraction; it doesn’t allege that the study contained any error. Since the study is full of footnotes to the research it reviewed, and since it is undeniable that masks reduce oxygen intake while increasing carbon dioxide intake, and since lowering oxygen levels obviously is not medically smart, and since its conclusions generally line up with the German study which is still published and available online, I will report this information until somebody shows me significant errors in it. The quotes below are from the study. The study is archived here.
A cure worse than the disease. The study begins with the implied question: Are masks a cure worse than the disease? The mortality of covid is like that of Influenza - about 0.1%. It rarely causes death by itself. While masks are unsafe, ineffective, psychologically harmful, and bad for health.
The effects of less oxygen
“Acute” deprivation of oxygen or buildup of carbon dioxide “even for a few minutes can be seriously harmful or lethal....[while] chronic mild or moderate hypoxemia [less oxygen] and hypercapnia [more CO2] such as from wearing facemasks result[s] in shifting to higher contribution of anaerobic energy metabolism [where tissues consume glycol and glycogen to stay alive until normal oxygen is restored, which the brain can’t do very much], decrease in pH levels and increase in cells and blood acidity, [lowering the PH makes the blood more acid], toxicity, [poison], oxidative stress [damage to cells and tissue], chronic inflammation [inflammation that can last for years], immunosuppression [suppression of the immune system] and health deterioration.”
More medical conditions from lowered oxygen
“In normal conditions at the sea level, air contains 20.93% O2 and 0.03% CO2, providing partial pressures of 100 mmHg and 40 mmHg for these gases in the arterial blood, respectively. These gas concentrations [are] significantly altered when breathing occurs through facemask. ...trapped air remaining between the mouth, nose and the facemask is rebreathed repeatedly in and out of the body, containing low O2 and high CO2 concentrations, causing hypoxemia and hypercapnia....Low oxygen content in the arterial blood can cause myocardial ischemia, serious arrhythmias, right or left ventricular dysfunction, dizziness, hypotension, syncope and pulmonary hypertension . Chronic low-grade hypoxemia and hypercapnia as result of using facemask can cause exacerbation of existing cardiopulmonary, metabolic, vascular and neurological conditions....
Not just lowered oxygen: more germs, poisons, heat
“In addition to hypoxia and hypercapnia, breathing through [a] facemask [builds up] residues [of] bacteria and germs...on the inner and outside layer of the facemask. These toxic components are repeatedly rebreathed back into the body, causing self-contamination. Breathing through facemasks also increases temperature and humidity in the space between the mouth and the mask, resulting [in] a release of toxic particles from the mask’s materials. A systematic literature review estimated that aerosol [through the air] contamination levels of facemasks includ[ed greater exposure to] 13 to 202,549 different viruses.
“Rebreathing contaminated air with high bacterial and toxic particle concentrations along with low O2 and high CO2 levels continuously challenge the body homeostasis, causing self-toxicity and immunosuppression.”
Stress to heart and lungs
“Oxygen deficiency overworks [the] lungs and heart, slows brain and coordination. A study on 39 patients with renal disease found that wearing N95 facemask[s] during hemodialysis significantly reduced arterial partial oxygen pressure (from PaO2 101.7 to 92.7 mm Hg), increased respiratory rate (from 16.8 to 18.8 breaths/min), and increased the occurrence of chest discomfort and respiratory distress. Respiratory Protection Standards from [the] Occupational Safety and Health Administration, US Department of Labor states that breathing air with O2 concentration below 19.5% is considered oxygen-deficiency, causing physiological and health adverse effects.
===Disruption of clear thinking
“These include increased breathing frequency, accelerated heartrate and cognitive impairments related to thinking and coordination. A chronic state of mild hypoxia and hypercapnia has been shown as primarily mechanism for developing cognitive dysfunction based on animal studies and studies in patients with chronic obstructive pulmonary disease.
Surgeons’ 4x more headaches, faster heartrate, lower oxygen levels
The adverse physiological effects were confirmed in a study of 53 surgeons where surgical facemask[s] were used during a major operation. After 60 min of facemask wearing the oxygen saturation dropped by more than 1% and heart rate increased by approximately five beats/min. Another study among 158 health-care workers using protective personal equipment primarily N95 facemasks reported that 81% (128 workers) developed new headaches during their work shifts as these become mandatory due to COVID-19 outbreak. For those who used the N95 facemask greater than 4 h per day, the likelihood for developing a headache during the work shift was approximately four times higher [Odds ratio = 3.91, 95% CI (1.35–11.31) p = 0.012], while 82.2% of the N95 wearers developed the headache already within ≤10 to 50 min .
List of potential medical harms
• Shortness of breath
• Increase lactate concentration
• Decline in pH levels
• Increase in stress hormones level (adrenaline, noradrenaline and cortisol)
• Increased muscle tension
• Activation of “fight or flight” stress response
• Chronic stress condition
• Mood disturbances
• Compromised cognitive performance
• Increased predisposition for viral and infection illnesses
• Cardiovascular disease
• Alzheimer disease
• Exacerbation of existing conditions and diseases
• Accelerated aging process
• Health deterioration
• Premature mortality
Tiny germs, wide open spaces
“Due to the difference in sizes between SARS-CoV-2 diameter and facemasks thread diameter (the virus is 1000 times smaller), SARS-CoV-2 can easily pass through any facemask.” (From the beginning of the Covid scare, the widely published hope was that most of the virus would be carried through the air on droplets so much bigger than the virus that masks could stop them. But the research summarized next, showing zero benefit from masks, should have dashed that unsupported hope.)
Research settles it. Even before covid, “no protective effect” against “viral infections or influenzalike illness” was found in six randomized control trials (RCT’s). 23 “observational” studies reviewed by this report found no help against SARS, the family of viruses of which Covid is a member. Another review of 39 studies involving 33,867 participants found no help against “influenza or influenza-like illness”.
There was another review of 44 studies with 25,697 participants. “Although the overall findings showed reduced risk of virus transmission with facemasks, the analysis had severe limitations to draw conclusions.” For example, only four of the cases studied covid; of those, one found no cases in either arm of the study so no comparison was possible, and two had “unadjusted models” which couldn’t be compared.
So how did masks come to be mandated all over the world?
Was it the World Health Organization’s idea? “the WHO repeatedly announced that ‘at present, there is no direct evidence (from studies on COVID-19) on the effectiveness face masking of healthy people in the community to prevent infection of respiratory viruses, including COVID-19”.
Harm from masks was admitted from the beginning. (The study continues:) "Despite these controversies, the potential harms and risks of wearing facemasks were clearly acknowledged. These including self-contamination due to hand practice or non-replaced when the mask is wet, soiled or damaged, development of facial skin lesions, irritant dermatitis or worsening acne and psychological discomfort. Vulnerable populations such as people with mental health disorders, developmental disabilities, hearing problems, those living in hot and humid environments, children and patients with respiratory conditions are at significant health risk for complications and harm.’ ” “The Central for Disease Control and Prevention (CDC) made similar recommendation, stating that only symptomatic persons should consider wearing facemask.”
Cloth masks most dangerous
A huge RCT involving 14 hospitals found “there were no difference between wearing cloth masks, medical masks and no masks for incidence of clinical respiratory illness and laboratory-confirmed respiratory virus infections. However, a large harmful effect with more than 13 times higher risk [Relative Risk = 13.25 95% CI (1.74 to 100.97) was observed for influenza-like illness among those who were wearing cloth masks. The study concluded that cloth masks have significant health and safety issues including moisture retention, reuse, poor filtration and increased risk for infection, providing recommendation against the use of cloth masks.” Relationships. 249 studies involving 708,000 people showed somewhere between 13-50% greater deaths resulting from reduced contact with people. Masks compromise “Basic human-to-human connectivity through face expression...and self-identity is somewhat eliminated....reduced human-to-human connections are associated with poor mental and physical health.
Reduced Communication with Patients
This is not a published randomized study, or even a published news artice, but a testimonial, an “anecdotal” report. A Des Moines nurse told me her elderly patients, with hearing loss, rely on lip reading. So to talk to them, she has to step back six feet so she can take off her mask. That distance of course makes it harder to hear, and harder to see lips. She is furious with the requirement, knowing the research. Nurses on her wing are required by the hospital, following CDC guidelines, to wear shields over their masks, but the nurse in charge of the wing refuses to enforce that requirement.
Masks, like any sound-absorbant material, obstruct the sound of consonants, which are carried in the high frequencies from 1,000 to 4,000 Hz, or vibrations per second. Those frequencies are especially vulnerable to any obstacle; the higher the frequency, the less they can pass through obstacles like walls, and the less they can go around obstacles. I know that as a musician; that is why speakers for a musical performance, or for speeches or sermons, can have the big subwoofers anywhere, like on the floor, but the "tweeters" or "cones" must be elevated where anyone in the audience can see them. (So they are in their "line of sight".)
I myself have hearing loss, and sometimes I have to ask a nurse or doctor to take off his or her mask and repeat.
Children Struggle to Recognize Mask Wearers
“The main findings from this paper are that children struggle to recognize masked faces. We found a decrease of 20 percent in their ability to recognize masked faces, while the average decline is around 15 percent for adults,” Erez Freud, assistant professor in the Faculty of Health at York University in Canada, one of the researchers, told The Epoch Times in an email. The Study Summary
“Not only do masks hinder the ability of children to recognize faces, but they also disrupt the typical, holistic way that faces are processed,” Freud said in a statement. “If holistic processing is impaired and recognition is impaired, there is a possibility it could impair children’s ability to navigate through social interactions with their peers and teachers, and this could lead to issues forming important relationships.” The researchers did not challenge the assumption that masks prevent covid.
(There are many other studies showing the harm of masks for children other than medical harms. I give only this one example here, because it is a problem to which we can all relate, since adults’ recognition of each other is disrupted almost as much.)
Part 3 - PCR tests, most trusted of Covid tests: Unreliable
The CDC finally admits that PCR covid tests can't tell live from dead virus so they give positive results for 12 weeks after covid is gone.
The PCR test can't even distinguish between covid and other illnesses! The inventor of the PCR test, Kary Mullis, who won a Nobel Prize for his work, explains this in a video that is in an article by Joseph Mercola, from which this selection is summarized.
From the earliest days of the COVID pandemic, the PCR test has been a source of unrelenting controversy, with experts repeatedly pointing out that it’s not a valid diagnostic and produces inordinate amounts of false positives.
Importantly, a PCR test cannot distinguish between “live” viruses and inactive (noninfectious) viral particles. This is why it cannot be used as a diagnostic tool. As explained by Dr. Lee Merritt in her August 2020 Doctors for Disaster Preparedness1 lecture, media and public health officials appear to have purposefully conflated “cases” or positive tests with the actual illness in order to create the appearance of a pandemic. A PCR test cannot confirm that SARS-CoV-2 is the causative agent for clinical symptoms as the test cannot rule out diseases caused by other bacterial or viral pathogens. The inventor of the PCR test, Kary Mullis, who won a Nobel Prize for his work, explains this in the video.
Almost universally, health authorities have also instructed labs to use excessively high cycle thresholds (CTs) — i.e., the number of amplification cycles used to detect RNA particles — thereby ensuring a maximum of false positives.
From the start, experts noted that a CT over 35 is scientifically unjustifiable,2,3,4 yet the U.S. Food and Drug Administration and the U.S. Centers for Disease Control and Prevention recommended running PCR tests at a CT of 40, and the World Health Organization recommended a CT of 45. Reaction, Jon Rappoport, [ Youtube], FDA.
So why, now? What the CDC admits was known two years ago. CDC director Walesky answered CNN, "It really had a lot to do with what we thought people would be able to tolerate,” she said. Some have understandably translated that as “how much tyranny we thought people would be able to tolerate.”
In his MSNBC interview, Fauci was asked why health care workers are being treated differently, having to isolate for seven days rather than five, and still have to get a negative test, when the test can falsely remain positive for up to 12 weeks? What data supports this, and is it publicly available?
According to Fauci, the data to support this difference “is internal to the CDC,” but really, there’s “no specific data” to back it up, he adds. The CDC merely made “a judgment call.”
The CDC’s belated admission that the PCR test can’t identify active infection raises another question: What does this mean for those who died with a positive test? Did they actually have an active infection? If not, should they have been designated as COVID deaths?
The obvious answer to the last two questions is, of course, no. The vast majority were likely false positives, and the real death toll from COVID-19 considerably lower than we’re led to believe. The CDC undoubtedly knew this all along, seeing how they’ve been relentlessly criticized for their recommendation to run the PCR at a CT of 40. They’re trying to pretend that they just realized this, but that’s simply not believable.
Joseph Mercola writes, "The FDA has given emergency use authorization to 281 tests for COVID-19 but not one has received approval; this means their manufacturers have zero liability if the tests don’t work". September 23, 2022 email.
Several statements in Mercola's summary are from an [https://substack.com/redirect/fab9ae1c-acc0-4f48-af21-7767db00bf35?r=nvd3y interview of Dr. Meryl Nass, MD, a board-certified internal medicine physician with special expertise in bioterrorism and the Gulf War. Numbers below indicate the minutes and seconds into that interview.
The PCR Testing Fiasco
Problems with testing began almost immediately after the pandemic began. In the beginning, only tests from the U.S. Centers for Disease Control and Prevention were allowed, and the tests were virtually meaningless, as asymptomatic people were plagued by false positives. Host Dr. Paul Thomas described it as an epidemic of positive test results that got translated into an epidemic of the infection.⁷[36:50] According to Nass:⁸[37:11]
“For the first two months of the pandemic, the CDC only offered its own test, and it knew very early on that its test didn’t work … so the SARS-CoV-2 infection spread throughout the U.S. during January, February and early March of 2020, when CDC only allowed a few hundred people, maybe 1,000 people during that period of time, to be tested with their tests. And they all had to have a clinical picture that almost proved they had COVID.
After the whole country was really frustrated with this, FDA did two remarkable things … in the beginning of March, Stephen Hahn, the [now former] FDA commissioner, said OK, we’re going to now allow other entities — universities, labs, anybody who has developed or can develop a test for COVID — to do so, and send us the paperwork and we’ll work really fast to get it done and allow your tests to get out there.”
The paperwork, however, was so complicated that it took companies a week to complete it. By then it was the middle of March 2020 and there were still only a few tests available in the entire U.S.
“So then Stephen Hahn did something else. He said, OK, anyone who has a test for COVID, you start using it, you put it out there. You can start testing people, you’re allowed … you send us the paperwork in a few weeks.”⁹[38:53] At this point, testing basically turned into a free for all, with tests from China, Germany and other countries overseas coming in.
Nearly 300 EUA PCR Tests — Not One Approved
As of Nass’ latest count, the FDA has given emergency use authorization to 281 different PCR tests for COVID-19. Not a single one has been approved or licensed.
“This means, under emergency use authorization, you can’t sue the manufacturer if your test is no good,” Nass said. “And that means FDA doesn’t have to stand by any of those authorizations … no one’s responsible. So that’s a disaster. They’ve also authorized about 50 antibody tests and other rapid tests. So we have a testing mess, and we’ve always had a testing mess.”¹⁰[39:39]
The CDC also created an “odd” set of case definitions for COVID-19, basically turning “a positive test into a positive diagnosis even if you didn’t have symptoms.” The case definitions, Nass said, were so complicated they required reading through several pages of information and included whether or not the person was in an area were COVID-19 was present, whether the person had had an exposure to a known COVID case and a list of symptoms that helped formulate the definition.
She continued, “Despite all that, a positive PCR test was labeled a probable case. That’s all you really needed. And then the CDC relabeled probable cases as cases. So as everybody else has noticed, that meant we had a case-endemic. We didn’t exactly have an epidemic.”¹¹[41:00]
Hospitals Paid to Diagnose COVID Cases
The number of people who actually had and/or died from COVID in the beginning of the pandemic is unknown, because everybody who died “with COVID” was labeled a “COVID-caused” death. Health officials could count deaths from unrelated causes — even gunshots¹²CBS Local December 14, 2020 and motorcycle accidents¹³FOX 35 Orlando July 16, 2020 — as COVID-19 deaths if the person had the virus within the last 30 days. According to Nass:¹⁴[41:00]
“At the beginning, the number of cases, the number of people who died with COVID … everybody who died with COVID was called a COVID-caused death, and that was again due to the CDC playing with their definitions and hand coding all of their COVID deaths and requiring doctors, even if you went into the hospital with a heart attack and then they tested you in the hospital, you wound up being labeled a COVID death.”
Hospitals had every reason to go along with the questionable labels, as they earned more money if they diagnosed COVID-19 more often. They didn’t even need a positive test to do so. The end result is that the actual number of COVID-19 cases was heavily skewed and it may be impossible to sort out the real figures at this point:¹⁵[42:31]
“Hospitals were financially incentivized to up the number of COVID cases because they got paid more if their patients had a COVID diagnosis. And they were told by the CDC that they didn’t even need a positive test. If it looked like a COVID case, you could call it a COVID case and then up your reimbursement. So we were all stuck with that kind of shenanigans, and it’s hard to know now who were the COVID cases and who were the COVID deaths.”
This means all the numbers of COVID deaths you hear being bandied about by mainstream are major misinformation. They are nothing more than cleverly inflated statistics based on the major incentive to identify virtually every death they could as due to SARS-CoV-2. Best estimates are the number of deaths authentically due to COVID are at least half what they say they are.
Part 4 Vaccines Kill
Steve Kirsch Review of Evidence
From his Sept 21, 2022 email:
Kirsch calls it "A short collection of key pieces of evidence showing the COVID vaccines are not 'safe and effective.' Not even close. They are the most deadly vaccines we've ever produced."
"ere’s a high level collection of some of the most compelling pieces of evidence I’ve seen to date. This is not an exhaustive list, but just the key pieces of data that are impossible to explain if the vaccines are safe and effective.
"I’ve divided the collection into sections and I’ve tried to limit each section to the most compelling data points. So don’t be disappointed if your favorite item isn’t mentioned in this article; I wanted to keep it short enough to be read..
"I’ll try to keep this updated over time. It can be found in the Reference section of my Substack."
Here are the categories of evidence you will find at the link, each loaded with great links. After each category, I add very brief excerpts:
The phase 3 clinical trial data. The Pfizer trial 6 month report showed that more people died (and were injured) who got the drug than who got the placebo....The Pfizer vaccine had 4X as many cardiac arrests in the treatment group than the placebo.
The Pfizer trial 6 month report showed that at best, the drug saved only 1 COVID life per 22,000 recipients. This means that at best, after vaccinating 220M Americans, we might save 10,000 lives from COVID. But the Vaccine Adverse Event Reporting System (a database of side effects) lists well over 10,000 deaths caused by vaccines, and there is only about one VAERS report made for every 41 actual "adverse events".
Pfizer admitted to clinical trial fraud in federal court. Their defense was that the FDA was in on it.
Official government data Why are there more adverse events reported for these vaccines than for all other vaccines in history combined? The US Social Security Death Master File showed a 60% increase in the all-cause death rate in September 2021 vs. September 2020 for ages 18 to 55. Insurance companies aren’t asking the family of the policyholders who died whether they were vaccinated with the COVID vaccine and when. U.S. disability rose dramatically soon after the vaccines rolled out.
Statements from government officials. The Israeli Ministry of Health revealed in a confidential meeting with scientists that the reason that they never notified the people of Israel about the safety issues from the vaccines was because of budget/staffing issues.
Independent expert reports solicited by government officials. The Israeli vaccine safety data showed very clearly the side-effects are serious, long-lasting, and caused by the vaccines. Secondly, it showed that the Israeli authorities and the worldwide mainstream media are covering it all up.
The Canadian report prepared for the Liberal Party of Canada (Trudeau’s party) showed no benefit for infection, hospitalization, and death for those under 60. “The empirical evidence investigated in this report from PHO and PHAC does not support continuing mass vaccination programs, mandates, passports and travel bans for all age groups.”
Pre-prints from highly credible sources. ("Preprints" means research prepared for peer-reviewed publications which haven't been formally published yet. Formal publication often takes months and sometimes years after completion of the research.) The Thailand study did blood tests before vs. after the jab and determined that nearly 30% of young adults experienced cardiovascular injuries after the jab. This was a simple blood test before and after the vaccine. And why didn’t anyone in the US ever do such a study? Do we not want to know?
The study by Bhakdi and Burkhardt showing 93% of deaths after vaccination were caused by the vaccine.
Papers published in peer-reviewed medical journals. The Levi cardiac arrest rate elevation paper showed a troubling correlation between vaccine doses and increased cardiac events from January–May 2021. When they tried to get data after May 2021, they were refused access.
There are over 1,250 papers published in the scientific peer-reviewed literature showing the vaccines cause significant adverse events.
Articles by respected vaccine experts interpreting the data. Are the Covid mRNA Vaccines Safe? was written by Harvard professor Martin Kulldorff who until recently was on vaccine committees of the FDA and CDC. He wrote that It is the responsibility of the manufacturers and FDA to ensure that benefits outweigh harms. They have failed to do so.
Articles on court rulings and expert opinion. An analysis of Canadian court rulings on covid complained about over-reliance on government witnesses. Courts are supposed to find the truth and not rely on government representations or propaganda.
Articles debunking bogus studies in the peer-reviewed scientific literature.
Autopsy reports. There are specialized tests required to diagnose a death from the COVID vaccine. The CDC has never told any medical examiner in the US about these tests.
Retracted papers published in peer-reviewed journals. (After research is published in peer-reviewed journals, it can be retracted. When the reasons given make little sense we legitimately wonder if the real rejection was of reality. Their rules require reasons to be given. Fortunately copies of the research are still available online.)
Hard-to-explain anecdotes. ("Anecdotes" means, in research lingo, isolated cases which we might dismiss as just "one in a million".) The Died Suddenly group on Facebook was adding users at 20,000 per day making it the fastest growing group in Facebook history.
The embalmer data, such as pulling 30" long blood clots out of corpses of people recently vaccinated before formaldyhide could be pumped in.
Insurance company data from insurance companies worldwide: Adults Aged 35–44 Died at Twice the Expected Rate Last Summer, Life Insurance Data Suggests Millennials Experienced 84 Percent Rise of Excess Mortality’ Into Fall 2021: Former BlackRock Portfolio Manager.
My neurologist stats: 11 years without needing to do a single VAERS report; this year, she needs to file 1,000 VAERS reports on 20,000 patients in the practice. This is similar to the 4.5% rate of neurological injury reported earlier by the Israeli Ministry of Health.
A local news station (WXYZ-TV) asked people to report on unvaxxed loved ones that became sick and died and instead they got hammered with hundreds of thousands of people saying they lost loved ones to the jab.
Woman collapses and dies 7 minutes after Booster shot… The death was ruled as “natural causes”
Cancers. The doctors there told him they’ve seen a significant spike in cancer cases well above what could be explained by people missing getting screened due to the pandemic. What’s more though is that they catalogue the vaccine status of every cancer diagnosis and the spike in the number of cases is only occurring in those who are vaccinated-
Books. Turtles all the way down: Vaccine science and myth shows There isn’t a single risk-benefit trial on all cause mortality and morbidity vs. placebo for any of the 70 approved vaccines even though they’ve had 60 years to do this.
Dissolving Illusions: the history of vaccines shows they did a lot less than people think; probably next to nothing.
The Real Anthony Fauci: illustrates the corruption in the medical community today. For example, they created a more accurate adverse event reporting system (ESP:VAERS) system and then scrapped it after it showed all the vaccines were unsafe.
~ ~ ~ ~ (I'm running out of steam and am skipping excerpts under the remaining categories.)
Mitigation measures: masks, vaccines, lockdowns, social distancing, 6 foot rule, …
Origin of the virus investigation
Conflicts of interest
Early treatment options
Questions for lawmakers
Questions I’d like to ask the CDC
The unanswered questions
Articles about the corruption of science
Using all the available evidence
The precautionary principle of medicine
The Pfizer clinical trial showed the vaccine saved only one COVID death per 22,000 injected. That means we might only save around 10,000 lives if we inject 200M Americans. So if VAERS, which is at least 41 times under reported, is showing over 12,000 deaths associated with the vaccine, any reasonable person should say that killing more than 41 people to save 1 life is nonsensical… shouldn’t we put a PAUSE on this intervention until we resolve the uncertainty?
Higher Death Rate among the Vaccinated
October 27, 2021: "The Office for National Statistics reports on vaccine effectiveness are grossly underestimating the number of unvaccinated people," (which leads to gross overstatement of their death rate), according to a British study by Martin Neil, Norman Fenton and Scott McLachlan at Queen Mary, University of London, UK. This is proved by "numerous discrepancies and inconsistencies" in "current publicly available UK Government statistics" which have this additional shortcoming: they "do not include raw data on mortality by age category and vaccination status....To determine the overall risk-benefit of Covid-19 vaccines it is crucial to be able to compare the all-cause mortality rates between the vaccinated and unvaccinated in each different age category."
The study tries to establish the facts despite these limitations. Since many deaths have several causes, ("comorbidities"), making it a bit subjective which cause was the primary cause of death, it is useful to check how many people died of all causes. This certainly does not directly measure how many died of covid, but it is a way to double check covid death rate claims.
The study found that among the unvaccinated, 25.3 people per hundred thousand died during the two month study period. But 89.34 died among those with a single covid vaccine dose! However, 14.7 died among those with two doses. This is "hard to explain", the study concedes.
But after analyzing multiple conflicting sets of government figures, the study explains why "there is the possibility that as many as 22 million people...were unvaccinated rather than the 9.5 million reported." If that is so, then the reported death rate for the unvaccinated would be about 2.5 times too high.
"Our analysis clearly suggests that...all-cause mortality (UMR) for vaccinated people, compared to unvaccinated people, is certainly higher in single dosed individuals and slightly higher in those who are double dosed."
A summary of this study was published by The Independent Sentinal.
LOWER Death Rate among the Vaccinated
The CDC, as in the preceding British study, looked at "all cause" deaths - deaths from all causes, including accidents - and found that the COVID shot reduces your risk of dying from all causes.
All causes, that is, except from covid! "They filtered out anyone who had died from Covid-19 or after a recent positive coronavirus test", CNN reported. The CDC excluded covid related deaths, being interested only in whether covid shots reduce deaths from every other cause EXCEPT covid! The CDC decided they do! (As reported by CNN Health, October 22, 2021
"Part of this is probably because people who get vaccinated tend to be healthier than people who don't, the researchers noted." Do you get the sense that something is missing from this story?
Dr. Joseph Mercola pointed out in November 10 that this study used the same statistical gimmick that the CDC used to "claim 99% of COVID-19 deaths and 95% of COVID-related hospitalizations were occurring among the unvaccinated" - by counting months where hardly anyone was vaccinated, and stopping their count just before "a rapid rise in vaccine-related deaths reported to the U.S. Vaccine Adverse Events Reporting System (VAERS)".
He writes, "the mortality rate in 2021 is 14% above the 2018 rate" which had the highest all-cause death rate before covid. "The obvious question is, why did more people die in 2021 (January through August) despite the rollout of COVID shots in December 2020? Did COVID-19 raise the death toll despite mass vaccination, or are people dying at increased rates because of the COVID jabs?"
Mercola also links to Matthew Crawford whose analysis shows that covid shots killed an estimated 1,018 people per million doses in Europe. He analyzed data in the 23 nations with the clearest data, comprising a quarter of the world's population. He estimates an average death rate of 411 per million doses. At 673 million doses as of August 1, that comes out to 276,603 deaths caused by covid vaccines, not counting other adverse events.
Mercola also cites Steve Kirsch, executive director of the COVID-19 Early Treatment Fund, who estimates that 300,000 Americans alone have been killed by covid vaccines, as 2 to 5 million more have been injured.
This is close to the 205,809 death estimate made in the following study by Dr. Rose.
Covid vs. Other Vaccines: UNSAFE
Jessica Rose, Ph.D., who holds degrees in applied mathematics, immunology, computational biology, molecular biology and biochemistry, presented a [ slide show] explaining VAERS reports. (Vaccine Adverse Event Reports.)
Over the previous 10 years, the highest report totals, for all vaccines combined, for any adverse reaction, was less than 50,000 for the year. During the first eight months of 2021, the total reports for covid vaccines alone was 521,667. By October 22 it grew to 837,593.
Deaths alone, over the previous 10 years, caused by vaccines, never rose above 183 for any year. During the first eight months of 2021, the total was 7,662. By October 22, 17,619.
But these figures are vastly underreported, by an estimated factor of 31, called the URF, the "under-reporting factor". URF-adjusted, covid shots through August are responsible for 205,809 deaths, 81,747 Bell's palsy cases, 149,017 herpes zoster infections, 305,660 paresthesia, 528,457 myalgia cases, 230,113 miscellaneous life threatening events, 212,691 permanent disabilities, and 7,998 birth defects. Oh, and 365,955 "breakthrough cases", the name for when someone who is fully vaccinated miraculously gets covid anyway.
43% of VAERS reports are made within 48 hours of either jab, so studies of vaccine safety which don't count anyone as "fully vaccinated" until 10 days after the second jab conveniently leave out the majority of vaccine-caused injuries and deaths. By day 10, Dr. Rose's chart shows that the surge of reports has dropped to a low steady level.
Covid Vaccines: Safer than Natural Immunity! says CDC
Alex Berenson took this on the next day. He said the CDC relied on "raw data that actually showed almost four times as many fully vaccinated people being hospitalized with Covid as those with natural immunity — and FIFTEEN TIMES as many over the summer."
He linked to an August 25 preprint reaching the opposite conclusion.
He said the study runs counter to a much larger, much more honest study finding that "vaccinated people were 13 times as likely to be infected — and 7 times as likely to be hospitalized — as unvaccinated people with natural immunity."
Dr. Joseph Mercola summarizes Berenson's analysis, adding the analyses of Rep. Thomas Massie, Martin Kulldorff, Ph.D., professor of medicine at Harvard Medical School and a biostatistician and epidemiologist in the Division of Pharmacoepidemiology and Pharmacoeconomics at Brigham and Women's Hospital, along with his own observations.
Vaccines Kill More than they Cure
Fifth Largest Life Insurance Company Reports a “Catastrophic” 40% increase in deaths in 2021
Lincoln National Life Insurance Company’s Employer-provided Group Life Insurance policies for employees ages 18 through 64 paid out $500 M in death benefits in 2019, the year before the pandemic, and $548 million, a 9% increase in the 1st year of the pandemic, and out $1.4 Billion, in the first full year of the vaccine, in which about 90% of the adult population were vaccinated, and which included mandatory vaccines for employees of many companies). The $1.4 Billion in 2021 was a 163% increase over the amount paid in the 1st year of the pandemic. Lincoln National stated that these increases were due to “non-pandemic related morbidity” and “unusual claims adjustments”
Its CEO of One America Life Insurance company, said that “We are seeing, right now [in 4th quarter 2021] , the highest death rate we have seen in the history of this business — not just at One America. The data is consistent across every player in that business. [The increase in deaths represents ‘huge, huge numbers,’ and it’s not elderly people who are dying, but ‘primarily working age people 18-64’ who are the employees of companies that have group life insurance plans through One America]
And what we saw just in third quarter, [and are seeing in] the fourth quarter, is that death rates are up by 40% over what they were pre-pandemic. Just to give you an idea of how bad that is, a three sigma or a one in 200-year catastrophe would be 10% increase over pre-pandemic . . . So 40% is just unheard of.”
Lincoln National is a large life insurance company that’s so old that when it was started, the founders actually asked Abraham Lincoln’s son whether it was okay to use his father’s likeness in their company branding.
How many deaths are represented by the 163% increase? It is not possible to determine by the dollar figures on the statements.
But the average death benefit for employer-provided group life insurance, according to the Society for Human Resource Management, is one year’s salary.
If the average annual salary of people covered by group life insurance policies in the United States is $70,000, this may represent 20,647 deaths of working adults, covered by just this one insurance company. This would represent at least 10,000 more deaths than in a normal year for just this one company.
(source: Epoch Times)
Vaccines Kill 1 in 800 in Netherlands and England
"Now it’s very clear that there is a good correlation between the number of vaccinations that are given to people and the number of people that die within a week after that.” It is clear from seeing a jump in the total number of deaths in excess of the five-year-average of the number of deaths, while nothing else seems to have changed other than a huge new wave of covid shots. Dr. Schetters, a recipient of the Medal of Honour of the Faculty of Pharmacy at the University of Montpellier in France, said it is essential to look at all-cause mortality, as the vaccine “potentially affects all organs.”
In the Netherlands the booster rollout in different regions was staggered over a number of weeks allowing an analysis by region. In other words, using the U.S. for an example, Iowa has mass inocculations, and a week later thousands die beyond the average death rate. The death rate in other states is unchanged. Then Nebraska has mass inocculations, and a week later thousands die beyond the average death rate, while the death rate in other states remains unchanged. etc.
By comparing "all cause mortality" rates with past averages and with vaccine rollouts, Schetters roughly calculates that covid shots kill about one in 800 who get them.
An interview with Schetters, by Dr. Robert Malone who invented the mRNA process, describes many steps taken to rule out other possible causes.
An example of the correlation in England: August 2, 2022 figures from England's Office for National Statistics reveal that deaths from all causes were 18.1% higher - 1,680 - than the previous five-year average of "non-Covid deaths registered in England and Wales in the 13 weeks since April 23rd."
During that period, 4,182,483 spring covid boosters were given until July 22nd.
745 mentioned COVID-19 on the death certificate as a contributory cause and 463 mentioned COVID-19 as underlying cause, leaving 1,217 deaths from a different underlying cause.
England's government doesn't seem curious. "When Member of Parliament Esther McVey, Chair of the Pandemic Response and Recovery All-Party Parliamentary Group (APPG), submitted a written question asking the Cabinet Office what steps it was taking 'to investigate the higher than expected rate of deaths of 12.2% above the five-year average'", she was "referred to the U.K. Statistics Authority, which, in turn, ...said it will continue to publish the relevant statistics."
Dr. Theo Schetter, a vaccinologist based in the Netherlands who has played a leading role in the development of a number of vaccines, has analysed the official data from the Dutch Government and found a very close correlation between when fourth vaccine doses were administered in the country and the number of excess deaths. "The correlation is striking, , to the extent that if you have more vaccines in a week then you also have more excess deaths, and if you have fewer vaccines in a week, you have fewer deaths."
Dr. Schetters says he has written to the Director of the Institute of Health in the Netherlands to alert him to the findings. “…So what we’ve done is we have written a registered letter to the director of our Institute of Health and presenting the results and expressing my concerns....[and asking], please reconsider vaccination strategy."
Dr. Theo Schetters: "...of course, we do not get the real, what we call the granular data, which means that we do not have this from person by person. These are group type figures. So that group received that number of vaccines. And in that age group, you see this number of excess mortality. But we do not know whether this is really correlated one by one. And so that’s why we asked for more data, because Ronald Meester said – Ronald Meester is a professor in statistics and we’ve discussed it here and said, okay, give us those data within a week.
"We know what’s happening. Simple. But we can’t get the (granular) data. So that leaves us with a correlation, with an observation. But I think, by now, it’s getting so strong that at least, if you talk about precautionary measures- that’s the way they sold the vaccines, actually, they sold them as precautionary measures. So to keep us safe. Then I would say, I use the same argument now. If I see these correlations, although I cannot prove causality at the moment, from a precautionary measure, you should say let’s stop this."
(Clarification: this information is not from published research but from an interview.)
17,000 doctors: Stop the Jabs!
Dr. Robert Malone heads an organization of 17,000 doctors who agree covid vaccines should be halted.
“I stand as the President of the International Association of Physicians and Medical Scientists. So we’re 17,000 that are only physicians and medical scientists, all verified, no nurses, not because we don’t like nurses, but it has to do with the positioning with the press and messaging. So that’s the basis for our organisation.
“Months ago, we came out with a press conference in a clear unequivocal statement that one can find at www.globalcovidsummit.org where we made a clear, unambiguous statement. In our opinion, as an organisation, these vaccines should be withdrawn. They are no longer justified on a risk-benefit ratio. And as the person who is responsible for the genesis of this technology, I’m often criticised. Didn’t I realise what I was doing? And there’s no way for me to have known that the normal standards for regulatory development and testing and clinical would be circumvented.
“But I stand as someone who has intimate, detailed knowledge of the technology and its risks and benefits, the nature of the formulations, the role of the pseudouridine, [Pseudouridine is the most abundant modified type of nucleoside across all species of RNA] all of those things. It’s my opinion and that of the organisation that I represent, that the data are now sufficiently clear that, in our opinion, the ongoing campaign for vaccination is no longer warranted.”
Toddlers Getting Seizures from Vaccinations
Reported by Steven Kirsch July 5, 2022
I’m getting multiple reports from my nurse friends about kids 2 and 3 years old having seizures. It is ONLY happening on vaccinated kids, and symptoms start 2 to 5 days after the COVID vaccine.
The medical staff is not permitted to talk about the cases to the press or on social media or they will be fired....doctors are instructed to convince the parents that it isn’t vaccine related and that they are the only ones having the problem.
Total American deaths up 40% among vaccinated
Working age people (18 to 64) are dying at a rate that is 40% higher than prepandemic rate, reports OneAmerica, a national life insurance company. There is also an increase in long term disability claims. The Insurance Regulatory and Development Authority of India also reports a 41% rise in death claims in 2021. Deaths attributed to covid are significantly down from 2020 to 2021, leaving the experimental covid vaccines the only other medical event able to account for such a high death toll.
Scott Davidson, CEO of OneAmerica, explained: "death rates are up 40% over what they were pre-pandemic. Just to give you an idea of how bad that is, a three-sigma or a one-in-200-year catastrophe would be 10% increase over pre-pandemic. So, 40% is just unheard of." Statistician Steve Kirsch writes that “Normally death rates don’t change at all. They are very stable. It would take something REALLY BIG to have an effect this big. The effect size is 12-sigma. That is an event that would happen by pure chance every 2,832 years....It’s basically never."
Kirsch notes that There are more excess deaths than any time in history, indicating some very different, very new cause. Like the vaccine rollout, which is when total deaths rose. Deaths have a reported wide variety of causes, ruling out any single pathogen, but consistent with the fact that doctors and scientists have detailed several mechanisms of action by which the COVID shots can maim or kill.
So what is Scott Davidson's solution? Why, of course: require all OneNow employees to get vaccinated!
Meanwhile New York State AssemblymanPatrick Burke (D-Buffalo) proposed punitive legislation that would permit insurers to deny COVID-related treatment coverage for individuals who choose not to get vaccinated! And many of those injured by COVID vaccines report denials of health and disability insurance coverage!
Studies documenting vaccine deaths
(1) Covid vaccines cause 38% more cases, and 31% more deaths, according to a study named "Worldwide Bayesian Causal Impact Analysis of Vaccine Administration on Deaths and Cases Associated with COVID-19: A BigData Analysis of 145 Countries". (PDF)
The abstract of the study states: "The statistically significant and overwhelmingly positive causal impact after vaccine deployment on...total deaths and total cases per million...indicate a marked increase in both COVID-19 related cases and death due directly to a vaccine deployment.
(2) "The correlation between the excess mortality in [Germany] and their vaccination rate when weighted with the relative number of inhabitants...is .31. This number is surprisingly high and would be negative if vaccination were to reduce mortality. For the period under consideration (week 36 to week 40, 2021), the following applies: The higher the vaccination rate, the higher the excess mortality." PDF. The last clause is the title of the study.
(3) "This study shows that after three months the vaccine effectiveness of Pfizer & Moderna against Omicron is actually negative. Pfizer customers are 76.5% more likely and Moderna customers are 39.3% more likely to be infected than unvaxxed people." That is actually the first comment after the post on the medrxiv medical website. The comments criticize the study for rosy vaccine conclusions not supported by its own evidence.
(4) "German Government Data for the alleged Omicron variant of Covid-19, suggests that most of the 'fully vaccinated' will have full blown Covid-19 vaccine-induced acquired immunodeficiency syndrome (AIDS) by the end of January 2022, after confirming that the immune systems of the fully vaccinated have already degraded to an average of minus 87%." The Expose, analysis based on German official figures.
(5) "The latest figures published by the UK Health Security Agency show that despite the elderly and vulnerable receiving a booster shot in September and October, and the NHS turning into the National Booster Service ever since, the triple/double vaccinated population still accounted for 4 in every 5 Covid-19 deaths throughout December 2021." The Expose.
(6) "Lancet: 89% Of New UK COVID Cases Among Fully Vaxxed." - Principia Scientific International. In England, covid transmission was 25% of vaxxed families but 23% in unvaxxed. In Germany, "breakthrough cases" (where a fully vaxxed person gets covid) were 16.9% last July but had climbed to 58.9% by October 27, among people 60 and over. Back in England, "a total of 100,160 COVID-19 cases were reported among citizens of 60 years or older during weeks 39-42. 89,821 occurred among the fully vaccinated (89.7 percent), 3395 among the unvaccinated (3.4 percent)". "The week before...in all age groups over 30", the case rate was higher among the vaxxed than among the unvaxxed." In a study 14 fully vaxxed patients died or became seriously ill; the two unvaxxed patients only had mild disease. Lancet conclusion: "Many decision makers assume that the vaccinated can be excluded as a source of transmission. It appears to be grossly negligent to ignore the vaccinated population as a possible and relevant source of transmission when deciding about public health control measures."
(7) James Lyons-Weiler recently showed that the US state data shows that the more we vaccinate, the higher the # of COVID cases.
(8) "Increases in COVID-19 are unrelated to levels of vaccination across 68 countries and 2947 counties in the United States" That's the title of a study published at pubmed.
The introduction begins: "Vaccines currently are the primary mitigation strategy to combat COVID-19 around the world. For instance, the narrative related to the ongoing surge of new cases in the United States (US) is argued to be driven by areas with low vaccination rates." BUT...
"countries with higher percentage of population fully vaccinated have higher COVID-19 cases per 1 million people." "Of the top 5 counties that have the highest percentage of population fully vaccinated (99.9–84.3%), the US Centers for Disease Control and Prevention (CDC) identifies 4 of them as “High” Transmission counties. Chattahoochee (Georgia), McKinley (New Mexico), and Arecibo (Puerto Rico) counties have above 90% of their population fully vaccinated with all three being classified as 'High' transmission. Conversely, of the 57 counties that have been classified as 'low' transmission counties by the CDC, 26.3% have percentage of population fully vaccinated below 20%."
"Even though vaccinations [ostensibly] offers protection to individuals against severe hospitalization and death, the CDC reported an increase from 0.01 to 9% and 0 to 15.1% (between January to May 2021) in the rates of hospitalizations and deaths, respectively, amongst the fully vaccinated."
60 times more deaths from covid vaccines than all other vaccines combined, even though thousands of reports are being deleted
(Summarized from a Dr. Mercola report which is no longer online.)
Over the past 10 years before covid vaccines, the average number of deaths was 155 from all vaccines combined. There are now 60 times that many deaths from the covid vaccines alone. Over 10,000. Is there any number of deaths that should make Americans and our government treat the vaccines as unsafe?
As of November 26, 2021, the death toll was 8,986 in the U.S. and its territories, and 19,532 worldwide.
The VAERS (Vaccine Adverse Event Reports)is a central database of vaccine injuries established in 1990. It takes an average half an hour for a doctor to fill out the forms, and most people haven't heard of it so patients don't know they can fill out the information themselves; so only a fraction of "adverse events" are reported. Estimates range from 10%, to only 1% Steven Hirsch has calculated that for covid vaccines, there are 41 times more events than are reported. Jessica Rose found that Pfizer's own trial data supported 31 times more events. Ronald Kostoff has also published a paper in Toxicology Reports, and his estimate is 100.
The U.S. Food and Drug Administration and Centers for Disease Control and Prevention outrageously deny that a single death can be attributed to the COVID jabs. Jessica Rose, Ph.D., a research fellow at the Institute for Pure and Applied Knowledge in Israel, observes, “It's not even statistically plausible to say that not one death out of 10,000 was caused [by the shot]. It’s not scientific to say that ... Those people, not 100% of them would have died anyway? That's not how life works.”
The Bradford Hill criteria are 10 criteria of whether a death after a jab was actually caused by the jab. One is how soon after the jab a death occurred in a previously healthy person. About 50% of reported vaccine deaths are within 24 hours of the jab.
In addition to the underreporting factor, reports are actually being deleted! Rose investigated this after seeing videos saying hundreds, perhaps thousands, of people had their reports deleted. She’s been downloading all the data sets since January 2021, and comparing the data sets. They are updated each week, so she has copies of all of them and can see which reports are removed from later reports!
She confirmed the deletion of over 1,000 reports. 18% of them were deaths. A lot of babies' reports were removed, which could be because babies aren't supposed to get covid shots - although there is evidence in the VAERS reports that doctors are not confirming age before jabbing. 5,570 reports had a metric code indicating that the product was given to a patient of inappropriate age. But the removals are made without explanations.
"60 children had died between the ages of zero and 18, and 38% of those children were under 2. [The next week] that [reported] percentage went down to 30%....What happened to them?...there was this big chunk of data for the 50- to 75-year-olds pertaining to myocarditis reports last week, and this week, it's one-half."
To learn more, be sure to peruse Rose’s website, Jessica’s World. There, you’ll find links to videos in which she summarizes her various findings, and a weekly graphic update of the latest VAERS data for death, female reproductive issues, breakthrough COVID infections, cardiovascular events and immunological events.
Another excellent resource is OpenVAERS, which summarizes the most pertinent VAERS data for you on a weekly basis.
Vaccination Doubles the Death Rate
The death rate for England's vaccinated is double that of England's unvaccinated, the chart below shows. The chart shows how many people per 100,000 died during each month of all causes. That doesn't directly tell how many died of covid; maybe no vaccinated Englishmen died of covid, but they just happened to have twice as many auto accidents. However, the fact that twice as many vaccinated died as unvaccinated, without any alternative theory to explain the difference, certainly points to vaccinations as the cause of that many more deaths.
Alex Berenson, Thanksgiving Day 2021: The brown line represents weekly deaths from all causes of vaccinated people aged 10-59, per 100,000 people.
The blue line represents weekly deaths from all causes of unvaccinated people per 100,000 in the same age range.
Vaccinated English adults under 60 are dying at twice the rate of unvaccinated people the same age And have been for six months. This chart may seem unbelievable or impossible, but it’s correct, based on weekly data from the British government.
I have checked the underlying dataset myself and this graph is correct. Vaccinated people under 60 are twice as likely to die as unvaccinated people. And overall deaths in Britain are running well above normal.
I don’t know how to explain this other than vaccine-caused mortality.
The basic data is available here, download the Excel file and see table 4.
"Complete vaccination increases the likelihood of death" is the conclusion of a German comparison of vaccination rates and death rates in 16 countries reported by the Steve Kirsch [statistician Newsletter], November 20, 2021. The correlation was documented in all 16 countries.
The authors write (translated into English): “The correlation is + .31, is amazingly high and especially in an unexpected direction. Actually, it should be negative, so that one could say: The higher the vaccination rate, the lower the excess mortality. However, the opposite is the case and this urgently needs to be clarified. Excess mortality can be observed in all 16 countries…”
Kirsch says this is consistent with his own analysis of covid statistics showing "The smallpox vaccine used to be the most dangerous vaccine in human history. The COVID vaccines are over 800 times more deadly." He has a $1,000,000 offer for anyone who will debate. (See following article.)
From the article, using a Google translate plugin:
"Federal states [nations] with a high vaccination rate have the highest excess mortality. The higher the vaccination rate, the higher the excess mortality. November 19, 2021.
"The physicist Dr. Ute Bergner, who formerly belonged to the FDP parliamentary group in the Thuringian state parliament, commissioned an analysis which she presented November 17 in her speech before the Thuringian state parliament.
"She commissioned two statisticians, Prof. Dr. Rolf Steyer and Dr. Gregor Kappler, to investigate whether there was a connection between the vaccination rate and excess mortality in the 16 federal states [nations].
"The results are alarming. The summary of the analysis states:
"Excess mortality can be found in all 16 countries. The number of Covid deaths reported by the RKI in the period under review consistently only represents a relatively small part of the excess mortality and above all cannot explain the critical issue:
"The higher the vaccination rate, the higher the excess mortality.
"The most direct explanation is: Complete vaccination increases the likelihood of death."
$1,000,000 offer for anyone who will debate
Dr. Steven Kirsch is so confident in his analyses, he’s offered a $1 million academic grant to anyone who can show his analysis is flawed by a factor of four or more. So far, no one has stepped up to claim the prize. He’s even offered $1 million to any official willing to simply have a public debate with him about the data, and none has accepted the challenge.
(This summary of Kirsch's challenge consists of quotes from the summary by Dr. Joseph Mercola posted 10/9/2021; Mercola leaves his posts up only 48 hours. Mercola's title: "More Than 200,000 Have Already Died From the COVID Jab in the US". Lower down, Mercola summarizes the evidence that "An estimated 300,000 Americans suffered permanent disability from the COVID shots, and anywhere from 2 million to 5 million may have suffered adverse reactions".)
Kirsch addresses "Five False Narratives" about jab safety:
1. The shots are safe and effective
2. No one has died from the COVID shot
3. You cannot use VAERS [the Vaccine Adverse Effects Registry] to determine causality.
4. The SARS-CoV-2 spike protein [which the vaccine genetically orders healthy cells to create] is harmless
5. Only a few adverse events are associated with the shots and they’re all “mild”.
Here are his "Five False Narratives" about treatment solutions:
1. Vaccines are the only way to end the pandemic
2. Vaccine mandates are therefore needed
3. Masks work
4. Early treatments do not work
5. Ivermectin is dangerous
Kirsch and his entire family took the COVID shot early on, so he’s not coming from an “anti-vax” position.
Kirsch cites information from Dr. Peter Schirmacher, chief pathologist at the University of Heidelberg, who is recognized as one of the top 100 pathologists in the world. Schirmacher did autopsies on 40 patients who died within two weeks of their COVID jab, and found 30% to 40% of them were conclusively due to the shot, as there was no other underlying pathology that could have caused the deaths. Now, he did not rule out that 100% of the deaths could have been caused by the shots. He just could not conclusively prove it.
There’s also Pfizer’s six-month study, which included 44,000 people. During the blinded period of the study, the deaths were just about even — 15 deaths in the vaccine group and 14 in the control group. So, one life was saved by the shot.
But then, after the study was unblinded and controls were offered the vaccine, another three in the original vaccine group died along with two original placebo recipients who opted to get the shot. None of these deaths was considered related to the Pfizer “vaccine,” yet no one knows what they actually died from.
So, the final tally ended up being 20 deaths in the vaccine group and 14 deaths in the control group. What this tells us is the Pfizer shot offers no all-cause mortality benefit. The shot saved one life, and killed six, which gives us a net-negative mortality rate. The reality is that five times more people are killed by the shot than are saved by it.
How come nearly 15,000 reported deaths haven’t set off emergency alarms and in-depth investigations? Historically, 50 deaths have been the cutoff point at which a vaccine is pulled.
68 Countries, 2947 counties: The more vaccinations, the more Covid
The European Journal of Epidemiology published its study 0/30/2021. From its "Findings":
"There appears to be no discernable [reduction of Covid from increasing the percentage of people fully vaccinated.] In fact, the trend line suggests...that countries with higher percentage of population fully vaccinated have higher COVID-19 cases per 1 million people. Notably, Israel with over 60% of their population fully vaccinated had the highest COVID-19 cases per 1 million people in the last 7 days. [If we compare] Iceland and Portugal....Both countries have over 75% of their population fully vaccinated and have more COVID-19 cases per 1 million people than countries such as Vietnam and South Africa that have around 10% of their population fully vaccinated.
"Across the US counties too,...There also appears to be no significant signaling of COVID-19 cases decreasing with higher percentages of population fully vaccinated.
"Of the top 5 counties that have the highest percentage of population fully vaccinated (99.9–84.3%), the US Centers for Disease Control and Prevention (CDC) identifies 4 of them as “High” Transmission counties....Conversely, of the 57 counties that have been classified as “low” transmission counties by the CDC, 26.3% (15) have percentage of population fully vaccinated below 20%."
"All Cause Mortality" up, implicating vaccines
Deaths in the U.S. from all causes are 16% higher than in 2018, the highest pre-covid year. This is a pretty indirect way to measure how many died of covid, or of vaccines, but it raises the question, why didn't the death rate go down since vaccines were rolled out last December? Weren't the vaccines supposed to lower the death rate? Are vaccines killing anyone?
A Statistician's Evidence that Death Rates Increase as Vaccinations Increase
Matthew Crawford, statistician and educator, explains that for every million doses of covid vaccines delivered, 200-500 people die.
there are 200-500 deaths per million doses of covid vaccines, according to deaths reported as covid deaths. "This would suggest, based on 4 billion doses already administered throughout the world, that 800,000 to 2,000,000 of the COVID-19 deaths recorded are actually vaccine-induced deaths."
This is difficult to confirm because U.S. officials "behave as if examination of the bodies is completely unnecessary". But based on examination of bodies in Norway, their death rate per million doses comes out to 575. Then there is "Cambodia, which has 1442 COVID deaths as of earlier this week---every one since the start of the vaccination program...COVID deaths per day have been 11.61 times as high for these nations [where statistics are reasonably reliable, with a quarter of the world's population] as prior to the outset of vaccination! 5 of these 13 nations have seen over 90% of their COVID-19 fatalities since the outset of vaccination programs. Only Uzbekistan has seen less than 48.5% of its COVID-19 deaths since the start of its vaccination program."
The number of new COVID cases (i.e., positive tests) after the start of the COVID jab campaign is 3.8 times higher than it was before the rollout of the shots, and the daily COVID death rate is 3.82 times higher.
"Meanwhile, health authorities still seem to have no issue with the lack of risk report or risk-benefit analysis performed by any of the vaccine manufacturers or anyone else. This strikes me as one of the worst signs in my lifetime that corporations have taken over government on an essentially complete level."
Grossly Exaggerated Covid Deaths
Vaccine mandates are justified by a frightening number of unvaccinated people dying of covid. Apparently an accurate report of how many are dying is not frightening enough. Several county coroners in Colorado, in small counties where a single coroner processes every death and therefore knows if government stats are reporting for their county correctly, have noticed a number of stats reporting covid deaths where covid had nothing to do with death and was never mentioned on death certificates. Some were not even dead. They went together to their governor to ask him to fix the problem, but the governor said he doesn't want to handle stats differently than all the other states. See story at Full Measure News, 9/18/2021.
Grossly Underreported Vaccine Deaths
Non-severe "Breakthrough Cases" Not Tracked
Pro Publica, 8/20/2021. "On May 1 of this year — as the new variant found a foothold in the U.S. — the Centers for Disease Control and Prevention mostly stopped tracking COVID-19 in vaccinated people, also known as breakthrough cases, unless the illness was severe enough to cause hospitalization or death."
“I was shocked,” said Dr. Leana Wen, a physician and visiting professor of health policy and management at George Washington University. “I have yet to hear a coherent explanation of why they stopped tracking this information.”
When the CDC halted its tracking of all but the most severe cases, local and state health departments were left to make up their own rules.
An example of the kinds of cases no longer counted as side effects of vaccines: "Meggan Ingram was fully vaccinated when she tested positive for COVID-19 early this month. The 37-year-old’s fever had spiked to 103 and her breath was coming in ragged bursts when an ambulance rushed her to an emergency room in Pasco, Washington, on Aug. 10. For three hours she was given oxygen and intravenous steroids, but she was ultimately sent home without being admitted."
There is now little consistency from state to state or even county to county on what information is gathered about breakthrough cases, how often it is publicly shared, or if it is shared at all.
The above report does not document underreported deaths, but underreported near fatalities that don't quite result in death or a full day in the hospital. Below, is a Project Veritas video link. It is posted on Youtube, so who knows how long before Youtube takes it down?
Why Few Vaccine-caused Deaths are Reported
But doctors are secretly filmed saying the reason vaccine deaths are hardly ever reported is that it takes half an hour to fill out the form, besides other pressure. A medical person is shown saying she was emphatically told she would lose her job if she makes Ivermectin available. The "whistleblower" says she is willing to give up her job for the truth after a friend, a nurse who for religious reasons held off getting the vaccine as long as she could, was finally forced to take it, and it killed her.
The Project Veritas video is 13 minutes.
Partial quotes from the video were reported by Dr. Joseph Mercola, 10/5/2021, but Mercola only posts his articles for 48 hours in an attempt I don't understand to ward off serious threats. He reports:
"In a stunning Project Veritas report, Jodi O’Malley, a nurse working for the U.S. Department of Health and Human Services, reveals health officials are ignoring and covering up COVID-19 vaccine injuries.
O’Malley says she’s seen “dozens of people come in with adverse reactions,” including myocarditis, congestive heart failure and deaths, yet the reactions are not being reported. This, despite the fact that both the U.S. Food and Drug Administration and the U.S. Centers for Disease Control and Prevention require any suspected injury from an emergency use vaccine to be reported.
“If everyone is supposed to gather this data and report it, but no one is reporting it, how will anyone know the vaccine is truly safe? They don’t,” O’Malley says.
Another whistleblower, Deborah Conrad, was recently featured in a Highwire exclusive. Conrad, a physician’s assistant, reveals there’s a complete disregard for the requirement to report COVID jab injuries at her hospital too.
Mercola also gave a link to a public hearing hosted by Senator Johnson where people gave horrendous stories of what the vaccine did to them and their children, for over an hour.
September 10, 2021, WXYZ-TV Channel 7 posted a request on Facebook, asking people who had lost an unvaccinated loved one to COVID-19 to contact them for a story. The post has received more than 241,000 comments and most are about someone who was injured or died from the COVID shot, or who got severe COVID-19 despite being fully vaccinated. You can browse through the comments here.
Hospital Administration Blocked VAERS Reporting
"over 90% of a Hospital’s Admissions were Vaccinated for Covid-19 and No One Was Reporting This to VAERS", reports Project Veritas 10/17/2021. (VAERS: Vaccine Adverse Events Reporting System.)
"A concerned Physician Assistant, Deborah Conrad, convinced her hospital to carefully track the Covid-19 vaccination status of every patient admitted to her hospital. ...[in] a community in which less than 50% of the individuals were vaccinated for Covid-19...approximately 90% of the individuals admitted to her hospital were documented to have received this vaccine."
Through a legal firm emails were sent to heads of five relevant federal agencies. No response, except that after that, "when doctors came to Ms. Conrad for assistance with filing VAERS report for their patients, the hospital prohibited her from filing these reports."
The lawyers' letter to the hospital says:
"... For the past few months, on her own time, Ms. Conrad has been assisting doctors and other medical professionals at the hospital to report such events to VAERS. Instead of praising her efforts, numerous individuals at the Hospital, including Tara Gellasch and Peter Janes, ordered Ms. Conrad to stop reporting to VAERS altogether unless the patient she was reporting on was her patient. Since being given this order, Ms. Conrad has knowledge of dozens patients whose conditions necessitate a VAERS report and whose treating nurses and doctors have not filed a VAERS report. As you are likely aware, healthcare workers are mandated by federal law to report certain medical events arising after vaccination to VAERS. Pursuant to 42 U.S.C. § 300aa-25:
Each health care provider and vaccine manufacturer shall report to the Secretary— (A) the occurrence of any event set forth in the Vaccine Injury Table, including the events set forth in section 300aa–14(b) of this title which occur within 7 days of the administration of any vaccine set forth in the Table or within such longer period as is specified in the Table or section, (B) the occurrence of any contraindicating reaction to a vaccine which is specified in the manufacturer’s package insert, and (C) such other matters as the Secretary may by regulation require...."
The two letters are worth reading in full. The first has contact emails for the 5 federal agency directors. The second has legal definitions of "adverse events" and more details about interaction with hospital administration. An administrator called her an "anti-vaxxer" for trying to fulfill the hospital's legal obligation to report "adverse events" to VAERS.
Grossly Exaggerating the Death Toll
Before Covid, during the 2017-2018 flu season, the CDC estimated that about 177,000 Americans died of flu and pneumonia. It was not a national panic. No lockdowns. No mask or vaccine mandates. Although people were advised to cough into their elbows, which was very weird.
On Sept. 22, 2021, CNN triumphantly announced that 200,000 people had died from COVID-19 in the United States. But on that same day, the CDC reported a total 187,072 deaths attributed in some way to COVID-19, but that number includes flu and pneumonia! It’s not clear how many deaths were caused by the coronavirus alone, how many died with but not simply from infection by the coronavirus, and how many died of other things but just happened to be infected around the time of death.
Less than a month earlier, the CDC had estimated that the virus directly caused only 6 percent, or now just over 11,000 of the 187,000 attributed deaths. The remaining 94 percent died with and not exclusively of the coronavirus. These people also were on average elderly and had 2.6 other serious health problems. In other words, most deaths attributed to the coronavirus were already very sick people.
Numbers of "cases" are irrationally inflated by counting people who aren't even sick, but who test "positive" on a test notorious for a high rate of "false positives". According to The COVID Tracking Project, in September we averaged over 800,000 tests every single day. Even if the "false positive" rate is as low as 1%, which some claim, every million tests will generate headlines about "10,000 new cases".
This information is summarized from Here’s how the media is deliberately misreporting COVID-19’s death toll in America
How to Make 13% effectiveness look like 90% effectiveness
The New England Journal of Medicine September 8, 2021 (DOI: 10.1056/NEJMoa2110362) said the vaccines are almost 90% effective. Effectiveness among those 85 and older, those with chronic medical conditions, as well as Black and Hispanic adults, ranged from 81% to 95%.
Effective at what? They estimated "vaccine effectiveness by comparing the odds of a positive test for SARS-CoV-2 infection among vaccinated patients with those among unvaccinated patients." That is, the goal of the study was to figure the odds of a positive covid test among vaccinated people compared with unvaccinated folks. The effectiveness was 89% [for avoiding] hospitalization, 90% [for avoiding] ICU admission, and 91% [for avoiding an] emergency department or urgent care clinic visit."
But those who had been vaccinated less than 14 days before their medical emergencies are excluded from that claim. "1872 hospitalizations and 1350 emergency department or urgent care clinic visits were excluded..." That excludes all whose hospitalizations were caused by the vaccine; a large number of serious effects from the vaccine within the first few days are widely reported.
The excuse for not counting them: "protective immunity is unlikely immediately after vaccination." With the most blissful disinterest in how many were hospitalized in reaction to the vaccines, the study says "the effectiveness of [vaccination] ...14 days after the first dose, but without the second dose was 54%...and the effectiveness of [vaccination] ...1 to 13 days after the second dose was 73%."
Second, the percentage of patients who were clinically tested for SARS-CoV-2 by molecular assay differed across network partners and clinical settings, and vaccine-effectiveness estimates can be biased if clinicians make testing decisions based on vaccination status.38,39
Sounds great! But look what they did to sound that great.
The study was extensive enough. Out of 103,199 hospitalizations over six months, over 41,000 cases were studied. Excluded were those under 50, and those whose jabs were within 14 days. Leaving out those recently jabbed skews the results, because the first 14 days are when
https://mobile.twitter.com/USMortality/status/1443431541737078789 Twitter Ben M September 30, 2021
the effectiveness of the mRNA shots against lab-confirmed SARS-CoV-2 infection, 14 or more days after injection, was 89%, on average.
The effectiveness of the Janssen “vaccine” against lab-confirmed infection leading to hospitalization was 68%, and 73% against infection requiring emergency care.
How the Spike Protein Hurts the Heart Posted September 28, 2021 by Joseph Mercola but removed 2 days later. Excerpts:
As of September 3, 2021, the vaccine adverse event reporting system (VAERS) had received 675,591 reports of adverse events following vaccination. Of these, there were 14,506 deaths, 6,422 heart attacks and 5,371 cases of pericarditis or myocarditis.
It is important to note that the VAERS has tracked adverse events since 1990. In 2019, there were 605 reports of deaths from all vaccines given. In 2021, there were 14,594 deaths reported in nine months.
Although these numbers are significant, a 2010 Harvard study commissioned by the Department of Health and Human Services revealed data demonstrating the VAERS likely only represents approximately 1% of those who are injured....
Dr. J. Patrick Whelan is a pediatric rheumatologist who warned the FDA of the microvascular injury the vaccine may cause to the kidneys, brain, liver and heart before it was released to the public. Whelan specializes in treating children with multisystem inflammatory syndrome (MIS-C), which is associated with coronavirus infections.
In March 2021, a research study was published in the American Heart Association’s journal Circulation. However, it is important to note that the study was preprinted online in December 2020, before the first vaccine was administered in the U.S.
This is important, since the study demonstrated that the spike protein associated with SARS-CoV-2 damages endothelial function. In other words, before the emergency use authorization jab that injected instructions to create the spike protein was first administered, the CDC, FDA and NIAID were well aware the spike protein was likely causing damage to the endothelial cells lining the circulatory system....
Then, a second paper was published online March 8, 2021, investigated the potential that the spike protein is an inflammagen, or an irritant that can trigger inflammation at the cellular level. The researchers sought to determine if the spike protein was the underlying cause of the hypercoagulation found with a COVID-19 infection.
Mass spectrometry showed the spike protein damaged fibrinogen, prothrombin and complement, all compounds used in coagulation. They suggested that the presence of the protein was contributing to hypercoagulation and may result in large microclots that have been observed in plasma samples from patients infected with COVID-19....
A third study published April 27, 2021, again demonstrated in an animal model that exposure to the spike protein alone was enough to induce severe lung damage. And yet, there was no move by governmental agencies to slow the distribution of this genetic experiment....
The researchers evaluated 789 professional athletes who had COVID-19 and found no adverse cardiac events in those who underwent cardiac screening. In this group of healthy individuals, it appeared very rare for there to be systemic involvement of the spike protein.
However, in the VAERS reports September 3, 2021, there were a total of 11,793 individuals who suffered heart attack, myocarditis or pericarditis in the nine months that the vaccine had been administered. The effect of COVID-19 on the heart is well documented....
Worldwide Censorship: Dr. Malone explains how it's done
Dr. Malone, inventor of the mRNA process used by covid vaccines has submitted several research papers that were published, after being passed by peer review, including top reviewers at the FDA. Yes, they were submitted, passed, published - and then pulled without explanation.
Vaccine manufacturers bribe peer reviewed publications by buying multitudes of "reprints" of articles favoring them. This somehow escapes the responsibility of publications to disclose conflicts of interest. It is a very significant part of the income of publications.
The FDA gives Pfizer expedited review, while throwing up consecutive obstacles, delaying for months research investigating the "politically correct" treatment protocols.
Pfizer funds politicians down to the local level. Media sells a majority of their ad space to drug companies. But the vaccine companies, as well as media, are owned by the Vangaard and Black Rock investment companies.
I was at Heritage. They said Black Rock is close to the Chinese Communist Party.
The conspiracy to kill early treatment by government is well documented.
Crowd Formation Psychosis, the analysis of how Hitler arose according to psychiatrists, describes what is happening in the world today. Governments know they can now completely ignore informed consent. Government has eliminated research ethics.
Even aspirin resists the blood coagulation of covid and of vaccines.
Solution: think global, act local. Find physicians willing to administer drugs. Relief shows on the faces shown the facts. They see this is survivable. Hospitals are forcing doctors to resign, which drives doctors to set up competing clinics.
Trial Site is the platform for this interview. It makes information available not available through peer review any more. In Florida, employers which had fired people for not vaccinating, are rehiring. There are moves to outlaw third party attacks on doctors' licenses, by non-medical complainers.
Dr. Malone response to Twitter suspension
Twitter has no problem with self esteem.
Twitter's failure to have a single person on its staff with a medical license - at least anyone whose name Twitter has enough confidence in to make public - has not made Twitter ashamed to suspend the world's leading expert on mRNA vaccines: Dr. Malone, the guy who invented the mRNA sequence.
If the inventor of mRNA isn't qualified to discuss mRNA vaccines, is Twitter??!!!
Malone responded by questioning if he can’t discuss “inconvenient” scientific facts about the Covid vaccines, then who can?
"If there's no merit to my voice being in the conversation, whether it's true or not, whether I'm factually correct or not, let's park that just for a minute. Whether or not I'm right in everything I say, and I freely admit, no one's perfect. I'm not perfect. It's one of my core points, is people should think for themselves," said Malone.
"If it's not okay for me to be part of the conversation, even though I'm pointing out scientific facts that may be inconvenient, then who can be allowed?" he questioned.
"And whether you're in the camp that says I'm a liar, and I didn't invent this technology, despite the patents, and there's a whole cohort of that. But I played a major role in the creation of this tech and virtually all other voices that have that background, have conflicts of interest, financial conflicts of interest. I think I'm the only one that doesn't, I'm not getting any money out of this."
Dr. Mengale was Germany's top doctor under Hitler. His medical competence, and dedication to the health of his patients, is suspiciously similar to whoever Twitter's pretend doctors are promoting, but at least Mengale had a genuine medical license.
Pfizer data saying one person was saved from covid, says 4 died of heart attacks
Speech of Senator Robert Kennedy Jr. (son of assassinated Attorney General Robert Kennedy, nephew of President John F. Kennedy) to Green Pass protesters in Italy:
No government in the history of mankind has ever relinquished power voluntarily. The power that they have taken away from us over the past 20 months they will never give back. They have taken away our freedom of speech, they have closed the churches, they have taken away jury trials against companies, no matter how negligent they, no matter how reckless they are, no matter how grievous your injury, you cannot sue that company.
They have taken away our property rights in the United States. They closed a million businesses for a year with no just compensation and no due process. They have taken away our right to be free of warrantless searches and seizures and surveillance by the government. In the United States all of those rights are enumerated in our Bill of Rights of the United States Constitution. And among the most important of those rights, after the right to free expression, which is gone, is the right to be able to participate in rule-making.
So, when the government wants to pass a law, it has to publish the law, propose the law, it has to explain the scientific basis for that law, it has to do a cost-benefit analysis of that law and explain it to the public, and then we have comments, that all the public can participate in, and then we have a hearing where people oppose the law, like myself, and bring in our own scientists and experts and scientific studies and it’s all transparent. All of those safeguards have been obliterated. Today, the law is what one man says it is, the top doctor in the United Sates, Anthony Fauci.
In one month, in March of 2020, Tony Fauci told the world masks don’t work, they’re scientifically worthless, two months later he ordered every American to put on a mask. He didn’t give us any scientific studies that made him change his mind, he simply told us, that’s the new law, do what you’re told.
All of these rights that the Founders of our country died for, sacrificed their properties, their livelihoods, to give us the Bill of Rights, and all of these rights over 20 months have been obliterated, taken from the American people — but not just the American people. This is a global coup d’etat against liberal democracies across the planet.
And all of these rights that were taken away from us, these governments said it was only temporary. They said it would only be two weeks. In truth, you can all see what is happening: They will never give them back unless we make them.
And the Green Pass is their coup d’etat. The Green Pass is how they consolidate their power over your lives. The Green Pass is not a public health measure. It is a tool for totalitarian control of your transportation, your bank account, your movement, every aspect of your life.
And this is not a new idea. This is the same idea they used in Germany in 1937. They issued a pass for people they wanted to control. And when the South African apartheid government wanted to control the black population of South Africa, what was the most important thing they did? They issued a green pass.
I want you to ask all of people and journalists and press who are here today. If the Green Pass is about public health, why is it not issued by the health ministry? It’s being issued by the financial ministry. Do they think that we are stupid?
Because this is a way to control your money, Once you have that Green Pass and they have the digital currency, if somebody tells you, Do not leave Milan, and you go on a trip to Bologna, your money won’t work in Bologna. If the government tells you not to buy pizza, they can make it so that your money won’t buy pizza at a pizza store. They can control every aspect of your life.
They tell you that we need a Green Pass to make sure everybody gets vaccinated. But they admit it: the vaccine does not prevent transmission, the vaccine does not prevent you from getting the disease, the vaccine doesn’t stop the pandemic. So why do we need to get vaccinated if the vaccine doesn’t stop transmission?
I’m gonna tell you for two minutes — I’m going to talk about the vaccines. People say I’m against vaccines. I’m not against vaccines. I’m only against bad vaccines.
I’m not going to tell you what Robert Kennedy thinks. I’m going to tell you what Pfizer told the United States FDA.
Pfizer is the company that has an approved vaccine in the United States. And Pfizer was supposed to have a three-year-study, but they cut it to six months. And then they gave vaccinations to all of the controls. Why did they do that? Why did they end the study in six months? Because they learned that the antibodies disappear in six months and the vaccine no longer provides protection. So they had to end it in six months. They could not do what they planned (three years). They took all of their records for that six months and they gave them to FDA. The most important table is the table that tells you All Cause Mortality. How many people died in the vaccine group, how many died in the placebo group during that six month period. That table is called “s4.” You can all look it up.
Here’s what the numbers say. There were 22 thousand in the vaccine group. Over six months, one died from covid. In the placebo group, the control group, there were 22 thousand people, two died from covid in six months. That allowed Pfizer to tell the American public that the vaccine is 100 percent effective because two is 100 per cent of one.
Most Americans and most Italians when they hear that the vaccine is 100 percent effective, what they think is that if they take the vaccine, I have 100 percent of not dying from covid. That’s not what it means. What it means is they have give 22 thousand vaccines to protect one person from dying of covid. That means they better make sure that the vaccine itself does not kill one person even, because if it kills one person then you cancel out the entire benefit.
Here’s the important thing. In the vaccine group, 20 people died over six months from all causes — 20 people of the 22 thousand. In the control group, only 14 people died of 22 thousand. That means that if you take the vaccine you are 48 percent more likely to die over the next six months than if you don’t.
These are Pfizer’s numbers, not mine, Here’s how the people died. In the control group, one person died of a heart attack over the six months. In the vaccine group, five people died of heart attacks over the six months. That means if you get the vaccine you have a 500 percent risk of a fatal heart attack within six months. It also means that for every one person who is saved from dying of covid, the vaccine is killing four people from heart attacks.
This is not a good public health policy, Public health is supposed to save lives. But this is about control and controlling our society and controlling our children. And the only reason that people don’t understand what I just said and that people still support the vaccine is one reason: the manipulation of fear.
This is simple mathematics. Anybody can look it up. If you look it up you will be more scared of that vaccine than you are of covid. But the government and the pharmaceutical companies have a method for turning off people’s brains so that they can no longer do simple mathematics. That device is fear. Fear stops us from exercising critical thinking. It allows us to believe that if we just do what we’re told then that that is the only way to save our lives. It’s called the Stockholm Syndrome. And the captors, they lock down a whole country for a year, and people become grateful to their captors and think the only way we can leave here alive is if we have absolute obedience.
I’m going to make one more point and that’s this. How many people here have heard of Event 201?
If you haven’t heard of it, you should go look at it on Youtube. Event 201 was a simulation of a corona virus pandemic that occurred in New York City in October 2019. We now know that covid was circulating in Wuhan on September 12, 2019, so a month later there is a simulated corona virus pandemic in New York.
The people who came to that were the big social media companies, the media companies, Johnson & Johnson, the biggest vaccine company, and it was hosted by three people: 1) Bill Gates, 2) George Fu Gao who’s the head of the Chinese CDC, and 3) Avril Haines, the deputy director of the CIA.
Avril Haines is today the top number one spy in the United States, She is the head of Joe Biden’s National Security Agency, so she went from Event 201 to becoming the top spy in our country.
[There are a couple of seconds of weird transmission interference here.]
Who knew that the CIA is a public health agency? It came as a surprise to me.
Because the CIA does not do public health. The CIA does coup d’etats. Between 1947 and the year 2000, the CIA was engaged in 73 coup d’etats, most of them against democracies, one-third of the countries in the world. If you look at Event 201, there was no discussion of public health. Nobody was talking about how do we get Vitamin D to all the people? How do we get people to lose weight? How do we make sure they eat good food? How do we repurpose medicines to treat people? How do we quarantine the suck? How do we preserve Constitutional rights? Not a word was said about public health.
Instead, what they were talking about is how do we use the pandemic as a pretext to clamp down totalitarian controls and to deconstruct democracy. They spent one-quarter of the day talking about how to make sure nobody’s allowed to spread the rumor that the coronavirus pandemic is laboratory- generated. This is October 2019! And they talk about how to lock down the population, how to force them to take experimental vaccines, how to make sure that black people don’t start resisting. Because in our country, blacks are very suspicious of the medical establishment, and they were deeply concerned about that resistance.
When I researched my book, what I learned was that this event, Event 201, was not a one-time occurrence. We found 20 separate pandemic simulations beginning in 2000. One thing they had in common — most of them Bill Gates was involved in, Tony Fauci was involved in — but every one of them the CIA was involved in. The CIA wrote the script, high-level CIA officials participated in every one of those pandemic simulations.
And they involved hundreds of thousands of people. They were conducted secretly. They used frontline workers, they were training police, and hospital systems and utilities in Europe, in Italy, in Germany, in Canada, in Australia, all at the same time, to do a response to a pandemic, but it was not a public health response. It was a response to use the pandemic for something else.
So they practiced again and again and again: How to use the pandemic as a pretext for imposing totalitarian controls and for obliterating liberal democracy across the planet.
One of the experiments that they used, they found, is called the Milgram experiment — it was a CIA experiment in 1967 — and what the CIA found is that if a powerful medical official orders people to do something wrong, something that violates their conscience, that violates their basic values, 67 percent of people will obey authority over their values. And 67 percent of the people will be hypnotized by fear into obeying a position of authority, a figure of authority. But thirty-three per cent of the people will not obey. And you are the 33 percent.
And our job is to go out from here today and reach out to our brothers and sisters, the people who are still hypnotized, and tell them that we are going to fight for their freedom until they are able to fight for it themselves. We need to reach out when we leave here today to all of our brothers and sisters, the 67 percent who are still hypnotized, and we have to tell them that you need to love your freedom more than you are scared of a germ.
This year we saw the destruction of the American Constitution. That Constitution was written by a group of people who understood that there are worse things than dying. And they put their lives on the front line, their property, their careers, their livelihoods, to fight for freedom, and to fight for those rights that we have lost in the previous 20 months.
And now it’s our job now, it is the job of everybody in this crowd, to go out and fight back, to resist, resist, resist, resist, and to reclaim our government, to reclaim our lives, to reclaim our liberty, for our children, for our country, and for all future generations.
And I can tell you this. I will stand side by side with you, and if I have to die for this, I’m going to die with my boots on.
Just Plain Ignoring Evidence: Fauci & Birx
From an interview with Dr. Scott Atlas, who served on President Trump's covid task force with Anthony Fauci and Karen Birx:
"What I saw when I was in the task force meetings were three doctors on the task force that controlled the medical policy really, which were Dr. Fauci, who was the most visible face of the policy to the country, but not in charge of the task force. Dr. Deborah Birx, who was in charge of the medical side of the task force, she was the official task force coordinator with capital letters. She had the role and personally wrote all of the written advice to every state. All of the governors received her advice as the federal policy guidelines. She flew to dozens of states, she personally visited all of these state’s public health officials doling out the federal guidance. And Dr. Redfield was the third doctor who was the head of the CDC.
"These people were bureaucrats, Drs. Fauci and Birx were 40-year bureaucrats. I was very different. I had more than a decade of health policy expertise practicing. I had 25-plus years of medical science clinical research and education. I brought in dozens of papers, the world’s literature.
"When I was asked a question in the task force meeting by Vice President Pence, for instance, I gave the data. … I was going through all the data, all the world’s publications, all the scientific papers. I was critiquing the papers. If I look at a scientific paper and the methods, the study was done incorrectly or poorly, the conclusion is not valid.
"This is what medical science people do, who are competent. I went through 12, 15, 20 papers when I was asked a question. And when I did that, for instance, on an occasion where I was us about the risk to children, I went through all the data very quickly, but I had all the papers in my briefcase. I was met with silence from Drs. Birx and Fauci with an accusation, I’m an outlier. And at the end of that discussion, which there was none refuting anything I said, there was no critique of anything I said by data, there was no scientific criticism.
"I was the only one who ever brought a publication to the table in the task force of the meetings I went to. The only comment at the end of that, when Dr. Redfield was asked about his comment was, well, let’s say the jury’s still out.
"I wrote this in my book, “A Plague Upon Our House,” [available at Amazon] because the American people need to know the level of incompetence, the lack of rigor, the lack of critical thinking. I was stunned at what I saw. We had bureaucrats in charge of the policy and that policy was the restrictions in lockdown. And it failed. It failed by the data to stop the spread of the infection. It failed to protect the elderly and stop them from dying. And it destroyed millions and millions of families, including the children who were sacrificed, and I’m talking about particularly low income families."
New Zealand Doctor Sam Bailey was knocked off her government-sponsored TV medical program for "misinformation". For stating the established facts about the RT-PCR tests for COVID-19. (The tests have a lot of "false positives" - that say you have covid when you don't.) The complaint against her was initiated by someone with no medical training.
So she started a firestorm of confusion and evidence-dodging with her question, after New Zealand health minister Andrew Little appropriated $42 million to fund 36 projects directed at reducing misinformation and “vaccine hesitancy”: “What is the definition of ‘COVID-19 misinformation’ for the purposes of the allotment of funding to address this problem?”
No authority would answer!
At New Zealand Doctors’ SOS, or NZDSOS, more than 38,000 health care professionals have signed a declaration reminding authorities of the Nuremburg code and that COVID-19 injections must be voluntary and not forcibly administered.
Facebook Censoring Jokes
From January 14, 2022 email from Babylon Bee:
Did you know Facebook is now banning jokes?
They started out banning people for spreading so-called "misinformation." As I'm sure you know, we got caught up in their fact-checking web many times. It was difficult to break free. But with your help, we made some noise and managed to maintain a presence on the platform. We even got Facebook to apologize and admit that there's a difference between fake news (which is intended to mislead) and satire (which isn't).
But they've decided it's not as simple as giving satire a blanket exception. There need to be rules. There need to be limits and restrictions on the kinds of jokes you're allowed to make.
We're not kidding.
In a recent announcement, Facebook said they're developing and rolling out "a new satire framework." This framework will be used to determined what counts as "true satire" and what doesn't. For example, true satire, as they put it, "does not 'punch down' . . . Indeed, humor can be an effective mode of communicating hateful ideas."
In other words, Facebook is coming after comedy they don't like. They want to ban jokes they consider hateful.
Mere days after the Big Tech giant made this announcement, a liberal media outlet published a piece accusing The Babylon Bee of having a "nasty tendency to punch down" because we push back on the madness of transgender ideology and make silly jokes about how women can't throw grenades as well as men (they really can't, though). This was no coincidence. The groundwork is being laid. It's only a matter of time before The Babylon Bee is penalized for violating Facebook's new policy against hateful comedy.
But let's get one thing straight. We are not "punching down." We're punching back. Conservatives have been on the ropes in the culture war for a long time. We're in a defensive posture, fighting back against the top-down tyranny of the Left's progressive agenda. And that agenda is driven by all the nation's most powerful people, corporations, and institutions. If that's not punching up, I don't know what is.
More importantly, Facebook's new prohibition of "punching down" is speech suppression — it's people in positions of power protecting their interests by telling you what you can and cannot say. Comedians who self-censor in deference to that power are themselves a joke. You certainly won't find us doing it.
We're going to keep making jokes on the internet. And we're going to keep punching back—not down—at the Left's progressive agenda and their endless efforts to silence us.
Will you team up with us in that effort by becoming a subscriber today?
Deliberately Manipulating Statistics
Relative (95%) v. Absolute (0.84%) Risk Reduction
Before getting into actual vaccination figures, here is an illustration of Absolute and Relative Risk Reduction with numbers easier to visualize.
Suppose a researcher followed one million volunteers, half jabbed and half unjabbed, for one hour, and found that one jabbed volunteer and two unjabbed volunteers got sick during that hour. So the researcher told reporters, "put off the jab and you face a whopping 0.000004% chance, 2 in 500,000, of catching covid. But get the jab like a good little boy, and you slash your danger to a mere 0.000002% chance, 1 in 500,000, of catching covid. To put this in scientific terms, the difference between 0.000004% and 0.000002% is 0.000002%, which is how much better your odds are if you get jabbed. We call this the ARR, Absolute Risk Reduction."
The reporter says, "Not much difference, huh?" and starts to walk away.
The researcher shouts, "No wait! I just told you the facts. Now let me give you something you can quote: 'people who don't get jabbed are twice as likely to catch covid.'"
The puzzled reporter says "But you just said..."
The researcher explains, "Two people in the unjabbed group got sick, but only one in the jabbed group. Not getting jabbed doubles your risk! See, scientists call this the RRR, the Relative Risk Reduction, where we just compare the numbers from the jabbed and the unjabbed groups."
See? Both figures are true. The unjabbed are twice as likely to get sick, and jabbing increases your protection by 0.000002%.
WHICH FIGURE MOST HONESTLY MEASURES THE PROTECTION OFFERED BY JABS?
WHICH FIGURE MORE LIKELY PERSUADE THE PUBLIC TO GET JABBED?
WHICH FIGURE IS BEING REPORTED BY CDC, GOVERNMENT, AND MEDIA?
- - - -
In vaccination statistics, "absolute" protection compares your chance of being infected with the jab, with your chance of being infected without the jab. Your chance is calculated as a percentage of the jabbed population that gets infected compared with the percentage of the unjabbed population that gets infected, during a selected period of time. The difference between the two percentages is how much difference the jab makes.
Now let's look at some actual vaccination stats.
Pfizer’s COVID shot was said to be 95% effective against the infection, but this is the relative risk reduction, not the absolute reduction. The absolute risk reduction for Pfizer’s shot was a meager 0.84%.
An incredibly low number of people were infected in the first place because of the shortness of the trial. Only 8 out of 18,198 vaccine recipients developed COVID symptoms (0.04%), and 162 of the 18,325 in the placebo group (0.88%). Had the trial lasted longer than 6 months there would have been more interesting results but it was decided that with 95% protection "established", it would be cruel to deprive the "control" group of the real "protection", so the study was terminated by "unblinding" the participants and offering the real shot to everyone.
Since the risk of COVID in the short trial was minuscule to begin with, even if the shot was able to reduce the "absolute" risk by 100%, (so that no one in the vaccinated group got sick) it would still be trivial in real-world terms.
Indeed, the six-month follow-up of Pfizer’s trial showed 15 deaths in the vaccine group and 14 deaths in the placebo group. Then, during the open label phase, after Pfizer decided to eliminate the placebo group by offering the actual shot to everyone who wanted it, another five deaths occurred in the vaccine group.
Two of those five had originally been in the placebo group, and had taken the shot in the open label phase. So, in the end, what we have are 20 deaths in the vaccine group, compared to 14 in the placebo group. We also have the suspicious fact that two of the placebo participants suddenly died after getting the real deal.
A peer-reviewed study explains why reporting only the RRR, not the ARR, is dishonest: “With the use of only RRRs, and omitting ARRs, reporting bias is introduced, which affects the interpretation of vaccine efficacy. When communicating about vaccine efficacy, especially for public health decisions such as choosing the type of vaccines to purchase and deploy, having a full picture of what the data actually show is important, and ensuring comparisons are based on the combined evidence that puts vaccine trial results in context and not just looking at one summary measure, is also important.”
The authors go on to stress that comparing the effectiveness of the COVID shots is further hampered by the fact that they use a variety of different study protocols, including different placebos. They even differ in their primary endpoint, i.e., what they consider a COVID case, and how and when diagnosis is made, and more.
“We are left with the unanswered question as to whether a vaccine with a given efficacy in the study population will have the same efficacy in another population with different levels of background risk of COVID-19,” the authors note.
One of the best real-world examples of this is Israel, where the relative risk reduction was 94% at the outset and an absolute risk reduction of 0.46%.
The information in this article which is accurate was taken from Dr. Joseph Mercola.
Pfizer won't release its vaccine data
A whistleblower, Brook Jackson, told the British Medical Journal (BMJ) that the Pfizer vaccine trial documentation was riddled with issues, including the falsification of data. He alerted the FDA and was fired within hours. Jackson had worked for Ventavia Research Group, which operated several of the Pfizer trial sites in the fall of 2020. The FDA did not inspect Ventavia’s trial sites, BMJ said.
A group of doctors and scientists, including Yale's Harvey Risch, called Public Health and Medical Professionals for Transparency (PHMPT), sued the FDA for public release of its vaccine trial data. They sued because the FDA would not release the information out of court. The FDA told the court it wants 55 years to release the information, at 500 pages per day, so it can have plenty of time to "redact" (black out) information it considers sensitive.
Aaron Siri, whose law firm represents the doctors/scientists, marvels that the FDA was able to process Pfizer's 329,000 pages of trial data in 108 days before it approved the vaccine for public distribution, but now it needs 20,000 days to decide which of it is safe for the public to see?
Real Flu Death Numbers Are A State Secret: Judge
PENNLIVE – The Pennsylvania Department of Health doesn’t have to give a news media group its “raw” data on deaths from influenza and pneumonia in the state for 2019 and 2020, a Commonwealth Court panel ruled Tuesday.
That decision, outlined in an opinion by Judge Renee Cohn Jubelirer, upholds a ruling the state Office of Open Records issued regarding the information request by Pittsburgh-based PublicSource.
Jubelirer agreed with the OOR that the data being sought is not yet in a form subject to public release under the state’s Right to Know Law.
PublicSource filed its request last year, at the height of the COVID-19 pandemic.
The judge said the health department had proved “there was no database from which it could simply pull the requested information” and that the raw data it supplies to the CDC contains personal information that is barred from release under the RTK Law. That law does not require a state agency to create a record that does not already exist.
“The OOR found… that the (Health) Department would have to correlate, verify, extrapolate, and code the information from death records - manually, in some cases -and present it in a different way than was available to Department employees before it could produce the information to” PublicSource, Jubelirer wrote.
Well, fine, but in all that time, the Health Department felt no responsibility to organize those covid stats for the benefit of the public, before anyone thought about court?
The judge ruled according the technical requirements of law: the Freedom of Information Act only requires bureaucrats to turn over information it already has, in the form it has it. The judge had no authority to rule on whether the government has a moral obligation to organize the data which its laws have required to be collected, in a way that can help the public understand whether its covid mandates have any basis in reality.