Monthly VAERS Reports

This page displays monthly reports on event data from the US government’s Vaccine Adverse Event Reporting System (VAERS). Reports are provided by Mothering Expert Steven Rubin, PhD, a computer scientist who maintains the online searchable VAERS database, MedAlerts, and volunteer data reporter for the National Vaccine Information Center (NVIC). Please view his bio at the bottom of this page.

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About VAERS - from the VAERS website

The Vaccine Adverse Event Reporting System (VAERS) is a national vaccine safety surveillance program co-sponsored by the Centers for Disease Control and Prevention (CDC) and the Food and Drug Administration (FDA). VAERS is a post-marketing safety surveillance program, collecting information about adverse events (possible side effects) that occur after the administration of vaccines licensed for use in the United States.

The National Childhood Vaccine Injury Act (NCVIA) of 1986 requires health professionals and vaccine manufacturers to report to the U.S. Department of Health and Human Services specific adverse events that occur after the administration of routinely recommended vaccines. In response to NCVIA, CDC and FDA established the Vaccine Adverse Event Reporting System (VAERS) in 1990 (Chen, Vaccine, 1994).

About MedAlerts - from the MedAlerts website

Medalerts.org offers an alternative to CDC Wonder, the U.S. Government’s official search engine. Medalerts is built directly from the U.S. Government data so it contains the same information. However, this site offers a better user interface, more powerful search capabilities, and more extensive reporting.

About NVICfrom the NVIC website

The National Vaccine Information Center (NVIC) is a national, non-profit educational organization founded in 1982. The oldest and largest consumer organization advocating the institution of vaccine safety and informed consent protections in the mass vaccination system, NVIC is responsible for launching the vaccine safety and informed consent movement in America in the early 1980′s.

Available Reports – compiled and written by Steven Rubin, PhD

View the available monthly reports, in reverse chronological order, below.

 

August 2011

This month, let’s look at children’s vaccinations. The CDC has two recommended immunization schedules, for ages 0-6 and ages 7-18. How do these vaccines affect our children?

To find out, we will use MedAlerts to look at serious VAERS events in these age groups. Serious VAERS events (those that are life-threatening, involve hospitalization, permanent disability, or death) are important measures of a vaccine’s safety.

To do the search, make a graph of Vaccine Type. Then, in Section 4 of the search form, check Serious in the upper-left and in Section 5 of the search form, click on Age (Range) and specify a range of ages in the From and To fields:

  • To see children ages 0-6, set From to 0 and To to 7. Note that the “To” field is the upper bound, so making it 7 requests everything below 7, or 0-6.
  • To see children ages 7-18, set From to 7 and To to 19.

The two graphs are shown below (with only the recommended vaccines shown).

As you can see, children age 0-6 years are reporting the most VAERS events following a DTP vaccination.

Children ages 7-18 years are significantly affected by the Human Papillomavirus (HPV) vaccination. Note that HPV is already associated with over 100 deaths, and is not limited to girls (there are three reports of boys who have died following an HPV vaccination). This is not the most widely given vaccination for 7-18 year olds, but it appears frequently in VAERS and is associated with serious adverse effects.


July 2011

Our ability to understand information often requires us to have other, related information, in order to “get the big picture”.

For example, we know that there have been 1822 Flu-related VAERS reports from the state of Illinois, and 1829 Flu-related VAERS reports from the state of Massachusetts. This information might make us think that the chance of having an adverse reaction from a Flu vaccine is the same in each state. But Illinois has about 12 million people and Massachusetts has about 6 million people, so in truth, Illinois has an adverse Flu vaccine reaction rate that is half that of Massachusetts. MedAlerts knows how to use state population information to give us a better understanding of the VAERS data (for more, see the May 2010 blog entry).

Another piece of related information that has been missing from MedAlerts (but is now available) is the number of doses of each vaccine that have been given. Without this information, it might appear that a widely-given vaccine, such as MMR, is more dangerous than a less-given vaccine (like Yellow-Fever) because there are many more VAERS reports that mention MMR. But if we consider the actual number of vaccinations that are given, it might turn out that the rate of injuries is much different.

How does MedAlerts know the number of vaccines that have been given? The CDC has actually been gathering this information for many years and making the data public (they call it “biologics surveillance”). Each year, pharmaceutical manufacturers report the number of doses distributed as well as the number of doses that are returned (hospitals and doctors can return unused doses to the manufacturer). The difference between the number of doses distributed and the number of doses returned is the net number of doses, and is considered to be the number of doses given. Of course, this figure is certainly higher than the actual number of doses given, because there must be doses that get destroyed, lost, or otherwise not actually given. Nevertheless, these figures are the best information available for determining the number of vaccines given. To see the latest dosage data that is used by MedAlerts, including references to the original CDC documents, click here.

And how can MedAlerts use this data? As usual, it is necessary to check Expert Mode in the upper-right of the search form, because seaches that use this information are specialized. Then, it is possible to apply this data by individual year, or by total reports across all years. To make a graph or table by individual year, select Year of Vaccination (dose-adjusted). To see a graph or table that considers all years, select Vaccines (dose-adjusted).

Let’s make a graph of each vaccine and look at the rate of VAERS reports associated with each (across all years). Make a graph of Vaccines (dose-adjusted). It looks like this:

First the good news: the numbers are quite small. The average vaccine is below the first vertical line (0.0010) which means that for every 1000 vaccines given, only one VAERS report is filed. But of course, we have already established that MedAlerts is using a vaccine dose count that is too high, and it is well known that the number of VAERS reports is low (by anywhere from a factor of 10 to 20 to a factor of 25 to a factor of 10 to 100). Both of these errors actually mean that the rate of vaccine injury is much higher than shown here.

The second thing that is clear from this graph is that some vaccines have an unusually high rate of VAERS reports. The worst offender is the Anthrax vaccine, which seems to be nearly 10 times as dangerous as any other vaccine. Could it be that this vaccine is unsafe, but because it is primarily given to military personnel, its danger is overlooked when compared with the other hazards of military life?

Two other vaccines show a high rate of VAERS reports: the Lyme and the Rotavirus vaccines. Both of these were given for only a few years and then withdrawn (Lyme ran from 1999 to 2001 and Rotavirus was available only in 1998). The rotavirus vaccine was withdrawn because of side-effects (bowel obstruction) and this graph supports the suggestion that it had significant side-effects. Removal of the Lyme vaccine is attributed to “poor sales” (see page 7 of this CDC document) but considering the large number of injury reports that appeared in a very short time, it would seem that there might have been another reason for withdrawing the vaccine.

There is much to be learned by combining multiple sources of information, and MedAlerts constantly strives to do this in order to further study issues of vaccine safety. The website’s new dosage data is just starting to be explored, and hopefully more useful analysis will come from it as time goes on.


May 2011

This month I will investigate flaws in the VAERS data. It should come as no surprise that there are mistakes in VAERS data: this sort of thing happens all the time. The culprit is people, and people make mistakes. Let’s look at two problems:

Problem 1: Hospitalization. There are two outcomes in each VAERS report related to hospitalization: Hospitalized and Extended Stay in Hospital. Could it be that a VAERS report indicates an extended hospital stay but does not indicate hospitalization? Clearly, that would be a mistake. To find out, go to Section 4 of the search form and set Hospitalized? to “No” and Extended stay? to “Yes”. The result shows 627 VAERS reports with this mistake!

The ramifications of this mistake are actually significant, because the government often makes a distinction between those VAERS reports that are “serious” and those that are not. Non-serious VAERS reports are typically discarded as unimportant. The definition of “serious” includes hospitalization, life-threatening, disabled, or death, but it does not consider the extended-stay outcome. In fact, of those 627 reports with the hospitalization mistake, 505 of them are non-serious and would, if the mistake were fixed, become serious situations.

Problem 2: Gardasil underreporting. Each VAERS report lists the vaccinations that were given and also has a write-up that describes the problem. Is it possible that Gardasil is mentioned in the write-up but is not in the list of vaccinations that were given? To find out, check Expert Mode (needed to search for vaccines that were not given). Then in Section 2, set the Write-up field to “gardasil”. Finally, in Section 3, choose the “HPV” and “HPV4″ vaccines and check Excluded. HPV4 is Gardasil and HPV is a generic vaccine that could be Gardasil or Cervarix. By excluding both of these possibilities, we are finding VAERS reports that specifically do not list Gardasil.

How many reports match this search? 116! But let me immediately point out that this search does not necessarily indicate a mistake in the VAERS data. A careful reading of the write-ups in these reports reveals that many of them mention Gardasil without claiming that it was given to the patient. Some of the write-ups say that “Gardasil was not given” or that the patient intended to get Gardasil but was given a different vaccine instead. Some describe newborn infants who were exposed to Gardasil during their mother’s pregnancies. Of the 116 reports uncovered by this search, 43 of them follow one of these patterns and indicate that Gardasil was not given.

And what about the 73 reports that claim Gardasil was given? Why wasn’t it listed in the report? Some are clearly human error (either the VAERS submission form was filled-out incorrectly or a typo was made). Some appear to combine multiple medical situations into a single report and lose information in the process. Some list an “unknown” vaccine having been given, but it is clear from the writeup what that vaccine actually was.

Remember that I am not a health professional, so it is possible that some of these 73 VAERS reports are simply not Gardasil-related. In any case, here are the 73 reports that I think are mistakes. The numbers listed here are the VAERS ID numbers. Click on them to see the full report.

188549 273437 275509 275604 282553 290709 290916 291020 291023 291131
292483 294675 299087 302119 302324 303464 305287 305397 305679 306626
306710 307011 308064 308192 308245 309086 313806 313931 314847 316136
318397 318485 319741 321093 321118 321327 323639 324149 324636 327723
330258 330468 335597 336766 339137 341496 342125 342365 343296 344175
348025 350028 351587 354656 356422 359436 365986 368786 370905 377450
381727 386584 388326 388387 394854 397983 398183 407916 417338 418531
421475 423293 423546

Some people might jump to the conclusion that this an attempt to hide information, but I do not think so. There are many people involved in the collection of this data, all of whom can make mistakes:

  • Patients and relatives. Inexperienced people can easily make mistakes when filling out the VAERS submission forms.
  • Doctors. Busy doctors filling-out forms at the end of a long day can make mistakes.
  • Drug companies. Some reports are submitted by the drug companies, and they are dealing with third-hand data.
  • VAERS. The people at the VAERS agency might make mistakes, too. To me, this is the least likely explanation as I discussed a few months ago. In fact, I’m hoping that this blog reaches the appropriate people, and that the VAERS data is fixed. If this happens, then people reading this blog years from now will not be able to reproduce the mistakes I’ve described.

 


April 2011

This month, let’s look at the most simple of VAERS data searches: Age. In particular, we will ask what is the typical age of a VAERS patient, and what is the typical age of a patient who died following a vaccination.

Now if vaccination-related deaths happen uniformly, to people of all ages, then the two curves should look the same. If, however, vaccination-related deaths happen more predominantly to certain age groups, then this will stand-out. Here are the graphs:

The graph of all VAERS reports (on the left) is not surprising. It show that most VAERS reports involve young patients, which makes sense because most vaccinations are given to children. There is also a peak in the 17-44 category. But this is not a real peak; it is an anomoly caused by the unequal groupings. The 17-44 year range is the widest by a large margin, so it includes a large number of VAERS reports.

The graph on the right (VAERS events where the patient died) is surprising. It shows a much stronger peak among young children (below age 3). This peak is so strong that it even towers over the wide grouping of 17-44 year-olds.

There are really two problems with these graphs: (1) the age groupings are not uniform, making some groupings stand out unfairly, and (2) it would be helpful to analyze the 0-3 year old range in more detail to see exactly when these children are dying.

To solve this problem, MedAlerts lets you set different age groupings. It is another of the site’s “special features,” so to use it you must check the “Expert Mode” box in the upper-right. Then, instead of making a graph of Age, make a graph of Age, Custom. Custom Age graphs let you specify where you want the age breaks to occur. There are even a few buttons on the right side of the age break section that automatically fill it in with some “standard” schemes.

So let’s redo the above two graphs, but this time use the age breaks that CDC Wonder suggests (click “Set Wonder” in the Custom Age section). The results are here:

Now the graph of all VAERS events (on the left) does not show such a strong peak in the 17-44 range, but instead has most of its emphasis on people 18 years and younger. This is to be expected.

We also see in the graph of patients who died (on the right) that the peak for young people continues to be pronounced, and that this peak happens in the first 6 months of life.

Can we explore this at even more detail? Just set the age breaks to be even smaller. The graph below sets age breaks at 0.1 years, 0.2 years, 0.3 years, etc. This is the level of resolution that appears in VAERS reports (they seem to report age in tenths of a year, rather than twelvths of a year as you might expect). The graph below shows the age of patients who died in the first year of their life:

And now we see where it is happening: at about 3 months of age. No other age seems to die after a vaccination as much as these 3-month olds. It makes you wonder whether this is a bad time to get vaccinated.


March 2011 VAERS Report

This month, let’s look at the most simple of VAERS data searches: Age. In particular, we will ask what is the typical age of a VAERS patient, and what is the typical age of a patient who died following a vaccination. Now if vaccination-related deaths happen uniformly, to people of all ages, then the two curves should look the same. If, however, vaccination-related deaths happen more predominantly to certain age groups, then this will stand-out.

Here are the graphs: The graph of all VAERS reports (on the left) is not surprising. It show that most VAERS reports involve young patients, which makes sense because most vaccinations are given to children. There is also a peak in the 17-44 category. But this is not a real peak; it is an anomoly caused by the unequal groupings. The 17-44 year range is the widest by a large margin, so it includes a large number of VAERS reports. The graph on the right (VAERS events where the patient died) is surprising. It shows a much stronger peak among young children (below age 3). This peak is so strong that it even towers over the wide grouping of 17-44 year-olds. There are really two problems with these graphs: (1) the age groupings are not uniform, making some groupings stand out unfairly, and (2) it would be helpful to analyze the 0-3 year old range in more detail to see exactly when these children are dying. To solve this problem, MedAlerts lets you set different age groupings. It is another of the site’s “special features,” so to use it you must check the “Expert Mode” box in the upper-right. Then, instead of making a graph of Age, make a graph of Age, Custom. Custom Age graphs let you specify where you want the age breaks to occur. There are even a few buttons on the right side of the age break section that automatically fill it in with some “standard” schemes. So let’s redo the above two graphs, but this time use the age breaks that CDC Wonder suggests (click “Set Wonder” in the Custom Age section).

The results are here: Now the graph of all VAERS events (on the left) does not show such a strong peak in the 17-44 range, but instead has most of its emphasis on people 18 years and younger. This is to be expected. We also see in the graph of patients who died (on the right) that the peak for young people continues to be pronounced, and that this peak happens in the first 6 months of life. Can we explore this at even more detail? Just set the age breaks to be even smaller. The graph below sets age breaks at 0.1 years, 0.2 years, 0.3 years, etc. This is the level of resolution that appears in VAERS reports (they seem to report age in tenths of a year, rather than twelvths of a year as you might expect).

The graph below shows the age of patients who died in the first year of their life: And now we see where it is happening: at about 3 months of age. No other age seems to die after a vaccination as much as these 3-month olds. It makes you wonder whether this is a bad time to get vaccinated.

December 2010 VAERS Report

2010 is over and complete VAERS data for the year has been published by the government. Since 1990, when VAERS began, the number of reports added each year has almost always gone up. But not this year. In 2010, there were 36,818 new reports added, whereas 2009 had an all-time high of 37,181 (really, not very different). Here is a graph of the number of VAERS events released each year. To see this for yourself, click Show Graph (in Section 1) and graph Year of Appearance.

Last January, I looked at the dramatic rise in the the number of VAERS events during the past few years and analyzed the cause. In that report, I separated the VAERS events according to the vaccines given and the diseases they address. Let’s look at that graph again with the 2010 data included. To do this, click Show Graph (in Section 1) and graph Year of Appearance and Vaccine Type. To make it easier to read, I have simplified the graph by removing diseases that are associated with few VAERS events.

The graph shows a serious spike in Influenza-related reports during the last two years. Suddenly, there are about three times as many adverse events being reported following Flu shots. Of course, concerns about the H1N1 Flu caused more people to be vaccinated during these years, but were there really three times as many people vaccinated? The numbers do not show that. The CDC reports that in the 2005-2006 Flu season, about 30% of adults (age 18-49) got the vaccination. Older people got it at higher rates (36% of 50-64 year olds and 69% of people 65 and over). Further, they claim that this figure was a drop of about 5% from the 2003-2004 season. Other reports on the web confirm that about 1/3 of adults get a Flu shot in a typical year. And what about the 2009-2010 Flu season? The Rand Corporation estimates that during last year’s Flu season, 39% of adults were vaccinated, which is only a small increase over typical years. So it is not reasonable to blame the rise in adverse events following the Flu shot on the increased number of people getting it. There must be some other explanation. One explanation for the rise in the number of Flu reactions is that during the 2009-2010 Flu season, people got two shots, for both Seasonal Flu and H1N1 Flu. Of course, that would only account for a factor of two rise, not a factor of three. Also, not everybody got two shots. Let’s graph the three main Flu vaccinations that were reported in the past two years. The red line is Seasonal Flu, the purple line is the H1N1 Flu, and the green line is this year’s Seasonal Flu (which has H1N1 in it). While it is true that 2009 had a double-spike of Flu reports, 2010 has just a single spike. Something is causing an increase in the number of reactions to the Flu shot, and it isn’t just that more people are getting it. We should all wonder why nearly half of recent VAERS reports involve people who have gotten a Flu shot.

 


 

November 2010 VAERS Report

It has been suggested that the H1N1 Flu vaccine causes miscarriages (see, for example, here, here, and here). This month, I want to see if the claim is supported by VAERS data. How do we determine whether a VAERS event resulted in a miscarriage? VAERS uses the MedDRA symptom classification, which organizes all known symptoms at five levels of detail. At the second level of detail is an entry “Abortions and stillbirth” which has under it “Abortion related conditions and complications”, “Abortions spontaneous”, “Stillbirth and foetal death” and “Abortions not specified as induced or spontaneous”. Each of these is further refined into specific symptoms. So it seems that this second-level term (or as it is known in MedDRA, the High-Level Group Term or HLGT) is a valid way to identify miscarriages. Now let’s search all of the VAERS events (going back to 1990) for this symptom and make a graph of the vaccines listed in those events. To do this, check Expert Mode (to enable MedDRA searches), click Show Graph and graph Vaccines (in Section 1), and select the MedDRA level HLGT under the symptom list and then select Abortions and stillbirth (in Section 2). This graph will surely favor vaccines that have been given for 21 years over those that have been recently introduced, because such vaccines will have been given much more, and so will have produced many more symptoms. In other words, this graph should de-emphasize the H1N1 Flu vaccine, which has existed for just one year. We should see relatively few H1N1-related miscarriage events compared with the “Seasonal” Flu vaccine which has been administered to many more patients. Here is the graph:

The results are shocking. First of all, the H1N1 Flu vaccine has appeared in miscarriage events more often than almost any other vaccine. Of the 1115 VAERS events that mention the abortion/stillbirth symptom, 203 are cases where the H1N1 Flu vaccine was given (200 with the FLU(H1N1) vaccine code and 3 with the FLUN(H1N1) vaccine code). This ignores the current Flu vaccine being given which has the H1N1 strain in it (the FLU(10-11) vaccine code). By contrast, there are only 63 abortion/stillbirth events associated with the Seasonal Flu Vaccine (vaccine codes FLU and FLUN) and this vaccine has been administered to millions of people over 21 years of data collection! If you consider that the H1N1 Flu vaccine has been associated with 3 times as many abortion/stillbirth events, and that it has been given for just 5 percent of the time that Seasonal Flu vaccines have been given, then it appears that the H1N1 Flu vaccine is 60 times more likely to cause a miscarriage than the Seasonal Flu vaccine. But the graph has more shocking results for us. The H1N1 Flu vaccine appears in many of the abortion/stillbirth cases, but not the most. The “winner,” appearing in 297 of the VAERS records associated with miscarriage, is Gardasil (vaccine code HPV4)! Once again, this vaccine is a newcomer, having only existed for 4 years. So pregnant women should read the product manufacturer’s insert for the vaccine they are considering and speak with one or more trusted health care professionals before making a decision about vaccination during pregnancy.

 


 

October 2010 VAERS Report

October VAERS data is out and it has a few surprises.

HPV

Four new deaths were reported in conjunction with Gardasil. This is relatively high for a single month. But more significantly, it was the first time in which one of them was a boy. There are now 89 VAERS reports in which the patient died after being given a Gardasil or Cervarix vaccination.

H1N1 Flu

But even more surprising in the October VAERS data is the appearance of 217 new reports about last season’s H1N1 Flu vaccine. This batch of bad news lists 14 deaths and another 76 “serious” cases. The H1N1 Flu vaccine has now been associated with 105 deaths. Why, when this winter’s Flu season is in full swing, are we still learning about the last Flu season? The answer has two parts: (1) the new reports are not from the US and (2) they took a long time to get here. Each of these new reports states in its write-up that it was sent by the manufacturer on August 25 of this year and involves a patient in a “foreign country” (but does not say which). You can find these reports for yourself by searching for “25 August 2010″ in the Write-up Symptom field. What can we learn about these reports? I wanted to find out when these vaccinations were given so I made a graph of the vaccination dates, by month. On the left is a graph of the new reports and on the right is a graph of the previous H1N1 data.

The new reports follow the same pattern as existing data, which peaks at the start of the winter Flu season. But notice that the new data is shifted by half a year and peaks in April! The obvious explanation for the half-year shift is that these reports come from a country below the equator, where the winter Flu season is in April. That means the data comes from Australia, New Zealand, or somewhere in Africa, or South America. But one question remains: why, if the data was sent on August 25, did it take this long to appear in VAERS? Every VAERS report has date information telling when it was submitted to VAERS and when it actually appeared in VAERS. It would make sense if the submission date of these new reports was in August or September. However, only one of these reports was submitted in August and just 67 of them in September. The bulk of them (149) were not submitted until October. Who knows whether more will be submitted in November. Why the delay? It could be pointed-out that VAERS, which is chartered with releasing this data, is also chartered with protecting the identity of the people involved. This “sanitizing” of the data to hide identification probably takes some time. However, most drug companies that collect and submit data to VAERS do a pretty thorough job of sanitizing the data themselves. In fact, the typical VAERS report that comes from a pharmaceutical corporation has so much of the data removed that it is less useful for normal analysis (for example, the state in which the patient lives is often missing). Regardless of whether or not the full story has been told, this new data from a southern-hemisphere country shows that the H1N1 Flu Vaccine left a wide swath of damage in its path.

 


 

September 2010 VAERS Report

The government has released data to the end of September, 2010, and Flu related VAERS events are starting their standard upward spike. Last year, I looked at 20 years of Flu related VAERS events, broken out by month of vaccination. It showed a typical trend that starts to be noticeable in September, peaks in October, and then tapers off through the rest of the winter. This is when people get their Flu shots. This month I will run the same analysis as last year and see how it compares. First last year’s graph:

Last year at this time it was clear that September reports were unusually high. The month already had 1000 Flu-related VAERS events (see point “A”), and when all of the reports were in, September ended up with over 2500 events (see point “B”, below). This is phenomenal because no prior year had recorded even 400 events: last year showed a 600% growth in Flu-related VAERS events! So what does the graph look like this year, as of the end of September? There is much lower pressure this year for getting Flu shots: no media and government fear-reports, nobody shouting “pandemic”, and no fears of insufficient serum. There should be many fewer people getting Flu shots, and therefore many fewer VAERS reports. But it’s only getting worse: This September is already showing 1262 Flu-related VAERS events (see point “C”). This is a sizeable increase over the figure as of last September. What is going on? Could it be that more people are getting Flu shots than ever before? Or is the Flu serum particularly toxic this year? Keep in mind that this year’s Flu serum contains three different strains: Influenza B, H3N2 (Hong Kong), and last year’s H1N1 Flu. Some countries have banned the H1N1 Flu vaccine, as I discussed two months ago. One of those countries, Australia, has already been through the Flu season (winter is over down-under). Their experience might be useful to us. Regardless of the cause of all of these Flu vaccine reactions, this year is shaping-up to be an even worse year than last for Flu-related VAERS reports.

 


 

August 2010 VAERS Report

This month I will explore onset intervals, the number of days between taking a vaccination and getting adverse symptoms. I will examine VAERS data by asking this question: What is the typical onset interval, and does it vary with each vaccine? As my January 2010 report showed, examining the database by looking at all of the 70 different vaccines shows way too much information to examine clearly. The solution is to graph vaccine types instead. This groups the vaccines according to the diseases they are attempting to prevent. Since there are only 27 different diseases, the graph is easier to analyze. So for each vaccine type, we want a plot of the number of VAERS events that have a particular onset interval. To do this, check “Show Graph” (in part 1 of the search form) and under it graph “Onset Interval” and “Vaccine Type”. You can uncheck “Show Table” and “Show Event Details”. Here is the graph (ignoring the “unknown” onset intervals): The graph clearly shows that most adverse events happen in the first few days. There seems to be a spike from 10 to 30 days, but this is really a graphing side effect caused by the fact that it starts off going one day at a time and then switches to groups of days (10-14, 15-30, 31-60, etc.) If we redo the graph so that days are never grouped, and then look more closely at the first month, it shows a smooth tapering-off: >From these two graphs, some trends can be seen. The second graph, which zooms closely into the first month, shows a period from 7 to 10 days after the vaccination when some vaccines have a resurgence. What this tells us is that for most vaccines, if there is no adverse reaction in the first 6 days, there probably won’t be one at all. The exceptions are the rubella (German measles) and varicella (chicken pox) vaccines, which may still cause reactions up to 10 days. But the first graph shows another spike that happens years after the vaccine has been given, and it happens only for varicella. This vaccine seems to have extremely long onset intervals, and the graph shows that there are thousands of reports of damage that happen years after the innoculation. What is going on? A look at the reports shows two unfortunate reactions:

  • Varicella. In some cases, the vaccine simply does not work, and the patient develops chicken pox years later. A search of the VAERS data for late onset of chicken pox (more than 120 days) after getting the varicella vaccine turns up 922 reports.
  • Zoster. In some cases, the the patient develops zoster (also called “shingles”) years later. A search for late onset of shingles after getting the Varicella vaccine turns up 775 reports.

Can the varicella vaccine cause shingles? When I did my original research for this this article, just a few months ago, I found a document on the CDC website (www.cdc.gov/vaccines/vpd-vac/varicella/faqs-nipinfo-varicella.htm) which had this in it:

How often does zoster (shingles) occur following varicella vaccination? Varicella vaccine is a live virus vaccine, and may result in a latent infection, similar to that caused by wild varicella virus. Consequently, zoster in vaccinated persons has been reported. Not all of these cases have been confirmed as having been caused by vaccine virus. The risk of zoster following vaccination appears to be less than that following infection with wild-type virus. However, longer follow-up is needed to assess this risk over time.

This statement is no longer available on the CDC website, but it can be found at the Internet ‘wayback machine’ which saves old copies of web pages. A 2005 New York Times article also discusses this problem. So even if the CDC no longer believes that the varicella vaccine can cause shingles, it still seems to be the case from the VAERS data.

 


 

July 2010 VAERS Report

This year, Americans will be offered a Flu shot that has a combination of three different strains: Influenza B, H3N2 (“Hong Kong”), and the 2009 H1N1. But some countries are banning H1N1. This month I will look at two countries that have banned H1N1 and see whether their reason for doing this is true here in the United States.

Finland

Finland has banned H1N1 because of an alarming rise in the number of narcolepsy cases (they had 15 cases following H1N1 flu injections). Have narcolepsy rates associated with Flu shots changed in the United States? To answer this question, we must define “narcolepsy” so that it can be found in MedAlerts searches. As usual, we will consult the MedDRA classification of symptoms. It shows narcolepsy in two different places:

Nervous system disorders    Sleep disturbances       Narcolepsy and hypersomnia
Psychiatric disorders    Sleep disorders and disturbances       Narcolepsy and associated conditions
    (top-level term)    (next-level term)       (mid-level term)
(top-level term)    (next-level term)       (mid-level term)

So we will do this MedAlerts search:

  • Section 1: Check “Expert mode” in the upper right (to get access to MedDRA searches). Check “Show Graph” and graph Month of vaccination.
  • Section 2: Check the MedDRA level called “HLT” (High-level terms), and select the keywords: Narcolepsy and hypersomnia and Narcolepsy and associated conditions.
  • Section 3: Choose the 4 vaccine products: FLU, FLU(H1N1), FLUN, and FLUN(H1N1).

Here is the graph: The number of cases is shown below the date. We can see that in all of the years up to the 2006-2007 season, there were only rare instances of narcolepsy, sometimes 1 or 2, usually none. In the last 3 seasons the rate has increased, going to 12 in the 2007-2008 season, 14 in the 2008-2009 season, and a surprising 60 in the 2009-2010. But this graph combines Seasonal Flu and H1N1, so how do we know whether H1N1 is responsible for the spike? If you separate the 60 events in the 2009-2010 season, 26 are from Seasonal Flu and 34 are from H1N1. So although Seasonal Flu was associated with a large number of narcolepsy cases, H1N1 was found in even more of these events. It appears that Finland’s experience with the Flu vaccine is also happening here in the United States.

Australia

Australia has banned H1N1 because of 23 convulsion cases (mostly in children). The MedDRA places convulsions here:

Nervous system disorders    Seizures (incl subtypes)     (top-level term)    (next-level term)

So we will do this search:

  • Section 1: Check “Expert mode” in the upper right. Check “Show Graph” and graph Month of vaccination.
  • Section 2: Check the MedDRA level called “HLGT” (High-level group terms), and then select the keyword: Seizure (incl subtypes).
  • Section 3: Choose the 4 vaccine products: FLU, FLU(H1N1), FLUN, and FLUN(H1N1).

Here is the graph: The spike this year is easy to see: the 2009-2010 flu season had 587 events that indicate seizure-related symptoms and the administration of a Flu vaccine (274 for H1N1 and 313 for Seasonal Flu). Last year had only 132 events and the year before, 139. Let’s look in detail at the 2009-2010 season to see if children are more strongly affected (as Australia claims). Here is a graph of H1N1 flu associated with convulsions, broken down into three age groups: under 5 years old, 5 to 10 years old, and over 10 years old (these are the cut points for policy recommendations): The children under 5 years of age are indeed more affected by the H1N1 vaccination. So as with Finland, it seems that Australia’s experience with the flu vaccine is also happening here in the United States.

 


 

June 2010 VAERS Report

Autism is an epidemic. Time Magazine reports that 1 in 100 children are autistic. A parent survey claims that it appears in 1 out of 91 children and that boys are four times as likely to be autistic. Although medical professionals deny that there is a link between vaccination and autism, many parents feel otherwise (see here or here). They often blame the MMR vaccine. Are they correct? Let’s ask MedAlerts which VAERS events list autism as a symptom, and which vaccines were given to those people. The first question is which VAERS events have autism as a symptom. This can be asked in two ways, both in Section 2 of the search form:

  • Symptoms. We can search for autism symptoms. To do this, it is helpful to understand the MedDRA symptom classification, which organizes all known symptoms at five levels of detail. MedAlerts normally shows only the lowest level of the symptom classification in the “Symptom Keywords” list. However, in “Expert Mode” (obtained by checking the box in the upper-right of the search form) it is possible to look at any level of the symptom classification. Autism is a collection of low-level symptoms, so it is easier to look one level higher (the “PT” level) for these symptoms. To do this, check “Expert Mode”, choose “PT” under the Symptom list, and then select two entries: “Autism (10003805)” and “Autism spectrum disorder (10060974)”.
  • Write-up. We can search for the word “autism” in the event write-up. This is certainly easier to do: just type “autism” into the “Write-up” search field. Of course this is less accurate because the word may be mentioned in cases where autism is not really indicated, and also it may be omitted in cases where the symptom does exist.

Once the symptom is selected, use Section 1 of the search form to request a Table of “Vaccines”. This will give a list of every vaccine associated with an event that lists the autism symptom. Click on the green down-arrow at the top of the table to sort it by the number of events.

What do we see?

If the search is for actual symptoms, 2230 events are found, and the top vaccines (those that account for more than 10% of the results) are shown here.

Searching Symptoms
Vaccine Events Percent
MMR 1437 64.44%
HIBV 446 20.00%
DTAP 353 15.83%
HEP 338 15.16%

If the search is for the “autism” keyword in the write-up, 1862 events are found, and the top vaccines are shown here.

Searching Write-up
Vaccine Events Percent
MMR 1170 62.84%
HIBV 360 19.33%
DTAP 301 16.17%
HEP 267 14.34%

So no matter how you search, the result is the same. The MMR vaccine has been given to nearly two-thirds of all people who subsequently report an autism-related VAERS events. No other vaccine comes close to showing such a strong link.

 


 

May 2010 VAERS Report

This month I will look at map reports which both MedAlerts and CDC Wonder offer. The map shows the density of VAERS events that occur in each state. However, no matter what you ask, it always looks more-or-less the same, because the states with the highest population always have the largest number of VAERS events. Here are four different map views of VAERS data:

  • Upper-left All VAERS data.
  • Upper-right Only VAERS events that mention H1N1 Flu shots.
  • Lower-left Only VAERS events that involve a child under 6 month of age.
  • Lower-right Only VAERS events that report a life-threatening reaction.

This tells us very little: no matter what you ask, most reports happen in California, New York, Texas, and all of the other densely-populated states. This is not news. What is really needed is to adjust the map so that it accounts for the population and shows the proportion of people in each state who are affected. And of course, MedAlerts is able to do that. To show an adjusted map that accounts for population, you must first check “Expert Mode” in the upper-right of the search form. This offers a new option under “Show Map” called “Adjust for Census”. What it does is to take 2009 estimated state populations and adjust the results so that they describe per-capita proportions. When you do this, the above four maps look much different: Suddenly California, Texas, and other large-population states look like safer places to live because the percentage of people who have these vaccine reactions is much lower. Now it seems that Alaska and North Dakota are high-risk states. In fact, northern states seem to have more VAERS events overall. Why do the northern states have more VAERS events per person? Could this be related to the cold weather and the Flu? Let’s find out. Another feature of MedAlerts in “Expert Mode” is the ability to reverse a vaccine search so that, instead of looking for VAERS events with a given vaccine, it looks for VAERS events without a given vaccine. So under the vaccine choices, next to “Selected Vaccines”, check “Excluded”. Then choose the four Flu vaccines. The result is here: The northern states still seem bad, in fact even worse with Flu reactions removed. So the suggestion that colder climates are somehow related to Flu shots is not true. What else could explain this map? I looked at a number of factors, including per-capita income by state, health-care spending by state, and health facilities by state. One measure does match: the number of hospitals per person. But it matches in reverse. The map below, from www.statemaster.com, shows the density of hospitals in each state, with dark green being the lowest, and yellow/orange being the highest. What this data suggests is that as the number of hospitals per person grows, so does the chance of having a VAERS events. Of course, there are surely many other explanations, but it seems from this data, that you can be healthiest if you steer clear of hospitals.

 


 

April 2010 VAERS Report

We live in a fast-paced society and we like to get things done quickly. We don’t want to visit the doctor multiple times to get all of our innoculations, so we get all of them at once. Is this wise? This month I will attempt to answer that question using data from VAERS. Unfortunately, it is difficult to answer this question by using VAERS data because it shows only the negative outcomes that occur after a vaccination. There is no way of knowing how many vaccinations were given that had no adverse effects. Therefore lets ask a different question: Does the rate of “serious” VAERS reports increase as more vaccinations are given at the same time? What is a “serious” VAERS report? Each report has a number of possible outcomes which include:

  • Life threatining?
  • Emergency Room visit?
  • Hospitalized, and if so, extended stay?
  • Permanent disability?
  • Death?

CDC Wonder defines “serious” as any combination of Death, Permanent disability, Life threatening, or Hospitalized (see vaers.hhs.gov/data/instructions). So we can answer this month’s question by asking two different questions: (1) what proportion of the VAERS reports are serious and (2) how many different vaccines were given to those people? First we will ask for a breakdown of VAERS reports by the number of vaccines given. To do this, go to MedAlerts and under “Show Table” set the Tabulate field to “Vaccine Count”. The results are here:

Number of Vaccines Given at Once Number of VAERS Reports
1 206,300
2 50,963
3 44,186
4 23,825
5 4,721
6 760
7 82
8 28
9 4
11 2

Most of the VAERS reports involve just one vaccination, but there are a significant number of reports in which more than one vaccine was given. Some VAERS reports describe a surprisingly large numbers of vaccinations that were given at once (as many as 11!) However, there are relatively few of these extreme reports, so to simplify the analysis, we will consider only reports where 5 or fewer separate vaccinations were given at once. Next we want to break this down according to the outcome of each VAERS report. To do this, go to MedAlerts and under “Show Table” set the Tabulate field to “Event Category” and under that set the next field to “Vaccine Count”. The result is a two-level table showing the different outcomes broken down by the number of vaccines that were given at once. Here is the first part of the table, showing the number of VAERS reports that listed a death, and the number of vaccines that were given:

Number of Vaccines Given at Once Number of Deaths
1 2028
2 651
3 951
4 612
5 121

At first, it would seem that the worst thing to do is to get just one vaccine, because the most number of deaths were reported among people who did that. But recall that most of the VAERS reports involved just one vaccination, so in order to make sense of the numbers, it is necessary to “normalize” them, dividing the number of deaths by the total number of VAERS reports. Doing this gives different numbers:

Number of Vaccines Given at Once Number of Deaths Number of VAERS Reports Deaths per Report
1 2028 206,300 0.00991
2 651 50,963 0.01287
3 951 44,186 0.02167
4 612 23,825 0.02593
5 121 4,721 0.02588

Now the numbers make sense. And not only that, they show a clear trend: when one vaccine is given, a smaller proportion of the VAERS reports show a death, and as more vaccines are given, higher proportions of the VAERS reports show a death. Putting all of these numbers into a spreadsheet gives the following graph. (Note that the numbers associated with each outcome are so very different, that it is necessary to do a second pass of normalizing to make the bars in each category have similar lengths. Without this, some categories would have all of their bars be very short and others would have very long bars.) What does this graph show? Let’s discuss each category separately:

  • Death. This shows a clear trend toward increased chance of death as more vaccines are given at once.
  • Life threatening. This also shows a trend toward increased liklihood as more vaccines are given at once.
  • Permanent disability. This shows no definite trend, and in fact there seems to be an indication that single-vaccination reports are worse. This is the only outcome that does not follow the same trend, but it does not follow a reverse trend, either. Instead it is somewhat random.
  • Hospitalized. This again shows a clear trend: increased chance of hospitalization as more vaccines are given at once.
  • Hospitalized, prolonged. This does not show a trends toward increased liklihood as more vaccines are given at once. However, this outcome is often reported incorrectly (there are very few reports of Prolonged Hospitalization, and many of them incorrectly fail to mention that the patient was hospitalized at all).
  • Emergency room. This shows an inconclusive result, but still shows a preference for single-vaccination situations. But consider that Emergency Room visits are not considered serious, so this result is not relevant.
  • Not serious. MedAlerts reports this outcome when none of the others apply. Here we see a reverse trend, showing that more reports are Not Serious when fewer vaccines are given at once. Of course, this actually reinforces most of the other trends in the graph.

In conclusion, VAERS data supports a recommendation that vaccines be given separately, and not all-at-once in a single visit to the doctor.

 


 

March 2010 VAERS Report

Flu season is over, thank goodness. Reports of Flu-related vaccine injuries followed a standard curve, peaking in early winter: Now that Flu season is over, let’s investigate a simple question:

Who should get the Flu shot?

I will limit this question to age recommendations, not health recommendations. And I’m not considering this year’s H1N1 Flu vaccinations, just the yearly Seasonal Flu.

The CDC recommends that people from 6 months of age to 19 years old, and also people above age 50, should get a yearly Flu shot. Those between age 20 and 50 are less likely to need one. This recommendation is based on the risk of having complications from getting the Flu. What about the risk of having complications from getting the Flu shot? Are certain age groups reacting to the vaccine more than others? Let’s find out. We will ask MedAlerts to look at all of the VAERS events that mention the Seasonal Flu vaccine, and to make a graph of the patients’ ages, broken down into 5-year brackets. In addition, we will ask that each year of data collection be shown separately, so that trends can be seen. That graph is shown below. You can skip now to the graph and my comments below it, or read on to find out how that graph was made. To make this graph for yourself, start by going to the MedAlerts search page. Before doing anything else, check “Expert Mode” in the upper-right. “Expert Mode” turns on many advanced search features, including a feature we need here: powerful age groupings. Then do this:

  • Section 1, Desired Reports: Check “Show Graph”. Since you only want a graph, it is safe to uncheck “Show Table” and “Show Event Details.” Then, under “Show Graph”, select “Age, Custom” and under that, “Year of Vaccination”. When you select “Age, Custom” a new section of the search form will appear titled Custom Age Ranges. Click on “Set Uniform” in the lower-right corner of this section and the age breaks will be automatically set to uniform, 5-year steps.
  • Section 3, Vaccines: Select the FLU and FLUN vaccines. Do not select FLU(H1N1) or FLUN(H1N1).
  • Section 5, Demographics: Click “Age (range)” and set the range to run from 0.01 to 150 (to eliminate blank and unknown entries).
  • Section 6, Dates: Set the “Vaccination date” to run “From” 1991 and “To” 2009 (eliminate years with incomplete data).
  • Click “Find” Here is what you get:

Each line of the graph shows the number of Flu-related VAERS events during a particular year, broken down by the patient’s age, in 5-year steps. For example, the green point in the upper-right is telling you that during 2009 there were 1042 VAERS reports in which the Seasonal Flu vaccination was given to a patient under 5 years old. It is no surprise that 2009 (the green circles) is the year with the highest numbers and 2008 (the maroon “+”) has the next highest…VAERS events are increasing every year. What is interesting is that the lines have a similar shape every year. This lets us see trends that span across individual drugs and years. The first thing that stands out in the graph is the very large numbers for 0-5 year olds. Even the next bracket, 5-10 year olds, are affected strongly. One obvious explanation for this is the large number of vaccinations that are given to children, and the possibility that the adverse events are from some other vaccine that was given at the same time as the Flu shot. Nevertheless, it is impossible to tell for sure, so the Flu shot may still be a contributing factor. Perhaps more suprising is the peak in the 45-55 year olds. Many of these people are not even advised to get the vaccination, and yet they report injuries at significant rates every year. The trends that appear in the graph suggest a change to the CDC’s age recommendation for who should get the Flu shot. It would seem, given the rate of VAERS reports associated with the Seasonal Flu vaccine, that children under age 10 should not receive it. Perhaps young people should only be vaccinated against Seasonal Flu when they are over 10 years of age, not starting at 6 months as the CDC recommends. Similarly, it may be preferable that older people start getting vaccinated when they are 55 years and up, not 50 and up as the CDC recommends, because of higher rates of Flu vaccine injury in the 45-55 age group.

 


 

February 2010 VAERS Report

People ask what is the difference between the MedAlerts search engine and the official U.S. Government’s search engine, called CDC Wonder (Wide-ranging Online Data for Epidemiologic Research). Both search engines use data from VAERS, a joint project between the FDA and the CDC. VAERS records look something like this:

VAERS ID: 135246    Vaccination Date: 1990-08-14
Age: 1.3   Onset Date: 1990-08-16    Days later: 2
Gender: Male   Date Submitted: 1990-09-08
State: Ohio   Date Entered: 1990-09-14
Primary Report? Yes  

Life Threatening Illness? No
Died? No
Disability? No
Recovered? No
ER or Doctor Visit? No
Hospitalized? Yes, 3 days
    Extended hospital stay? No
Current Illness: Spitting, gagging
Diagnostic Lab Data: EEG 21AUG showed seizure activity w/slowing background
Previous Vaccinations: DTP #2
Other Medications: NONE
Preexisting Conditions: Hearing loss – Rx PET

     Number of vaccines given: 2

Vaccination Manufacturer Lot Dose Route Site
HIBV LEDERLE PRAXSIS M205EP 2 SC A
MMR MERCK & CO. INC. 1494S 0 SC A

Administered by: Private      Purchased by: Public
Symptoms: Convulsion, Pallor, Pyrexia, Rash, Rash maculo-papular, Stupor
Write-up: Pt vaccinated with MMR/HIB developed fever X 24hrs w/mild erythema rash upper trunk – Macular papular on 27AUG90; Reevaluated- fever, fading of rash. Short periods of starring, face color changed & dazed state seizure were short.

The VAERS database is updated continuously, and even very old records get changed from time to time: they never close a report. At different times of the month, the data is released to the public, either by offering data downloads (used by MedAlerts) or by sending the data to CDC to be put into Wonder. Because the frequency of posting downloads is different than the frequency of updating Wonder, it is rare to find the two search engines current to the same date. Wonder is typically more up-to-date by as much as 3 weeks, but occasionally MedAlerts is more current.

The Advantages of CDC Wonder

Often More Up To Date. As I mentioned, Wonder is typically more up-to-date than MedAlerts because of the frequency with which they update it.

Primary/Secondary report distinction. Wonder shows secondary reports (VAERS reports that are follow-ups to the primary report). Secondary reports are not included in the downloaded data used to build MedAlerts. It is not known whether the information is missing from MedAlerts or is somehow combined into the primary reports.

General Purpose. One interesting aspect of Wonder is that it is a general-purpose search engine which can handle much more information than just Vaccine data. For example, the CDC uses it to report AIDS, Cancer, Tuburculosis, etc.

The Advantages of MedAlerts

(Full-disclosure: I wrote the MedAlerts website, so clearly I find it superior.)

MedAlerts has a better user interface. The site includes popup help messages and a help page with examples. An “Expert Mode” for power users offers many advanced features including the ability to program your own searches.

MedAlerts has a more powerful search engine. It can look for information in any of the fields of a VAERS event, whereas Wonder cannot. For example, Wonder cannot search for a Vaccine lot, dose, route, or site, nor can it search in any of the descriptive fields such as write-up, previous conditions, or previous medications. Besides letting you search all fields, MedAlerts also lets you search related information that is not directly in the database. For example in addition to searching for specific symptoms, you can search for high-level classes of symptoms because MedAlerts understands symptom hierarchy (as defined by MedDRA).

MedAlerts has a more powerful reporting facility. Both MedAlerts and Wonder can generate Tables and Graphs from their search results, but MedAlerts has more tools for organizing these reports. Only MedAlerts lets you organize results by vaccination route or site, and by all of the event dates. In addition, MedAlerts lets you report according to useful combinations of data, for example the combination of vaccine and manufacturer.

MedAlerts has better mapping. The Wonder map is tiny and shows only 5 gradations in its coloration whereas the MedAlerts map is larger and shows 7 gradations.

MedAlerts has faster graphing. Both search engines can produce many different types of graph (line, bar, pie, etc.) but Wonder must reload the page in order to make any change to the graph, taking 30 seconds or more. MedAlerts has live graphs that can instantly be redrawn in a different style. Also, MedAlerts graphs are interactive, letting you point the mouse anywhere and see the actual data values.

MedAlerts can show the entire VAERS record. This is the key difference between the search engines: they both produce tables, graphs, and maps, but only MedAlerts can show the event-details. The event-details report includes every field in the VAERS record (as illustrated above). Wonder does not provide any way to see this information.

A Minor Flaw in Wonder

Besides all of the disadvantages of CDC Wonder described so far, there is one other problem with Wonder that causes its searches to be incorrect by almost 10%!

Both MedAlerts and Wonder have similar search forms that let you choose which VAERS events you want to see. Each of the fields in the form controls the search by limiting it to certain values (for example, a vaccine, a symptom, a range of dates, etc.). At MedAlerts, all of the search fields start in the “off” position, causing the includsion every vaccine, any symptom, and all dates. At Wonder, most of the search fields start in the “off” position, except for one.

The problem appears in Section 5 of Wonder, where the default selection of State/Territory is set to “The United States, Territories, and Unknown.” This excludes the foreign data, a large piece of the VAERS database. Some would argue that the foreign data is far from complete and that VAERS is primarily a US database. But there is real information here that naive users will not see if they do simple searches.

How much data is lost? See for yourself. Click “Send” at Wonder (without making any other selections) and you will get 302,920 VAERS events. Now change “The United States” to “All Locations” and you will get 328,453 events. So Wonder supresses over 25,000 events, nearly 10% of the database, by default.


 

January 2010 VAERS Report

Now that 2009 is over, it is interesting to look at the growth of VAERS reports over its 20-year history. Here is a graph of the number of reports that were added to VAERS each year. You can see this result for yourself by going to the MedAlerts search page and graphing “Year of Appearance”. Note that 1990 has a small number of reports because it was the first year of operation and does not represent a full year of data collection. In the remaining graphs of this report, I will ignore 1990.

VAERS January 2010 Graph

The number of reports added in 2009 was, as expected, another record-breaking year. However, what is particularly noticeable about this graph is the sudden jump in the past 3 years. Why is this?

Let’s go back to MedAlerts and graph the individual vaccines over the last 20 years. Below is the graph of “Year of Appearance” and “Vaccine”. Unfortunately, there are over 70 vaccines, so the result is a jumbled mess that is hard to interpret.

VAERS January 2010 Graph

Although it is hard to tell what is going on, some vaccines do make a jump in the last three years. But rather than try to isolate those vaccines, let’s look at it a bit differently: let’s look at “Vaccine Type” instead of “Vaccine”.

The reporting of “Vaccine Type” organizes vaccines according to the diseases that they address. Some vaccine types are straight-forward (the YF vaccine is the only one of type “Yellow Fever”). Many vaccines have multiple types (the MMR vaccine has the types “Measles”, “Mumps”, and “Rubella”) and many vaccine types have multiple vaccines in them (there are 19 different vaccines with the type “Diphtheria”). If you want the full list of types associated with each vaccine, see the list of MedAlerts abbreviations. Graphing the vaccine type is useful because there are three times fewer vaccine types than vaccines, so this reduces clutter and may provide some insight into what is going on. Here is that graph of the “Year of Appearance” and “Vaccine Type”.

VAERS January 2010 Graph

In the above graph, each line falls into one of four different categories:

   1. The lowliers at the bottom of the graph that never have many VAERS reports and haven’t grown lately. These include Anthrax, Cholera, Encephalitis, Lyme, Plague, Rabies, Smallpox, Tuberculosis, Typhoid, and Yellow Fever. These types are not interesting and can be ignored.
   2. The middle group, which do have significant number of VAERS reports, but have not increased in the past few years. These include Measles, Mumps, Rubella, and Polio. These types are also not interesting and can be ignored.
   3. One particular type that has shot up dramatically in the last year and spikes to the top of the graph on the right (you guessed it: Influenza). This is interesting, but not relevant to the question of the last three years.
   4. The remaining types, which show a noticeable rise in the past few years and are detailed below.

VAERS January 2010 Graph

What does this tell us? First of all, it is well known that Tetanus, Diphtheria, and Pertusis are usually given together, so it is no surprise that these three curves follow each other. Some vaccine types are new (HPV and Shingles) so their rise in recent years is the result of their introduction. Much more information needs to be known before any conclusions can be drawn. Nevertheless, it is instructive to see these trends, and MedAlerts provides some tools needed to do this.

Tip of the Month for using MedAlerts

MedAlerts graphs are very powerful and can be changed on the fly. For example, each line of a graph can be removed simply by unchecking its name in the legend area below the graph. This makes it easy to remove clutter quickly and find the relevant curves, as I showed above. Another graphing tip is that you can see the data behind a particular point in the graph by placing the mouse over that point and waiting for a “tooltip” to appear. You can also change many other aspects of a graph without redrawing the web page because Medalerts graphs are “live” and very powerful. See the graphing help page for more information.


 

December 2009 VAERS Report

This month wraps up 2009, a year that had more VAERS reports than ever before. In past months I have focused on the growth of VAERS reports related to both Seasonal and H1N1 Flu as well as HPV vaccinations. This month, I will do something different and explore a question of vaccine safety.

Which vaccine has a higher chance of causing a VAERS injury report to be filed: H1N1 Flu or Human Papiloma Virus (HPV)?

The chance of having a VAERS injury report filed is equal to the number of VAERS reports, divided by the number of people vaccinated. We can ask MedAlert or CDC Wonder for the number of VAERS reports, but we don’t know how many people were actually vaccinated. However, many estimates have been made, and we can find these numbers on the Internet.

First let’s look at H1N1 Flu. What percentage of people given an H1N1 Flu vaccination file a VAERS injury report?

The Washington Post claims that 20% of Americans got the H1N1 Flu vaccine (as of January 16, 2010). They claim that this is 61 million people.

How many VAERS reports were generated by these 61 million vaccinations? As of January 29, there are 9319 reports of injuries associated with H1N1 Flu. And given the rate of growth of these reports, this number can easily grow to 12,000 in the next two months (see graph). Given that it takes a few months for people to get their injury reports into the VAERS system, it is not unreasonable to consider 12,000 as a conservative estimate.

 

VAERS December 2009 Graph

The red dot in the upper-right is a projection based on the slope of the curve. It predicts that there will be 12,000 VAERS reports associated with H1N1 Flu by the end of March. The latest real data point (the rightmost blue dot) is on January 29 and lists 9319 reports.

If 61 million people were vaccinated, and 12,000 of them filed injury reports, that’s one injury report for every 5000 vaccinations. If we discard the projection of 12,000 VAERS reports and stick to the current numbers, we get a conservative estimate of one injury report for every 6500 vaccinations.

Next let’s look at HPV. What percentage of people vaccinated against HPV file a VAERS injury report?

According to the FDA over 23 million doses of Gardasil were distributed in the three-year period of 2006-2008. Assuming a constant rate of distribution, this means about 30 million doses up to the end of 2009. Considering that it takes three doses of Gardasil to immunize someone, it really means that 10 million people have been vaccinated with Gardasil. And if you think that these numbers are wrong because there are other HPV vaccines besides Gardasil, consider that nearly 99% of the HPV-related VAERS reports specifically mention Gardasil, so it is safe to say that 10 million people have been vaccinated for HPV.

How many injury reports have been filed for HPV? As of January 29, there are 17,822 VAERS reports associated with HPV. So if 10 million people were vaccinated, then 1 out of every 560 people vaccinated filed a report.

Assumptions

There are many assumptions and likely inaccuracies in these calculations. Let me list a few of them:

  •   I assumed that the number of doses of Gardasil distributed in 2009 grew at the same rate as it did in 2006-2008, but it surely did not. In fact, it probably increased. This means that more people were vaccinated than 10 million, and my estimate of the chance of filing a report is too high.
  •   The FDA reported the number of Gardasil doses distributed, which is, of course, more than number of doses actually administered. This means that fewer than 10 million people were vaccinated, and my estimate of the chance of filing a report is too low.
  •   Not every patient gets all three doses of Gardasil. This means that more people were vaccinated than 10 million, and my estimate of the chance of filing a report is too high.
  •   The HPV calculation does not account for future VAERS reports based on vaccinations already given, and the H1N1 Flu calculation makes a conservative guess that all reports will be filed in two months. This means that there will probably be even more VAERS reports, and my estimate of the chance of filing a report is too low.

The point I’m trying to make is that numbers are easily manipulated. Everyone does it, and so do I in these calculations. But I want to show that I’m trying to be fair.

Conclusion

1 out of every 560 people who are vaccinated against HPV files a VAERS report.
1 out of every 5000 to 6500 people who are vaccinated against H1N1 Flu files a VAERS report.

So if you get the HPV vaccine, you are about 10 times more likely to end up filing a VAERS report than if you had gotten the H1N1 Flu vaccination.

Tip of the Month for using MedAlerts or CDC Wonder

Many of you will want to verify these numbers for yourselves. When you do, keep in mind that a vaccine may have multiple codes. For example, the code “HPV4″ is for Gardasil, “HPV2″ is for Cervarix, and “HPV” is used when the manufacturer is unknown. As far as H1N1 Flu codes go, there is “FLU (H1N1)” for the injection, “FLUN (H1N1)” for the nasal dose, and “FLUX (H1N1)” for unknown manufacturers. The proper way to count the number of VAERS reports associated with a vaccination is to select all of the relevant codes in the search form.


 

November 2009 VAERS Report

  • Flu – Seasonal and H1N1

This graph shows the number of events reported as a result of Flu vaccines administered during a given month.  The alarming line is the red one on the right: September 2009 events.  This bar is 5 times higher than it has ever been during September (1949 this year as opposed to the previous high of 357 last year).

To view both of the available flu graphs for November please click on the image below.

November VAERS data Flu

Once again, there is an alarming red line on the right that shows a terrible month in September 2009. This bar is nearly six times higher than it has ever been during September (2125 events this year as opposed to the previous high of 356 last year).

Typically, the worst month is October (shown in blue) but this year October is not much worse than September, and is lower than it was last year. Part of this is explained by the fact that October data is not yet completely reported (there are still people who were vaccinated in October and have not yet filed VAERS reports). Another explanation, however, is the rise of H1N1 which became available in October. It is likely that many people stopped getting Seasonal Flu shots in October and switched to H1N1 vaccinations. So the right thing to do is to combine H1N1 and Seasonal Flu reports into a single graph. Doing this shows that the number of VAERS events related to Flu vaccines is through the roof, dwarfing all previous years.

To view both of the available flu graphs for November please click on the image below.

November VAERS data Flu 2

 

 

  • HPV

Finally, a continued update on the VAERS reports associated with the HPV vaccines. November had another 247 events reported, 4% of the events for the month. But let’s put this 4% figure into perspective by ignoring the Flu reports. If we take the number of events reported in November (6267) and subtract the events that related to Seasonal or H1N1 Flu (4971) we have 1296 non-Flu events reported. Now the percentage of HPV-related events is 19% which, unfortunately, is a typical rate for any given month.

Think of all of the vaccinations given and consider how few of them are HPV vaccinations. Then consider that over the past two years since the introduction of HPV vaccinations, about 20% of the adverse events have been related to these HPV vaccinations. It’s mind-boggling. Not only that, but 57 women have died in events related to HPV (CDC Wonder is showing 61). Of course, I’m only guessing that all 57 were women, because a breakdown of these reports by gender shows 50 of them were women and 7 were of unknown gender.


 

October 2009 VAERS Report

  • Flu – H1N1

Let me start by showing you a graph of the growth of H1N1 Flu events since the beginning of October when the vaccine was released. Adverse events associated with it have been rising steadily. This information comes from a combination of Medalerts and CDC Wonder. As of November 24, there are 3889 events associated with H1N1 and 17 deaths (this is from Wonder).

October VAERS

 

  • Flu – Seasonal

But what about the seasonal Flu vaccinations? In August and September, I showed graphs predicting the worst year for Flu events in the 20 years of VAERS data collection. October’s data clearly shows this trend becoming more pronounced.

This graph shows the number of events reported as a result of Flu vaccines administered during a given month. The alarming line is the red one on the right: September 2009 events. This bar is 5 times higher than it has ever been during September (1949 this year as opposed to the previous high of 357 last year).

You might think that the October line is not very high, but keep in mind that the month has just ended, and many people vaccinated during the month have probably not yet filed a report. Last month, there were just 1000 events reported for September and since then that number has doubled. So October, which currently shows 1738 events, promises to break through the top of the chart.

To view the available seasonal flu graph for October please click on the image below.

October VAERS Seasonal Flu

 

  • HPV

Finally, a continued update on the VAERS events associated with the HPV vaccines. October had another 241 events reported, 5% of the events for the month. Don’t be fooled by the low percentage: October had 4930 events reported, more than twice the normal amount for any given month. And the worst news is that there are now 57 deaths associated with HPV vaccinations (although CDC Wonder shows 58 right now).

Even more interesting is the appearance of a new HPV vaccine: Cervarix from Glaxo Smith Kline (code name HPV2). This vaccine is listed in the following event in which a 14-year-old girl died within hours of getting Cervarix. 


 

September 2009 VAERS Report

  • Flu – Seasonal

The month adds 2409 events to the database and nearly half of them (1137) associated with Flu shots! Once again, there are no reports that mention H1N1 specifically, but there is one report that mentions H1N1 in the writeup, see this page.

Last month I showed a chart of Flu reports by month over the last 20 years. I thought that the August numbers were much higher than usual and indicated a bad trend. Well the trend continues to be bad, as the updated graph shows. September (the red line) has never been this high and is as large as the peak month October (shown in blue). So either Flu events are peaking early, or it will be the worst year for Flu events ever.

To view the available seasonal flu graph for September please click on the image below.

Sept VAERS Flu

 

  • Gardasil

This September, 262 of the 2436 new events were due to Gardasil (11%) bringing the total number of Gardasil-related events to 16,703. One new death was reported this month, but it happened 53 days after the vaccination, so it may not be related to Gardasil, see this page.


 

August 2009 VAERS Report

This August added 2436 new events to VAERS, causing the total number of VAERS events to break the 300K barrier (there are now 300,108 events).

  • FluSeasonal

Because the government data lags by a few months, and since the H1N1 vaccine has just come out, there is no data on it at this time. However, seasonal flu reactions are already starting to come in (258 of the 2436 new events were Flu-related).

It is interesting to look at the cyclic nature of Flu injury reports, and I have prepared a graph of it using Medalerts. The graph shows the number of VAERS events that are associated with flu vaccinations, broken down by the month that the vaccine was administered.

Each year flu injury reports peak in October (blue) with fewer cases in September (red) and November (green). Rarely is there any activity in August (cyan) but this August is different. The cyan line on the far right is larger than it has ever been (showing 54 reports for vaccines administered in August). This could be a sign of much larger number of Flu-related events this year than ever before.

If you are confused about the fact that there were 258 flu-related reports in August but only 54 shown in the graph below, the distinction is that the 258 August reports were those that appeared in VAERS during August, whereas the 54 reports in the graph below were reports where the vaccine was administered in August.

To view the available seasonal flu graph for August please click on the image below.

August VAERS

 

  • Gardasil

This August, 283 of the 2436 new events were associated with Gardasil. Considering the total number of vaccinations administered, and the relatively small proportion of them that are Gardasil, it might seem unusually high that 12% of the reports are about Gardasil injuries. But in fact, Gardasil is typically mentioned in 20% of the monthly reports, so August is actually showing improvement.

The total number of Gardasil-related events now stands at 16,440. Fortunately, no new deaths were reported this month, leaving the total at 51.

 

End of Available Reports

 

 

Dr. Steven M. Rubin Biography

Steven M. Rubin, Ph.D. is a computer scientist who maintains MedAlerts.org, the online searchable VAERS (Vaccine Adverse Event Reporting System) database.  He has been doing this in cooporation with the National Vaccine Information Center (www.nvic.org) since 2005.  This website allows anyone to search the U.S. Government’s reports of vaccine injuries.

Dr. Rubin has worked in the computing field for over 40 years, both as a teacher and a researcher. He holds a Ph.D. in Computer Science from Carnegie Mellon University (1978).  He has taught computer graphics at Carnegie Mellon University and at Stanford University and has worked at Bell Telephone Laboratories, Schlumberger/Fairchild, Apple Computer, and Interval Research. He is currently a Distinguished Engineer at Sun Microsystems Laboratories. His current work is on a system called “Electric,” an open-source program for designing integrated-circuit chips, and his work on this also includes a textbook on chip design software.

Dr. Rubin’s youngest son, Max, was autistic and was cured with Homeopathy. This sparked his interest in vaccine safety, and it led his wife, Amy Lansky, to write her popular book: “Impossible Cure: The Promise of Homeopathy” (www.impossiblecure.com). Interestingly, Dr. Rubin was also the lead singer of “Severe Tire Damage,” the first band to perform live on the Internet.

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