Population Attributable Fraction: A Primer

I. What is it?

The Population Attributable Fraction (PAF) answers a specific and important question: if we could eliminate a particular exposure from the entire population, what fraction of all cases of a particular disease would disappear?

It bridges the gap between two different ways of thinking about causation:

• Individual risk: In this case, “How much more likely is a vaccinated child to develop autism than an unvaccinated child?” (In prospective studies this is usually expressed as the risk ratio, RR, and in retrospective studies this is usually expressed as the odds ratio, OR.)

• Population burden: “How much of the total autism in the population is attributable to vaccination?” (This is the PAF.)

The formula is:

PAF = Pe(RR − 1) / [Pe(RR − 1) + 1]

Where:

• Pe = prevalence of exposure in the population (what fraction of the population is exposed)

• RR = relative risk, also known as the risk ratio, (or one can use the odds ratio as an approximation if the incidence in the population is low)

II. The history of PAF

1953: Smoking and lung cancer

The intellectual foundation was laid by Morton Levin, an epidemiologist at Roswell Park Memorial Institute in Buffalo, in a 1953 paper in Acta Unio Internationalis Contra Cancrum. Levin was trying to answer a practical public health question: we know smokers get lung cancer at much higher rates, but how much of the total lung cancer burden in the population could we eliminate by ending smoking? He called his measure the “attributable risk percent” and derived the initial formula.

1960s: Refinement and naming

Brian MacMahon and colleagues at Harvard helped formalize the framework during the 1960s. The terminology was inconsistent for decades — in the literature one sees “attributable risk,” “attributable fraction,” “etiologic fraction,” and “population attributable risk percent” — all referring to essentially the same concept. This terminological chaos may have slowed its adoption but this was clearly a valuable concept for epidemiology and public health.

1974: Miettinen’s contribution

Olli Miettinen, a Finnish-American epidemiologist, published a highly influential paper refining the formula and clarifying the distinction between the “attributable fraction in the exposed” (how much of the risk in exposed individuals is due to the exposure) versus the “population attributable fraction” (how much of the disease in the whole population is due to the exposure). Attributable fraction in the exposed is used in toxic tort litigation today (see Schachtman, 2015).

1980s onward: Public health adoption

PAF became standard in chronic disease epidemiology — tobacco, obesity, alcohol, occupational exposures, air pollution, etc. The CDC and WHO began routinely publishing PAF estimates for major risk factors. The massive Global Burden of Disease (GBD) project at the Institute for Health Metrics and Evaluation (IHME), which began in 1990 and is now updated annually, uses PAF as its central tool for ranking risk factors by their contribution to the disease burden worldwide. When you see headlines that say “alcohol causes X% of all cancer deaths” — that’s PAF.

III. Who uses PAF today?

Epidemiologists use it to prioritize which risk factors to target for public health intervention. If Risk Factor A has a high OR but low exposure prevalence, and Risk Factor B has a lower OR but near-universal exposure, PAF reveals that B may be the more important target.

Health economists use it to estimate the cost savings from eliminating a risk factor — e.g., how many hospitalizations and how much spending disappears if smoking rates drop by 20%.

Regulatory agencies use it to justify interventions — the EPA, for instance, uses PAF-type calculations when setting air quality standards to estimate how many deaths would be prevented.

IV. We can calculate the PAF for vaccines and autism

Three key studies help us create a range of plausible estimates of the PAF for vaccines and autism.

Mawson et al. (2017) in a study of homeschool children in Florida, Louisiana, Mississippi, and Oregon found that vaccinated children had 4.2 times higher odds of an autism diagnosis compared to unvaccinated children (OR = 4.2; CI: 1.2, 14.5).

Mawson & Jacob (2025) using Florida Medicaid data found that children with 11 or more visits to the doctor that included vaccinations were 4.4 times more likely to have been diagnosed with autism than those with no visit for vaccination (95% CI: 2.85, 6.84).

Hooker & Miller (2021) in a study of three medical practices in the U.S. found that vaccination increases the odds of developing autism 5.03-fold (95% CI 1.64, 15.5).

So we can now plug these into our formula:

PAF = Pe(RR − 1) / [Pe(RR − 1) + 1]

Where:

• Pe = prevalence of exposure in the population (what fraction of the population is exposed)

• RR = relative risk (I’m using odds ratio as an approximation which is justifiable in this case because autism prevalence is still considered somewhat “rare” — in the single digits)

We’ll use a Pe of 0.97 to reflect the fact that 97% of children are vaccinated.

And then we’ll calculate the PAF for each of the three key studies:

Mawson et al. 2017 — OR = 4.2, Pe = 0.97

PAF = 0.97(3.2) / (0.97 × 3.2 + 1) = 3.104 / (3.104 + 1) = 3.104 / 4.104 = 75.6%

Mawson & Jacob 2025 — OR = 4.4, Pe = 0.97

PAF = 0.97(3.4) / (0.97 × 3.4 + 1) = 3.298 / (3.298 + 1) = 3.298 / 4.298 = 76.7%

Hooker & Miller 2021 — OR = 5.03, Pe = 0.97

PAF = 0.97(4.03) / (0.97 × 4.03 + 1) = 3.909 / (3.909 + 1) = 3.909 / 4.909 = 79.6%

So that gives us our range — 75.6% to 79.6%. What this means is that, if the OR is real and causal, approximately 75.6% to 79.6% of current autism cases would not exist if no children were vaccinated. That is an extraordinarily large number.

V. Qualifications and limitations

1. A modest OR combined with near-universal exposure produces a huge PAF. As I showed in my last article, even a 4-5x individual OR becomes a massive epidemic in society when 97% of children are exposed, which is what is happening with vaccines and autism. One could choose a lower Pe (say, the percentage of children who are “fully up to date” on vaccines according to the CDC schedule) and that would bring down the PAF estimates somewhat.

2. A key limitation — PAF assumes the OR (or RR) is causal, not merely associational. If the association between vaccination and autism is confounded — for instance, if children who aren’t vaccinated are systematically different from children who are vaccinated in ways that independently affect autism risk — then the PAF calculation would overstate the true causal burden.

We can have that conversation, however, I don’t think it will change the results. The best available vaccinated vs. unvaccinated studies (Mawson et al. 2017, Hooker & Miller 2021, and Mawson & Jacob 2025) control for confounders and examine a wide range of study populations yet reach similar conclusions.

Furthermore, numerous independent scholars (e.g., Christopher Exley, Lucija Tomljenovic, Christopher Shaw, Romain Gherardi, Yehuda Shoenfeld, and Peter McCullough) have worked out plausible pathways by which vaccines can cause autism and several studies have been published that satisfy the Bradford Hill criteria for causation (see Tomljenovic & Shaw, 2011; Bjelogrlić, 2025; and Hooker et al. 2026).

3. The confidence intervals in Mawson et al. 2017 and Hooker & Miller 2021 are large. If one calculated a PAF using the lower bound of their 95% confidence intervals one would have a much lower PAF (roughly 16%). But the sample size and number of autism cases in Mawson & Jacob 2025 are large (resulting in a narrower confidence interval) and the results are consistent across the three studies which lends credibility to these estimates.

4. There is a way to convert OR to RR using a formula from Zhang and Yu (1998). It’s laborious and introduces other uncertainties in the process (namely whether the unexposed group is truly unexposed in previous studies). I ran the numbers anyway and this only reduces my upper-bound PAF estimate by two points, not enough to significantly change my conclusions.

VI. Putting this in context

Smoking and lung cancer. In the Norwegian Women and Cancer Study the PAF of lung cancer deaths attributed to smoking was 85.5% (Hansen et al. 2020). A 2011 meta-analysis found a PAF of lung cancer cases caused by smoking of 93.1% in men and 82.6% in women (Pesch et al. 2011). As smoking has declined in the U.S., the fraction of lung cancer deaths attributable to smoking decreased from 81.4% to 74.7% (Shiels et al. 2023).

Asbestos and mesothelioma. Drawing on the Global Burden of Disease 2019 dataset across 204 countries, Chen et al. (2024) found that 91.7% of mesothelioma deaths were attributable to occupational asbestos exposure. Only about 4% of lung cancer cases in U.S. men are attributable to asbestos exposure (McCormack et al. 2012).

Radon and lung cancer. Radon is a naturally occurring radioactive gas that seeps up from soil and rock into buildings. It is the second leading cause of lung cancer after smoking and the leading cause among non-smokers. Gaskin et al. (2018) estimated that residential radon causes approximately 16.5% of global lung cancer deaths (that was the median PAF across the 66 countries surveyed).

So the PAF for vaccines and autism cases is about the same as the PAF for smoking and lung cancer deaths, somewhat less than the PAF for asbestos and mesothelioma deaths, and significantly higher than the PAF for radon and lung cancer deaths.

Seen in this light, vaccines are one of the most harmful exposures in the world and pose a massive health burden on the population — particularly since the exposures are so widespread.

VII. Conclusion

Steve Kirsch was the first person to calculate a PAF for vaccines and autism but I was not aware of his work on this topic until after I calculated it myself. We both reached the same conclusions — Mr. Kirsch found a PAF of 75% to 80% and I found a PAF of 75.6% to 79.6%. This is an astonishingly high number and it shows that vaccines are one of the largest preventable harms to the health of the public.

If history is any guide, supporters of the status quo will launch waves of ad hominem attacks in response to these findings. But these results are difficult to dismiss. The best vaccinated vs. unvaccinated studies show that vaccines increase autism risk by a factor of 4.2 to 5.03. All I’ve done here is to plug the best available data into a widely used epidemiological equation to calculate the percentage of autism cases in the population caused by vaccines. You likely haven’t seen these calculations before because widespread regulatory and epistemic capture prevents mainstream scholars from asking questions they know might end their careers.

While the pharmaceutical industry tries to figure out how to protect its profits from the devastating and possibly criminal implications of these findings, for everyone else, this is extremely good news — we now know how to prevent up to 79.6% of autism cases — stop vaccinating.

Given these straightforward findings and the high quality of the underlying data I am calling on President Trump, Secretary Kennedy, NIH Director Bhattacharya, and FDA Commissioner Makary to immediately halt and permanently end the CDC Child and Adolescent Vaccine Schedule and the CDC Pregnancy Vaccine Recommendations.

I am also calling on all states to immediately halt and permanently end vaccine mandates for school or any form of employment.

And I am calling on all parents who currently use mainstream allopathic pediatricians to fire that provider and instead find a functional, integrative, or naturopathic medical doctor who doesn’t vaccinate in their practice.

Autism is just ONE harm caused by vaccines. The next task is to calculate the PAF for vaccines and a wide range of additional harms including ADHD, allergies, arthritis, asthma, autoimmune disorders, Alzheimer’s, childhood cancers, diabetes, ear infections, eczema, epilepsy/seizure disorders, Gulf War Syndrome, and hundreds of other chronic conditions.

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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In January, I presented some of my research on autism at a conference in Connecticut.

I pointed out that autism rates have increased 32,158% in the last 52 years (from 1 in 10,000 children with autism in 1970 to 1 in 31 in 2022). I noted that I’m the only person who cites this figure even though everyone has access to this information.

A hand went up from an esteemed participant in the conference followed by a question that went something like this:

I saw your Senate testimony and read your work and I think you’re probably right about vaccines increasing autism risk. But the studies you cite on vaccines show that they increase autism risk by anywhere from 300% to 400%. Okay fine. But how do you get from a 300% to 400% increased risk of autism from vaccines to a 32,158% increase in autism prevalence in the population? I’ve tried to do the math a lot of different ways and I cannot get from the individual increased risk to the much larger increase in population prevalence that you cite.

It’s the most thoughtful question I’ve ever gotten about my work because it takes the best existing data seriously while also interrogating patterns that still don’t make sense.

I said I didn’t know the answer but I would figure it out and get back to him. I’ve been working on this problem ever since. Now I think I have the answer and along the way I stumbled upon a few new insights into autism prevalence modeling that I don’t think anyone has ever mentioned before.

Let’s work through it piece by piece.

Editor’s note: Throughout this essay I use the words “risk” and “odds” interchangeably even though they are somewhat different concepts. Risk is the number of people who develop the condition divided by the total number of people in the group. Three children out of 100 develop autism → risk = 3/100 = 0.03. Odds is the number of people who develop the condition divided by the number who don’t. Three children out of 100 develop autism, 97 don’t → odds = 3/97 = 0.0309. As you can see, for conditions where the prevalence is low (single digits), the two measures are roughly equal and thus for my purposes here, can be used interchangeably. When you take the ratio of risks you get RR (generally used in prospective cohort studies); when you take the ratio of odds you get OR (used in retrospective case-control studies).

II. The prevalence data

Darold Treffert at Winnebago State Hospital in Wisconsin was one of the first people to measure autism in the general population. His study, “Epidemiology of Infantile Autism,” published in Archives of General Psychiatry in 1970, showed an autism rate of less than 1 in 10,000 children (less than 0.01%).

According to a study by the EPA, sometime around 1987 the autism rate in the United States began to skyrocket.

The most recent report from the Autism and Developmental Disabilities Monitoring Network (ADDM) showed that 1 in 31 eight-year-old children in the U.S. in 2022 were on the autism spectrum (Shaw et al. 2025). That’s a 32,158% increase in the last 52 years.

In many blue states the rates are even higher.

III. Rising prevalence is NOT the result of changing diagnostic criteria

Some will claim that rising autism rates are a product of changing diagnostic criteria. The evidence does not support this.

As most of my readers already know, high quality studies by Byrd et al. (2002) and Hertz-Picciotto & Delwiche (2009) concluded that better awareness, changes in diagnostic criteria, and earlier age of diagnosis only explain a small fraction of the rise in autism prevalence.

In addition, there are about 50 studies on how changes to the DSM definition of autism since 1980 have impacted prevalence estimates. I’ve reviewed them all and the quick summary is that:

• The DSM-III definition of autism in 1980 was too restrictive and significantly undercounted true autism prevalence;

• The DSM-III-R (1987) substantially broadened criteria;

• The DSM-IV (1994) partially narrowed core criteria while expanding the spectrum;

• DSM-IV-TR (2000) made no changes to the diagnostic criteria for autism; and

• The DSM-5 (2013) narrowed autism criteria, producing a reduction in autism prevalence estimates by about 20%.

The bottom line is that we are still likely UNDERCOUNTING true autism prevalence based on the current DSM-5 definition of autism.

IV. The iatrogenic risk data

Mawson et al. (2017a) in a study of homeschool children in Florida, Louisiana, Mississippi, and Oregon found that vaccinated children had 4.2 times higher odds of an autism diagnosis compared to unvaccinated children (OR = 4.2; CI: 1.2, 14.5).

Mawson et al. (2017b) found that preterm birth, coupled with vaccination increases the odds of neurodevelopmental disability by more than 12-fold compared to preterm birth without vaccination.

Hooker & Miller (2021) in a study of three medical practices in the U.S. found that:

• Vaccination increases the odds of developing autism 5-fold.

• Vaccination in the absence of breastfeeding increases autism risk 12.5-fold.

• Vaccination in addition to C-section birth increases autism risk 18.7-fold.

Mawson & Jacob (2025) using Florida Medicaid data found that children with 11 or more visits to the doctor that included vaccinations were 4.4 times more likely to have been diagnosed with autism than those with no visit for vaccination (95% CI: 2.85, 6.84).

These are the best numbers that exist on the increased risk of autism as a result of vaccination — somewhere between 4.2- and 5-fold increased risk.

But the problem remains… how does one go from a 4.2- to 5-fold increased risk for EACH INDIVIDUAL CHILD to a 323-fold increase in autism prevalence in the POPULATION since 1970? (Technically it’s a 322.58-fold increase but I rounded up to 323 for the sake of simplicity.)

For those who prefer to think in terms of percentages, the question is: how does one go from a 320% to 400% increased risk for EACH INDIVIDUAL CHILD to a 32,158% increase in autism prevalence in the POPULATION? Just a reminder for anyone who needs it: (Fold increase − 1) × 100 = percentage increase. So a 4.2- to 5-fold increased odds of autism from vaccines = 320% to 400% increased odds.

For now we are setting aside the increased risk of premies + vaccines (12-fold increased risk), absence of breastfeeding + vaccines (12.5-fold increased risk), and c-section birth + vaccines (18.7-fold increased risk). However those are just variations on the same mathematical problem — how does one get from a 12-, 12.5-, or 18.7-fold increased individual risk to a 323-fold increased prevalence in the population?

V. The overlooked statistic that unlocks the mystery

I went back through Mawson et al. (2017a), Hooker & Miller (2021), and Mawson & Jacob (2025) — the three best vaccinated vs. unvaccinated studies ever conducted — and discovered something astonishing: the autism rate in the UNVACCINATED childhood population today is 100 times higher than in the childhood population studied in Treffert (1970).

The autism rate in the UNVACCINATED population in recent studies:

Mawson et al. (2017a) = 1.15% (the published study shows 1.0% but I believe that’s a rounding error. When I re-run the calculation using the reported numbers [3 autism cases out of 261 unvaccinated children] it comes out to 1.15%)

Hooker & Miller (2021) = 0.95%

Mawson & Jacob (2025) = 1.1%

Heretofore, I think people overlooked the autism rate in the unvaccinated population because the rate in the vaccinated population is so much (4.2 to 5 times) higher. And the people pushing the ‘autism is genetic’ narrative may have lulled us into thinking that a 1% autism rate is the “natural” (genetic) rate in the population. But remember, the autism rate in the childhood population in 1970 was less than 0.01% and now the autism rate in the unvaccinated population is 100 times higher than that.

So, I’ve stumbled upon a “rising floor problem” which is that every recent study of vaccines and autism is measuring odds ratios against a contaminated baseline. It seems that the “unexposed” control group is exposed to something toxic, just not vaccines in those children per se.

VI. Recalculating odds ratios now that we know about the rising floor problem

Understanding the rising floor (as a result of widespread toxic exposures in society) unlocks a number of new insights into the autism epidemic:

A child born in 2014 (who turned 8 in 2022 — this is the latest data that we have available from ADDM) has a 1 in 31 chance of developing autism (3.2%).

I now realize that the proper comparison to understand the dynamics of the autism epidemic is NOT between a vaccinated and unvaccinated child born in 2014 because the unvaccinated child in our current era has been exposed to a lot of toxicants as well (we’ll explore this more in a moment).

The proper comparison is between the childhood population in the most recent ADDM study (Shaw et al. 2025) and the childhood population in the first autism prevalence study (Treffert, 1970). Said differently, the proper comparison is between a child born in 2014 who has a 1 in 31 chance of developing autism and a child born between 1950 and 1955 (Treffert, 1970, studied the incidence of autism in an entire state population age 12 during the period 1962 to 1967) who had a less than 1 in 10,000 chance of developing autism. The odds of developing autism in a child born in 2014 are more than 323-fold higher than in a child born in 1950.

When one makes this comparison between the two time periods, the odds ratio (323) and the overall prevalence increase (32,158%) match. So the answer to the question posed at the Connecticut conference is this: a 4- to 5-fold individual OR today becomes a 323-fold population increase when the comparator is corrected from a contaminated 2022 baseline to the 1962 to 1967 pre-epidemic baseline. (We’ll deal with challenges to this logic in a moment.)

If we continue this line of reasoning, my hypothesis is that the odds ratio of developing autism between a vaccinated child born in 2014 and an unvaccinated child born between 1950 and 1955 is probably between 420 and 500 (41,900% to 49,900% increased odds). Independent researchers likely missed this before because previously no one had identified the rising floor problem.

By the same token, I hypothesize that the odds ratio of developing autism between a child born in 2014 who was born via c-section, vaccinated, and not breastfed vs. a child born between 1950 and 1955 who was delivered vaginally, breastfed, and not vaccinated is probably around 1,870 (186,900% increased odds) — likely the highest odds ratio you will ever see for any measurable harm on planet Earth other than perhaps enlisting in a war.

(To be clear, Hooker & Miller 2021 calculate odds ratios for “c-section birth” and “not breastfed” separately. I was just looking to come up with a “highest risk” modern cohort vs. a “lowest risk” historical cohort. I use the odds ratio from the higher risk category, c-section birth, rather than absence of breastfeeding; however I’m not implying an interaction effect between these two categories even though there very well could be one. The 100-fold higher OR from vaccines in these scenarios is what we would see if the comparison group had an autism rate of about 0.01% which is what we see in Treffert, 1970, rather than the 1% rate we see in the unvaccinated population today.)

VII. Fine tuning the revised estimates of odds ratios between time periods

Treffert, 1970, actually had 3 groups in his study on autism prevalence: Group A (“classic infantile autism”), Group B (a later onset psychotic disorder that sounds like regressive autism), and Group C (“probably psychosis” along with “deafness, aphasia, or other evidence of brain damage” — it is unclear to me whether these are autism comorbidities or a different diagnosis altogether). Treffert writes:

Of the cases, 25% fit the definition of classic early infantile autism (group A);

56% fit into group B, and

19% into group C.

In prevalence terms these work out to:

Group A, 0.775 cases per 10,000 children (that’s where we get “a prevalence of less than 1 in 10,000 children” as the shorthand for this study).

Group B, 1.736 cases per 10,000 children.

Group C, 0.589 cases per 10,000 children.

(Apologies for using three decimal places, however if I round them off it breaks the math later so I thought it better to be precise.)

If one only uses the prevalence estimate for Group A as the point of comparison in the model I built in Section VII above, the odds ratios for harms from vaccines and other toxicants between the two eras rises from 323 to approximately 416 — a roughly 29% increase from my initial calculation.

Using Groups A + B (0.775 + 1.736 = 2.511 autism cases per 10,000 children) as the baseline comparator the fold-change drops from 323 to about 129 — a reduction of roughly 60% from my estimate in Section VII.

Using Groups A + B + C (3.1 autism cases per 10,000 children) as the comparator the fold-change drops to about 104 — a reduction of roughly 68% from my estimate in Section VII.

However an OR of 104 is still more than twenty-fold higher than the odds ratios published in Mawson et al. (2017a), Hooker & Miller (2021), and Mawson & Jacob (2025) — which are already so high that the mainstream scientific and medical community refuses to discuss the contents of these studies and resorts to ad hominem attacks instead.

VIII. What explains the rising autism rate in the unvaccinated population?

The roughly 1% autism rate in the unvaccinated population today is likely the effect of the 86,000 industrial chemicals registered for use in the U.S. that are generally not regulated at all (this includes some of the toxicants studied by CHARGE, MARBLES, SEED, and EARLI).

Bioaccumulation means that these toxicants can become more concentrated within a species over time and biomagnification means that these toxicants can become additionally concentrated as they move up the food chain.

We may be seeing teratogenic effects as well — whether from vaccines or other toxicants. A teratogen is a toxicant that causes developmental abnormalities in a fetus or embryo. It seems plausible that aluminum and other ingredients in vaccines could be teratogens although that research has not been conducted because Pharma would never allow government to fund that sort of research and any professional who studied that would soon be censored and blacklisted by academia, scientific journals, government, and the media.

A recent study (Korolenko et al., 2026) showed intergenerational effects from a single exposure to a toxicant (vinclozolin, a fungicide) that impacted offspring for all twenty-three future generations of animals examined.

The rising autism rate in unvaccinated populations is consistent with intergenerational teratogenic effects — epigenetic modifications, maternal immune activation, and microbiome disruption — transmitted through the maternal lineage from prior decades of toxicant exposure. That could be from vaccines or from some combination of the 86,000 chemicals in use, EMF/RFR, nuclear weapons testing in the 1950s and 1960s, coal-fired power plants, etc.

If this explanation is correct, no single birth cohort today can serve as a clean unexposed control for any subsequent cohort, because each generation inherits an already-modified biological substrate from the previous one. The autism epidemic is thus not merely a story of direct individual exposure; it may also be a story of accumulated biological harms across generations.

IX. A new model of the autism epidemic

So the model of the autism epidemic that I’m building looks something like this:

Vaccines clearly increase autism risk. The CDC’s own internal research in 1999 showed that those with the highest mercury exposures in the first month of life had 11.35 times higher autism risk (see report from SafeMinds). The removal of mercury from most vaccines in the early 2000s only made a small impact on autism prevalence because several aluminum-containing vaccines were added to the schedule soon thereafter.

Vaccinated vs. unvaccinated studies are a relatively recent phenomenon — they should have been conducted all along but never were. Once parents realized, in the late 1990s, that the necessary studies had never been done, they called for researchers to conduct vaccinated vs. unvaccinated studies for the first time. Only a handful of independent researchers stepped up to do this foundational work as mainstream academia and government were already captured by the pharmaceutical industry. All proper vaccinated vs. unvaccinated studies have shown statistically significant harms from vaccines.

By my count, 25 changes have been made to the CDC vaccine schedule since 1986 and 23 of them increased the total toxic load imposed on children. The only exceptions are the replacement of whole-cell DTP with acellular DTaP in 1997 which slightly reduced the rate of fatalities from the shot while still causing catastrophic harms to others and the withdrawal of RotaShield in 1999.

RoundUp Ready® seeds became widely available in the 1990s and so herbicide exposures vastly increased (Waldman et al., 2017).

More children are born underweight and early (premies).

More birth drugs are used.

More children are delivered via c-section.

More moms use formula instead of breastfeeding because of aggressive marketing from formula companies and difficulty breastfeeding caused by toxicants in both mother and baby that make nursing more challenging.

As I showed in my thesis (2019), there is no regulatory system in the U.S., only the appearance of a regulatory system (we have regulatory theater, but 99.99% of chemicals are approved).

Over time the total allostatic load becomes overwhelming and children are the canaries in the coal mine whose bodies break first.

What we need is a whole-of-society approach to reducing toxicants, starting with eliminating vaccine schedules altogether (and offering, at most, three optional vaccines to those who want them). We also need reductions or bans of endocrine disrupting chemicals, fire retardants, toxic ingredients in plastics, herbicides/pesticides/fungicides, other pharmaceuticals (Tylenol, antidepressants), and EMF/RFR along with better regulation of pollutants in our air, water, and soil.

X. Criticisms, qualifications, and rejoinders

1. The strongest criticism of the work I’ve done here is that I’ve just switched from an individual risk model (Mawson et al., 2017a; Hooker & Miller, 2021; and Mawson & Jacob, 2025) to a population-based model comparing two time periods. Of course the odds ratio in this model matches the total societal increase over that time period because it’s a population-based model comparing two time periods!

Fair enough, but the rising floor problem is a genuinely unique and I think important contribution to autism prevalence modeling. A 0.95% to 1.15% autism rate in completely unvaccinated populations is astonishingly high — at least 100 times higher than what one would expect based on earlier modeling of autism prevalence. And the rising floor problem obscures the true increased individual and societal risks from vaccines over time so it’s instructive to correct for that.

2. It’s possible that the estimates in Treffert (1970) are an underestimate of true autism prevalence at the time. However, I’m reminded of this section in Andrew Solomon’s book, Far from the Tree (2012), where the former director of the National Institute of Mental Health, Thomas Insel (no friend of anti-vaxxers), “recounted a time during the 1970s when an autistic child was admitted to Boston Children’s Hospital; the chief of service called the residents together to observe him, reasoning that they might never see an autistic child again” (p. 261). THAT’s how rare autism was in the 1970s. Medical records from Leo Kanner’s practice also show that historically, autism was vanishingly rare. So it’s also possible that Treffert (1970) was an overestimate of autism prevalence at the time (particularly if one combines all three groups that he studied as the comparison group as I explained above).

3. It’s possible that in fact the “unvaccinated” population in Mawson et al. 2017a, Hooker & Miller 2021, and Mawson & Jacob 2025 were not unvaccinated but instead received some vaccines and their medical records were incomplete. Perhaps, but these scholars are very thorough and the results are consistent across three different study populations. So I don’t put much stock in the ‘actually vaccinated unvaccinated’ hypothesis.

4. The final obvious criticism is that there were high levels of pollution in the United States in the 1950s and 1960s, so it’s strange to use this cohort as the “uncontaminated” comparison group. Fathers and mothers smoked like chimneys exposing children to secondhand smoke; there were few if any regulations on emissions from factories and cars; lead was in gasoline; and DDT and other toxicants were routinely sprayed on crops, wetlands, and sometimes directly on children. Point taken. But isn’t it interesting then that children in that era had such lower rates of chronic illness than children today?

Rather than refuting my insights here I think this illustrates how much more toxic our environment and our bodies have become — that the bloated childhood vaccine schedule and other modern toxic exposures (endocrine disruptors, fire retardants, herbicides/pesticides/fungicides, EMF/RFR, and other pharmaceuticals) along with possible intergenerational effects from previous toxic exposures leave more than half of all children chronically ill today (as compared with single digits in the 1950s).

XI. Conclusion

I believe that the “rising floor problem” is a new and unique insight into autism prevalence modeling. The best available vaccinated vs. unvaccinated studies (Mawson et al., 2017a; Hooker & Miller, 2021; and Mawson & Jacob, 2025) show an autism rate of about 1% in the UNVACCINATED population today. That’s more than 100 times higher than one would expect from reading Treffert, 1970.

The rising floor problem obscures the true dynamics of the toxicological crisis we are in. Calculating odds ratios across eras shows that a child born today has a 323-fold higher risk of developing autism than a child born in the 1950s and a child born today who is vaccinated according to the CDC childhood vaccine schedule has a 420- to 500-fold higher risk of developing autism than a child born in the 1950s. Children who are born via c-section and/or are not breastfed face even higher risks.

The rising floor problem is explained by increasing toxic exposures across the whole population and possible intergenerational effects from toxic exposures in previous generations. While pollution was abundant in previous generations, the potency, persistence, and ubiquity of toxic exposures today have caused a massive increase in chronic illness in children.

We need a whole-of-society approach to massively reduce toxicants in society immediately and permanently. Unfortunately, in spite of a sea change election in 2024 and the inclusion of the Make America Healthy Again movement in the new governing coalition, toxic exposures in society have increased in the last year as some environmental protections have been rolled back by the Trump administration (e.g. the EPA’s reapproval of toxic dicamba, the glyphosate executive order, and a recent EPA decision to rescind pollution controls on power plants).

Regulatory, financial, and epistemic capture likely prevent the CDC and NIH from conducting this sort of modeling even though it is well within their technical capabilities and statutory obligations.

The bottom line is that we know how to bring down the risks of developing autism. Now we must summon the political will to implement the obvious and necessary reforms.

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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Why haven’t we won already given that the data are so overwhelmingly in our favor? And, What’s it going to take to finally convert our progressive friends to the rightness of our cause?

Some panelist gave good replies but everyone has a different theory of change and at this point no one really knows what will work (these are questions that the movement has been debating since the beginning).

[You can watch the full film and the panel discussion here.]

Out on the patio at the reception following the film I found myself in a lovely group with an artist, a natural healer (Lisa Cory), a marketing guru who was new to the movement, and a warrior mom (Ronna Yelin). The sun was warm, the bar was open, the DJ was spinning 80s tunes, and we were all still wrestling with Jimmy Dore’s questions — why haven’t we won already and what will it take to convert our progressive friends to the obvious truth.

Lisa gamely proposed an answer:

Reaching the people who still believe that the Covid vax was good for public health will not be accomplished by engaging the intellect alone, as has been proven by the copious amount of scientific evidence and data already presented yet still being ignored and denied. We must learn how to speak to the heart as well. For at the root of this discussion is the experience of betrayal, the realization that people we trusted to care for us actually harmed us — the many people working in healthcare harmed us via indoctrinated ignorance, the very few in charge of healthcare harmed us via design and intent. It’s the same dynamic at play in abusive relationships, where the abused will ignore, excuse and hide their wounds while defending their abuser, insisting on maintaining the relationship against all better judgement and caution, rather than face the crushing emotional reality of betrayal.

Everyone agreed that this was a promising answer that provided a path forward. And then I said,

I think you’re right. And I think I like your answer better than I like my answer. But let me lay out my theory of the case so that we can compare them and see where we end up.

So I began…

Since the Enlightenment, religiosity has declined in society. But it turns out that people really need something to worship. So we started worshipping Scientism — not science itself, but the vague notion that our society should be guided by sciency-sounding ideas. Vaccines are the pinnacle of science as religion — doctors are seen as the new high priests, vaccines are the sacrament and the baptism, and, subconsciously, the vaccinators believe that someday soon they will be able to achieve immortality right here on Earth. As they often say, “death is just a series of preventable diseases” (it’s not, but that’s what they believe).

So when we step forward and say, ‘Well actually, your vaccines don’t work very well and they cause more harm than good,’ we have not just rejected a medical product, we’ve falsified their religion and their entire understanding of the universe. We’ve shattered their immortality project. Our work leaves people staring into a giant, terrifying metaphysical void. People will do anything, up to and including murder [Charlie Kirk had just been assassinated a month earlier], in order to avoid feeling that way. So they shout us down and exclude us from polite society and call us names because they don’t want to stare into that existential void.

I’m reminded of this scene — Shouting into the Infinite Abyss — from the movie Garden State (sorry for the poor image quality):

I continued:

And this is going to keep happening until we provide them with an alternative metaphysics* that has greater explanatory power and makes their lives better.

It’s like Indiana Jones in the opening scene of Raiders of the Lost Ark — where he tries to switch the golden idol with a bag of sand — when we take away their Scientistic Metaphysics we have to replace it with something of equal weight or else they will come after us with poison arrows and try to kill us. (Unlike Raiders of the Lost Ark, I don’t want to just replace their Molochian idol with a bag of sand, I want to replace it with something better.)

We have to be able to explain our place in the universe, how nature works, what is time, what happens when we die, how to relate to each other, and how to cure disease. And our answers have to be qualitatively better than their answers.

Lots of people, including Patrick Deneen at the University of Notre Dame want us to return to a pre-Enlightenment Metaphysics — the church is in charge; the church knows best; patriarchy, family, and tradition are all that matter. It’s true that evangelical Christians fared better than many other groups during Covid because they had something other than Scientism to rely on when society fell apart. But I don’t think Deneen’s ancient reset point will work for most people. The cat’s already out of the bag.

Whatever metaphysics we come up with has to be future-facing. It has to include everything we know right now and also transcend it with a more comprehensive story of the universe, nature, and our place in it. In general, I believe that we need to be much more ambitious and audacious in our thinking — and practice the courage of our convictions — if we are to break out of the current crisis.

We spent the rest of the afternoon debating Jimmy Dore’s provocative questions and discussing the possibilities of a new metaphysics. It was the best day I’ve had in a very long time. An Inconvenient Study won Best of Festival at the awards ceremony later that night.

Since then, I’ve had a lot more time to think about a new metaphysics and what that might entail. I’ve queried ChatGPT and Claude and they are surprisingly adept at discussing these ultimate questions. I believe that my theory of the case — that we need a new metaphysics — is correct. And I have a few additional thoughts about how we might proceed on this journey of discovery:

1. It turns out that nearly ALL fields of inquiry are captured and have been captured for about a century. Bret Weinstein and his brother Eric have done much better work than I have in exploring how capture happened in nearly every field. But my sense is that after World War I, and certainly after World War II, the U.S. didn’t have any viable competitors in any field. So the university gatekeepers in physics, chemistry, biology, political science, sociology, art, etc. hired people who think and act exactly like they do, and this continued for five generations — copy, upon copy, upon copy… — until all disciplines were a hollow imitation of their former selves and there had not been much real innovation in 100 years. We’re in an epistemic crisis right now because so many things are either factually wrong (owing to corruption) or obviously outdated. However, one is not allowed to break paradigms without getting one’s knees broken by the gatekeepers these days.

2. Karl Popper’s An Open Society and Its Enemies and Paul Feyerabend’s Against Method give us tools for unlearning dogma and starting innovative scientific inquiry again. As I’ve argued many times before, we need to have a big, messy, on-going conversation about the philosophy of science in order to survive and break free from our captured era.

3. I thought that “Everything is energy” might be a good candidate for a new metaphysics. Dr. Richard Gerber wrote a thought-provoking book called Vibrational Medicine that operates from this understanding. Australian Substacker, Lies are Unbekoming, explores this idea as well — building on the work of Liam Scheff (1971-2017) who was skilled at breaking existing paradigms (by actually doing the reading and showing the weaknesses and contradictions of existing theories).

But ChatGPT chastised me by saying that “everything is energy” is already embedded in Einstein’s equation E=MC^2 and that’s already more than 100 years old.

I pushed back and said ‘so-called modern medicine has not incorporated “everything is energy” into its theories nor has it incorporated the insights from quantum mechanics which is now already 100 years old as well.’ And ChatGPT was forced to admit that indeed, with the possible exception of MRI machines, modern medicine is still stuck in an 18th century mechanistic understanding of the world and has yet to incorporate the insights from physics from 100 years ago.

4. “Everything is plasma” and “The Living Universe” are also intriguing possibilities that are related to “Everything is energy.” I think it’s important to note that one of the top plasma scientists in the world, Nuno Loureiro, was assassinated in December of last year (like the assassination of Charlie Kirk, the official story of what happened is nonsensical).

5. String theory, “multiple universes,” and “everything is a hologram” seem like dead ends to me.

6. Rachel Carson probably did the best recent work at moving to a new paradigm in Silent Spring when she showed that everything is a system. But it’s still a materialist worldview (albeit more comprehensive) and I think we can do better than that.

7. I’m pretty sure that The Hidden Life of Trees by Peter Wohllenben and Braiding Sweetgrass by Robin Wall Kimmerer offer us some starting points — with their vast, scientifically provable work on previously unseen networks of communication in the microbial kingdom, between plants, and between animals.

8. One can make a strong case that we don’t need a new metaphysics, that we are winning the materialist argument already. In this view, our job is just to call for a return to proper (materialist) science — vaccines are not adequately tested, the data that we do have show that vaccines don’t work very well and they come with horrendous side effects so we’d be better off with proper nutrition, clean water, antibiotics, and antivirals. Just take the win and be done with it.

The thing is, the materialist worldview ALREADY crumbled 100 years ago with the theory of relativity and quantum mechanics (and the tensions between the two that are begging for a higher synthesis). It’s just that nobody has been able to accurately describe what comes next because of extreme gatekeeping and capture across nearly all fields of inquiry.

Materialism was always an incomplete picture of our universe and our place in it. Perhaps one reason the existing gatekeepers have become so monstrous is because they are already staring into the abyss — on some level they realize that their theories are insufficient. In the meantime they are looting as much as they can from the existing system before the new paradigm comes in and dislodges them from their comfortable perch.

Stopping the ruling class from enslaving humanity via chronic illness is the defining task of our generation. It’s going to require all of our talent and tenacity for the foreseeable future. I just think that paradoxically, this work gets easier if we are simultaneously building a new metaphysics that provides a more comprehensive view of reality than bougie mechanistic materialism.

What do you think — do we need a new metaphysics and if so, what, for you, are the starting points for that journey?

*Definition of metaphysics from Claude:

Metaphysics is the branch of philosophy concerned with the fundamental nature of reality — what exists, what kinds of things exist, and what are their basic properties and relations.

Core metaphysical questions include: What is existence? What is the relationship between mind and matter? Do abstract objects (numbers, properties) exist? What is causation? What makes something the same thing over time? Is there free will? What is the nature of time and space?

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the alternative society our hearts know is possible. ✊

In the comments, please share your thoughts on the above questions.

As always, I welcome any corrections.

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The Rogers Test for vetting health science reporters

Any reporter who wants to interview anyone from the medical freedom movement should first demonstrate their bona fides as follows. Send a link to an article you wrote where you:

☐ Respectfully interviewed a parent of a vaccine injured child.

☐ Respectfully interviewed someone who was injured by a Covid vaccine.

☐ Cost the pharmaceutical industry money (bit the hand that feeds you and survived).

☐ Critically reviewed a Pharma-funded study and showed how it was rigged.

☐ Acknowledged that none of the shots on the childhood vaccine schedule have been tested against a proper saline placebo.

☐ Acknowledged that Covid shots cause more harms than benefits.

Any reporter who cannot meet these six basic conditions has no business talking with the people who risk their lives every day standing up to the pharmaceutical cartel.

I cannot think of any mainstream reporter who meets this minimal threshold of human decency. So we should not waste our time and energy talking with them.

Of course there are a few legendary examples of activists who converted a hostile reporter in connection with a particular article or news story. However, those reporters are under tremendous pressure to return to their previous biases because all of the incentives in the mainstream media are to take care of the pharmaceutical mafia that pays the bills. The few reporters who have become long term champions — Sharyl Attkisson, Del Bigtree, and Tucker Carlson come to mind — have continued to tell the truth by building their own programs and distribution channels outside of the mainstream system.

Ten years ago, the only way we could get our message out was by talking with mainstream reporters who hated us, who we hoped might allow a tiny bit of the truth to shine through their dripping contempt. Today, allies including Joe Rogan, Tucker Carlson, DarkHorse Podcast, The WarRoom, and The Highwire have audiences five to 10 times larger than the highest rated cable news programs. Substack, X, Rumble, Spotify/Apple podcasts, and Wordpress allow anyone to get a message out (although Meta, TikTok, LinkedIn, and Square continue to censor us). Heck, on a good day I can reach a larger audience than most cable news shows even though I have no paid marketing. The point being that we don’t have to beg for table scraps from the genociders anymore. We are the media now, we’re part of the government, our movement grows larger every day — there’s no need to help awful people, who belong in jail, sell more newspapers or generate more clicks.

So if a reporter asks you for an interview, just send them The Rogers Test and see how they measure up!

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please tell me how you would improve the Rogers Test.

As always, I welcome any corrections.

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As the Informed Consent Action Network has demonstrated, the hepatitis B vaccines Recombivax and Engerix — injected into the vast majority of American children at birth, one month, and six months of age — never should have been licensed by the FDA in the first place.

The clinical trials for Recombivax and Engerix:

• did not include a proper saline placebo control group;

• were too small to detect uncommon adverse events; and

• were too short to detect the majority of harms (the Recombivax trials monitored safety for just five days, the Engerix trials monitored solicited adverse events for just four days).

II. Hepatitis B vaccines are associated with autism

The real world data that are available on the safety of hepatitis B vaccines are horrifying. When autism rates in the U.S. exploded in the 1990s, the CDC looked into the possible role of vaccines. They assigned one of their senior scientists, Thomas Verstraeten, at the Epidemic Intelligence Service, to do the analysis. At the time, hepatitis B vaccines had mercury (thimerosal) in them. Dr. Verstraeten found that children in the highest exposure group had an 11.35x increased relative risk of autism.

Source: SafeMinds.

Then, because the CDC works for the pharmaceutical industry, Dr. Verstraeten did four additional rounds of data manipulation, that were not scientifically warranted, to try to make the signal go away. We have Dr. Verstraeten’s emails and the five different rounds of analysis because SafeMinds did a FOIA request to get all of Dr. Verstraeten’s communication about the study (see SafeMinds Powerpoint presentation here). The corrupted data were used in the final published paper and the original findings were covered up.

The CDC had this information in 1999 and has lied about it for 26 years (which I mentioned in my recent Senate testimony). In 2001, Dr. Verstraeten was scheduled to present his findings to the Institute of Medicine but he quit on the morning of the presentation to go work for vaccine manufacturer GlaxoSmithKline in Belgium (see Evidence of Harm).

Mercury was eventually taken out of hepatitis B vaccines however aluminum adjuvants remain. CDC/ACIP subsequently added several more aluminum containing vaccines to the childhood schedule. What we see in the autism prevalence data after the removal of mercury, together with the increase in total aluminum in the schedule, is that autism rates keep rising (owing to the increased aluminum) but the proportion of severe autism cases as a percentage of the total declined somewhat (owing to the removal of thimerosal which is even more toxic than aluminum).

III. Hepatitis B vaccines have killed an astonishing number of children in the U.S.

I asked the warrior mamas at OpenVAERS (who are doing the work that the CDC should be doing) to calculate the total number of deaths from hepatitis B vaccines from 1990 to the present. The results that came back show that hepatitis B vaccines are a crime against humanity.

Hepatitis B is a component in many combination vaccines including Twinrix, Pediarix, and Vaxelis. When one looks at VAERS reports in the U.S. for all vaccines containing a hepatitis B component there are 1,348 deaths of children and 82,980 total reports of harm across all ages.

Just looking at Recombivax and Engerix, U.S. reports, there are 643 deaths of children and 52,281 total reports of harm across all ages.

Remember that VAERS reports are a significant undercount of harms. The Lazarus and Klompas study for HHS in 2011 estimated that VAERS undercounts actual harms by a factor of 100x. More recent scholarship by Steve Kirsch, Mathew Crawford, and Jessica Rose in 2021 calculated a VAERS Under-Reporting Factor of 41x.

A similar estimate by VAERS Analysis (necessarily anonymous because whistleblowers are hunted by Pharma) in 2021 shows an Under-Reporting Factor of 44.64x for deaths. If that Under-Reporting Factor is correct, then an estimated 60,175 children have been killed by all vaccines with a hepatitis B component over the last 35 years in the U.S.; of that total, an estimated 28,704 children have been killed by Recombivax and Engerix in the U.S. over that same time period.

OpenVAERS also calculated the “days to death post vaccine” for all VAERS reports of death associated with hepatitis B containing vaccines and for Recombivax and Engerix. There we have a causal smoking gun as the largest numbers of deaths are on the day of vaccination or one or two days after.

IV. Conclusion: hepatitis B vaccines must be removed entirely from the CDC childhood schedule

The members of the ACIP are under tremendous pressure from the Pharmaceutical Industrial Complex to simply delay the timing of hepatitis B vaccines to day 30 or to 12 years of age. However, the fact remains that there are no data proving the safety and efficacy of hepatitis B vaccines on day 1, day 30, or 12 years of age.

If one wants to return to “Gold Standard Science” one must conduct proper double-blind randomized controlled trials, with an inert saline placebo in the control group, a large enough sample size (at least 60,000) to detect rare events, and long enough post vaccination monitoring (10 years) to capture non-specific effects.

No “Gold Standard” hepatitis B vaccine safety and efficacy studies in pediatric populations exist right now and so hepatitis B vaccines must be removed altogether from the CDC childhood schedule.

Hepatitis B vaccines were developed for IV drug addicts and prostitutes because those are the high risk groups. If hepatitis B vaccines are to be used at all, they should be properly tested and returned to that original purpose and that intended market. If prison guards want to get them as well because they are dealing with a high risk population that’s fine. Also, the benefits of hepatitis B vaccination appear to outweigh the risks for children born to mothers who are hepatitis B positive (and we know exactly who those children are because all pregnant women are tested for hepatitis B in the hospital prior to giving birth). However, the idea of administering hepatitis B vaccines to nearly the entire childhood population is self-evident madness.

Here’s the whole story in a one-page infographic created by OpenVAERS. Please share it with your networks because the lives of thousands of children and the fate of the Republic is on the line.

Hepatitis B Vaccine Reports In Vaers 1990 To 2025

219KB ∙ PDF file

Download

Download

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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We live in a time of transition. The old paradigms are failing and new paradigms with greater explanatory power are struggling to be born.

Standing in the breach are mainstream health science reporters. They tend to be progressive, just out of college, with little to no graduate education. A quick look at their LinkedIn pages suggests that they were elated to get what appear to be prestigious jobs for Stat News, KFF, Politico, the New York Times, or any of the hundreds of Pharma-funded narrative enforcement (aka “fact check”) organizations that sprang up during Covid. They’re just smart enough to be arrogant but not wise enough to know what they don’t know.

Then they get assigned a story about some facet of the vaccine debate where they encounter a group of people who think very differently than they do — and they suddenly lose all sense of decency.

Proper reporting, back when that was still taught, would require sufficient research to accurately describe the viewpoint of this different social tribe.

“Position switching” (putting oneself in the shoes of another) is the basis of empathy and a slightly more experienced reporter would do everything possible to view the world through the eyes of his/her interviewee.

A skilled reporter might even try to “steel man” this alternative perspective to find the strengths of the opposing argument rather than exaggerating weaknesses that do not accurately represent the views of the people being studied.

Proper editors, back when that was still a thing, would not sign off on an article until the reporter had gotten to the heart of the matter and captured the essence of the other worldview.

But none of that happens in health science reporting today. Instead these wet-behind-the-ears reporters all follow the same script — ‘anyone who disagrees with the mainstream narrative must be a nutter who could not possibly be understood by anyone in polite society.’

Mainstream health science reporters almost never interview the parents of vaccine injured children or vaccine injured people themselves about their injuries. Any reporter who does so quickly resorts to gaslighting as a way of managing their internal distress.

These reporters often seek the opinions of doctors, lawyers, scientists, and others with advanced degrees. Yet if any scholar contradicts the mainstream narrative he or she will be portrayed like a homeless schizophrenic person spinning in circles and talking nonsense (actually, schizophrenics are treated infinitely better than vaccine skeptics by mainstream health science reporters because schizophrenics don’t threaten the narrative).

In the movement for medical freedom we have thousands of peer-reviewed sources, nearly everything we do is public, and our work is meticulous because we get torn to shreds for decades by the Big Pharma media machine if we ever make any mistakes. But mainstream health science reporters almost never actually read our work. It’s not that they disagree with us — they never read enough of our work to even understand our position (at most they do a quick search to find a “gotcha quote” that they can pull out of context and wield like a bludgeon). So their bias leads to bad methods that they try to cover up by portraying us as shadowy conspirators whose beliefs are indecipherable. This extreme “othering” has become a requirement of the mainstream health science reporting profession.

II. They should know better

Nearly all of these reporters are progressives who should know better. If their undergraduate education was anything like mine, it likely included extensive lectures, readings, and research papers on the importance of not “othering” people, the grave injustice of bigotry, the evils of colonialism, and America’s long history of exploitation and violence.

But the progressive worldview today makes an exception for vaccine skeptics who are treated with systematic contempt as a requirement of the faith. Furthermore, to the progressive mind it does not matter if the vaccine skeptic is better educated, more qualified, or more well-versed in the topic — anyone who questions vaccines is treated as subhuman and all of their claims are dismissed out of hand regardless of the sources that they provide.

Because mainstream health science reporters think that people in the medical freedom movement are less than human, these self-righteous stenographers for the drug cartel see no contradiction between their anti-genocidal, anti-colonial, anti-bigotry worldview and the fact that their reporting leads to iatrogenocide, supports Pharma Colonialism, celebrates bigotry, and encourages segregation. Antivax bigotry is the only form of bigotry still allowed in polite society today and progressives are loud and proud of their contempt for this “other.”

I believe it is massively destabilizing for society that supposedly smart people routinely engage in this sort of doublespeak — expressing one set of deeply-held values and then immediately violating those values — without the self-awareness to see their own hypocrisy. This makes mainstream health science reporters look ridiculous. Furthermore mainstream doctors and scientists debase themselves because they never correct the record or demand fairness when it comes to this stigmatized “other.” The emergence of this style of reporting and its persistence suggest that a new form of totalitarianism is in operation in the U.S. that is exemplified by total mental capture of this profession (and many others).

III. Sane people should be able to have a rational conversation about these matters

Let me explain this as clearly as possible.

The work of Children’s Health Defense, the Informed Consent Action Network, the Highwire, Stand for Health Freedom, Health Freedom Defense Fund, the National Vaccine Information Center, etc. is extremely straightforward. They endeavor to understand, scientifically and medically, how toxic exposures cause harm and then work, legally, to reduce or eliminate those toxic exposures. That’s it.

The work of the medical freedom movement is no different from the efforts of the Environmental Working Group — with the exception that the medical freedom movement has the courage to address iatrogenic injury and take on Big Pharma, which most mainstream environmental groups are too scared to discuss.

The work I do is related to, but somewhat different from, the work of the large medical freedom non-profits. I seek to understand the politics, economics, and sociology of the chronic disease crisis. Why do government officials respond with urgency to infectious disease but ignore the much larger problem of chronic disease? How did chronic disease become an industry that is now too big to fail? How does financial capture override previously held beliefs without producing unbearable cognitive dissonance? Brownstone Institute, where I’m currently a Fellow, also works on the politics, economics, and sociology of this crisis.

Anyone should be able to have a rational conversation about these issues. No need to get the vapors and retire to the fainting couch anytime someone questions the bloated junk science CDC vaccine schedules. And yet every single mainstream health science reporter fails this basic test of human decency, and insists, as a requirement of the job, that these damn dirty antivaxxers cannot possibly be understood and must be from Mars.

The dehumanization of people like me who want to keep toxic chemicals out of children’s bodies serves a purpose. It sets up the pretext for systemic violence and discrimination against us. It protects Pharma’s enormous profits. And it enables mainstream science and medicine, and bourgeoise society itself, to pretend that they are not currently engaged in iatrogenocide.

The psychology and sociology of the cowardice displayed by mainstream health science reporters is pretty straightforward as well. It is terrifying to comprehend the total depravity of mainstream science and medicine (and government, corporations, and large swaths of civil society). Many people, and certainly most mainstream health science reporters, lack the courage to stare reality in the face. Furthermore, they lack the moral fortitude to speak truth to power. So they retreat to comforting lies, clichés, and demagoguery of the “other” in order to protect their fragile Polyannaish worldview.

The problem is, this is not a mere difference of opinion. When mainstream health science reporters repeatedly ignore evidence that vaccines cause harm they are engaged in racketeering on behalf of the pharmaceutical industry. And when mainstream health science reporters engage in “othering” to protect the genocidal status quo they are committing crimes against humanity. We don’t have enough political power yet to prosecute these crimes, but the pressure is building and things could change quickly.

The only good news in all of this is that the mainstream information distribution channels are dying and the new parallel economy — with heaps of alternative news sources including Substack, podcasts, and publishers including Brownstone Institute, Chelsea Green, and Skyhorse — is thriving. But the mainstream media landscape will be ugly for a while as the old paradigm goes through its final death throes.

Further reading (my prompts are below and the links will take you to the replies from ChatGPT):

Define the social science concept of “othering.”

Please map “othering” onto the fact that nearly all mainstream health science reporters in the U.S. act as if “anti-vaxxers” are completely indecipherable when in reality they are just normal everyday people who have a family member who was injured by a vaccine.

Please trace how “othering” intersects with epistemic capture/epistemic injustice in health and science.

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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[Transcript]

Transitional justice is completely fascinating. It’s the field of law where a tyrannical regime has been overthrown, the revolution succeeded, Eastern Europe collapsed… What do you do next? How do you have justice for the crimes of the old regime and set the foundation for the new future for the country?

We need a Transitional Justice effort for the crimes of the Covid era and for the crimes of the 1986 Act and the childhood vaccine schedule. That’s foundational. It’s tricky to pull it off because the old guard’s still around and they still have some power and they may overthrow you if you go too far, too fast. It is difficult to pull off.

Every country that tries to do this does it in a different way:

South Africa did a Truth and Reconciliation Commission. That was a particularly spiritual approach to these questions.

We had Nuremberg Trials at the end of World War II that led to the Nuremberg Code. And that was one way to do it. Military trials.

In Eastern Europe, they had what was called lustration laws, which is where you open the books of the government so people can see how they were tracked and surveilled by the secret police and all that. I’m sure there are files on nearly everybody in this room for the work that we’ve done during the Covid era. What would it be like to open up the files and release those to the public?

But we have to stop the harms that are happening right now:

1. We have to pull the Covid shots from the market. We have to stop new people from being injured. That’s foundational. That’s a start.

2. We have to get rid of vaccine schedules altogether and have individualized medicine for everyone in this country. That’s foundational. Those are building blocks.

3. But we also have to have a dialogue led by spiritual and religious leaders about the moral injury and the moral crimes of this regime — of the pharmaceutical industry.

4. And then we need just compensation. We need to set aside a trillion dollars to compensate autism families who’ve been injured by the childhood vaccine schedule.

5. And we need to set aside a trillion dollars to compensate people like Brianne Dressen who’ve been hurt by Covid-19 vaccines. That is foundational.

[Jeffrey Tucker] And small businesses!

Absolutely, absolutely, that is foundational to this country rebuilding and becoming a democracy again. We need to have a conversation about Transitional Justice. We need a Transitional Justice process. And until that happens, this country’s not going to be able to heal.

You can watch the full “Injured America” panel discussion (here) starting about the 58 minute mark.

Further reading:

What Is Transitional Justice? International Center for Transitional Justice

The International Journal of Transitional Justice, Oxford University Press

Transitional Justice, Grokipedia

An Introduction to Transitional Justice, edited by Olivera Simić, Routledge, 2011.

Transitional Justice, by Christine Bell, Routledge, 2013.

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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[Transcript]

The biological colonialism argument that Jeffrey alluded to goes something like this:

So for the last 500 years, if you were a nation that wanted to get rich, the way you did it was you built a bunch of ships, you loaded them full of soldiers and guns and horses, and you sailed from Europe, to the New World, and you took their stuff. You took their gold, you enslaved their people, you forced people to work in the gold mines and that sort of thing. That’s how Europe got rich. That’s how the UK got rich. And so that’s the historical pattern for 500 years. 500 years of colonialism.

And then later there was neocolonialism with unfair trade deals that kept enriching Europe and the United States. And then more recently, with the backing of the U.S. military, we can get Third World nations to produce stuff for us for low cost that makes us feel rich. So historically, for 500 years, that’s been the pattern.

Here’s the problem: At some point, there were no new lands left to conquer. And so what the ruling class decided was that where the money is — the peasants to be exploited — were the middle class in the United States and throughout the developed world. And how do you extract wealth from the middle class? You do it through iatrogenic injury.

So if you can get the entire population to inject their kids 72 times during childhood and then get all the rest of the population and the kids to take Covid shots and you can injure them, you can enslave them for life to chronic illness. So in my research, I show that lifetime care costs for autism are in the range of $5 million to $7 million per kid. That’s a lot of money. And it goes somewhere, and it goes to the pharmaceutical industry, the hospital industrial complex, and the ruling class.

And so with Covid shots, what we have is — picture a middle-aged woman in Orange County, California, who gets a Covid shot and then she gets myocarditis. So now she has to do regular appointments with the cardiologist. She’s in and out of the hospital, she’s sick all the time. So over the course of the next five to ten years of her life, her health care costs are going to be in the range of about $2 million. And that all goes to Pharma, doctors, and the pharmaceutical industrial complex.

If that same woman was enslaved in a gold mine in South America, you could only get about $20,000 worth of labor out of her — the most if you worked her to the bone. And then she would, you know, eventually, perish. The old model of colonialism, right? But in five to 10 years in the U.S. you can squeeze $2 million out of this one person through iatrogenic injury, through a Covid shot that causes myocarditis that sends her in and out of the hospital for 10 years of treatment. And so the insurance company pays, the government pays, she mortgages her house, her family pays, it extracts all wealth out of her and her family, and then after 10 years, the pharmaceutical industry allows her to perish.

So the crisis that we’re in right now — and why we’re all just traumatized all the time — is that western allopathic medicine has become a machine to extract wealth out of the middle class, working class, and lower classes in the United States to enrich the pharmaceutical industry and the ruling class through iatrogenic injury. That’s the crisis that we’re in right now. And it was already happening with autism and other chronic illnesses in children before, and then it just blossomed in size during the Covid epidemic, and the response, and the junk science Covid shots.

You can watch the full “Injured America” panel discussion (here) starting about the 58 minute mark.

Further reading:

Did liberalism fail? (my first essay on biological colonialism).

What we are up against (a short case study of the costs of one Covid vaccine injury)

Working definition:

Biological colonialism: the ruling class strategy of using iatrogenic injury to extract wealth from the middle and working classes in the U.S. and throughout the developed world. Also called vaccine colonialism and iatrogenic slavery.

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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Then this past weekend a curious thing happened. On Saturday (October 18, 2025) the NY Times published “A Furious Debate Over Autism’s Causes Leaves Parents Grasping for Answers.”

The story follows two families dealing with autism interspersed with quotes from various mainstream autism “experts.” It conforms to the standard paint-by-numbers script — ‘autism a mystery; it couldn’t possibly be caused by vaccines, Tylenol, or food dyes; Robert Kennedy Jr. is terrible;’ etc. And then, out of nowhere, the NY Times reporters (Gina Kolata and Azeen Ghorayshi) demolished the official genetic narrative:

But genetic mutations still only explain about 30 percent of cases, typically those with the most severe forms of the disorder.

So, not 100%, not half, not even a third of autism cases are genetic. That’s a MASSIVE paradigm shift. Next:

Dr. Audrey Brumback, a pediatric neurologist at the University of Texas at Austin, said she offers genetic testing to most of the patients she diagnoses with autism even though, as she cautions the parents, a relevant genetic mutation will be found in only one out of four cases.

One out of four is 25%, so they’re already backing away from the 30% claim. And THEN:

A landmark publication in 2007 showed that children with autism were much more likely to have so-called de novo mutations, spontaneous mutations that were not present in their mother’s or father’s genome.

Oh, so these children are NOT inheriting these genes from their parents (heritability is always what’s been implied by the multibillion dollar search for the mythical ‘genes for autism’). Instead these are de novo genetic mutations that are only found in the child with autism.

Do you know what else causes de novo genetic mutations? TOXICANTS.

That narrows the possibilities down considerably. Autism is not genetic — that’s not me talking now, that’s the NY Times. The most likely toxic exposures are from vaccines, SSRIs, Tylenol, pesticides/herbicides/fungicides, fire retardants, chemicals in plastics, EMF/RFR, and pollutants in our air, water, soil, and food — all the toxicants that I reviewed in my 2019 doctoral thesis.

So I figured out and published the definitive systematic review of the autism causation literature six years ago. My reward was to be hunted, censored, and economically blacklisted. The Washington Post, Guardian, BMJ, Springer/Nature, USA Today, Reuters, AP, Vice, and Politico have all published hit pieces on me. They never engage with my actual work, they never present contrary data, and all are engaged in racketeering on behalf of the pharmaceutical industry. I stood my ground and fought back by telling the truth and citing the relevant data. Now the paper of record has abandoned the genetic narrative which opens the door for a thorough examination of the role of toxicants in autism causation.

We are winning this debate. The official narrative is crumbling before our eyes.

I doubt the NY Times reporters even realize what they’ve done. When a paradigm shifts it’s not even necessarily a conscious choice, people just feel the overwhelming gravitational pull of the new narrative.

The people at the Simons Foundation, even though they are quoted favorably in the article, will be none too happy with this development. They won’t be able to win the Nobel Prize in Medicine once everyone realizes that autism is not genetic. Presumably their staff are on the phone right now calling for retraction of all of the evidence that reveals the multibillion dollar autism genetics research grift.

And the pharmaceutical industry will not be happy either. The heads of GSK, Merck, Sanofi, and Pfizer have likely instructed their representatives to deal with the NY Times editors who allowed this information into print. This crack in the official narrative is so enormous that I would not be surprised if the pharmaceutical industry resorts to dirty tricks to try to change the narrative and distract the public in the coming days.

But the genie is out of the bottle — autism is not genetic. Our task is to just keep telling the truth, one difficult conversation at a time, until we stop the autism epidemic.

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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[Transcript]

Autism is a political economy problem. These are all political economy problems. So let me explain how this works.

Thus far, government has failed in response to the autism epidemic because of regulatory capture. Rather than protecting public health, regulators have advanced the interests of the pharmaceutical industry. That’s pretty straightforward.

Science and medicine have failed in response to the autism epidemic because of epistemic capture. And what I mean by that is that the pharmaceutical industry has captured every step in the knowledge production process in science and medicine.

Big Pharma controls what is studied, how it is researched, and what qualifies as evidence. Now this capture permeates every level of the system:

• Medical school textbooks and curricula are influenced by financially conflicted academics.

• Universities and department chairs hold substantial pharmaceutical ties.

• Most clinical trials are conducted by for profit contract research organizations in China and the Third World.

• A large share of scientific journal articles are ghostwritten.

• The pharmaceutical industry spends over $27 billion annually on drug promotion and continuing medical education.

• Standards of care are authored by conflicted physicians.

So from the first day of medical school to the final years of practice, doctors live inside an epistemic bubble engineered by the pharmaceutical industry to increase its profits.

Senator Blumenthal and Dr. Scott only pay attention to captured science — science that’s controlled by the pharmaceutical industry.

The correct answers, the best science, is happening outside of that epistemic bubble.

The entire system of knowledge production in science and medicine needs to be overhauled to liberate it from the biases and distortions imposed by the pharmaceutical industry.

So just to wrap up… an estimated 115,000 children develop autism every year in the United States.

That means that 315 children develop autism every day in the U.S.

Now if Dr. Sally Ozonoff’s work is correct — she’s at UC Davis — she shows that 88% of autism cases are characterized by regression. So if she’s right about that, and I think she is, that means that 277 children regress into autism every day in the United States.

Regression suggests an acute toxic exposure, not genetics, not better awareness, an acute toxic exposure, which means that most cases of autism are preventable.

Autism is not a medical or scientific mystery. We know beyond a reasonable doubt that toxicants — mostly from vaccines and about a dozen additional toxicants are causing autism.

If we repeal the 1980 Bayh-Dole Act, the 1986 National Childhood Vaccine Injury Act, and the 2005 PREP Act, that would remove the structural incentives that created the autism epidemic and the chronic disease epidemics in this country.

Thank you.

You can watch the full hearing on The Highwire.

Chapter 5 of The Political Economy of Autism provides all of the receipts on the role of regulatory and epistemic capture in the autism epidemic.

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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As expected, midway through the hearing Senator Blumenthal challenged Mr. Siri with the “You’re not a doctor” nonsense. And Mr. Siri hit that pitch so far out of the park that it’s still sailing!

Then Senator Blumenthal searched for conflicts of interest in connection with Mr. Siri and that went nowhere because there are none.

Next, Senator Blumenthal directed his attention at me.

He started with the “You’re not a doctor” thing. I was ready for that.

Then, it seems that Senator Blumenthal’s senior committee staffer, Jen Gosar, had done some opposition research and found a mean tweet that Senator Blumenthal wanted to use to paint me as some sort of extremist.

The problem for Senator Blumenthal was that my tweet was pretty straightforward — calling for Nuremberg 2 trials to deal with the crimes of the Covid era (which is what any reasonable person should want). So Senator Blumenthal had to embellish and try to put words in my mouth to distort the tweet to match his agenda.

Prior to the hearing I had done extensive background research on the discursive rules (both written and unwritten) of the Senate. And they’re completely fascinating. One must be respectful at all times. One must focus on the contents of the argument and not the person. And as a sworn witness, I had an obligation to be responsive to any Senator’s questions even if I didn’t like them — evasion or defensiveness is frowned upon. Basically one is expected to assume that everyone involved wants what’s best for the country even when we disagree.

Also, I had written in my notes, “Always try to find the humanity in the other person.” There are parts of Senator Blumenthal’s career that I respect. For example, as Attorney General in Connecticut in the 1990s he did great work on the Master Settlement Agreement with the tobacco industry that secured hundreds of billions of dollars to treat smoking-related disease.

So when he came after me for my mean tweet, you can see me trying to be respectful even though I thought he was off base.

I started with one sentence, “I believe that we are in the midst of one of the greatest crimes in human history.”

And then just tried to build my logic from there and land as many factual points as possible before getting cut off.

Also I was genuinely trying to understand why he was not demanding accountability in light of these enormous crimes against humanity. (Unfortunately he never bothered to explain his illogical anti-human position.)

The whole exchange was fraught. It’s not fun having a U.S. Senator try to mischaracterize me or my work.

However something about this exchange has captured the public’s imagination. Online my responses to Senator Blumenthal’s questions have generated several millions views. In the comments, many people I’ve never met expressed gratitude that I plainly and calmly spoke truth to power. Others noted that this is one of the first times that they have seen anyone demand accountability, in an official Senate hearing, for the cover up of the autism epidemic and the crimes of the Covid era.

So perhaps this will build into a tidal wave of demands for accountability.

I’ve broken my reply into two clips to make them more shareable.

Reply 1

I believe that we are in the midst of one of the greatest crimes in human history.

We have a product being injected into children 70+ times over the course of their development that’s never been tested against a proper saline placebo.

Over the course of that time period (1970 – 2025), chronic illness in this country has gone from 10% of children having one or more chronic conditions to now more than 50% of children having one or more chronic conditions.

Secretary Kennedy in the hearing that was last week said — the latest data from the CDC says that 76% of Americans now have one or more chronic conditions.

And I believe that lots of these chronic conditions stem from iatrogenic injury.

We have 3 million children with autism. Back in 1970 the rate was so low that it was essentially zero.

I’m outraged by that and I think every person in this room should be outraged by that.

I don’t know how to say it anymore clearly that we need to change course in this country.

And I’m terribly disappointed by the medical profession. In the social sciences, there’s this term called epistemic capture, which is when the entire knowledge production process becomes captured by one industry (Big Pharma). And that’s what’s happened with science and medicine.

And so I think we need to change course. And I think the people who have covered up the autism epidemic and the epidemics of iatrogenic injury should be held to account for their actions.

Reply 2

The state, however you define that…

The military, CDC, Tony Fauci, Ralph Baric at the University of North Carolina…

Created a weaponized virus.

Correct?

Gain a function research.

They contracted it out to China and it caused a pandemic around the world once it was released.

The government created a weaponized virus that then got out and caused a global pandemic.

When are we going to have accountability for that?

I genuinely don’t understand why government officials are allowed to engage in gain of function research [and then not be held to account for their actions].

[Senator Blumenthal]

I’m not putting words in your mouth, I’m just quoting your words.

[Toby Rogers]

I would like to have accountability for the crimes of the Covid era and I’d like to have accountability for the fact that the CDC has known since 1999 that vaccines cause autism and they’ve covered it up for 26 years.

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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[Toby Rogers]

In Ph.D. programs, you have to read original sources and you have to define terms. Let’s be crystal clear about the definitions of these terms, because the fate of the Republic depends on getting these definitions right and Dr. Scott is playing fast and loose with these definitions. So let’s be crystal clear about what we mean.

Inert should mean that the substance does not cause a chemical or biological reaction in the body. When supporters of the status quo use the word inert, they can mean just about anything. Paul Offit routinely calls mercury and aluminum inert, even though they are known neurotoxicants. Philippe Grandjean and Philip Landrigan are the best two toxicologists in the world. They published a study in 2014 that says both aluminum and ethylmercury are known neurotoxicants [see Supplemental webappendix]. But the supporters of the status quo say that these things are safe, and they’re not, they’re absolutely not.

In the context of vaccines, placebo should mean saline as verified by independent third party testing. That’s NOT what the supporters of the status quo mean when they say placebo. The fact is the FDA has no regulations concerning the contents of placebos [see Beatrice Golomb 1995 and 2010]. So manufacturers can put whatever they want into the comparator intervention and can still call it a placebo by law. Furthermore, scientific journals have no regulations concerning the contents of placebos. Sometimes the manufacturers disclose them in connection with the study and about two-thirds of the time they do not [see Golomb 2010].

And a double-blind randomized controlled trial should have two groups — a group that receives the vaccine, that’s the treatment group, and a completely unvaccinated group given a saline placebo, that’s the control group. That’s not what the supporters of the status quo mean when they say randomized controlled trial. They compare two groups, but one group gets the new vaccine and another group gets a shot full of aluminum adjuvants. Or they compare a new shot to an older shot. But the one thing they never do is to compare a completely unvaccinated group with a vaccinated group because everyone knows that such a trial would show harms.

So if you go through all seventeen hundred and four trials in the database that Dr Scott has put together, as Aaron Siri has done, you’ll find that the inert ingredients are not inert, the placebo is not saline, and the randomized controlled trial does not have a completely unvaccinated control group.

And we know that my assertion here is correct because on page nine of his written statement, Dr. Scott states that “vaccinated versus unvaccinated studies are especially prone to bias.” It’s hard to imagine a more Orwellian statement! Up is down, left is right, dogs are cats, and, according to Dr Scott, a proper vaccinated versus unvaccinated study is “unethical.” That’s why we’re in this mess. That’s why we have an autism and chronic disease epidemic in this country.

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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[Toby Rogers] I want to add to this debate. I watched every single meeting of the Advisory Committee on Immunization Practices and the Vaccines and Related Biological Products Advisory Committee in 2021, 2022, and 2023 when all these Covid shots were being authorized for use in this country.

And after a while, the CDC’s own research showed that the protection from the vaccine, if any, was between months two and six, and by six months it showed negative efficacy.

So I’m watching the hearings on my computer screen at home. I’m yelling at the screen… The Covid shots have negative efficacy after six months! Tell me how a shot with negative efficacy is saving lives!? And it has the worst side effect profile of any vaccine in human history. So how exactly is a vaccine with the worst side effects and negative efficacy saving lives? That’s a preposterous claim!

What ended the Covid pandemic was the Omicron variant that was more transmissible but less lethal. The vaccine? How many people it helped? I think it’s an open debate. It could be a net negative.

[Aaron Siri] Well maybe we can look at the clinical trial data in which 21 people died in the vaccinated group and 17 died in the placebo group.

[You can watch the full three-hour event here.]

This is the four-year anniversary of my Substack and my 300th article! Thank you to everyone who has been a part of this journey!!! 🎉🥳🎊

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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On July 4, 2015, my then-partner’s son was diagnosed as being on the autism spectrum. I was in a Ph.D. program in Political Economy at the University of Sydney where I had access to almost all current scientific and medical journals. I wanted to better understand what was happening so I went to the CDC’s webpage on the causes of autism. As a Ph.D. student I was trained to focus on primary source documents, so I read all of the references in their footnotes.

To my surprise, I quickly discovered that the CDC’s narrative did not add up:

• Claims that autism is genetic don’t make sense because autism prevalence was rising too fast — there’s no such thing as a genetic epidemic.

• Then the CDC blamed valproic acid, a treatment for epilepsy that is contraindicated in pregnancy, and thalidomide, which was never approved for use in the U.S.

• Finally, the CDC pointed to advanced parental age; but the odds ratios were modest and the increase in the proportion of older parents is insufficient to explain the surge in autism prevalence.

Furthermore, the cost of autism was already in the hundreds of billions of dollars a year in the U.S. and yet government was not responding with a sense of urgency.

I changed my doctoral thesis topic to “The Political Economy of Autism” and spent the next four years reading and analyzing nearly everything that has been written on autism prevalence, causation, and cost.

In 2019, my thesis passed rigorous external peer review. It’s now in the top 10 of the most downloaded doctoral research papers in the history of the University of Sydney.

Since then I’ve continued my research with Children’s Health Defense, as an independent journalist, and as a Fellow at Brownstone Institute.

Here are the facts:

In 1970, the first autism prevalence study in the U.S. found an autism rate of less than 1 in 10,000 children [Treffert, 1970].

According to a study by the EPA [McDonald & Paul, 2010], sometime around 1987, the autism rate in the U.S. began to skyrocket.

The most recent report from the CDC showed that 1 in 31 eight-year-old children in the U.S. in 2022 were on the autism spectrum [Shaw et al. 2025].

That’s a 32,158% increase in the last 52 years.

Two massive studies from the best epidemiologists in California show that changes in diagnostic criteria only explain a small fraction of the rise in autism prevalence [Byrd et al. 2002 and Hertz-Picciotto & Delwiche, 2009].

There are 22 studies that claim that vaccines don’t cause autism. None of these studies have a completely unvaccinated control group. So unfortunately, if you want to understand what’s causing the autism epidemic, these studies are of no use.

Then there are five large genetic research projects — AGRE, SSC, ASC, MSSNG, and SPARK. Together they have produced 501 published papers. The search for “the gene for autism” has consumed over $2.3 billion dollars and researchers have almost nothing to show for it because genes don’t suddenly create epidemics — the human genome just doesn’t change that fast.

Then there are four large epigenetic research projects (so, genes and the environment) — CHARGE, MARBLES, SEED, and EARLI. Combined they’ve produced 437 publications that look at the effects of:

• air pollution

• pesticides

• fluorinated substances

• PCBs

• nutritional factors

• flame retardants

• maternal metabolic conditions [obesity and diabetes]; and

• volatile organic compounds.

None of these studies control for vaccines as a possible covariate or confounder, so it’s impossible to know the true impact of these variables.

The critical missing piece in autism research is vaccinated vs. unvaccinated studies.

Thankfully there are now six good studies that we can rely on. Unfortunately, these studies have been systematically suppressed and ignored by the mainstream media and the medical establishment.

Two studies by Gallagher and Goodman [2008 & 2010] show that the birth dose of the hepatitis B vaccine significantly increases autism risk.

Three studies by Anthony Mawson (2017a, 2017b, and 2025) confirm that vaccination increases the odds of developing autism by at least 4.2-fold.

Preterm birth, coupled with vaccination increases the odds of neurodevelopmental disability by more than 12-fold compared to preterm birth without vaccination [Mawson et al. 2017b].

And finally, a study by Hooker & Miller, published in 2021, found that:

• Vaccination increases autism risk 5-fold.

• Vaccination in the absence of breastfeeding increases autism risk 12.5-fold.

• Vaccination in addition to C-section birth increases autism risk 18.7-fold.

After conducting this systematic review of 1,000 studies my belief is that the autism and chronic disease epidemics are primarily caused by toxicants — mostly from vaccines and about a dozen additional toxicants. If we stop exposing children to these hazards in the first place that would stop the epidemics of chronic illness in children. Now we must summon the political will to act.

Thank you.

Video courtesy of The Highwire:

You can also watch the hearing on:

U.S. Senate, Permanent Subcommittee on Investigations website

CHD-TV

C-Span

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know your thoughts on the hearing.

As always, I welcome any corrections.

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Here are the facts for anyone who wants to read them:

Jessica Steier runs a science-for-hire company, “Unbiased Science.” She uses a number of pass-through organizations to launder contributions from large pharmaceutical and chemical companies. However, one can still figure out a lot of her funders (see article on “Unbiased Science Podcast” in SourceWatch). Steier advises an infant formula company and is an affiliate for a company that makes monosodium glutamate (MSG). Her podcast has taken money from 3M, Procter & Gamble, Pfizer, Johnson & Johnson, Novartis, Moderna, and CSL Seqirus (a flu vaccine manufacturer).

Steier is cartoonishly evil. From SourceWatch:

Steier’s Unbiased Science Podcast:

• Described the herbicide glyphosate as “safe for use”

• Declared polytetrafluoroethylene (PTFE) in Teflon to be “non-toxic to humans”

• Called the Environmental Working Group Dirty Dozen list of produce with the most and least pesticide residues “a fear-based marketing ploy”

• Claimed GMOs are “safe,” “nutritious,” and “beneficial to consumers, producers, and the environment” and

• Called hydrogenated oil “a safe dietary fat.”

The Unbiased Science Podcast recorded two episodes on organic food and farming in December 2022 and January 2023 in which they argued that organic pesticides are more harmful than synthetic pesticides used in chemical farming...

Andrea C. Love [Steier’s co-host] defended the artificial sweetener aspartame as “safe,” said in an interview that she has “at least one diet soda a day,” and the Podcast posted on Instagram that “aspartame does not pose a health risk to humans, cancer or otherwise, especially at levels we would consume.”

Love and Steier were critical of the International Agency for Research on Cancer’s ranking of the chemicals considered possibly carcinogenic to humans in 2023.

SourceWatch provides even more evidence of Steier’s toxic sophistry here.

For those who are new to these topics, mountains of evidence from The Defender, Beyond Pesticides, and Moms Across America, among others, show why all of Steier’s claims listed above are junk science.

Nearly everything Steier writes in her “Guest Essay” on autism is demonstrably false. For example, Steier:

• Thinks mercury and aluminum in vaccines are fine even though they are known neurotoxicants (see Grandjean and Landrigan, 2014, Supplementary appendix).

• Omits the fact that Mark, Anne, and David Geier sued the Maryland Board of Physicians and won (and then a higher court retroactively granted “absolute immunity” to this private board even though the Maryland legislature never gave it that right).

• Has apparently not read any of the 55 autism prevalence studies in the U.S. since 1970, so she is oblivious to the fact that autism rates have increased 32,158% over that time period.

• Seems unaware that a Danish study she cited favorably recently issued a correction after they discovered, post-publication, 136% more neurodevelopmental events, including autism and ADHD, that changed their research findings.

• Has never read, or just plain ignores, the six vaccinated vs. unvaccinated studies that show that vaccines significantly increase autism risk (see summaries in Rogers, 2025).

Science-for-hire companies will say or do anything for money. Steier’s company, “Unbiased Science,” is relatively new. However, it uses the same playbook developed by other notorious science-for-hire firms, including Gradient, Exponent, and Ramboll. They are often referred to as “rented white coats” (see discussion in Rogers, 2019). Anyone citing Steier as a “public health expert” has no idea what they are talking about.

The NY Times devoted considerable resources, including two graphic designers and prominent placement online and in the Sunday print edition, in the attempt to make this trashy hit piece look presentable to its readers. The NY Times’ failure to disclose Steier’s extensive conflicts of interest and its refusal to publish critical comments in connection with this “Guest Essay” make me wonder if this was a paid advertorial at the behest of a pharmaceutical company.

The autism epidemic is a matter of enormous national importance. Yet everything that the NY Times publishes on autism is an attempt to cover up the causes and protect the powerful industries that are culpable. Unfortunately, in the midst of this crisis, the NY Times has abandoned its role as “the newspaper of record” and is now a criminal syndicate that is endangering the health of all Americans.

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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As I showed in my two previous articles, the exclusive focus on double-blind, randomized controlled trials (RCTs) by Evidence-Based Medicine is ridiculous because:

• There are no proper RCTs of vaccines. Pharma and regulators do not want any data that might contradict their biases and interfere with their profits.

• The Contract Research Organizations (CROs) that conduct clinical trials (usually in China and the Third World) work at the behest of the pharmaceutical industry and use a wide variety of tricks to give their clients any results they want.

• RCTs perform no better than other types of studies according to the former head of the MHRA in the U.K. (Michael Rawlins, 2008) and the former head of the CDC in the U.S. (Thomas Frieden, 2017).

• Even Bradford Hill, one of the key figures in the development and popularization of modern RCTs, cautioned against overreliance on them, saying, “Any belief that the controlled trial is the only way would mean not that the pendulum had swung too far but that it had come right off the hook” (Hill, 1966).

During World War II, RCTs showed that antibiotics can treat some bacterial infections. By the early 1970s, the pharmaceutical industry figured out how to rig RCTs to produce any results they wish. And so now RCTs are just a way to give the appearance of safety and efficacy to toxic, useless, and deadly drugs.

We can and must do better than this, particularly when it comes to autism research.

II. Activist-Initiated Participatory Science and Samizdat literature

It turns out that independent autism research is the best example of Activist-Initiated Participatory Science in history — but almost none of the mainstream academics in this field will talk about autism because they don’t want to lose their jobs.

From my doctoral thesis:

According to Moore (2006), Activist-Initiated Participatory Science has a long history going back to the social movements of the 1960s and 1970s that were alarmed by the role of scientists in the chemical and weapons industries. Scientists were both targets of and sometimes participants in these activist social movements. Activist-Initiated Participatory Science has often been a key feature of anti-toxics/anti-pollution campaigns [Brown, 1992; Bullard, 1994; Lichterman, 1996; and Allen, 2003] and health-related social movement groups [Morello-Frosch, 2006]. Many of these studies could also be considered examples of “popular epidemiology” which is defined as “the process by which laypersons gather scientific data and other information, and also direct and marshal the knowledge of other experts in order to understand the epidemiology of a disease” [Brown, 1992].

As I will show below, in the autism debate some of the most insightful data are from:

• parents’ groups;

• censored, banned, and blacklisted academics and doctors;

• independent and foreign scholars;

• court proceedings;

• registries and testimonials; and

• documentaries.

Historically, this was called the “gray literature” in academia and library sciences (neither the mainstream “white literature” nor the completely inaccessible classified “black” documents). But this term does not do justice to the context in which this groundbreaking autism research is being produced. A more fitting description is Samizdat literature. From Grok:

Samizdat literature refers to the clandestine production, reproduction, and distribution of written works, often political, literary, or dissident in nature, that were banned or censored by authorities, particularly in the Soviet Union and other Eastern Bloc countries during the 20th century. The term comes from Russian, meaning “self-published” (sam = self, izdat = publishing), and typically involved individuals or small groups secretly copying and sharing manuscripts, poems, essays, or books using typewriters, carbon paper, or other rudimentary methods to evade state censorship.

Independent autism research is being done amidst the most extreme propaganda and censorship regime in history. Elected officials, regulators, the media, and the entire knowledge production process in science and medicine are captured by and work at the behest of the pharmaceutical industry. The fact that any independent research is produced at all is remarkable. The fact that this independent autism research often attracts world-class scholars who are willing to risk everything to tell the truth is a testament to the indomitable human spirit.

Nearly all of the studies that I discuss in this article are censored by the search engines and ignored or covered up by public health agencies and medical associations. But this article will help you to find many of them.

There is also a substantial body of proprietary data that would likely demonstrate autism causation and we’ll need to find creative ways to access those data in the years to come.

III. Ginger Taylor’s database of 237+ autism studies shows mechanisms of causation

Autism parents approach the autism data differently from mainstream academics. Autism parents start with the question: “How can I help my child get better (regain speech, have fewer seizures, have less pain)?” Mainstream academics approach the autism data with visions of publishing and career advancement — and the knowledge that if they ask too many forbidden questions they’ll get fired.

Many autism parents had high level training in statistics, science, or medicine before their children regressed and that serves them in good stead when they are reading late into the night trying to figure out what happened. Also, autism parents have a tremendous advantage in that they can try treatments with their child to detox, improve gut health, reduce inflammation, etc. and see which ones work.

In 2002, Ginger Taylor gave birth to a healthy boy. At 18 months he regressed following a DTaP shot. She had gone to a prestigious graduate school so she knew how to read scientific studies. She began by reading vaccine inserts. In the early days of blogging she started Adventures in Autism to share what she was finding and learning from others. In 2005, Evidence of Harm was published and became a NY Times bestseller. Ginger went to the references and found 15 to 20 papers, mostly on mercury and autism. In the early 2000s lots of autism parents shared studies with each other on Yahoo groups (when those were a thing) and then later on Facebook. Ginger collected and curated these studies and posted them to her website.

She started with about 60 studies linking vaccines and autism. These tend to be mechanistic studies — e.g. how do vaccines impact mitochondria and how does mitochondrial damage relate to autism? By 2010 she had gathered 100 studies and distributed them through Scribd (a digital library site that’s good for sharing PDF documents). By the start of Covid she had gathered 160 papers on vaccines and autism. And then waves of parents started questioning the childhood schedule so she moved her collection of studies over to HowDoVaccinesCauseAutism.org.

Today, Ginger has 237 studies covering all aspects of autism causation including adjuvants, the different types of vaccines, and the different facets of the autism experience from encephalopathy to seizures to cytokine storms. As she told me on the phone, “If you want to understand the relationship between vaccines and autism, these are the papers you need.” These are the studies that NIH, FDA, and CDC pretend don’t exist but they are all there in black and white with excerpts, abstracts, and links to the full study in every case. See for yourself:

https://howdovaccinescauseautism.org/

IV. Parent testimonials are data

One of my “red pill” experiences during my Ph.D. studies was reading the website followingvaccinations.com. I’m grateful to investigative journalist Dan Olmsted (1952-2017) for writing the article that alerted me to the site.

Set up by South African warrior mom, Joan Campbell, Following Vaccinations allows parents to tell the story of their child’s vaccine injury (and autistic regression is a widely-reported outcome). There are now thousands of parent testimonials on the site. It’s impossible to read for more than a few minutes without breaking down crying. The site functions as an autism and vaccine injury registry. Government could easily set up something similar as a sort of Autism Truth Commission but they are too captured and cowardly. I imagine that most people who read the testimonials on followingvaccinations.com will never vaccinate their children again.

Children’s Health Defense has organized a number of similar efforts that are brilliant:

• The People’s Study includes several hundred video testimonials about vaccine injury.

• The Dedications page includes the names of 1,300 people who signed the Vaxxed Bus to indicate that they or a family member is vaccine injured.

• I also really like the Hear This Well: Autism Parents Speak campaign.

Other efforts along these lines include:

• The Highwire’s Dear Moms campaign.

• The #WeDid hashtag campaign on Instagram and Twitter by Freedom Keepers.

Were it not for massive censorship on YouTube, there would be hundreds of thousands of these autism and vaccine injury testimonials for the public to watch. We should bring a class action lawsuit against YouTube — and ask Secretary Kennedy to join our effort as well — to get access to these censored testimonials of vaccine injury. Censorship literally kills: the CEO of YouTube, Susan Wojcicki, died at 56 as a result of turbo cancer following Covid vaccination. Had she allowed free speech she could have learned the information that likely would have prevented her premature death.

V. Official reports are data:

OpenVAERS.com contains 2.7 million reports of vaccine injury. You can search by keyword, symptom or vaccine type.

The Informed Consent Action Network has obtained hundreds of thousands of pages of government public health documents via the Freedom of Information Act. They are building a searchable database of these documents so that independent scholars can use them. Sign up at icandecide.org to be notified of further developments.

Siri & Glimstad LLP, on behalf of Public Health and Medical Professionals for Transparency, successfully sued the FDA in 2021 to force the agency to release Covid-19 vaccine data. The Pfizer and Moderna documents are now available on the PHMPT website (phmpt.org) and the Pfizer documents are also available on the ICAN website (icandecide.org/pfizer-documents). Naomi Wolf also led a group of thousands of independent scholars to analyze the documents. They produced a book, The Pfizer Papers, and lots of articles and interviews (Dailyclout). While these documents are focused on a wide range of different vaccine injuries, Covid-19 vaccines may increase the risk of autism owing to immunoexcitotoxicity (see Blaylock, 2025).

VI. Books by suppressed, banned, and censored authors contain a treasure trove of great studies

Everyone needs to read Dissolving Illusions: Disease, Vaccines, and the Forgotten History (Humphries and Bystrianyk, 2nd edition, 2024). It’s simply the best thing that’s ever been written about vaccines and it includes thousands of sources.

Miller’s Review of Critical Vaccine Studies: 400 Important Scientific Papers Summarized for Parents and Researchers (2016) is essential reading for survival in this era.

How to End the Autism Epidemic by J.B. Handley (2018) is magnificent. In a just world it would have won a Pulitzer Prize.

The Age of Autism by Dan Olmsted and Mark Blaxill (2010) was one of my red pills and provides a best-in-class history of the autism epidemic.

The 192 peer-reviewed papers authored or co-authored by Christopher Exley on the dangers of aluminum are world-class.

The 37 studies in Vaccines and Autoimmunity by Shoenfeld, Agmon-Levin, and Tomljenovic (Eds.) (2015) are groundbreaking. There’s a high degree of overlap between autism and autoimmune disorders but the mechanisms of action are undertheorized because government doesn’t want to fund studies that would hurt the interests of large corporations that are the biggest donors to political campaigns.

Independent scholar Forrest Maready has written five of the best books ever published on vaccines and autism and each includes hundreds of sources:

• The Moth in the Iron Lung: A Biography of Polio (2018);

• Crooked: Man-made disease explained (2018);

• Unvaccinated: Why growing numbers of parents are choosing natural immunity for their children (2018);

• The Autism Vaccine: The Story of Modern Medicine’s Greatest Tragedy (2019); and

• VaxBaby: The Curious Parent’s Guide to Pediatric Vaccines (2019).

Turtles All the Way Down (O’Toole & Holland, Eds, 2022) is a helpful overview of the entire debate and includes over 1,200 sources with links that will take you right to each study.

The preponderance of evidence supports the claim that vaccines cause autism.

Of course there are many more great books on this topic. Please add your favorites in the comments below.

VII. Ashley Everly’s Vaccine Guide

Warrior mom Ashley Everly has built a 2170-page binder of relevant information to help people make informed decisions about vaccination. The content is free on her site Vaccine.Guide and includes:

• relevant laws and court decisions;

• vaccine schedules and inserts;

• 34 studies on vaccine ingredients, excipients, and contaminants;

• 14 studies on asymptomatic transmission and shedding;

• 23 studies on vaccine effectiveness, outbreaks in vaccinated populations, and the limits of herd immunity;

• 39 studies on whether vaccines are necessary and effective alternative treatments;

• 58 studies on adverse reactions; and

• 26 documents on misconduct and financial incentives/conflicts of interest.

It’s an astonishing collection. You can download the documents piece by piece or download all of them in one PDF.

Resources including Vaccine Guide are another reason warrior moms and dads are fearless in the public square. We’ve usually read thousands of pages of original studies and we’re going up against people who have read no original studies and are just parroting Pharma propaganda that they heard in the mainstream media.

VIII. 10,000 news stories collected and curated in Loss of Braintrust

Anne Dachel has built an extraordinary online library of more than 10,000 news stories since 2017 about the autism epidemic. Her site is foundational to any serious understanding of this crisis.

IX. Documentaries are data

Imagine you or someone you love is injured by a vaccine. You could write about it, but no mainstream magazine would publish it because they are captured by the pharmaceutical industry. I suppose you could go to medical school or get a Ph.D. to prove your case but scientific journals are also captured so the odds of getting published are close to zero. In the absence of other venues, a lot of people who have been afflicted by the Great Poisoning have made documentary films to tell their story.

Some of the best “vaccines and autism” documentaries, news reports, and films include:

Vaccine Roulette (1982, WRC-TV)

The first in-depth televised report on the mercury-autism link, showing parents whose toddlers slipped away after vaccinations at 18-month. Grainy but still powerful after all of these years.

The Greater Good (2011)

Award-winning portrait of injured families — Gardasil paralysis, DPT seizures, and a baby who died post-Hep B — balanced against Pharma talking heads who end up incriminating themselves.

Bought (2014)

Overlays Big Pharma campaign donations with VAERS injury graphs and ends with an ex-Pharma rep admitting they buried negative trials. You can stream Bought on Brighteon (thanks to reader Martin Vandenberg for finding it).

Trace Amounts (2014)

One man’s mercury-poisoning odyssey turns into a forensic deep-dive on thimerosal, complete with FOIA-obtained CDC emails and footage of congressional hearings the mainstream media ignored. You can stream Trace Amounts on the Internet Archive.

Vaxxed: From Cover-Up to Catastrophe (2016)

An investigation into how the CDC destroyed data from a 2004 study that showed a link between the MMR vaccine and autism. Features interviews with the legendary warrior mom Dr. Sheila Ealey (1960–2024).

Vaxxed II: The People’s Truth (2019)

A road-trip across America in the Vaxxed Bus collecting thousands of injury stories; raw, unfiltered, and impossible to dismiss.

1986: The Act (2020)

This is a feature film but the information shared by the characters is factual. It explains how the 1986 National Childhood Vaccine Injury Act gave Pharma legal liability protection and created the no-fault vaccine court that shields this heinous industry.

Vaxxed III: Authorized to Kill (2024)

Children’s Health Defense embarked on a nine-month journey across America, gathering powerful testimonies from vaccine injured people and their families. Their interviews range from mothers and fathers to teenagers, families, medical professionals, whistleblowers, lawyers, and people from all walks of life.

I know there are many more excellent documentaries on this topic. Please add your favorites in the comments below.

X. Cost studies are data

I’m intrigued by the “societal cost of autism studies” because they are an objective indication of the size and scope of the autism epidemic and a measure of the policy challenge ahead (that is currently being ignored by government). Also, the Pharma goons decided to censor the best cost study ever produced (that I co-authored) so that lets us know that we are right over the target.

There are now seven good “societal cost of autism studies”:

• Jarbrink and Knapp, 2001;

• Ganz, 2007;

• Knapp et al., 2009;

• Buescher et al., 2014;

• Leigh & Du, 2015;

• Cakir et al., 2020;

• Blaxill, Rogers, & Nevison, 2023.

They all show sharply rising prevalence and cost. On the current trajectory, the U.S. and much of the developed world is facing societal and economic collapse from the tsunami of vaccine injury. Quite literally the only way to save the Republic is to stop poisoning children in the first place. The fact that this is controversial shows the degree of mental capture in our society.

XI. Holland et al.’s (2011) investigation shows that even the Vaccine Court acknowledges that vaccines cause the symptoms of autism

Holland, Conte, Krakow, and Colin (2011) discovered 83 instances where the Vaccine Injury Compensation Program in the U.S. awarded compensation to families of children who developed autism as a result of vaccines. Holland et al. (2011) point out that the table of injuries that can be compensated by the VICP includes encephalopathy and the VICP’s definition of encephalopathy is very similar to the DSM-IV definition of autism (p. 495). In a cruel twist of administrative law, sometimes the Special Masters of the U.S. Court of Federal Claims (aka the Vaccine Court) are willing to grant compensation for vaccine injuries that produce symptoms characteristic of autism so long as the petitioners describe these symptoms as “autism-like” (rather than autism per se) and/or include other co-morbid conditions (Holland et al., 2011). So officially the Court claims that vaccines could not possibly cause autism but in many cases the reality is undeniable.

This was true in the Hannah Poling settlement as well. In the Hannah Poling case (one of the original test cases in the Omnibus Autism Proceedings) the CDC admitted that vaccines cause autism in the presence of an underlying mitochondrial disorder which is the case for a large percentage of people on the spectrum (see discussion of mitochondrial disorders in Handley, 2018). Hannah’s parents were paid $20 million, Hannah was removed from the Omnibus Autism Proceedings (even though the CDC conceded her test cases) and the other 5,600 plaintiffs were denied compensation. This is an example of the cruel Orwellian doublespeak of our current system.

XII. Mountains of relevant data are currently hidden but should be shared with the public via litigation or government action.

In Eastern Europe after the fall of Communism, countries including Poland, the Czech Republic, and East Germany instituted what are called “lustration” laws (from the Latin lustratio, meaning purification). Members of the secret police or Communist Party were removed from government positions. In addition, secret government archives were opened so that the public could see the records that had been kept hidden by the regime. Something similar needs to happen with proprietary autism data that are currently hidden by government and corporations.

Currently all of the records of the U.S. Court of Federal Claims (aka the “Vaccine Court”) are sealed. That means that there are millions of pages of documents — affidavits from doctors and other medical experts, testimony from parents and other family members, medical records, and more — that are not available to independent scholars for research. Sealing these court records serves the interests of the pharmaceutical industry but harms the public interest. Given that we are in the middle of an autism epidemic, this unnecessary secrecy is unconscionable. ALL documents in connection with the U.S. Court of Federal Claims should be made public (either through litigation or executive action by the Secretary of HHS) so that independent researchers can draw their own conclusions. It would be fairly easy to anonymize all of the data. And what we will likely see is that the U.S. Court of Federal Claims is one of the most corrupt institutions in the history of medicine — consistently ignoring a wealth of data proving causation and going out of their way to protect the pharmaceutical industry. The Omnibus Autism Proceedings (involving 5,600 plaintiffs) were wrongly decided and those records must be unsealed as well.

The same thing is true of the British MMR Litigation (involving 1,500 families) — those records are currently sealed and they must be anonymized and released to the public.

Other records of vaccine injury that are currently hidden that must be pried open via litigation or executive action include:

• The Vaccine Safety Datalink (VSD). With nine million records from four U.S. health maintenance organizations, it was taken offline before Robert Kennedy was sworn in as HHS Secretary to keep the data hidden. Access must be restored immediately.

• Medicaid data. 49% of U.S. children (37 million children total) were enrolled in Medicaid or the Children’s Health Insurance Program as of October 2024, according to an analysis of data from the Centers for Medicare & Medicaid Services (AAP, 2025). As the recent Mawson & Jacob (2025) study of Florida Medicaid records shows, independent scholars find patterns in the data that captured scholars refuse to examine.

• Pediatricians’ records. Every mainstream pediatric practice in the U.S. has evidence of crimes against humanity in their files if we could get access to them.

• Insurance company records. Every insurance company in the U.S. has evidence of crimes against humanity in their files if we could get access to them.

• Head Start data. Head Start (pre-K for low-income children) mandates that programs comply with state immunization requirements for enrollment and attendance. In blue states and many red states this means children have to be up-to-date with the CDC schedule in order to participate. Access to anonymized Head State data would likely show rising autism prevalence and regression in children forced to catch up on vaccines.

• Hospital records. Hospitals know who received the hepatitis B vaccine and “vitamin K” shot. They also know who returned later for high fevers, seizures, vomiting, and other symptoms of autistic regression. The U.S. hospital system could easily prove what is causing autism but thus far they have chosen to keep those records secret.

• Databases of military dependents — MHS Genesis, Composite Health Care System (legacy), and TRICARE Claims Data Systems. The children of U.S. service members regress into autism just the same as the civilian population (probably at a higher rate though because of a greater insistence on being up-to-date with the CDC schedule). The U.S. military has those records and they must be released.

• Google search histories. Google has detailed profiles on the search histories of nearly every American that they sell to advertisers. But those search histories would also show the following pattern for lots of children who regressed into autism: Google Maps search for directions to the pediatrician; Google search for fever, incessant crying, seizures; Googling directions to the hospital; Googling autism symptoms. All of that would occur within a few hours or a few days. Quite literally in the Google search history is the record of the autism epidemic for the entire country since Google became the dominant search engine around 2002. All of that data can and should be anonymized before being released.

• The National Security Agency (NSA) monitors every phone call, email, financial transaction, iCloud photo upload, and more in this country. Again, within that database is the evidence that vaccines cause autism. Using AI and other existing tools from Palantir and others, the NSA could very easily prove the case just as I outlined above in connection with Google. They must be ordered to do so. Of course the data can and should be anonymized.

• Facebook censorship records. In 2015 and 2016, Stop Mandatory Vaccination (started by Larry Cook) grew to over 150,000 members. I watched it nearly every day. I saw that lots of parents turned to this group to get advice on their children’s vaccine injuries — sometimes just hours after they happened. Nearly every week there were also SIDS deaths reported to the group by parents trying to understand why their child died suddenly and unexpectedly. Facebook later deleted the entire group without warning. I believe Facebook engaged in racketeering by covering up these injuries and deaths on behalf of the pharmaceutical industry. All of those posts and replies still exist somewhere within the Facebook servers. Facebook must be forced to turn over all of the anonymized records of Stop Mandatory Vaccination and the thousands of other vaccine injury groups that once had pages on their site.

What I am alleging in this section is that the obvious evidence of autism causation runs throughout our society — in databases controlled by government, the military, private corporations, and tech giants. The leaders of these organizations can come forward. Whistleblowers within these companies can perform these searches and save western civilization. Or we can use courts to compel them to do the right thing.

XIII. Conclusion

In my first “Mapping” article I covered about 850 studies and showed the six that stand out as the best — Gallagher & Goodman (2008 & 2010), Mawson et al. (2017A & 2017B), Hooker & Miller (2021), and Mawson & Jacob (2025).

In this article, I’ve covered several thousand more sources including hundreds of studies and a wealth of alternative data sources that provide a comprehensive picture of the autism epidemic in the United States. Together these two articles provide the most comprehensive map of the autism epidemic ever created. Previously I’ve made the case that medical decisions should be made based on the totality of evidence — well, this is the totality of the autism evidence as it stands right now.

A few weeks ago, I read the guidelines for the much-touted new $50 million Autism Data Science Initiative from NIH. The rules of the grants are designed to guarantee that the causes of autism will never be found. They include a misplaced focus on genetics and a specific request for more studies on wearables (I wish I was kidding). Independent researchers (including me!) are barred from even applying.

There is no need for the NIH to conduct further fraudulent studies covering up the causes of the autism epidemic or for the MAHA Commission to produce further reports that will be watered down by Susie Wiles with Pharma lobbyists looking over her shoulder. It’s all right here. We know what is causing autism — the mass poisoning of children, mostly from vaccines and a few additional toxicants. That also means that we know how to stop the autism epidemic (stop poisoning children in the first place). Now we need to summon the political will to implement the obvious and necessary reforms.

Here’s the entire story in one infographic (thanks to the talented designers at OpenVAERs):

You can also download it as a PDF that you can share with friends:

Activist Initiated Participatory Science & Samizdat Autism Literature

136KB ∙ PDF file

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Update, March 7, 2026:

I want to draw your attention to a brilliant new database set up by React-19 that contains 3,751 studies on Covid vaccine adverse events. Next time someone claims that Covid vaccines are safe, please send them a link to this database.

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please add any additional sources of autism data that you know about that I overlooked.

As always, I welcome any corrections.

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In a previous article, I presented ten practical and material criticisms of Evidence-Based Medicine (EBM). But there are even larger metaphysical, ontological, and epistemological problems with EBM. Numerous authors make the case that EBM and evidence hierarchies elide important debates in the philosophy of medicine. In this article I will review seven philosophical debates in connection with EBM and evidence hierarchies including:

1. Hierarchies are not how causation in science is usually constructed;

2. Evidence and interpretation are two different things;

3. The inferential gap may be unbridgeable;

4. Bayesian statistics has long since proven superior to the frequentist statistics relied on by RCTs;

5. Science can never prove hypotheses, only refute them;

6. Actual medical practice is necessarily pragmatic and different from the objectivism of EBM; and

7. Medicine is a practice not a science per se.

1. Hierarchies are not how causation in science is constructed

Several authors have noted that EBM tends to overlook and ignore the contributions of basic science (also called “bench” or “fundamental” science and I will use these three terms synonymously in this section). Bench research is defined as “any research done in a controlled laboratory setting using nonhuman subjects. The focus is on understanding cellular and molecular mechanisms that underlie a disease or disease process” (“Bench research”, n.d.). Merriam Webster’s Dictionary defines basic science as, “any one of the sciences (such as anatomy, physiology, bacteriology, pathology, or biochemistry) fundamental to the study of medicine” (“basic science”, n.d.).

The CEBM evidence hierarchy lists basic science as the fifth level of evidence, below the threshold suggested by Strauss et al. (2005) and others as even worth reading. To be clear, the CEBM and other evidence hierarchies are not excluding bench science entirely from the study of medicine — they are proscribing the consideration of bench science by doctors when they make clinical decisions (presumably others, namely pharmaceutical companies and academic researchers would be free to continue with a more comprehensive approach). Excluding basic science in this way is an odd choice because basic science has always been an essential component of establishing causation.

Bluhm (2005) writes,

[B]ench [laboratory] research and clinical (epidemiological) research are intimately related. The history of epidemiology shows that advances in one of these aspects of biomedical research often depends on advances in the other; this point is particularly clear in the case of infectious diseases but is equally important for understanding chronic disease (p. 538).

Bluhm (2005) argues that EBM should move from hierarchies of evidence to “networks of evidence” in which both epidemiology and lab-based biochemistry work hand in hand (p. 535). It is a fine point as far as it goes, but it strikes me that one could push this idea of networks of evidence even further — to include the subjective wisdom of both doctors and patients as well. I will elaborate on this point later in the article.

Rawlins (2008) writes:

Hierarchies attempt to replace judgment with an over-simplistic, pseudo-quantitative, assessment of the quality of the available evidence.... Hierarchies of evidence should be replaced by accepting — indeed embracing — a diversity of approaches (p. 586).

Goldenberg (2009) argues that the degradation of pathophysiology in evidence hierarchies is unwarranted “as pathophysiology often provides more fundamental understanding of causation and is in no way scientifically inferior” (p. 180).

La Caze (2011) voices alarm that evidence hierarchies overlook the contributions of basic science. As pointed out above, basic science is usually assigned to the lower tiers of evidence hierarchies. While the assignments to the different tiers are rationalized based on reference to “quality” in fact, “proponents of EBM provide little justification for placing basic science so low in EBM’s hierarchy” (La Caze, 2011, p. 96). “Proponents of EBM urge clinicians to base decisions on the outcomes of large randomised studies rather than the mechanistic understanding of pharmacology and physiology provided by basic science” (La Caze, 2011, p. 83).

While it is true that leaders of the EBM movement such as Sackett et al. (1996) mentioned integrating the totality of evidence in early statements on EBM, in practice, evidence hierarchies have become a sorting mechanism for what studies to read (RCTs) and what evidence to ignore (everything else). Contrary to holistic approaches to medicine that recommend evaluating the totality of evidence, in EBM, “evidence from randomised studies is taken to trump evidence from lower down the hierarchy, including evidence from basic medical science” (La Caze, 2011, p. 84):

La Caze (2011), in his defense of basic science, draws attention to an issue that will be explored in greater depth below — the problem of inference from a sample population to a particular patient (La Caze refers to this as the problem of “external validity” and Upshur (2005) below refers to it as the “inferential gap”).

EBM’s account of medical evidence fails to recognise how interrelated the mechanisms of basic science and applied clinical research are. EBM is wrong to treat the different kinds of medical evidence as discrete. The problems of EBM’s account of medical evidence become especially clear when judging the relevance of clinical studies for individual patients. This is the problem of ‘external validity’. External validity is the extent to which the results of a study can be generalised to patients outside of the study, it is usefully contrasted with internal validity. Despite being well recognised, there is precious little in the EBM literature on how the problem of external validity might be overcome. This is because any reply to the problem of external validity relies on interpreting clinical research in light of basic science. EBM is left short because it lacks an account of the relation between basic science and clinical research (La Caze, 2011, p. 89).

The various branches of science and medicine usually work together as an interwoven system so it is strange for EBM to privilege one strand of the system over all others.

Theory, experiment and data are all linked; the basic science that specified, and helps to assess, the models of the experiment are part of the results of applied clinical research (La Caze, 2011, p. 94).... Clinical research may refute basic science, but more often it refines and improves the understanding of how the mechanisms described in basic science are realised in clinical care. Just as basic science alone fails to predict patient outcomes, the statistical findings of clinical research alone fails to give direction on how the results can be applied appropriately. Rather than view basic science and the statistical findings of applied clinical research separately, considerably more progress can be made by recognizing the connections between these sources of evidence (p. 96).

The denigration of bench science is yet another example of how EBM overlooks systems while privileging certain parts and certain actors.

2. Evidence and interpretation are two different things

Upshur and Tracy (2004) point out that evidence itself does not indicate what should be done; the interpretation of evidence is key. But EBM elides this distinction between evidence and interpretation and implies that proper evidence (in their view, RCTs) is dispositive. In the process they smuggle in, without debate, a deterministic philosophy, which runs counter to actual medical practice. Upshur and Tracy (2004) take pains to correct the deterministic view of evidence that has emerged via EBM:

Evidence has distinct properties which are important to note. Evidence derived from clinical studies is provisional, defeasible, emergent, incomplete, constrained (by ethical, economic, and computational forces), collective in nature, asymmetrically distributed across help disciplines, historically limited, and influenced by markets (Upshur, 2000) (Upshur and Tracy, 2004, p. 201).

But actually applying the evidence requires a different set of skills:

The art of the practice of medicine is to be learned only by experience. It is not an inheritance. It cannot be revealed. Learn to see, learn to hear, learn to feel, learn to smell, and know that by practice alone you can become expert (Osler, 1968, cited in Upshur and Tracy, 2004, p. 202).

Upshur’s views on evidence also show up in this correspondence with Gupta (2003):

...Upshur (personal communication) states that evidence itself does not constitute truth; rather, evidence plays a role in determining what is believed to be true. He points to the legal notion of evidence as a comparison. In a court case, ‘evidence’ is used to support various theories of what actually happened during a crime. One of these theories is ‘discovered’, on the basis of the available evidence, to be most likely to be true. The selection of evidence to support conclusions is negotiated and debated and is affected by social and other forces such as power, coercion, and self-interest of one negotiator, or group of negotiators, vis-à-vis another. These forces may have an impact on which conclusions or theories are ultimately selected as most likely to be true (Gupta, 2003, p. 116).

Gupta (2003) continues:

[E]vidence is a status conferred upon a fact, reflecting, at least in part, a subjective and social judgment that the fact increases the likelihood of a given conclusion being true. For any given set of phenomena, there may be many available facts that could count as evidence for more than one conclusion or theory. However, only some facts will be deemed as evidence for one successful conclusion or theory, which itself is chosen from among several options. Thus, evidence is not, as EBM implies, simply research data or facts but series of interpretations that serve a variety of social and philosophical agendas (p. 116).

If one is looking to solve complex problems in medicine, the relationship between evidence and interpretation matters enormously. If one is just looking to sell profitable drugs, that relationship is not as important. The fact that EBM has not adequately addressed the fundamental distinction between evidence and interpretation is troubling indeed.

3. The inferential gap may be unbridgeable

Upshur (2005) points out that the sample population used in trials is often quite different from the actual population that uses a particular treatment. Doctors are expected to extrapolate from a sample population to their particular patient — but Upshur (2005) argues that such deduction (sometimes also referred to as extrapolation or inference) is more problematic than it would appear. He writes:

Clinical research evidence in the form of RCTs and meta-analyses provides at best a provisional warrant — that is, drug X may work, not drug X will work. The probability of successful treatment with the assortment of agents available varies dramatically; there is a wide range of ways of framing these benefits, but there is no such thing as a treatment that works every time. Consequently, there is nothing in any way directive about such evidence and nothing inevitable about a p value or confidence interval: the evidence does not tell a physician or a patient what to do and has no compelling epistemic or moral force (p. 483).

Upshur (2005) shows that medicine faces an irreducible problem in that average outcomes in RCTs do not indicate what treatment is appropriate for the individual patient. But EBM as currently constructed ignores this “inferential gap.” He writes:

[M]eta-analysis and RCTs use statistical techniques to calculate outcome measures that are average values distributed across populations. There seems to be an irreducible problem around the heterogeneity of treatment effects (Kravitz, Duan, and Braslow 2004).... [H]aving an average-value outcome in no way directs what one ought to do for any individual patient. Knowing that, on average, drug X is better than placebo for condition Y, does not tell you that drug X is going to work for a particular patient with condition Y. This still leaves a possibility for misapplication. One could believe that drug X is the appropriate manoeuvre for patient Z for condition Y, only to find that, in actuality, it has either no effect, or even harmful effects (p. 488).

This inferential gap is unlikely to ever be bridged because there is infinite variety in the human population so responses to medical interventions will always vary as well. Bayesian statistics might help narrow the gap a bit (see next section) as it allows one to continually refine estimates as new evidence becomes available (conditional probabilities that affect the prior probability of the hypothesis). But even with Bayesian statistics, the best one can come up with are probabilities, not the deterministic thinking of EBM. These are extraordinary debates at the core of the philosophy of medicine — and it is exactly these sorts of debates that EBM proponents circumvent in making RCTs the sole tool for clinical decisions.

4. Bayesian statistics has long since proven superior to the frequentist approach relied upon by RCTs

Worral (2002) is withering in his critique of the over-reliance on RCTs within evidence-based medicine. The picture he paints is a battle between frequentist statisticians and Bayesian statisticians (and philosophers) over the epistemological basis of EBM. He notes that frequentist statisticians have elevated RCTs to the top of the evidence hierarchy as a sort of panacea for overcoming research bias but that such a ranking is not warranted by the evidence.

Worrall (2002) writes that three arguments have traditionally been used in favor of randomization:

1. “The Fisherian Argument from the Logic of Significance testing” — namely that frequentist tests of significance, by definition, require randomization in order to be valid, “so that any given individual in the trial had the same probability of landing in either group” (p. 321);

2. The belief that “randomization controls for all variables known and unknown” (p. 321); and

3. Randomization controls for selection bias (p. 324).

Worrall (2002) makes the case that none of these arguments withstands close examination.

Ronald Fisher was an English statistician whose insights helped to create modern statistical science (Hald, 1998). Fisher argued that randomisation was the only means by which “the validity of the test of significance can be guaranteed” (1947, in Worrall, 2002, p. 321).

Worrall (2002) responds to this line of reasoning by writing,

• “[F]irst... it is not in fact clear that the argument is convincing even on its own terms [citing Lindley, 1982, and Howson and Urbach, 1993];”

• “secondly... there are, of course, many — not all of them convinced Bayesians — who regard the whole of classical significance-testing as having no epistemic validity, and hence who would not be persuaded of the need for randomisation even if it had been convincingly shown that the justification for a significance test presupposes randomization” (p. 321).

• He continues (citing Dennis Lindley, 1982) that “there are indefinitely many possible confounding factors” so it is in fact, not possible to control for all variables known and unknown as frequentists claim (p. 324).

• Furthermore, while blinding of the clinician via randomization does help control for selection bias, it is simply one of many ways to achieve this methodological goal (p. 325).

In 2008, Michael Rawlins gave the annual Harveian Oration at the Royal College of Physicians of London where he challenged many tenets of EBM. He stated his view that, “Decisions about the use of therapeutic interventions, whether for individuals or entire healthcare systems, should be based on the totality of available evidence. The notion that evidence can be reliably or usefully placed in ‘hierarchies’ is illusory” (Rawlins, 2008, p. 579). It was a direct challenge to a healthcare system increasingly designed around the use of EBM and evidence hierarchies. As part of his address, he also politely sided with the Bayesians over the frequentists:

A growing number of statisticians (Ashby, 2006) believe that the solution to many of the difficulties inherent in the frequentist approach to the design, analysis and interpretation of RCTs is the greater use of Bayesian statistics. This notion of probability — subjective or inverse probability — is the likelihood of a hypothesis given some data. Thus, while the frequentist approach is about the probability of some data conditional on a specific hypothesis (usually the null hypothesis), the Bayesian approach is the reverse (i.e. the probability of a hypothesis conditional on the data) (p. 581).

But he notes that “regulatory authorities have sometimes been hesitant to concede that Bayesian approaches may have advantages” (Berry et al. 2005, in Rawlins, 2008, p. 582).

5. “Science can never prove hypotheses, only refute them...” (The Popperians vs. EBM)

Eyal Shahar (1997) similarly challenges the epistemic basis of EBM — but from a Popperian perspective. Shahar, a doctor and epidemiologist, sees EBM as an end run around complicated epistemological issues that some scientists would rather not discuss. He writes: “‘evidence-based medicine’ is at best a meaningless substitute for ‘medicine’ and, at worst, a disguise for a new version of authoritarianism in medical practice” (Shahar, 1997, p. 110).

He continues:

[I]t is quite simple to argue logically against the use of the term ‘evidence-based medicine’, if evidence means biomedical science. At least one school of logical thought submits that scientific work can never prove or even ‘nearly prove’ scientific hypotheses but can only, in principle, falsify them (Popper 1968; Agassi 1975; Miller 1982). Scientific hypotheses — and medical hypotheses are no exception — are forever conjectures about the truth. They might be conjectures that have survived many tests and have attracted a large crowd of believers, but that does not change their permanent conjectural status (Shahar, 1997, p. 110).

For Popperians, the problem with EBM goes beyond the general and technical problems noted by others. Rather the problem is that the inductive method relied upon by EBM (inferring from a clinical trial to a particular patient) is not a valid methodology. Shahar (1997) writes,

Inductive procedures — that is, inferring from the observed to the unobserved — are always illogical (Popper 1968; Popper & Miller 1987) and they are just as illogical in the case of a clinical trial.... (1) no number of successful trials provides logical support to the theory that treatment A is always superior to placebo and (2) no number of ‘negative’ trials provides logical support to the theory that treatment A is never superior to placebo. As Popper and others have relentlessly argued: inductive logic does not exist. It is impossible to construct a system of inductive logic (Miller 1982) (p. 111).

While Upshur (2005) was troubled by EBM’s leaps across the inferential gap, Shahar (1997) goes further by arguing that this gap can never be closed completely. Popperians similarly reject the frequentist assumptions that underlie RCTs:

Statistical hypothesis testing, and especially the concept of ‘statistical significance’, have been subject to devastating criticism with almost no rebuttal (Rothman 1986a; Gardner & Altman 1986; Poole 1987; Goodman & Royall 1988; Oakes 1990; Schervish 1996). If anyone insists on rules for statistical interpretation of the results of a test (e.g. P < 0.05), he [sic] should be reminded that there are no such logical rules — neither in physics nor in clinical research (Shahar, 1997, p. 111-112).

Shahar (1997) argues that given a heterogeneous population, personalized medicine is the only logically justified approach to evidence:

The best empirical experience, at least in the case of chronic stable medical conditions, should be provided by a randomized, double-blind, cross-over trial that includes only one patient: the patient in question (Guyatt et al. 1986). No literature search for evidence is superior to an ‘n-of-1 trial’ whenever feasible. Interestingly, evidence-based medicine is a poor product of several of the scientists that should be praised for introducing the n-of-1 trial methodology into clinical practice in the 1980s [most notably Guyatt]. Why contributors to both themes failed to realize that literature-based evidence and the n-of-1 trial methodology do not thrive together is an enigma to me (p. 114).

For Shahar (1997) EBM is an illegitimate attempt to elide the uncomfortable realities of the uncertainty that comes with medical practice:

One may ask how doctors are to make medical decisions in the presence of permanent uncertainty. The answer is very simple: on the basis of some interpretation of empirical experience — a subjective exercise with no universally accepted logical rules (p. 115).

Shahar (1997) concludes by writing:

Whenever someone waves the flag of evidence-based medicine in your face, demand a straightforward answer to the following question: whose evidence is the evidence in evidence-based medicine? (p. 116)

Based on the evidence presented in Chapter 5 of my doctoral thesis we already have the answer to Shahar’s question. Practically speaking, the evidence generated by pharmaceutical companies through their contracts with overseas (usually Chinese) CROs, written up by ghost writers employed by pharmaceutical companies, and published in scientific journals that often have their own financial conflicts of interest, is the evidence that EBM tells doctors to rely upon. EBM is a corporate takeover of medicine by stealth with only a handful of critics raising questions about its troublesome context and implications.

6. The Pragmatists vs. EBM

The pragmatic school in the philosophy of medicine also takes exception to what they call the objectivist ontology of EBM. Pragmatism is defined as “a philosophy emphasizing practical applications and consequences of beliefs and theories, that the meaning of ideas or things is determined by the testability of the idea in real life” (pragmatism, n.d.). Objectivism is defined as “one of several doctrines holding that all reality is objective and external to the mind and that knowledge is reliably based on observed objects and events” (objectivism, n.d.).

The irony is that EBM sees itself as a pragmatic movement. But Goldenberg (2009) argues that EBM is actually an objectivist philosophy.

As DeVries and Lemmens (2006) argue, “evidence” is a social product, influenced by the variable power and authority held by different stakeholders (patients, medical researchers, hospital administrators, clinicians, policy makers, etc.) in producing and determining the parameters for what counts as evidence. The displacement of these normative considerations in favor of technical and methodological considerations like the criteria of best evidence or scientific rigor is regarded as ethically suspect (Goldenberg 2005). While evidence-based approaches are concerned with finding the best evidence (according to their predefined standards) to answer research and treatment questions, the critics ask the challenging question: whose evidence is setting the standard of best practice (Harari 2001; Shahar 1997; Stewart 2001;Walsh 1996; Witkin and Harrison 2001)? (Goldenberg, 2009, p. 170).

Goldenberg (2009) argues that EBM’s objectivist tendencies make it ill-suited to the demands of day-to-day medicine.

[T]he term objectivity carries considerable epistemic weight in science and other knowledge-pursuing activities. It has been described allegorically as a “figure cast in stone, standing in our cultural pantheon among symbols of divine knowledge” (Burnett 2008). Objectivity’s typical association with such equally powerful concepts as reality, truth, and reliability further emphasizes its cognitive might. Yet this objectivist ontology, where the evidence “speaks” and reliable knowledge follows, presents an occupational hazard to (actual) medical practice. Subjective content muddies up even the most rigorous evidence-based practice by the inescapable layers of interpretation and sociocultural influence that enter in the setting of research agendas (including what projects gets funded and why), the production of evidence in primary research, and the selection of which evidence is chosen to inform policy and practice (Goldenberg, 2009, p. 170).

Goldenberg describes a certain paradox to EBM — on the one hand its proponents appeal to a certain pure standard of objectivity (via RCTs) while on the other hand ignoring evidence that RCTs are not as objective as they seem.

EBM’s rigid and rule-based hierarchy of evidence stands in contrast to the open-ended and ad hoc style of pragmatic scientific inquiry. The hierarchy’s ranking has been explained by the EBM originators as being based on levels of certainty (Sackett et al. 1991). It stands as EBM’s point of departure from pragmatic science to a more objectivist epistemology, as the RCT’s gold standard status will be shown to be problematically upheld by various abstract commitments to the universal rigor and applicability of randomized trial methods that are not substantiated in the actual practices of health research. Instead, different health research studies call for different designs and so there is no gold standard methodology (Goldenberg, 2009, p. 174).

One of the things I find so troublesome about EBM is not its positivism or objectivism per se, but rather that it displays a certain corporate positivism and corporate objectivism. What I mean is that in EBM, (mostly) corporate-derived data is granted exclusive privileges for decision making in spite of evidence suggesting it is of low quality, while other valid but often non-corporate methods, such as observational studies or registries, are dismissed outright.

Goldenberg argues that the “absolutist search for certainty can explain the appeal and rapid uptake of EBM” (p. 181).

Paul Feyerabend (1978) has described science as being obsessed with its own mythology of objectivity and universality, while in medicine, Katherine Montgomery (2006) has argued that medicine mis-specifies itself as a science, with an image of science that is antiquated and that does justice to neither medicine nor science. Science has also been described, again by Feyerabend among others, as a repressing ideology that started as a liberating movement. EBM reinforces these images, to a certain extent, with its objectivist account of scientific medicine and rigid hierarchy of evidence. If the hierarchy of evidence was put in place to refute skepticism and ensure certainty, it stands as an example of what Feyerabend abhorred: science making claims to truth well beyond its actual capacity. Science, the critics insist, cannot fulfill this epistemic quest for certainty. Science is at best — and is at its best — when it is recognized to be democratic, ad hoc, and fallible (Goldenberg, 2009, p. 182).

It is not that science and medicine could never be tools for liberation. It is that actually existing science and medicine in the U.S., for the most part, are monopoly capitalist science and medicine that elevate profits over the well-being of people, which puts them in conflict with their own stated methods and principles.

7. Medicine as science vs. medicine as practice

In How Doctors Think, Kathryn Montgomery (2006) argues that medicine is neither a science nor an art but a social science — specifically the development of practical reasoning which Aristotle called phronesis. She writes,

The assumption that medicine is a science — a positivist what-you-see-is-what-there-is representation of the physical world — passes almost unexamined by physicians, patients, and society as a whole. The costs are great. It has led to a harsh, often brutal education, unnecessarily impersonal clinical practice, dissatisfied patients, and disheartened physicians (citing Engel 1977, in Montgomery, 2006, p. 6).

But medicine as science just does not fit the evidence of how doctors actually do their work according to Montgomery (2006).

No matter how solid the science or how precise the technology that physicians use, clinical medicine remains an interpretive practice. Medicine’s success relies on the physicians’ capacity for clinical judgment. It is neither a science nor a technical skill (although it puts both to use) but the ability to work out how general rules — scientific principles, clinical guidelines — apply to one particular patient. This is — to use Aristotle’s word — phronesis, or practical reasoning (Montgomery, 2006, p. 5).

Montgomery (2006) calls medicine a “practice” and proceeds to reintroduce ancient wisdom into the conversation. She writes,

What is neglected by the science-art duality is medicine’s character as a practice.... Aristotle describes phronesis in the Nicomachean Ethics as the intellectual capacity or virtue that belongs to practical endeavors rather than to science. Although twenty-first-century beneficiaries of science are not much used to thinking of different kinds of rationality, phronesis or practical reasoning is nevertheless a valuable, even a familiar concept. As an interpretive, making-sense-of-things way of knowing, practical rationality takes account of context, unpredicted but potentially significant variables, and, especially, the process of change over time (p. 33).

If medicine at its best is properly thought of as a social and philosophical practice, EBM as currently taught interrupts that practice. EBM fixes medical practice to a frequentist, corporate ontology. By design, EBM quite explicitly turns off the multiple, conflicting, ever-changing ways of knowing and replaces them with a single corporatized channel, RCTs.

Conclusion

As with any successful marketing program, the words themselves are unobjectionable and pleasing: evidence-based medicine. But the actual program behind Evidenced-Based Medicine™ as practiced throughout the developed world over the last thirty years is corporate, captured, runs roughshod over essential debates in the philosophy of medicine, and promotes deadly junk science as the gold standard. Think about this: over the last three decades, the biggest blockbuster drugs include vaccines, SSRIs and other psychopharmaceuticals, and statins. All of them were licensed using EBM rubrics. And yet none of them have been shown to have more benefits than harms in the real world. EBM has turned allopathic medicine into a Potemkin Village — a pretty façade with almost nothing of substance behind it.

The history of EBM reads like a Greek tragedy. A bunch of smart, seemingly well-intentioned people organized themselves to take over the practice of medicine. They wanted to make it better. It went well for a while but then hubris, greed, power, and corruption took over. Epidemiologists became a new priestly class and replaced science with dogmatism. Once unleashed, EBM became a runaway freight train. Now it is actively harming patients and destroying allopathic medicine in the name of saving it.

We need not sacrifice our dignity, common sense, and rational faculties on the altar of EBM as Guyatt and others have done. Rigged RCTs are not evidence. Corporate science is not science. We need to return to the old ways. We must let doctors be doctors again, relying on evidence, experience, and intuition — phronesis as Aristotle taught us (and Kathryn Montgomery reminds us). And we must let parents be parents again. Personal sovereignty and responsibility are the foundation of medicine and society. No financially conflicted epidemiologist in an ivory tower thousands of miles away (or heaven help us, Washington D.C.) knows what’s best for a person. The era of corporate EBM is over and the future of medicine is decentralized, N-of-1, non-corporate, non-government, person-to-person, direct primary care, based on the totality of evidence, decency, life experience, dialogue, and personal values.

REFERENCES

basic science. (n.d.). https://www.merriam-webster.com/dictionary/basic science

bench research. (n.d.). https://web.archive.org/web/20181209194911/http://medical-dictionary.thefreedictionary.com/bench+research

Bluhm, R. (2005). From Hierarchy to Network: a richer view of evidence for evidence-based medicine. Perspectives in Biology and Medicine, 48(4), 535-547. https://sci-hub.se/10.1353/pbm.2005.0082

objectivism. (n.d.) Farlex Partner Medical Dictionary. (2012). https://www.thefreedictionary.com/objectivism

Goldenberg, M. J. (2009, Spring). Iconoclast or Creed?: Objectivism, Pragmatism, and the Hierarchy of Evidence. Perspectives in Biology and Medicine, 52(2). https://sci-hub.se/10.1353/pbm.0.0080

Gupta, M. (2003). A critical appraisal of evidence‐based medicine: some ethical considerations. Journal of Evaluation in Clinical Practice, 9(2), 111–121. https://sci-hub.se/https://doi.org/10.1046/j.1365-2753.2003.00382.x

La Caze, A. (2011). The role of basic science in evidence-based medicine. Biology and Philosophy, 26(1), 81-98.
https://sci-hub.se/https://link.springer.com/article/10.1007/s10539-010-9231-5

Montgomery, K. (2006). How doctors think: Clinical judgment and the practice of medicine. Oxford University Press. https://global.oup.com/academic/product/how-doctors-think-9780195187120

pragmatism. (n.d.) Farlex Partner Medical Dictionary. (2012). http://medical-dictionary.thefreedictionary.com/pragmatism

Rawlins, M. (2008, December). De Testimonio: on the evidence for decisions about the use of therapeutic interventions. Clinical Medicine, 8(6). http://doi.org/10.7861/clinmedicine.8-6-579

Sackett, D. L., Rosenberg, W. M. C., Gray, J. A. M., Haynes, R. B., & Richardson, W. S. (1996, January 13). Evidence based medicine: What it is and what it isn’t. British Medical Journal, 312(7023), 71–72. https://doi.org/10.1136/bmj.312.7023.71

Shahar, E. (1997). A Popperian perspective of the term ‘evidence-based medicine’. Journal of Evaluation in Clinical Practice, 3, 109-116. https://sci-hub.se/10.1046/j.1365-2753.1997.00092.x

Upshur, R. E. G. and Tracy, C. S. (2004, Fall). Legitimacy, Authority, and Hierarchy: Critical Challenges for Evidence-Based Medicine. Brief Treatment and Crisis Intervention, 4(3), 197-204. http://doi.org/10.1093/brief-treatment/mhh018

Upshur, R. E. G. (2005, Autumn). Looking for rules in a world of exceptions: reflections on evidence-based practice. Perspectives in Biology and Medicine, 48(4), 477-489. https://sci-hub.se/10.1353/pbm.2005.0098

Worrall, J. (2002, September). What Evidence in Evidence-Based Medicine? Philosophy of Science, 69(S3), S316-S330. https://sci-hub.se/http://doi.org/10.1086/341855

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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I. Introduction

Evidence-Based Medicine (EBM) is a relatively recent phenomenon. The term itself was not coined until 1991. It began with the best of intentions — to give frontline doctors the tools from clinical epidemiology to make science-based decisions that would improve patient outcomes. But over the last three decades, EBM has been hijacked by the pharmaceutical industry to serve the interests of shareholders rather than patients. Today, EBM gives preference to epistemologies that favor corporate interests while instructing doctors to ignore other valid forms of knowledge and their own professional experience. This shift disempowers doctors and reduces patients to objects while concentrating power in the hands of pharmaceutical companies. EBM also leaves doctors ill-equipped to respond to the autism epidemic and unable to produce the sorts of paradigm-shifts that would be necessary to address this crisis.

In this article I will:

• provide a brief history of EBM;

• explain how evidence hierarchies work;

• explore ten general and technical criticisms of EBM and evidence hierarchies;

• examine the American Medical Association’s 2002, 2008, and 2015 evidence hierarchies;

• highlight the corporate takeover of EBM; and

• explore the implications of these dynamics for the autism epidemic.

II. History of Evidence-Based Medicine

Medicine faces the same challenges as any other branch of knowledge — deciding what is “true” (or at least “less wrong”). Since its emergence in 1992, EBM has become the dominant paradigm in the philosophy of medicine in the United States and its impact is felt around the world (Upshur, 2003 and 2005; Reilly, 2004; Berwick, 2005; Ioannidis, 2016). Through the use of evidence hierarchies, EBM privileges some forms of evidence over others.

Hanemaayer (2016) provides a helpful genealogy of EBM. Epidemiology — “the branch of medical science that deals with the incidence, distribution, and control of disease in a population” — has been a recognized field for hundreds of years. But clinical epidemiology, defined as “the application of epidemiological principles and methods to problems encountered in clinical medicine” first emerged in the 1960s (Fletcher, Fletcher, and Wagner, 1982). Feinstein (1967) is credited as the catalyst for the emergence and growth of this new discipline. Feinstein, in his book Clinical Judgment (1967) wrote, “Honest, dedicated clinicians today disagree on the treatment for almost every disease from the common cold to the metastatic cancer. Our experiments in treatment were acceptable by the standards of the community, but were not reproducible by the standards of science.” So Feinstein proposed a method for applying scientific criteria to clinical judgements in clinical situations.

According to Hanemaayer (2016), around the same time, David Sackett was leading the first department of clinical epidemiology at McMaster University in Canada. Sackett was influenced by Feinstein and trained an entire generation of future doctors in clinical epidemiology. In the 1970s, Archibald Cochrane expanded the use of randomized controlled trials to a broader range of medical treatments. In 1980, the Rockefeller Foundation funded the International Clinical Epidemiology Network (INCLEN) which took the methods and philosophy of clinical epidemiology worldwide. The efforts of INCLEN would later receive the support of the U.S. Agency for International Development, the World Health Organization, and the International Development Research Centre.

Various terms have been used to describe the methods of clinical epidemiology. Eddy (1990) used the term “evidence-based.” At about the same time the residency coordinator at McMaster University, Dr. Gordon Guyatt, was referring to this growing discipline as “scientific medicine” but apparently this term never caught on with the residents (Sur and Dahm, 2011). Eventually Guyatt settled on the term “evidence-based medicine” in an article in 1991 (Sur and Dahm, 2011).

An Evidence-Based Medicine Working Group (EBMWG) was formed, comprised of 32 medical faculty members mostly from McMaster University but also from universities in the United States. In 1992, the EBMWG planted a flag for their particular approach to the philosophy of medicine with an article in JAMA titled, “Evidence-Based Medicine: A New Approach to Teaching the Practice of Medicine.” The article reads less like a traditional scientific journal article and more like a political manifesto. In the first paragraph they announced their intention to supplant the traditional practices of doctors with the methods and results from clinical epidemiology.

A NEW paradigm for medical practice is emerging. Evidence-based medicine de-emphasizes intuition, unsystematic clinical experience, and pathophysiologic rationale as sufficient grounds for clinical decision making and stresses the examination of evidence from clinical research. Evidence-based medicine requires new skills of the physician, including efficient literature searching and the application of formal rules of evidence [in] evaluating the clinical literature (EBMWG, 1992).

The article mostly consists of recommendations to consult the epidemiological literature following “certain rules of evidence” which are not defined before making any clinical decision (EBMWG, 1992). The authors also provide an evaluation form for “more rigorous evaluation of attending physicians” based on how consistently they “substantiate decisions” by consulting the medical literature (EBMWG, 1992). But the important point was not the steps per se, but who had ultimate decision-making authority within the medical profession. The EBMWG (1992) article was an announcement that henceforth, clinical epidemiology was at the top of the authority pyramid (what remains to be explained is why doctors fell in line). Over the next ten years the EBMWG published twenty-five articles on EBM in JAMA (Daly, 2005).

Many have questioned the tone and approach of the early EBMWG vanguard (see: Upshur, 2005; Goldenberg, 2005; and Stegenga, 2011 and 2014). But the article, along with extensive organizing within the medical community, had the desired effect. EBMWG (1992) has since been cited over 6,900 times and EBM has become hegemonic throughout medicine — thoroughly reshaping the practices of doctors, clinics, medical schools, hospitals, and governments.

In 1994, Sackett left McMaster University to start the Centre for Evidence-Based Medicine at Oxford University which quickly became a dominant force in the EBM movement (Hanemaayer, 2016). Sackett et al. (1997) systematized EBM to include the following five steps:

1. Formulate an answerable question;

2. Track down the best evidence of outcomes available;

3. Critically appraise the evidence (i.e. find out how good it is);

4. Apply the evidence (integrate the results with clinical expertise and patient values); and

5. Evaluate the effectiveness and efficiency of the process (to improve next time).

So far so good, but the Devil is always in the details.

III. Evidence Hierarchies

At first glance EBM appears straightforward and helpful. Problems appear once one tries to operationalize it. At the heart of evidence-based medicine are evidence hierarchies (Stegenga, 2014). Evidence hierarchies, as the name suggests, are categorical rankings that give preference to some ways of knowing over others. Rawlins (2008) found that 60 different evidence hierarchies had been developed as of 2006. Some of the best known evidence hierarchies include the Oxford Centre for Evidence-Based Medicine (CEBM), the Scottish Intercollegiate Guidelines Network (SIGN), and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) (Stegenga, 2014).

For the purposes of this initial discussion I will focus on the Oxford CEBM because it was the first in widespread use and it is representative of the larger field (Stegenga, 2014).

Table 1, simplified version of Evidence Hierarchy, Oxford Centre for Evidence-Based Medicine last updated by Howick, 2009:

*The CEBM definition of “systematic reviews” sometimes includes meta-analysis.

Source: Stegenga (2014). Available from the Centre for Evidence-Based Medicine (2009).

In theory, EBM and evidence hierarchies could be two separate things. In practice, evidence hierarchies are how one “critically appraises the evidence” — Step 3 in Sackett et al. 1997 described above (Stegenga, 2014).

IV. Ten general and technical criticisms of evidence-based medicine and evidence hierarchies

In this section I will review ten general and technical criticisms of EBM. The arguments are that:

1. EBM has become hegemonic in ways that crowd out other valid forms of knowledge;

2. Evidence hierarchies do not just sort data, they legitimate some forms of data and invalidate other forms of data;

3. Meta-analyses and systematic reviews of RCTs are beset with epistemic problems;

4. Most RCTs are designed to identify benefits but they are not the proper tool for identifying harms;

5. RCTs are designed to address selection bias but other forms of bias remain;

6. Case reports and observational studies are often just as accurate as RCTs;

7. EBM is not based on evidence that it improves health outcomes;

8. EBM and evidence hierarchies reflect authoritarian tendencies in medicine;

9. Evidence hierarchies have reshaped the practice of medicine for the worse; and

10. Evidence hierarchies objectify and/or overlook patients.

1. EBM has become hegemonic in ways that crowd out other valid forms of knowledge.

There is widespread agreement that EBM has become the dominant paradigm in clinical medicine. Upshur (2005) writes:

Now virtually every dimension of health care — from nursing to mental health care to policy making to humanitarian medical intervention — is striving to become evidence-based. PubMed currently has over 20,000 citations to “evidence-based.”

Reilly (2004) is unconcerned with EBM’s shortcomings and unequivocal in assessing its dominance in medicine today (this passage is flagged by critics of EBM including Goldenberg, 2009, and Stegenga, 2014 for its stridency):

Few would disown the EBM hypothesis — providing evidence-based clinical interventions will result in better outcomes for patients, on average, than providing non-evidence-based interventions. This remains hypothetical only because, as a general proposition, it cannot be proved empirically. But anyone in medicine today who does not believe it is in the wrong business (Reilly 2004).

Berwick (2005) provides a history of the promising early origins of EBM but then warns that things have gone too far. He writes:

...we have overshot the mark. We have transformed the commitment to “evidence-based medicine” of a particular sort into an intellectual hegemony that can cost us dearly if we do not take stock and modify it. And because peer reviewed publication is the sine qua non of scientific discovery, it is arguably true that hegemony is exercised by the filter imposed by the publication process...

Berwick (2005) then draws attention to common sense ways of knowing such as practice, experience, and curiosity, that are excluded by EBM (I love this quote!):

How much of the knowledge that you use in your successful negotiation of daily life did you acquire from formal scientific investigation — yours or someone else’s? Did you learn Spanish by conducting experiments? Did you master your bicycle or your skis using randomized trials? Are you a better parent because you did a laboratory study of parenting? Of course not. And yet, do you doubt what you have learned?

Far from setting doctors free to practice their craft at the highest level, Berwick (2005) sees EBM as encouraging doctors to exclude valuable ways of knowing:

... the very success of the movement toward formal scientific methods that has matured into the modern commitment to evidence-based medicine now creates a wall that excludes too much of the knowledge and practice that can be harvested from experience, itself, reflected upon.

2. Evidence hierarchies do not just sort data, they legitimate some forms of data and exclude other forms of data.

Although EBM in the early years made reference to the totality of evidence, soon EBM became a way of excluding all studies except double-blind, randomized, controlled trials (RCTs) from the analysis. Stegenga (2014) writes: “The way that evidence hierarchies are usually applied is by simply ignoring evidence that is thought to be lower on the hierarchies and considering only evidence from RCTs (or meta-analyses of RCTs).”

Often this is not just implicit but explicit:

In an article which purported to provide the best way to distinguish effective medical interventions from those which are ineffective or harmful, the article stated that one should “discard at once all articles on therapy that are not about randomized trials” (Department of Clinical Epidemiology and Biostatistics, 1981, in Stegenga, 2014).

Strauss et al. (2005), in a textbook on the practice and teaching of EBM, also suggests that some forms of evidence can be discarded:

If the study wasn’t randomized, we suggest that you stop reading it and go on to the next article in your search. (Note: We can begin to rapidly critically appraise articles by scanning the abstracts to determine if the study is randomized; if it isn’t, we can bin it.) Only if you can’t find any randomized trials should you go back to it (Strauss et al. 2005 in Borgerson, 2009).

3. Meta-analyses and systematic reviews of RCTs are beset with epistemic problems.

Meta analyses of RCTs and/or systematic reviews of RCTs are consistently at the top of most evidence hierarchies. The concept of aggregating the findings from several studies seems unassailable. But understanding how it works in practice reveals that it has the appearance of accuracy and objectivity only by eliding the subjectivity at the core of the technique. Meta-analyses tend to treat evidence as a commodity like wheat, copper, or sugar that just needs to be sorted and weighed. Stegenga (2011) explains that:

Meta-analysis is performed by (i) selecting which primary studies are to be included in the meta-analysis, (ii) calculating the magnitude of the effect due to a purported cause for each study, (iii) assigning a weight to each study, which is often determined by the size and the quality of the study, and then (iv) calculating a weighted average of the effect magnitudes (p. 498).... [B]y pooling data from multiple studies the sample size of the analysis increases, which tends to decrease the width of confidence intervals, thereby potentially rendering estimates of the magnitude of an intervention effect more precise, and perhaps statistically significant.

While meta-analysis aims for greater objectivity, in fact, it is still a subjective exercise. Stegenga (2011) writes, “Epidemiologists have recently noted that multiple meta-analyses on the same hypotheses, performed by different analysts, can reach contradictory conclusions.”

Furthermore, many meta-analyses are plagued by the same financial conflicts of interest as RCTs and other ways of gathering evidence:

Barnes and Bero (1998) performed a quantitative assessment of multiple meta-analyses which reached contradictory conclusions regarding the same hypothesis, and found a correlation between the outcomes of the meta-analyses and the analysts’ relationships to industry.... In another example, there have been 124 meta-analyses of antihypertensive drugs. Meta-analyses of these drugs were five times more likely to reach positive conclusions regarding the drugs if the reviewer had financial ties to a drug company (Yank, Rennie, & Bero, 2007 in Stegenga, 2011).

Meta-analyses are not nearly as precise as their proponents would have one believe.

Different weighing schemes can give contradictory results when evidence is amalgamated. An empirical demonstration of this was given by Jüni, Witschi, Bloch, and Egger (1999). They amalgamated data from 17 trials testing a particular medical intervention, using 25 different scales to assess study quality (thereby effectively performing 25 meta-analyses).... Their results were troubling: the amalgamated effect sizes between these 25 meta-analyses differed by up to 117% — using exactly the same primary evidence. The authors concluded that “the type of scale used to assess trial quality can dramatically influence the interpretation of meta-analytic studies” (Jüni et al. 1999 in Stegenga, 2011).

Meta-analyses also suffer from low inter-rater reliability.

Not only does the choice of quality assessment scale dramatically influence the results of meta-analysis, but so does the choice of analyst. A quality assessment scale known as the ‘”risk of bias tool” was devised by the Cochrane group to assess the degree to which the results of a study “should be believed.” Alberta researchers distributed 163 manuscripts of RCTs among five reviewers, who assessed the RCTs with this tool, and they found the inter-rater agreement of the quality assessments to be very low (Hartling et al., 2009). In other words, even when given a single quality assessment tool, and training on how to use it, and a narrow range of methodological diversity, there was a wide variability in assessments of study quality (Stegenga, 2011).

It is not that subjectivity itself is necessarily a problem. The subjective wisdom that comes from years of experience could be quite helpful in evaluating the evidence. The problem with meta-analyses as currently practiced is that those involved usually do not acknowledge their own subjectivity while simultaneously excluding the sort of reasoned subjective analysis (from doctors, patients, or perhaps even philosophers) that might be helpful. Indeed, meta-analyses as currently practiced leave out the political and economic contextual factors that are likely to corrupt a study’s results:

A good review is based on intimate personal knowledge of the field, the participants, the problems that arise, the reputation of different laboratories, the likely trustworthiness of individual scientists, and other partly subjective but extremely relevant considerations. Meta-analysis rules out any such subjective factors (Eysenck, 1994 in Stegenga, 2011).

Stegenga (2011) concludes, “the epistemic prominence given to meta-analysis is unjustified.”

4. Most RCTs are designed to identify benefits but they are not the proper tool for identifying harms.

Upshur (2005) writes that:

RCTs can serve potent economic interests, and the ascendancy of the randomized trial as the most reliable form of evidence detracts from considering other, equally cogent forms of evidence as informative or having standing in debates about the safety and harm of treatments. RCTs are also parsimoniously powered to get answers efficiently, usually in the shortest period of time, largely because the pharmaceutical company sponsoring the trial needs the data for regulatory approval.... So RCTs and meta-analysis are underpowered to tell us what the likely accurate harm/benefit ratio of therapy is, and they are conducted and, once available, become “evidential” on populations for the most part quite unlike those that take the drugs, often with significant co-morbidity burdens. Therefore, we actually do not have the full “evidence” of what a medication is capable of doing on the basis of RCTs alone.

Michael Rawlins chaired the Committee on the Safety of Medicines (UK) from 1992 to 1998 and was the founding chair of the National Institute for Clinical Excellence from 1999 to 2013. From 2012 to 2014 he was President of the Royal Society of Medicine and in 2014 served as chair of the Medicines and Healthcare products Regulatory Agency (roughly the equivalent of the medical portion of the U.S. Food & Drug Administration). Rawlins (2008) writes,

RCTs are designed to ensure that the statistical power will be sufficient to demonstrate clinical benefit. Such power calculations do not, however, usually take harms into account (Evans 2004). As a consequence, although RCTs can identify the more common adverse reactions, they singularly fail to recognise less common ones or those with a long latency (such as malignancies). Most RCTs, even for interventions that are likely to be used by patients for many years, are only of six- to 24-months duration. And, if adverse events are detected at a statistically significant level, it is easy to dismiss them as being due to chance rather than a real difference between the groups (Rawlins, 2008).

Rawlins (2008) concludes that “only observational studies can offer the evidence required for assessing less common, or long-latency, harms.”

Stegenga (2014) writes,

The vast majority of RCTs in medical research maximize the power to detect benefit at the expense of the power to detect harm. The majority of serious harms caused by medical interventions are detected by so-called Phase IV post-approval studies, which are almost always limited to observational analyses of anecdotal clinical reports. Thus, for hypotheses of this kind this intervention causes harm, medical research is limited to evidence from methods not typically placed near the top of mainstream evidence hierarchies...

Stegenga (2016) deepens his critique of how RCTs fail to detect harms:

Most evidence regarding the harms of medical interventions is generated by studies which are funded and controlled by the manufacturers of the interventions under investigation, and whose interests are best-served by underestimating the harm profile of such interventions. This leads to widespread limitation of the evidence regarding harms that is made available to independent scientists and policy-makers, and this, in turn, contributes to the underestimation of the harm profiles of medical interventions. Regulators lack the authority to properly estimate harm profiles of medical interventions, and frequently contribute to shrouding the relevant evidence regarding harms in secrecy (Stegenga, 2016).

Like Upshur (2005) and Rawlins (2008), Stegenga (2016) points out that most RCTs are just long enough to detect benefits but often not long enough to detect harms and the size of the trial is usually calculated to achieve statistical significance for obvious benefits while not being large enough to capture “severe but rare” harms. But he also points out ways that RCTs are intentionally manipulated to produce desired outcomes:

To maximize the observed effect size and minimize the variability of data, trial designers employ various criteria constraining what subjects are included or excluded from the trial.... The most egregious of these trial design features are called “enrichment strategies”: after the enrollment of subjects, but prior to the start of data collection, subjects are tested for how they respond to placebo or the experimental intervention, and those subjects that do well on placebo or (and sometimes and) those subjects that do poorly on the experimental intervention are excluded from the trial (Stegenga, 2016).

FDA post-market surveillance is under-funded by design and not sufficiently staffed to respond to the size of the task. Stegenga (2016) points out the ways that EBM contributes to make the problem worse:

There is strong reason to think that post-market passive surveillance severely underestimates harms of medical intervention. One empirical evaluation of this puts the underestimation rate at 94% (this was based on a wide-ranging empirical survey by Hazell and Shakir 2006). Unfortunately, because observational studies and passive surveillance do not involve a randomized design, they are typically denigrated relative to randomized controlled trials.... Since most evidence regarding harms of medical interventions comes from non-randomized studies (especially rare severe harms), the dominant view of the evidence-based medicine (EBM) movement thereby denigrates the majority of evidence regarding harms of medical interventions (Stegenga, 2016, p. 495).

Stegenga (2016) concludes that, “Because harms of medical interventions are systematically underestimated at all stages of clinical research, policy-makers and physicians generally cannot adequately assess the benefit-harm balance of medical interventions.” Systematically underestimating harms, lack of adequate information for regulatory decisions, and insufficient funding for post-market surveillance are a reflection of the power of pharmaceutical companies to shape the regulatory and political environment.

5. RCTs are designed to address selection bias but other biases remain.

Upshur and Tracy (2004) write that the purpose of randomized trials is to minimize selection bias. However, they note, “this leaves undisturbed concerns about affluence bias, that is, the ability of certain interests to purchase and disseminate evidence; or the relevance bias, that is, the ability of interests to set the evidence agenda” (Upshur and Tracy, 2004).

The high cost of RCTs means that there are only certain actors who are able to engage in this sort of research — usually pharmaceutical companies and academics working under large government grants. Rawlins (2008) points out that the median cost of an RCT in 2005-2006 in the U.K. was 3.2 million pounds (about 5.7 million U.S. dollars given exchange rates at the time) (p. 583). So privileging RCTs in evidence hierarchies privileges certain actors over others as well. The pharmaceutical companies who can afford to implement these methods have a strong incentive to find benefits and ignore harms from their products. Making matters worse, the evidence presented in this article suggests that RCTs are not epistemically superior to other levels in the evidence hierarchy nor are they necessarily superior to other ways of knowing not mentioned in the evidence hierarchies.

EBM makes the same mistakes that Kuhn (1962) and other philosophers of science make — they overlook the very real problem of corporate influence. Gupta (2003) writes:

EBM is uncritical in that it does not build any strategies into its critical appraisal scheme to scrutinize the potentially biasing effects of the source of funding nor does it equip clinicians with the tools to assess their impact. Furthermore, it is permissive of source-of-funding bias. In its relentless pursuit of an ever-greater quantity of evidence, EBM does not acknowledge how the interests of the private research funders (such as pharmaceutical companies) might differ or even directly conflict with the interests of clinicians and patients. EBM thereby creates and fosters the illusion that social processes that contribute to EBM and social consequences of EBM are non-existent, or at least, irrelevant.

Jadad and Enkin (2007) argue that sources of bias are potentially limitless and they identify sixty of the most common types. So simply controlling for selection bias is not sufficient to guarantee scientific integrity. Furthermore, it is not even clear that RCTs as currently practiced actually prevent selection bias:

A research group conducted a systematic review of 107 RCTs about a particular medical intervention, using three popular QATs [Quality Assessment Tools] (Hartling et al. 2011). This group found that allocation concealment was unclear in 85% of these RCTs, and that the vast majority of the RCTs were at high risk of bias. Another group randomly selected eleven meta-analyses involving 127 RCTs on medical interventions in various health domains (Moher et al. 1998). This group assessed the quality of the 127 RCTs using QATs, and found the overall quality to be low: only 15% reported the method of randomization, and even fewer showed that subject allocation was concealed (Stegenga, 2015).

Perhaps the authors of these studies were simply careless in describing their methods. But given that directors of Contract Research Organizations boast of their ability to deliver the results desired by their clients (Petryna, 2007 in Mirowski, 2011) it seems reasonable to wonder whether double-blind randomization is actually happening at all in some clinical trials that purport to be RCTs.

6. Case reports and observational studies are often just as accurate as RCTs.

The definition of a case report in the Dictionary of Epidemiology is notable for its internal contradiction:

Case reports: Detailed descriptions of a few patients or clinical cases (frequently, just one sick person) with an unusual disease or complication, uncommon combinations of diseases, an unusual or misleading semiology, cause, or outcome (maybe a surprising recovery). They often are preliminary observations that are later refuted.... They may also raise a thoughtful suspicion of a new adverse drug event and are an important means of surveillance for rare clinical events. They help to reflect on and learn from medical error (citing Fletcher et al., 2014; Haynes et al., 2006; Koepsell and Weiss, 2003, Vandenbroucke, 2001; Pollock, 2012, and Sackett et al. 1991 in Porta, 2014).

So on the one hand, it is held that case reports are often refuted (even though no reference is supplied) and on the other hand, case reports “may also raise a thoughtful suspicion” (Porta, 2014).

Case reports are second from the bottom in the CEBM evidence hierarchy, ranked above only “expert opinion” and below the threshold that many epidemiologists consider worth reading. “First reports” are case reports of the first recorded incidence of a new disease or adverse event in reaction to a new drug (or new use of an existing drug). But what is the actual evidence as to the reliability of such reports?

Venning (1982) examined 52 first reports of suspected adverse drug reactions published in BMJ, the Lancet, JAMA, and NEJM in 1963. He followed up on each of these reports 18 years later to assess whether in fact they had subsequently been verified.

• “Of 52 first reports, five were deliberate investigations into potential or predictable reactions, and in each case causality was reasonably established.”

• The remaining 47 were what Venning calls “anecdotal” which is never defined but the context in the rest of the article suggests nine or fewer cases, and often just one case, with no control group. Venning found that “35 out of 47 anecdotal reports were clearly correct and that some of the remaining 12 unverified reports may also have represented true adverse reactions...” So 75% of these anecdotal reports were later confirmed to be correct and there was no proof of any false positives.

• The remaining 12 adverse reactions were associated with syndromes that were either so rare, that there were not many other cases to compare them with or so common that it was difficult to separate out the effect of the drug versus chance (Venning, 1982).

When one compares the 75% success rate of anecdotal first reports with the fact that 75-80% of the most widely cited cancer RCTs cannot be replicated (Prinz, Schlange, and Asadullah, 2011; Begley and Ellis, 2012), the decision to place RCTs at the top of the CEBM evidence hierarchy, while denigrating case series, appears unwarranted.

Three studies from the early 2000s confirm that RCTs are not superior to observational studies.

• Benson and Hartz (2000) found “little evidence that estimates of treatment effects in observational studies reported after 1984 are either consistently larger than or qualitatively different from those obtained in randomized, controlled trials.”

• Concato, Shah, and Horwitz (2000) write, “[t]he results of well-designed observational studies... do not systematically overestimate the magnitude of the effects of treatment as compared with those in RCTs on the same topic.”

• Petticrew and Roberts (2003) maintain that the particular research question should be matched with the appropriate research methodology in a matrix rather than a hierarchy. Furthermore, they argue, “in certain circumstances the hierarchy may even be inverted, placing for example qualitative research methods on the top rung.”

In 2017, Thomas Frieden, the former Director of the CDC, made the case in the New England Journal of Medicine that a wide range of different study types can have a positive impact on patients and policy. He makes the simple point that each type of study has strengths and weaknesses and the study type should match the type of problem the researchers are trying to address. He points out that alternative data sources are “sometimes superior” to RCTs.

So a wide range of different types of evidence can be valid and help inform clinical decision-making and yet the current practice of EBM systematically excludes everything other than the large RCTs favored by pharmaceutical companies.

7. EBM is not based on evidence that it improves health outcomes.

Numerous authors, including Sackett and his colleagues, have acknowledged that EBM violates its own evidence-based norms because “there is no evidence that EBM is a more effective means of pursuing health than medicine-as-usual” (Norman 1999 in Gupta, 2003).

Upshur (2003) notes that, “Ironically, the creation of these classifications has not as yet been informed by research but is driven in large part by expert opinion.” Defenders of EBM (such as Reilly, 2004) state that such evidence is not provided because it “cannot be proved empirically.” Yet that is not exactly true. One could easily create a natural experiment that compares patient outcomes between two equally ranked hospitals where one continues with business as usual and another implements EBM. While not exactly an RCT, there would be ways to compare before and after results within and between hospitals and even blind investigators.

Upshur and Tracy (2004) write:

[T]he entire edifice of evidence hierarchies is not based on systematic research at all, but on expert judgment or consensus. In other words, the warrant or justification for viewing evidence in such a hierarchical structure rests on the lowest form of evidence, that is, the beliefs of a few (p. 200). Also, the benefit that evidence-based approaches bring to patients is as unproven as the evidence hierarchy itself.

EBM began with the assumption that surely it would improve patient outcomes but there is little evidence to support that assumption.

A fundamental assumption of EBM is that practitioners whose practice is based on an understanding of evidence from applied health care research will provide superior patient care compared with practitioners who rely on [an] understanding of basic mechanisms and their own clinical experience. So far, no convincing direct evidence exists that shows that this assumption is correct (Haynes, 2002, in Upshur, 2005).

It’s interesting to note that the rise in chronic illness in the United States (1986 to the present) roughly corresponds to the rise in EBM in the medical profession (1992 to the present). EBM has been completely unable to stop the rise in chronic illness (particularly among children) but the rise in the stock market value of pharmaceutical companies since 1992 has been spectacular.

8. EBM and evidence hierarchies reflect authoritarian tendencies in medicine.

A number of authors have highlighted the authoritarian tendencies of EBM.

Shahar (1997) was one of the earliest critics to note the authoritarian tendencies of the EBM movement:

I think that, mistakenly, they [supporters of EBM] call for a new type of authoritarianism, hidden behind an amorphous entity called evidence-based medicine. They suggest replacing healthy scientific debates, in which no one should claim authority over the truth, with authorities of scientific knowledge — readers of the literature who will announce a verdict about the evidence and ensure that their verdict is properly executed.

Rosenfeld (2004) is fulsome in her praise for the early days of EBM:

In the 1990s, EBM streaked like a comet across the medicine skies. The advent of EBM was like the translation of the vulgate bible into English by John Wycliffe in the 15th century or the later publication by Tyndale and Coverdale in the 16th century. It was revolutionary. It was populism. It was a change. The practising doctor was going to be able to understand the evidence behind clinical practice, or the lack thereof. EBM gave us the tools to evaluate our daily practice.

But Rosenfeld (2004) then argues that those promising early days have receded to reveal a much more troubling current reality:

[D]uring the last 3 years, EBM has gone from a tool to a religious doctrine and fixed dogma. There are its priests — men and women who are known for practising and preaching EBM and changing the books and literature. You have to have one of these priests on every board and journal, or you are not up to date. Anyone who speaks against these priests is blaspheming EBM, and obviously unscientific or backward. There are thousands of acolytes, those who have heard the word and will accept nothing else.

Rosenfeld (2004) is especially critical of the EBM gatekeepers that prepare meta-analyses for consumption by the wider medical community:

There are secretive organizations that create the dogma — such as the Cochrane group, the ‘Task Force’, or Best Evidence. Who are these people? We know where they are located and sometimes their names, but we must blindly believe in their methods. They come up with conclusions that are published and then the conclusions become codified.... Only a few sources are now considered ‘true’ or reliable EBM. Some organizations list 11-15 ‘proper’ and ‘acceptable’ sources of EBM. All else, including good research, books, and reviews, are not evidenced-based, and may not be used.

Rosenfeld (2004) concludes: “We have come full circle to faith-based medicine. We are encouraged and, even, forced to mould our practice of medicine to the authority of those practitioners of EBM that are ‘approved’ and ‘acceptable.’”

Upshur (2005) similarly recounts the shift from the joyful early days of EBM to its more troubling present form:

[I]t seems a new orthodoxy is emerging, as resistant to criticism and reflection as the “paradigm” it sought to replace. The joy of inquiry, questioning, and uncovering inconsistencies and paradoxes in the belief structure of medicine has given way to what seems to be an adherence to a near-religious belief. Assertion has replaced argument. It is no coincidence that the cover of the British Medical Journal’s 10-year anniversary reflection on EBM features a picture of what looks like three priests in a high tower. Evidence is a concept health care is avidly embracing, for legitimacy and authenticity. However, it has come to be more like familiar advertising slogans, an attractive package, a branding exercise, one that draws people in with its seductive promises of being more rigorous and scientific in the application of medical principles.

9. Evidence hierarchies have reshaped the practice of medicine for the worse.

Evidence hierarchies have reshaped the practice of medicine in ways that are advantageous to pharmaceutical companies and disadvantageous to doctors and patients.

Upshur (2003), recounting a story from his medical practice, gives a glimpse of how pharmaceutical companies use EBM to sell their products:

A pharmaceutical company distributed evidence-based guidelines to my clinic. According to the guidelines, level 1 (best) evidence required one well-designed randomized control trial, and a grade A recommendation required one level 1 study. The guidelines were accompanied by a report of the randomized trial sponsored by that same company and published in a peer-reviewed journal. By disseminating the guidelines with the supportive paper, the company sought to persuade me that I would be following evidence-based guidelines if I prescribed the drug (p. 673).

The process that doctors are taught to use in connection with EBM is an idealized process. In the real world, doctors rarely have the time to follow all of the steps. So instead, they use shortcuts supplied by medical publishers and others.

Recently, there has been acknowledgement of a distinction between evidence-based practitioners and evidence users (Guyatt et al. 2000). Particularly in primary care, there is a trend toward using pre-appraised sources of evidence. One of the most popular of these sources is InfoPOEMs (patient-oriented evidence that matters), a daily email service that provides summaries of research studies relevant to primary care [now part of Essential Evidence Plus]. Each summary is accompanied by the level of evidence, using the Oxford Centre nomenclature (Upshur, 2003).

This shift from evidence-based practitioner to evidence user is presented by proponents of EBM as an acceptable alternative to the idealized process. Yet if one examines these developments in their wider context, it is clear how problematic they are. What started out as a process to empower doctors now has doctors essentially taking orders from the pharmaceutical companies who run most of the clinical trials. Even though many of these studies are not replicable, harried doctors with detailers in their office showing them the latest “evidence-based medicine” are going to feel enormous pressure to conform. Clinicians who do not follow the latest EBM guidelines may also wonder whether such independent thinking might expose them to additional risk of malpractice suits.

Groopman (2007) in How Doctors Think describes the impact of EBM on the hospital workplace and the mindset of doctors:

Each morning as rounds began, I watched the students and residents eye their algorithms and then invoke statistics from recent studies. I concluded that the next generation of doctors was being conditioned to function like a well-programmed computer that operates within a strict binary framework.

What likely started out with good intentions, can become paint-by-numbers medicine that constrains the wisdom and creativity of some of our finest minds:

Clinical algorithms can be useful for run-of-the-mill diagnosis and treatment... But they quickly fall apart when a doctor needs to think outside their boxes, when symptoms are vague, or multiple and confusing, or when test results are inexact. In such cases — the kinds of cases where we most need a discerning doctor — algorithms discourage physicians from thinking independently and creatively. Instead of expanding a doctor’s thinking, they can constrain it (Groopman, 2007).

Goldenberg (2009) provides an extraordinary account of the political economy of EBM and how EBM shapes the mode of production in medicine:

Given the demands of keeping up with the literature, the time associated with evaluating the abundance of clinical research, and the importance of “getting it right,” it did not take long for EBM to replace its earlier call for individual critical appraisal of the evidence by practicing clinicians with a veritable industry of systematic review and meta-analysis (available for a fee, typically through electronic databases). While thought by many to be timely and useful, the availability of meta-analyses and clinical summaries immediately derails EBM’s early anti-authoritarian programmatic. The initial program of equipping all practicing physicians with critical appraisal skills (and “a computer at every bedside”) was intended to democratize medicine by discarding the hierarchical nature of expert opinion and received wisdom. That very authoritarianism seems to be restored by the creation of “expert” EBM sources that proliferate clinical guidelines, meta-analyses, educational products, electronic decision support systems, and all things worthy of the brand name “evidence-based medicine” to a captive and paying audience of clinicians who desire to be “evidence-based practitioners.”

EBM is now a brand and everything that goes along with being a brand — a shortcut to decision making, very powerful at shaping decisions, essential to marketing and profit but not a very precise indicator of the quality of the contents.

10. Evidence hierarchies objectify and/or overlook patients.

EBM objectifies patients in ways that run counter to the traditional practice of medicine and more recent paradigms such as “patient centered medicine.” Upshur and Tracy (2004), write, “[I]t is interesting to note that patients do not become relevant until Step 4 [in the EBM process outlined by Sackett et al., 1997, summarized above]. In fact, patients are seen as passive objects that have evidence applied to them after the information has been extracted from them.”

Such discounting of patients’ experiences and inherent subjectivity would seem to be a violation of fundamental values in medicine and yet it is the dominant philosophy of medicine today. Upshur (2005) writes:

Patients are seen very much as objects from which information is to be gleaned and then inspected. Nowhere in the EBM process is listening to patients and their concerns, and legitimizing their questions, regarded as important. Gadamer (1975) writes of the hermeneutical priority of the question and how this establishes direction and dialogical relationship. Which question is considered or reflected upon establishes whether the relationship between doctor and patient is one of inspectorial power or of dialogue, mutual respect, and deliberation. In the sense that the voice of the patient is explicitly excluded in the steps of EBM, except insofar as it is a voice of pathological information that can be transformed into searchable terms, it is no wonder that proponents of EBM can still write of the problematic nature of including patient values and perspectives (see, for example, Haynes 2002). They are omitted from the process by definition.

I will return to this issue below in my discussion of implications for the autism epidemic.

V. The AMA’s 2002, 2008, and 2015 evidence hierarchies

In 2002, the American Medical Association created its own evidence hierarchy, The Users’ Guide to the Medical Literature (Guyatt and Rennie 2002) and it contained a fascinating twist. It resembled the CEBM, except at the very top of the hierarchy, the AMA listed N-of-1 randomized control trials.

Table 2

Source: Guyatt and Rennie (2002), p. 7.

An N-of-1 trial is a clinical trial in which a single patient is the entire sample population. N-of-1 trials can be double-blinded (both patient and doctor do not know the treatment vs. the placebo) and the order of treatment and control can be randomized using various patterns (Guyatt, et al., 1986, p. 889-890).

N-of-1 medicine is an important step in the right direction because it reflects a philosophy of medicine that is in keeping with the heterogeneity of the human population. But few formal N-of-1 trials are conducted each year. By 2008, Kravitz et al. wrote, “What ever happened to N-of-1 trials?” noting that “Despite early enthusiasm, by the turn of the twenty-first century, few academic centers were conducting n-of-1 trials on a regular basis” (p. 533). Lillie et al. (2011) write, “Despite their obvious appeal and wide use in educational settings, N-of-1 trials have been used sparingly in medical and general clinical settings” (p. 161).

Curious about the dearth of N-of-1 trials, I started researching what happened. And what I discovered shocked me.

In 2000, the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Work Group began to meet. Gordon Guyatt was one of its leaders. By 2004 they published their framework and it is the opposite of transparent — it takes the different levels from the evidence hierarchy and converts them into a “quality scale” — “high, moderate, low, and very low.” At the top of their evidence hierarchy is RCTs. So according to GRADE, if a study is an RCT, it is considered “high quality” which is defined as “We are very confident that the true effect lies close to that of the estimate of the effect. Further research is very unlikely to change our confidence in the estimate.”

GRADE converted a system based on data to one based on normative labels — “high quality,” “high confidence,” even though as I have shown above, RCTs are not more reliable than other forms of evidence. GRADE is an opaque wrapper that hides what’s inside the model and gives all the power in decision-making to the people preparing the recommendations. Governments and public health agencies including the WHO, FDA, and CDC love GRADE because it tells people what to do in no uncertain terms without having to deal with the messiness of odds ratios, confidence intervals, and p values.

In 2008, the American Medical Association published a new edition of The Users’ Guide to the Medical Literature and N-of-1 trials had been downgraded below systematic reviews of RCTs. Given how these evidence hierarchies work, anything below the first tier is considered inferior and ignored which means that the AMA had abandoned N-of-1 as a valid methodology for clinical decision-making.

The third edition of The Users’ Guide to the Medical Literature published in 2015 fully embraces GRADE as the AMA’s preferred framework for making prevention and treatment decisions.

I saw GRADE in use when I watched every meeting the FDA’s Vaccines and Related Biological Products Advisory Committee (VRBPAC) and the CDC’s Advisory Committee on Immunization Practices (ACIP) in 2022 and 2023. GRADE is a tool to give legitimacy to ANY medical intervention no matter how abysmal the data. For example, the FDA and CDC used GRADE to authorize:

• The use of the Pfizer COVID vaccine in adults even though more people died in the treatment than the control group;

• The use of Covid vaccines in children even though the clinical trial showed no clinically significant benefit to children; and

• Covid vaccine boosters for all age groups with no human testing whatsoever and only 28 days of antibody results in six mice.

So within 13 years (from the first edition in 2002 to the third edition in 2015) the AMA went from the best-in-class evidence hierarchy that acknowledged individual difference to a cartoonish monstrosity, GRADE, that is just a tool for laundering bad data on behalf of the pharmaceutical industry. In the process the AMA sold out the doctors in their association and the patients in their care to the drug makers.

VI. More details on the corporate takeover of EBM

Ioannidis (2016) recounts his conversations and correspondence with David Sackett over the course of many years about how EBM changed since its initial conception:

As EBM became more influential, it was also hijacked to serve agendas different from what it originally aimed for. Influential randomized trials are largely done by and for the benefit of the industry. Meta-analyses and guidelines have become a factory, mostly also serving vested interests. National and federal research funds are funneled almost exclusively to research with little relevance to health outcomes. We have supported the growth of principal investigators who excel primarily as managers absorbing more money.... Under market pressure, clinical medicine has been transformed to finance-based medicine (Ioannidis, 2016, p. 82).

One of the many problems with EBM is that focusing on poorly defined notions of “quality” sometimes overlooks important dynamics and variables.

Now that EBM and its major tools, randomized trials and meta-analyses, have become highly respected, the EBM movement has been hijacked. Even its proponents suspect that something is wrong (Greenhalgh et al. 2014 and Greenhalgh, 2012). The industry runs a large share of the most influential randomized trials. They do them very well, they score better on “quality” checklists (Khan et al. 2012), and they are more prompt than non-industry trials to post or publish results (Anderson et al. 2015). It is just that they often ask the wrong questions with the wrong short-term surrogate outcomes, the wrong analyses, the wrong criteria for success (e.g., large margins for noninferiority), and the wrong inferences (Every-Palmer and Howick, 2014; Turner et al. 2008; and Lexchin et al. 2003)... The industry is also sponsoring a large number of meta-analyses currently (Ebrahim et al. 2016). Again, they get their desirable conclusions (Jørgensen et al. 2006) (in Ioannidis, 2016).

As I pointed out in chapter 5 of my doctoral thesis, even meta-analyses and systematic reviews, which sit at the top of most evidence hierarchies, are contaminated by corporate influence. Iaonnidis (2016) notes that even the widely respected Cochrane Collaboration “may cause harm by giving credibility to biased studies of vested interests through otherwise respected systematic reviews” (p. 84).

Ioannidis (2016) provides a vivid illustration of the current mode of production in medicine and how EBM has become the corporate tail wagging the dog.

In most developed countries, clinicians are under tremendous market pressure. Most discussions in department meetings are about money. One can sense the pressure to deliver services, to capture the largest possible market share (a synonym for ‘‘patients’’), to satisfy customers (synonyms for ‘‘humans’’), to get high satisfaction scores, to charge more, to perform more procedures, and to tick off more items on charge forms. (As an aside, a nice joke is that these charge driven electronic health records are then used for research.) This is not what I thought medicine would be about, let alone EBM. This is mostly finance-based medicine. I would not blame anyone. These physicians have no other option. This is how the world works; they are fighting to keep their jobs. Yet, how likely is it that physicians will design studies whose results may threaten their jobs by suggesting that less procedures, testing, interventions are needed? How likely is it that, if they do design such studies, they will accept results suggesting that they should quit their jobs?... Is EBM doomed to be heartily accepted only when it leads to more medicine, even if this means less health (Glasziou et al. 2013; Grady and Redberg, 2010)?... In some settings, we are close or past the tipping point where medicine diminishes rather than improves well-being in our society (p. 85).

This is a startling turn of events. Doctors are often seen as heroic, selfless, and wise. EBM was conceived with the best of intentions to further improve medical practice. And yet, Ioannidis (2016) is openly stating that the whole endeavor has been hijacked to serve corporate ends rather than patient needs.

VII. Analysis and implications for the autism epidemic

I want to highlight nine facets of EBM and evidence hierarchies as they apply to the autism epidemic.

1. CEBM, GRADE, and other evidence hierarchies replace the varied ways of knowing with a single tool — RCTs. Supporters of EBM seem to base their model entirely on an idealized view of science. A more “evidence-based” approach would be to read the CEBM evidence hierarchy in the context of how science is actually done. Most RCTs are done at overseas (usually Chinese) CROs (Mirowski, 2011). 50% (Horton, 2015) to 80% (Prinz, Schlange, and Asadullah, 2011; Begley and Ellis, 2012) of what is published is not replicable. To claim that RCTs are the “highest quality” evidence and that one should not bother to read anything else is clearly untenable, unscientific, and not in the interests of patients.

2. It is striking how much the CEBM evidence hierarchy, GRADE, and other evidence hierarchies degrade the contribution of doctors. Starr (1982, 1997) and others have pointed out that doctors have been gradually losing agency as capital and corporations have come to play an ever-greater role in medicine. But to place a doctor’s “expert opinion” at the bottom of the hierarchy, below even “poor quality cohort and case-control studies” is an example of epidemiologists putting their own work above those actually practicing and interfacing with patients in the real world. Instead of viewing doctors as trusted advisors whose instincts, experience, and intuition are key to successful outcomes, the CEBM, GRADE, and other evidence hierarchies regard doctors as the least reliable form of evidence. In the process, the role of the doctor shrinks from discernment to obedience.

3. Individual patients are nowhere to be found in the CEBM evidence hierarchy, GRADE, or other evidence hierarchies. One’s own perspective and insights into one’s disease state do not even make it onto the chart at all. The experiences and insights of patients, the views of doctors, and alternative forms of evidence can provide the data that challenge paradigms. To denigrate these ways of knowing leaves existing paradigms in place even when they have failed to serve the public.

4. EBM has changed the practice of medicine. “In 2023, the United States had 1,010,892 active physicians of which 851,282 were direct patient care physicians” (Association of American Medical Colleges, 2024). There are multiple ways of knowing including RCTs, meta-analyses and systematic reviews, prospective and retrospective cohort studies, case-control studies, cross-sectional studies, ecological studies, observational studies, case reports and series, registries, bench research, and more. In a crisis like autism, it would seem that all available resources — the talents of over a million trained professionals and multiple ways of knowing would be brought to bear on stopping the epidemic. By contrast, EBM represents a deskilling and circumscribing of the practice of doctors, an exclusion of multiple streams of evidence, and a turning over of the process of discovery to a smaller number of specialists, often in the employ of pharmaceutical companies. The result is a calcified practice of medicine, ill-equipped to respond to the crises it faces and the crises to which it contributes.

5. From the corporate-funded studies that produce the outcomes desired by their patrons, to the studies that never get funded, to the studies that get funded only to get quashed, to the studies that get completed but that never lead to regulation, to the rules of “scientific” evidence in the courts that protect corporations and harm plaintiffs, to the philosophy of medicine that discounts methods for detecting harms and favors corporate ways of knowing over other valid epistemologies — medicine in the U.S. is a system that is more hegemonic than scientific; more an expression of power relations than a method for producing good data or improved health outcomes for patients. It is a system that is quite good at protecting the profitable status quo but not very good at producing the sort of open-ended inquiry that can lead to the paradigm shifts necessary to stop the autism epidemic.

6. Given a philosophy of medicine that privileges a certain sort of epidemiology to the exclusion of all other forms of knowing, is it any wonder then that doctors routinely dismiss the thousands of parents who try to explain to their doctors the origins of their child’s autism symptoms (Campbell, 2010; Habakus and Holland, 2011; Handley, 2018)? The experiences of these parents were dismissed long before the family ever walked in the door — they were excluded in medical school when the future doctor was studying evidence-based medicine and learning to follow an epistemology that favors corporate interests and excludes other ways of knowing.

7. It is beyond infuriating that evidence-based medicine has spent more than three decades extolling the virtues of double-blind, randomized, controlled trials, and yet all of the so-called RCTs in connection with vaccines are fraudulent. Everyone knows that they are fraudulent (even though the mainstream medical profession tries to excuse this fraud). In clinical trials for vaccines, the control group is not given an inert saline placebo and is given another toxic vaccine or the toxic adjuvants from the trial vaccine instead. The Informed Consent Action Network (2023) has the receipts. So at the end of the day, the entire evidence-based medical system — including the tens of thousands of published papers and the thousands of careers dedicated to promoting EBM — is a giant theatrical production to empower epidemiologists and enrich the pharmaceutical industry. The professionals involved do not believe their own stated values and are actively participating in the mass poisoning of the population and the destruction of civilization. This is one of the most extreme examples of a failure of moral courage and dereliction of scientific duty in the history of the world.

8. If one wants to be scientific, it would follow that one should turn to those who are making important discoveries first. The parents’ group, the National Society for Autistic Children (founded by Bernard Rimland, now the Autism Society of America) proposed an environmental influence on autism in 1974 (Olmsted and Blaxill, 2010), forty-two years before Project TENDR reached the same conclusion (Bennett et al., 2016). By the mid 1990s, it was common knowledge among parents of children with autism, that autism had a gastrointestinal component (Kirby, 2005) — two decades before the microbiome became the “new frontier in autism research” (Mulle, Sharp, and Cubells, 2013). We know that EBM is a fraud because it ranks rigged corporate studies ahead of the paradigm-shifting breakthroughs discovered by parents that are actually helping autistic children.

9. Going forward, any system of medicine in connection with autism must start with the individual child and his/her family as the highest form of evidence (because obviously they are). All forms of data, no matter how unconventional or “outside the box,” must be brought to bear on supporting recovery and preventing this injury from happening to others. Rigged corporate RCTs have no place in actual medicine; their only appropriate use is as evidence of crimes against humanity in future Nuremberg trials of pharmaceutical executives and their enablers in government. The revolution we seek is thus a return to actual science instead of the genocidal corporate nonsense posing as evidence-based medicine today.

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Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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The paradox of autism causation studies is that we already know beyond a reasonable doubt what’s causing autism but mainstream science will never “know” in the conventional way because of economic and political factors surrounding the autism epidemic.

Let’s start with the first half of that sentence:

I. We already know

Eyewitness testimony is foundational to our criminal justice system and relied upon by judges and juries every day to administer justice. In Neil v. Biggers (1972) the U.S. Supreme Court outlined five factors for evaluating reliability of eyewitness testimony: opportunity to view, degree of attention, accuracy of description, level of certainty, and time between crime and identification. That testimony can then be corroborated by documentary evidence and additional witnesses.

Parental testimony about autistic regression is at the highest end of the range in every case. Parents are with the child 24/7, the degree of attention could not possibly be higher, the parents know more details about the child’s life than anyone, they are certain about what they saw, and they generally know right away when something is wrong. In a sane society, the following testimony would be sufficient:

Your honor, my baby was perfectly healthy and meeting all of his developmental milestones. We went to a child “well baby” visit, my child got 4 shots. Over the next several days my child was with me 24 hours a day. He had a high fever, seizures, vomited, and screamed at a high pitch. We went to the emergency room, they ran a bunch of tests, but they couldn’t help us. Since then the child no longer speaks, makes eye contact, or has any social skills. The child now has a diagnosis of autism.

The judge and jury can verify any of these facts by examining before and after video; reviewing medical records; and interviewing other family members, care givers, etc. These are relatively straightforward cases. A child was developing normally, they experienced an acute toxic exposure at a child “well baby” visit, and the child regressed. This happens in up to 88% of autism cases. When this testimony is then repeated tens of thousands of times by moms across the country, it’s clear that we are in the midst of a major crisis.

However, we live in a society where our economy is based on enslaving children through chronic illness to enrich the ruling class. The 1986 National Childhood Vaccine Injury Act combined with the wrongly decided Omnibus Autism Proceedings and the wrongly decided Supreme Court decision in Bruesewitz v. Wyeth LLC turned off the Seventh Amendment right to trial by jury for the vaccine injured. Wide swaths of society have been brainwashed by carrots (the trillion dollar pharmaceutical industry and the soon to be trillion dollar autism industry), sticks (exile, banishment, and blacklisting for anyone who questions the narrative), and the most expensive and sustained propaganda campaign in history, to think that this is normal and okay.

Unfortunately, trying to achieve justice in connection with vaccine injury in the U.S. means going up against the medical mafia that runs all aspects of society — the courts, the political system, the regulatory system, the media, the medical system, the scientific system, Wall Street, academia, etc. And they tilt the playing field and the evidentiary standards to protect their interests.

However, as free, sovereign, and sane people we need not accept the edicts of an insane society. We can simply acknowledge that “I saw with my own eyes what happened” is sufficient to establish causation with regards to vaccine injury.

As I explained in my last article, we also have a FOIA document and a whistleblower at CDC, two vaccinated vs. unvaccinated studies from Gallagher & Goodman (2008 & 2010), a vaccinated vs. unvaccinated study from Hooker & Miller (2021), and three vaccinated vs. unvaccinated studies from Anthony Mawson (2017A, 2017B, & 2025) all showing that vaccines cause autism.

The mainstream medical community will likely never accept any studies that don’t originate from within their own ranks. They engage in circular reasoning by refusing to study the question and then they claim that no valid studies exist. But again, as sane people we need not accept their excuses and instead can simply acknowledge that we have already proved beyond any reasonable doubt that vaccines cause autism.

Now let’s look at the second half of that introductory sentence:

II. Mainstream science will likely never “know” in the conventional way what causes autism

Any honest philosopher of science will tell you that establishing causation is a thorny epistemological problem. Many fine books are written on the problem of causation and the deeper you go, the less you know. We live in a universe with an infinite number of variables. One cannot control for them all so there is always the possibility of confounding. Quantum mechanics establishes (for now) that uncertainty is built into the fabric of the universe. In physics the “laws” thought to govern large objects do not align with the “laws” thought to govern subatomic particles so there is clearly something that we’re missing in our understanding of the properties of matter. And then even if one could figure out all that, we might still be missing additional dimensions of reality that we cannot see or measure.

Given that unsolvable epistemological problem, but also with the need to proceed with our lives nonetheless, scientists have developed proxy measures that get us somewhat closer to establishing our best guess at causation (even though we will never be 100% certain).

The Bradford Hill Criteria are probably the most famous steps for establishing causation. From Grok:

The Bradford Hill criteria are a set of nine principles used to assess whether an observed association between an exposure and an outcome is likely to be causal. Proposed by Sir Austin Bradford Hill in 1965, they are widely used in epidemiology to evaluate evidence for causation, particularly when randomized controlled trials are impractical or unethical. Below is a concise overview of each criterion:

1. Strength of association: A strong association (e.g., a high relative risk or odds ratio) between exposure and outcome is more likely to indicate causation.

2. Consistency: The association is observed repeatedly across different populations, settings, and studies.

3. Specificity: The exposure is linked to a specific outcome or disease, with minimal association to other outcomes.

4. Temporality: The exposure must precede the outcome.

5. Biological gradient (dose-response relationship): The risk of the outcome increases with higher levels or duration of exposure.

6. Plausibility: The association is biologically or mechanistically plausible, based on existing knowledge.

7. Coherence: The association aligns with broader knowledge about the disease, such as laboratory findings or historical trends.

8. Experiment: Experimental or quasi-experimental evidence, such as randomized trials or natural experiments, supports the association.

9. Analogy: Similar exposures causing similar outcomes provide supporting evidence.

The original 1965 article on which this is based is somewhat more chatty.

The Bradford Hill Criteria is just one of many causal criteria systems including:

1. U.S. Surgeon General’s Criteria (1964 and later)

• U.S. Department of Health, Education, and Welfare. (1964). Smoking and Health: Report of the Advisory Committee to the Surgeon General of the Public Health Service.

3. Rothman’s Sufficient-Component Cause Model (1976)

• Rothman, K. J. (1976). “Causes.” American Journal of Epidemiology, 104(6), 587–592.

3. Henle-Koch Postulates (adapted for epidemiology)

• Evans, A. S. (1976). “Causation and Disease: The Henle-Koch Postulates Revisited.” Yale Journal of Biology and Medicine, 49(2), 175–195.

4. Susser’s Causal Criteria (1986, 1991)

• Susser, M. (1991). “What is a Cause and How Do We Know One? A Grammar for Pragmatic Epidemiology.” American Journal of Epidemiology, 133(7), 635–648.

5. International Agency for Research on Cancer (IARC) Framework

• IARC Monographs on the Evaluation of Carcinogenic Risks to Humans. General methodology described in the Preamble (2019).

6. Modern Causal Inference Methods

• Directed Acyclic Graphs:

  • Pearl, J. (2000). Causality: Models, Reasoning, and Inference. Cambridge University Press.

• Propensity Score Matching:

  • Rosenbaum, P. R., & Rubin, D. B. (1983). “The Central Role of the Propensity Score in Observational Studies for Causal Inference.” Biometrika, 70(1), 41–55.

7. Weight of Evidence Approach

• EPA Guidelines for Carcinogen Risk Assessment:

  • U.S. Environmental Protection Agency. (2005). Guidelines for Carcinogen Risk Assessment.

• WHO Framework:

  • WHO (2021) Human Health Risk Assessment Toolkit: Chemical Hazards, second edition.

I would add Evidence Based Medicine (EBM) as another causal criteria system. There are over one hundred EBM hierarchies and dozens of EBM services that one can subscribe to that will summarize the latest studies via an EBM framework.

The point being — if one wanted to establish scientific causation in the conventional way in connection with autism, one would need a very large data set that included upwards of 1,000 variables for each person: race, sex, gestational weight, birth weight, age of the mom, age of the dad, all underlying conditions, region, all pre-pregnancy exposures, all exposures in utero, all exposures in infancy, each vaccine would be its own variable, the timing and order of the vaccines would be another variable, you’d need dummy variables for things that you missed, and a placeholder variable for a natural error rate in the calculations. And then you’d run a series of regressions to control for each different factor to see the relative contribution of each.

And it’s pretty clear from the data that we already have that what you would see is a series of escalating risk tiers:

• Lowest risk: No vaccines, no birth drugs, normal gestation period, and no infant formula (exclusively breastfed), and the lowest level of exposures to pollution, plastics, fire retardants, pesticides, and EMF (so perhaps Amish, Mennonite, or off-grid) — we should expect to see an autism rate of less than 1 in 10,000 children (consistent with the first autism prevalence study, Treffert, 1970).

• Low risk: No vaccines but one is exposed to urban air pollution, plastics, fire retardants, pesticides, EMF, and other pharmaceuticals — we should expect to see an autism rate of about 1 in 715 (consistent with Thomas & Margulis, 2016).

• Moderate risk: An alternative vaccine schedule, urban air pollution, plastics, fire retardants, pesticides, EMF, and other pharmaceuticals — we should expect to see an autism rate of about 1 in 440 (consistent with Thomas & Margulis, 2016).

• High risk: CDC vaccine schedule, urban air pollution, plastics, fire retardants, pesticides, EMF, SSRIs, & Tylenol — we should expect to see an autism rate of about 1 in 31 (consistent with Thomas & Margulis, 2016).

• Highest risk: CDC vaccine schedule, birth drugs, c-section, premature birth, infant formula, urban air pollution, plastics, fire retardants, pesticides, EMF, SSRIs, & Tylenol — we should expect to see an autism rate of about 1 in 21 or even as high as 1 in 10 (which is what we are already starting to see in Black and Hispanic boys in aggressive vaccine mandate states including California and New Jersey).

I’ll eat my hat if this isn’t right but from everything we can see right now, this appears to be what’s happening.

1. Genes only confer a slight risk of autism.

2. Pollution, plastics, and pesticides set a somewhat higher base rate.

3. Any vaccines at all increase autism risk.

4. The more vaccines the higher the autism risk.

5. And then all of the ubiquitous toxic chemicals + birth drugs + c-sections + premature birth + infant formula (no breastfeeding) + the CDC vaccine schedule, and the autism rate goes through the roof.

Now here’s where the story gets really weird. We basically had the comprehensive 1,000 variable study that I just described, but then-NIH Director Francis Collins killed it in 2014. From my thesis:

The failure of the National Children’s Study

As the autism rate increased dramatically in the United States in the 1990s, many leading public health figures called for comprehensive research into possible environmental causes. In 1998, the President’s [Clinton] Task Force on Environmental Health and Safety Risks to Children recommended a National Children’s Study (NCS) and authorizing legislation was included in the Children’s Health Act of 2000 (Landrigan et al., 2006).

The act called for a prospective cohort study that would track 100,000 children from shortly after conception through age 21 (Landrigan et al., 2006). The act called for “a complete assessment of the physical, chemical, biological, and psychosocial environmental influences on children’s well-being; data collection to evaluate “environmental influences and outcomes on diverse populations of children, which may include the consideration of prenatal exposures;” and consideration of “health disparities among children, which may include the consideration of prenatal exposures” (H.R. 4365, 2000). In other words, Congress funded exactly the sort of comprehensive epidemiological study that would enable scientists to identify the possible environmental causes of autism.

But the study never got off the ground. The NCS spent from 2001 to 2007 consulting with a range of experts and advisory committees on questions of study design. In 2007, Congress appropriated funding for a pilot called the Vanguard Study (Kaiser, 2014). In 2009, the NIH began enrolling 5,000 mother-infant pairs in 40 academic centers across the United States (Kaiser, 2014).

The original director, Peter Scheidt was ousted in 2009 for “misleading Congress about the true cost of the study” (Tozzi & Wayne, 2014). In 2012, the NIH dropped the 40 academic centers and turned the study subjects over to private contractors (Kaiser, 2014). In 2014, after spending fourteen years and more than $1.3 billion on the study that was still in the pilot phase, Francis Collins, director of the NIH, killed the study altogether (Collins, 2014).

Following the cancellation of the project, Collins and others made statements about continuing the research in some form using less expensive methods (Collins, 2014), but such promises have not come to fruition. During the fourteen years that the NCS spent unsuccessfully trying to launch the study, the autism rate increased nearly five fold from 1 in 250 to 1 in 59 (CDC, 2018).

It would be easy to blame bureaucratic incompetence for the failure of this project. But Francis Collins, who led the NIH from 2009 to 2016 (and was reappointed as head of NIH in 2017 by President Trump), previously led the Human Genome Project — so he had experience shepherding complex multibillion dollar projects to completion.

Francis Collins and the autism industry took all of the money for the study, produced nothing, and then shut down the study altogether. If it had been successful (at identifying causes of autism) spending several billion dollars on the NCS would have been a bargain, given that autism already cost the U.S. $268 billion per year by 2015.

Presumably the reason Francis Collins shut down the study is that he knew what they would find and that threatened the trillion dollar pharmaceutical industry and the growing autism industry.

Now, more than a decade later, the chances that HHS Secretary Kennedy will be able to push through a new conventional study and do it in the six months that he’s publicly promised are essentially zero. The pharmaceutical industry is stronger and richer than ever before, the autism industry is bigger and more powerful than ever before, and there are literally hundreds of thousands of people who are complicit in the largest crime in human history who don’t want to go to jail.

We are living in a crime scene. Practically speaking, one could conduct a study to satisfy the Bradford Hill Criteria or any other system of causation to prove that vaccines cause autism and other intellectual disabilities (in fact, this has already been done, see Bjelogrlic, 2025). Politically speaking, the mainstream scientific community will never arrive at this answer themselves because of their own complicity and culpability.

III. The conundrum

All of the data we have on autism are flawed. The mainstream vaccine studies don’t have a control group. The gene studies are based entirely on spurious correlation. The mainstream environmental studies fail to control for vaccines lest the researchers get blacklisted. And the alternative studies are small and underpowered. Nearly every study published since the 1980 Bayh-Dole Act has a financial conflict of interest. Quite literally we have conflicted, poorly-designed studies from the trillion dollar pharmaceutical industry vs. testimony from moms and dads and alternative studies funded by a parents of vaccine injured children.

Those are the data we have to solve an epidemic so large and expensive that it will cause the collapse of the developed world in our lifetime. And the data will not get any better in our lifetime either because the pharmaceutical industry and the autism industry are so large, rich, and powerful that they can prevent any new research from being conducted (and if it is somehow conducted they can find ways to kill the study as they did with the National Children’s Study or manipulate the analysis or block the release of the findings).

But the reason I bring all of this up is that this realization sets us free. There’s a particular moment in soccer, often late in the game on a counterattack, when a striker has to make a split-second decision to press the attack or wait for additional midfielders to join the play. A teammate who has a better view of the playing field will sometimes yell out, “What you see!” It conveys a lot of information with just three words. It means that no additional help is coming and the best opportunity you have is to make the play with what you see in front of you. I think that’s what we have to do with autism as well.

We know what’s causing autism. We should not wait for a double blind RCT because a double blind RCT is never coming given the political economy of autism. Instead we should trust each other in community against the predatory forces of global monopoly capitalism that are trying to enslave and kill us. We must return to the wisdom of parents and trusting each other if we are to survive this toxic pharmacological assault on humanity.

So we avoid vaccines. Yep, all of them (unless you’re in the third world and want to take BCG to reduce the risk of tuberculosis). Of course we avoid other toxicants too. We warn others, one at a time. We slowly back away from the genocidal culture that did this to us and we build our own parallel society and our own self-sufficient communities. Mainstream society is dying and will collapse completely on its current trajectory. So we step off that path and chart our own better course. That’s the work of the next 50 years.

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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It seems to me that the proper way to understand the autism epidemic is to read everything that has been written on autism causation, throw out any studies that are characterized by a financial conflict of interest or fatally flawed study design, and see what patterns emerge from the papers that are left. During my doctoral thesis I reviewed about 80 of the top studies in autism epidemiology and toxicology. That was groundbreaking at the time because the vast majority of mainstream scholars don’t have the courage to discuss any papers that threaten the profits of powerful industries.

As I’ve continued to work in this space over the last six years I now realize that there are about 1,000 autism causation studies in the English language focused on the U.S. It’s daunting to think about trying to wrap one’s head around a field that large. So most public health officials just grab a favorite study here or there to justify their biases and that is exactly the wrong way to approach this topic. There has to be a better way of working through the available knowledge on this issue.

Now I believe that I’ve figured out how to map the entire field of autism causation studies in one article. If you sat down to read each article individually, it would likely take you several years. But as I will show below, you don’t necessarily have to do that. There is a way to move through all of the literature at a meta level that I believe leads to the right answer and a viable plan for how to stop the autism epidemic.

Let’s start with a quick introduction and then get into the different types of studies.

In the early 1980s, vaccines were so harmful that vaccine manufacturers routinely lost in court. They lobbied the U.S. Congress to pass the 1986 National Childhood Vaccine Injury Act to give themselves liability protection. And they pinky-swore to make vaccines safer but there was no legal mechanism in the bill to enforce that promise so they never did.

Pharmaceutical companies proceeded to add as many vaccines as possible to the schedule. Prior to 1986, there were 3 routine vaccines totaling 7 injections. Today the CDC’s Maternal and Child & Adolescent vaccine schedules include 19 vaccines requiring 76 injections with 94 total doses of antigen (I’m actually less worried about the antigens than the other ingredients in the shots).

No one in a position of authority bothered to measure the impact of the growing vaccine schedule on the health of children. Most regulators were auditioning for a job with Pharma because that’s where the money is. Politicians depend on Pharma donations for their re-election campaigns. The mainstream news media get most of their revenue from Pharma advertising so they were never going to bite the hand that feeds them. Pharma invested heavily in public relations to lay siege to any remaining pockets of resistance.

Mercury (thimerosal) was grandfathered in as “Generally Recognized As Safe” because it’s easier to do that than actual safety testing. Aluminum adjuvants were allowed with only minimal safety testing — 1 man, 3 rabbits, and ever-moving goal posts (chapter 9 of my thesis covers the regulatory history of aluminum adjuvants). The gold rush was on so vaccine manufacturers were free to add whatever they wanted to vaccines and they would all be approved because the regulators and the medical industry were captured mind, body, and spirit by Pharma.

The autism rate skyrocketed in the 1990s and has continued to increase ever since. Rates of ADHD, life threatening allergies, autoimmune disorders, asthma, childhood cancers, diabetes, and epilepsy soared too and those are probably vaccine injuries as well. But autism spectrum disorder (ASD) is more costly than those other conditions because it’s a lifelong disability with no known effective treatment (some parents have been able to recover their children through holistic and alternative therapies but the percentage who are successful in doing so is still in the single digits).

At that point, the people who created the autism epidemic had to pretend to look for the cause. But they had to make sure to never find the actual cause because then the flow of research funding would stop and lots of these doctors and scientists would go to jail or be hung from lampposts by angry parents of injured kids. So an entire industry was created to cover up the autism epidemic.

II. TWENTY-TWO STUDIES IN THE VACCINE COVER-UP

Since 2000, more than twenty scientific studies have concluded that there is no association between vaccines and autism. The most widely cited studies are:

• Fombonne & Chakrabarti, 2001;

• Madsen et al., 2002;

• Mäkelä, Nuorti, & Peltola, 2002;

• Pichichero, Cernichiari, Lopreiato, & Treanor, 2002;

• Hviid, Stellfeld, Wohlfahrt, & Melbye, 2003;

• Madsen et al., 2003;

• Nelson & Bauman, 2003;

• Stehr-Green, Tull, Stellfeld, Mortenson, & Simpson, 2003;

• Verstraeten et al., 2003;

• Wilson, Mills, Ross, McGowan, & Jadad, 2003;

• Andrews et al., 2004;

• Heron & Golding, 2004;

• Smeeth et al., 2004;

• Honda, Shimizu, & Rutter, 2005;

• Fombonne et al., 2006;

• Miles & Takahashi, 2007;

• Thompson et al., 2007;

• Baird et al., 2008;

• Hornig et al. 2008;

• Schechter & Grether, 2008; and

• Tozzi et al., 2009.

Most of these are studies that claim no association between MMR or thimerosal-containing vaccines and autism, which is odd because the CDC’s own internal research shows that both of these types of vaccines do indeed cause autism (see 2014 statement from William Thompson and 2014 SafeMinds analysis of FOIA documents obtained from former CDC researcher turned GSK executive Thomas Verstraeten).

J.B. Handley also documents the conflicts of interests and fatal flaws in study design for most of these papers on a brilliant website called 14studies.com.

More recently, vaccine supporters have made a last stand with Hviid et al. (2019) but that study is also fatally flawed (for example the autism rate in their sample was more than 65% lower than in the general Danish population; see analysis in Hammond, Varia, & Hooker, 2025 and James Lyons-Weiler, 2019).

Furthermore even though randomized, double-blind, placebo-controlled trials are the gold standard of biomedicine, none of the studies listed above has a proper control group of unvaccinated children (the Informed Consent Action Network provides the details here). The failure to conduct proper double-blind RCTs renders all of these studies scientifically invalid.

And just like that we’ve demolished the entire basis for the claim that vaccines do not cause autism.

III. FIVE LARGE AUTISM GENETICS STUDIES

In the 1990s, the Human Genome Project captured the public’s imagination and the government’s scientific spending. Claiming that autism is genetic was a win-win because it offered the hope that autism might be curable through genetic engineering.

The federal government then sank more than $2 billion into searching for the gene(s) for autism… and found nothing that explained more than 1% of cases.

Not to be outdone by the federal government, private foundations also sought to prove that autism is genetic and failed categorically.

The genetic explanation for autism has always been problematic because there is no such thing as a genetic epidemic — the human genome just doesn’t change that fast.

AGRE

The Autism Genetic Resource Exchange (AGRE) was established in 1997 by the Cure Autism Now (CAN) foundation, a predecessor organization to Autism Speaks (which later merged with CAN in 2007). AGRE collected genetic (DNA) and phenotypic (clinical, behavioral) data from 2,000 families with at least one member diagnosed with ASD and made the data freely available to qualified researchers globally. This led to the production of 169 scientific journal articles but no major breakthroughs that get us any closer to understanding autism causation or treating autism symptoms. Below I’ll explain more why and how all of these gene studies fail in a similar fashion.

SSC

As readers of this Substack will remember, Jim Simons (1938 – 2024) was a billionaire hedge fund manager with a daughter with autism. He wanted to invest some of his wealth in addressing autism and many of the top scientists in the country took advantage of him by telling him that autism was likely genetic. Jim set up the Simons Foundation and proceeded to spend over $300 million searching for the gene(s) for autism. The Simons Foundation Autism Research Initiative (SFARI) launched a project called the Simons Simplex Collection (SSC) in 2007 that gathered genetic, clinical, and behavioral information from approximately 2,600 “simplex” families — those with one child diagnosed with ASD, unaffected parents, and typically one unaffected sibling. SSC has produced 132 peer-reviewed publications and identified “102 risk genes.” But it has produced no major breakthroughs that get us any closer to understanding autism causation or treating autism symptoms.

ASC

In 2010, the Autism Sequencing Consortium (ASC) was founded by Joseph Buxbaum at the Icahn School of Medicine at Mount Sinai, New York and supported by the Broad Institute and NIH. Like other multi-million dollar health studies, ASC launched with a breathless promotional article in a major journal. Rather than focusing on the whole genome, ASC focuses on sequencing the exome which is “the portion of the genome that contains all the exons, which are the protein-coding regions of DNA.” The claim is that the exome “represents a small percentage of the total genome, about 1-2%, but it contains a majority of the known disease-related genetic variations.”

To date, the ASC has sequenced approximately 50,000 exomes from ASD cases, unaffected siblings, and parents. A search of PubMed shows 22 peer-reviewed publications associated with ASC. In 2020 they published a paper highlighting the role of 102 genes in autism and in 2022 they identified 72 more. These sorts of studies produce excited headlines in the mainstream media but no breakthroughs that get us any closer to understanding autism causation or treating autism symptoms.

IN 2011, A COMPREHENSIVE STUDY OF TWINS AND AUTISM SHOWED THAT AUTISM IS NOT PRIMARILY A GENETIC DISORDER… AND THIS MADE NO DIFFERENCE IN THE TRAJECTORY OF THE INDUSTRY

In the early 2000s, as the autism rate soared, political leaders in California wanted to better understand what was happening. So California contracted with sixteen of the best geneticists in the U.S. and gave them access to all birth records in the state. They produced a study titled “Genetic heritability and shared environmental factors among twin pairs with autism” (Hallmayer et al., 2011) which is the most comprehensive study of twins and autism to date. They found that genetic heritability explains at most 38% of ASD cases; in two places they explain that this is likely an overestimate. So at least 62% of autism cases (and likely significantly more) are caused by something other than genes. But the search for the gene(s) for autism had already become a large and very profitable industry and this study showing that autism is NOT primarily genetic did little to slow the growth of this field.

MSSNG

As the cost of genetic sequencing went down, Autism Speaks launched the MSSNG study in 2014. MSSNG is not an acronym, the leaders of the study just liked the way it sounded (it’s pronounced “missing”). They’ve sequenced the genomes of 13,801 individuals belonging to what they call family “trios” (two parents and one affected child) or “quads” (two parents and two affected children). To date, MSSNG has produced 138 peer reviewed publications. They claim to have identified 134 “genes associated with autism” but again produced no major breakthroughs that get us any closer to understanding autism causation or treating autism symptoms.

SPARK

Undeterred by the failure of all genetic research projects to date, the Simons Foundation massively expanded their genetic research portfolio with a new project in 2016 — the Simons Foundation Powering Autism Research for Knowledge (SPARK). As of 2025, SPARK has enrolled over 100,000 individuals with ASD and 250,000 total participants (including family members) across the U.S. Recruitment is facilitated by 31 clinical sites (mostly major pediatric research hospitals). To date, SPARK has produced over 40 peer-reviewed publications. Thus far they’ve identified “ten new autism-risk genes” but no major breakthroughs that get us any closer to understanding autism causation or treating autism symptoms.

STRAIGHT UP CENSORSHIP

As the failures of the Simons Foundation genetic research efforts mounted, rather than change course they hired the editor of Retraction Watch, Ivan Oransky, to push for retraction of studies that question the genetic narrative in connection with autism research. Given that there is an entire multibillion dollar industry built up around gene and autism studies, scientific journals are more than happy to accede to Oransky’s requests to censor the narrative on behalf of their patrons.

WHY STUDIES OF GENES AND AUTISM FAIL (THIS WAS KNOWABLE IN THE EARLY 2000S BUT MOSTLY IGNORED BECAUSE THERE WAS SO MUCH MONEY TO BE MADE)

The human genome contains 3.1 to 3.2 billion base pairs. When one feeds thousands of human genomes with several billion base pairs each into a computer and asks it to look for an association, it will certainly find many based on chance alone. But it’s the classic problem of “correlation is not causation.”

One of the world’s foremost epidemiologists, John Ioannidis, points out in “Why Most Published Research Findings are False” (2005) that only about 1/10th of 1% of these sorts of fishing expeditions (“discovery oriented exploratory research with massive testing” — usually nutrition and genetic studies with large numbers of variables) are reproducible.

As Sheldon and Gruber show in their book Genetic Explanations: Sense and Nonsense (2013) the entire theory of the case that single (or even multiple) genes code for a particular disease has unraveled in recent years.

Generally speaking, the Mendelian understanding of genes has been replaced in recent years by a completely different paradigm. British philosopher of science John Dupré at the University of Exeter argues in his book Processes of Life: Essays in the Philosophy of Biology (2012) that DNA is neither a blueprint nor a computer code for biological outcomes but rather a sort of warehouse that the body can draw upon for a range of different purposes:

The assumption that identifiable bits of DNA sequence are even “genes” for particular proteins has turned out not to be generally true. Alternative splicing of fragments of particular sequences, alternative reading frames, and post-transcriptional editing — some of the things that happen [naturally] between the transcription of DNA and the formatting of a final protein product — are among the processes the discovery of which has led to a radically different view of the genome.... Coding sequences in the genome are therefore better seen as resources that are used in diverse ways in a variety of molecular processes and that can be involved in the production of many different cellular molecules than as some kind of representation of even a molecular outcome, let alone a phenotypic one (pp. 264–265).

The people who actually study genetics know that, at least when it comes to autism, genetic determinism is dead. But there is a fortune to be made from pretending otherwise. So the story that is sold to government and private foundations is that the “genes for autism” are out there somewhere just waiting to be found if only they will keep the research money flowing.

Government plays along with this ruse because funding genetics research keeps scientists away from studying toxicants which might threaten powerful interests. The result is an entire multibillion dollar research industry that produces hundreds and hundreds of peer-reviewed articles that never get us any closer to understanding autism causation or providing a cure.

As the search for an “autism gene” repeatedly failed, geneticists came up with a placeholder theory that they call “genetic dark matter” patterned after the dark matter in astrophysics that is said to make up most of the universe — that astrophysicists cannot explain or measure. The idea is that a gene for autism must surely exist but that they do not have the tools to detect it yet. This has kept the grant money going for now. But the entire scheme is untenable.

For more on the boondoggle of the mythical search for the “gene(s) for autism” please see my article, “Nearly everything that we’ve been told about genes and autism is wrong” (2025).

IV. FOUR LARGE EPIGENETIC STUDIES

CHARGE

The University of California, Davis launched the Childhood Autism Risks from Genetics and the Environment (CHARGE) study in 2003 to investigate environmental causes and risk factors for autism and developmental delay. It is led by one of the most respected and widely-published environmental epidemiologists in the world, Irva Hertz-Picciotto. CHARGE is a case-control study where researchers identify children age 2 to 5 with autism and compare them with similarly matched children without the diagnosis of autism. They have enrolled more than 2,000 autism families in their studies and produced foundational reports on the effects of:

• air pollution (e.g., particulate matter, nitrogen dioxide, ozone)

• pesticides (e.g., organophosphates, pyrethroids, carbamates)

• heavy metals (e.g., mercury, lead, cadmium)

• per- and polyfluoroalkyl substances (PFAS)

• polychlorinated biphenyls (PCBs)

• nutritional factors (e.g., folic acid, vitamin D)

• flame retardants (e.g., polybrominated diphenyl ethers – PBDEs)

• maternal metabolic conditions (e.g., obesity, diabetes) and

• volatile organic compounds (VOCs).

To date, CHARGE has generated 144 peer reviewed publications. But I recently discovered that none of their studies controls for vaccines (vaccinated vs. unvaccinated, number of vaccines, timing of vaccines, etc.) as a possible confounding factor — even though in many cases that information is available to them. The failure to control for vaccine exposures renders all of the CHARGE studies unreliable.

To be clear, all of the toxicants they study are a problem, can likely cause autism, and should be better regulated or banned. What I’m saying though is that one cannot measure the relative impact of each of these chemicals without including a variable for the potentially confounding effect of vaccines.

So for example, a brilliant CHARGE study, Shelton et al. (2014) found that mothers who lived within 1.5 km (less than 1 mile) of agricultural fields sprayed with various pesticides had elevated risks of autism in their offspring. But who is most likely to live that close to the fields? Farmworkers and other low income residents. So it is also possible that the children born to women who live closest to agricultural fields get lower quality vaccines through the Vaccines for Children Program and this explains the higher autism risk. Or perhaps these children were not vaccinated at all and the increased autism risk is entirely from pesticides. But we’ll never know the relative risk of each factor because Shelton et al. (2014) did not control for vaccination status.

Or take another example. Lots of CHARGE studies claim that supplementation with folic acid during the first month of pregnancy reduces autism risk. But vaccines and other toxicants can cause dysregulated folate metabolism. And for some of these women, supplementing with folic acid increases autism risk in their offspring because their bodies cannot convert folic acid to folate (see Raghavan et al. 2018). By failing to control for the number of vaccines taken by the mother before and during pregnancy we are unable to unravel the relative effects of genetic mutations, vitamin supplementation, vaccines, and pesticides.

Why would some of the best epidemiologists in the world spend so much time, money, and effort and then make a mistake this basic? The answer is pretty straightforward — the field of autism research is so polarized and politicized that everyone involved with these studies knows that if they include vaccines as a variable they would instantly lose all of their research funding and be blacklisted from future research funding. That one, principled, and scientifically necessary decision would immediately and permanently end their careers. So they avoid the variable that shall not be named even though this omission renders all of their work unreliable.

I would just add that all of these mainstream autism causation studies fail in a similar way — they engage in circular reasoning (the logical fallacy in which the premise of an argument assumes the conclusion to be true).

• The vaccine studies assume that vaccines are safe and effective so they never bother with a proper placebo group that might prove otherwise.

• The gene studies assume that genes are the cause so they just gather trillions of data points until they can find a spurious association (the gene studies don’t control for vaccination status even though the possible mutagenic effects of vaccine ingredients on DNA is an ongoing concern).

• And the epigenetic studies assume vaccines could not be a factor so they don’t control for them (in spite of the fact that some of the toxicants they are studying in the environment are the same toxicants being injected directly into children’s bodies).

CHARGE (and other epigenetic studies that I describe below) are following standard practice in epidemiology that typically does not consider vaccination status a confounding variable in examining environmental risk factors for autism. But that’s precisely the problem — standard practice in each of these research fields assumes away the question of vaccines rather than studying it. The political economy of autism causation research is such that these scholars will likely never fully understand the autism epidemic because they are prohibited from stepping outside the constraints of circular reasoning (not because they are bad people per se but because assuming away politically explosive problems is how these professions survive in the face of overwhelming corporate power).

MARBLES

In 2006, the UC Davis MIND Institute launched the Markers of Autism Risk in Babies – Learning Early Signs (MARBLES) study. MARBLES is a prospective longitudinal study for pregnant women who already have a biological child with autism. Information about each participant’s genetics and environment is collected through a number of sources, including:

• Blood, urine, hair, saliva, and breast milk, as well as through home dust samples, in order to obtain a comprehensive picture of the environment surrounding each pregnancy.

• They also conduct interviews with the mother and access medical records in order to uncover more information about any behavioral aspects or trends that may contribute to the development of autism.

• Mothers maintain detailed diaries tracking health symptoms, diet, and product use during and after pregnancy.

• They also conduct standardized assessments of the child’s development up to 36 months of age.

To date they have enrolled 460 pregnant women with an 84% retention rate. One branch of the MARBLES study produced 71 peer-reviewed publications. Another branch — that studied fecal microbiome, the fecal glycome, and measures of household environmental exposures in infants who do and do not subsequently develop autism — produced 80 peer reviewed publications.

With a study design that comprehensive one would imagine that they would be able to figure out autism causation fairly quickly. But once again, MARBLES studies do not control for vaccines (vaccinated vs. unvaccinated, number of vaccines for the mother and child, timing of vaccines, etc.) even though they have access to that information. The failure to control for these known and potentially large toxic exposures renders all of the MARBLES research unreliable.

When I was writing my doctoral thesis I was very impressed by epigenetic studies including MARBLES because they were so complex and looked at toxicological variables that most mainstream scientists lacked the fortitude to study. I read as many as I could and included detailed summaries in my thesis. But now that I know that they never controlled for vaccines I find these studies deeply troubling. MARBLES is a prospective study that follows women who already had one child with autism through a subsequent pregnancy and they never gave these women informed consent because they did not discuss with them the dangers of vaccines. For researchers to then turn these children — many of whom developed autism because of this lack of informed consent — into data for their peer-reviewed published papers, I believe violates the Hippocratic Oath, the Declaration of Helsinki, and the Nuremberg Code.

SEED

In 2007, the CDC launched the Study to Explore Early Development (SEED) — a multi-site, case-control study to identify risk factors and early indicators of autism spectrum disorder and other developmental disabilities in children aged 2 to 5 years. SEED has enrolled over 4,500 families, including more than 1,500 children diagnosed with autism, across multiple phases of the study. The study uses parental questionnaires, clinical assessments, biospecimen collection, and medical record reviews to gather data on genetic, environmental, and behavioral factors that may influence autism risk. The budget was over $5 million a year and the study is still ongoing. To date, the SEED study has produced 54 peer-reviewed publications. None of the SEED studies control for vaccines (vaccinated vs. unvaccinated, number of vaccines for the mother and child, timing of vaccines, etc.) even though they have access to that information. The failure to control for these known and potentially large toxic exposures renders all of the SEED research unreliable.

EARLI

In 2008, the NIH and Autism Speaks launched the Early Autism Risk Longitudinal Investigation (EARLI) study — a multi-site prospective cohort study aimed at identifying environmental and genetic factors contributing to autism spectrum disorder. It enrolled over 260 pregnant mothers who already had a child with ASD, following the younger siblings through age 3 to examine possible environmental risk factors and genetic contributions for autism. The consortium includes Johns Hopkins University, UC Davis, Drexel University, the University of Pennsylvania/Children’s Hospital Philadelphia, and Kaiser Permanente Northern California.

One branch of EARLI (primarily looking at diet, nutrition, and phthalate exposures) produced 39 peer-reviewed publications; another branch (primarily looking at industrial air pollution and exposure to heavy metals) produced 40 peer-reviewed publications; and a third branch (primarily looking at air pollution from freeways and diesel-powered trucks) produced 9 peer-reviewed publications. But none of these studies controlled for vaccines (vaccinated vs. unvaccinated, number of vaccines for the mother and child, timing of vaccines, etc.) thus rendering all of the EARLI results unreliable.

The best case I can make for these large epigenetic studies is that the researchers assume that everyone is vaccinated and everyone got the same vaccines at the same time so they don’t need to include that variable. None of that is true, but just for the sake of argument let’s pretend that the researchers believe this. The large epigenetic studies then measure the harms from other toxicants in addition to the base rate that includes the fact that everyone is vaccinated. But that’s not necessarily true either. There are likely synergistic effects between various toxicants, vaccines, and systems in the body (endocrine, immune, digestive, etc.) so we cannot know the relative harms from these other toxicants without knowing what vaccines the person has already received.

Anything that causes an immune activation event — an infectious disease, a toxicant, or a vaccine — can cause autism. But research from Thomas and Margulis (2016) shows that the autism rate in children with no vaccines is 1 in 715 and the autism rate in vaccinated children is 1 in 31. So these large epigenetic studies that fail to control for vaccines can help explain the 1 in 715 autism cases but they are unlikely to help us stop the autism epidemic unless they radically change their protocols.

One last note on this section: three large gene studies described above (ASC, SSC, and SPARK) share their data with the National Database for Autism Research (NDAR) which in turn shares its data with the Environmental influences on Child Health Outcomes (ECHO) Program. The four large epigenetic studies described here (CHARGE, MARBLES, SEED, and EARLI) all share their data with ECHO as well. Access to ECHO is controlled through the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Data and Specimen Hub (DASH). But gatekeepers at DASH make it nearly impossible for independent researchers to access the data (I’ve applied repeatedly and been turned away every time). So American taxpayers have spent several billion dollars generating autism data and the public cannot get access to it even as the autism epidemic grows larger every year.

V. SO THEN THAT LEAVES US WITH A MUCH NARROWER SET OF STUDIES FOR UNDERSTANDING AUTISM CAUSATION

The key study that helps us to understand the relative impact of the different toxicants that contribute to causing autism was led by Sally Ozonoff at UC Davis and it was published in 2018. Using a brilliant study design she showed that up to 88% of autism cases are characterized by autistic regression — the child was developing normally and then suddenly over the course of hours, days, or weeks the child lost eye contact, speech, and the ability to socialize with others. This suggests an acute toxic exposure and we now have eyewitness testimony from hundreds of thousands of parents that the acute toxic exposure that preceded the autistic regression was a “well baby” vaccine appointment with a pediatrician.

The holy grail in autism research is to find vaccinated vs. unvaccinated studies. Thankfully there are now six good studies that we can rely on.

GALLAGHER & GOODMAN (2008 & 2010)

Gallagher and Goodman (2008), using data from the National Health and Nutrition Examination Survey 1999–2000, found that boys who received all three doses of the hepatitis B vaccine (n = 46) were 8.63 times more likely (CI: 3.24, 22.98) to have a developmental disability including autism than boys who did not receive all three doses (n = 7).

Gallagher and Goodman (2010), using data from the National Health Interview Survey 1997-2002, found that boys “who received the first dose of hepatitis B vaccine during the first month of life had 3-fold greater odds for autism diagnosis (n = 30 with autism diagnosis and 7,044 without autism diagnosis; OR = 3.002; CI: 1.109, 8.126)” as compared with “boys either vaccinated later or not at all” (p. 1669).

And that’s just the effect of one shot. No one knows the effect of doing that 76 more times but that’s what’s recommended by the CDC Child & Adolescent Vaccine Schedule.

MAWSON (2017A & 2017B)

Anthony Mawson was a visiting professor of epidemiology at the Jackson State University School of Public Health with a thirty-year career in epidemiology and a long publishing track record including two publications in The Lancet. In 2017, Mawson and his co-authors designed “a cross-sectional survey of homeschooling mothers on their vaccinated and unvaccinated biological children ages 6 to 12” and they worked with the National Home Education Research Institute, a homeschool think tank, to implement the study. They obtained results for 666 children of which 405 (61%) were vaccinated and 261 (39%) were unvaccinated. The study controlled for race, gender, adverse environment (not defined), antibiotic use during pregnancy, preterm birth, and ultrasound during pregnancy.

As one would expect, they found that vaccinated children were significantly less likely than the unvaccinated to have had chickenpox (7.9% vs. 25.3%; OR = 0.26; CI: 0.2, 0.4) and whooping cough (pertussis) (2.5% vs. 8.4%; OR = 0.3; CI: 0.1, 0.6).

The results for chronic illness were a different story. Vaccinated children were significantly more likely than the unvaccinated to have been diagnosed with

• a learning disability (5.7% vs. 1.2%; OR = 5.2; CI: 1.6, 17.4);

• ADHD (4.7% vs. 1.0%; OR = 4.2; CI: 1.2, 14.5);

• autism (4.7% vs. 1.0%; OR = 4.2; CI: 1.2, 14.5);

• any neurodevelopmental disorder (i.e., learning disability, ADHD or ASD) (10.5% vs. 3.1%; OR = 3.7; CI: 1.7, 7.9); and

• any chronic illness (44.0% vs. 25.0%; OR = 2.4; CI: 1.7, 3.3) (Mawson et al. 2017a).

Mawson, Bhuiyan, Jacob, and Ray (2017b) conducted a separate analysis of the data on preterm children (aka “premies”), vaccination status, and health outcomes. The authors found:

• No association... between preterm birth and neurodevelopmental disability [NDD defined as learning disability, ADHD, and/or ASD] in the absence of vaccination.

• Preterm birth coupled with vaccination increased the odds of NDD by more than five-fold as compared to non-preterm children who were vaccinated (48% vs. 8.9%; OR = 5.4; CI: 2.5, 11.9).

• Preterm birth coupled with vaccination increased the odds of NDD by more than twelve-fold compared to preterm birth without vaccination (48% vs. 0%; OR = 12.3; CI: 0.67, 224.2, p=.024; but “not technically significant because no child in the sample with an NDD was both preterm and unvaccinated”).

• Preterm birth coupled with vaccination increased the risk of NDD by more than fourteen-fold “compared to children who were neither preterm nor vaccinated” (48% vs. 3.3%; OR = 14.5; CI: 5.4, 38.7).

If Mawson et al. (2017b) are correct, then the high rates of NDD amongst children born preterm may be due almost entirely to the effect of vaccination, rather than the early arrival.

HOOKER & MILLER (2021)

Brian Hooker at Simpson University in California and independent researcher Neil Miller (2021), using survey data from respondents associated with three medical practices in the US, compared vaccinated children to unvaccinated children for the incidence of several chronic health conditions including autism. Vaccinated children were significantly more likely than unvaccinated children to be diagnosed with:

• severe allergies (OR = 4.31, 95% CI 1.67 - 11.1),

• autism (OR = 5.03, 95% CI 1.64 - 15.5),

• gastrointestinal disorders (OR = 13.8, 95% CI 5.85 - 32.5),

• asthma (OR = 17.6, 95% CI 6.94 - 44.4),

• ADHD (OR = 20.8, 95% CI 4.74 - 91.2), and

• chronic ear infections (OR = 27.8, 95% CI 9.56 - 80.8).

Vaccinated children were less likely to be diagnosed with chickenpox (OR = 0.10, 95% CI 0.029 - 0.36). But that’s a bad trade to make (increases in lifelong chronic illnesses in return for a decrease in a temporary rash).

The findings in this study on the relationships between vaccination and breastfeeding status and the relationship between vaccination and birth delivery status are particularly shocking:

Children who were “vaccinated and not breastfed” had a more than 12-fold higher risk of autism (OR = 12.5, p < 0.0001).

Children who were “vaccinated and delivered via cesarean section” had a more than 18-fold higher risk of autism (OR = 18.7, p < 0.0001).

These are the highest odds ratios I’ve ever seen in any study of autism causation. In a just world the findings from this study would have been front-page news across the country and immediately led to Congressional hearings and regulatory action against vaccine makers, formula makers, and obstetricians/hospitals with high c-section rates. But because the mainstream media and the political system in the U.S. are completely captured by Pharma this study received little mention at all.

MAWSON & JACOB (2025)

Anthony Mawson and Binu Jacob returned with another groundbreaking study in (2025). The study population comprised children born and continuously enrolled in the Florida State Medicaid program from birth to age 9. The analysis of claims data for 47,155 nine-year-old children revealed that:

1. vaccination was associated with significantly increased odds for all measured neurodevelopmental disorders (NDDs);

2. among children born preterm and vaccinated, 39.9% were diagnosed with at least one NDD compared to 15.7% among those born preterm and unvaccinated (OR = 3.58, 95% CI: 2.80, 4.57); and

3. the relative risk of autism spectrum disorder increased according to the number of visits that included vaccinations. Children with just one vaccination visit were 1.7 times more likely to have been diagnosed with ASD than the unvaccinated (95% CI: 1.21, 2.35) whereas those with 11 or more visits that included vaccinations were 4.4 times more likely to have been diagnosed with ASD than those with no visit for vaccination (95% CI: 2.85, 6.84).

We know what’s causing the autism epidemic. The bloated, unscientific, profit-driven CDC vaccine schedules are causing the autism epidemic. The U.S. must immediately shift to a science-based, individualized, N-of-1 approach to immunization, with no liability protection for vaccine makers or the medical profession, and only those vaccines shown to produce more benefits than harms allowed on the market.

VI. CONCLUSION

Mainstream studies that attempt to prove that vaccines do not cause autism are all invalid because they do not have a proper unvaccinated control group.

The over two billion dollars spent searching for the “gene(s) for autism” has not been a good investment — other than to definitively rule out genes as the primary driver of the epidemic.

The large epigenetic studies are somewhat better designed and show courage in investigating toxicants made by powerful industries. Unfortunately their failure to control for vaccination exposures renders all of their conclusions unreliable.

So that leaves us with six very good vaccinated vs. unvaccinated studies that show that vaccines cause autism. Vaccination in general seems to increase autism risk about 4-fold (the range across these six studies is 3.002 to 8.63). Vaccinating premies (OR = 14.5), vaccination in the absence of breastfeeding (OR = 12.5), and vaccination + c-section delivery (OR = 18.7) causes autism risk to skyrocket. That’s what’s causing the autism epidemic, according to the best available scientific evidence.

The takeaway from all of this is that the entire field of autism research is a shambles. Parents of autistic children are spending what little money they have to fund proper scientific research while corporations, foundations, and the government use their considerable power to cover up the causes of the epidemic.

The good news is that tens of thousands of parents appear to have figured it out. The best available scientific evidence suggests that we can stop the autism epidemic by only allowing beneficial vaccines on the market (a couple of live virus vaccines) and giving them, if at all, under conditions of informed consent at later ages when the body’s immune system can respond appropriately. Reducing the over-use of c-sections and birth drugs and supporting breastfeeding are also likely to produce large reductions in the autism rate. Somewhat smaller but still significant reductions in the autism rates are also likely through reducing all toxic exposures (including air pollution, pesticides, endocrine disruptors, other pharmaceuticals, etc.) for everyone.

Here’s the entire story in one infographic:

You can also download it as a PDF:

Mapping The Entire Field Of Autism Causation Studies

128KB ∙ PDF file

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Update, May 22, 2025:

An astute reader pointed out that there are a handful of independent studies of other toxicants in addition to the studies I’ve described above. This is true and I covered them in my thesis. But I will mention a few of them here:

Palmer et al. conducted a couple of fascinating studies on coal fired power plants and autism (2006 and 2009). Like the pesticide study I mentioned above, the failure to control for vaccines is a major limitation of these studies.

I like the two landmark EMF and autism studies by Martha Herbert and Cindy Sage (2013a and 2013b). These studies mostly focus on the impact of EMF on cells, so they cannot control for vaccines per se.

Stephen Schultz has done groundbreaking studies on Tylenol and autism (2008 and 2016) although I really wish those studies would have controlled for vaccines because that’s a major confounding factor. Bauer et al. (2018) is a systematic review of 9 Tylenol studies, although again, a failure to control for vaccines makes the effect sizes unreliable.

And then there are many independent studies outside the U.S. that are intriguing. For example, Larsson et al. (2009), in a study initially designed to look at allergies found that vinyl flooring in the parents’ bedroom was associated with an increased risk of ASD by 140% (OR = 2.4; CI: 1.31, 4.40). Vaccines were not controlled for and may be a confounding factor.

I imagine we could pull together another 50 to 100 studies of toxicants that increase autism risk. But in my experience none of them control for vaccines even though they are a major confounding factor and none will have odds ratios as high as the six vaccinated vs. unvaccinated studies described above.

Blessings to the warriors. 🙌

Prayers for everyone fighting to stop the iatrogenocide. 🙏

Huzzah for everyone building the parallel society our hearts know is possible. ✊

In the comments, please let me know what’s on your mind.

As always, I welcome any corrections.

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