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Josh Stirling: Dissecting Excess Death Data and How Insurance Industry’s Trillions Could Be Deployed

“The more doses on average you have in a region within the United States, the bigger increase in mortality that region has had in 2022 when compared to 2021,” said Josh Stirling, an insurance research analyst who has been dissecting alarming trends in life insurance, mortality and disability data over the past couple of years.

Looking at CDC data, Stirling ranked the number of doses administered across regions in the U.S. and compared that to the increase or decrease in mortality in 2022 compared to 2021. He said what he found was a clear regression line to the right. In other words, more doses correlated to greater increases in mortality.

He has also conducted extensive analysis of U.K. data which show greater mortality rates among the vaccinated than the unvaccinated in 2022, as well as German hospital data showing alarming trends in immune-related issues and female fertility.

According to Sterling, COVID-19 vaccine manufacturers have turned their backs on the vaccine-injured—and face essentially no financial consequences for doing so. But there is one multi-trillion industry that actually does have a big financial incentive to help the vaccine-injured, said Stirling. He is the founder of Insurance Collaboration to Save Lives.

“If we were actually just screening for these people, the vast majority of these health issues—before they become catastrophic—could very easily be managed, not necessarily solved, but certainly managed with amazing medical advances and simple things like blood thinners, or changes in lifestyle,” he said.

“If we can help at scale people understand their current health situation, then, absolutely, we can save a bunch of lives,” said Stirling.


Interview trailer:

Watch the full interview:



Jan Jekielek:

Josh Sterling, such a pleasure to have you on American Thought Leaders.

Josh Stirling:

Jan, I’m so happy to be here. Thank you for the opportunity.

Mr. Jekielek:

We met last December at the hearing that Ron Johnson convened on COVID-19 vaccines; what they are, how they work, and the possible causes of injuries. And indeed, you presented at this hearing some very interesting and very troubling data around all-cause mortality, and some ideas about what might be causing a very significant increase in America and other places around the world. Why don’t you just remind us of what you presented?

Mr. Stirling:

What I presented at the hearing in DC was the semi-famous chart that tells the whole story, which is using data from the United Kingdom’s Office of National Statistics, where for about 18 months they had been tracking the monthly mortality for the vaccinated populations by the number of doses, as well as the unvaccinated in the United Kingdom.

Starting in January 2021, they generated this data with a couple of months lag. They released the most recent version of it over the summer of 2022. What you see when you analyze this data is that although the vaccinated appear to have had lower mortality in the year 2021 in general and aggregate across all ages, in 2022, generally the vaccinated have had much higher mortality than the unvaccinated.

In particular, there were a couple of really troubling things that emerged, which is one of the reasons that Senator Johnson was so interested in this data. You can see that people who only took one dose of the vaccine had 145 per cent higher mortality in the more recent months, and that’s not a recent phenomenon. That’s what’s been going on for a number of months throughout this dataset.

That’s probably because they were injured by the shot, and of course that’s a real tragedy, because we all know someone who had a bad reaction to the COVID vaccine shot. That’s a very common thing, unfortunately. It also showed that on average across all populations in the United Kingdom, you can see that overall, in the last data we have available, there’s a 26 per cent higher mortality rate for those who’ve been vaccinated, versus those who haven’t. And under the age of 50 it’s a 49 per cent higher mortality rate.

Those are really troubling numbers. I’ve gotten a fair amount of interest in what I said in DC. Just to put a pin in it, if you just take those numbers and you apply them against the United States, we have about three million deaths a year.

If you use the number of people who are vaccinated, the different proportions of the United States and the different categories, and you apply the experience from the United Kingdom to the United States, you end up concluding that we are probably having about 20 per cent additional mortality as a result of the vaccine, which if those numbers hung true, would be 600,000 deaths a year in the United States.

Mr. Jekielek:

This isn’t something where you know for sure this is the cause, just to be clear.

Mr. Stirling:

No. I used to work on Wall Street, and you were a financial detective where you pulled pieces of data from lots of different things to try to figure out what’s happening right now, and what’s likely to happen in the future. And so, we’re working with lots of different types of data and consulting with medical doctors and people in the insurance community and public health researchers.

Ultimately, there’s a lot of different ways to look through the numbers. There’s at least three or four different ways to triangulate into a similar conclusion from big data sets that have tens, if not hundreds of millions of people in them. But ideally, we would all like to do a lot more research to know for sure.

Mr. Jekielek:

Because there are other reasons why there might be higher mortality. For example, when the shelter-in-place policies were active. And actually, in the UK it was a bit different than here too, which is interesting. But arguably, that could be a factor that plays in. How do you tease that out?

Mr. Stirling:

Let me share some data that could possibly speak to some of that. One of the data sets that insurance people in particular look at is non-COVID mortality. Let’s just set aside COVID, and just talk about what’s going on besides COVID. That’s what that means.

In the summer of 2020, during peak lockdown in a lot of places, there was a little bit of a blip in non-COVID mortality. That was probably attributable to social deaths from isolation, loneliness, the loss of a job, alcohol, fentanyl, and things like that. But those went away, and you saw non-COVID mortality be like a net benefit. It was lower than you would expect for a couple of quarters late in 2020, and then early in 2021.

What’s happened on that data series is since the third quarter of 2021, it generally has continued to be elevated. And recently, non-COVID mortality, excess mortality but not from COVID, represents about 62 per cent of our current mortality problem. And so, it’s not COVID. It could be a lot of things. It could definitely be some of the social stuff. It could possibly be contributed to long-term lockdown impact. Long COVID is a possibility, too.

The spike protein floating around does a lot of damage, it really doesn’t matter where it’s coming from. There are multiple sources, obviously, whether it’s the vaccine or whether it’s the infection. But for the big systemic change, as a data analyst if you’re looking at the time series, you end up saying the easiest way to explain this, and probably the most statistically likely way to explain this is in fact the change that occurred in 2021 was largely when the vast majority of the world got vaccinated.

Because the group I’ve been working with is a bunch of insurance geeks, and we’ve looked at it in a bunch of different ways. The UK data is one of the most powerful ways of looking at it. Ultimately, what they’ve done is not a randomized control study, because there’s going to be sample biases between people who do or don’t take the vaccine. It’s hard to know for sure if they’re healthier or they’re less healthy.

There’s a lot of different theories on what the bias would be, either a good guy or a bad guy for different analysis. But ultimately, what you’re looking at is that it’s a real-world experiment with tens of millions of lives. And so, the statistical credibility is real. How one interprets it is always open for debate.

Mr. Jekielek:

This last bit of data you were describing, I think that was U.S. CDC data, if I’m not mistaken.

Mr. Stirling:


Mr. Jekielek:

But then before you were talking about UK data. Why not just use CDC data across the board?

Mr. Stirling:

Because this is a global phenomenon, one of the issues that’s been helpful is that there’s a lot of different global public health authorities with different types of data available in different amounts. The CDC provides a lot of data, but they don’t provide some of the most critical pieces of data. We’ve done work with German hospital records, because the Germans are very well organized, and they’re very open and transparent with a lot of their records. You can analyze what the trends are, different diseases and symptoms, treatments, and the procedures in hospitals in Germany. That data is not public in the United States. It’s just not available.

Similarly, I would love to do a report showing that in the United States we’ve got 250-something million people who have taken the vaccine at varying levels of dosing and a number of boosters. Obviously, the U.S. government, through the CDC and Social Security Administration as well of all the various states, has records that could be merged to do all of these things, and to literally recreate that same study. If they’ve done that study, they haven’t published it. They absolutely haven’t released it to the public, the data analyst community, the public health researchers, and the insurers for us to do it ourselves.

The best we can do in the United States is to use the aggregated data that the CDC does release. One of the things that’s really interesting—everybody involved with this is working 24/7, it’s an emerging problem and there’s a lot of things happening quickly—is that we didn’t have this data in DC.

But since then, we’ve pulled together an analysis that uses CDC data from the United States that compares the vaccination status ranked by the number of doses across regions in the United States and then compares that to the amount of increase or decrease in mortality this year versus last year.

If the vaccine was neutral, there would just be no relationship between these two things. If the vaccine was helpful at reducing all-cause mortality, you would see that the more doses of region, in the state of Vermont or Maine or Hawaii or Connecticut or someplace that’s pretty highly vaccinated, you would see lower levels of mortality year over year, because people got more vaccines than in other places that didn’t do as much for whatever reason, you would see an improvement and you would see a line that slopes down to the right.

Instead, when we did that analysis and cut it a number of different ways, by different types of city and region and by age group as well, we gave it some thought to make sure there wasn’t a bias in it. But no matter how you do it, what you end up seeing is that you create a regression line goes up and to the right, which is simply to say that the more doses on average you have in a region within the United States, the bigger increase in mortality that region has had in 2022, when compared to 2021.

That is an aggregate statistical tool that exactly confirms the conclusion of the UK data. It’s a different way of doing it. It’s a totally different dataset. But ultimately, it leads to a very similar mathematical conclusion. It’s a really unfortunate one, because obviously, hundreds of millions of us had our friends and family and all of society having to deal with these long-term health consequences. I’m hopeful that we as a society can start to focus on those, because that’s an opportunity to solve this problem by focusing on health.

Mr. Jekielek:

There’s something that’s a bit unintuitive, but you’re arguing that it tells the same story. One of them is what you just described, that with this regression line, the more boosted people are, the mortality among those groups increases. But in the UK data, you said that it’s the first shot that actually shows the highest mortality. How are these things not in opposition to each other?

Mr. Stirling:

It’s a really good question, Jan. It has to do with how the data is structured. On an individual basis, you can make a better prediction for a person’s mortality risk based on the UK data. Which is to say that if you took one dose and stopped, because it wasn’t a design study and it’s an observational study, it’s literally that you stopped at one dose.

Then, we can infer, based on the statistics that we have from the UK, you’re likely to have substantially higher elevated mortality. The reason that we can speculate intuitively to explain that, is that these people stopped because they were injured on the first dose.

Mr. Jekielek:

Basically, they said, “Okay, I’m not doing this again.”

Mr. Stirling:

Within 21 days they were supposed to get a second dose and they said, “No, I’m not going to do that.” In the U.S., that’s about 12 per cent of Americans. What the data would suggest here is that if the relationships in the UK are the same in the U.S., those people would have a 145 per cent higher mortality rate. The reason that doesn’t carry on to the U.S. data in aggregate is because when you look at big groups of people, the little individual signals of their behavior is washed out. Because really what we’re just saying is “Were there more doses in Georgia than Alabama, or in Vermont versus Maine?

In that case, it’s all just a question of what is the aggregate level of dosing? In which case, if you use the regression line on that data, you end up being able to very clearly draw a conclusion that says the slope of the line is basically how much mortality increase you’re getting from every dose. It’s about a 7 per cent increase in aggregate mortality from U.S. data per dose. If you’re over the age of 50 and you took all five doses, that would be a 35 per cent increase.

Mr. Jekielek:

Right. For the benefit of our viewers and my own sanity, in the UK you know that there are specific people; one, two, three, four people that you’re tracking. In the U.S., you can only say that overall, in this state or that state, this is what it looks like.

Mr. Stirling:

Yes, and that’s exactly right. The statistical department in the UK is really good, and they seem like they’re really good in Germany too, so we have better data to work with overseas. But the data we have here is troubling. We started our conversation talking about excess mortality, generally. As of the third quarter COVID is in the rear-view mirror now.

It depends on how you calculate these things, but if we use CDC numbers and then compare it to 2019, current mortality is elevated by about 12.4 per cent in the third quarter of 2022, relative to where it was in 2019. Approximately, that rounds up to 400,000 people a year just on that number.

Mr. Jekielek:

That’s across all age groups?

Mr. Stirling:

It is across all age groups. You get into measurement questions with the different age group levels, because of challenges in the pull forward effect in trying to figure this out, which is particularly extreme in the older ages. The increased mortality isn’t as extreme for the older ages than the younger ages, largely because there’s about a million people who died in 2020 and 2021, mostly in the older ages, who if they hadn’t died in those years due to COVID, or due to failure to treat COVID, or bad hospital protocols that led to deaths that were not necessary, if those people hadn’t died then, they would be dying now. But since they have already died, it looks like we have less deaths now. That’s not really a win. That’s kind of double counting.

You would say it’s a distortion. A Wall Streeter might talk about it as a pull forward effect, like when a retailer runs a special and a promotion and they sell a lot of extra toasters this year, but then nobody buys the toasters the next year, because they just got a big discount. So then, their numbers are much lower the following year.

That’s what is going on in a lot of the U.S. in particular, because we had much higher mortality than a lot of other countries for a variety of reasons. We have a bigger pull forward effect too, which is why it looks like on some measures we have lower mortality right now than in other places.

Mr. Jekielek:

It was concentrated in some of those higher risk groups, especially of significantly advanced age people.

Mr. Stirling:


Mr. Jekielek:

Wow. You’re clearly a numbers guy. Why don’t you tell me how you got interested in this? The numbers are fascinating in themselves, but they’re also pretty morbid. At the same time, you could get in a lot of trouble looking at these numbers from what we’ve seen over the last few years. Please tell me about how you got here.

Mr. Stirling:

The short answer is I’ve been an insurance guy my whole career and I’ve had enough prior experiences looking at numbers that are controversial and getting in trouble, and that didn’t push me away. I’m not an economist, but every morning I wake up and I look at a whole bunch of charts about the economy, because I’m a former Wall Street guy. I like thinking about numbers. I like understanding the relationships of things.

All of a sudden, this explosion of public health data coming out led me to this journey of trying to understand what’s going on. Along the way I became passionate about it as a matter of faith and of calling. I want to try to help people, because I began to realize what the data was saying.

I began to either meet or see people, and I’m sure it’s just anecdotal, who were real people that were harmed in some fashion by COVID policy in general. But in particular, I saw some of the things that are driving mortality, morbidity, and disability up through the roof at record levels in 2022. I just felt moved to try to help folks. Ultimately, that’s why I’m here with you today, and that’s why I met with Senator Johnson last month.

Mr. Jekielek:

You’re a father as I understand it.

Mr. Stirling:

I am. I’ve got two beautiful girls. I’m very lucky they are okay. I saw videos of people like Maddie de Garay, the poor girl who was in the Pfizer child study who suffered completely debilitating paralysis. And I can’t speak for her. I’m not sure of her current status, but ultimately the stories are heart-wrenching as a father.

As a professional analyst who likes to read things and likes to look at numbers, I read the child study, the Pfizer study, and realized that they didn’t even code her as a serious adverse event. That starts to piece things together. I began to realize there was a lot to this where I, as a moral duty, and as a humanitarian calling, could use those skills that I learned on Wall Street for a better and more noble purpose. And that’s why I’ve been trying to help.

Mr. Jekielek:

Insurance industry data is very difficult to interpret. This is what became your specialty to try to tease through it and explain it to the Wall Street types who are deciding how to deal with different realities. You were quoted in this story about Lincoln Financial and their unusual credit downgrading. There seems to be some kind of signal, in one insurance company at least, that suggests that there is increased mortality and they’re concerned about it. But you’re not seeing it in other places. Is that really a signal that needs to be looked at?

Mr. Stirling:

You’re seeing it in the raw data. I don’t think this is just a Lincoln thing. Certainly, most life insurance companies are going to face different, potentially very serious challenges coming out of whatever we want to call this, the knock-on effects of COVID. Whether we say it’s the vaccine or something else, it doesn’t really matter.

The legal complexities, in terms of losses, as well as in the terms of incidental litigation that will come from this and other complexities, are likely to be a problem. But for your viewers, I used to be a professional insurance analyst. For many years I kept a fortune cookie I had happened to find on my desk to remind me, and the fortune cookie was saying it’s your job to simplify.

But the simple story for life insurers in particular, and insurers generally, is that their accounting is not bad. It’s the way it’s designed, and they follow the rules. But the rules are designed to smooth out bumps in the road and make very gradual changes over long periods of time. As an industry, they also really don’t have to borrow any money.

For your financially astute viewers, you’ll recognize those things are basically exactly the opposite of banks and hedge funds and other types of financial intermediaries that borrow most of their money, and they sometimes borrow it overnight, so a lot of their assets and obligations are very much marked to the market.

Here is something which can be like a canary in a coal mine in the insurance industry for potentially huge problems. A leading industry player like Lincoln Financial gets downgraded from A+ to A. I’m not saying anything bad about Lincoln, and I don’t think it’s their fault.

They are being downgraded because their policyholders are keeping their policies longer as they age, presumably because they want their production, and presumably because maybe they’re feeling like they’re not as healthy as they were hoping to be. That would argue for potentially more losses in the future relative to higher mortality, because the policy holders themselves are revealing through their actions their choice to keep their policies, and that perhaps there are adverse health signals.

Mr. Jekielek:

Basically, you’re saying people are not canceling their insurance policies at the normal rate, and that indicates that people have health concerns, so they’re keeping them. Am I reading this right?

Mr. Stirling:

Yes. That would be the best interpretation. That’s the underlying signal, and that’s the way I interpret it. AM Best regulates insurance companies, and I’ve talked to them a number of times about these issues. They were very kind to quote me in this article talking about that saying, “Hey, we think this could be a sign of things to come,” politely.

Again, it’s not a Lincoln thing. It’s a systemic thing. The way it works in insurance world is this could take two decades to play out. If this is unbelievable, with people who’ve heard of long-term care, maybe some of your viewers have these policies. The insurance industry was right into them gangbusters in the 1990s. GE [General Electric] back in those days was a life insurance company, and they did all sorts of things under Jack Welch back in the 90s.

They sold that business, in part because of all the money they were losing in long-term care in the mid-2000s. They took it public, and it became Genworth. Genworth, after a decade completely imploded in the 2010s, because of problems created in the 1990s. They had lots of financial troubles, got downgraded, and became more of what they call a company in runoff that doesn’t really write new business.

The regulators were very much looking over everything they did. In 2018, shortly before COVID, GE surprised the world when all of a sudden, they found they still had problems buried in GE relating to long-term care, which the world had thought were gotten rid of in 2004 or 2005. They were bad decisions relating to long-term care insurance policies that were made in the early 1990s.

Life insurance accounting in particular is very long duration. It’s important to look for the signal and not get too hung up on the accounting, because the accounting is going to take a lot longer to play out than the actual underlying reality.