Editor's note: You can find a full transcript of Doc and Matt's briefing, complete with slides, below the video. If you'd like to view a pdf of the slides, click here.
Dr. David Eifrig: Hello, everybody, and welcome to this week's COVID conversation No. 20. I'm Dr. David Eifrig, and with me, and still socially distanced, is Matt Weinschenk. Matt, welcome.
Matt Weinschenk: Hello, Doc. How are you doing?
Doc: I'm doing well. How about yourself?
Matt: I'm good, I'm good, you know.
Doc: Good, good. Folks, if you have questions, feel free to write us at firstname.lastname@example.org – that's email@example.com – and then you can get free updates. We put out a daily free letter that's about 750-1,000 words, every day, where we dive into health and well stuff – free letter. We put this stuff in there, we put stuff that is just fantastic information, and you can get that at healthandwealthbulletin.com. Feel free to send that to friends and family, old and young – we welcome you. And let's dive in.
Matt: Yeah, so let's get started. So, this, you know, in case you're just joining us, I feel like we haven't recapped in a while. This is our unedited conversation about what's going on, parsing the evidence, seeing what's new and what we can figure out in these uncertain times, and we usually go: virus, economy, and market – in that order. And we had three weeks off, and, you know, the news is kind of slower on the virus, so, part of what we'll be doing is sort of kind of a check-in. Like, what's the overall story, at this point? What have we found out? And most importantly, to me, I think, what we don't know and what's gonna happen.
And, you know, this is all in the – this isn't necessarily in the spirit of saying what we should do, or policy, or anything like that, but what is happening and what can we expect, I think, is a more fruitful way to look at things. So, cases are on the decline, for the most part. Little blip, you know, maybe that schools reopening, maybe it's just a little dot, there, but, you know, the second wave has come back down. Why is that? You know, you can – there are studies that show it's masks, there are studies that show it's not masks, there are studies that show it's distancing and it's not distancing, and that it's the virus itself.
And really, the answer is, so, you know, part of my background is econometrics, and that whole thing is trying to take things that don't have, necessarily, clear a relationship, or there's lots of confounding factors, and trying to pull out what's actually happening in there. And this has gotta be the biggest project you could ever come up with. It is so complicated to try and understand – to try and prove that maybe it was masks or it's the interventions or it's lockdowns or it's not. It is so complicated, there's so many different jurisdictions, so many different rules, so many different – everything's happening at different times, it's very hard to tease out why exactly this is the case. So, you can have – everybody has their theories and their answers, and there's evidence on a lot of sides, but the – to me, I mean, the final answer right now, Doc, is we still don't know.
Doc: Yeah, I wanna push you a little bit, or at least tell our audience that, when we started this thing 20 of these ago, we made the case – and I am sticking with that – that modeling is a worthy journey, but you have to really be careful about not anchoring to whatever it is you believed. You gotta continue to gather evidence, you gotta understand mechanism of action, you put all the science, the biology, you put it together. You – you know, you being an econometrics guy – and you start to run a model it, you gotta be careful that you just don't get stuck on it, 'cause you – you know, you're not trying to fit things in, stuff'em in a drawer when they don't fit. And I – anyway, I just wanna remind people that we're not trying to kind of say, "Ah, you know, it's complicated," except, we are. It's very complicated, as you'll find, today, that even the case counting is complicated.
We've talked about it before, the reporting of deaths is complicated. And worst of all, we're in a time, in our country's history, where it's really political, you know? I saw the state of California, they're talking about not opening anything, or one of the candidates or something, like, till after the election. And election has nothing to do with the science to a disease, and whether or not you can afford daycare so you can go to work. You know, the second Tuesday of November has nothing to do with biology, so…
Matt: Yeah, and I tend to get exhausted with politics, heading into every election, and, boy, I mean, just now, I just wish, you know, we could talk about this. You should see some of the – the e-mails we get are just – just look at this, you know, honestly. And, you know, we'll talk a little bit about just information out – and the way the information has moved throughout this pandemic. But if you have a viewpoint, if you're working on confirmation bias and you're saying, "Here's what I think. Let me find the studies," you can find the studies. Sometimes they're studies and sometimes they're studies. There is enough, out there, that is so confounding, and it's very hard to judge what's a good study and what's not, even for experts, sometimes.
Doc: I'll bet you, Matt, you could find a study that shows COVID didn't come from China, secret lab, working on bats, but came from outer space – I bet you could find one of those.
Matt: There are studies that posit both of those – let's see what we get to, today. All right, but the good news is: case count declining –
Doc: The good news is deaths are declining, right?
Matt: Yeah, good news is deaths are declining.
So, this second wave, if you wanna call it that – and we've talked about, you know, whether it's that, before – appears to be – has been much less deadly than the first. So, that's, undoubtedly, good news. But, you know, news is relative, you know, that's still almost 1,000 people a day, at this point, we know they're mostly older, their risks aren't the same for everybody. The total – I haven't even looked at the total, in a while, so, 185,000, you know –
Doc: I mean, wait a second, wait a second, Mr. Econometrics, you said 1,000 a day – this looks like 750.
Matt: I said under 1,000 a day, I said under 1,000 a day, so.
Doc: I didn't hear the "under" turn my aid up here. Hang on.
Matt: So, you know, good news is relative – at least things are headed in the right direction.
So, again, it's hard to tell what's doing this, but one of the theories – and I think, Doc, you mostly subscribe to this theory, but we'll – is that there's a natural path to a virus, it's – you can use the term "herd immunity," I think that's a little aggressive, but – as more people, you know, as more people have immunity, like, the transmissibility goes down. Whether you're at full herd immunity where you get below one is another thing. But –
Doc: I you're asking do I believe in a Gompertz curve, then, yes, the answer is yes.
Matt: Okay, sure, sure. So, you know, look, Florida and New York have, roughly, the same population, they're both about 20 million for New York State. And New York got the virus and it spiked and it went away. And, yes, there were lockdowns and masks and things and – but, you know, this is – people are out and doing things, now, and it hasn't really come back. And Florida kind of saw the same kind of curve, right? And then it came down, hopefully that keeps going down. So, yes, it does look like a natural path of a virus could be doing this, so, let's dig into that herd immunity, a little more.
If you wanna put the numbers together, Doc, you know, like, ballpark these with me.
So, let's say, especially in heavily affected areas, so, like, New York, for instance, 0 prevalence studies, which are blood tests to determine who has antibodies to the disease, are somewhere around 20%, right? Call it 15-20%?
Matt: And then, you know, there is T-cell immunity, which you've talked about, which is, essentially – I'm gonna oversimplify, but people who have had something similar to this, a similar, and so, maybe they are more immune already before COVID even came along. Again, oversimplification. So, add that in, so now you're talking 30 percent, maybe, of people – now, that's not quite herd immunity, but that's up there, that could slow the spread of a virus, okay? So, those are all points in favor of the herd immunity theory. Now, we all like to do both sides of things here, right? We like to look at disproving evidence.
So, Spain had a big surge. Spain –
Doc: Wait a second, go back to that slide before, because we first talked about this.
Matt: So, this is just a survey, and I just like the thought of people going, "Yeah, I'm pretty sure I had COVID." I don't know why that phrasing strikes me as funny, but – so, 14% say they're pretty sure they had COVID. And, you know, there's a lot of asymptomatic cases, so maybe, you know, they're – that's putting the number, again, around 20% or something like that.
Doc: I love the "some college or less," like, 4% had a positive test, they're right in the middle, there, and 11% were, like, "Pretty sure I had it."
Matt: Yeah. All right, so –
Doc: I mean, I actually have to confess, I'm probably one of those who'd be, like, "Yeah, I'm pretty sure I had it," but, you know, until I test, I won't know.
Matt: Yeah, well –
Doc: We'll talk about testing, in a minute.
Matt: Yeah, okay. So, let's see, okay, so, on the opposite side of the herd immunity argument, Spain had 20%t 0 prevalence; they were in the zone where they – it went away. They should've pretty much been in the clear, and they've had cases just absolutely surge, and there's not really a single explanation for it. So, if herd immunity, if we were on that path and we were getting there, this shouldn't have happened. Again, lots of confounding factors.
Doc: I think that even though this is a bad news chart, the good news, in Spain, is that the deaths haven't run up behind it, right? So that's good news.
Matt: Yes, absolutely, yeah, the deaths haven't trailed. Maybe it's late, but it's been a little while; they really haven't moved up at all, like, and if you give it a couple weeks' delay, it should be moving up. So maybe, you know, it could be younger people, it could be – obviously, better treatments are part of it, all over, so, at least that's some good news for Spain, at least, so far. And then, you know, herd immunity as an explanation for why case counts are down is one thing. Herd immunity as the strategy a country should pursue is another.
And again, I'm not here to judge, but this is what we're doing, and we've got 500 deaths per million, and most of the world has done a lot better.
Is that worth, I mean, whatever benefits we got? I mean, we didn't exactly – our economy didn't come soaring through this thing. But the other thing is the story's not over, right? So, you know, New Zealand is down to zero because they've been on a huge lockdown, but are they just delaying the inevitable, right? You can't be on lockdown forever, you know, they're probably waiting for a vaccine, we'll talk about that in a little bit. But, you know, that's the cost of herd immunity, and you can judge, you know, whether it's worth it or not.
Doc: And I might try to make the case softly. I don't wanna dive in on this slide, 'cause the next ones are gonna help me back-up some of the thought, here. But I have a suspicion that a good percentage of these, even though it's labeled "Confirmed COVID Deaths Per Million," that it's super high in some places, including the US, because there have been errors in test procedures, as well as incentives to label people with COVID-19 as the cause of death.
And there's political advantages to do that; if you're at the CDC, there's an advantage in having more attention to your stuff, if you can get more COVID deaths, 'cause now you gotta help save America. But we know that, from good European data, that a third of respiratory infections like this, they're coinfected with another respiratory infection that can also kill you. And we've not tested for those in the United States; we've really focused on COVID.
We also know that people who, coming in – you know, I think this is a little misleading and I think we should look at – we have, before, so it's not like you and I are arguing or disagreeing. We've looked at the excess deaths during periods, and less than normal deaths in last year, like, the 12 months leading up to, where older people have been talked about as being tinder, and they were more likely to die, and that's led to spike in deaths. But I suspect that this number is lower, and maybe, say, 400, and maybe Europe is a little higher because they're much more particular about their European infectious disease testing systems, in my opinion. But it still doesn't explain that it's still high and it's still something that we're sorting out. So, are you gonna let me go with that and dive into the testing thing?
Matt: Yeah, yeah, I mean, that's another just – and, you know, a more general thing, there's so much cross-border data, there's different measurement things, I mean, if people wanna talk about the numbers, there are so many questions, there, you gotta do a lot of work to dig into'em.
So, yeah, there's questions around everything, and if you have a model or a study, like, every input into that can be questioned in all sort of ways. And it's very difficult, but I think what people – I think what's important is to find the line between skepticism and cynicism, right? You should be skeptical, but I don't like it when people throw up their hands and say, "Ah, you know, all these numbers are fake. There's nothing we can know." I mean, you have to study what you can study, and just do it intelligently. So, speaking of numbers, right?
Doc: Yeah. So, this week, a story came out in the New York Times, and it was: "Your coronavirus test is positive, and maybe it shouldn't be." And what this relates to is this idea that, if you have a positive test and this test answers yes or no – you can go to the next one, if you want – that it's either a positive or negative answer. And you can get to positive in a certain methodology, which we'll talk about in just a second, and I'll share with you how it works.
But I'm gonna argue that the key is not whether it's positive or negative – and again, this is a datapoint, you decide – but it looks like and this New York Times story is making the hypothesis that maybe 85% to 90% of people who tested positive were carrying barely any virus, and, thus, very little risk of spreading it.
And I'll be truthful, that's about the first paragraph, in maybe a decade, that I've read in the New York Times that is right on, perfect, beautiful, great science, great thinking, a great statement. Because it's been the case that how much virus you have and infectious disease is how likely you are to die. How ramped up your immune system gets over a period of time is how likely you are to die. You've got acute respiratory distress syndrome, where your lung is really thin and your blood vessels, and if that breaks down acutely and quickly, you're gonna die. This is a study out of the Lancet, September 1st, and they looked at patients and confirmed that, yes, the viral load.
And how do you look at viral load? Well, we'll get to that in a second, but amount of virus that you're exposed to and have relates to your probability of death. And for people that don't believe me or think I'm nuts, think about HIV: HIV was a disease and now is managed almost as a chronic disease, where, they measure viral load to see how risky you are to spread the disease, or were, and then how well the drug therapies are working. And there are people like Magic Johnson, who's had zero viral load for decades. That is the point: if you have low viral load, both exposure and in your body, you are less likely to spread it, and less likely to have symptoms, and less likely to get sick and die.
So, what I wanna show you is, this test that they were doing that gives you a yes or no answer. And just relax, it's a picture, it's not complicated. But they take a strand of DNA, they heat it up so it kind of unwinds, but the pairs, the little steps, stay together. And then they start to cool it down and add some things that are called primers, that fill in the other half of the DNA strands, as they're cooling, use some enzymes, and all of a sudden, you get two strands of DNA, all right? So you started with one, and you do this breakdown, and now you have two.
And then what happens is if – this is a cycle. And so, you can imagine, if you do it once, you get two, if you do it twice, you'll have 4, then 8, then 16, and how many times you cycle determines how many you're left with at the end. And so, you can imagine, if you do it 20, 30 times, you're gonna get 1,000, 10,000, 100,000, a million copies, right? Well, you look at this on a – it's called a gel, maybe people have heard about, and when you see it and it shows up and it lights up, you're, like, "Bingo, I'm positive." You have enough DNA, you have that disease. But tests around the United States, some places were cycling 25 times, some were cycling 40 times, some were cycling 35, some were cycling 30. And that determines how much shows up.
So – and just bear with me – people who do this for a living and science know that, really, kind of the sweet spot to get kind of the correct connection to how much you started with, to standardize it, is around 25 to 30 cycles. You can see 35, here, it says almost half the tests are positive – at 30 cycles, which is probably the max that anyone should've been doing, 63% of these positive tests would no longer be positive. It would mean that those people would, even though on the 31st cycle and the 32nd cycle they would still be positive, they're not positive. They're not positive because they had such a low load, which makes them asymptomatic and likely non-spreading.
This is something I have shared, Matt, you and I have talked about this for months, now, and finally, in the New York Times, like, who knew, I was excited to see that.
So, the problem is the PCR test, the problem is that – so I guess I want people to be aware that, when you look at this next chart that we show you about confirmed cases, that, if you test enough people and you run your PCR too many times, you're gonna get as many positive cases as you want, or need.
I'm not guessing about intentionality, but I am talking about science, and then having science that Matt can plug in and model, and we can put together and say, "This is true. This is true. This is not true. This is what's affecting this and that." So, is that too much, Matt, have I babbled on?
Matt: No, no, I mean, it's interesting and it's a lot to think about. Because in my mind, I think – so, you know, when you choose your cycles, you're choosing how powerful your test is. But you still – and so, you can take someone with a low load and in an asymptomatic case, and you can do more work to find out if they're positive. But I don't know if that's the same as turning a negative into a positive.
Doc: Fair enough, sure.
Doc: Well, except, if you – and that' was the point, originally, with these German guys, when they started testing in China, in February, the German guys said, "Hey, here's the gold standard. Do it," and I think they said, like, "Cycle it 22 times. This is where we know that the DNA hasn't reannealed incorrectly. It's true virus. It's been tested against virus that's been grown in a lab virus. Off you go." And now we know that people are, like, "Well, let's just keep cranking it. How many times should we do it?" you hire, you know, a new biology undergrad to come out – I mean, like, it's – yes, the virus was there, but I would just, I would say, and maybe you don't wanna believe me, but if I give you 100 virus particles and put'em in your nose right now, you're not gonna get sick.
And you might have sniffles, but you're gonna generate immunity, assuming your immune system is operating. And you would be positive for coronavirus. But should I restrict your liberties? Should you be staying at home? Should you go and see grandma? I would say it doesn't matter: you're not gonna spread that, and your immune system's gonna get rid of it. Does that make sense? Like, you had it – and this idea, this fear, this panic was, like, "Oh, my god, people who are asymptomatic all over the place are gonna spread it." Like, that would be the first bug that I've ever heard of and know of that that's gonna happen.
It depends on viral load, and by the way, the human body works is, when you have a high viral load, you react to it. When you have a low viral load, you don't react to it. Like – does that make sense?
Matt: Yeah, yeah. And then, I don't know if you know this. Is there a standard way to know the cycle standards across countries? Is that, like, a number you could find?
Doc: I mean, this is people like Thermo Fisher who does some of the sort of major cycling machines in labs, you know, they have a curve where they show you the optimal place to – and really, to find specific DNA for diseases like a gene, like, you wanna go to only 10 or 12 cycles. Because the more you cycle, you know – a long time ago, early on in this, I remember the guy whose lab I was working was, like, "You know, Dave, if you cycle this, you know, 60-70 times – " which we were laughing about, 'cause you'd run out of – you know, you'd have to keep adding chemicals into the system to do it. But, you know, you could pull in any amount of DNA from anybody that had ever walked in the building, like, its' floating in the air, it's floating in the machine, it's, you know, it – you can get any result you want was sort of, I remember it being implied.
But, yeah, there are standards for in-a-lab science, and it's, you know, up to 25-30, you're talking a place where you get garbage after that. Garbage meaning that it doesn't distinguish between useable information versus a signal that, you know?
Matt: Yeah. One other question, then we'll move on. Do you know, if you get a positive test, can you find out how many cycles was done on your sample?
Doc: I would seriously doubt it, yeah, I would seriously doubt that.
Matt: Okay, interesting, yeah, this is definitely – I wasn't familiar with this particular stuff, but – okay, we've got some T-cells in here.
Doc: Yeah, so, this – we showed this last time, so, a couple weeks back, and I wanna put it in again, just to point out the knowledge and the information that's coming at us. 'Cause I hadn't really even thought about it, truthfully, but the immune system is not just antibodies. So, what we know, now, is we've taken virus particles and tested for it; that's the PCR. Everyone knows there was a question of, like, okay, how do you know that you've got immunity? Well, you test for antibodies. And antibodies are relatively easy and relatively inexpensive to test for, especially relative to T-cells. And so, here are these – this is a chart showing five different points from five different blood samples from groups of people, and it shows what we consider are T-cell memory cells.
So, these are T-cells that are sitting there, sentries on-guard with their missile launchers, their tanks, their guns, ready to go after SARS-CoV-2, specific antigens, like, they're ready to go. And you can see, in 2019, a bunch of blood donors, about 20% of T-cells in these blood donors were ramped up and ready to go to SARS-CoV-2. Now, how could that be? Well, you might remember that part of the SARS-CoV and the coronaviruses have parts that are similar to each other, and that's what this is from. So, you know, that's good news, I'm happy, that suggests that I probably have 20% of the population can react with their T-cells to COVID, and maybe clear it.
And then, in 2020, about the same number of people had antibodies already to it. And this is not exposed, as far as we know, and then, you can see even T-cells, in the 2020 blood donors, had been exposed. And these are people that, you know, report on this in the study that, no, they had no infection, hadn't got it, no, don't have any record of it. So it suggests, to me, the immune system in humans is working. And I don't wanna bore you, but you can see exposed, mild, and severe, and this stuff goes up. So, if you're even mildly exposed, you've got tons of antibodies, and you've got T-cells, and they're ramped up, ready to go, ready to clear this thing, whew, fantastic.
Matt: Yeah, and the central takeaway from the T-cell is that it's another step towards herd immunity, that we can sort of add on to what we think – and of people who have already been infected, there's a certain percentage of people who are immune, already, so it gets us a little further down that path.
Doc: Yeah, and the next slide is gonna show that – I have good faith in the science we're seeing, I have good faith, now, in what we just talked about and shared, and the human immune system, and herd immunity, it's happening, it's growing, it's great. But this thing came out, this week, in the New York Times, and I just, I wanted to cringe, because it – it says: "And even if the viruses don't change significantly, immunity against them gradually wanes and may be all gone by the next flu season." Well, gradually wanes between now and the next flu season is nonsense. Even if the viruses don't change significantly – I don't know what they're talking about – the point is, once you get this immunity, you can see that in the last chart, in 2019, a year later, these people had T-cell immunity from the year before, on a – not the exact same virus.
So, you get immunity, you get antibodies, this stuff lasts for a long time. Think of when your doctor says, at ten years, "Have you had a tetanus shot in the last ten years?" you get a booster. Yes, we know that tetanus wanes over time: some people still have it at ten years, some people lose it at eight. This is nonsense. This would mean vaccines wouldn't work. The whole idea of vaccines is to give you immunity that lasts for a long time. This is nonsense. New York Times science writer, fail.
Matt: All right, so the other thing we wanna check in on is just the mortality rate. You know, this – we're kind of recapping where we've gone over this whole five months, whatever it is. At the start, it looked quite deadly, right? You know, the numbers out of China and the numbers out of Italy were high, five percent, something like that, there's a lot of, you know – and since then, we've learned more about how many people had it, we've got better treatments, hospitals haven't overloaded. So, it's undoubtedly not as deadly as first thought, so that's good. On the other hand, it is, you know, 185,000 people have died, it is deadly, and there's often this argument, "Oh, it's the same as influenza," and then people argue if it's not or it is.
And I think that framing is completely unhelpful; there's no need for analogy, here. We can judge this and people can make decisions on what to do based on its own thing. But just to recap to where the numbers are converging, right? This is how science goes: we have a guess, we get more information, we get closer and closer to the right answer. So, case fatality rate, which is the number of known cases, how many of those die is two to three percent. And if you wanna compare it to influenza, that's pretty similar, okay?
The infection fatality rate, which is sort of an unknown number, right, this is how many people get it, how many people get it, and how many of those die. So, these might be people who never get tested or never go to the doctor, so there's some estimation going on to find that. Now, we're finding that through zero prevalence and all sorts of other things, so the infection fatality rate of COVID is about 6.5%. Again, I'm sure you'll –
Matt: Zero point – about a half percent, a little more than a half percent. And that number is gonna change, but we're in the ballpark, now, right? It may go down a bit, probably not gonna go up, I would think, but we're in the ballpark. And if you wanna compare that to influenza, simple comparison: it is about six times as deadly as the flu. Again, I think that's an unhelpful framing, they are not the same, it's a novel virus which means it's a completely different scenario, so even if it was the same, you know, it's not. Even if those mortality rates were the same, you're gonna have a lot of dead people this year, and what you can do about that is your own decision.
So, but this is kind of the summary of where we're at now, as very little BS or bias as possible. What do you think, Doc, would you agree with these numbers?
Doc: Yeah, I think, for the sake of not getting me off on a tangent again, it's – yes, I'm fine with them. I think the point really is, for the CFR, the case fatality rate, it's about the same, and for the IFR, it's more deadly. And, you know, these are subtleties and nuances that we could talk about, but I – yeah, I'm fine with leaving it up here and saying some stuff is similar and some stuff is different, and we can go on. Like, I don't – helpful at all, yeah.
Matt: Yeah, yeah, no, no, I think so. I just wanted to give you a chance to alter these or shade these a little bit, if you wanted to. But I think most reasonable researchers would agree that these are – we're in the ballpark, here, okay? They're not perfect, but that's what we're looking at, that's kind of – okay. So, out there in the world, interest in coronavirus is fading a bit, people are tired of this, it seems like the election's a bigger news story – we'll actually have some charts on that in a little bit. We're kind of all living with this, everybody has got a very different experience, but it's not – you know, things are just changing, right, we're moving on.
Further into the information of the coronavirus era, you know, I think this has been a real indictment of both the media, of both government communication, in this particular case, and you used to be able to sort of retreat to the scientific studies, if you wanted some real information.
And, you know, we've talked about preprints, before, and obviously, you know, these things aren't going through peer review because there's a need for faster information, and so people are jumping on things. But also, I mean, you can go into these studies and find, you know, "This one was retracted. This is how 5G induces coronavirus in skin cells," which is – I don't wanna say impossible, but it's impossible, I mean, that's just, that's nonsense.
This study just came out, I think – I don't see a date, here, but I think this is new – and this is a theory that coronavirus came on an asteroid, or I guess a meteorite would be the correct term. And again, never say never, but I'll say never on that one. So –
Doc: Maybe it came from Area 51.
Matt: Maybe it did, maybe it did. It's just been a wild time, and, you know, between misinformation on social media and all these things, it's just a real indictment of the information age. And I think – you know, there'll be a lot of lasting legacies on this, but I think an examination of this is gonna be really one of them.
And that leads into vaccines, so, quick check-in on vaccine progress. We spent a lot of time on this in the last talk, progress being made; timelines sound too optimistic to us, but you can always get lucky. But it's probably gonna be a while.
I did see a deep-dive on vaccines, and one of the bright points of this is that, I think the development pipeline, there's a lot of learning, there's a lot of new technology happening, there, and that if we're unlucky enough that the next global pandemic is soon, I mean, we've learned a lot and we've got a much better system, now. And I saw one compare it to, you know, like, aircraft design after World War II, it went from, like, you know, pencils and paper to, like, "We can put together a real flying machine, like, because we had to." So that might be a little bit of upside, but I don't know how much it helps us, the current vaccine.
But back to information, you know, if people don't take a vaccine, it's not gonna help us, and trust in vaccines is declining. And this, interestingly to me, I think, goes across the political spectrum, right? I think, traditionally, maybe the right was less trustful of science, but there was also an antivax movement which was a little bit more on the liberal side, previous to all this. But now, because of the way things are being rushed and because of the less distrust in this administration, now people are worried that what comes out is not gonna be safe. So basically, the number of people who are excited to take this vaccine has gone from 65% down to, call it, 50-48%, in only a few months.
So, if a vaccine was gonna save us, you know, and the science is saying it's gonna take a while, you know, it's gonna take even longer if people don't take it. And that might be the correct decision – I'm not gonna judge that.
Doc: Right. And, you know, I would point out, I'm not an antivaxxer, as people know, but I am a cautious science guy that knows of and makes a living of reporting nonsense that institutions come up with and do to rip off regular folk. You know, I mean, there's a history of things, with the CDC, on Agent Orange. There's some question, now, about their delays for probably 15 years in the mercury, when they had the data in Scandinavia but hid it from the CDC, even though the CDC was sending money over there to a guy that, you know, was buying Harley Davidsons and Porsches and – and, you know, this stuff comes out. We know there's risk with vaccine under Gerry Ford, where we saw this increase in Guillain-Barre syndrome, which is so rare that it suddenly made its way into textbooks in the next couple years, related to as a problem that can happen with vaccines.
Now, not everyone got that Guillain-Barre syndrome, which can lead to paralytic lungs and put you on a breathing machine and – we know, I mean, there's – you can see how vaccines have helped, we've shown these, before, with measles and smallpox. So, yeah, I can see how people would be worried and nervous, especially, again, to go back to the beginning, it's so political. Like, you don't know who to believe about anything, anymore, and it's just, like, "Ack." So, we're looking into this, we're following this stuff, we look at the science, I think there's enough eyeballs on it and enough transparency that's going to happen in the last phases, that I think we should be fine.
But, you know, if you told me you hadn't tested it on some primates, nonhuman, and then now you show that you've tested it on human and it's safe, I'm much more interested in that. Yeah, should we move on to the?
Matt: Yeah, yeah, let's move on. Yeah, so, economy, the big story, here, is still the same, you know, we had a nice recovery – this is an activity index that combines sort of a bunch of things and across countries – decline, resurgence, and then we just can't get back up to this 100, right? We're stuck here at 60 – this white line that's buried in here is the U.S., but it's a lot the same. So, look recovery, flat – we can't seem to get back to those higher levels. And a lot of businesses sort of need that last amount of revenue, that full capacity, to really work – I'm sure we'll talk about that, in a minute.
This is credit card spending, just kind of the same story, with different dataset, you know, still can't get up to that thing, that top level, here.
And this is by state, same data by incomes. And, you know, low income is kind of back to where they were, because a lot of their spending is maybe more required than high income who can put things off that are nonessential. But still not getting up that last bit –
Doc: Oo, which, what you just said there makes me even more excited for your pick in Income Intelligence. I love it.
Matt: Yeah, if you subscribe to Income Intelligence, it'll be coming out about the same exact time as this e-mail. But let's just say there's a lot of room for growth in these high-income customers to start buying something they've been putting off. Okay.
Okay, here's a little bit of – I won't get too far into this, 'cause we're going pretty long – just a little bit of silver lining. This is an estimate of GDP that's more rapid than the actual measures of GDP, which take a long time. That shows a little bit of an upsurge. This is a pretty good measure, it's not perfect, and that's higher than the consensus, so that's a bit of good news.
Sort of, in the same way, there's a few unknowns left with the virus, stuff reopening in the winter, the winter season coming, the seasonality of it may be a risk for a resurgence – we don't know. The kind of risk on the economic side is, now, the stimulus – a lot of the stimulus has run out, the extra unemployment checks have run out, and we don't know exactly how big an effect that's gonna have. This is those super forecasters – I just needed a chart to show that stimulus has really run off the rails. It was very likely a while ago, and now it seems to be a lot less likely.
And we don't know what that's gonna do to the economy. It's obviously, you know, it's obviously gonna hurt people. You know, we talked, last time, how –
Doc: Matt, it's time to get your pied-a-terre in New York City.
Matt: I think I'll be all right, for a while. That'd be you who's gonna get one, Doc, so.
Matt: We talked, last time, about how, despite people struggling with rent, evictions hadn't stepped up, and maybe, you know, landlords were delaying it or they were working things out. It looks – some of the numbers I've seen show that that is not the case, anymore; evictions are starting to trend up. That's partially because, probably, these unemployment benefits have run out and people are just ready to, you know, start collecting rent again. So this is the change in rental listings, they have gone up a lot, and just some numbers, not charts, that show that evictions have gone up.
Small businessowners – this was interesting, Doc – you know, we were closed down and nobody knew what was gonna happen, and then things started opening, May, June, July, August. And now we're kind of in this equilibrium where people are doing stuff, not everything, but, you know, life's a little more normal – no concerts, but, yes, restaurants, things like that. But still, small businessowners who think their business will survive, that number is on the decline over – even during this reopening. You'd think there'd be more visibility, you'd think people have a greater grasp on what's happening, but it's actually getting more uncertain for small businessowners, which is worrisome.
Doc: Reality sort of easily smashes hope against the rocks.
Matt: Yeah, exactly.
Doc: Well, I love this chart – this is showing zombie companies. These are companies where their profits are less than the interest they paid on their debts, for at least three years. And this makes me nervous – does it make you nervous, as well? I mean, we're approaching the dot-com days, where you can't – like, whatever you're making doesn't even pay your interest cost. With low interest, do you think it's – do you think the can will be kicked down the road, or do you think this is important?
Matt: Yeah, it depends on credit conditions. I mean, a zombie company is sort of a company that has no business doing business, unless someone's willing to give'em money to keep going. So, if credit conditions improve, you know, these things can go on for a while, but, you know, that's a high number, almost 15% of the Russell 3000. You know, so, I would say a third of those are not gonna get through. I'm not gonna say all of them are gonna go under, but, yeah, that's worrisome. And some of those are big companies.
All right, this is kind of a complicated chart – I'll do a quick version of it. This shows credit spreads, this shows the risk associated with corporate bonds, and it's surged and it's kind of back to normal. So, people are buying corporate bonds and are getting sort of normal interest rates, even though we're in a sort of tumultuous time. And you can see, over here, this is the spread between, like, this black line is normal times, how big the spread between good investment grade bonds and bad investment grade bonds are, right? So, if this spread is wide, that means people are looking at bonds and saying, "This one's good and this one's bad."
But these spreads have contracted, the range has contracted, and to me, that says people are buying bonds sort of indiscriminately, and this has driven it, you know, by interest rates and the liquidity out there, and not by people judging the credit risk of these particular bonds. So, that's worrisome, you know, this is gonna go back to this, and that means some bonds are gonna tank and go up to these higher spread levels. So, the credit market looks too complacent, to me, right now.
And we've talked about how value has underperformed growth, for a long time; we've been talking about this through this series, and it's reached new lows. So, even though I keep going, "It's gotta turn around. It's gotta turn around," just keeps getting worse for value investors.
Doc: I think I'll increase my purchases in my –
Matt: On value stocks.
Doc: – value funds, yeah.
All right, this is just showing that tech stocks – this is something that we have looked at before, and just to kind of get a flavor, again, going back to the dot-com days, price to sales and price to book, we're getting up there, getting up in places that are frightening to us.
In option land, people have been – this is a ratio, so, puts have been decreasing relative to calls, and we think this is due to incredible speculation. Just buy a call option, have the stocks run up and make tons and tons of money, when it gets to – this is an extreme – I've seen extremes, this is an extreme – and then put the call ratio for tech.
So, that's got me nervous in, really, this sector and section of the stock market that is held things up and taking stuff to, you know, new highs and being positive for the year, so, that makes me nervous.
Matt: Yeah. And then, this is another bit of evidence from the option market – these are term structures on protection on some of these things. So let me – we'll just look at the VIX one, and then you can see how they're all in extreme. So, this is the difference between buying protection on stocks two months out and one month out. Now, normally, they're kind of similar, right? You know, there's not a lot different from what's gonna happen two months from now from one month from now, but you can see the price, this has gone way up.
It's way out of range of anything, and you see the same thing on – this is on foreign currencies, this is on credit, and this is on interest rates. So, people are worried about something coming up soon, and that thing is – up here – it's the election, or it's at least the time of the election. So, this hasn't been this extreme in past elections, hasn't been this extreme for five years, so, you know, we're talking about COVID, but right now the market is paying a lot for protection from whatever is gonna happen in this election. It could be – I mean, well, let's not get into what it could be, I mean, people know enough about the election. You can't avoid news on it anyway. But this is what's roiling or prepared to roil financial markets right now.
Doc: Well, this slide just kind of shows us that, hey, September, we're halfway through it, but, you know, watch out, keep your wits about you, because this is a month that, on average, for a long, long, long time, 92 years, 93 years, has been a negative one. And I just – it's fun to look at this and contemplate, think, be aware.
Matt: Yeah. All right, and this our bright spot – I'm gonna run through this quick. So, despite, you know, these terrible times, I'm an eternal optimist. Doc, you're a little – I don't know if you'd call yourself the same thing, but on certain things you are. You're sort of a financial pessimist on the markets, with debt. Anyway, I'm already off-track, and I said I was gonna do this quickly – all right, so let's get back to this. Look, these are reported deaths per 1,000 person, in New York City, from 1800 to 1930. So, this here was the terrible, terrible influenza pandemic of 1918.
And at that time – you know, so after that, though, you know, deaths about 10 per 100,000, in New York City. So, look, we're at a scary time, we're in a pandemic, people are dying, economy's bad, but, look, this is still one of the best times, you know, in the world. So, let's say we wanted to draw this line out to right now, okay? We don't even talk about deaths per 1,000, anymore. We talk about deaths per 100,000, right? So, if you take this 700 per 100,000, if you were to chart this out just normal times, this would get you down to 7, right? So, the deaths per 1,000, the mortality of people in New York City – and by extension, you know, the United States – has just been a decline, just been declining, declining.
And if you add in New York City's coronavirus deaths, COVID deaths, you put two back on top of that. So, yeah, it's just gone down, down, down, and a little blip. This is back-of-the-envelope, I just kind of put this together, this morning, but just trying to get a bit of perspective that, you know, this will end. We're still in a wonderful time for science and medicine and – maybe not politics.
Doc: You were reading this week.
Matt: I was, of course I was, I was, I was doing my own research off Factfulness, which is a book that Doc loves, by Hans Rosling. You know, people can look it up, it's – maybe we'll put a link below, in the transcript, but – so that's all I got, a little bit of optimism.
Doc: All right, and now I wanna be a shill for the Health & Wealth Bulletin, and just remind people that Matt and I, here, on August 19th, we talked about – well, in the Health & Wealth Bulletin, we wrote about this and we put it out there August 19th: it's time to get conservative on stocks.
We talked about warning signs, we had that little blip and scare September 2nd, we said the same thing: it's time to get a little bit more bearish.
We're not trying to predict market moves, per se, but I'm just letting people know that, in the Health & Wealth Bulletin, which is our free daily, you could share kind of how we think about stuff and look at stuff.
And it's out there, and we publish this for free, so, please help us get stuff out there in your social networks. We'd love to have people experience our stuff, because we make our money when we convince you to subscribe and get our, really, content that we're devoted to.
So, we've been sharing with you, this is our 20th COVID, this has been fun – Matt, I've enjoyed it. And I think the next time, we're probably gonna do a COVID conversation, again, at our alliance meeting in October, first week in October, where we'll be live doing that together, in Baltimore. So, look forward to that. Anything else from you?
Matt: No, that's it for me, Doc.
Doc: Thanks, everybody.