The zombie anti-vaccine lie–Peter Doshi and the appeal to authority

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Updated 4 November 2014 to add some ironic analysis of Doshi’s “not-an-epidemiologist” background.

A few  months ago, I wrote an article about Peter Doshi, a Ph.D. who is doing some postdoctoral work at Johns Hopkins University, one of the leading institutions of higher learning in the USA. Doshi is truly not very notable in science, except last year, he wrote an article about flu vaccines, basically employing the Nirvana Fallacy that because flu vaccines aren’t 100% effective they are worthless. Since vaccines are fundamentally a medical procedure to mitigate risk with a very low risk of adverse events, even 50% effectiveness will save thousands of lives. But we’ll get back to that.

The article he wrote is not actually based on real research, but appears to be an opinion paper–kind of like the opinion papers written by creationists who want to convince anyone who will listen that dinosaurs lived with humans. Doshi denies that most flu’s are even caused by the influenza virus. I guess the CDC’s high tech diagnostic tests for influenza are all wrong. But then again Doshi presents no evidence.

Because of the zombie myths of the antivaccination world, myths or papers that are reanimated every few months because the vaccine denier community actually lacks any fresh evidence to support their nonsense. So Doshi’s paper from 2013 is resurrected in the antivaccination press. A few days ago, an obscure pseudoscience promoting website started banging the drum about Doshi’s comments. The article, found in the Realfarmacy website, has this scary headline: “Johns Hopkins Scientist Reveals Shocking Report on Flu Vaccines.” Makes it sound like Doshi wrote another article. Which he didn’t. Continue reading “The zombie anti-vaccine lie–Peter Doshi and the appeal to authority”

The antivaccination cult’s idea of what constitutes “peer-reviewed”

autism-mercury-geier

Update 1. Added more criticism of this paper (since the data is not new) from Emily Willingham.

One of ongoing criticisms of science deniers (and more specifically, of vaccine deniers) is that they make claims without the support of peer reviewed published articles. What the antivaccination movement doesn’t understand (really, it’s about all anti-science groups, but this is about vaccines) is that “peer review” is not by itself some magical bit of information. It’s really the result of the quality of journal, the reputation of the authors, the methods that were used to gather the data, the quality of statistical analysis of the data, and whether the conclusion is supported by the evidence or data.

So it’s not magic, it’s discernible and objective quality.

Moreover, it’s important to know if this research is repeated and used to build stronger hypotheses in subsequent research. A scientific paper, standing by itself, may or may not have any usefulness going forward. I’m sure you’ve read how marijuana cures cancer, but the data supporting that is based on one-off, unrepeated animal studies. This happens all the time. The mainstream news will claim XYZ prevents ABC cancer. Within 12 months, no one talks about it anymore, because the research is never repeated.

That’s why, on the hierarchy of scientific research, systematic- or meta-reviews rank at the very top, because they roll-up data from all of the other studies, giving more credence to studies that are repeated over and over again. And the better the journal in which they’re published, the better the systematic review. Primary research exhibited at a medical conference, unpublished, and then loudly advertised by a press release ranks near the bottom (but still higher than anything at Natural News). Continue reading “The antivaccination cult’s idea of what constitutes “peer-reviewed””

Hey antivaccination gang–it’s really really simple math

©2014, Amazon.com
©2014, Amazon.com

Yesterday, I tried to show in the most simple mathematical terms that the risk of contracting measles, in the New York City outbreak, was 30X higher in unvaccinated children than it was for vaccinated. I knew I vastly underestimated the actual rate because I used a larger population than I should, because I lacked the more specific geographic spread of the disease. I’ll leave that to a peer-reveiwed paper that I’m sure will be published in the next few months that will accurately describe everything about the outbreak. Don’t hold your breath vaccine deniers–their conclusions will only vary from mine because they’ll present a much higher risk of contracting measles amongst non-vaccinated children.

Someone suggested that I discuss another article that analyzed a measles outbreak in Corpus Christi, TX, which compared those who were vaccinated with the MMR vaccine to those weren’t. The results are clear and relatively straightforward:

  • 1732 children were seropositive (meaning they had antibodies to measles) and over 99% of them were vaccinated. None, and not close to none, but absolutely 0 of these children contracted measles.
  • 74 children were seronegative (they lacked measles antibodies). Fourteen (14) of these children contracted measles.

So, let’s look at the math. All of the kids who had measles antibodies (presumably as a result of the MMR vaccine, since 99% were vaccinated) avoided the disease and its consequences. On the other hand, 18.9% of the children who lacked antibodies got sick.

Again, if this isn’t clear…0% contracted the disease if they had antibodies from vaccines, 18.9% contracted the disease if they didn’t have antibodies.

Now, the 74 children who were seronegative also were vaccinated (though the paper did not tell us how many vaccines were given, it takes at least 2 to confer full immunity). If there are no other issues (and again, the article didn’t report that) like some type of compromised immune systems in some of the 74 children), the vaccine was 96% effective in seroconverting and preventing measles.

This story is rather basic. The MMR vaccine is extremely effective in boosting the immune system to produce anti-measles anti-bodies. A small group seems to have not seroconverted for unknown reasons. But even though most of the population in this study were protected against measles, the disease is so pervasive, so pathogenic, even a small group of susceptible individuals can catch it. But because the vast majority, 96% were protected against the disease, this measles outbreak didn’t spread further.

But think about this. If the number isn’t 96%, but 70% because parents refuse to vaccinate. What happens is that the random chance that an infected child encounters an unvaccinated child increases dramatically, increasing the risk of a much larger outbreak. With all of the consequences of measles.

As I said before, it really is simple math. So simple that a vaccine denier could do it.

Use the Science-based Vaccine Search Engine.

Key citation:

Hey antivaccination gang–it’s really simple math

As you may be aware, there is a relatively large measles outbreak in New York City, hitting 26 individuals according to the most recent report (pdf) from the New York City Department of Health. An outbreak of 26 cases of measles may seem small, but compared to the historical average of around 60 measles cases per year for the whole United States, it really is a relatively large outbreak.

©2014, RubellaMeaslesInitiative
©2014, RubellaMeaslesInitiative

According to the most recent data, 12 of the cases are children and 14 are adults, and nine of 12 children were unvaccinated (2 were because parents got an exemption, and the other 7 because they were too young to be vaccinated with the MMR vaccine). In addition, it was difficult to determine the vaccination status of the adults, but we’ll focus on the children.

If you read the most obnoxious antivaccination websites (and I did it for you), you’d see claims that only 2 of the 26 were unvaccinated (simply not true or an ignorant misreading of the actual data), implying that 90% of those who caught measles were vaccinated. In fact, it’s at least 9 who were unvaccinated.

So let’s go with some simple math, just based on this small sample. But if the antivaccination lunatics are going to invent numbers, it is my job to obtain real numbers that show factually what is happening.

The outbreak is centered in Upper Manhattan and The Bronx areas of Manhattan, a total population of just under 2 million individuals. Now the outbreak is actually more focused than those areas, but it makes the math easier for the anti-science crowd.

I’m going to vastly oversimplify the risk of the measles outbreak, because I am aware that the antivaccine crowd is math challenged. If I used real epidemiological data, measure the risk in the exact geographical areas of the outbreak, data that I don’t have, the incidence rate would be much higher. If I did this by actual age, say 0-18 months, the risk would absolutely frighten you. But we’ll keep it simple.

  • Total risk for measles for vaccinated children, 3/496,850 or 6 out of one million
  • Total risk for measles for unvaccinated children, 9/53,372 or  169 out of one million

So, despite what you’ve heard from the antivaccination squad, the risk for contracting measles in an outbreak is nearly 30X higher in the unvaccinated group. Again, my numbers here vastly underestimate the risk, because the actual calculation would be done using data from the small area that this outbreak occurred, with the risk for the unvaccinated group probably being 10,000X higher than stated here. And I’m not even getting to risk reducing strategies like increasing the vaccination uptake rate to 95 or 96%, and the herd effect would have stopped this outbreak in its tracks.

It really is simple math. So simple that a caveman could do it.

Use the Science-based Vaccine Search Engine.

Key citation:

Save children from risks–vaccinate and keep them away from guns

child-gun-deaths-01_0Vaccine deniers are basically clueless about science. They invent stuff about the immune system, while missing how a vaccine induces a long-lasting immune response. They conflate correlation with causality, an important distinction if you’re going to understand epidemiology. They deny the germ theory of disease, one of the fundamental pillars of modern biology, which states that many diseases are caused by microorganisms. They simply ignore what makes science a logical and repeatable process, called the scientific method, preferring anecdote and cherry-picked data over randomized clinical trials and peer-reviewed systematic reviews. 

But one of the more important scientific failures of the antivaccine gang is an unsophisticated lack of understanding of basic mathematics, specifically the measurement of risk. Using 2010 USA numbers only, let’s look at the top mortality risks for children aged 1-14:

  • Unintentional injury (motor vehicle accidents, bathroom falls, etc.): 53.75 (out of every 100,000 Americans between the ages of 1-14)
  • Malignant neoplasms: 22.33
  • Congenital anomalies (commonly called birth defects): 14.25
  • Homicides: 11.43
  • Firearms (number broken out from the numbers for all homicides): 3.68
  • Heart disease: 6.09
  • Suicide: 4.85
  • Chronic respiratory disease: 3.26
  • Influenza and influenza-related pneumonia: 2.87
  • Benign neoplasms: 2.50
  • Meningitis: 0.58
  • Meningococcal infection: 0.25

The average risk for “serious” complications from vaccines range from 0.1 to 1 in 100,000, with the risk of death from vaccines found to be so small, it can be barely measured as a risk. By the way, those of you who think that VAERS (Vaccine Adverse Event Reporting System) should be used to estimate risk, the best I could say is that VAERS is pretty much useless, since it cannot establish causality, it is gamed by those with an antivaccine agenda, and the rate of adverse events is frequently below the background rate for these events in a typical populations of Americans. VAERS is an incredibly useful tool to spot potential new adverse events that might arise from vaccination, but the numbers themselves cannot be used to determine risk.

The risk of a serious reaction, like an allergic one, from getting the flu vaccine is less than 0.1 in 100,000, far far less than the actual death rate from influenza at around 2.87 per 100,000. Moreover, meningitis (and meningococcal infection) have risks of death far higher than the risks of vaccines. 

The saddest thing about these numbers is that I’m spending so much time defending vaccines, which are as safe as drinking a glass of filtered water and clearly save lives from preventable diseases. The antivaccine activists, who claim to be worried about children, don’t focus on the things that actually kill children. Motor vehicle accidents, some portion of which are probably a result of drunk drivers. Or firearm homicides? Where is the outrage, that young children are dying from gunshots? Or that the risk of a child dying of suicide is thousands of times higher than the infinitely tiny risk of death from vaccines (if it even exists)?

Why is it that these vaccine deniers show incredible outrage over an indefensible belief that vaccines are dangerous, yet not try to stop homicides, especially with guns? Or safer cars? Or something that actually will help kids live longer.?

Actual guns kill more actual kids than the antivaccine myth that vaccines harm actual children. You see, vaccine deniers don’t actually care about children, or they would be yelling and screaming about guns. And drunk drivers. And the lack of mental health care for teenagers.

If you need to search for accurate information and evidence about vaccines try the Science-based Vaccine Search Engine.

How pseudoscience makes its case-Part 2. Revised and repost.

Recently, we discussed how science works. It’s not a belief. It’s not a random set of rules. It is a rational and logical process to determine cause and effect in the natural world. Pseudoscience, by its very nature, ignores the scientific process; instead, it claims to come to conclusions through science, usually by using scientific sounding words, but actually avoids the scientific process.  They tend to use logical fallacies to make their case.  Just to be clear, logical fallacy is essentially an error of reasoning. When a pseudoscientist  makes a claim, or attempts to persuade the public of this claim, and it is based on a bad piece of reasoning, they commit a fallacy. Continue reading “How pseudoscience makes its case-Part 2. Revised and repost.”

How pseudoscience makes its case. Part 2.

Recently, I discussed how science works. It’s not a belief. It’s not a random set of rules. It is a rational and logical process to determine cause and effect in the natural world. Pseudoscience, by its very nature, ignores the scientific process; instead, it claims to come to conclusions through science, usually by using scientific sounding words, but actually avoids the scientific process.  They tend to use logical fallacies to make their case.  Just to be clear, logical fallacy is essentially an error of reasoning. When a pseudoscientist  makes a claim, or attempts to persuade the public of this claim, and it is based on a bad piece of reasoning, they commit a fallacy.

There are several types of logical fallacies that they employ.  My favorites are Appeals to Antiquity, or old ideas are somehow better than new ideas; Appeals to Authority, or someone who should know better supports the claim even if everyone else does not; Appeals to Popularity, or everyone does it, so it must be useful; and the Genetic Fallacy, where the source is more matter than the merits of the evidence.  Logical fallacies are so prevalent in skeptical community, there are websites devoted to describing them.

The typical pseudoscientist will use logical fallacies to state very definitively that “it’s proven.” It’s the same whether it’s creationism (the belief that some magical being created the world some small number of years ago), alternative medicine (homeopathy, which is nothing but water, has magical properties to cure everything from cancer to male pattern baldness), or vaccine denialists (I’ve discussed this topic before, no need to belabor).  The worst problem is that in the world of the internet, if you google these beliefs, the number of websites and hits that seem to state that they are THE TRUTH overwhelm those that are more skeptical or critical.

So how can you tell the difference between science and pseudoscience in medicine? In medicine, we gather and analyze evidence in one of two ways.

Almost any medical product, device, drug or procedure must, by law, must studied in a Randomized Controlled Trial, which is sometimes called a clinical trial. Essentially, it is a scientific experiment, designed to test the hypothesis of whether the safety and efficacy of a particular medical product is better than a placebo. That is, does the medical product produce results better than doing nothing at all. This is the “gold standard” of investigation, and if the study does confirm the hypothesis, you can be assured it has a benefit to your life (although the degree may be subject to argument). Alternative medicine just doesn’t do this (most of their reasoning is that their beliefs just doesn’t fit into the clinical trial model), so their is no proof that their products work. A clinical trial usually has thousands of participants, and is done in a manner that the patient and the physician do not know who is and who is not receiving the treatment. The results are analyzed statistically and published in peer-reviewed journals. Furthermore, the results are reviewed and investigated by the FDA (and legal bodies in other countries), before a drug or device can be used by a physician. This is an expensive and time-consuming process, in which alternative medicine hardly ever participates.

Now it’s not ethical to test every medical hypothesis with a clinical trial. For example, we know that smoking is bad for your health. Yet, tobacco manufacturers love to insist that there has never been a clinical trial that makes this conclusion. The reason that is true is that it would be unethical to give one group of adults cigarettes for 20 years and another group nothing to see if one would die at a higher rate. So we use epidemiological studies to determine if we can see in a population whether a cause has an effect. We can review records of thousands of smokers to see what the effect will be. Once again, pushers of alternative medicine therapies have not published a study of all the patients who might have used their therapy and see the result. Epidemiology is a scientific process that is critical to preventative medicine–without it, we cannot know if some behavior or public health issue has a causal effect on health.

Remember, anecdotes (“my mother’s friend’s cousin’s daughter was cured by eating this leaf”) are not reasons to accept alternative medicine. Even anecdotes that try to sound like science (“90 out of 100 people think this leaf does work”) aren’t a reason to “believe” in a pseudoscience.

You might have heard that taking lots of Vitamin C helps prevent colds. It doesn’t. And that conclusions is supported by large clinical trials, so unless you are afflicted by scurvy, there’s no reason to take large doses of the vitamin. And that’s the difference between real science and pseudoscience.