Fact-Check: Billboard Claims Unvaccinated 16x More Likely to Die Than Boosted
The California Department of Public Health (CDPH) has launched a billboard ad campaign that makes the claim that unvaccinated people are 16x more likely to die than boosted individuals.
This particular image is at bus stops, near freeways, just about anywhere it can be seen by hundreds, and thousands of people. You may have seen it.
The thing that strikes me most is the oversimplification that the only difference between people is their vaccine status. Yet, still, an unvaccinated healthy 20 something year old still has a lower COVID-19 risk than a triple vaccinated, comorbid 70 year old.
Vaccines are not the only difference between people, and each person, depending on their age, and their health, has a different, unique “absolute” risk. This ad campaign ignores all of that, and uses fear and manipulation to coerce vaccination of the working class, without giving all of the information needed to make a healthy, informed decision.
A few things:
Who is it targeting?
It’s targeting people who commute. People who work. Not people in nursing homes. Not people who are highest at risk of COVID-19. I know this is an extremely charged topic, but facts are facts. To date, over 74% of deaths have occurred in people over the age of 65, compared to only 4% of deaths have occurred in people under the age of 45. Despite the commonly held belief that vaccines save lives, more people died of COVID-19 in 2021 a year where vaccinations were not just available, but widely used, compared to 2020, a year without any COVID-19 vaccine. Odd right?
Yet here is this ad, in plain view of people who are mostly not at risk of COVID-19. Notwithstanding, the vaccine does not prevent transmission, infection, hospitalization or death, in everyone, as to this day, we still have vaccinated and boosted people dying of COVID-19.
Is it just COVID-19, or All-Cause Mortality?
The sign doesn’t actually say the words COVID-19. We are graciously filling that part in for them. The language literally says “more likely to die.” Are we the viewer (the average person) supposed to assume they mean COVID-19? Are they taking advantage of the fact that some people will associate vaccines with being life-saving in general–even though there is no evidence to support that?
What about the odds?
It’s a true statement that 16 is a number that is 16 times more than 1. That is the relative risk, and the difference may feel big. But what about the absolute risk? In California, during the height of omicron in late January, an average of 2 per 1,000,000 boosted and 27 per 1,000,000 unvaccinated deaths were recorded daily. The overall, absolute odds of dying are very low. And, there is no discussion from the CDPH of the other factors that provide context for COVID-19 deaths, ie. age factors, comorbidities, race-related differences in health outcomes. The only difference between people is not their vaccine status.
BTW: Weeks later deaths fell to 20, 3 and 1 per million (for unvaccinated, double vaccinated, and boosted) and a few weeks after that to 10, 1 and 0.8 per million (for unvaccinated, double vaccinated, and boosted). Keeping in mind that the majority of the “unvaccinated” deaths are still going to be elderly, multiple comorbid people who for whatever reason chose not to be vaccinated or boosted, possibly because they were in hospice or felt there would be limited benefit for them to be vaccinated.
What about an age-stratified risk?
Advanced age is highly associated with poor outcomes with COVID-19. A person who is 65 is 65 times more likely to die of COVID-19 than an 18 year old. Why not be more clear about the age-stratified risks? Why not target the correct audience for an ad? Vaccination itself is far more risky for an otherwise healthy, young person who is at a zero percent risk for death or serious outcomes from COVID.
What about the risks of the vaccine?
What are the odds of something like blood clots or myocarditis associated with the COVID vaccines? And how do these risks vary for different sexes, ages, etc? The rate of myocarditis after Pfizer vaccine is 105 per million in 16- and 17-year-olds, a particular demographic who is at a lower risk of serious outcomes with omicron. The rate of blood clots associated with the J&J vaccine hover around 1 per 100,000 women, or 10 per million in women ages 30 to 49.
What about the risks we can’t talk about?
This all goes back into the basic messaging of vaccines: the ‘vaccines save lives’ trope. We can’t talk about the fallout of vaccines, because it’s a belief system, but when you actually fact-check it, the opposite is true: vaccinated people are more likely to die than unvaccinated people. Yep, I said that, and I can back it up.
SOURCES FOR THAT STATEMENT:
Increased mortality after introduction of DPT vaccine https://www.frontiersin.org/articles/10.3389/fpubh.2018.00079/full
Increased mortality associated with high titre measles vaccine https://pubmed.ncbi.nlm.nih.gov/8671571/
Recipients of DTP or polio vaccine had higher mortality than children who received none of those vaccines. Only live virus vaccines (because viruses can be beneficial) are associated with decreased mortality. So, in other words, it suggests that viruses are associated with decreased mortality since live virus vaccines are attenuated live viruses. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC27544/
Pfizer 6 month report had more deaths in the vaccine group than the placebo group:
During the blinded, placebo-controlled period, 15 participants in the BNT162b2 group and 14 in the placebo group died; during the open-label period, 3 participants in the BNT162b2 group and 2 in the original placebo group who received BNT162b2 after unblinding died. None of these deaths were considered to be related to BNT162b2 by the investigators.Causes of death were balanced between BNT162b2 and placebo groups (Table S4).
After vaccine deaths: 20
After placebo deaths: 14
https://www.nejm.org/doi/full/10.1056/nejmoa2110345
Overall, completely unvaccinated children are healthier than the vaccinated children:
Let’s Look at the Fine Print
There is an asterisk which takes you to a small interval of dates. The dates are not really that important, because the dates change for different ads, but it is cherry picked in January right when the omicron surge happened, probably to gather the most cases, hospitalizations and deaths as possible.
The ad directs you to myturn.ca.gov, a generic website meant to facilitate getting you vaccinated, making an appointment, finding a testing site, finding a walk-in clinic–all in one.
But where does the data come from?
CA’s COVID State dashboard (which was sourced in this article and made a similar claim):
California Health & Human Services Agency’s open data website contains a table of raw data: COVID-19 Post Vaccination Statewide Stats.
The California Department of Public Health (CDPH) is identifying vaccination status of COVID-19 cases, hospitalizations, and deaths by analyzing the state immunization registry and registry of confirmed COVID-19 cases.
I am curious how are they arriving at the “unvaccinated” cases which would not be in the CAIR system. Are they in this ‘registry of confirmed COVID-19 cases’ and if so, how accurate and comprehensive is this?
Because right off the bat, it seems there are some inconsistencies.
Here is the Table the CDPH is using to come up with that statistic, scroll to page 36 for the January data, or page 42 for most recent data:
How reliable is this data? Does this include every single positive case? Of course not. We know a significant proportion of people self-test at home, or don’t test at all. Unvaccinated people may be less likely to rush to get PCR tested, and included in government registries.
One thing to keep in mind when looking at that table is that it excludes all people with only 1 dose (curious). And it only includes people 12 and up.
How does the CDPH define these vaccine categories?
Unvaccinated Deaths
Total number of laboratory-confirmed COVID-19 deaths among persons age 12+ with a date of death on the provided date with no record of any doses of COVID-19 vaccine. Persons considered partially vaccinated are not included in the unvaccinated deaths.
Unvaccinated Deaths recorded on March 27, 2022:
7
Population listed as unvaccinated on March 27,2022:
4,091,607
Vaccinated Deaths
Total number of laboratory-confirmed COVID-19 deaths among persons age 12+ with a date of death on the provided date with a complete COVID-19 vaccine series (≥14 days after the 2nd dose of a two-dose series or ≥14 days after a single-dose vaccine). Persons considered partially vaccinated are not included in the vaccinated deaths.
Vaccinated Deaths recorded on March 27, 2022:
7
Population listed as vaccinated on March 27, 2022:
13,213,951
Boosted Deaths
Total number of laboratory-confirmed COVID-19 deaths among persons age 12+ with a date of death on the provided date with a complete COVID-19 vaccine series and additional or booster dose (date of death ≥14 days after the additional or booster dose).
Boosted Deaths recorded on March 27, 2022:
2
Population listed as boosted on March 27, 2022:
13,773,708
The definition for the unvaccinated population is in the data dictionary:
California Department of Finance (DOF) population estimates 2020 for ages 12+. This number only includes those persons that have not received any doses of COVID-19 vaccine, which is derived by subtracting the number of fully vaccinated persons and number of partially vaccinated persons from the total population estimate.
Let’s look at January 24, 2022:
102 unvaccinated died
51 vaccinated died
21 boosted died
Another way to categorize this data is:
102 unvaccinated died
72 vaccinated died
Then what they do is take these deaths as the numerator and then divide it by the total populations for these groups at this time which again are their estimate. They do not divide the number of deaths by the cases reported, as is typical of “case fatality rates”. It’s based on the entire populations. What is curious to me, is they don’t age stratify: because we all know that more deaths happen in the elderly. And there may be many elderly too sick to be vaccinated, in hospice, who have chosen not to take a vaccine.
How they came up with the 16x figure
From the dates Jan. 24-Jan. 30, an average of 131 unvaccinated people died per day out of a population of 4.7 million unvaccinated people (the unvaccinated population could be inaccurate) verses an average of 21.5 boosted people out of a population of 12 million people.
That’s it. That’s how they came up with it. It wasn’t out of “cases”, it wasn’t out of “hospitalizations”, it was merely x number of people died out of the entire population.
0.00017 x 16 = 0.0027
So another way to say this, 27.8 deaths per million in the unvaccinated compared to 1.75 deaths per million in the boosted. And 27.8 is 16 times higher than 1.75.
So, an unvaccinated person had a 0.0027% chance of dying of omicron vs a boosted person’s 0.00017% chance during this 7 day period during an omicron surge.
Overall, both groups had very small risk of death.
It would be wonderful if we had these deaths age-stratified, because an average person looking at that billboard is going to think that demonstrates their individual risk, not considering that most deaths are still in the elderly, that the first people to get a booster often have a healthy user bias, and among those elderly not getting triple vaccinated they are often the sickest and closest to death they don’t feel a third dose would benefit them at all.
Serious questions remain about how accurate are these numbers?
The reporting in these tables seems low to me at first glance. On January 24th, at the height of omicron, this table reports a total of 55,852 cases, 10,456 of who were boosted, and 21,259 of who were doubly vaccinated. So in all, of the 55,852, 31,715 of the cases were fully vaccinated.
But then other website data is reporting more cases. The New York Times graph relays that over 200,000 new cases were added on January 24, in California, with a 7-day average of over 100,000 cases.
So which is correct? Why such a large discrepancy? Are most infections in people under 12 or one-dose of the vaccine?
Unanswered Questions
Throughout this whole pandemic we know there are both an overcounting and undercounting of cases, hospitalization’s and deaths due to COVID-19. Cases are being missed because many people may not test, or know they have an infection, while others may be counted as a case that are recovered or not contagious. PCR tests can be positive up to 3 months after an infection. Many people are routinely screened at hospitals, and counted as hospitalizations, even if incidental, or not there for COVID at all. And deaths may be counted as COVID-19 with little supporting evidence–a positive test within 30 days prior, or even a positive well after hospital admission.
But more grotesquely–why is the CDPH relying on data that may not be completely accurate, and purposely not age-stratifying, or controlling for the comorbidities that are highly associated with poor COVID-19 outcomes to make an ad campaign that convinces average, working class people to get a vaccine that may harm them more than the virus??
I think we all know that answer.
