Simple linear regression of official CDC data shows COVID vaccination is associated with increased mortality

If you wanted to prove the vaccine worked, this is the data and approach you'd use. It shows the COVID vaccine was a failure. If you followed their advice, it increased your risk of dying.

Executive summary

If you wanted to show the American public that the COVID vaccines saved lives, the easiest proof is to plot each state (or county) based on its vaccination rate (x axis) and its change in mortality from pre-vaccination baseline on the y-axis.

I did this. The slope is positive.

This means that more vaccinations are associated with higher mortality.

Can this be challenged?

I don’t think so.

The data is the data. They can’t change it. And there is only one way to draw a line through the data. If the shots worked, the slope would be strongly negative and it’s not.

This is likely why not a single paper attempts to do the most obvious analysis. They probably did it, saw that it was not supporting the narrative, and then decided not to publish.

Results for state regression and county regression

The slope was positive and statistically significant for both the state and county analysis. This means that the COVID vaccines did the opposite of what they promised: it increased your risk of death.

The R2 value of .31 is quite spectacular and it means this isn’t an accident.

This is the 50 state analysis (Washington DC substituted for Hawaii because Hawaii doesn’t report vaccination status to the CDC). x axis is doses per 100p. The more vaccinated you were, the more your mortality increased from baseline in 2021 and 2022.

And it’s positive slope for 2021 and 2022 individually:

County data

All counties analysis shows the same thing:

This is the regression of change in mortality from baseline vs. % fully vaccinated for each county in the US. The positive slope was statistically significant (upper and lower slopes listed above). A positive slope means higher compliance (% fully vaccinated) causes higher mortality.

Just to prove I didn’t cherry pick the counties, I computed the slopes for all different number of counties and you can see that all the slopes were positive meaning more shots—> higher all-cause mortality whether you looked at the 50 largest counties, the 500 largest counties, all the counties, or anywhere in between.

Here it is by each year individually starting with 2021:

For 2022:

Baseline mortality (the troughs) went up significantly after the shots rolled out

Look at 40-44 year old mortality before the shots rolled out vs. after the shots rolled out. 35% higher baseline mortality, but nobody noticed (except me)

75 year olds baseline mortality

You can see the 20% increase in this chart as well

You can also see that no miracle occurred in 2021 or 2022

The gap between baseline and 2020, 2021, and 2022 are all similar for the elderly who supposedly are now “supposed” to immune to COVID. So what’s killing them at the same rate? Did COVID “suddenly” become more deadly and the vax exactly equalized it? I don’t think so. In 2022, people weren’t dying from COVID anymore, but the ACM was just as high as it was in previous years since the vaccine rolled out.

Data sources

State
County

The details

x-axis: doses/100p (as of Nov 2021) for state; % of fully vaccinated (as of Jan 4, 2022) for county

y-axis: average(2021,2022) mortality divided by the baseline mortality.

The baseline mortality is calculated in the same state/county in the second half of 2020 (excluding December since December was half vaxxed vs. pre-vax)

In short, I took the closest baseline for each state/county and compared it with the total 2021/2022 mortality.

The method and choice of baseline were validated by ChatGPT as being the most appropriate and accurate.

It was indeed since the 2021/2022 mortality vs. baseline was nearly exactly 1.0 suggesting a very accurate baseline pick. For the counties, the average y value was 1.0021 which is damn close to 1. So it was an excellent baseline!

You always want your baseline to be RIGHT BEFORE the intervention and it should be very close to the numbers right after the intervention.

Did I make a mistake?

If you think I made a mistake, let me know in the comments.

The analysis is as straightforward as it gets.

Download the CDC data, create a pivot table, create the x and y values, and plot it. Or start with the spreadsheets in the Data section above.

No sleight of hand involved.

39 country study is confirmatory

Jarle Aarstad just published a study showing this graph with an R2 of 57%:

“Analyses from 39 countries with over a billion inhabitants show that per capita corona vaccination doses explain nearly 57 percent of the variation in all-cause excess mortality, with a beta value of .75 (1 is a perfect correlation). A conservative estimate is a ten percent higher mortality rate in high-vaccination countries than in low-vaccination countries.”

“Are there alternative explanations? No. The study has controlled for different countries’ accumulated excess mortality, socioeconomic development, median age, and population size (6).”

Full article.

Ed Dowd’s Excess Mortality Project analysis is confirmatory

This is for all ages in Q4 of 2022. R2=.41.

This is for all of 2023 for all ages:

This US analysis is also confirmatory (done by a friend who has to remain anonymous)

This is US using CDC data. It goes into <65 vs. >65 in all regions, large metros, and small metros:

If the vaccine worked, there would be a “knee” in the curve when the vaccines rolled out. There is no slope discontinuity at all!

Look at how the unvaccinated countries “pull away” from the highly vaccinated countries which, despite the vaccine rollout, have no slope discontinuity at all.

Here’s the US

We break from the line 15 months AFTER the vaccine rolls out.

Summary

There is simply no way to spin this as the vaccine provided a benefit.

All the data is from the CDC and there is only one way to draw a line through it.

If the vaccine worked, they’d be promoting these graphs to prove to you it worked.

But the graphs show that the CDC recommendations were more likely to kill you than to save you, so that may be why they aren’t promoting this data.

I asked ChatGPT for a comparable analysis of the CDC data showing the opposite slope for the change in ACM vs. vaccination rate and it couldn’t find a single paper.

So now you know.

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