Palko points to this link to a recent Pew Research Report which states, “Nearly two-thirds have high confidence in vaccine effectiveness, and about half trust their safety testing and schedule; Republican support for school vaccine requirements continues to slide,” and includes the above graph.
The focus of the online discussion was that Democrats’ views have remained stable while Republicans have shifted a lot, in a disturbing direction. From a political science perspective, this is an interesting example of partisan polarization of an issue attitude happening in real time.
But I was struck by something else: Even back in the pre-covid era, before vaccination became politically polarized, a sixth of Americans opposed vaccine mandates. Some of this must be from the question wording (“Parents should be able to decide not to vaccinate their children, even if that may create health risks for others,” rather than, say, “Schools should be able to require that children be vaccinated”), but I wonder if some of this is a sort of costless opposition. It’s possible to oppose a policy in principle, without any expectation that it will be repealed.
P.S. This post’s title harks back to the John Lennon classic, What joker put seven dog lice in my Iraqi fez box?
Although I find the opposition to vaccination appalling in light of the miracle and evidence of what vaccination has given us, I would be willing to exclude children that were not vaccinated from public schools. If parents are willing to make irrational but personal choices for their families, their choices should not be foist upon others. If you make libertarian choices, you should be willing to shoulder the burden of libertarian consequences.
The vaccine issue is more that some people want to keep funding (as the most egregious example) the current whooping cough vaccine that doesn’t work rather than figure out how to make one that does work. I.e., people who require low standards of evidence vs high.
Huh? I can’t find any source — not even wacko ones! — that suggest that whooping cough vaccine doesn’t work.
Possibly your search failed because it is uncontroversial. Wikipedia:
https://en.wikipedia.org/wiki/Pertussis_vaccine
The question here is what “work” means. That is, does the vaccine prevent you from being infected at all, or does the vaccine keep you from (or sharply reduce the chances of ) getting seriously sick. I get a flu shot every year to keep me from getting seriously sick.
The first paragraph of the linked Wikipedia article says it’s 70-80% effective.
Yep, the problem is a large group of people have been trained by marketing/propaganda to have such low standards. The goalposts move further away almost every year.
Then this low standard group knows deep down something is wrong. So they resort to a high emotional state when confronted with people who have higher standards.
Pertussis vaccine is known to wane pretty rapidly. Time from vaccination to when you can get the disease and it will cause serious consequences (for example uncontrollable coughing lasting 6 weeks or longer) was well modeled by an exponential distribution with a mean of just a few years if I remember correctly from what I read back in say 2010-ish. (I was trying to decide if I should get tdap, considering I had pertussis in 2000)
At the time tdap booster vaccine was recommended for a single lifetime dose in adults. I think now its every 10 years. To maintain good pertussis immunity the pertussis component probably requires every 2 or 3 year redose which we dont do probably for good reason. The most important population for pertussis vaccine is kids under 5, and they get multiple doses in that timeframe.
Acknowledgung the the pertussis vaccine is imperfect but works isn’t having low standards. It’s accepting the best currently available solution. We’d all love a 99 or 100% effective vaccine, but we’re not there yet.
The evidence is solid: the pertussis vaccine works. It’s not perfect. But it’s a lot better than nothing.
I would add to Daniel Lakeland’s excellent summary about pertussis immunization the fact that even having pertussis disease leaves only temporary immunity in its wake. For this reason, I am pessimistic that a better vaccine against pertussis is even possible.
The most important thing is to see that young children get immunized and get their immunization updated because they are the ones who can get seriously ill with pertussis. For older children and adults the disease is a really annoying and persistent nuisance, but generally not life-threatening.
Anon, I get it, when you said it “doesn’t work” you meant it “doesn’t work as well as some other vaccines work against their diseases.” That is not the plain-English meaning of “doesn’t work.” I’ll be less confused about your posts if you use words the way they are normally used!
As a general rule, immunisation against microbes that multiply in the respiratory mucosa does not prevent infection nor transmission. This applies to Pertussis, Covid, influenza and others. The problem is that vaccines given via the intramuscular route do not induce the same sort of immune response as natural infection via the respiratory mucosal route.
Pertussis infection kills on average 2 neonates per year in Australia (pop. 20+ million). In older people pertussis is just one of the pantheon of respiratory pathogens that assail us and is not particularly severe. Prolonged cough (up to 6 weeks) has been described but this can occur with other infections too. Over my 35 year career, most of the prolonged cough patients I have seen have tested negative for pertussis.
Unfortunately, immunity to everything wanes in the elderly.
TL;DR The pertussis vaccine has been over-hyped.
There are bundling implications here. Being firmly in the camp of science, all parents should have the right to make education and healthcare decisions for themselves and their children. This includes home schooling, and delayed vaccinations, among other options. The burden of proof for criminal neglect should be sky high – all men created equal and all innocent until proven guilty.
Schoolboards composed of (or elected by) parents should have the right to make decisions for the public schools. This includes some public health decisions; hopefully they will leverage health department advice. Other bodies govern for profit schools, religious schools, in an analogous fashion but only as supported by those who choose to pay for the institutions and parents who choose to send the children to them (with allowance for wards of the state as an exception).
Health departments have the right to make recommendations for local polities, like cities, but only to the extent they are accountable to elected officials who make policy decisions – which can include delegating time sensitive matters to the experts.
None of this should be controversial, yet it is made controversial by people who believe they, from a distance, should be able to overrule people and communities whom they hold in contempt.
What does that say about conflicts between parents’ right to choose, school board’s rights to set policies, and health departments’ right to make recommendations? It is easy to assert these rights – they are uncontroversial until they come into conflict. Unfortunately, conflicts between rights are the norm, with vaccination being an example.
By this logic, all people should also have the right to decide what side of the road they drive on, to be held accountable only after they cause an accident and are proven negligent beyond a reasonable doubt.
This is literally true today. You can literally go out today and start driving on the left side of the road in the US, you will quickly be stopped by the laws of physics and you will only be punished by the courts after a trial. 🤷♀️
No, the police may well stop you and issue a citation — a punishment— even if you do not cause an accident.
Phil, if you drive on the left side of the road you will be stopped by the laws of physics far sooner than any police in basically every case (maybe middle of the night drag racing or something is an exception)
So my point is that this is unlike the vaccine question where no laws of physics prevent you from going ahead and refusing vaccines. Even if you do get the disease most diseases aren’t anything like 100% fatal so you can then continue to go without the vaccine without physical laws preventing it, for years at a time. Drive on the wrong side of the road more than a few seconds and you’ll have a head on collision. The two situations are not particularly similar and the analogy doesn’t work well.
“Being firmly in the camp of science, all parents should have the right to make education and healthcare decisions for themselves and their children. ”
This sentence reads funky. I think you mean “[Me], being firmly…” vice asserting that *all parents* are firmly in the camp of science, no?
That that second interpretation doesn’t hold water.
I like your democratic view of things expressed locally, but the realities of that process are anything but smoothly executed.
My goal in responding is to spark a debate among statisticians about the state of the art in causal inference, but without inane binary political commentary. Three successive administrations have got COVID public health policy wrong because they do not yet understand the evidence they so painstakingly gathered. I’m hoping a reasoned, civil, professional discussion here might help shed some light and protect the public.
There is considerable evidence that any discussion of vaccines is the equivalent of discussing the thread count of various flak jackets while obliviously standing on a railroad track with a freight train approaching at high speed. Flak jackets are simply not designed to protect against that much high velocity metal. The vaccines may protect against a “natural” exposure infection rate, but their subtle benefit would be round-off error in comparison to a sudden massive injection of live virus into cells and bloodstream.
Any assessment of the effectiveness of ANY COVID-19 intervention, which did not control for the overwhelming effect of a billion or so nasopharyngeal swab procedures forcing inhaled SARS-CoV-2 virus, formerly safely trapped on the surface of the nasopharyngeal mucus and destined for relatively safe expulsion through the GI tract via mucociliary clearance (MCC), instead into direct contact with delicate epithelial cells and broken blood vessels, is quite simply and tragically wrong.
I would offer the following as evidence, for starters:
1) CDC COVID Data Tracker reveals that the time series of Weekly Positive Test Results provides an astoundingly precise forecast of Weekly COVID Deaths over a period of several years from 2020 to present, for all 10 HHS Regions and the US as a whole. Example below is HHS Region 4.
Granger Causality For:
Weekly Deaths = f((Weekly % Test Positivity) X (Test Volume) / 100)
(In plain language, Weekly Deaths as a function of Weekly Positive Tests)
F: 444.076253317656
p: 1.22814865610815e-59
Archived calculation in case you want to see the code, parameters and inputs:
https://www.freestatistics.org/blog/index.php?v=date/2025/Nov/05/t1762319148iuwknl699evb5of.htm/
************************************
2) CDC COVID Data Tracker also reveals that the time series of simple exposure to SARS-CoV-2 virus is not nearly as good a predictor of Weekly Deaths.
Granger Causality For:
Weekly Deaths = f(Weekly % Test Positivity)
(In plain language, Weekly Deaths as a function of a weekly estimate of actual cases (% Test Positivity x population), whether detected by test or not)
F: 86.3329567908082
p: 4.50647341707774e-18
citations:
Data:
CDC COVID Data Tracker (now defunct since a few days after I reported my findings to HHS, but still available on Internet Archive)
Bivariate Granger Causality, implemented in R:
Wessa, P. (2025), Free Statistics Software, Office for Research Development and Education,
version 1.2.1, URL https://www.wessa.net/
************************************
For a more complete description of the problem and hypothesis, including a proposed new technique for confirming the presence of, and then dis-entangling the relative contributions of multiple causes to a common outcome based on their rates of action, please see my comment on FDA Emergency Use Authorization protocols at:
https://www.regulations.gov/comment/FDA-2023-D-5365-0018
There are a couple of pre-print papers attached to the Comment, which go into a lot more detail with additional supporting evidence from other geographies and demographics, original unaltered data files from CDC, etc.
Cross-Correlation is just one pre-requisite for inferring causation in time series data. Granger Causality is more illuminating, perhaps, but I’m looking for any additional criteria you can suggest that could be used to either support or refute the hypothesis. Time ordered, non-spurious, etc.
Again, I’m hoping for a reasoned debate on the statistical methods employed, without political commentary. Preventing the next inadvertently manufactured pandemic will require a cross-discipline effort from many scientists and engineers. I am confident that American and global scientists are up to the challenge, provided that counterproductive binary politics can be set aside.
That said, it will not be easy. The confounding variable of policy-driven increased testing at every uptick in test positivity makes it confusing at first, but this confounding variable becomes manageable once you realize that the eventual sudden curtailment of widespread swabbing of near-random asymptomatic subjects around April, 2022 provided us with a (partial) control group for what amounts to a deadly and very badly designed public health experiment.
It seems like the entire argument here is built upon the difference in p values, with exponents of -18 and -59.
I say that because a lot of the other claims are kind of weird. The number of people who got nosebleeds from swab testing is similar to the number of people tested? The infections go from the nose to the blood to the lungs? (I thought Covid was not a blood infection?) The CDC really hid their data because you questioned it? Vaccines had little effect despite a fatality ratio of over 7 to 1 between unvaccinated and vaccinated? (Is this the conspiracy where the vaccine manufacturers are giving doctors kickbacks to fix the vaccine death numbers?)
One more point. The opposing viewpoints on Covid vaccines are not “political.” They represent the difference between sober (but not always correct) assessment of the most pertinent data, versus a tendency to seek indirect data that deviates slightly from expectations and form conspiracy theories around that.
Quote from above: “One more point. The opposing viewpoints on Covid vaccines are not “political.” They represent the difference between sober (but not always correct) assessment of the most pertinent data, versus a tendency to seek indirect data that deviates slightly from expectations and form conspiracy theories around that.”
https://www.youtube.com/watch?v=O0KBo95HsSM
Some questions:
Is what can be seen in the youtube video what you call “sober assessment” by people like Fauci and the drug companies?
In case you generally think events like those that can be seen in the youtube video concerning the COVID-19 situation and the advise given are an example of “sober assessment” and you reason something like “Well, the more information that became known, the better the ‘sober assessment’ was. That’s just science!”, would you reason it’s definitely a “sober assessment” to be a way more apprehensive and careful a possible next time given what “we have learned now” concerning things like vaccination advise and associated efficacy?
Can “follow the science” be seen or used in a way that resembles a donkey that follows a carrot on a stick that’s being presented in front of them by someone or something the donkey is unable to see? And if so, is it “political” to think and talk and ponder about the possibility that someone might be holding a carrot in front of the donkeys? And if not, are the donkeys and the people holding the carrot on a stick possibly the ones involved with “politics” in this example?
If you think about how many COVID-19 vaccinations and/or booster-shots (or whatever they are called) you personally had, were the decisions regarding these vaccinations based on the “scientific information” and “most pertinent data” that people like Fauci and the drug companies and newspapers and TV programs mentioned and shared?
Have you now, after all these years, drawn any conclusions about how and why things might be portrayed at a certain point in time, by certain people?
“Follow the science”, there’s the carrot
Now keep walking, and repeat it like a parrot
“Two weeks to flatten the curve”
That will bring them all to the next swerve
“Masks don’t work” is what they told you
Years ago that is, later on that was no longer true
“If you get vaccinated you get a free burger and fries”
Trust and believe them, other things are obviously manipulation and lies
Psychopaths, con-artists, and a little man with a big mouth
Collaborating, and working together, to create a road heading south
But they can’t do it without the parrot, the sheep, and the donkey
They can’t do it without those that think they know, but truly can’t see
They can’t direct, steer, dangle the carrot, and pave the way
Without the self-righteous, the “scientists”, and all others led astray
And before you get mad at me
Please take of your blinder and for once try and truly see
I’m not the one telling you what you should do or how to be
I’m just the one asking whether it might be important to be free
Another way to put it:
The NULL HYPOTHESIS, as advanced by FDA in their Emergency Use Authorization: “Test sample collection is perfectly safe from any imaginable medium or long term risk, with exactly zero possibility of accelerating an exposure into a serious infection – i.e. – ‘Long COVID’ or Death.” (Yes, I’m paraphrasing – they used a LOT more words to say it here: https://www.regulations.gov/document/FDA-2023-D-5365-0015)
Of course, any self-respecting biostatistician would immediately point out that no medical intervention is perfectly safe, and that the art of public health policy should be to rely upon evidence to find an acceptable balance between cost, risk and benefit. I would wholeheartedly agree.
Considering that the FDA’s NULL HYPOTHESIS is prima facie ridiculous, the challenge is to not to disprove it, but rather to quantify it. We need to answer the question, “How many SARS-CoV-2 exposures were accelerated by over a billion nasopharyngeal swab procedures, and how much were they accelerated?”
Normally, the FDA would insist that anybody else must answer this sort of question in great detail by conducting Randomized Controlled Trials.
I would claim that RCTs are no longer appropriate, because sufficient Observational data exists to demonstrate convincingly that these particular swabs have been killing roughly 1% of the test subjects who test positive, and causing “Long COVID” and other serious respiratory infections in many more, not to mention causing additional chains of transmission. (See my comments on excess deaths due to nasopharyngeal swabbing in the presence of other respiratory pathogens here: https://downloads.regulations.gov/FDA-2023-D-5365-0018/attachment_1.pdf )
I chose Dr. Gelman’s forum in the hopes of bringing this problem to the attention of some of the world’s leading experts on inference and imputation of cause based on statistical evidence. If there are other methodologies of assessing causality besides Granger, (Bayesian inference, stan, blme, mi, arm, mcsim, etc.) I would like to see them applied to the same data to test the hypothesis. I will need some help accomplishing this, and it’s better if others perform these verifications. I’m happy to help if needed.
I also want to have a permanent public record of the discussion, since it is obviously important, and too many have agreed with my analysis in private, but then done nothing about it due to career risk, etc. Epidemiologists are particularly sensitive to the career risk, many having loudly and repeatedly pushed for more and more of these “gold standard” tests. They have trouble admitting the possibility, even to themselves. Economic statisticians and pure theorists may be less conflicted.
If the CDC is allowed to sweep the evidence under the carpet, then there WILL be another manufactured pandemic. Next time, I would be unable to describe it as “inadvertently manufactured”.
You certainly have an ax to grind. I yield to your superior knowledge about these things as you seem to know a bunch of stuff that I do not. However, if you want credibility, then you have to earn it. You have this statement which you attribute to the FDA:
“Test sample collection is perfectly safe from any imaginable medium or long term risk, with exactly zero possibility of accelerating an exposure into a serious infection – i.e. – ‘Long COVID’ or Death.”
But the link you provide does not seem to contain that statement. If the FDA did say anything had “exactly zero possibility” I’d be inclined to go along with you, as that would be an absurd statement for them to make (sort of like the Harvard claim that “the replication rate in psychology is quite high–indeed, it is statistically indistinguishable from 100%”). But you have to point to where they actually said that. I read through the link you provided and I could not find that statement. So, if you want me to take your arguments seriously, let’s start by you linking exactly to where you say the FDA made that statement. Please.
Full context of my comment included the following: (Yes, I’m paraphrasing – they used a LOT more words to say it here: https://www.regulations.gov/document/FDA-2023-D-5365-0015).
In other words, not a direct quotation, but a condensed description of the effect of the following absolutely accurate example quote of the EUA itself from the Federal Register:
“As set forth in the EUA, FDA has concluded that: (1) SARS-CoV-2 can cause a serious or life-threatening disease or condition, including severe respiratory illness, to humans infected by this virus; (2) based on the totality of scientific evidence available to FDA, it is reasonable to believe that the product may be effective in diagnosing COVID-19 and that the known and potential benefits of the product when used for diagnosing COVID-19, outweigh the known and potential risks of the product; and (3) there is no adequate, approved, and available alternative to the emergency use of the product.” ref: https://www.federalregister.gov/documents/2021/07/23/2021-15680/authorization-of-emergency-use-of-certain-medical-devices-during-covid-19-availability
The problem is that FDA made a judgment about unknown “potential risks” being outweighed without any more justification than a few literature reviews of immediate adverse events requiring further intervention, without even considering medium and long term effects. Specifically FDA did not conduct Randomized Controlled Trials to quantify medium and long term “potential risks” of NP swab procedures on asymptomatic subjects. (Not that they should in future, now that there is ample evidence NP swabs kill people.)
Dictionary.com:
par·a·phrase
/ˈperəˌfrāz/
verb
verb: paraphrase; 3rd person present: paraphrases; past tense: paraphrased; past participle: paraphrased; gerund or present participle: paraphrasing
express the meaning of (the writer or speaker or something written or spoken) using different words, especially to achieve greater clarity.
I stand by the substance of my statement, but will allow that the form could have been more accurate, albeit at the expense being far less understandable and less useful as a concise NULL HYPOTHESIS.
Where we do seem to agree is the absurdity were FDA not to consider such “potential risks”, now that observational evidence of the effect exists.
For the sake of clarity, and as just one of many examples, I’ll “paraphrase” the interpretation of the Granger Causality analysis since a previous commentor also seems to have some questions.
The bivariate Granger causality test, as implemented in R at https://wessa.net/rwasp_grangercausality.wasp (replace the default values there with actual CDC data if you want to reproduce my results) provides a dimensionless output “F” which is a measure of the likelihood of causation. A larger value of “F” imputes a more likely causation. It is useful for comparisons between possible causes.
The bivariate Granger causality test also outputs a “p” value, which indicates the probability of an associated null hypothesis being true. The p values are exceedingly small in this case simply because the sample sizes are exceedingly large.
Comparing “F” values allows for assessing the relative likelihoods of causes.
In the case of HHS Region 4, for simple exposure to SARS-CoV-2, F= 86.3329567908082
For exposure to SARS-CoV-2, AND a positive test result F= 444.076253317656
In plain language, the Granger Causality test imputes with exceptionally high confidence that inhaled exposure to SARS-CoV-2 is quite likely a cause of COVID-19 death. Not really surprising.
What is absolutely shocking though, is that the Granger Causality test imputes with even higher confidence that the combination of inhaled exposure to SARS-CoV-2 AND a nasopharyngeal swab is about five times more likely to cause death.
As noted before, I consider this to be sufficiently compelling evidence that the FDA gravely erred in not immediately assessing this particular “potential risk” when I first reported it way back in 2022.
As noted before, I am open to considering any other evidence and/or statistical techniques that may be suggested to either refute or support the hypothesis that NP swabs are killing people by accelerating exposures into serious infections. I’ve been trying to refute my own hypothesis for several years and will continue to do so, but so far, I’ve only found additional instances of evidence and analysis that support it.
I am still hopeful that experts in imputing statistical causality in various fields will eventually weigh in with substantial critiques and suggestions for additional / better techniques. I’m aware that Granger Causation analysis is mostly employed in economic forecasting and neuroscience, but rarely, so far, in epidemiology. That is why I’m asking people like Dr. Gelman, etc. for help in identifying and applying other appropriate techniques to the same data for additional insight.
Also, if anyone can suggest a better forum for this discussion which is likely to focus a bit more on the substance of the statistical analysis that would be great.
I’m sorry, but nothing in what you say translates to the FDA saying that anything has an “exactly zero possibility.” On the basis of that alone, I am going to cease reading your lengthy comments. The other basis is that I don’t have the technical background to evaluate your comments, but they are failing to educate me and seem more like a biased presentation of your own position about a fairly technical matter. These are the types of comments that I don’t find add to my understanding, nor do I find them convincing. If others feel differently, then they can pursue, but I’m dropping this discussion now.