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GAME OVER: Medicare data shows the COVID vaccines increase your risk of dying

Published: March 1, 2023 | Print Friendly and PDF
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Source: Steve Kirsch

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Nota Bene

This may well be the most important article I’ll write in 2023.

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.

The truth is like a lion. You don't have to defend it... - SermonQuotes
This is a great quote. Unfortunately, the "Truth is like a lion" quotation attributed to St Augustine was never penned by him, nor by any notable philosopher, sage or theologian before the twenty first century.

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).

 

Figure 0. Days to death from Dec 15, 2020 for everyone in Medicare in Connecticut (vaxxed and unvaxxed). Each bar is a 5 day period. The point of this graph is to show that the COVID outbreak exacerbated the slope since you are seeing effects of seasonality PLUS the waning part of a COVID outbreak. This is why there is a 40% drop from peak values.

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:

Figure 1. This is the weekly death counts from 2015-2019 summed over all US states for ages 65-84. This was created using a visualization on the CDC website using this dataset. Epidemiologists are very familiar with this effect. There are no surprises here. The peak is 256K, the trough is 213, so there is a 17% seasonality drop in deaths from the peak.

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:

Figure 2. This is the weekly death counts summed over all US states for 2021. This is essentially the control graph. This was created using a visualization on the CDC website using this dataset. Epidemiologists are very familiar with this effect. There are no surprises here. The deaths drop for the first 11 weeks of the year then stabilize. The peak is 81K, the trough is 50K so there is a 39% combined drop from peak to trough.

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

Figure 3. Connecticut vax rollout schedule for <80 Medicare participants peaked in weeks 3 and 4 of 2021. Each bar is a week

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.

Figure 4. This shows days until death from Shot #1 where shot #1 was given in Q1 2021 to Medicare recipients under 80. Every single day is a dot on this graph. What is supposed to happen is the line is supposed to slope DOWNWARD due to seasonality. If nothing “bad” is going on, this should look like a weighted moving average of Figure 2 (using the weights in Figure 3). As you can see, the slope goes the wrong way. Note that the increase in risk is still present after 2 years from the initial value at day 50, but at least it’s not getting any worse over time. NB: The graph drops off starting at 660 days out because we run out of months to die (since the shot is given in Q1 and the person must die before Feb 1, 2023).

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.

Figure 5. Same as Fig. 4 except we restrict shot #1 to be given in Q2. Not that the peak shifts since seasonality does not move. The drop off is now starting at 570 since we are now giving the shot a quarter later.

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:

Figure 6. Shots 1 and 2 were quickly rolled out to the Medicare community with most everyone getting fully vaccinated in Q1 of 2021. This is from Medicare data from Connecticut.

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

Figure 7. This chart is days till death from Shot #2 given that shot #2 was delivered in 2021. Since most of the shot #2 were delivered in Q1 2021, you should see a strong downward slope here as well. You don’t. The slope goes the wrong way for shot #2 too. That’s inexplicable.

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…

Figure 8. Shot #3 delivered in 2021. Most people in Medicare got their booster in October 2021, so we’d expect the slope to go down after 60 days. That doesn’t happen. The slop remains flat which is problematic.

This is the most damaging chart I’ve seen

Figure 9. Number of days died after dose #2 if you just got dose #2. So there is a rapid fall off at Day 200 which is people opting for Dose #3 and beyond. But I realized later that fewer than 50% opted for >2 shots. So we can raise the baseline by 2X and get a conservative estimate of steady state. This allows us to clearly see that the shots elevated your risk of death by around 50% for at least the first 200 days after the shot. This is a DISASTER and it’s also going to be impossible for the CDC to explain away.

This is a chart of people who just got two shots and no more. At first, I dismissed it because if you got 3 or more shots, you’d leave the group so the flat part starting at day 400 isn’t a valid steady state number because the size of the cohort changes due to the “no other shots” criteria.

But then I did a calculation using the Connecticut data and found that when there were 23,259 deaths from Dose #2, there were only 10,557 deaths from Doses #3 onwards. So this suggests to me that fewer than half the people in Medicare opted for the jabs.

Then I confirmed in USA FACTS that fewer than half the people who got shot #2 got any of the boosters (68% vs. 33%).

So if we simply take our 200 deaths per day flatline number from the chart above and adjust it for the people who left the cohort (i.e., double it to 400 steady state deaths per day), we can see that the first 200 days, we had a 50% increase in the rate of death (600 per day) vs. the 400 per day rate after 1 year (which itself might be elevated from normal).

This is a complete disaster no matter how you look at it.

The good news here is that it shows if you stop the shots, it appears your risk lowers after a year.

As you can see from this chart, if you keep on with the shots, as half the people did, your risk of death remains elevated!

Figure 10. This is the same as Figure 9, but here we do NOT have the restriction that you didn’t get any more shots. The number of deaths remains elevated due to the fact that half the people opted for subsequent shots. If nobody opted for any more shots after shot #2, we would have expected the curve to flatline at around 400 deaths / day.

Shot #4 elevates your risk as well, for the few that took it

People in Medicare got up to 7 total shots. That’s really stunning.

For example, in Connecticut, the numbers are: 31170, 23259, 8902, 1428, 217, 9, 1. So only 1 person got a 7th shot.

Here’s the graph for people who got Shot #4:

Figure 11. The fourth shot increases your risk of death too. People get the fourth shot late in 2022 so it drops off after day 100.

So people got shot #4 in 2022 which is why the graph falls quickly after day 200 (you simply run out of time to die). But you can see the same elevation in risk happening after this shot as well.

Death curve for the unvaccinated

James Surowiecki said was confused by this article because I didn’t include the unvaccinated.

I purposely didn’t include that chart because it would be confusing.

But if James was confused because I didn’t include it, I’ll include it with a big caveat.

The problem with the Medicare data is that the unvaccinated are a mix of people with vaccination and no vaccination so it is not pure. This is because Medicare patients went to a pharmacy to get their free vax and it wasn’t recorded in the Medicare records. This is why half the Medicare records don’t have any vax info at all. For Connecticut for example, there were 57,297 records of people in Medicare who died since Dec 14, 2020 and 26,092 had no vaccine records.

Also, people migrate from the unvaccinated group to the vaccinated group at an unknown rate (even Medicare doesn’t know the rate) which makes it problematic to use. That’s why I didn’t include it.

 

But since James was confused about this, I’ve now added the unvaccinated Medicare records from CT to the excel file (since those are the only unvaxxed records I have right now).

The plot is below. As you can see, the slope is downwards, just like you’d expect. No surprises.

Hopefully, James is less confused now.

Figure 13. The death curve for the unvaxxed in CT. This was added to the dataset you can download. This shows the deaths per day since Dec 15, 2020 for people in CT with no vax records who are in Medicare and < 80. Compare this with Figure 0 above (Figure 0 is ALL deaths whereas this is just the unvaxxed deaths).

Medicare reference data on the shot

This table may be helpful to some people.

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