New Paper Says Flu Vax Increases Chance Of Flu: Let’s Look

New Paper Says Flu Vax Increases Chance Of Flu: Let’s Look

Can flu vaccine give you flu? New paper seems to say yes. Their conclusion: “the risk of influenza was significantly higher for the vaccinated compared to the unvaccinated state…yielding a calculated vaccine effectiveness of -26.9%”. The negative number means taking the vax was, in their sense, worse than not taking it. We need to figure out what their sense is.

The paper is “Effectiveness of the Influenza Vaccine During the 2024-2025 Respiratory Viral Season” by Shrestha and others at MedRxiv, which helpfully and hilariously tells us “This article is a preprint and has not been certified by peer review…” Certified!

Well, I laughed.

First thing that struck me was reading in the Abstract “Among 53402 employees, 43857 (82.1%) had received the influenza vaccine by the end of the study”, and then seeing shortly after in their Setting: “For several years Cleveland Clinic has had a mandatory participation influenza vaccination program, which requires employees to either receive an annual influenza vaccine or seek an exemption on medical or religious grounds. The vaccine is provided to healthcare personnel free of charge.”

How did those 9,545, or 17.9%, get away with not taking the mandatory shot? Are they all medical or religious exceptions? Probably some. All? One doubts. Maybe the majority of the unshot are like Yours Truly, who tells HR, “Yes, you’re right, this is very important. How scary not to have the shot! As soon as I finish this job, I’m going to get mine. Thanks so much for the reminder.” That job would take me a long, long time to complete.

Now, of you readers that did not get a flu vax, which I’m guessing is many of you, if you got sick during the year for what you took to be a bad cold or flu, did you run to the doctor for it? Did you insist on a test to confirm it? or did you grab a bottle of Jamesons and some tea and ride it out? Again, I’m guessing a bunch of you did not seek out official confirmation, because you didn’t need to hear “Yes, Mr Smith, it appears when you say you are sneezing that you are, medically speaking, sneezing.”

What that means is that there’s a good chance many in the unvaxed population who did get sick never had their illness officially diagnosed. And so they’d be listed as “No flu”. The opposite is also likely: the first in line for the shots are more apt to have their sniffles blessed as The Real Thing.

Both things combined would make the vax appear worse than it is. It would also make a placebo appear to have a negative effect. Because a greater proportion of those who got the placebo would have their illnesses diagnosed.

I am happy to report our authors, unlike many, thought of this:

To assess whether there was a difference in the propensity to get tested among the vaccinated and the unvaccinated, the ratio of the proportion of the vaccinated who got tested to the proportion of the unvaccinated who got tested on each day of the study was examined, as was the ratio of the proportion of vaccinated persons’ tests that were positive to the proportion of unvaccinated persons’ tests that were positive on each day of the study.

The first proportion, vax vs. unvaxed seeking tests, takes care of the concerns mentioned above. If this ratio is 1 (or so), then seeking the vax is unrelated to seeking tests. The second ratio takes care of severity of infection in a similar way, but since it’s not a direct measure of severity it’s imperfect. In other words, if the vax has some efficacy, those in the vaxed group with only minor or unnoticed infections may get tested less. Whereas it’s plausible only the sickest in the unvaxed would get tested. So this second ratio is not fully informative.

Finally the results: “A total of 53402 employees in Ohio remained after excluding 1700 subjects (3.1%) for whom age or gender were missing.” Dude, that’s a good chunk. How is sex or age missing from a hospital employee’s record? Temporary workers?

You can see, I hope, how difficult it is to measure cause in this experiment. The authors should have tried to get a mandatory test of infection on at least a sample of employees. As it is, using voluntary tests sought conflates several possible causes.

What of our concerns? “The ratio of the proportion of the vaccinated who got tested to the proportion of the unvaccinated who got tested for influenza on each day of the study was significantly higher than 1.00 for most of the study (Figure 1), suggesting that the vaccinated were more likely to be tested than the unvaccinated on any given day.” Here’s the figure. Ignore the line.

Did you ignore the line? Of course you didn’t! The line is not the data. The data is the data. But eyes are inexorably drawn to these lines, at which point the Deadly Sin of Reification kicks in, and the line becomes “truth”, and those blue dots a distraction.

What’s worse here is that the line is drawn after “excluding outlier values”, i.e. those values that say the data is not a line.

It’s unfortunate they didn’t size the dots by sample size. That would tell much. But it’s clear enough that the vaxed were a lot more likely to seek testing. Which makes the vax (or a placebo, had one been given) appear worse. If those tests were coming back positive. That’s this second chart/ratio. Ignore the line.

Did you ignore the line? Of course you didn’t! You can’t! It’s like ignoring rap “music” at a restaurant. It’s there and overwhelms all other senses.

Here not sizing by sample size really hurts. We don’t know how many people are represented. So the figure is mostly a wash, unless there are a lot more people in those much-larger-than-1 ratios, which is likely. Don’t forget that, consistently, the vaxxed sought testing more often, so here the blue dots less than 1 are likely often the likely sicker unvaxxed.

Which all means there is no way to eliminate our concerns. Thus, it is likely a good portion of the signal of a negative vax efficacy is caused by behavior: the same people who like the vax like testing.

There’s more evidence of this. Turns out the hospital employs 75% females. And that in their models being a man is protective against flu! We don’t see the raw data—another unfortunate common failing—but the signal for males in the models is not small, with hazard rates around 0.7 (meaning less chance for having flu).

My dear readers, men man up more than women. Yes, even in these Equality-mad times. Women like testing and being sick more than men. Women like being vaxed more than men. All on average, of course. Also, those in clinical jobs, which of course are exposed to more illnesses but also with greater ease and facility of being tested, were also more prone to flu.

Summary? I think they authors tell it nicely enough: “This study found that influenza vaccination was associated with a higher risk of influenza among adults in the healthcare workforce in northern Ohio, USA, during the 2024-2025 winter season, suggesting that the vaccine has not been effective in preventing influenza this season.”

Meaning this particular vax concoction in this situation and in this milieu did nothing or made things slightly, though probably not much, worse.

What of those people who got the shot and then soon after developed flu? People who return to the doctor to complain, and with the doctors saying, “Oh, you must have had it in your blood before you got the shot”. Share this paper with them, along with a warm chuckle.

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5 Comments

  1. Paul Fischer

    Morning William!
    Well I did a quick look over this paper. Read maybe half of it. Not a very well done. Where are the hazard ratios? So many variables unaccounted for. Sloppy work. I did an analysis of flu vaccines years ago. I came away with an efficacy of 1%. They do not work. But then again how could they. It’s a shot in the dark. They never know what strain is going to show up. The last time I got the flu vaccine (about 8 years ago) I got both the A and B flu. I stopped getting the flu vax at that point and haven’t been sick once since then. Hmm.

  2. Tars Tarkas

    I just assume this is the case based on my own experience. Though I haven’t had a flue shot since before 2020, the years I get the flu shot tend to be the years I catch a cold/flu, though generally a mild version. The last time I had a major flu without a shot was 2003. That one was a doozie, I was in bed for nearly a week.

  3. shawn marshall

    i got Flu A – didn’t have the shot – wife got it too – no shot either – 3 days hospital for her – bacterial pneumonia and blood problems – not related to flu – would not have known about blood problems without hospitalization

  4. nw45

    seems to me there is the possibility that the “risk factor” here is just being in the numerator group when comparing a series of ratios whatever they may be.

    e.g. generate series a and b of 1000 (not really)random integers in the range 10 to 99
    the average a/b and b/a are both well above 1, but the ratio of the totals of a to the totals of b is almost exactly 1.
    (python example below)

    import numpy as np
    rng = np.random.default_rng()

    n = 1000
    a = rng.integers(10, 100, size = n)
    b = rng.integers(10, 100, size = n)

    print(“avg a[i]/b[i] : “,(1/n)*sum([a[i]/b[i] for i in range(n)]))
    print(“avg b[i]/a[i] : “,(1/n)*sum([b[i]/a[i] for i in range(n)]))

    print(“sum(a) / sum(b)”, sum(a)/sum(b))
    print(“sum(b) / sum(a)”, sum(b)/sum(a))

    ————————————–
    result-
    avg a[i]/b[i] : 1.4231215877667744
    avg b[i]/a[i] : 1.4264024986720856
    sum(a) / sum(b) 0.9995584826520475
    sum(b) / sum(a) 1.0004417123716274

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