US nursing home data shows clearly COVID vaccines made things much worse

Written by Steve Kirsch on August 24, 2023. Posted in Current News

CMS publishes record-level nursing home data by week. When you analyze this data different ways, the conclusion is always the same: the vaccines were a disaster, increasing the death rate from COVID

This is a very important article. Perhaps the most important article I’ve written to date.

In a nutshell, I analyzed the “gold standard” official US nursing home data and gave the vaccine every benefit of the doubt by analyzing it under “best case conditions” when the vaccine matched the variant, and soon after the vaccine was given so that it would be before the protection waned and a booster would be required.

If the vaccine worked as claimed, there should have been a huge drop in the infection fatality rate (IFR) and this data would be covered in every mainstream media outlet in the world.

This didn’t happen because the data clearly shows the opposite: a dramatic increase in the IFR post vaccination; it nearly doubled: odd ratio (OR)=1.45.

There is no way for them to explain this away. This is why the CDC never referenced this data even though it has been available for years.

If this data could be analyzed in any way that is positive for the vaccine, they would have done this.

So you don’t even have to read my analysis or even agree with any of it; the very fact that they have said nothing in the two years since this data was first made available about THE SINGLE MOST IMPORTANT “gold standard” data shows you CLEARLY that the data didn’t support their narrative.

We finally have the “gold standard” ground truth data that nobody can argue with showing that the COVID vaccines were a disaster for the elderly, the very population they were meant to protect.

The source of the data? Weekly infection, mortality reports from over 15,000 US nursing homes who were required to report their numbers to Medicare (aka CMS).

What makes this so important is that around 40% of the COVID deaths were in nursing homes. So nursing home COVID infection and death data is the “holy grail.” You cannot get any better than this.

And we set up the analysis to look when the variant matched the vaccine, and limited our analysis to the few months after vaccination before immunity starts to wane. So we set up the vaccine for success. We did everything possible to find the strongest possible signal of effectiveness.

So if this data is bad, it’s all over. There is no place to hide.

And the data is bad. Really bad. It would be hard to analyze this data and show it is a success.

CMS made a huge mistake by making the US Nursing home COVID data public where anyone who wanted to know the truth could analyze. Data transparency means that the truth is in plain sight. That’s really bad for the narrative.

So I did what any respectable “misinformation superspreader” would do… I downloaded the data and analyzed it.

I analyzed the data using three different methods (see my Excel spreadsheet) that I thought would be fair and objective and the results were consistent.

If the vaccines really worked, the IFR in the months after the vaccine (after a waiting period) should have plummeted, but it went up by 20 percent.

In addition, an analysis of elderly facilities in Ireland was fully consistent with what my analysis found: death rates in nursing homes skyrocketed right after the vaccines rolled out.

The CMS data shows that the vaccines were a disaster for the elderly three different ways:

1. Short-term death rate of 25 percent or more: People died instantly or shortly after the shot was given. For example, at Annandale Care Center, MN, eight people died on the day of the shot. The facility only has only 60 beds but at the time the facility was less than half full at 29 beds. So that is HUGE. That’s a same day death rate from the jab of 28 percent if everyone got the jab and it’s a higher rate if not everyone got the jab. This is crazy dangerous. But not all facilities get the same batch so that’s why the same-day kill rate can be very high at a single facility and lower at other facilities. Note: Annandale Healthcare Center was in the news and is a much larger facility, but is not the facility I just described, so be careful when fact checking this.
2. Up to 2X higher likelihood of dying from COVID short term and an increased risk of catching COVID as well: Residents got a compromised immune system from the jab, so they got COVID and died from COVID in record numbers. For example, at Apple Valley Village Health Care Center (AVV) in MN, there were 90 COVID cases in the first three weeks of Jan 2021, and at least 28 people died as a result of those infections. Yet in all of 2020, there were just 27 COVID cases and not a single death from COVID. At AVV, they went from a 0:27 death:infection track record (pre-vax) to 28:90 in just three weeks right after the jab was given at the end of December 2020. Same facility. Same COVID variant. Why was the COVID infection-fatality rate (IFR) so drastically different with the same variant, the same facility, and the same resident population? I wanted to know the answer to that but everyone at AVV refused to return any of my calls. But we see this in other places. The only thing that makes any sense is that it was the vaccine because it checks all the boxes. No other hypothesis has been offered. The good news is the doubling of the COVID IFR appears to be temporary as the IFR was only 20 percent higher in the months after the shots were given.
3. Up to 34 percent higher overall mortality risk for years post-jab: The jabs have permanently (or at least long term) weakened the immune system of all the recipients, young and old, so they are dying at a higher rate overall post-jab. On a small scale, you can see this in the Apple Valley deaths, for example (see the Apple Valley section below). On a larger scale, you can see this in all the excess deaths being reported such as BBC headlines the UK having their highest excess deaths in 50 years or in this article showing that 35-44 year olds are now dying at a rate 34% higher than before. That is a MASSIVE change. How can medical authorities be unable to explain the cause and fix it? Simple: they are not permitted to blame the vaccine so this will be a mystery forever. And they will never reveal the vaccination status of the kids who are dying because that would be a privacy violation. However, if you are unvaccinated and die, the news media is free to report that. Have you noticed that for all these sudden deaths and cardiac arrests, they never say “…and he was not vaccinated.”

The only good news was that the number of COVID infections dropped which means the COVID deaths dropped which resulted in a big drop in the all-cause mortality. Could this have been caused by the vaccine reducing the risk of infection?

Yes, it’s possible. But we have excellent studies, such as the Cleveland Clinic study, showing the vaccine does the opposite: making you more likely to get COVID. And in nursing homes where we could validate the data from an insider, we learned that both the COVID rates and IFR dramatically increased right after the vaccine; this one facility cannot be explained away as a “fluke.”

So the most likely hypothesis is that the virus simply burned itself out (and we see the ebb and flow of the COVID case rates over time where we actually got higher highs compared to the pre-vaccine period which is consistent with the studies (like the Cleveland Clinic study) that the vaccine made things worse).

The biggest surprise for me in viewing the data was the huge variation in the IFR even in the same month of the year between facilities, even those with high numbers of cases (where you would expect to see the most consistent numbers).

This suggests that the vaccine batches are variable or there is something else going on. Some vaccine batches make you highly susceptible to getting COVID and/or dying shortly after the shot, and other batches are duds.

While batch variability is negatively impacting outcomes, it doesn’t seem like it works the other way, i.e., that any vaccine batches are actually improving outcomes. I only hear negative stories.

When I ask for specific named facilities with a success story, I hear crickets.

A note to fact checkers: your guide to debunking this article

Simply complete all the items in this checklist.

1. Compute the actual OR for COVID death:survivor for the period immediately before the vaccine vs. after the vaccine rollout. I got 1.45 as shown in my Excel spreadsheet. Please show your data and formulas just like I did.
2. If you think you cannot calculate an IFR, show us the actual data that shows that the data that CMS collected is confounded. Explain precisely what the confounder is, adjust the data for the confounder, and show us the revised analysis showing the IFR actually plummeted after the vaccine rollout.
3. If you are making the unfounded claim that a large number of people came “into the system” from outside and stopped being tested upon admission in just the month of February 2021 (which could explain an IFR increase if there is supporting data), please show us your data proving that. The nursing homes I’ve talked to test every new admission and they test those people who are symptomatic. What is the explanation for the IFR nearly doubling after the vaccine rollout?
4. Show us one or more analyses of the CMS Nursing Home Medicare data published in the peer-reviewed medical literature showing that the vaccines REDUCED THE IFR after it was administered or resulted in an OR value that was <1.
5. If no such papers exist, you need to explain why there isn’t one because the data has been publicly available since July 21, 2021. Why would the CDC ignore such a rich dataset that would prove that the vaccines work if it worked?
6. Explain what happened at Apple Valley Village (see below). If it wasn’t the vaccine, what caused all these events (workers called in from holiday to deal with all the deaths right after the vaccine was given and an IFR that went from zero to 33 percent right after the shots were given)? It sure didn’t happen by chance so how do you explain the observations all of which are verifiable by third parties (and/or third party data).
7. Please publish your data backing up your analysis on a website or Github. After all, as a fact checker, you shouldn’t be afraid of anyone checking your work.

The data has been on the website for two years and nobody can explain it with an argument that is actually backed by data?

The bottom line is this: the raw data shows a huge signal in the wrong direction.

If you want to make the signal “go away” you need to either:

1. Delete the offending data from your study so you get the result you want (this is the technique used by the CDC in the pivotal DeStefano paper)’
2. Name the specific confounder and reanalyze the data “correctly” and show us the correct analysis with the confounder taken into account. Is it that in one percent of the reports that the cases were under counted? How does that change the OR? Show the data proving this.
3. You’ll need to explain the anecdotes like Annandale with a 28 percent death rate on the day of the shot and AVV where the IFR was zero until the shots rolled out and then it jumped to a nearly 30 percent death rate. Those are statistically impossible if the vaccine is dramatically lowering the IFR. You cannot dismiss these as anecdotes. They are evidence that is verifiable.

When you have a huge raw data signal like this, massaging it away is extremely difficult especially when there is no confounder available that could significantly move the needle on the odds ratio.

Good luck with that.

This is taken from a long document, read the rest here substack.com

Some bold emphasis added

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