I have written numerous times about the Vaccine Adverse Event Reporting System (VAERS) because it is the database of choice for the anti-vaccine world to “prove” that a vaccine is dangerous. It is misused even though it does not tell scientists whether a vaccine is harmless or harmful.
Even though I’ve discussed it many times, I’ve usually critiqued VAERS here and there in different ways, so I wanted to write down, in easy-to-consume, bullet points. I love bullet points since if you have a limited amount of time to read through thousands of words, you can find the information you need easily.
So here we go, let’s take a look at the dumpster-diving into the VAERS database.
What is VAERS?
The Vaccine Adverse Event Reporting System (VAERS) is one of the systems employed by the US Centers for Disease Control and Prevention (CDC) and the Food and Drug Administration (FDA) to monitor vaccine safety. VAERS is a post-marketing surveillance program, collecting information about adverse events (including death) that occur after the administration of vaccines to ascertain whether the risk-benefit ratio is high enough to justify the continued use of any particular vaccine.
VAERS, the Vaccine Safety Datalink (VSD), the FDA’s Post-licensure Rapid Immunization Safety Monitoring System (PRISM), and the Clinical Immunization Safety Assessment Network (CISA) are the major tools used by the CDC and FDA to monitor vaccine safety. These are powerful tools that provide full information about each patient so that correlation and causation may be determined through powerful case-control or cohort analyses of the data.
And in contrast to VAERS, PRISM, VSD, and CISA are active reporting systems in that electronic health records are actively monitored for AEs after vaccination to identify potential safety signals.
However, there are no analyses that can establish any type of causation between the vaccination and the claimed adverse event that is reported to the VAERS database. Frankly, it can be gamed by those with nefarious intentions, which can limit the value of the VAERS data.
To be honest, VAERS is a feel-good system for those who think that there’s a link between vaccines and something terrible, but without an active investigation, the data is just above the level of totally meaningless. Most epidemiologists know it is valueless as a database to determine correlation and/or causation. Even the VAERS system itself says that the data cannot be used to ascertain the difference between coincidence and true causality.
According to the CDC:
Established in 1990, the Vaccine Adverse Event Reporting System (VAERS) is a national early warning system to detect possible safety problems in U.S.-licensed vaccines. VAERS is co-managed by the Centers for Disease Control and Prevention (CDC) and the U.S. Food and Drug Administration (FDA). VAERS accepts and analyzes reports of adverse events (possible side effects) after a person has received a vaccination. Anyone can report an adverse event to VAERS. Healthcare professionals are required to report certain adverse events and vaccine manufacturers are required to report all adverse events that come to their attention.
VAERS is a passive reporting system, meaning it relies on individuals to send in reports of their experiences to CDC and FDA. VAERS is not designed to determine if a vaccine caused a health problem, but is especially useful for detecting unusual or unexpected patterns of adverse event reporting that might indicate a possible safety problem with a vaccine. This way, VAERS can provide CDC and FDA with valuable information that additional work and evaluation is necessary to further assess a possible safety concern.
The VAERS website adds the following disclaimer:
VAERS accepts reports of adverse events and reactions that occur following vaccination. Healthcare providers, vaccine manufacturers, and the public can submit reports to the system. While very important in monitoring vaccine safety, VAERS reports alone cannot be used to determine if a vaccine caused or contributed to an adverse event or illness. The reports may contain information that is incomplete, inaccurate, coincidental, or unverifiable. In large part, reports to VAERS are voluntary, which means they are subject to biases. This creates specific limitations on how the data can be used scientifically. Data from VAERS reports should always be interpreted with these limitations in mind.
The strengths of VAERS are that it is national in scope and can quickly provide an early warning of a safety problem with a vaccine. As part of CDC and FDA’s multi-system approach to post-licensure vaccine safety monitoring, VAERS is designed to rapidly detect unusual or unexpected patterns of adverse events, also known as “safety signals.” If a safety signal is found in VAERS, further studies can be done in safety systems such as the CDC’s Vaccine Safety Datalink (VSD) or the Clinical Immunization Safety Assessment (CISA) project. These systems do not have the same scientific limitations as VAERS, and can better assess health risks and possible connections between adverse events and a vaccine.
Point 1 — It cannot establish a correlation
- The database is biased to those who have reported an adverse event. No one submits a report to VAERS stating “everything was perfect.”
- The reports are nothing more than anecdotes. Medical reports are not submitted to VAERS, so we cannot actually show that there is a temporal relationship between the reported adverse event.
- The system can be gamed by people submitted frivolous or fake reports.
- VAERS lacks information to establish confounding data which may show that adverse events after vaccination are correlated to other health factors.
- To establish correlation, one needs two groups, or cohorts, with full medical records to compare adverse events between a vaccinated and an unvaccinated cohort. There are powerful databases that actually allow you to do this, including the Vaccine Safety Datalink (VSD).
- Because correlation requires a comparison to
- VAERS reports are perfect examples of post hoc ergo propter hoc fallacies — assuming that if one event follows another event, the first event must cause the second event. It mostly does not.
Point 2 — Without correlation, you cannot establish causation
Even if you could show correlation, as I’ve written before, correlation is not equivalent to causation. Establishing causation, if you have established correlation requires several steps:
- The data must be strong. If one observes correlation, the next step is to establish whether the data is strong enough to support a causal link. For example, if we’re examining an increase in the risk of something, the numbers have to be substantial.
- The data must be consistent. If one shows data that could imply causation, it must be consistent across a number of studies with different populations (gender, ethnicity, income, age).
- The data must be specific. The data must predict causality, very precisely. One cannot show causality with general data, such as found with VAERS, simply because the data is too imprecise.
- The data must be temporal. To show causality, the medical event must (whether adverse or beneficial) follow the proposed cause within a relatively short period of time. As the length of time grows between the cause and the event, confounders become more and more difficult to separate from the causal factor that you’re trying to examine. Moreover, there may be a background rate for a particular adverse event that happens in unvaccinated populations.
Now, an anti-vaxxer may jump on this point and try to claim that a vaccine’s adverse effects could show up 20 years from now. My response is to “show me correlation, and then we’ll talk.” Moreover, a vaccine only takes a few hours to cause the adaptive immune system to create antibodies, and then it disappears from the body. It is implausible to argue that a vaccine that only remains in the body for a few hours or a day can cause an effect many years from now, but all I can say is “show me.”
- The data must possess a dose-response effect. That is, one can show that as you consume or receive more of X, the specific Y response increases. Back to smoking –the more cigarettes smoked, the higher the risk of lung cancer. So, if we were to examine a particular specific adverse event to vaccines, then the rate of that specific risk must increase in a linear fashion with additional numbers of vaccines.
- The implication of causality must be biologically plausible. You must show a biologically plausible mechanism that could presumably explain a link between the vaccine and an adverse effect.
Plausibility doesn’t mean we take the easy way and just say, “well, just because we don’t know of a mechanism doesn’t mean there isn’t one.” Actually, we shouldn’t say that. We know a lot about human physiology. It’s not a giant mystery wrapped around an enigma. Human physiology is complex and detailed, but it is possible to determine what may or may not be plausible.
- The data must be coherent. Other types of evidence, like experimental ones in other models or clinical trials, ought to support the causality.
Point 3 — It is cherry picking
Those that use VAERS to support their claims about the danger of vaccines cherry-pick VAERS data while ignoring published clinical trials, peer-reviewed epidemiological studies, and better databases that completely contradict the “conclusions” from VAERS.
They use VAERS because it’s easy and because they can ignore all the published evidence that debunks their claims while using the one thing that supports their pre-ordained conclusions.
Point 4 — Dumpster diving with bad math
Those individuals who use VAERS to make their point often use simplistic math without powerful statistical analyses that can determine correlation. Finding X number of cases of something and then dividing that by the presumed number of total vaccines or, worse yet, the total number of reports in the database is not how real analyses of adverse events are done.
A bunch of people, who do not have experience or education in epidemiology and statistics (or the statistics of epidemiology), are downloading Excel files from VAERS and making amateurish attempts at establishing a correlation between vaccines and adverse events. This is almost laughable if it weren’t such a serious problem in vaccine hesitancy — people without an understanding of VAERS are scared by what is being stated after misusing the database.
Point 5 — Peer-review
Most of the VAERS-based studies are not published in respected peer-reviewed journals. Because if they had real data that showed hundreds of deaths after vaccination, that would be big research, and the top journals would fall all over themselves to publish it.
Instead, most of these studies are either self-published (with no peer review) or published in predatory journals, which have cursory or no peer review at all. Peer review is not perfect, but for top journals, which have to uphold their reputation by making sure that some experts review the data and analyses. And most peer-reviewers would look askance at VAERS data being the basis of any conclusion.
But my central point remains — if an anti-vaccine “researcher” wants to convince me of some adverse event being causally related to vaccines, it better be in the form of the highest quality evidence.
Point 6 — There are better tools available
The surest sign that the anti-vaccine “researchers” are not interested in real science is that they ignore the more powerful databases that can be accessed by anyone who agrees to their terms (like keeping patient data confidential, something that anti-vaxxers have violated in the past).
Like I mentioned before, the Vaccine Safety Datalink, the FDA’s Post-licensure Rapid Immunization Safety Monitoring System, and the Clinical Immunization Safety Assessment Network are all high-quality databases that allow the researcher to do powerful cohort and case-control studies that can be used to develop a convincing correlation between vaccines and adverse events, if they do, in fact, exist.
Point 7 — How to use VAERS properly
As Orac recently wrote, “…VAERS is a hypothesis-generating, not a hypothesis testing, system, and its hypotheses are tested using better systems, like VSD, CISA, and PRISM.” VAERS is an observational system — it’s like the canary in the coal mine, it tells us that there might be a problem, but it lacks specificity.
So the CDC observes VAERS for reports, then uses more powerful, less-biased databases to determine if the observation is linked to vaccines. That is what is meant by “safety signaling” — VAERS triggers further analysis by the CDC and/or FDA. Anti-vaccine “researchers” are trying to convince us that the safety signal is factual rather than do the hard work to do further scientific analysis using better databases.
I am beginning to sound like a broken record complaining about the abuse of VAERS. The database does have usefulness — it is an observational tool to watch for safety signals. And if those signals appear, then, using better tools and better analytical methods, one can determine if the safety signals are just random or are correlated with vaccination.
But downloading an Excel file from VAERS, then claiming it tells us something is just bad science, bad statistics, and bad epidemiology. It has almost no meaning.
Don’t be fooled when someone says they have a “gotcha” with the VAERS database, because because of the points I made above, they probably haven’t. No, not probably, most definitely they haven’t.