Coronadoom Research Reaching Levels Of Asininity Never Thought Possible

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The reason I like to say there is too much Science because Science is now too easy to do, is because—and here I note I say this with great resignation—is because it is true.

Any grant-holding tenure-posturing peer-reviewing midwit professor with a computer can pump out papers faster than even the hardest hardcore bureaucrat can issue regulations. This is not a good thing.

I don’t know how many tens of thousands—or was it hundreds of thousands?—of coronadoom papers there were during the course of the panic, most of which could not possibly have been of any value. But now that the panic has cooled, and reached its farcical phase, a stage where you’d expect the flow to abate, it has only risen.

Here are two bad post-panic papers. The first we learned of from friend of the blog Kip Hansen. The second made the publicity rounds last week.

The Science One: Exposure To Conservatism

Paper one is “Relationship of political ideology of US federal and state elected officials and key COVID pandemic outcomes following vaccine rollout to adults: April 2021–March 2022” by Nancy Krieger and others in The Lancet: Regional Health.

Here’s their stated background: “Scant research, including in the United States, has quantified relationships between the political ideologies of elected representatives and COVID-19 outcomes among their constituents.”

There is no awareness in our authors that the research is scant because the idea is asinine.

Methods?

We analyzed observational cross-sectional data on COVID-19 mortality rates (age-standardized) and stress on hospital intensive care unit (ICU) capacity for all 435 US Congressional Districts (CDs) in a period of adult vaccine availability (April 2021–March 2022). Political metrics comprised: (1) ideological scores based on each US Representative’s and Senator’s concurrent overall voting record and their specific COVID-19 votes, and (2) state trifectas (Governor, State House, and State Senate under the same political party control). Analyses controlled for CD social metrics, population density, vaccination rates, the prevalence of diabetes and obesity, and voter political lean.

Before commenting on the depressing inanity of this, here’s their big “Finding”: “During the study period, the higher the exposure to conservatism across several political metrics, the higher the COVID-19 age-standardized mortality rates…”

Exposure to conservatism.

Yes. Exposure to conservatism causes coronadoom deaths and higher ICU usage.

I can think of no more cheering message that elites can tell each other than “We are on the right team.” This “research” does no more than that.

Here’s the 2022 electoral map for the House of Representatives. The red areas represent exposure to conservatism. Notice anything our brilliant Harvard authors did not?

How ’bout that hospital access away from the exposure-to-wokeism big cities?

And how about this: older people are much more exposed-to-conservatism than younger, and the doom killed the older and vastly higher rates.

This distressing paper uses various statistical shortcuts which they believe “control”—a horrible, horrible misnomer in stats, for this is no control of anything—for age and “social characteristics”.

Proof? How about this?

Because county-level death data were suppressed if the county had fewer than 10 deaths (13.8% of counties), and to avoid bias due to reported associations between counties’ political lean and their rural vs. urban status, we imputed suppressed county death counts using the observed state-specific rates applied to the county population and used these data to generate indirectly age-standardized rates per 100,000 person-years

So the counties most like to be exposure to conservatism didn’t even have real, but fake, data. The uncertainty of the faked data was not, you will not be surprised to learn, carried forward.

The exposure to conservatism was as robust: “a score for each member based on how they voted in roll call votes in the 117th Congress for 2021–2022”.

The authors do take this seriously! But they do allow this: “A key limitation of our study is that it is a descriptive, not causal, analysis.”

This is equivalent to “It’s only a correlation! Wink-wink, nudge-nudge, knowwhatimean.” The paper is saturated with knowing causal language.

In the end, this is another instance of the epidemiologist fallacy. This cannot be taken seriously.

The Science Two

You might have missed paper two last week, because it was embedded in a series of Tweets in my Tom Nelson podcast post. I know podcasts aren’t to everybody’s taste—though I don’t know why; I had thought my dulcet croakings were ideal soporifics.

A brief recap.

Paper is “COVID Vaccine Hesitancy and Risk of a Traffic Crash” by Donald A. Redelmeier and others in The American Journal of Medicine.

“Crashes” were identified only if they showed up as an Emergency Room visit, and thus recorded. “Crashes” that didn’t require a hospital visit did not make the list. Worst! “crashes” included “driver, passenger, or pedestrian”.

Passengers and walkers! DANGER! Walking while unvaxxed could lead you into a car crash! DANGER! Do not get into a car as a passenger while unvaxxed! It could lead you into a car crash!

The youngest age group was least vaxxed, because needing it laest, but—drumroll—had the most crashes. Our authors rediscovered the young crash more often.

They conclude risky driving “possibility relates to a distrust of government or belief in freedom that contributes to both vaccination preferences and increased traffic risks.”

Astonishingly stupid.

These silly studies should show you how easy it is for smart people to go wrong. They excel at discovering evidence which confirms their theories, but they stink, like the rest of us, at finding contradictory evidence.

Buy my new book and learn to argue against the regime: Everything You Believe Is Wrong.