How well do you understand placebo effects?

“Placebo effect” is a term that almost everyone knows but few seem to understand. Misconceptions about placebo effects are rampant and usually center around the idea that a placebo effect occurs when you feel better because you thought a treatment would work. In reality, there are multiple types of placebo effects, many of which have nothing to do with whether or not you expect a treatment to work.

Understanding this is important, because misconceptions about placebo effects lead to erroneous arguments and poor medical decisions. These misconceptions are commonly manifested in the argument that, “a placebo effect is still an effect.” This argument is used as a justification for the continued use of treatments that have failed scientific testing because, according to it, even if the treatment only produces a placebo effect, that effect is still beneficial. As we will see, however, this argument is oxymoronic and completely falls apart once you understand what placebo effects actually are.

Another common argument asserts that a treatment must actually work because benefits have been seen in young children and/or pets who can’t possibly have expected the treatment to work. Likewise, I often hear people make statements like, “well I didn’t think it would work, but I still got better, so it can’t have been a placebo effect.” Both of these arguments are, again, based on the misconception that placebo effects simply mean getting better because you think you will get better. As we will see, the reality of the situation is far more complicated.

What are placebo effects?

You may have noticed that I keep saying “placebo effects” (plural). I’m doing that because the “placebo effect” is actually a collection of lots of different factors that we shove into a single category for convenience. To borrow a definition from Science-Based Medicine,

“A placebo effect is any health effect measured after an intervention that is something other than a physiological response to a biologically active treatment.”

In other words, “placebo effect” is a broad, catch-all term for any measured change in a patient that is caused by something other than an actual, biological effect of the treatment. This is an inherently wide definition, and there are lots of different types of placebo effects that contribute to that change.

Let me elaborate with an example. Suppose I think that diseases are caused by an electrical imbalance and shocking yourself with an electric current will cure you. So, I get people who are sick or in pain to come to me, I zap them, pronounce them healed, and they go on their way. Within a few days, many notice that they are feeling much better. Some may even find that real doctors run tests and conclude that their condition has improved.

Did my treatment work? Maybe, but we can’t actually conclude anything from those anecdotes because there are other possible explanations for that result. Let’s tally up some of those possibilities:

  • Biased reporting (i.e., people who feel better are more likely to go online and post about their miracle cures)
  • Spontaneous remission that has nothing to do with the treatment
  • People sought treatment when their symptoms were at their worst and, as a result, they would have felt better in a few days regardless (i.e., regression to the mean)
  • They made some other change in lifestyle, diet, work, etc. that caused the improvement
  • There were measurement errors or misdiagnoses by the doctors during the initial visit or the follow up
  • They feel better because they think they are supposed to feel better (the classic placebo effect most people think of)

anecdotal evidence anti-science

This is why anecdotes simply are not valid evidence of causation. If we actually want to know whether electrocuting someone (or any other treatment) works, we have to collect a large group of people, randomly assign half of them to receive the treatment while another half receives a placebo (without either group or, ideally, the doctors knowing who is in which group), and control for factors like age, sex, other health conditions, and other medications. When we do that, we will probably still find that there is a change in our placebo group over time. That change will be caused by some combination of factors like the ones listed above. Some people might feel better simply because they thought they should feel better. Others may have improved because of some other change. Others may have sought treatment when their symptoms were at their worse so they would have felt better over time regardless, etc.

All of those things are types of placebo effects, the sum of which gives the total placebo effect in that experiment. It is the background change in patients that has nothing whatsoever to do with an actual biological response to the treatment being tested. So, for the treatment to be effective, it must, by definition, produce an effect greater than the placebo effect. This why we do placebo controlled trials: to tell us whether the recovery rate from the treatment is greater than the background recovery rate without the treatment.

Do you see why that automatically makes statements like, “a placebo effect is still an effect” utter nonsense? The placebo “effect” is an experimental construct. It’s just a measure of the background noise in the system so that we can tell whether or not a treatment actually works. It is madness to try to claim that the background noise in the system is a legitimate therapy!

Regression to the mean

In case I haven’t made my point entirely clear, I’m going to focus for a minute on one of the most common types of placebo effects: regression to the mean. That is a fancy term that basically just means that things usually return to their normal state over time even without intervention (think of it as “return to the average”).

Chronic pain provides a good example of this (see figure). People with chronic conditions typically have good days and bad days. There are days where they are in lots of pain, and those days eventually give way to days with less pain. If we plot the pain over time, we get a wave-like graph with pain oscillating around an average value. Thus, if you start at any given point on the graph and wait long enough, it will eventually go back to the average value (i.e., it regresses to the mean). Critically, times with the worst pain are, by definition, followed by times with less pain. In other words, anything you do when the pain is at its worst will inherently eventually be followed by days with less pain.

This is where things become important for understanding placebos (and anecdotes). People are much more likely to seek treatment (including trying unconventional treatments or enrolling in a clinical trial) when they are experiencing the worst symptoms, but, as we’ve just established, they would have felt better several days or weeks later regardless of the treatment simply because of regression to the mean!

regression to the mean

Chronic pain provides a good illustration of regression to the mean. People with chronic conditions tend to have some good days and some bad days that oscillate around an average (mean) value. Thus, from any given point on the graph, if you wait long enough, the condition will eventually return (regress) to the average value.

Look at the figure for a second and imagine you are the person on day seven. You’ve had a really rough week of severe pain. You’re now desperate enough to try anything, even an alternative treatment of which you are skeptical. So, you try my electric shock therapy, or acupuncture, or homeopathy, or anything else you can think of to relieve your suffering, and, by the next day, like a miracle, you are already feeling better. A few days later, you’re feeling better than you’ve felt in a long time. You might, naturally, conclude that the treatment actually worked. At a quick glance that seems like a perfectly reasonable conclusion, and it’s totally understandable that so many people fall for it, but as you can see in the graph, the treatment didn’t actually work! The condition simply regressed to the mean, and you would have improved even without it.

Conversely, people who are currently feeling good and are at the low points in the waves are much less likely to seek unconventional treatments. If they did, regression to the mean would often make it appear that the treatments made things worse. This disparity in when people are the most likely to seek treatment creates a strong bias towards treatments “working” in both anecdotes and clinical studies, and it is one of the many reasons why it is so critical to run placebo-controlled trials so that we can measure those background changes and test whether the treatment is producing a real improvement.

The common cold provides another excellent example. Countless times I’ve heard people insist that some quack treatment cures colds because they had a really bad cold, and nothing was helping, then they took this treatment, and in a few days, they felt way better. Well, of course they felt better in a few days; that’s how long colds last! Also, if they’d already been suffering for several days, then they were probably at the tail end of it anyway, so even a fairly rapid recovery after the quack treatment isn’t surprising. It is easily explainable once you understand regression to the mean.

My point here is two-fold. First, notice that regression to the mean has utterly nothing whatsoever to do with either getting better because you think you should get better or with an actual effect of the treatment. It is literally just what would happen if you did nothing. This is why arguing that a treatment is valuable even if it is “just a placebo” is madness. When something is studied and found to be no better than a placebo, things like regression to the mean are a part of that placebo effect being measured, and they are clearly not valid therapies.

Second, regression to the mean is responsible for a lot of anecdotes. People frequently tell me with great conviction about how they had suffered for a long time and nothing had worked until they tried X. They often say that they didn’t think X would work, but they became so desperate that they tried it anyway, and afterwards they felt better! As you can hopefully now see, that sort of situation is to be expected from regression to the mean. If people seek treatment when things are at their worse, there is no place to go but better.

To be clear, this doesn’t automatically mean that those treatments don’t work. Rather my point is simply that the anecdotes are not valid evidence that they do work. Science is all about eliminating possibilities so that you can be confident in the conclusion. We have to conduct properly controlled trials to actually test the treatments, and if the treatments fail those tests, we can then be confident that the anecdotes are from factors like regression to the mean, rather than from the treatment actually working.

Pets, children, and unbelievers

At this point, I want to directly address the arguments that, “it can’t have been a placebo effect because it worked on animals/children/someone who didn’t think it would work.”

I’ve described several types of placebo effects throughout this that have nothing to do with belief or a conscious awareness of what is going on (e.g., regression to the mean), and those are already sufficient to deal with these arguments, but for thoroughness, I want to bring up a few additional points.

The first is something known as placebo by proxy. Children and many animals (e.g., cats and dogs) are perceptive. The mood of people around them affects them, and those effects can go on to affect the outcomes of their treatment. So, if you take your dog or child to receive acupuncture (which is just a placebo btw), your dog or toddler might not expect it to work, but you do, and, as a result, your mood is likely to improve because you think your pet/child is receiving a valuable treatment. The fact that you seem more at ease and less worried makes your pet/child more at ease, which improves their symptoms. Again, to be clear, the acupuncture (or whatever treatment it was) did nothing. It was entirely your response that caused the apparent improvement.

A related problem arises because improvements in pets and children are often self-reported by the owners/parents. So, if you think the treatment works, you’re more likely to see an improvement that isn’t really there. That is human nature. If you think acupuncture works (for example), you are pretty likely to think your dog is limping less after receiving it simply because that is the result you expected to see. Our brains are pattern recognition machines, and while that serves us very well in some cases, it also makes us very prone to biases. This sort of bias in the reporting of outcomes is yet another type of placebo effect, and, again, it has utterly nothing to do with an actual improvement in the patient.

The point is simply that placebo effects absolutely can be at play for children, pets, and skeptics; so the fact that an anecdote relates to them does not make the anecdote reliable evidence of causation, nor does it mean that the observed result wasn’t a placebo effect.

It’s not “mind over matter,” and it’s not effective

As I bring this post to a close, I want to stress that none of these placebo effects are situations of “mind over matter.” They are not situations where people are actually getting better because of the placebo. I’ve been largely focusing on placebo effects that aren’t related to the patient expecting to get better, but I should explicitly state that those effects do exist as well. A patient that thinks they are receiving a useful treatment is more likely to report a reduction in some subjective symptoms, such as pain, but even in that subset of placebo effects, emphasis has to be placed on the word “symptoms.” They are not actually getting better; their brain is simply playing a trick on them to make them feel better. So no underlying condition has actually been treated (which is pretty ironic given how often the same people who tout placebo effects like to erroneously claim that “modern medicine doesn’t treat the underlying causes of illness”).

All of this makes it absurd to argue that a treatment is still beneficial even if it is “just a placebo.” As you can hopefully now see, that is a hollow argument. Placebo effects are not actual improvements. They are the background changes that are not caused by a biologically active treatment. They are, by definition, a lack of effect of the thing being tested. Indeed, for some types of placebo effects (such as regression to the mean) they are literally what would happen if you did nothing! So, passing off quack treatments as actual therapies in order to “elicit” a placebo effect is dangerous and unethical.

Further, even if you want to narrowly focus on the subset of effects that result in patients feeling better because they think they should feel better, it should be noted that real treatments can also generate that transient perception of an improvement. So why on earth should we recommend a quack treatment when we can recommend a real one?

Also, on that note, there are certainly things that can and should be done to increase the efficacy of real medicine. We know that things like good patient-doctor relationships improve how patients feel. So absolutely we should work on things like that in tandem with science-based medicine (indeed that is part of science-based medicine), but it absolutely does not mean that we should use discredited treatments and chase magic and wishful thinking in the vain hopes of evoking a placebo effect.

Note: Please read this post and the systematic reviews and analyses discussed therein before claiming that acupuncture actually works.

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No, those photos don’t disprove sea level rise/climate change

plymouth rock meme sea level cliamte change hoax

A popular example of the type of meme I’m talking about.

It is an indisputable scientific fact that the average global sea level is increasing. Nevertheless, numerous memes and posts on the internet claim to have photographic proof that sea level rise (and by extension, global climate change) is a hoax. These posts generally contain an old photograph of a shoreline next to a recent photo of the same shoreline, with similar water levels in both photos. Therefore, according to the purveyors of this misinformation, the sea level has not changed and global warming is not real. Checkmate, science nerds, right? Not so much.

There are many versions of this argument (particularly popular ones include the Plymouth Stone, Palm Beach Florida, and various bridges), but they all suffer the same fundamental problem, so there is no need to harp on specifics (with one exception discussed later).

The core problem here is that the photos don’t take into account several critical factors, such as tides. The sea level is not static. It goes up and down twice every day, in some places quite dramatically. Further, the timing of peak high and peak low tides shifts from one day to the next, and the magnitude of the tides changes throughout the year. This means that the sea level at any one location is constantly changing. As a result, two photos of the same spot at two different time points are completely meaningless. If, for example, the old photo was at high tide and the recent photo was at low tide, it is going to look like there was no change in sea level, but that’s clearly a bad comparison because the tides were different! You can’t just ignore the existence of tides.

meme climate change sea level sydney harbour old photo

Another example of the type of meme I’m talking about. Once again, tides were ignored.

Beyond tides, there are factors like storm surges and the ground itself raising or subsiding. Further, because of a wide range of factors, sea level rise is happening faster in some places than in others. All of these things have to be taken into account to actually measure long-term patterns in sea level change. So, just like for temperature, scientists use a massive array of recording stations and satellites and carefully factor in tides, storms, etc. so that they can see the long-term trends.

When scientists account for these factors, they find that on average, the global sea level is rising, and that rise is caused by anthropogenic climate change. Indeed, the most recent IPCC report (IPCC 2022) made the following conclusion (their emphasis):

“Global mean sea level (GMSL) rose faster in the 20th century than in any prior century over the last three millennia (high confidence), with a 0.20 [0.15 to 0.25] m rise over the period 1901–2018 (high confidence). GMSL rise has accelerated since the late 1960s, with an average rate of 2.3 [1.6 to 3.1] mm yr –1 over the period 1971–2018 increasing to 3.7 [3.2 to 4.2] mm yr –1 over the period 2006–2018 (high confidence).”

There are four important things to note from that:

  1. Scientists are highly confident. Scientists are a cautious bunch, and we reserve that terminology for cases where the evidence is extremely clear and compelling.
  2. Over the past 100 years, the sea level rose faster than at any comparable period in the past three millennia. So, to those who try to attribute all of this to natural cycles, no, this isn’t normal. We’ve looked at the natural cycles and they don’t explain what we are seeing now (details here).
  3. The change so far has been relatively small, about 20 cm (7.9 inches). That’s small enough that you might not notice it on an occasional trip to the beach (or when looking at old photos of shorelines and structures), but it is enough that it is already having impacts on coastal properties (McAlpine and Porter 2018; Moftakhari et al. 2015).
  4. The rate of rise is increasing. This is the really concerning part. Things are going to get really bad if we don’t act immediately and drastically, and old photos don’t change that fact.

“but the predictions have all been wrong!”

sea level rise skeptical science

IPCC predictions compared to our actual observations. Figure from the Copenhagen Diagnosis 2009See Skeptical Science for more information.

At this point, I can hear the people shooting, “but the models have all been wrong! What about all those doomsday predictions!? I thought New York was supposed to be under water by now?” This misinformation comes from a range of sources, none of which are the actual scientific studies. The actual predictions made in the peer-reviewed literature have been very accurate (more details here). Studies have compared the IPCC model predictions with subsequent observations and, guess what, the predictions were correct (Wang et al. 2021; The Copenhagen Diagnosis 2009).

You don’t even need to understand complex modelling or scientific jargon to see that the actual predictions by scientists do not match climate change deniers’ caricatures but do match our observations. Just read the executive summary (written in plain English) from the first IPCC report (the report was in 1990 and the summary was released in 1992).

“Under the IPCC Business-as-Usual emissions scenario, an average rate of global mean sea-level rise of about 6 cm per decade over the next century (with an uncertainty range of 3—10 cm per decade), mainly due to thermal expansion of the oceans and the melting of some land ice. The predicted rise is about 20 cm in global-mean sea level by 2030, and 65 cm by the end of the next century.”

Notice that they did not predict that all of Florida would be under water by now, nor did they forecast meters of sea level rise by 2020. They predicted 20 cm of rise by 2030 with 3–6 mm per year, which, you’ll notice, matches the observations I reported earlier, and before you baselessly accuse the IPCC of trickery, you can look at their work and read the studies they cited. The data are unequivocal. It is a simple fact that sea levels are rising and coastal flooding risk is increasing (Church and White 2011; Sweet et al. 2019).

So if scientists weren’t the ones making those inaccurate doomsday predictions, where did they come from? In some cases, the media is to blame, and honestly, I’m surprised that I have to say this because if there was one thing that I thought climate change deniers and I could agree on, it was that the media is often sensational and doesn’t report things accurately. News outlets are notoriously bad at getting the science right and love to latch onto unlikely worst-case scenarios and present them as if they are what most scientists are claiming is likely. This then provides fodder for idealogues who deliberately misrepresent the science for personal gain, and before you know it, the misinformation has been repeated so many times that people take it for granted that scientists predicted the complete demise of Florida by 2020 even though they actually predicted nothing of the kind.

An additional factor is that people simply fail to grasp the timescale of the predictions (and this can again get distorted). There certainly are models that predict that large parts of New York, Florida, etc. will be submerged by 2100 (if we don’t change our actions), but you can’t take a prediction for 80 years from now and say, “well it hasn’t happened yet, so the scientists are wrong.”

Likewise, I’m sure that if you dig around you can find one off statements made by various scientists, that turned out to be wrong. but don’t confuse those off the cuff remarks or the predictions of a few outliers for the actual predictions being made by the actual models in the scientific literature. Again, the actual IPCC predictions have been accurate (in some cases erring on the side of caution).

Please read this post before claiming that scientists predicted an ice age in the 70s (they didn’t)

“but when floating ice melts, the water level doesn’t increase”

It is usually around this point that I encounter a particularly comical counterargument. This one is generally stated as a simple experiment that you can do yourself to prove that climate change isn’t causing the sea level to rise. All you have to do is take a cup of water, put some ice cubes in it, mark the water level, then wait for them to melt. Once they have melted you will find that, lo and behold, the water level is unchanged. Therefore, according to those with degrees from Google University, climate change is a myth and the sea level isn’t rising.

It is true that as floating ice melts the water level is unchanged (but see note), but it is also a straw man fallacy.  Melting icebergs (floating ice) are not the cause of sea level rise. Rather, sea level rise is being caused by the thermal expansion of water as it heats up (i.e., warm water expands and takes up more space compared to cold water) and the melting of land-based ice (Frederkikse et al. 2020).

Note: Although the melting of floating ice does not change the water levels in freshwater, it can have an effect in salt water because of the difference in the density of salt and freshwater (sea ice is predominantly fresh). So melting sea ice does technically have an impact on sea levels, but that impact is quite small compared to the impact of melting glaciers on land and thermal expansion (Noerdlinger and Brower 2007).

Scientists aren’t stupid

As I’ve explained before, if you think that you have found something extremely obvious and simple that every scientist in the world has missed, you are almost certainly wrong and, honestly, are being extremely arrogant. I don’t say that to attack or belittle anyone. Rather, I am trying to get you to think rationally and engage in some basic plausibility checks.

Which one of the following actually seems more likely to you?

  1. Despite years of training and a lifetime spent doing research and studying the factors that affect sea level, all of the world’s scientists (tens of thousands of people from hundreds of universities, government institutions, etc. from all over the world) completely missed an extremely basic fact of physics, and you have completely overthrown decades of research with an elementary school science experiment involving nothing more than a cup, water, and ice cubes, or
  2. Your understanding of the topic is incomplete and scientists know more about their areas of expertise than you do

Believing option A is the very epitome of hubris. If you are intellectually honest, you have to acknowledge that option A is wildly implausible, and that should, at the very least, make you spend a few seconds googling the causes of sea level rise rather than going around pretending that all scientists are absolute idiots. It should make you ask questions like, “if the problem with climate change is this obvious, why aren’t scientists aware of it?”

Likewise, it is absurd to completely ignore a mountain of data collected by thousands of scientists from all over the world using cutting edge technology and sophisticated statistical methods simply because you found a black and white photo online. Really think about this. Does it honestly seem rational that all of that research is so hopelessly wrong that a simple photo will discredit it? Do you seriously think that all of the world’s scientists are that utterly incompetent? Do you really think that none of them bothered to go down to the shore and check? Really ask yourself, which is more likely, that essentially all of the world’s experts are hopelessly wrong, or the situation is more complicated than you realize?

Again, the answer to that question should be obvious, and it should make you do some basic fact checking. As I’ve said repeatedly on this blog, I’m not advocating for blind faith in authority (fact check everything), but you need to have some extremely good evidence before claiming that all of the world’s experts are wrong, and in cases like this, mere minutes on Google would be sufficient to explain why the experts are right and the memes of old photos are wrong.

Indeed, in a particularly laughable display of wilful ignorance, the Plymouth Rock photo has been among the more popular memes I’ve seen floating around, but that rock has, in fact, been moved multiple times! You don’t even need to know anything about tides to know that the claim being made in the meme is bogus, and that fact is easily discoverable to anyone who checks.

This is, in many ways, the most frustrating thing about the anti-science movement, in my experience. The arguments used against science are generally so laughably naive and childish that anyone could easily find and comprehend information explaining why they are wrong if they would only bother to look, but most people don’t bother to look. They see something that conforms to their preconceptions, so they blindly believe and repeated it without ever testing its veracity, thus forcing people like me to spend our days explaining that tides exist and that scientists are in fact aware of how ice melts.

Don’t go through life blindly believing things you agree with and dismissing things you disagree with. Be curious. Be intellectually honest and rigorous. Take the time to check the facts and look at the evidence before you decide what to accept and reject.

Recommended reading:

Related posts

Literature cited

  • Church and White 2011. Sea-Level Rise from the Late 19th to the Early 21st Century. Surveys in Geophysics 32:585–602
  • Frederkikse et al. 2020. The causes of sea-level rise since 1900. Nature 584: 393–397
  • IPCC 1992. First Assessment Report Overview and Policymaker Summaries and 1992 IPCC Supplement.
  • IPCC 2022. Fox-Kemper et al. Ocean, Cryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate
  • McAlpine and Porter 2018. Estimating Recent Local Impacts of Sea-Level Rise on Current Real-Estate Losses: A Housing Market Case Study in Miami-Dade, Florida. Population Research and Policy Review 37: 871-895
  • Moftakhari et al. 2015. Increased nuisance flooding along the coasts of the United States due to sea level rise: Past and future. Geophysical Research Letters 9846-9852
  • Noerdlinger and Brower 2007. The melting of floating ice raises the ocean level. Geophysical Journal International 170:145–150
  • Sweet et al. 2019. 2019 State of U.S. High Tide Flooding with a 2020 Outlook. NOAA Technical Report NOS CO-OPS 092
  • The Copenhagen Diagnosis 2009. Updating the world on the Latest Climate Science. Allison, et al. The University of New South Wales Climate Change Research Centre (CCRC), Sydney, Australia, 60pp.
  • Wang et al. 2021. Reconciling global mean and regional sea level change in projections and observations. Nature Communications 12
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Debunking 30 bad arguments about COVID/vaccines

The COVID era has been a golden age of misinformation. It has seen the development of innumerable false claims and shoddy arguments, and it has breathed new life into ancient anti-vaccine tropes. Indeed, I find it impossible to make any posts about this topic on social media without the comments immediately becoming a raging dumpster fire of falsehoods. The arguments are so innumerable that trying to debate them with someone quickly becomes an exercise in futility that feels like fighting the mighty hydra. As soon as one argument is debunked, several more pop up to take its place.

This article is my attempt to ameliorate that situation by compiling most of the common arguments I encounter into a single location where they can all be debunked in one fell swoop. Because there are so many of them, I will address each one only briefly and provide citations to the relevant studies as well as links to articles that go into more detail. To those fighting the good fight against misinformation, rock on, and I hope this article will make a useful addition to your arsenal. To those who arrived on this page because someone directed you here when you made one of these bad arguments, please actually look at the evidence. Please stop listening to your favorite politician, commentator, youtuber, fringe doctor, etc. and look at the actual evidence.

Many of these arguments are interrelated and somewhat redundant, but they are often presented as separate arguments, so I wanted to deal with each explicitly here. They are ordered roughly into the following categories:

  • 1–8 = Arguments about COVID risk/mortality rates
  • 9–13 = Arguments based on the novelty of the vaccines
  • 14–20 = Arguments about vaccine effectiveness
  • 21–23 = Arguments about the reliability of science
  • 24–30 = Miscellaneous: conspiracy theories, VAERS, anecdotes, etc.

With that out of the way, let’s do this.

and here we go

Bad argument #1: COVID isn’t dangerous

Reality: Yes it is; millions are dead

Over 5.5 million people have already died, including over 850,000 in the USA alone. Something that has killed millions of people in only two years is, by definition, dangerous. Indeed, COVID was the 3rd highest cause of death in the USA in 2020 (Murphy et al. 2021) and 2021 (only cancer and heart disease were higher), and during outbreaks, it spiked to the #1 slot (see graph here). So unless you are going to tell me that accidents, stroke, diabetes, Alzheimer’s, and every other cause of death that COVID beat aren’t dangerous, please stop making the insane claim that COVID isn’t dangerous. Finally, death is not the only possible negative outcome, and hospitalization, long-term effects, time off work, etc. should all be considered (Mitrani et al. 2020; Fraser 2020).

 Bad argument #2: 99.9% survive

Reality: That still means millions of deaths 

  1. The survival rate varies greatly among ages, populations, strains, etc. So a blanket number like this isn’t accurate or useful.
  2. That is still a high death rate, and it has resulted in millions of deaths (see #1).
  3. Diseases can be very dangerous to a population either by having a high mortality rate or by having a high infection rate (or both), and COVID has a very high infection rate. If you have two diseases, one of which has a 10% mortality rate but only infects 100,000 people, and the other of which only has a 0.1% mortality rate but infects 10,000,000 people, you end up with 10,000 deaths either way.

More details here 

Bad argument #3: People only die because of comorbidities, so the actual COVID death rate is very low/COVID death rates are inflated by comorbidities.

Reality: Comorbidities don’t change the fact that these people died as a result of COVID

Comorbidities are simply additional factors that contributed to a death, and their existence does not negate the critical role of COVID in those deaths. If someone with a blood clotting disorder is stabbed and bleeds to death, the clotting disorder will be listed as a comorbidity because it was a contributing factor, but it would be insane to argue that this death is “inflating stabbing mortality rates” or that “stabbing wasn’t really the cause of death, because they had a clotting disorder.” The fact remains that they would not have died at that point in time if it had not been for the stabbing, and something that would have prevented the stabbing would also have prevented their death. The same is true with COVID comorbidities. In most cases, these people would not have died at this particular point in time if it wasn’t for COVID. Further, a huge portion of people have conditions that predispose them to severe COVID and would count as comorbidities if they die (CDC: People with Certain Medical Conditions).

More details here. 

Bad argument #4: It’s no worse than the flu

Reality: Yes it is

In the United States of America, influenza kills between 12,000 and 52,000 people annually, with a total of 342,000 flu deaths from the 2010–2020 seasons (CDC flu data). In sharp contrast, COVID has already killed >850,000 Americans, and in 2020 alone, the USA suffered 377,883 COVID deaths (Ahmad et al. 2021), with an even higher number of deaths in 2021. In other words, COVID kills more people in a single year than the flu kills in a decade. So please stop with this nonsense that it is no worse than the flu. 

Bad argument #5: I’m young and healthy, so I don’t need a vaccine

Reality: You can still become seriously ill and/or spread it to others

Being young and healthy lowers your risk, but it does not eliminate it. There are thousands of previously young healthy people who have died of COVID, and thousands more who became seriously ill (see CDC data). Further, young healthy people can still spread it to those who aren’t young and healthy (see #).

Also see #25

Bad argument #6: I trust my immune system, so I don’t need vaccines

Reality: Your immune system is only as good as its training

Even a healthy immune system has to learn how to fight a novel disease before it can do so effectively. Vaccines simply train your immune system so that it knows how to fight a disease like COVID when it encounters the real thing. This argument is about like saying, “I trust the military, so I don’t think they need intelligence reports on the enemy.”

Details here

Bad argument #7: Humans have survived for thousands of years without vaccines

Reality: The species has lived, but millions of individuals have died.

Homo sapiens as a species has survived, but countless individuals died, and since their invention, vaccines have saved untold millions of lives. No one is saying that COVID is going to wipe us our as a species. Rather, we are saying that millions of individuals could be saved with the vaccines.

More details here

Bad argument #8: Maybe previous strains were dangerous, but Omicron isn’t

Reality: Omicron is less dangerous, but still dangerous

Early evidence does suggest that Omicron is less deadly than other strains, but that does not mean it isn’t dangerous. Further, the current data also suggest that it is more easily transmitted, which means that your total risk may still be high, because risk is determined by the combination of the probability of catching the disease and probability of serious injury or death if you catch the disease (see #2). Further, even a less-deadly strain can still have substantial impacts by flooding hospitals with thousands of infected patients, which is exactly what is happening. Indeed, the USA just set a new record for hospitalized COVID patients, and remember that deaths always lag behind infections and hospitalizations.

Bad argument #9: The vaccines alter your DNA

Reality: mRNA cannot alter your DNA, and this is not genetic engineering.

that's not how this works memeDNA is the master copy of your genetic material and is stored in your cells’ nuclei. Think of DNA like the original architectural plans for a building. To make proteins, that double-stranded DNA gets transcribed in single-stranded RNA, and the RNA is then transported to ribosomes which use it as the plans for making proteins. Think of RNA like the blueprints used at a worksite that have been copied from the master plans. Thus, mRNA does not alter your DNA, because that’s simply not what RNA does. Further, you get exposed to substantially more COVID mRNA during an actual COVID infection, and your body is already teaming with RNA from the millions of micro-organisms that live in and on you.

More details here

Bad argument #10: The vaccines are too new/rushed

Reality: No, they aren’t/weren’t 

  1. We have been studying mRNA vaccines for many years (e.g., this study [Fleeton et al. 2001] from over two decades ago, also see this review: Pardi et al. 2018). These studies include human trials, some of which followed patients for over a year (Craenenbroeck et al. 2015, Bahl 2017, Alberer et al. 2017, Feldman et al. 2019).
  2. These vaccines were developed quickly by using that existing knowledge, investing heavily in the vaccines, and streamlining the process by running different stages in parallel. All normal checks and criteria for approval were still met (i.e., they weren’t rushed).
  3. The key to determining safety and efficiency is sample size, not time, and because COVID is so prevalent, scientists were able to generate massive sample sizes extremely quickly (Polack et al. 2020, Mahase 2020, Qianhui et al. 2021, Barda et al. 2021b just to list a few). These are some of the largest studies in medical history, and the evidence they present is so comprehensive and compelling that we are well beyond the stage of reasonable doubt. Anyone who says that we don’t know enough about these vaccines is either ignorant of the evidence or is choosing to blindly ignore it.

More details here and here 

Bad argument #11: We don’t know the long-term effects

Reality: Yes, we do

No vaccine has ever caused a serious, unpredicted adverse event that only showed years down the road. That is simply not how vaccines work. Because vaccines train the immune system before being quickly eliminated, their effects happen quickly (within minutes or days, not years later). We now have way more than enough data to be highly confident in the safety of these vaccines (see #10). This concern is completely unjustified and has no scientific basis. Further, if we are going to play the game of fearing the unknown, it is far more likely that COVID itself will have long-term adverse effects than it is that the vaccines will.

 More details here and here 

Bad argument #12: My children and I aren’t lab rats and won’t take an experimental vaccine

Reality: The vaccines have already passed experimental testing

Again, these vaccines have been thoroughly studied using massive sample sizes (see # 10). They are no longer experimental. They have passed the experimental stage. So this argument is nonsense. It blindly ignores all of those studies.

Bad argument #13: Children and pregnant women shouldn’t be vaccinated

Reality: They are safer with vaccines

Hospitalization and death from COVID are less common in children, but they still happen, which is both tragic and preventable. The vaccines have been tested in children, and are safe and effective, resulting in 10x lower risk of hospitalization (Delahoy et al. 2021, Olson et al. 2022, Principi and Esposito 2022, Stein et al. 2022).

In contrast to children, pregnant women are actually at an increased risk of serious adverse events from COVID, but like children, the vaccines have been well-studied, and a large study (>40,000 participants) found that COVID19 vaccination is safe during pregnancy (Lipkind et al. 2022). 

Bad argument #14: The vaccines aren’t 100% effective

Reality: Nothing is 100% effective, but they are still very useful

This one is an anti-vaccer classic that has been around for ages. The reality is that almost nothing is 100% effective. Helmets, parachutes, seat belts, air bags, birth control, etc. are all less than 100% effective, yet clearly the are very useful. Risk is inherently about probabilities, not absolutes. So, when we talk about how well vaccines work, we are always talking about risk reduction, not risk elimination, and the vaccines do greatly reduce risk (see #10, 15, 16).

More details here and here. 

Bad argument #15: The vaccines don’t prevent you from getting COVID (breakthrough cases)

Reality: They reduce risk and severity

Again, almost nothing is 100% effective (see #14), but the vaccines reduce your risk. This has been borne out by study (Polack et al. 2020) after study (Mahase 2020) after study (Fowlkes et al. 2021) after study (Martínez-Baz et al. 2021). Further, even if you become infected, the vaccines dramatically reduce your risk of getting a serious infection, and the rates of hospitalizations and deaths are substantially lower among the vaccinated than among the unvaccinated (Martínez-Baz et al. 2021, Self et al. 2021, Tenforde et al. 2021). Indeed, the CDC data (COVID tracker) for October (the most recent complete month at the time I’m writing this; see update below) showed that, compared to vaccinated individuals, unvaccinated individuals were 5 times more likely to test positive for COVID and 14 times more likely to die from COVID (also see Yek et al. 2022)!

This argument is like saying, “car safety features like ABS brakes, seat belts, and air bags don’t prevent you from getting into a car accident.” Sure, they don’t completely prevent it, but some of them (e.g., brakes), make it less likely, and even if you are in an accident, they greatly reduce the risk that you will be seriously injured by the accident.

If you’ve ever had to do a risk assessment for a job, you know that risk involves both the likelihood of an event and severity if the event occurs.

Update 30-1-2022: The updated CDC data (going through December 25 2021) show that the unvaccinated are 13X more likely to test positive for COVID and 68X more likely to die from COVID, compared to people with three doses of the vaccine.

Bad argument #16: The vaccines don’t prevent you from spreading (transmitting) COVID

Reality: They reduce risk of transmission

Vaccinated individuals can spread the virus, but you have to be infected with COVID before you can spread COVID, and the vaccines greatly reduce your risk of becoming infected (see #15). Further, multiple studies (some of them quite large) have compared the COVID infection rates among family members of people who did or did not receive the vaccine, and exactly as you’d expect from herd immunity, infection rates were lower for the people with a vaccinated family member (Anoop et al. 2021, Geir et al. 2021a, Geir et al. 2021b, Singanayagam et al. 2021). So yes, breakthrough cases do happen (see #15) because nothing is 100% effective (see#14), but again, the risk is greatly reduced by the vaccines, and the data are unequivocal: vaccinating protects those around you. 

drunk driving analogy, vaccines, anti-vaccers

An example of inconsistent reasoning among anti-vaccers. Image via Refutations to Anti-Vaccine Memes

Bad argument #17: Most people who catch COVID are vaccinated

Reality: You have to look at ratios, not raw numbers

This claim is often untrue, but even when it is true, that is only because most people are vaccinated. We have to look at the rates not the raw numbers. By way of analogy, most car accidents involve sober drivers, but that doesn’t mean it is safer to drive drunk; it’s simply that most people drive sober, and we can see this when we look at the rates. Even so, when it comes to vaccines, the rates (infections per person) clearly show that the vaccines work and reduce risk (Polack et al. 2020, Mahase 2020, Fowlkes et al. 2021, Martínez-Baz et al. 2021, see #10 and 15).

More details here and here  

Bad argument #18: The vaccines are less effective against Omicron

Reality: They still help, and boosters largely restore effectiveness

Omicron is still too new for us to have a completely clear picture of this. Current evidence does suggest that the vaccines are less effective against omicron than they were against delta (particularly when it comes to completely preventing asymptomatic infection, but see #20 regarding boosters), but they current evidence also suggests that they still greatly reduce your risk of getting a serious infection that would require hospitalization. Indeed, a report that was just released by the UK Health Security Agency (2021) found that 3 doses of the vaccine were 88% effective at preventing hospitalization from omicron. Similarly, data from South Africa showed that even just two doses of the Pfizer vaccine resulted in 70% effectiveness at preventing hospitalization from omicron (Collie et al. 2021).

See #20 on boosters  

Bad argument #19: If vaccines work, why do you care if I am vaccinated?

Reality: Because I care about others 

  1. Vaccines greatly reduce risk, but they aren’t 100% effective (see #14–16).
  2. Many people can’t be vaccinated due to medical issues, but when everyone else is vaccinated, they are protected by herd immunity.
  3. Outbreaks can overwhelm the medical system and prevent others from getting the treatments they need (multiple uninfected people have died because of this; Sabbatini, et al. 2021).
  4. When most people are vaccinated, the risk of new strains emerging is reduced because it is harder for the virus to replicate (which is where new mutations come from) and spread.
  5. Outbreaks hurt everyone by harming the economy, causing lockdowns and restrictions, interfering with travel, etc.

Bad argument #20: They said we’d only need two doses, but now it’s three

Reality: So what? Why is that a problem?

  1. Many routine vaccines require boosters, and we’ve always known that was a possibility with COVID.
  2. Boosters really aren’t a big deal (they are safe [Hause et al. 2021]), and they greatly increase vaccine effectiveness (e.g., Barda et al. 2021a which had a sample size of over 1 million).
  3. The primary reason they are being pushed so hard now is because the situation has changed (i.e., a new variant [omicron] emerged, which is something scientists have warned about all along). Data are still limited and being reviewed, but early results suggests that the effectiveness of 2 doses is greatly reduced, but a 3rd dose (booster) helps to restore effectiveness (Gardner and Kilpatrick 2021*, Garcia-Beltran et al. 2022, Muik et al. 2022 [* this is a preprint and has not been peer-reviewed]).

reductioBad argument #21: But science has been wrong before

Reality: This is a misunderstanding of how science works

Science is inherently the process of discrediting previous ideas, but in the modern era, previous ideas generally turn out to be incomplete more than entirely wrong, particularly for topics like vaccines where the evidence for their safety and effectiveness of vaccinees is overwhelming (see #10, 13–16). Further, the fact that scientific conclusions have been wrong before absolutely does not mean that you can blindly assume that the current evidence is wrong. If it did, you could reject any scientific result you like on the basis that science has been wrong before. You have to present actual evidence that the current conclusions are wrong, and there is simply no evidence that we are wrong about these vaccines.

 Details here and here.

Also, see posts here, here, and here regarding the nature of a scientific consensus.

See this post regarding the claim that most scientific studies are wrong. 

Bad argument #22: They laughed at Galileo and Columbus

Reality: This is a misconception and doesn’t mean you’re right

Galileo was mostly criticized by the church (i.e., people who were ignoring evidence because of ideology) not his fellow scientists. Also, critically, he had actual evidence, not conjecture, conspiracy theories, or a blind denial of evidence. Columbus, on the other hand was painfully wrong about the size of the earth (everyone already knew it was round) and just got lucky that there was another continent that Europeans didn’t know about. Finally, again, you must have actual evidence that current conclusions are wrong (see #21).

Details here and here and here.

Bad argument #23: There used to be a consensus that smoking was safe

Reality: No there wasn’t

This is a complete myth. Scientists have known since WWII that smoking was dangerous (Proctor 2012). Tobacco companies never managed to buy off more than a handful of doctors and scientists. What they had was a good PR team, not a scientific consensus (also see #21 and 22).

See posts here, here, and here regarding the nature of a scientific consensus.

See this post regarding the claim that most scientific studies are wrong. 

vaccine scheduleBad argument #24: I just don’t trust pharmaceutical companies/It’s all about money

Reality: It’s about trusting science, not “big pharma”

I don’t trust “big pharma” either, and I’m all for tight regulations and oversight, removing lobbyist, making drugs affordable, etc. I do, however, trust the science, a very large portion of which has been conducted by independent scientists who are not funded by pharmaceutical companies. The thing about science is that it is self-correcting. If pharmaceutical companies faked their data, other scientists would find out and report it. Keep in mind also that there are multiple competing pharmaceutical companies who would love to discredit each other

See posts here and here for more on the “follow the money” argument.

Bad argument #25: [insert personal anecdotes]

Reality: Anecdotes are pretty meaningless in science

The fact that event A happened before event B does not indicate (or even suggest) that event A caused event B (that’s known as a post hoc ergo propter hoc fallacy). At best, anecdotes can suggest things to be studied, but to actually determine causation, safety, or efficacy we need large properly controlled studies, and those have shown that these vaccines are safe and effective (see #10, 13–16). Anecdotes simply are not reliable evidence of causation.

Additionally, one specific anecdote I’d like to deal with is the argument that, “I got COVID and was fine; therefore, it’s not dangerous.” This is known as a survivorship bias: i.e., those who died are inherently not here to share their stories. The fact that you were fine does not alter the fact that millions weren’t. Similarly, if you are unvaccinated, before you go around boasting that you have an incredible immune system because you haven’t caught COVID, consider the fact that every single person who has caught COVID could have bragged about not catching COVID until the moment they caught it. In other words, contemplate the possibility that you simply haven’t caught it yet.

More details here and here and here.

Bad argument #26: There are tens of thousands of vaccine injuries and deaths on VAERS

Reality: Being reported in VAERS does not mean that the vaccine caused the problem

VAERS is a self-reported database that often contains all manner of absurdities. It is meant as an early warning system, and you have to be very, very careful when using it. The fact that something was reported in VAERS absolutely does not mean that the vaccine caused it. VAERS itself is explicit about that (see screenshot below [bold was in the original]; also see #25).

 More details here


Bad argument #27: But there are real risks from the vaccines

Reality: Yes, but they are rare, and the benefits outweigh the risks

Adverse events exist for all real medications. For vaccines, however, serious side effects are very rare, and the benefits from the vaccines far outweigh the risks from the disease. Risk assessment is an exercise in probabilities, and for almost any medicine, there will be some small subset who end up worse off because of it, but that doesn’t change the fact that your risk (i.e., your probability of injury) is lower with the vaccines than without them. As a result, vaccines save millions of lives, with COVID vaccines already having saved hundreds of thousands of lives (Mesle et al. 2021).

See studies cited in #10, 13–16

does not meanBad argument #28: Various conspiracy theories/FDA corruption

Reality: Science is about evidence, not conjecture and conspiracy theories

Conspiracy theories are endless, but they all suffer the same fundamental problems of not having any credible evidence and stating assumptions as if they are facts. No actual evidence has been presented to show that data were faked, FDA officials were bought off to push the vaccines, etc. Further, this argument ignores the facts that there are countries other than the USA and health/regulatory agencies from around the world are in widespread agreement about the safety and effectiveness of these vaccines. The research is being conducted by tens of thousands of researchers from hundreds of universities, companies, and agencies from around the world. Faking these data would require a truly insane conspiracy in which virtually all of the world’s scientists, health agencies, governments, and major pharmaceutical companies agreed to work together to lie and endanger the public. If that level of agreement among rival nations and countries sounds absurd, that’s because it is absurd.

Bad argument #29: It’s my choice/freedom. We shouldn’t have vaccine mandates

Reality: You don’t have the right to endanger others or ignore public health

This is a political argument, not a scientific argument, but I will briefly make three points. First, a large portion of the people I see making this argument also use the other arguments in this post, suggesting that they are letting political views override facts. Second, personal freedoms always end as soon as they endanger someone else, and refusing to vaccinate does endanger others (see #16, 19). This is why you have the freedom to drive a car, but not the freedom to drive recklessly or while drunk. Third, at least in most countries, the mandates simply place restrictions on the unvaccinated (e.g., requiring vaccination for a workplace), which is not the same thing as “forcing” someone (e.g., the government doesn’t “force” you to be sober, it simply restricts your right to drive unless you are sober; even so, you aren’t being “forced” to vaccinate, your ability to work certain jobs is simply being restricted to protect your coworkers).

Bad argument #:30 But I heard on Youtube, Facebook, Joe Rogan, Fox, OAN, some random guy with cool sunglasses sitting in a pickup truck, etc…

Reality: Those are not good sources

Please just stop. Stop with the deluded belief that you know more than the experts. Stop listening to unqualified people. Stop cherry-picking your experts.  Multiple massive studies have clearly showed that COVID is dangerous and the vaccines are safe, effective, and help protect you and those around you. Either you accept that evidence or you deny it.

 More on fact checking

 Related posts

Literature cited

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Joe Rogan and the problem of false balance

joe roganThis is going to be a relatively short post because I only have one simple point that I want to make. Namely, “balance” does not mean presenting conspiracy theories and nonsense alongside facts as if they are equivalent. This is a problem that pervades media coverage of scientific topics and seriously damages the public’s perception of scientific results.

To illustrate this, I want to talk briefly about Joe Rogan, because a Facebook post about him is what inspired this article. Full disclosure, I am, to say the least, not a fan of Rogan. In my opinion he is (to quote a friend of mine), “a dumb person’s idea of a smart person” (which to be clear, does not automatically mean that anyone who likes him is dumb). He frequently makes claims that are nonsense, and he uses his podcast to give a voice to all manner of quacks and conspiracy theorists. At this point, you may be expecting one of my lengthy debunks, but that’s not what I’m going to do here. Rather, I want to focus on the way people perceive his podcast, and why it is a problem.

The post that inspired this article (which unfortunately I did not save) pointed out the false claims that he spouts and the fact that he profits from popularizing these “controversial” positions. What interested me, however, was not the post itself, but rather the comments under it. Tons of people jumped to his defense, and the prevailing argument was (paraphrasing),

“Yes, he sometimes has ridiculous guests, but he also has lots of real scientists and experts on his podcast. It’s called balance, and it’s good to hear both sides.”

NO! That is not balance. We have this idea of “two sides” so deeply ingrained into us that we feel like we have to give credence to opposing views, even if one of them is utter nonsense, but that is an absurd and dangerous position to take. On many topics (particularly scientific topics), there aren’t two sides, and the fact that two people disagree doesn’t mean that there are two valid positions that both have to be treated as if they have merit.

Now, I can already hear people objecting that Rogan often doesn’t endorse the views of his guests. He’s just discussing the topics, asking questions, and letting people voice their views. That may sound innocuous or even good, but when those “views” are demonstrably false and, in the case of medical topics, dangerous, it becomes extremely irresponsible for someone with Rogan’s viewership to give a voice to those positions. Again, letting people talk about utter nonsense as if it is scientifically valid is not being balanced. Factually incorrect positions deserve only ridicule, and they should not be discussed as if they have merit.

If, for example, I am running a podcast and I invite a geologist on to discuss why the earth bulges in the middle and is a spheroid rather than a true sphere, it would be insane for me to “balance” that interview by inviting a flat earther to be a guest. That’s not balance or presenting both sides. One of those people is factually correct, and the other is factually wrong to a laughable degree, and it would be irresponsible for me to give the latter a platform from which to spread their half-baked, factually incorrect ideas.

So, no, when people like Joe Rogan treat conspiracy theorists as if they are making rational arguments, they are not displaying “balance” or presenting “both sides.” They are spreading demonstrable nonsense, plain and simple, and you should stop listening to them. Journalistic integrity does not mean giving everyone a voice regardless of the factual accuracy of what they are saying. In fact, good journalism should figure out what is factually correct before reporting it.

This problem is, of course, much broader than Joe Rogan, with the media presentation of climate change probably being the most obvious example. The evidence for anthropogenic climate change is utterly overwhelming. Scientific studies to the contrary are almost non-existent, and the handful that do exist are riddled with problems. There is no serious debate among climatologists on this topic. Anthropogenic climate change is a fact that has been verified by numerous different lines of evidence and the media needs to stop pretending that this is an issue with “two sides.” Balance does not mean giving equal weight to climate change deniers. That would be just as absurd as giving equal weight to a flat earther (see note 2).

This post has become a bit more of an unhinged, rambling rant than I had intended, so let me close with a simple request. Please stop supporting people like Joe Rogan and do not delude yourself into thinking that they are giving you “both sides” of a story or presenting you with “balanced” information. They aren’t, and it is dangerous to pretend that they are. We are living in a golden age of misinformation, and listening to people like Rogan only helps to perpetuate the spread of falsehoods.

Note 1: Obviously any scientific result can, in concept, be overturned with future evidence, but that does not automatically mean that two sides exist. If scientists uncover and publish new, valid evidence that the earth is flat or we aren’t causing climate change, then and only then should we treat those as serious propositions.

Note 2: Please read this article before you bring up the fraudulent Oregon Petition or any other standard climate change denier nonsense.

Posted in Global Warming, Uncategorized, Vaccines/Alternative Medicine | Tagged , , , | Comments Off on Joe Rogan and the problem of false balance

Future (“long-term”) side effects from COVID vaccines are extremely unlikely

Concern over unknown, future side effects is by far the most common reason I hear people give for why they aren’t vaccinating against COVID. At a quick glance, that may seem reasonable, but when you start really looking into the science, it quickly becomes clear that there is simply no reason to suspect that there will be dangerous long-term consequences of these vaccines. Indeed, based on everything we know about the immune system, vaccines in general, and these vaccines specifically, it is extremely unlikely that they will cause unknown, serious, wide-spread side effects in the future, and the known risks from COVID far outweigh the hypothetical risks from the vaccines.

In this post, I’m going to carefully go over the science and logic that allows us to be so confident in the long-term safety of these vaccines, but before I do that, I want to briefly explain who my target audience is here, namely, the “vaccine hesitant.” I am refereeing to the people who usually would not consider themselves “anti-vaccers” and would usually vaccinate themselves and their children but have been swept up in the maelstrom of misinformation and fear about the new COVID vaccines. If you are someone who is truly seeking information and trying to think for yourself, then please hear me out and seriously consider the arguments and evidence that I am going to present. Do not give in to the baseless fearmongering that is rampaging through the internet and media.

To that end, I want to point out right at the start that this tactic of stirring up fear of future, unknown, long-term consequences is not new or unique to COVID vaccines. It is straight out of the traditional anti-vaccine playbook. It is something I was writing about long before COVID, and the argument is just as flawed now as it was then. So, if you are someone who eschews the title “anti-vaccer,” but are avoiding the COVID vaccines because of the arguments about unknown, long-term effects, please realize that these are not new arguments that arose out of legitimate concerns specifically about COVID vaccines. Rather, stoking fear of future unknowns is a standard (and flawed) anti-vaccer tactic that they have been using for decades and are now dressing up and presenting as if it is a novel concern for COVID vaccines. Do not be fooled by this tactic.

This post is necessarily long, because there’s a lot to talk about in order to cover this topic properly, but, again, I have written this for people who are truly trying to think for themselves, and are truly seeking information. So if that is you, please read this carefully in its entirety.

Because of the length of this post, I will summarize key points in bullets below, before elaborating on each of them.

Summary: TL;DR

  1. mRNA vaccines have been being studied for over a decade (including human trials).
  2. Current COVID vaccines have been extremely well studied, with sample sizes of hundreds of thousands of people, and studies have been compiled into large meta-analyses/systematic reviews. Thus, the short-term risks of the vaccines are extremely well-documented, and the benefits outweigh the risks. The only “unknown” is about long-term effects; however…
  3. No vaccine has ever caused the type of widespread, serious side effect years down the road that everyone is afraid of.
    1. Nearly all side effects occur shortly after vaccination (see #2).
    2. The only example of a sided effect that showed up months later appear within a year (whereas we’ve been using COVID vaccines for over a year) and was rare. The vaccine benefits still outweighed the risks.
  4. Vaccines rarely cause long-term (future) side effects because they use low doses over a short time.
    1. Vaccines simply train your immune system.
    2. Vaccines are quickly removed from the body.
    3. Most vaccine components were well-studied, and their safety is known.
    4. mRNA:
      1. mRNA does not alter your DNA.
      2. mRNA is very quickly broken down and removed.
      3. mRNA in vaccines cannot make your body produce entire viruses.
      4. You are constantly exposed to mRNA from viruses (e.g., from colds)
      5. If you catch COVID, your cells will use viral mRNA to make proteins just like they do from the vaccine, but…
        1. Your cells will make entire viruses, not just a single protein.
        2. You will be exposed to far higher levels of mRNA.
    5. Side effects from immune stimulation will usually happen right away and will usually be worse from actual infection with COVID.
  5. A demand for long-term studies is meaningless unless you can justify why a particular length of time is needed.
    1. No matter how long something has been studied, it is always technically possible that an effect won’t show up until slightly after the length of that study.
    2. This is true for all medications, foods, minerals, vitamins, etc., yet we don’t fear most of them.
    3. Therefore, you must provide actual evidence or reasoning to think that a futre side-effect is actually likely.
  6. Focusing on a highly-unlikely, unknown, hypothetical risk from the vaccine while downplaying the very real and serious risk from COVID is bad risk assessment.
  7. Fears over unknown long-term effects of the vaccines are baseless. The burden of proof is on anyone claiming that the vaccines are dangerous.

Not as new as you might think

Before we go into the details of the COVID vaccines, we need some background information to put them in context, and I think it is important to point out that these vaccine technologies are not as new as people are often led to believe. Sure, these exact vaccines were developed recently, but mRNA vaccines have been being developed and tested for years. Thus, the underlying technology is well-studied.

Let me direct you to a review paper published in 2018 (before COVID) titled, “mRNA vaccines — a new era in vaccinology” (Pardi et al. 2018). This review covers over a decade of research on mRNA vaccines, including safety and efficiency trials on mice (Fleeton 2001; Geall et al. 2012; Magini et al. 2016), ferrets (Brazzoli et al. 2015), pigs (Schnee et al. 2016), monkeys (Brito et al. 2014), and yes, even humans (Craenenbroeck et al. 2015; Bahl 2017; Alberer et al. 2017). As you’d expect in a rapidly growing field, even more studies were published following that review, (but prior to COVID). Feldman et al. (2019), for example tested mRNA influenza vaccines in over 200 people, including following them for a full year after the vaccines to assess safety and effectiveness. Similarly, studies like Alberer et al. (2017) followed patients for a year prior to publishing and continued to follow them after publication.

To be clear, those human trials were small trials; my point is simply that we were able to develop these COVID vaccines so quickly not by rushing, but rather by utilizing a robust body of research that had already been conducted. All of the information was there, waiting to be applied to something like COVID.

The way that people (including politicians and the media) are talking about these vaccines, you’d think that they represent totally uncharted territory. Reading the comments on my page, people are acting like we have almost no knowledge about them and are shooting in the dark, recklessly plowing into the unknown, but that’s simply not true. In reality, we knew a ton about mRNA vaccines before COVID, and that should really change your perspective on these vaccines.

It is so easy to give into fear of the unknown, particularly when you are so constantly bombarded with people’s concerns. I don’t blame anyone for that;’ it’s human nature, but it’s important that we use logic and facts to overcome our base fears, and if you step back and start to rationally look at the wealth of knowledge these vaccines were based on (including human trials spanning a year or more), that really should paint these vaccines in a different light and help to alleviate those fears.

Note that I only cited a small handful of the studies that had been conducted prior to COVID.


What we know: proximate (short-term) side effects

The crux of the concern over these vaccines is fear of the unknown, so before we can talk about the unknown, we need to be clear on what we do know, as well as clearly defining what we mean by “unknown, long-term effects.”

There are basically two categories of effects we need to talk about:

  • Proximate effects (short-term) = effects that first occur shortly after vaccination
  • Unknown future effects (long-term) = effects that do not show up for months or years after vaccination (Note 1)

It is important to make this distinction, because I often find that people meander back and forth between these two without having a clear understanding of what is actually known or how it is known. So let me try to be as clear as possible: we have an extremely robust understanding of proximate effects, and the fact that the vaccines are new is 100% irrelevant.

Proximate effects are fairly straightforward to test. First, scientists conduct phase 1–3 human trials using a randomized, placebo-controlled approach, where they follow thousands of patients for several weeks following vaccination. Then, once the vaccine is released to the general public, scientists continue to monitor it for side effects using things like large cohort studies and case-controlled studies. As the sample sizes increase, so does our ability to detect increasingly rare events. With tens of thousands of participants, we can detect events that occur every few thousand people, but we will miss events that happen once for every 10,000 people. At a few hundred thousand people, we can detect events that occur once per tens of thousands of people, but will miss events that happen once for every 100,000 people, etc. (Note: numbers are approximations).

There are two critical points here. First, because our ability to detect rare side effects is dependent on sample size, as the sample size increases, any new side effects will, by definition, be increasingly rare. By the time we are into the millions (as we are with COVID vaccines) we aren’t going to suddenly find a new common serious side effect, because those would have been picked up at much smaller sample sizes.

Second, the novelty of the vaccines is completely and totally irrelevant. Because we are talking about events that happen within a few weeks of being vaccinated, it does not matter if the vaccines have been available for two months or two hundred years. The only thing that matters is the sample size (i.e., number of participants). Let me say that again (in bold), our ability to confidently know the rates of proximate side effects depends entirely on the sample size; the age of the vaccine is 100% irrelevant.

In the case of COVID, we were able to get these sample sizes extremely quickly because there were so many cases of COVID and governments dumped so much money into massive vaccine campaigns. All of the currently recommended vaccines passed their initial phase 3 trials with large sample sizes. For example, Pfizer used over 43,000 participants (Polack et al. 2020), and Moderna used over 30,000 (Mahase 2020).

Following those phase 3 trials, numerous large studies have been released. Indeed, so many studies have been conducted that we can do systematic reviews and meta-analyses. As explained here, these combine the data from multiple studies to look for overarching effects and are the highest level of scientific evidence. Qianhui et al. (2021), for example, included 87 different safety studies, and concluded that, “Available evidence indicates that eligible COVID-19 vaccines have an acceptable short-term safety profile.”

Yet more studies have been conducted since that review/meta-analysis, and some of them are truly massive. Barda et al. (2021), for example, compared over 800,000 vaccinated individuals to over 800,000 unvaccinated individuals to look at the rates of adverse events from the Pfizer vaccine as well as the rates of those same events in people who develop COVID. Not only did the vaccine have low rates of serious side effects, but, for most conditions (including myocarditis and myocardial infarction), the rates of those events were higher in people who caught COVID than in people who received vaccines (Note 2).

Figure 4 from Barda et al. 2021 showing the risk of adverse events from the Pfizer vaccine and from COVID itself. For each side effect, risk was calculated by by matching over 100,000 people who had been infected with COVID with people who were not infected with COVID (for COVID side effect rates), and matching several hundred thousand people who had received the vaccine with people who had not received it (for the vaccine rates). In most cases, COVID infection itself carries more risk of these specific side effects than does the vaccine. The most obvious exception (lymphadenopathy) is merely a swelling of the lymph nodes, which is not generally a serious condition.

Figure 4 from Barda et al. 2021 showing the risk of adverse events from the Pfizer vaccine and from COVID itself. For each side effect, risk was calculated by by matching over 100,000 people who had been infected with COVID with people who were not infected with COVID (for COVID side effect rates), and matching several hundred thousand people who had received the vaccine with people who had not received it (for the vaccine rates). In most cases, COVID infection itself carries more risk of these specific side effects than does the vaccine. The most obvious exception (lymphadenopathy) is merely a swelling of the lymph nodes, which is not generally a serious condition.

Other calculations of the rates of specific adverse events have had even large sample sizes. For example, the Israel Ministry of Health used over 5 million people to calculate the rate of myocarditis following vaccination. Similarly, in the USA, the CDC has several hundred million vaccine doses to use in its calculations.

The point is that we are extremely confident about the short-term consequences of the vaccines. It’s hard to overstate the massive volume of data we have. Barda et al. (2021), for example, is one of largest cohort studies I have ever read. It is larger than most studies on the safety of well-established vaccines that have been available for decades. Indeed, we have been able to quickly collect so much data that our knowledge of the short-term safety of COVID vaccines is equal to or greater than our knowledge of the short-term safety of many standard vaccines.

Again, to be 100% clear, the fact that the vaccines are relatively new simply does not matter for these short-term effects. Further, these studies aren’t the result of “rushing.” Rather, it is simply matter of vaccinating so many people so quickly that we were able to rapidly collect the data that would usually take years to accumulate. It is the size and volume of the studies that matters, and we have numerous truly massive studies unequivocally showing that serious side effects are rare and the benefits outweigh the risks.

To put it simply, the short-term side effects of the COVID vaccines have been thoroughly studied and are extremely well-documented. Scientifically, these vaccines are no longer experimental (with the exception of their application to young children, in some cases). They have already passed numerous experiments and the evidence is clear (Pfizer isn’t “experimental” legally either). Insisting that we haven’t studied the vaccines well-enough to know the short-term side effects is, at this stage, science denial.

See Note 3 regarding the supposed vaccine-related deaths and injuries reported in VAERS.


Vaccines don’t cause wide-spread, long-term adverse events

Now we can finally turn our attention specifically to the topic of unknown, long-term effects (which, remember, are effects that do not show up for months or years after vaccination; Note 1). I realize I took a long time getting here, but that background was important, because I have shown that we have a massive body of studies showing that the COVID vaccines have few serious side effects shortly after receiving them. Thus, the only way to doubt their safety without outright science denial is to raise concerns over presently unknown, long-term effects, but, as I will show, those concerns have no scientific merit.

The type of future long-term consequence that everyone seems so afraid of (i.e., the type that only manifests months or years down the road) is virtually unheard of from vaccines. I looked long and hard for examples of this occurring, and in the entire history of vaccines, I was only able to find one: Pandemrix, an H1N1 vaccine used in Europe for the 2009–2010 flu season was associated with an increased risk of narcolepsy that usually only manifested weeks or months after the vaccine. You can read more details on Thoughtscapism and Skeptical Raptor, but there are just three points I want to make.

  1. Depending on the study, the lag between vaccination and onset of narcolepsy was 0-242 days (median = 42; Partinen et al. 2012) or 0-360 days (median not reported; Nohynek et al. 2012). Pfizer and Moderna both began their phase 3 COVID vaccine trials on 27 July 2020 (~400 days ago) and received emergency use authorization (thus starting mass vaccination campaigns in the USA) in December 2020 (~260 days ago). Indeed, Israel had already administered over 1 million doses by the end of 2020. This means we are already past the time frame where we should have started picking up something comparable to the long-term effects of Pandemrix.
  2. As is so often the case with vaccine side effects, the disease they prevent (influenza in this case) also causes the same side effect.
  3. This side effects was rare (between 1 in 52,000 doses and 1 in 57,500 doses in England [Miller et al. 2013] and 1 in 16,000 in Finland [Nohynek et al. 2012; for unclear reasons, Finland had a high rate that could not be generalized to other countries), and the benefits of the vaccine still outweighed the risk.

That last point is really important, because for it to turn out that avoiding the COVID vaccines was the safer choice, unknown future side effects would not only have to exist, but they would have to be so common and so serious that they outweigh the enormous known benefits of the vaccines, and that is a situation that has never occurred for any vaccine (Note 4). For reasons that I’ll explain in the next sections, that’s simply not how vaccines interact with the body.

So, if you are avoiding the COVID vaccines because of a fear of unknown, serious, long-term side effects, ask yourself, is that fear really rational given that future, long-term side effects of vaccines are virtually unheard of, and there has never been a case where those side effects were widespread and outweighed the benefits of the vaccines?


Why vaccines don’t cause future long-term effects: Low dose, short exposure

Let’s now talk about why vaccine side effects nearly always show up shortly after vaccination. The type of long-term consequence we are talking about typically comes from one of two causes: a very large dose over a short time, or a small dose over a prolonged period of time. Vaccines don’t fit either of those categories. They are fundamentally different from most medications because they simply train your immune system before being quickly removed. Your own immune system is what provides a lasting benefit. Further, vaccines do this via low, non-toxic doses. Remember, the dose makes the poison. Everything, even water (Garigan and Ristedt 1999), is toxic at a high enough dose and safe at a low enough dose. So people who scream about “TOXIC CHEMICALS” in vaccines are ignoring basic chemistry. There is no such thing as a toxic chemical, there are only toxic doses, and the doses in vaccines are not toxic.

One of the most common arguments I hear people making to justify concerns over COVID vaccines is, “look at all the examples of drugs that were approved, then years later long-term effects were found.” Those examples are, however, nearly always for drugs that were taken repeatedly. It’s the cumulative effect that causes the risk (particularly for chemicals that persist in your body for long periods of time). Vaccines, in contrast, have limited exposure, and your body quickly eliminates them. Within a few days of receiving the vaccine, the vaccine itself has been totally eliminated from your body. The long-term protection comes from immune system memory, not from the vaccines themselves.

This is really important, because it means we don’t have a mechanism through which COVID vaccines would cause long-term harm. Because vaccines are a low doses given 2-3 times, we expect any consequences to happen quickly, which is exactly what we find. The most common side effects are things like soreness and moderate flu symptoms that start within a few hours or days of receiving the vaccine. These effects aren’t because the vaccine is “toxic” but rather because it is doing exactly what it was designed to do and stimulating your immune system. It’s that activation of your immune system that makes you feel unwell, but that activation is critical, because it is how your immune system learns to identify and fight COVID. Similarly, serious side effects from the vaccines, while rare, usually show up shortly after vaccination.

Side effects that don’t show up for months or years simply aren’t expected from vaccines because of how vaccines work. Nevertheless, in the following sections, let’s look more closely at the three main hypothetical sources of long-term harm: adjuvants/preservatives, mRNA, and immune activation.


#1: Adjuvants and preservatives

Vaccines typical consist of three basic components: a representation of the infectious agent (antigens, weakened viruses, virus particles, mRNA, etc.), an adjuvant that simulates the immune system and/or aids in delivery of the antigen, mRNA, etc., and preservatives (usually salts, metals, and sugars) to avoid contamination and stabilize the other components.

The later two categories (adjuvants and preservatives) are historically the things that anti-vaccers have targeted (e.g., the infamous, and completely false, accusation that thimerosal [ethyl-mercury] caused autism). These accusations have, however, never stood up to scrutiny. Vaccine components have been well-studied and are safe at the doses used in vaccines.

Specifically for COVID vaccines, their components differ from one vaccine to the next, but the safety of the components is well-known. Many of them use standard salts/metals that have been used in numerous previous vaccines and medications, and the non-mRNA vaccines usually use the adjuvants that have already been used in other vaccines.

Specifically for the mRNA vaccines, they use a different type of antigen known as a “lipid nanoparticle” (basically a small, fancy fat) that stimulates the immune system and serves as a delivery mechanism for the mRNA. These are new for a commercially available vaccines (because we’ve never had commercially available mRNA vaccines before), but that doesn’t make the nanoparticles themselves new, and there is a wealth of studies on them (including studies on other vaccines that have been being developed [see previous section on the history of mRNA vaccines]). See Hou et al. (2021) for an extensive review of the topic.

My point is simply that while the vaccines are “new,” their components have been well-studied, and there is simply no reason to think that they pose a long-term danger.


#2: mRNA

Now let’s turn our attention to the big one that has so many people worried: mRNA. At the outset, we need to be clear on what mRNA is and which it does. Your cells contain DNA stored in the nucleus. This provides the plans for your body and how it runs, and it is what you pass on to make your offspring when you procreate. For the actual day-to-day running of your body, however, it has to be transcribed into mRNA (aka “messenger RNA”). This is a single stranded copy of your double-stranded DNA. The mRNA can then leave the nucleus and go to the ribosomes (little protein factories in your cells) which translate the mRNA into amino acids which are then strung together and folded to form proteins. This is happing millions of times in your body each second. Importantly, the process does not alter your DNA. Your genetic code is unaffected. Think of it like taking a master copy of a recipe, photocopying it, then giving that photocopy to someone who then follows the instructions on it.

Viruses are actually pretty neat and replicate by tapping into this system. They can’t reproduce on their own. Instead, they insert their DNA or RNA into your cells and hijack your molecular machinery by making the ribosomes translate their RNA and build new virus (some viruses have DNA and require a transcription step, others [like COVID] store their genetic material as RNA).

The mRNA vaccines tap into this same process. They include a small fragment of the RNA from the SARS-CoV-2 virus (specifically for the spike protein), thus causing your cells to produce that spike protein. Your immune system is then stimulated to attack the spike protein, and in the process, it learns to attack the actual SARS-CoV-2 virus. Take a minute to stop and marvel at the ingenuity of this system, because it’s incredible.

There are several important points that need to be made here:

  1. This process does not alter your DNA. The viral mRNA does not get integrated into your DNA. This is not gene therapy. All that happens is protein production by ribosomes. Again, this is like handing your cells a photocopy of a set of instructions.
  2. mRNA is a very fragile, short-lived molecule. During my PhD, I worked in a laboratory where some people do RNA research, and they often joked that if you looked at the vials the wrong way the RNA would vanish. The point is that the mRNA from the vaccines very quickly breaks down and is removed from your body. Within a few days of receiving the vaccine, it is totally gone.
  3. The vaccines only contain the mRNA for a single protein. It is impossible for them to cause your body to make the full virus. They simply don’t contain that information.
  4. This is a process that is already happening constantly in your body. Right now, you almost certainly have some viruses (even if you are healthy), and those viruses are hijacking your cells with their RNA and forcing your cells to make virus for them. Indeed, unlike with the vaccine, they are making your body produce entire viruses, not just a single protein. Similarly, anytime you become infected with a cold, the flu, etc., your body is exposed to tons of viral RNA which it then translates into proteins (entire viruses)
  5. (related to #4) If you become infected with COVID, this process is going to happen anyway, but unlike with the vaccine, your cells are going to produce the entire virus, and, because the virus will be replicating, you will be exposed to substantially more viral RNA for a longer period of time.

That last point is incredibly important, because it means that any fears you have about the mRNA in the vaccine should be even greater for the virus itself. It doesn’t make any sense to simultaneously downplay the seriousness of COVID while fearing the mRNA in the vaccines, because if you catch COVID, you are going to be exposed to substantially higher doses of viral RNA!

As you can hopefully see, none of this lends credence to the idea that the vaccine will cause long-term effects. There is simply no mechanism through which the mRNA could cause long-term harm, and even if there was a concern over long-term effects, that concern would be even higher from actually catching COVID!


#3. Immune activation

The final way in which vaccines could, in concept, cause harm is as a side effect of the inflammatory immune response they stimulate. Indeed, that is the cause of most vaccine side effects. The vaccine sets off a cascade of immune responses, and sometimes your body gets caught in the crossfire, though this rarely causes serious problems.

Importantly, however, this happens while your immune system is being stimulated. This isn’t a pathway that we would expect to not cause any noticeable problems shortly after vaccination, then suddenly cause massive problems down the road. It could, in concept, cause a problem that starts shortly after vaccination and persists long-term, but it’s unlikely to cause problems that don’t appear until months or years later.

This is important because, again, problems that arise shortly after vaccination and persist aren’t what we are talking about. Those aren’t unknown. Rather, we already know that those are rare because we can detect them shortly after vaccination (see previous section on short-term studies).

Finally, as I’ve alluded to several times already, problems that arise as a result of immune activation should also arise as the result of actual infection with SARS-CoV-2, and they’d usually be expected to be worse or more common from an actual infection. Indeed, that’s exactly what Barda et al. (2021) found.

So, once again, it makes no sense to fear this as a consequence of the vaccine while downplaying the seriousness of COVID, because infection with COVID is more likely to cause this problem (see Note 2 on absolute risk).


How long is long enough?

This is an issue that I’ve written about several times before (e.g., here and here), but in short, the demand for long-term data becomes extremely problematic unless “long-term” is carefully defined and justified beforehand. We already have over a year of data on COVID vaccines, plus many years of data on mRNA vaccines more generally. For most scientists, based on everything we know, that is plenty long enough to be confident in the safety of these vaccines, but if you are going to claim that it is not long enough, the questions become “why?” and “how long is long enough?”

As I said earlier, anti-vacces have used this argument against vaccines for ages, and the problem is that they constantly shift the goal posts. If you show them a 3-year study, they say, “well maybe effects don’t show up until 5 years.” If you show them a 5-year study, they say “well maybe effects don’t show up until 10 years.” If you show them a 10-year study, they switch to 15 years, 20 years, etc. They can keep extending it all the way until the end of the human life-span, and beyond the fact that continually shifting the goal posts is an ad hoc fallacy (and this whole thing is an argument from ignorance fallacy), demanding 15 years of data is only slightly more irrational than demanding 10 years, or even 5 years or 3 years.

Really think about this. Given that no vaccine has ever had a wide-spread, serious side effect that only shows up more than a year after vaccination, what is the justification for demanding 3 years of data instead of accepting the year+ of data we have? How is the demand for 3 years of data more logical than a demand for 10 years, or 20 years, or 60 years? All of those are time categories where we’ve never seen a vaccine suddenly cause new problems and for which we have zero reason to expect these vaccines to cause problems. The probability of a long-term effect only showing up over a year after vaccination is pretty close to zero, which means that it is close to zero for 3 years, 5 years, etc.


Bad risk assessment

As I’ve shown throughout this post, there is simply no good evidence to suggest that the COVID vaccines will have serious long-term consequences that only show up in the future. It’s a baseless fear. Meanwhile, we know that COVID itself is very serious. In the USA alone, it has killed over 650,000 people. In 2020, it was the third leading cause of death in the USA, and in early 2021, it briefly spiked to the #1 slot before dropping back to position #3. We should not be downplaying something that is so prevalent and deadly that it is the third leading cause of death. Further, beyond death, many people suffer serious complications from COVID, some of which will likely persist into the future (Mitrani et al. 2020; Fraser 2020).

Therefore, based on everything we know (which is a lot), risk assessment clearly shows that you are safer with the vaccine than without it, and while it is technically possible that there will be future unknown consequences of the vaccine, these would be even more likely from COVID itself, and it is incredibly unlikely that they will happen from the vaccines and be serious and widespread enough to alter the risk assessment.

By avoiding the vaccine, you are placing more weight on an unknown and unlikely hypothetical future risk than you are placing on a very real and serious known risk.

See the following posts for more details including the “99% survive” argument, precautionary principle argument, and COVID comorbidities


Long-term fears are baseless: The burden of proof

As I’ve explained throughout, there is not one shred of evidence nor a single logical argument that makes it likely that the vaccines will have unknown long-term consequences. This is a completely made-up concern. This isn’t a situation where we have preliminary data suggesting a concern, or a logical/scientific basis for thinking that there is a risk. Rather, this is a concern that was pulled out of thin air with absolutely no evidence behind it.

Further, to be clear, the fact that something is new does not make it likely that there are unknown long-term effects. Indeed, everything we know about vaccines and the immune system makes it extremely unlikely that there will be future, unknown, wide-spread, long-term consequences. Is it technically possible? Sure, but there are an infinite number of technically possible things that will probably never happen. “Technically possible” is not a valid justification for a fear, particularly if that fear will prevent you from taking a medication that greatly lowers your risk of disease and death.

For future unknown consequences to be a logically valid reason for not vaccinating, the probability of serious consequences occurring would need to be high enough to trump the massive known benefits of the vaccines. We would need some really compelling preliminary evidence to suggest that these future injuries will occur, and we simply don’t have it, not one scrap of it.

I say again, this is a made-up concern. Although it makes a certain amount of sense from the standpoint of the psychology of our panicky primate brains, it is a concern that is not based on any evidence or logic. You can’t just make up a concern, then demand action based on that concern. You need actual evidence to support the concern.

In medicine (and science more generally), it is not enough to simply say that something is technically possible. Rather, you have to show that there is a reasonable probability of it being true before it makes sense to treat it seriously (this is something known as the “prior probability”).

Imagine, for example, that I decide that taking aspirin while drinking soda is dangerous, and when asked to justify that fear, I simply say, “well we don’t know that it isn’t dangerous. It’s technically possible that it’s dangerous, and look at how many drugs have been recalled because of some complication with another chemical.”

I think that we can all agree that my fear would be irrational, right? In technical terms, it would be an argument from ignorance fallacy. The fact that something is unknown, doesn’t mean that I can act as if that thing is known to be dangerous. There are an infinite number of things that are unknown. There are an infinite number of potential interactions and long-term effects for all treatments, including vitamins, supplements, herbs, etc.  There haven’t been, for example, any 30-year studies on the effects of regularly taking most vitamins or supplements, and given that those are taken daily, they are far more likely to cause long-term issues. So why not be concerned about them?

Do you see the point that I am getting at here? The fact that we haven’t looked at 3-year effects of the vaccines (or 5 years, or 10 years, etc.) would only matter if we actually had evidence to suggest that there would be problems down the road, and we don’t have that evidence. Indeed, all of the evidence suggests the opposite. Therefore, this is a baseless fear and the burden of proof is on those who are avoiding the vaccine based on these concerns.

Now you could try to quibble with me and say that, “No one is saying that there definitely are long-term effects. We are just saying that we don’t know if there are and, therefore, we should not take the vaccine until we do know.” But, again, that doesn’t work for all the reasons that I’ve laid out. A lack of knowledge simply isn’t sufficient in and of itself. This is an abuse of the precautionary principle, and although you may not be claiming that there are, in fact, long term effects, by choosing to avoid the vaccines, you are, nevertheless, acting as if there will be those effects. As explained earlier, that’s bad risk assessment.

I want to conclude this with some questions. If you are not vaccinating because of concerns over unknown long-term effects, ask yourself, “why do I have those concerns?” Can you point to any actual data to justify them, or is it simply a fear of the unknown? If the latter, ask yourself how likely it is that those fears will come true. The fact that something is new or unknown doesn’t make it dangerous. Given the very real risk of COVID, the decade+ of research on mRNA vaccines, the decades of research on vaccines in general, the massive studies on the COVID vaccines, and the fact that no vaccine has ever had the type of serious, widespread, unknown, long-term side effect that everyone is so afraid of, does it really make rational sense to avoid the vaccines out of fear of the unknown? Does it really seem more likely that you will be injured by this totally hypothetical and unprecedented vaccine injury than by a virus that is currently the 3rd leading cause of death in the USA?



Note 1: When we talk about unknown long-term effects, we are not talking about adverse events that happen shortly after vaccination and continue to cause problems into the future (those are proximate events that have long-term consequences). We aren’t talking about something like myocarditis which, in rare cases, occurs shortly after vaccination and (in a small subset of the most extreme cases) can cause long-term damage. We already know that those events are extremely rare, because we’ve already been able to detect them. They aren’t unknown. In other words, because those events are first detected shortly after vaccination, we have been able to test them with the current short-term studies and have shown that they are extremely rare.

Note 2: Barda et al. (2021) was comparing rates among the vaccinated with rates among the infected, not absolute risk. Absolute risk depends on how likely you are to become infected. However, other analyses (e.g., Gargano et al. 2021) have shown that in high-risk countries like the USA, your absolute risk of serious injury and death is lower with the vaccine than without it, even if you are in a low-risk COVID group.

Note 3: There are many false claims floating around about thousands of deaths following vaccination. These claims are based on VAERS which includes anything observed following vaccination and does not establish causation. With millions of people receiving vaccines, it is inevitable that a few thousand will die shortly afterwards just by chance. In the vast majority of cases, there is simply no reason to think that the vaccines were responsible. Similarly, while some of the adverse events reported in VAERS may have been caused by vaccines, most probably weren’t. The database is self-reported (anyone can make entries), and some truly wacky submissions have been included. Further, again, the fact that something happened after vaccination absolutely does not mean that the vaccine caused it (that’s a post hoc ergo propter hoc fallacy; more details here and here). To quote the CDC “FDA requires healthcare providers to report any death after COVID-19 vaccination to VAERS, even if it’s unclear whether the vaccine was the cause. Reports of adverse events to VAERS following vaccination, including deaths, do not necessarily mean that a vaccine caused a health problem. A review of available clinical information, including death certificates, autopsy, and medical records, has not established a causal link to COVID-19 vaccines” (the bold was in the original). More details on VAERS here.

Note 4: Again, to be 100% clear, we are talking about injuries that won’t show up until later down the road. You certainly can find examples from decades ago where there were issues with a vaccine rollout (particularly concerning polio vaccines), but those issues were immediate, and that’s not what we are talking about here. The COVID vaccines all underwent massive randomized controlled trials and have been carefully monitored following release to the public, and with the hundreds of millions of doses that we have administered, we have a very clear picture of the immediate risks and benefits. Those aren’t unknowns.


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