The US Nursing home data shows the IFR skyrocketed after vaccine rollout. It was supposed to do the opposite.

ChatGPT admitted that the primary benefit of the COVID shot was reducing the IFR. It also said US Nursing homes are the most definitive source. OK, so let's have a closer look!

Executive summary

ChatGPT says the COVID vaccine’s impact on the infection fatality rate (IFR) is where the primary benefit was (since nobody is arguing it reduces infection or transmission risk because it doesn’t).

GPT claims the IFR was reduced by roughly a factor of 10.

It then says nursing home data is the most dispositive source of truth for measuring IFR impact on the elderly in the US. I agree on that one and the list of reasons.

It then cites 2 papers showing that the IFR dropped in nursing homes.

I will show you in this article that there wasn’t any IFR reduction caused by the vaccine; the IFR went up making the vaccines a huge disaster.

ChatGPT say correctly that vaccines impact R₀ and IFR and reasons that the primary benefit was IFR reduction

The COVID-19 vaccines impacted both R₀ (basic reproduction number) and IFR (infection fatality rate) in the elderly, though their effects on each metric differed.

Impact on R₀

R₀ is influenced by transmission risk, which depends on:

1. Susceptibility to infection (how easily an individual gets infected).

2. Infectiousness if infected (how much virus an infected person spreads).

3. Contact rate (how often people interact in ways that lead to transmission).

COVID vaccines:

• Reduced susceptibility: Vaccines provided protection against infection, particularly before immune-evading variants emerged.

• Reduced infectiousness: Vaccinated individuals who got infected generally had lower viral loads, reducing transmission risk.

• Indirect effects: Vaccination campaigns reduced overall case numbers, indirectly lowering exposure risk for elderly individuals.

However, the effect on R₀ was incomplete because:

• Vaccine protection against infection waned over time.

• Variants like Delta and Omicron had higher transmissibility and partial immune escape.

• Elderly individuals often had weaker immune responses, meaning lower vaccine efficacy against infection.

Thus, while vaccination reduced the effective reproduction number (Rₑ or Rₜ) at the population level, its impact on R₀ (which assumes full susceptibility) was more limited, especially after immune-evading variants emerged.

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Impact on IFR (Infection Fatality Rate)

IFR is the probability of death given infection. It depends on:

1. Baseline mortality risk (which is high in the elderly).

2. Severity reduction (whether interventions make severe disease less likely).

COVID vaccines:

• Significantly reduced severe disease: mRNA vaccines (Pfizer/Moderna) showed ~90%+ effectiveness against hospitalization and death in elderly individuals.

• Lowered IFR dramatically: Pre-vaccine, IFR in elderly (80+) was estimated at 5–15%. With vaccines, IFR dropped to ~0.5–2%, depending on variant and booster status.

• Durability issues: Protection against severe disease waned over time, but booster doses restored it significantly.

Thus, vaccination had a much stronger effect on IFR than on R₀ because protection against severe outcomes remained robust even as immune escape reduced infection prevention.

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Net Impact on the Elderly

• R₀ reduction: Moderate, but limited by immune escape and waning protection against infection.

• IFR reduction: Strong, with vaccines cutting the fatality rate in elderly populations by 5–10x or more.

This means that even when breakthrough infections occurred, vaccinated elderly individuals had a much lower risk of dying than unvaccinated ones.

ChatGPT said that US nursing home data is dispositive on the issue

I wrote: “Wouldn’t the data from the 15,000 US nursing homes be the most accurate estimate? These are all closed systems where the case fatality rate is known precisely because it’s a captive audience.”

Answer:

Yes, data from the 15,000 U.S. nursing homes is one of the most accurate sources for estimating IFR in the elderly because:

1. Closed system – Nearly all residents are monitored, so cases and deaths are captured with high completeness (unlike general population studies, which suffer from underreporting).

2. Consistent testing – Nursing homes had routine testing, reducing the undercounting of infections.

3. Captive audience – Infected individuals had near-100% follow-up, so there was no loss to follow-up bias that could affect IFR estimates.

4. Direct vaccine effect measurement – The first vaccine doses were prioritized for nursing home residents, allowing a clear before-and-after comparison.

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What Did the U.S. Nursing Home Data Show?

• Pre-vaccine IFR (2020): The case fatality rate (CFR) in U.S. nursing homes was ~20–30% in outbreaks.

• Post-vaccine IFR (2021): After full vaccination (mRNA vaccines), mortality among infected residents dropped to ~2–5%.

• Reduction in IFR: ~80–90% decrease in fatality rate among infected residents.

This data comes from the CDC National Healthcare Safety Network (NHSN) and was analyzed in studies published in the New England Journal of Medicine (NEJM) and JAMA.

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Strongest Nursing Home Study: NEJM (2021)

A study in NEJM (July 2021) analyzed U.S. nursing home residents vaccinated with Pfizer/Moderna:

• IFR in vaccinated residents fell by 85% compared to pre-vaccine.

• Even unvaccinated residents in the same facility had lower IFR due to reduced transmission.

Conclusion: Nursing home data provided the clearest and most precise IFR drop due to vaccination, making it the strongest real-world dataset.

Wait a sec…. IFR doesn’t change with cases!!

ChatGPT wrote: “Even unvaccinated residents in the same facility had lower IFR due to reduced transmission.”

It doesn’t work that way. IFR varies with vaccination and variants, not with cases.

The only exception to this is when cases overwhelm the healthcare system so people can’t access treatment. This can then impact the IFR in a community.

I then asked ChatGPT to summarize the findings of that paper which showed a dramatic 100% reduction in COVID deaths at Genesis healthcare per EMR records in 280 nursing homes across 21 states (N=18,242 vaxxed; N=3990 unvaxxed)

The study enrolled on Feb 15, 2021. The cutoff date for analysis was March 31, 2021.

Did the vaccine reduce infections among the vaccinated relative to the unvaccinated? NO!!!

You have to be sure to compare the same time intervals! So >14 days after the 2nd dose for the vaccinated is equivalent to 14+30 days for the unvaccinated = 44 days.

From the table you can see that both vaccinated and unvaccinated had a remarkable benefit in cases: only .1%!

From HART’s article on how to get your studies published, they wrote:

A New England Journal of Medicine paper showed a similar or lower proportion of unspiked care home residents caught covid compared to the spiked. The authors concluded, “Our observation of a reduced incidence of infection among unvaccinated residents suggests that robust vaccine coverage among residents and staff, together with the continued use of face masks and other infection-control measures, is likely to afford protection for small numbers of unvaccinated residents in congregate settings. Still, the continued observation of incident cases after vaccination highlights the critical need for ongoing vaccination programs and surveillance testing in nursing homes to mitigate future outbreaks.”

In short, HART noted that the unvaccinated had the same reduction of COVID cases as the vaccinated and the paper authors ascribed this to the protection afforded to them by being surrounded by the vaccinated.

That’s possible, but how can we rule out the more likely scenario that the vaccine didn’t work at all to reduce cases relative to the unvaccinated?

How about deaths? There were no COVID deaths in the vaccinated so the IFR dropped to 0!

To summarize, this study of 18,242 nursing home residents who got the shot showed that the COVID IFR dropped from 20 to 30% before vaccines to 0% after. That means the COVID vaccine reduced deaths by a factor of 20X or more.

Table 1 footnote said: “In the 9 fully vaccinated residents with incident symptomatic infection, the symptoms included cough (in 4 residents), fever (in 2), hypoxemia (in 2), tachycardia (in 2), and diarrhea (in 2). Of these 9 residents, 2 were hospitalized; all 9 were alive 30 days after testing positive.”

So in all 9 cases, nobody died.

This is hardly statistically significant proof of an IFR benefit since the normal IFR was around 15% so seeing 0 deaths while expecting 1.35 happens 26% of the time so it’s not statistically significant.

What the US Nursing home data really shows

The shots caused the CFR to shoot up from the start of the vaccination program till it leveled off. Then the CFR went back down to what it was. The IFR drops 40% in 2 weeks at the very start of each new COVID variant wave, NOT for the vaccine.

So the shots killed people for no benefit.

Spreadsheet here with the graphs.

Here’s the annotated graph:

Here is the IFR plot with the 95% confidence error bars:

Cases in US nursing homes agree with OWID cases

Here are the nursing home cases superimposed on the OWID graph for US. This shows the nursing home cases tracked the national numbers.

Also, the r value (Pearson correlation coefficient) was .99 when matching ACM deaths with COVID deaths with NO time shifting showing that they correctly identified that all the ACM bumps were COVID cases (it wasn’t random).

And the r value was .98 when matching cases with COVID deaths.

In short, the US nursing home data is dispositive.

Summary

The shots didn’t work for the very target they were intended for. They cost lives.

• R₀ reduction: none (it clearly went up as you can instantly see from the high case peaks in Israel)

• IFR reduction: None. IFR dropped with variants, not vaccination waves as you can see from the chart.

The all-cause mortality (ACM) increase mostly affected those younger than in nursing homes, raising mortality by 1 death per 1,000 shots. Clearest evidence of that is the FDNY firemen who sacrificed their lives to give us clear statistical evidence of harm. More about that in an article later this month.