Mental exercises for a better brain

There’s this discussion going on over at Respectful Insolence between an anti-vaccine activist and an epidemiologist, like me. The anti-vaccine activist — whom I thought was banned from there (oops) — is known to be quite “dense” when it comes to epidemiology and biostatistics. I don’t blame him, much. His highest degree in science is in Fire Science. I don’t know where this guy when to school, but most programs I’ve found, like this one, don’t have biostatistics or statistical reasoning in their curricula. This would explain the activist’s misunderstanding of a case-control study. Like the PhD in Biochemistry being discussed by Orac in that post, the activist thinks that matching cases and controls in a study somehow disallows for the examination of their vaccine status and its relationship to autism. They think that cases (autistic children) should have a different vaccine status than controls (neurotypical children), and then we can see if they have a difference in vaccine exposures.

Can you see the logical fallacy in that? Continue reading

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Autism: It is not a disaster

Believe it or not, people who are mentally ill are more likely to be victims of violence than perpetrators of violence. This doesn’t make much sense to people because we want to believe that someone who kidnaps, rapes, and murders a person has to be deranged. A “normal” mind can’t possibly do something so horrible, right?

Even worse, a lot of people are quick to point out that a criminal — especially a young criminal — was kind of “quirky” or maybe had “autism or something” instead of waiting for the facts to come through on a case. I believe that it’s our own attempt to justify what happened and to tell ourselves that we would never do something like that. Because, deep down, we’re afraid to be monsters ourselves.

Don’t deny it. It’s true.

Furthermore, autism and other neurological disorders are not mental health problems. You wouldn’t walk up to someone with cerebral palsy and say that they’re “crazy,” would you? Likewise, you wouldn’t say that Muhammad Ali, who has Parkinson’s, is more likely to commit violence than someone who is neurotypical. Would you? Nevertheless, for a very long time, children with cerebral palsy or autism have been treated as being “crazy” or “quirky,” and mass shooters as possibly being autistic (with the implication that said autism was the cause for their violence).

And so we come to yesterday’s news that “1 in 50 children have autism.” From Dr. Willingham’s post:

“According to the CDC, hidden within these numbers is the finding that most of the increase from 2007 to now occurred in school-aged children. In other words, given that it’s possible to diagnose autism as early as age 18 months and usually by age 5, many of these new autism diagnoses were in children who received them relatively later. Children who were, therefore, walking around for quite a few years with autism that went unrecognized … and uncounted. That fits with the idea that a lot of the increase in autism we’ve seen in the last decade has much to do with greater awareness and identification.”

The anti-vaccine blogs are already chomping at the bits at what this new prevalence number means, totally misunderstanding the meaning of the data. (I’m not surprised, are you?) Not only that, but they have their dire predictions:

“Any expressions of concern from anybody with the power to do something about this disaster? No . And the press, as usual is soft pedaling the findings. Fifteen years ago the autism rate was 1 in 10,000, 12 year ago it was I in 2,500, 10 years ago it was 1 in 1000, and so on. When President Obama was elected in 2008 the official rate was 1 in 150, then it went to 1 in 88 and now it is 1 in 50. Where is it going to stop?”

It will never stop. We will get to 100% saturation. Every child will be autistic.
I’m joking, of course. The prevalence rate will remain the same as it has always been. Our estimate of it will even itself out and approach the prevalence rate and remain there. This is because our ability to do surveillance for autism is improving. The identification of cases by healthcare providers is improving. People with autism are coming forward and demanding to be counted. Our elected leaders are devoting more resources to ways to assist people with autism to lead long and productive lives. These are all good things.
It is not a disaster.
What is a disaster is that people who call themselves “advocates” for children and adults with autism continue to say and do things that actually harm people with autism and other neurological disorders. They call it a “disaster” to have a child with autism, or they say that they “lost” their child to autism. They then write that their children are monsters or have monsters inside them. And we’re supposed to just stand back and be understanding because we don’t have children or children who are autistic? We’re supposed to agree that it’s a “disaster” when all rationality says that it’s not and that children with autism can and will grow up to be productive citizens who even appear on CSPAN as advocates of people with similar neurological disabilities?
No, we’re not. I won’t. And I hope you won’t either.

Vax vs. Unvax studies… FIGHT!

This doctor is asking that we do a vaccinated vs. unvaccinated study to determine if vaccines cause more or less “outcomes” (read: autism) than what is attributed to them. I never went to medical school, but I did go to epidemiology school with a lot of medical students. Maybe this doctor was too busy with other things when he was introduced to epidemiology, because it is very clear that he has no clue what he is asking for. (Or maybe he is just selectively remembering what is good for him and what isn’t?) See, in the world of epidemiology, there is a hierarchy of epidemiological studies. In ascending order of ability to show causality, the studies are these:

  • Case Study (describing one person with the condition, a case)
  • Case Series (series of cases)
  • Ecological Study (analysis of group statistics..for example, comparing rates of disease between two countries)
  • Cross-Sectional Study (assessing individuals at one time, such as a survey)
  • Case-Control Study (studying those with the condition vs. those without)
  • Cohort Study (following subjects over time to study the initiation and progression of a condition)


We did the case studies. We looked at children with autism and determined that there was no biologically plausible way for vaccines to cause autism. Furthermore, instances of unvaccinated children with autism kept coming up. There were even case studies of autism before many vaccines were around. So we moved one step up.

We did the case series. We looked at groups of children with autism and determined that some were vaccinated while others weren’t. Even within those who were vaccinated, we noticed that their symptoms preceded vaccination. In those who were unvaccinated, we noticed that their symptoms were similar to children with autism. And, like with the case studies, we found that vaccines have no biologically plausible way of causing autism. So we moved one step up.

We did an ecological study. We looked at autism rates in other countries and in this country. After adjusting for differences between factors in the different countries, we found that there is no difference between countries in the rates of autism. Furthermore, there are differences between those countries when it comes to vaccine availability. That is, it didn’t matter if the countries vaccinated more or less, we found no difference in autism rates. So we moved one step up.

We did surveys. (Heck, even the anti-vaxers wanted to do surveys.) And, after adjusting for all sorts of biases that surveys present, we found no difference between vaccinated and unvaccinated groups. (The anti-vaxers found a similar result, but that doesn’t stop them from wanting another round at it.) So we moved one step up.

We did case-control studies. We took children who had autism and children who had no autism, then we looked at their immunization records. It turned out that both groups had equal odds of being vaccinated. There was no difference between the two groups.

In short, everything we’ve done to date has failed to find a link between immunizations and autism. So you would think that the vaccine-autism link would be dead. Well, it isn’t. That doctor I told you about in the opening sentence wants a cohort study (aka Randomized Clinical Trial or Randomized Controlled Trial). Never mind the millions of dollars and thousands of man-hours lost doing such a study when all the previous evidence has shown no link. Never mind that we could do much better things with those resources. No. The anti-vaccine groups want to slay their dragon. They want to prove that vaccines did to them what they think vaccines did to them.

So what would it take to do such a study? Well, it would go like this:

Recruit participants at birth. Parents would be approached and told that their child would be participating in this study. Without their knowledge, their child would be assigned to one of two groups. One group is vaccinated while the other is given placebos. If you really want to give this study strength, you keep the group assignments secret from even the researchers.

Follow participants until a certain endpoint. This endpoint can be anything you want it to be: the diagnosis of autism, the age of ten — after which a diagnosis of autism is very rare, death, anything. Once all your participants reached the endpoint, then the study is done.

Analyze the data. You would then “unmask” the participants’ assignments and compare the vaccinated to the unvaccinated groups to see which of them reached those endpoints faster or in greater proportion. Which group has the most autistics?

However, can you see why this study is unethical and very likely to fail? First off, one half of the children — those assigned to the unvaccinated group — would be deliberately unprotected against some very nasty diseases. You tell me if you want your child to be unprotected against measles. If you’re an anti-vax parent, you probably don’t care. You probably think that your child will survive anything and come out stronger, despite all the evidence to the contrary. But what if you’re a pro-vaccine parent? Would you like your child to maybe not be vaccinated? And, if you’re anti-vaccine, would you like for your child to maybe be vaccinated?

Then there is the issue of bias. If you’re an anti-vaccine parent, and you think your child was vaccinated, you might make a bigger deal out of every little developmental delay. If your child doesn’t walk at 12 months, taking a few more weeks to get going, you might be more inclined to blame the vaccines. Or you might give your child an unproven therapy to try and “detox” them, and it might be that therapy that makes them ill.

On the other hand, if you’re a pro-vaccine parent, you might take your child to get a second round of vaccines if you think that your child ended up in the unvaccinated group. You want to make sure your child is protected, and, frankly, I can’t blame you for that. Also, being the responsible parent that you are, you might take your child to regular check-ups and discover autism (or any other “outcome”) much earlier than people who don’t take their children for check-ups.

And that’s just a few of the biases that could creep into this study.

The biggest problem with the study will be the deliberate lack of vaccination of half of the participants. No Institutional Review Board will allow you to do this because the liability is too great. If one kid in the control (unvaccinated) group get sick and dies from a vaccine-preventable disease, you will no longer be allowed to conduct research on human subjects, ever.

Of course, anti-vaccine activists will say that there are plenty of unvaccinated children, so finding children whose parents will deliberately leave them vulnerable to deadly pathogens wouldn’t be a problem. In that case, you’re not asking for a randomized clinical trial because you’re removing the “random” from it and you’re inserting a huge bias. If you see vaccines as an evil big enough to keep your children from being vaccinated, how likely are you to report that your child has autism, thus disproving your theory? In these cases, you’re asking for a case-control study, which has been done over and over again.

How much time, money, and God knows what other resources do you want us to keep on wasting in order to slay your dragon, to chase down your windmills, to find the bogeyman under your bed?

Then again, it’s not like ethics have kept the anti-vaccine forces from doing their thing.

When statistically significant is insignificant

I love Twitter. I got a hold of this little bit of anti-vax nonsense and just had to bring it to everyone’s attention. Check this out:

Source.

You can click on the image to see it a little larger. The original caption is what caught my eye. It reads: “Snapshot of the Verstraeten study dated 02/29/00 showing a statistically significant relationship between mercury exposure and autism.” My emphasis added in bold because this image shows no such thing. It shows a statistically insignificant relationship between mercury exposure and autism.

However, I realize that some of these terms might as well be in Chinese to some of you, unless you speak Chinese. So let’s break it down piece by piece.

Relative Risk (RR) is the ratio in the risk of developing autism given an exposure to thimerosal between a control and an intervention group. That’s the left-hand axis. The control group doesn’t get thimerosal. The intervention group does.

For example, if the RR is 10, then those exposed to thimerosal have a ten times higher risk of developing autism than those who were not exposed. An RR of 1 means that there is no difference in the risks; both exposed and unexposed have equal risks of developing autism. So, an RR of 1 means that the relationship observed is not statistically significant.

Statistical significance means that the results you observe are not due to random chance. That’s the 95% confidence interval (CI) part. That CI tells you the range of RR values you’d see 95 out of 100 times if you repeated the same experiment 100 times. The CI in this chart is represented by the error bars in each value.

At <37.5 micrograms, there was no difference between the two groups. The RR was 1. Note the lack of error bars for that value because of the low number of study subjects (n=5).

At 37.5 micrograms, the RR is still 1. Again, no difference.

At 50 micrograms, the RR is 0.93. This means that the control group is about 7% more likely to develop autism than the thimerosal group. BUT the CI includes 1, so there is a very good chance that your RR will be 1 if you repeat the experiment 100 times. As a result, this finding is not statistically significance. Certainly, I would not go out to the streets and proclaim that thimerosal protects from autism.

At 62.5 micrograms, the RR is 1.26, meaning that the group receiving thimerosal is 26% more likely to get autism than the control group. BUT look at the CI again! It still includes 1. As before, this result is statistically insignificant.

At over 62.5 micrograms, the RR rises to 2.48. The CI still includes 1. This result is statistically insignificant.

Wait! Doesn’t this show a trend whereby if the exposure is high enough, then the association will be stronger? Nope. It doesn’t. If you look at the error bars, you could hit 1.0 the whole time. Heck, with the logic shown in this article, I could make a case that thimerosal is protective against autism at certain levels.

It’s nonsense (to not use a harsher word).

But anti-vaccine advocates are not known for letting facts get in the way. The author of that piece of nonsense continues with quotes taken out of context from some meeting long used by anti-vaxers as evidence of a plot… Blah! Blah! Blah!

If you don’t know what is statistically significant and what is not, then that pretty much destroys your entire argument from the get-go. If you try to come off as a researcher, when you’re obviously not, then you lose the argument even worse.

But what about that study? Well, read all about it here, here, here, and here, and see how it has been misused to further the anti-vaccine agenda. Too bad they don’t know the difference between significant and insignificant, or they would have not used this study (or this graph).

Prevalence, Prevalence, Prevalence, Prevalence!

If you have an anti-vaccine agenda, and you want to scare people off vaccines by telling them that vaccines cause autism, and you want to scare them about autism, then all you have to do is get the definition of prevalence wrong. Then, take a national emergency like Hurricane Sandy and write some half-assed blog post about how autism is some sort of a national emergency that needs to be addressed immediately but is being hidden from the public by special interests.

How something that is emergent like that can be hidden remains a mystery to me, but — as always — facts don’t ever get in the way of a good anti-vaccine, anti-government, big conspiracy nut’s blog post. Like this one here. If you can stomach it, go read it, then come back for today’s breakdown of the [redacted] spewed there.

Let us begin with two quick definitions. “Incidence” is the number of new cases of a disease or condition divided by the number of people at risk. For example, the incidence of cervical cancer would be the number of new cases divided by the number of women with cervices. Note that we don’t include men in that rate/proportion because men don’t have uteri nor cervices.

“Prevalence” is the number of existing cases of a disease or condition divided by the total population. For example, the prevalence of diabetes is the number of total diabetes cases in a community divided by all of the people in that community. These two numbers, incidence and prevalence, tell you very different things epidemiologically. Only incidence can tell you if you have an outbreak, or national emergency, on your hands.

For a condition such as autism, where the person who has autism rarely, if ever, dies from it and can lead long, productive lives, the prevalence rate will continue to climb and climb as more people are diagnosed and more of them are living long. Even if the incidence (new cases) drops precipitously, the fact that there are new cases will mean that prevalence will continue to rise. I’ve explained this to you before, haven’t I?

I have.

I really wish the author of that post had an epidemiologist who she could ask about these things before looking foolish. All she has is an even more hardcore anti-vaxxer who is trying to become an epidemiologist. But that’s a whole other story.

Anyway, back to the post in question. In it, the author states the following:

“Starting in the 1980s the autism rate began an ever-ascending climb. 

1995 1:500
2001 1:250
2004 1:166
2007 1:150
2009 1:110
2012 1:88″

She quickly acknowledges having been told the reason for this climb in prevalence, but she immediately refutes it:

“For years the medical community has been credited with “better diagnosing” of a disability that’s always been around. In other words, we’ve always had people like this in society– we just didn’t call it autism… The trouble is, no one has ever had to prove the claim of “no real increasing—better diagnosing.””

Allow me to highlight the troubling part of her statement:

“…no one has ever had to prove the claim of “no real increasing —  better diagnosing”

No one? Really? What about this, this, this (.pdf), and this? Those don’t count because of [insert conspiracy theory here]? Oh, well, I tried.

And then she gets all conspiracist about it:

“That hasn’t stopped authorities from claiming that they’re out there somewhere, undiagnosed or misdiagnosed. It would be especially interesting to see the 40, 60, and 80 year olds with classic autism, whose symptoms are evident to all. It would be of real significance to find middle aged and elderly people whose health history also included normal development until about age two when they suddenly and inexplicably lost learned skills and regressed into autism.”

In other words, because the author doesn’t see them, they must not exist.

Tell me something. Do you “see” people with schizophrenia everywhere? Well, you should. You should see them because 1.1% of the world’s population suffers from it. As it turns out, 1.1% is 1 in 88.

Let that settle in for a little bit. Maybe get up and stretch and whatnot.

Based on prevalence, there are just as many people with schizophrenia as there are people with autism. In the cases of both conditions, the prevalence will continue to increase not because there is some “tidal wave”, “hurricane”, or “emergency” of number of incident cases. Nope. The prevalence will continue to increase because people with these conditions are being treated and accepted — diagnosed and intervened on — and allowed to be part of society. No longer are they being institutionalized in the same manner or proportion as they were in the past.

But we don’t “see” them everywhere because these kinds of conditions manifest themselves at A) a certain age, and B) as a spectrum. You don’t see kids with schizophrenia because it manifests in young adulthood. You don’t see a lot of schizophrenic adults because they are either being treated for their condition and lead “normal” lives or are institutionalized (e.g. sanatoria or even jail). Likewise, you don’t “see” autistic children everywhere because, well, seriously, how many of us wander around elementary schools? And the 1 in 88 adults? I’ll get to that in a second.

By the way, I have several friends with mental health issues, including schizophrenia, and central nervous systems that are not typical, and I love them to death. But I digress…

The author of the misinformed, misconstrued blog post then want to see the following:

“The problem is no one has ever been able to show us the one in 88 adults with autism.”

The author wants to believe — or make her readers believe —  that 1 in 88 adults has autism. I hope it’s an oversight on the author’s part because the prevalence rate on autism is for children. Here, I’ll show you:

“About 1 in 88 children has been identified with an autism spectrum disorder (ASD) according to estimates from CDC’s Autism and Developmental Disabilities Monitoring (ADDM) Network.”

It’s children. There are less children than adults in the United States. So you can’t extrapolate that number willy-nilly without use of some biostatistics. Again, if only she had a [expletive] epidemiologist to help her sort these things out and not read so idiotic.

Finally, if you can do me a favor and not even mention the author’s name in the comments. She’s been known to go all “decepticon” and have her bot fill comments sections with what can be best described as manure.

To understand autism, you need to understand incidence and prevalence

In 2012, the CDC put out a prevalence study of autism in the United States. It changed the prevalence number from “1 in 110” to “1 in 88”. There were many who were alarmed at this statistic. They thought that the chances of a child being born with autism increased from 1 in 110 to 1 in 88. Well, they didn’t. This was only a rise in prevalence, not a rise in incidence. While the two are related, they are not necessarily tied to each other. That is, if one rises, the other one doesn’t have to. One can rise and the other can fall. Why?

It’s a little complicated, but I’ll try to explain it.

Let’s look at the definition of incidence. Incidence is the number of new cases in a population, per unit of time (usually a year), divided by the number of people at risk in that population. So, if your population is 100,000 and 100 people get the disease in one year, then your incidence is 0.001 or 0.1%. But what if we’re talking about cervical cancer? In a normal population of 100,000, only half of the people in that population — the women — would get cervical cancer. Men don’t have the right equipment for that. In that case, 100 cases in an at risk population of 50,000 is an incidence of 0.002 or 0.2%.

If you fully recover from the disease, then you move over to the “at risk” population again. If you don’t — because it stays with you forever or because it kills you — then you stay out of the at risk population. You could have 100 cases each year, no more and no less, and the incidence would continue to rise if no one recovers or your at risk population is not replenished by new births fast enough. In the example I just gave you, the population at risk for year two is 49,900. If you get another 100 cases, then your incidence is 0.00200401 or 0.2004%. It’s a small increase, but it’s an increase nonetheless.

So, remember this: If the disease is not curable (because it is chronic, pervasive, incurable, or deadly), then the population at risk dwindles if it is not replenished by births or immigration. Lower the denominator in incidence, and you will get a higher number. To decrease incidence, you either increase the number at risk or you decrease the number of new cases.

Now, let’s move on to prevalence. Prevalence is the number of existing cases in a population, per unit of time, divided by the total number of people in that population. That’s total population, regardless of whether or not they have the disease. So, if you have 100 cases of cervical cancer on year one, your prevalence will be 100 divided by 50,000, which is 0.002 or 0.2%. Year two, you get another 100 cases, and you will now have 200 existing cases divided by the same population of 50,000, which is 0.004 or 0.4%. Your prevalence doubled!

This assumes, of course, that no one died of the disease or that the total population stayed static through some means. In real life, population levels change.

In year three of the above scenario, you get another 100 cases, making it 300 existing cases in a population of 50,000, for an overall prevalence of 0.006 or 0.6%.

So, remember this: If a disease is not curable, then the prevalence will increase as long as there are new cases. Prevalence will decrease if the increase in population outpaces the new number of cases or the number of existing case decreases because of death or recovery.

Now, onto autism.

As far as science and medicine can tell us, autism is not curable. It is treatable. With the right interventions and depending on the level of severity of the autism signs and symptoms, autism is treatable. Plenty of people with autism go on to live happy and fulfilling lives. Again, it is not curable. Not at this time. So any new cases of autism will pile-on to existing cases and… Prevalence will increase.

Not only that, but the number of new cases per year can go down, but there will still be all those previously-diagnosed cases of autism which are still being added on to even if the incidence falls. Incidence would have to reach zero, the number of new births would have to continue (some countries have a negative birth rate), and people with autism would have to start passing away before the prevalence of the condition decreases.

Here are some theoretical numbers, as an example:

Note that there was a successful intervention in this example.

The column headings are self-explanatory, but let’s just go over them again for clarity.

  • New cases – Number of newly diagnosed cases that year.
  • Existing cases – The number of new cases for the year plus the number of existing cases the previous years. (Let’s pretend that there were no existing cases in 1999.)
  • Incidence – The number of new cases for the year, divided by the population at risk.
  • Prevalence – The number of existing cases (new cases plus existing cases) for the year, divided by the total population.
  • Population – The total population.
  • Population at risk – The total population minus the number of new and existing cases.

As you can see, we had a steady increase in the number of new cases from 2000 to 2009. From 2009 to 2015, the number of new cases declined. Appropriately, the number of existing cases continued to increase throughout because the condition is not deadly. (Again, this is theoretical. People with autism die from other causes, like the rest of us.) As you can see, incidence climbed along with the number of new cases until 2009/2010, then it began it’s decline. On the other hand, prevalence started its increase in 2000 and continued increasing to 2015. Also note that I increased the population every five years or so in our theoretical place (city, county, state) because that’s what populations in the United States have been doing. We don’t have a negative birth rate.

So, as cases dropped and population increased, incidence dropped. Because cases didn’t die, and the new number of cases outpaced the population increase, prevalence continued to increase.

On a side note, one of the criticism someone mentioned about HIV/AIDS treatment is that prevalence continues to increase. In their mind, HIV/AIDS treatment is not working if that particular measure of disease continued to increase. Can you see now why they were wrong?

Can you see why the prevalence of autism increasing from 1 in 110 (0.9%) to 1 in 88 (1.1%) is not a clear indicator that the number of new cases each year is rising? It’s only an indicator that people with autism are living and that the number of existing cases each year is outpacing population growth. For prevalence to decline, you would have to drop the new number of cases per year to zero and wait for the number of existing cases to drop on their own as people with autism get old and die.

That right there is what puzzles me when certain groups say they want the prevalence of autism to plummet. And their ranting and raving about an increase in autism signaling an “epidemic” of autism is also puzzling. Hopefully, it will be puzzling to you as well, now that you have seen how incidence and prevalence work.

Of course, this assumes that all things are equal when it comes to autism surveillance. But they are not. But that’s for another blog post at a later time.

By the way, here is the graph of the information in the table above, for those of you who are more visual:

Even with a theoretical, successful intervention in 2009, prevalence continued to increase. Why?

Correlation And Causation With Some Plausibility For Good Measure

One of the biggest problems in the battle against diseases is figuring out exactly what thing or things cause a disease. In the late 70’s and early 80’s, men and women – a lot of them being gay – started to come down with opportunistic infections at an accelerated rate. The cause was not known, but epidemiologists did come to realize that those who developed the syndrome – later to be called AIDS – were more likely to be exposed to certain behaviors and sexual preferences. That is, the personal attributes and the disease correlated, but it would be unscientific and wrong to say that one would get AIDS for the sole fact of being gay.

That sure didn’t stop the “moral majority” and others from stigmatizing an entire segment of the population. It wasn’t until HIV was isolated and discovered as the causative agent – and some heterosexual celebrities acquiring the infection – that the term GRID (Gay-Related Immune Deficiency) beam AIDS.

Of course, AIDS is not the only example.


I told you just the other day how nationalities and ethnicities are associated with certain conditions. Lou Dobbs wrongfully claimed that immigrants brought more cases of Hansen’s Disease (Leprosy) to this country than naturally occur. A discussion on recent cases of measles in Milwaukee undoubtedly turned into an immigrant bashing that would have made the most liberal KKK members blush. And God help you if you’re from Africa and trying to donate blood.

All of these examples above are instances of correlation between a disease and a person’s (or people’s) origin. Biologically speaking, it doesn’t matter where you come from. You’re still game to be infected.

But there are other examples were people have wrongly associated two things and then deduced that one caused the other – or vice-versa. For example, two non-scientists writing for an anti-vaccine blog recently published a seven-part story associating arsenic in pesticides with polio. They eyeballed data from the last 120 years and decided that arsenate in pesticides must trigger polio outbreaks because more polio outbreaks have been detected since the use of those pesticides started.

Sounds plausible, don’t it? Well, actually…

We all had a chuckle when a skeptical writer recently said that cases of autism have been on the rise since microwaveable popcorn went into the mass market. If you plot the incidence of autism and the sales of microwaveable popcorn, the lines almost overlap. Again, that’s just “eyeballing” the data without much of a scientific investigation. And that’s where a lot of assumptions about causation go badly.

Even if a study is well-designed and carried out by reputable institutions, there can be mistakes. For example, some time ago, a study was performed to look at the association between coffee and pancreatic cancer. The study concluded – with really good statistical data – that people with pancreatic cancer were more likely to be coffee drinkers. The researchers left it at that and walked away from their study, letting the public decide on whether or not to drink coffee.

Well, astute epidemiologists the world over noticed a funny thing. They noticed that the data never took into account the coffee drinkers’ smoking habits. Once the smokers and non-smokers were placed into different categories, people with pancreatic cancer were more likely to be smokers AND coffee drinkers. People without pancreatic cancer were more likely to be coffee drinkers BUT NOT smokers. Yes, it was the smoking, stupid – or the smoking stupid. The coffee industry took a while to make a comeback after that.

This brings me to biological plausibility of the whole damn thing. In the example of the coffee and cancer, there was no known biological process by which coffee could trigger pancreatic cancer. On the other hand, there was a process by which smoking could trigger pancreatic – and other forms of – cancer. In the example with arsenate in pesticides, there is no known process by which pesticides somehow make the polio virus more virulent – capable of infection – or more pathogenic – capable of causing disease. And, in the case of HIV/AIDS, one could see where certain sexual behaviors could lead to a better transmission of the virus, but there is no evidence whatsoever that one’s sexual predilections – who we’d like to shag – would make any difference to the virus. It will still infect all who are susceptible, meaning the whole of humanity if we’re not careful in how we use contaminated sharps, how we have sex with each other, and how we test blood donors (regardless of their national origin or sexual orientation).

Does the scientific data change and certain once-implausible events become plausible? Absolutely. But they’re far and few in between, and the scientists who once held them to be implausible will correct themselves and admit that there is now evidence of plausibility. And, for God’s sake, don’t just “eyeball” the data. Run through something, anything… Even MS Excel will do in a pinch!

In the case of vaccines and autism, that kind of evidence still has not come forth, despite all sorts of attempts at finding it. In fact, we have been trying to close the book on the vaccine-autism “debate”, but the anti-vaccine people won’t let it go. Once they do, we will be able to move on and help autistic people not only know why they are autistic but how to better treat them so they may live fuller lives.

I ended by talking about anti-vaccine advocates for a reason, by the way. I was asked recently if I thought anti-vaccine advocates presented an existential threat to the world or even just the country. It’s a question that will be asked of the protagonist in “The Poxes” twice. He will be asked about it on “Vaccination Day” and then again in “Five Years Since”. His answer will be much like my own five years ago and then again a few days ago. So look for that.