In this article, I publicly reveal record-level vax-death data from the “gold standard” Medicare database that proves that:

1. The vaccines are making it more likely that the elderly will die prematurely, not less likely
2. The risk of death remains elevated for an unknown period of time after you get the shot (we didn’t see it return to normal)
3. The CDC lied to the American people about the safety of these vaccines. They had access to this data the entire time and kept it hidden and said nothing.

If there is one article for you to share with your social network, this is the one.

Executive summary

Isn’t it a shame that none of the world’s governments make the vaccination-death records publicly available? My claim is that if they did that, it would end the debate instantly and prove to the world that the vaccines are unsafe. So that’s why they keep it locked up.

But apparently there is one whistleblower who is interested in data transparency.

Last night, I got a USB drive in my mailbox with the Medicare data that links deaths and vaccination dates. Finally! This is the data that nobody wants to talk or even ask about.

I was able to authenticate the data by matching it with records I already had. And the analysis that I did on the data I received matches up with other analyses I have received previously.

The nice thing about this Medicare data is that nobody can claim that it is “unreliable.” Medicare is the unassailable “gold-standard” database. It’s the database that the CDC never wants us to see for some reason. They never even mention it. They pretend it doesn’t exist. So you know it is important.

Do you want to know what it shows?

It shows that these shots increase your risk of dying and once you get shot, your risk of dying remains elevated for an unknown amount of time. And that’s in the very population it is supposed to help the most!

Now you know why the CDC, which has always had access to the Medicare records, has never made them publicly available for anyone to analyze to prove that the vaccines are safe. Because the records show the opposite. That’s why they keep the data hidden from view and it’s why they NEVER talk about it.

Today, in this article, you will finally get to see what nobody outside the HHS has ever seen before: the “gold standard” Medicare records, i.e., the truth. You can analyze it yourself.

You’ll soon see for yourself why the CDC will never release this data and why the mainstream press is NEVER EVER going to ask to see the data: because it would reveal they lied to people and killed over 500,000 Americans by recommending they take an unsafe “vaccine.”

The bottom line is this:

When there is no data transparency, there is a high chance that the government is lying to you.

After all, if the data supported their narrative, they’d be tripping all over themselves to release the data. When it doesn’t support the narrative, they simply never talk about it and pretend it doesn’t exist and tell the press never to ask about it.

So you already know how this is going to end. Very badly. For Biden, the CDC, the FDA, the mainstream medical community, the mainstream press, and Congress. They all will have egg on their face because they never asked to see the data.

The “misinformation spreaders” will have been proven right with the government’s own “gold standard” database. It’s payback time.

Acknowledgements

I had Clare Craig of the HART Group look this over for any flaws. She liked it.

Professor Norman Fenton had a look as well and he didn’t find anything amiss either.

This doesn’t mean there aren’t any flaws, but it just means that there aren’t any obvious flaws. If you find a mistake, let me know in the comments.

Why this article is so important

If nobody can explain how the “slope goes the wrong way,” then this should be GAME OVER for the vaccination program because we are using their own “gold standard” database to prove that the vaccines are not safe and that they lied to us.

Unless I made a serious error, there is no rock big enough for them to hide under on this one. No excuses. No attacks. It’s basically bulletproof. The results simply cannot be explained if the vaccines are safe. And the numbers are huge. You don’t need a peer reviewed study on this one.

The Medicare data that I received

It’s in Excel, there are over 114,000 records, and you can download it here.

While I would have liked to receive the merge of all death records and vaccination records of everyone in the US, the data I did receive, when properly analyzed, is sufficient to prove the point that the vaccines are increasing your risk of death.

LIMITATIONS

Be sure to read the About tab for caveats about the data. It will help if you read and understand this article before you look at the records.

MEDICARE DATA NOTA BENE

Note that the scatter plots below were produced from a much larger set of Medicare records than the ones you can download. The plots from the records I received are included in the Excel spreadsheet and are consistent with the plots in this article which are the higher quality plots (and which contain dose 2 and 3 plots).

Overview of how to analyze the Medicare records

Because we only have vax-death records of people who have died (rather than the full set of records that any truly honest government would supply), we have to analyze the data in a certain way to understand what is going on.

This is a new way to look at the data so let me give you the bird’s eye overview first.

The main thing is that in Jan 2021 we have a double whammy of death: from COVID and seasonality (older people die more in winter).

 

So if the vaccine does absolutely nothing, we’ll see the slope of the histogram of the deaths per day curve go dramatically down in the first quarter as COVID and seasonality effects diminish. Then it will flatline for a time until seasonality picks up again in winter or there is another big COVID outbreak. The drop could be as much as 40% from the peak value (e.g., from 536 to 324) in Figure 0.

If the vaccine is PERFECT, we’ll see the same slope go down, but not as much because we’ll just see seasonality effects going down (since nobody is dying from COVID). It will then remain perfectly flat until it picks up again in winter. See Figure 1 below for what the “deaths per week” curve should look like for a perfect vaccine.

The main point is this: if the vaccine isn’t causing harm, the slope will go down and remain flat.

What I will be doing below is calculating the days until death from shot #1 if and only if shot #1 was given in Q1 of 2021. So that histogram should look very similar to Figure 1. It’s going to be smoothed somewhat since the shot was given over a quarter (rather than on a single day), but since most of the vaccine in Q1 was delivered in the first half of January, the curve will be pretty similar to Figure 1, but it will start to flatline a couple of weeks sooner.

Once you understand these concepts, you are ready for the details.

For people in Medicare, there is a strong seasonality effect on the death rate

For the elderly, there is a strong seasonality of deaths. They are high in the winter and low in the summer. The difference between peaks and troughs is around 20%. This data is from the CDC for ages 65-84:

What this means is if you got the shot in Q1 of 2021, and you look at the days until death, if the vaccines are safe, you should find that it will go lower in time and then turn upwards.

But what we find is the opposite.

The control group for 2021

Figure 2 shows the deaths by week in 2021 for all states ages 65-84. Note that the rates drop for the first 11 weeks and stabilize.

In 2021, there is a steeper drop than normal because of COVID adding to the drop:

The vaccine program was initiated on Dec 14, 2020, and peaked in the third week of Jan 2021 for people in this age group:

This means that if we limit our “days from shot #1 to death” analysis to people who got their first vaccine in Q1 of 2021, if the shot is harmless, we should see the rate of deaths dropping for at least 9 weeks after the shot, and then remaining flat for the next 15 weeks before turning upward. This is because about half the shots got delivered before week #3 (11-2=9)

The charts show the slope goes up instead of down

As we noted in the previous section, if the first shot is given in Q1, the number of days after the shot until you die should go down for at least 9 weeks and then stabilize for the next 15 weeks per the seasonality described in the previous section. So a safe vaccine would look like Figure 2

But it doesn’t. It goes up! That’s the problem.

Similarly, if we restrict our analysis to the first shot given in Q2 (most of which would have been given in April), we see the same problem. The slope should be flat for around the first 15 weeks after the shot is given (we are starting in a flat period (week 13) and we have about 15 weeks of flat deaths after that. Yet the slope is going up when it is supposed to be flat.

The same wrong slope happens with shot #2

The same problem happens with the second shot. About 75% of the people in Medicare were injected with shot #2 prior to April 15, 2021.

Here’s what the shot #2 injection schedule looked like in Connecticut:

Therefore, we should have seen a downward slope in the beginning and we are seeing the opposite again.

The same wrong slope happens with shot #3 too

Most people in Medicare got shot #3 in October, 2021. So we should see an upward trend for about 60 days (due to seasonality and another COVID wave), and then it should fall dramatically.

It doesn’t. It remains flat. That’s problematic. It suggests that if you lived until shot #3, it will still increase your risk of dying, just not as much as the earlier shots.

This chart would have been more useful had the Dose 3 vax window been narrowly restricted. Stay tuned…

Could there be an error in the queries?

No. I replicated the shot #1 charts myself and you can see them yourself in the Excel charts (which are drawn from the record-level data).

Is there any other way to explain away these results?

Not that I’m aware of.

I’d like to see someone try though. It would be fun to see the attempts.

Of course, you could interpret the upward slope as “See, the vaccine is saving COVID lives in the short term, that’s why the slope goes up over time as it wears off” but that is simply preposterous.

Nobody has ever claimed the vaccine reduces all cause mortality below baseline. There is no clinical trial showing that and there is no known mechanism of action whereby introducing a pathogen into your body will reduce all-cause mortality.

The only claim they make now is that the vaccine reduces COVID deaths. Fine. Let’s say that the vax is perfect and reduces every single COVID death, then the slope must still be downwards due to seasonality as we said before. But it’s not.

Professor Jeffrey Morris wrote “temporal HVE” on Twitter, but this is simply a handwaving dismissal of all this work with no evidentiary support whatsoever. HVE refers to healthy vaccinee effect. The “theory” is that the healthiest people get the vaccine first and since those people aren’t likely to die soon, it causes the slope to go upwards. But these are all Medicare patients and they were all vaccinated ASAP come December. What Jeffrey can’t explain is why the slope is even more distinct for people who got their shots in March 2021. Those would be the “stragglers” and thus less healthy, yet the upward slope is even more pronounced than in January. So his “explanation” just doesn’t fit the data. Nice try, no cigar.

That is why all these pro-vaccine people are upset about this data: because they can’t explain it. So they will have to ignore it and hope that nobody reads my article.

So if you share this article, you won’t let them get away with it.

Additional confirmation the vaccines are deadly

See my newly updated article on the UK data, which now includes US Mortality’s latest analysis:

Basically, even the flawed UK data still has a huge signal they couldn’t hide: there is a bigger killer than COVID and NOBODY can figure out what it is! Isn’t that odd?

Joel Smalley’s analysis of the UK data is superb as well. Even with the flaws relative to the unvaccinated, by focusing on the vaccinated, he can show they are dying at a disproportionally high rate.

Furthermore, Ed Dowd’s data, beautifully presented in his book “Cause Unknown,” is also hard for anyone to refute. How are working people 18-64 suddenly dying at a higher rate than non-working people in America right after the vaccine mandates hit? Nobody can explain that one.

Ed’s conclusions are the same as mine. So now you have two very powerful, but completely different datasets that are easy to explain if the vaccines are dangerous and impossible to explain using any other hypothesis.

And of course my favorite example is the VAERS excess deaths. How can there possibly be over 16,000 reported in VAERS if nothing is going on? The only vaccine with excess deaths is the COVID vaccine. All the other vaccines show the same number of excess deaths as in prior years. The argument that the COVID vaccines were rolled out to 100X more people than a normal vaccine is ridiculous. For example, the flu vaccine was given to at least 33% of the Medicare recipients so maybe you can argue a factor of 3X at most. So there is no way to explain the excess deaths which are effectively over 640,000 for a 41 underreporting factor.

The 640,000 number for the first two years of the vax rollout was validated in Mark Skidmore’s paper (which was published in a peer-reviewed journal) along with personal communications with Mark. Mark used polling and found a large number of deaths in 2021. Note that people are trying to get Mark’s paper retracted because they said it is unethical to ask people about vaccine deaths. Apparently, it’s OK to ask about COVID deaths, but it’s unethical to ask the exact same question about vaccine deaths. Also, they objected to the statement about who funded the study and wanted a complete bio of the funder. Mark has written over 70 papers published in the scientific literature and he’s never seen anything like these objections. The paper could easily note these, but they seem more interested in having the paper retracted because they don’t like the result. This is how science works. You can watch my interview with Mark Skidmore here so you can see first hand how science is manipulated with ridiculous objections when they don’t like what you find.

If the CDC wants to prove I’m wrong, it’s easy: release the data!

We need to stop holding the data hostage.

If the CDC wants to prove I’m wrong, the best way to do that is to publicly release all the data as specified in this article. That would be in the public interest.

Will they do that? No way. Never. They will come up with excuse after excuse why they can’t do this.

And that tells you EVERYTHING you need to know.

Summary

The record-level vax-death Medicare data I received is now publicly available. Now, for the very first time, you can analyze it yourself.

It shows the vaccines increase the risk of death for the elderly and that these risks appear to remain persistently elevated. It’s anyone’s guess for how long.

So now you know why the CDC never showed us the Medicare data. And now you know why the medical community and mainstream media never asked to see it and never will. They had it the whole time and kept it from public view so they wouldn’t create “vaccine hesitancy.”

If you think public health officials don’t hide the data, you should read this tweet from Chris Martenson where the Australian health authorities admit that they covered up vaccine deaths because they “didn’t want to undermine public confidence” in the vaccine. Get it?

If you think public health officials in the US want to see all the safety data even for just themselves, you should watch my video of Stanford Professor Grace Lee calling the Palo Alto Police on me when I tried to ask her if she wanted to see the safety data from the Israeli Ministry of Health. Basically, the health authorities in the US run the other way when you try to confront them with data showing they are wrong.

Finally, if your doctor still tells you to take the shot, ask her to first explain to you why the slope in the Medicare data goes the wrong way before you get the shot. And let us all know what they say in the comments.