Anecdotes of “Vaccine-Injured Children” – What Can They Really Tell Us?

If you’re familiar with the information provided by anti-vaccine websites, then you have probably encountered some anecdotal (word of mouth) accounts of children getting injured by vaccines. The story usually goes something like this: a child receives one or more vaccines and then within a short time frame after vaccination, the child experiences an adverse event. Examples of some of these stories include sudden infant death syndrome, autism, and others.

My heart goes out to the parents of these children. To some, this may come across as a disingenuous sentiment from an internet blogger. However, the truth is that a member of my immediate family has autism and I have witnessed firsthand, for over two decades, some of the challenges that parents may face following such a diagnosis. I have also experienced a variety of challenges as well.

These anecdotal stories can be incredibly alarming to the well-meaning parent that is trying to decide whether to vaccinate their own child, or to the parent trying to determine whether a vaccine was the cause of their child’s ailments. The end result is that many parents could come away with the impression that vaccines are unsafe and potentially life-threatening.

Reliability

It is certainly understandable that parents might associate an adverse event with a vaccine if these two occur around the same time. What is crucially important, however, is how reliable this temporal (timing) correlation of events is in terms of informing us as to what is true. Can this evidence reliably tell us whether there is a causal relationship between the two events?

Let’s consider the example of the measles, mumps, rubella (MMR) vaccine and autism. Although there is a lot of other evidence on this topic, for now, I am only interested in looking at the temporal coincidence of events and determining what this specific evidence can tell us.

Every year, roughly 4 million children are born in the US. It is estimated that the current rate of autism spectrum disorder (ASD) is about 1 in 68. So every year there are over 58,000 children diagnosed with ASD, which amounts to an average of approximately 160 children diagnosed with ASD every single day.

On average, children are diagnosed with ASD around the age of 4, but signs of ASD can be noticed by parents as early as before the 1st birthday. The vaccination schedule in the US recommends a first dose of MMR at 1 year of age and a second dose at 4-6 years.

Armed with this information, imagine a 6-year calendar (or 6 normal calendars linked together) that represents the first 6 year span of children’s lives. Next, populate that calendar with dots representing the time at which children are diagnosed with ASD. As mentioned earlier, the average rate is 160 per day, so each day on the calendar needs on average 160 dots. Now, children aren’t very likely to be diagnosed in the first few months, so move those dots to a later time in the calendar. For simplicity, let’s assume that all the kids’ parents follow the recommended schedule and give the first dose of MMR on their first birthday and the second dose on their 4th birthday.

Snapshot of a 2 week span in the calendar. One dot represents one ASD diagnosis on the given day. Is it possible to determine which dots are coincidental and which are not?

With this calendar in mind (marked with dots representing ASD diagnoses and two vaccine dates marked), is it possible that there are dots that happen to fall on the vaccination days, or within one week of vaccine administration? Given the large number of dots, basic statistical probability would say that it is extremely likely that some dots will fall after vaccine administration. In other words, it would be extremely unlikely if there were NO dots following the vaccination days. Given this, it is very likely that we will have some coincidences in timing between some ASD diagnoses and vaccination. This doesn’t mean that those dots are absolutely coincidences, but the simple truth is that based solely on this evidence, there is simply no way to determine which dots are coincidental, if any, and which dots might be due to the vaccines, if any.

This may seem like a somewhat contrived example, but the truth is that one can set it up however they like and the main conclusion is unchanged. We could add or remove vaccines, increase or decrease the number of diagnoses, change the length of the calendar, change the vaccine type, change the adverse event from autism to death or something else. We could even change the distribution of dots so that more dots are clustered around one time compared to others. No matter what, there is just no reliable way, based solely on this evidence, to be certain as to whether the adverse event is causally associated with the vaccine. We cannot separate the coincidental events from the causally associated ones. In order to do this, we need more evidence. We also need more evidence in order to answer questions such as: How many children that received the MMR were diagnosed? How many children that did NOT receive the MMR were diagnosed? Is there a significant difference between these two groups?

Unfortunately, instead of being skeptical and asking themselves these kinds of questions, many parents will understandably fall victim to a logical fallacy when faced with these kinds of vaccine injury stories. They may also fail to recognize that any emotional attachment to their belief, while being completely normal, has no influence on the truth.

Post Hoc Ergo Propter Hoc

Concluding a causal relationship based on succession of events is known in philosophy as a logical fallacy called post hoc ergo propter hoc, or post hoc fallacy for short. It is a logical fallacy that states “Since event Y followed event X, event Y must have been caused by event X.” For more on this, Paul Henne, a philosophy graduate student at Duke University, has a great video with further explanation.

Inconsistent Logic

Consider two cases:

1) You read a blog post about a child that received a vaccine and subsequently developed autism
2) You read a blog post about a child that received a vaccine and did not subsequently develop autism

If case 1 is sufficient evidence to assume causation, then case 2 must be sufficient as well. Clearly, this logic is inconsistent because it leads us to contradictory conclusions when both cases are considered.

Conclusion

Sadly, many well-meaning parents in the anti-vaccine movement fall prey to this logical fallacy. So from now on, if you hear about someone referring to their “vaccine-injured” child, remember that they are likely coming to this conclusion based on a succession of events and that in order to determine what is really true, we need to be skeptical and consider higher quality evidence.