In absolute number terms it's more deaths in total in the USA than the Spanish Flu (675k deaths total since it began), HIV (700k deaths total since it began) or any other pandemic. Population has increased so the US did lose a smaller percentage of population but on the other hand Spanish Flu didn't have a vaccine to stop it one year in. Hopefully enough of the population takes the vaccine now to stop this.
Note this also means COVID has been the number 1 cause of fatalities in total. The other top killers are heart disease and cancer. Heart disease kills ~660k a year and cancer 600k a year. We're not that much over 1 year now since the first cases in the USA. This means that COVID is absolute top cause of fatalities at the moment. For anyone that may feel the need to mention car crashes, guns or drugs those don't even rank in the top 10 of fatalities in the USA.
Something to consider if you see anyone trying to downplay this.
Also, during the influenza of 1918 there wasn’t widespread availability of oxygen. If we were still at that level of technology there would be significantly higher mortality. You can see a bit of this play out in India where people are dying who shouldn’t be.
Both HIV and the Spanish Flu killed young people with most of their lives ahead of them. All early loss of life is tragic, but the number of deaths alone isn't the only measure.
If you calculate the loss of lifespan, HIV would blow Covid out of the water, because the median age at death would mean ~40 or 50 years of life lost. Covid's median age at death is so high, it's often above a country's life expectancy.
It's also worth noting the US population has more than tripled since 1918 and grown by a third since 1990.
This isn't meant to downplay Covid's impact, but to make a more nuanced comparison with past pandemics.
It was #3 in 2020 even though widespread testing only started in March. Seriously frightening stuff. Imagine if we went from zero heart disease or zero cancer deaths to present numbers in the span of one year...
Heart disease and cancer aren't even singular diseases.
Hell, even the Flu is a combination of diseases: TypeA, TypeC, etc. etc. Even Flu-TypeA is a combination of different diseases: H3N2 (Bird Flu) and H1N1 (Swine Flu) are both Flu-TypeA.
For a singular disease + minor mutations (COVID19 vs B.1.1.7 vs P.1 extremely similar and covered by the same vaccine) to cause such a death count is pretty remarkable.
>Something to consider if you see anyone trying to downplay this.
Most of the downplaying I've seen has revolved around the idea that those who died would have, "died anyway" from some other ailment or that hospitals are finding any reason they can to attribute deaths to covid.
So, while you have a great argument, I doubt you'll change any minds because those who disagree flat out reject your premise.
>you can cite them numbers of average years of life lost per covid death
That's practically inviting them to cite back the average life lost from the 1918 flu. If you're trying to counter someone who's downplaying Covid that is probably not something you should invite them to do.
That's fine though. If they point out that COVID is merely in the same order of magnitude but not objectively worse than Spanish Flu then the point that COVID should not be downplayed has been won.
I believe there are a significant amount of these people that won't actually argue that just because the Spanish flu was worse in this way that the Covid pandemic isn't a problem.
As the other poster said, if that's the argument you're resorting to, I would say you've already lost.
I've found it is helpful to count by equivalent number of deaths to something that the person has actually experienced, as it is way too easy to brush away deaths that occurred in 1918.
For instance, it's as if you took the number of years of life lost in 9/11 and multiplied it by 120.
Is the point here to argue that the Spanish Flu was worse? Yes, it was. But I think someone crying, "This is the worst pandemic in 100 years", sounds like they are pretty on the money.
I believe the counterargument is to that what is worse, 1/15 of the population losing 15 years or the entire population losing 1 year keeping in mind that 1 year in your prime is probably worth more than 1 year in your old age. These numbers are not COVID specific, just going off your ~15.
For COVID numbers, even with 1M deaths, that would be 1/330 (US population) losing on average ~15 years vs. everyone losing almost 2 years now. It's emotionally tough to pick a policy when you are condemning one group to statistical death, but you still have to try and be objective. My personal opinion is that we'll be writing books about the "the lost generation" in 10 years about children currently in school.
1. The current death toll is with the existing lockdowns. There are good reasons to think that without (especially the early) lockdowns the death toll could have been way higher.
2. Being dead for 1 year cannot be equivalently compared to being socially distant for 1 year (not 2). Is that not obvious?
3. This is before we get into life long disability, etc. due to covid. I know someone whose parent had a covid caused stroke, essentially ending their existence as the person they were before.
Correct, all valid points. But we can assign numbers to all these things and the error bars are sufficiently large that there is ample room for debate. As for 2. is it obvious? My niece doesn't know that there are other humans like her, I would gladly take a year at the end of my life to give that gift to her. Given the current vaccination rates, many people will not see normal until 2022. For 3. it cuts both ways, how many new alcoholic parents and child abuse that ruins an entire lifetime?
> is it obvious? My niece doesn't know that there are other humans like her, I would gladly take a year at the end of my life to give that gift to her.
I'm not sure she is going to agree with you when she visits you toward the end of your life.
> For 3. it cuts both ways, how many new alcoholic parents and child abuse that ruins an entire lifetime?
It's far from obvious what the effects of COVID-19 are on child abuse. The data is hard to disaggregate because there are so many conflicting factors, but there isn't obvious reason to believe that child abuse is up during the pandemic given the data we have seen: https://www.ucsf.edu/news/2021/03/419961/child-abuse-surges-...
> The data is hard to disaggregate because there are so many conflicting factors
Basically sums up COVID policies. The point remains, I have yet to see any clear objective policy making that even tries to estimate impact on life of all citizens. In absence of anything resembling a consideration of all age groups, I just ignore any opinion of lockdown both for and against.
Important to keep in mind about the YLL numbers I cited: most of the YLL comes from younger people who died early, even though most of the deaths are among people 70+.
So if you are going by this "differential quality of different years" argument, you have to account for the fact that most of these years actually aren't for really old people.
Right, but given all the debate about COVID, we still don't have a number and agree a 1-to-1 is ridiculous. Policy makers need a number to convert lost time to death time. What are they using? It seems one side is using infinite and the other side is using 1-to-1. As with everything, the answer probably is probably somewhere in between the extremes.
I don't think one side is using infinity. The issue here is that lockdowns, if done effectively, don't have to last for a full year. Look at Australia. Look at New Zealand. They managed to lock down for substantially less than a year, get the disease under control, and resume life mostly as normal. The US was not, but that also needs to be included in the tradeoff. It wasn't obvious that applying enough pressure wouldn't have prevented the uncontrolled explosion that we now have to deal with.
I don't know how people compare two isolated islands that are multi hour flights to any other nation to the USA with a straight face. Think of the backlash at even proposing locking the Mexico border. Also, Australia and New Zealand just broke their travel bubble, I don't know if that still constitutes as a "short lockdown" if you haven't been allowed to leave your country the entire time.
> It wasn't obvious that applying enough pressure wouldn't have prevented the uncontrolled explosion that we now have to deal with.
I'm not sure exactly what you're saying here, but I think we agree. Nothing about this pandemic has been obvious.
> I don't know how people compare two isolated islands that are multi hour flights to any other nation to the USA with a straight face. Think of the backlash at even proposing locking the Mexico border.
Very little of our COVID infections have been linked to either of the geographic borders in this country. While I understand there are greater risks with those borders, it doesn't make the situation incomparable.
> Also, Australia and New Zealand just broke their travel bubble, I don't know if that still constitutes as a "short lockdown" if you haven't been allowed to leave your country the entire time.
Bars and restaurants and sports have been available the whole time. Even if there wasn't a travel ban from the country, where would people even go? Most other countries aren't allowing visitors.
I'm not sure how easy it'd be to link Covid infections to the Mexican border - they were having serious trouble even reporting accurate Covid death numbers, never mind anything more useful: https://news.sky.com/story/covid-19-mexico-underreported-cor... The Covid outbreak there was really bad and would no doubt have screwed the US if something else hadn't earlier. Though it does look like the immediate source of US infections was an unfortunately large amount of travel from a global epicenter of infections which was somehow reporting zero cases at the time. (Something went really wrong in Italy, and the English-language media has completely failed to examine what happened there - probably because their leader is a boring technocrat these days.)
Except we didn't lose a year. A lot of us actually kind of liked the last year. Many got to work from home and discovered it was a lot less stressful than commuting into an office every day, for example. I have a feeling that some of us are going to recall the last year with a bit of nostalgia in the future.
That isn't true. The parent comment said the "entire population" lost a year of their lives. K-12 students are about 17% of the US population, not all of it.
In my urban school district, areas with the largest concentration of poor students are the ones that most strongly support continued distance learning. Affluent + white families are the ones most opposed.
> keeping in mind that 1 year in your prime is probably worth more than 1 year in your old age.
I keep seeing statements like this, and I must disagree. My mom's retired, nearly 80, and having an absolute blast living her life. At her prime, she was the primary wage-earner, had two kids, and never had a moment to herself. Her quality of life now is much better than when she was "in her prime". She's got a bunch of friends in the same boat.
The studies that I've seen on years of life lost per COVID-19 death all appeared to suffer from co-morbidity bias, particularly around obesity and related metabolic disorders. We know those conditions seriously increase the risk of COVID-19 death.
So the actual average YLL is probably a little less than 15.
I don't blame the researchers for this bias. The detailed data to correct for it generally isn't available so they're doing their best with what they have.
I think it's kind of unlucky in some ways that Covid affected the old/unhealthy so disproportionately. I feel like we would have responded in a much more assertive and effective way had that not been the case. More people who were not in the risk groups would (ironically) have been saved, and we'd be a lot further on the road to recovery.
Not a lot of young people know a huge amount of people in the risk groups, it's easy to dismiss if it hasn't affected someone you know.
This seems obvious though; a lot of people assert that Covid isn't "that serious" - if it affected a larger swath of the population with more consistently negative outcomes, of course they would have taken it more seriously and responded more in line with that. I feel like that was their entire point?
Our surprisingly-terrible reaction to COVID, due to the reasons cited in this thread, made me think of an (I think) interesting book/show plot.
What if there was an epidemic virus, that, within a year +/- a few months of contraction, killed hosts over the age of X (20, 50, 70), regardless of underlying health conditions.
It raises some interesting questions! The three I’ve come up with so far:
(1) what does a society look like, without (mature, older, very old) people? What surprising positive and negative evolutions occur?
(2) how would our current societies react to the gradual onset and eventual global expansion of such a disease?
(3) if we found a cure for the disease a few (now, shorter than previously) generations later, who would take it?
It’s kind of similar Lord of the Flies, except instead of a shipwreck, it’s a disease and it happens gradually, to preexisting societies and cultures.
Set X to 30, and make the cause of death deceptive euthanasia, and you've got the movie "Logan's Run" [1]. Make X 21 and you've got the book "Logan's Run" [2].
You give us too much credit. Hold the size of the problem constant and spread the effects to more demographics. I guarantee there would have been a bigger response. We’re not that rational.
I didn't necessarily mean a bigger death count, just a more equally distributed one (like the Spanish flu). I think the end outcome could have been better for all demographics, and the world would be further on the road to recovery.
With Covid it was easy people to think it wasn't really a big deal, it reduced the appetite and compliance necessary to keep the pandemic contained.
"Most of the downplaying I've seen has revolved around the idea that those who died would have, "died anyway" from some other ailment or that hospitals are finding any reason they can to attribute deaths to covid."
The authors of this are doing exactly the same thing, but from the other direction:
> Given that there is insufficient evidence to estimate these contributions to excess mortality, for now we assume that total COVID-19 deaths equal excess mortality. For the reasons presented in this section, we believe that this is likely an underestimate.
This is all simply noise. The way we'll find out the answer to this question is when someone pulls the death certificates for 2020, and actually tabulates the percentage directly caused by Covid.
No, because without tests, doctors didn’t uniformly attribute deaths correctly to covid, and often the official causes of death even in cases of cancer are often “pneumonia” or sepsis, or organ failure — the literal thing that killed them at the moment of death, not the cause of the symptom that overwhelmed the body.
You are making an assumption that all (or even just the majority) of excess deaths are because of this.
Moreover, we know that there are examples of the opposite: deaths where Covid was on the certificate as a contributing factor, but not the primary cause. These aren't hard to find.
An 85 year-old with congestive heart failure and late-stage cancer and Covid reflects the modal situation here. It isn't some theoretical event -- it's incredibly common.
Right, and those happen at a pretty regular rate every year. If we suddenly have 50k+ more congestive heart failure cases, or 50k less, we can tell that in the statistics.
Well, sure. It will be good to get the actual data, and then we'll know.
Right now, what we have is aggregate death counts (which we know are high), and people speculating that they're elevated because of Covid (or in this case, making models based on speculation).
The problem is that there are financial implications for a state saying they have covid deaths. From some of US covid relief packages, the more covid deaths a state had, the more money they get.
As well, you get the over-the-top cases where someone that dies of a gunshot is included in the covid death count[0].
Some states have tried to do better by breaking it down a little finer. Like Colorado provides[1] a breakdown down by confirmed vs probable. But the data here is still not great.
> As well, you get the over-the-top cases where someone that dies of a gunshot is included in the covid death count[0].
? It's incredibly clear by looking at Colorado's numbers, there was no misclassification at all. Definitely mistakes have been made, but this isn't even an example of one.
Your comment is bizarre. The same case you're criticizing is from the state you go on to praise in the next sentence. These, unequivocally, have never been included in "death by covid" counts.
> financial implications for a state saying they have covid deaths
Yes, but there are also immense legal, financial, and political implications for lying about covid deaths. There is no evidence of this happening on a widespread scale.
Prior to April 2020 the diagnostic criteria for a covid death required 0 testing whatsoever. Combine that with financial incentives to record something as covid, and the lack of other income for hospitals as patients wouldn't come for minor things and elective operations were cancelled and you have a perfect storm for bad data
Not going to keep arguing about this, but there are a huge number of different ways we can confirm that our counts are roughly accurate.
There are obvious signals in total excess death counts indicating the number of deaths due to covid, we can do retrospective random testing of early classified covid deaths.
There is no evidence of some systematic conspiracy or anything of the sort. I encourage you to consider that you might be engaging in motivated reasoning.
How can you retrospectively test the people who died prior to April? How can you confirm any of the data that was generated by guesswork?
I'm fairly sure there is no tissue available to test from any of those bodies
The situation was ripe for fraud, and there is no way to prove it didn't happen en masse. Human nature suggests it did happen. The evidence of what caused those deaths is destroyed shortly after the paperwork is filled out. The whole thing is set up in such a manner that suggests inflation of the numbers, and to have no way to counter the claims as all evidence is gone
Is "pointing out" data considered downplaying? ~5% of deaths had "covid only" while the remaining 95% had other factors with the average having 4 other factors.
From the CDC:
> Table 3 shows the types of health conditions and contributing causes mentioned in conjunction with deaths involving coronavirus disease 2019 (COVID-19). The number of deaths that mention one or more of the conditions indicated is shown for all deaths involving COVID-19 and by age groups. For over 5% of these deaths, COVID-19 was the only cause mentioned on the death certificate. For deaths with conditions or causes in addition to COVID-19, on average, there were 4.0 additional conditions or causes per death...
Adding to this, pneumonia is merely inflammation of the (aveoli in the) lungs and it is almost always caused by some external factor, such as infection or illness.
> Is "pointing out" data considered downplaying? ~5% of deaths had "covid only" while the remaining 95% had other factors with the average having 4 other factors.
Is this a useful metric, though? If covid is the catalyst to cause death with preexisting conditions, is not covid the actual cause of death?
Covid in these cases is an acute condition that is the direct cause of death.
That's what he is attempting to imply is a massive overcounting in the data, but additional conditions that people point out as COVID deaths also having are mostly caused by COVID-19. Oh, they died of viral pneumonia after contracting COVID-19; pretty sure they would be in a different scenario had they not caught COVID-19.
The problem is we don't know, and "both sides" don't seem willing to admit that.
What I can guarantee is that of those 95% who died with COVID, some percentage of them would have died anyway, under almost identical circumstances, except without COVID.
However, it is also true that some of those people would have lived if they hadn't contracted COVID, even though COVID was not the "direct" cause of death. For how much longer, who knows. But certainly not when they did.
In other words: the people saying we should only be counting the 5% direct deaths are wrong, and the people that say we should be counting all 100% who had COVID as deaths from COVID are... also wrong.
We can use deaths-above-replacement (among other things) to determine how many more people died than normal from all causes, and then whittle down the obviously-not-from-contracting-covid deaths from there. The submission goes into very specific detail about how they did this, and they account for many of the potential confounders related to doing this analysis.
I believe we can be much more precise than you're giving us credit for in determining if contracting COVID was the direct cause of someone's death, even with comorbidities.
To be totally honest, when I see someone say, "we can't ever be totally sure" I nearly wholly discount that opinion, because it's very cheap to proffer, almost always true, and of very little value.
It is of immense value to say this when you have people in this very thread saying we might as well count everyone who had COVID as a death from COVID.
Also one of us is confused, and I don't think it is me. From what I've gleaned from this article, the 900,000 figure is not (as you say) "determining if contracting COVID was the direct cause of someone's death", but rather trying to figure out how many people would have died if this had been a "normal" year, i.e. if we could go to a parallel universe and make COVID never exist. This is absolutely not the same thing, as such a scenario will also count deaths as a result of our response to the virus as a death "due to the virus". This is my impression as they seem to be including things like suicide (criteria "c") and people who died because people with actual COVID were taking up hospital beds (criteria "b").
"Given that there is insufficient evidence to estimate these contributions to excess mortality, for now we assume that total COVID-19 deaths equal excess mortality."
I think this is the correct way to think about this problem, as it is likely to be an underestimate, rather than an overestimate.
In other words, counting suicides probably doesn't matter, as the number is very low. The paper says as much: "The main potential increases in excess mortality due to deferred care and increases in drug overdose and depression are hard to quantify at this point or are of a much smaller magnitude."
The paper overall goes into very great detail about what was and wasn't included and why, which is vastly more rigorous than what you seem to be presenting, which is effectively throwing up your hands and saying, "we'll never know!"
Just because we don't know exactly doesn't mean we aren't able to create good estimates. We don't know how many people die of any disease. But if you have a large enough dataset, and analyze it well, you can make good determinations of the approximate scale of each factor. The paper linked in this article does that, and concludes approximately 900,000 died of COVID who would not otherwise.
One is the OP's idea, "deaths due to COVID". This idea is "how many people would have died if COVID had never existed". However, what a lot of people hear when you say "deaths due to COVID" is "this is the number of people that died as either a direct or indirect result of having COVID in their system". But that is not the 900,000 number being cited.
It is made even worse by the HN headline, which is "death toll from COVID", which even more strongly implies the above.
Exactly! So rather than try to puzzle out this undecidable proposition for nearly a million individual deaths, let's just look at aggregate statistics. Did more people die on the whole during the pandemic than we would normally expect? Does that line up with a model that they probably died from covid?
And... that's exactly what the linked article is doing. And yeah, it turns out that all these people (on balance) would indeed still be alive had they not been sick with covid.
The linked article seems to be including suicide as a death resulting from COVID, when the increase in suicides is far more likely to be caused by our response to COVID, not having COVID.
It is definitely not only looking at whether people would have died sans covid in their system.
You think there were a half million excess suicides in the US due to our response to covid? Again, this is just nitpicking at an article that supports a (very obvious) conclusion you find politically inconvenient.
As to whether a suicide due to pandemic-induced depression "counts" as being "caused by the pandemic" or not, isn't exactly the kind of confounding effect you railed against above? Isn't the solution, again, to not demand that we micro-classify every death and simply look at the external effects we can measure?
A conclusion I find politically inconvenient? You have no idea what my politics are, please stop projecting.
To answer your question though, no, they should not be lumped together because they are not the same thing and so the mitigations would've/could've/should've been different. In other words, lumping all these things together as "caused by COVID" is the opposite of useful. For example, you do better next time with deaths due to COVID in your system (category "a") by ramping up vaccination faster/better facemask policy/earlier lockdowns/etc. You can decrease category "b" by having more hospital beds / more healthcare capacity. You can reduce the deaths in category "c" (seemingly suicides) by having lockdowns that aren't up-and-down rollercoasters / better mental healthcare / etc. All of these, though being "due to COVID" should be handled very differently so it is counterproductive to lump them all together.
Again, I think you might be projecting a bit here, because the only reason I can think of that you would want to lump them together is to push a political agenda. Not for any utilitarian reason.
You should be careful how far you go with that reasoning. If someone commits suicide due to loneliness during the lockdown does that mean covid killed that person? In an indirect way sure, covid kill him, but in my view it should not be counted as a covid death. Just taking excess deaths without differentiating these kinds of deaths is going to result in misleading statistics. It will cause people to think a person who did not have covid actually died from getting covid.
Alive when? Right now? By that logic the Spanish Flu has retroactively become quite harmless. The important question is, how much earlier did someone die because of Covid. 2 weeks of life just aren't worth as much as 50 years.
Yes, because many of those comorbidities are conditions that people could otherwise live with for decades... and furthermore, at least a couple of those comorbidities listed in that table are caused by COVID-19: pneumonia and respiratory failure.
If an obese person is in a car accident and immediately dies, we say that they died due to the more immediate health event: the car accident. -- even though we know that obese people are more susceptible to death in car accidents.
Those other factors like pnuemonia, arrythmia, organ damage, sepsis, etc. are mostly caused by COVID-19.
This is like saying that 0% of people who have contracted HIV have ever died of HIV, they died of other diseases. Well, sure, but what allowed those other diseases to be contracted?
I think where that 5% figure is used incorrectly: if you look at the other factors, they seem to not be "someone had a stroke, caught covid, and died", they're stuff like "Someone had Covid, developed pneumonia and died".
The top "other factors" are (in order): Pneumonia, "everything else", respiratory failure, high blood pressure, diabetes, cardiac arrest, heart disease, acute respiratory distress syndrome, etc.
It's pretty clear to say that far more than 5% died of Covid induced complications, not that they died of "natural" causes and also tested Covid positive. Saying the 5% number is almost certainly abuse of statistics, especially given the notable uptick in mortality in the US.
I'd consider it playing devil's advocate, depending on the scenario. The problem is, these days I often see a lot of bad faith arguments being passed off as "just playing devil's advocate".
You can be obese and diabetic and still live to be 80+ years old. My grandma is both, and will be turning 81 this year.
But if someone who is only 30, but obese and diabetic dies to COVID, it's a pretty damn bad faith argument to try to claim that COVID was not the cause of death.
At the end of the day, the question is, how many more deaths happened due to COVID than there would be otherwise. For that answer, we can look at excess mortality (which the article uses), which shows more deaths than the official COVID death tally.
> ~5% of deaths had "covid only" while the remaining 95% had other factors with the average having 4 other factors
Well, I don't even know where to find this kind of data, but your hypothesis could be tested by comparing the number of deaths in 2020 against the number of deaths in 2019, broken down by cause of death.
The "well they had comorbidities" argument does rather miss that after middle age that's true of pretty much everyone.
Or to take me as an example: I have asthma. That probably counts as a comorbidity, so if I die of covid, should that count as a covid death or not? I'm 42, I can reasonably expect another 42 years of life. Most chronic illnesses don't kill you.
> I have asthma. That probably counts as a comorbidity, so if I die of covid, should that count as a covid death or not?
I've actually seen some people with Asthma may have possibly survived because of certain Asthma medications that may do something to block covid, I can't remember the study, but if you're on that specific med, maybe that helped?
I'm > 400 lbs (690 in 2012), I'm 41, I survived having it. Except for long-covid which was a bitch.
That's one reason to look at excess mortality. The number of people who would have "died anyway" this year would be pretty similar to the number who died last year.
To add to this, looking strictly at deaths, neglects the long term affects and people with severe but none-fatal cases. Not to mention the capacity issues associated with Covid.
"cAsE fAtAliTy rAtE iS oNlY 1%" is a horrible metric to base any policy off of.
I had no idea about HIV deaths, I would have guessed it would be 2x-3x COVID deaths. I don't think that means "HIV had a smaller impact than I thought", I think that means COVID is bigger than I thought. We get desensitized to the numbers. Thanks for the perspective.
We'll have to wait 20+yr for the controversy to simmer down but I bet when you run the numbers using a metric like YPLL (which is the typical metric used for these sorts of comparisons) the difference between Covid and other big pandemic outbreaks over history is going to be more minor.
Flu seasons before vaccines were much worse than now though, it was like having covid every single year. The Spanish flu was about an order of magnitude worse than the normal flu seasons which is why it was so devastating.
> 900,000 death * 15 yll/death [0] = 13.5 million YLL
Right, so an average American lost 0.03 years of their life due to covid. I guess some thinks everything they did last year to save that 0.02 or so years was worth it. Basically you save a week by social distancing and locking down for a year.
Places that didn't do social distancing didn't lose much more, there is no evidence that social distancing saved more than I estimated here. My estimate was even very generous in your favour since I estimated death without social distancing to be the worst in the world. But we could estimate to be roughly the death rate in Florida, in which case most of the social distancing did basically nothing.
Right, and that was enough. Forcing kids and people under 60 to stay home and social distance didn't seem to be necessary to avoid disaster. But California still did it for over a year, that is the price you paid. How many years of life did it save in California compared to letting people distance as they themselves deem necessary? Not that many.
Right, I agree with that. But it was only valid for the first few weeks. The healthcare systems weren't critically overrun anywhere in the world. Yes, from time to time not every patient they wanted to put on a ventilator got one, but ventilators doesn't dramatically improve the odds of survival so it wasn't a big deal anyway.
So why did California continue with their measures for a year? They still did among the worst in the world so those measures seems to have had little to no effect at all.
> But it was only valid for the first few weeks. The healthcare systems weren't critically overrun anywhere in the world.
We live in a different planet? I live across the border with North Italy, and it was only 2 weeks what it took for the situation to go from "oops, looks like there's a problem" to "let's mobilize doctors out of retirement and potentially kill them to save people". There have been different levels of restrictions since. Same in France, Spain, Germany, pretty much anywhere in Europe.
> Yes, from time to time not every patient they wanted to put on a ventilator got one, but ventilators doesn't dramatically improve the odds of survival so it wasn't a big deal anyway.
Ventilators were abused at the beginning out of ignorance about the disease, but they're still the best last-resort treatment for critical cases. In my region, during the second wave, most deaths happened to people waiting for a ventilator, or during transfer from oxygen to a ventilator, and those on ventilators generally survived.
That said, now there's a more defined and effective protocol before reaching a ventilator that requires hospitalization nonetheless, and makes you require one if not followed.
> So why did California continue with their measures for a year? They still did among the worst in the world so those measures seems to have had little to no effect at all.
California had terrible numbers despite the fact that measures worked. It's been studied ad nauseam and social restrictions is the among most effective measures to be taken in every study, with a solid interval of confidence. One of my favourite studies is [0] because it shows that some things were done right (lockdowns, closing schools, remote work) but some had little to no effect (surface disinfection).
Is very small compared to the lives saved by those measures. Traffic safety laws saves about 20k young people per year in USA. Assume each had 40 years left to live, that is 0.8 million years, or about 0.002 years per person per year. That is about half a day of life saved per year per person, meaning 12 hours. Putting on a seatbelt takes a few seconds and you do it a few times per day, say 20 seconds per day. Add that up over a year and you get 100 minutes or about 2 hours spent seatbelting to save 12 hours of life.
Traffic lights takes more time, but they also allows for more dense traffic so I don't think that removing them would help at all. I doubt San Francisco traffic would get any better if you removed most traffic lights, likely it would get worse in all the chaos, so unless you prove to me that they actually hurt commute time rather than help I put those savings on the seatbelts.
> Is very small compared to the lives saved by those measures
Don’t get me wrong, I wear a seatbelt and stop at lights.
I was just agreeing with the parent comment. There seems a fairly strong vein that wanted no lockdown and for us to just accept any resulting carnage. I’m not part of that group.
You appear to be making the assumption that disease spread would not be different had lockdown not happened. The question isn't cost of lockdown vs cost of disease with lockdown, it's cost of lockdown vs cost of disease without lockdown. Without a lockdown, April and May would probably have had 10x (at least) more cases, and way more than 10x more deaths because hospitals wouldn't have had the space to hold everyone who was sick.
No country in the world is even close to an order of magnitude worse than USA regardless of what they did, so it isn't a reasonable estimate. Worst case is less than about 2x USA's numbers, I used that as an estimate of how many lives you saved with your measures.
Remember that life expectancy went from 60 -> 80 over the last century.
80% of the deaths have been from folks aged 65+. So, it is arguable that the Spanish flu would have killed a lot more if the average lifespan was higher.
It's an interesting point. Spanish Flu hit younger people, so having more older people might not have affected the numbers much. On the other hand, maybe having so many old people with covid affected which variant traveled around.
> The pandemic mostly killed young adults. In 1918–1919, 99% of pandemic influenza deaths in the U.S. occurred in people under 65, and nearly half of deaths were in young adults 20 to 40 years old.
I'm not trying to downplay it, I believe the official CDC counts, but some additional considerations are:
Is the high total death count related directly to our response(or lack thereof), or to our higher population of people pre-disposed/vulnerable to this virus? For the past few months the focus has been on people ignoring lockdowns, ignoring bans on gatherings, vaccine hesitance etc. but it seems that, based on the co-morbidities, we were an already largely unhealthy population to begin with.
We shouldn't downplay the progress we've made while we're at it. 100 million vaccinations is quite an accomplishment. If we're going to beat ourselves up for having the top total deaths(while not being in the top 20 per capita), we should pat ourselves on the back for that one. Getting 100 million people to do anything is hard.
To be fair, I feel it's been naturally downplayed already. It's really not shocking anybody anymore. There's a weird fuzzy average life that emerged where most people are just waiting for the thing to go away and the casualties have become numbers.
> Something to consider if you see anyone trying to downplay this.
It's invalid reasoning to use this study to "upplay" the pandemic.
It includes deaths due to depressions and delayed medical interventions, which you could argue isn't the result of COVID directly, but the result of lockdowns.
So when people use this study to claim "see, this many lives were lost, we were right to institute lockdowns" - that's circular reasoning, part of the reason so many lives were lost is because of lockdowns.
"Personally I lost access to badly needed medical care due to lockdown. Was quite scary."
My nearly 70 year old mother is in the same boat. She recently dealt with breast cancer treatments (a rare form) and thankfully was given the all clear before covid. She still needed to do follow up visits, more testing etc. but due to covid was told to stay away. Even though she was more comfortable with the risk of getting covid vs. ensuring her cancer is in remission they wouldn't see her.
I doubt that. People would naturally follow social distancing protocols (out of fear for their own lives). They would still hang out, but less and more in the open, and still go to the doctor, but less and only for the necessary issues. Literally the only place where "healthcare systems collapsed" (in the West) was Italy, which was caught completely unprepared.
There's a sensible middle ground between life-as-normal and enforced lockdowns.
We only know what happened with radical mitigation efforts. What happened was, ICUs repeatedly got near capacity and occasionally exceeded it in the US. What would happen without those radical mitigation efforts? ICUs would have had even more people with life-threatening illnesses and healthcare would have been rationed, resulting in more deaths.
And know that...how? Because "correlation = causation" is a legitimate scientific hypothesis now? Any legitimate scientific study has things like control groups to verify that the studied action wouldn't have happened otherwise, something I learned if high school biology in the first week. Your statement has none of that. And, any time you do look at places with NPIs vs non NPIs (Jutland in Denmark, or compare FL and TX vs Ny and CA, you see that your assumption is completely invalid.
If hospitals are full, not all people who need care can get care. It's not a complicated concept. ICUs in many parts of the country hit capacity during the pandemic, and that was with radical efforts to limit the spread of the virus.
Ventilators weren't as needed as originally thought. USA even killed a lot of patients by being over eager putting them into ventilators. If you put a healthy person in a ventilator there are a few percent chance of giving them pneumonia which typically kills them. When you blast air into their lungs it is really easy to accidentally blast bacteria all over them as well.
The articles about "we now know better how to treat patients" was mostly this, don't put them on ventilators unless it gets super critical, most patients got better without one. Also I haven't seen data on this but I strongly suspect the main reason USA lost so many young people to covid compared to other countries is that USA is way more eager to put people on treatment like ventilators, basically blasting bacteria into the lungs of young otherwise mostly healthy people killing them. Those young lives would have been saved if they weren't diagnosed in the first place.
> When you blast air into their lungs it is really easy to accidentally blast bacteria all over them as well
You might consider yourself lucky if they blast air into your lungs. Italian healthcare was using pure oxygen, which, used at prolonged periods of time basically burns your lungs. Some government officials recently admitted that this caused a lot of "COVID" deaths.
You say that, and they said it (only 90s kids will remember "fifteen days to slow the spread") but as of right now, it's a truism. Maybe the lockdown worked to ease the stress on the medical system. Maybe only the first 15 days of lockdown did that, or 30. I highly doubt that the entire year of lockdowns saved the medical system, and I would be willing to bet the effectiveness of the lockdowns in preventing a collapse of the medical system ended within the first 3 months. So suppose that's true, 3/4ths of the lockdown and all the mental health and depression related deaths associated with it were unnecessary. I don't know when the lockdowns stopped being effective in protecting the medical system, but I know it wasn't this morning. Some amount of those deaths are attributed to lockdowns that were unnecessary.
Also, you can't quantify the hypothetical death toll in that scenario in any real numbers, to say "would have skyrocketed" is unfounded. I could understand "would've been higher" that sounds reasonable.
> Something to consider if you see anyone trying to downplay this.
I admit I'm the morbid one in the group, memento mori and all. But I think the real stat we should track is years of lost life expectancy. That's the only statistic that makes sense when doing cross disease examinations. Not speaking specifically about covid, but more generally, something which primarily kills young people is much bigger deal than something which primarily kills old people.
I wonder if that measure should be used for criminal justice as well. As well as showing that killing an old person is less harmful, it also excludes babies. Both these groups seem to have lives that are worth less even to themselves and so it's (however distasteful) not as bad if they die. We already do that with abortion by valuing an unborn baby's life less.
Many places already has laws around infanticide which is much lower than manslaughter. Canada for example sentences mothers to at most 5 years with no minimum for killing their baby.
YLL is a horrifying metric because it values someone who is 20 over someone who is 60. The only argument I can see for its "usefulness" as a statistic is if you want to imply that the old are less useful than the young. This kind of statement about the bare utility of a human life is the same statement that underlies a lot of how we have treated the disabled or those on welfare in the past. And it only makes sense if you think about a human life in terms of its economic usefulness as some sort of cog in the economic machine that wears out and can be discarded safely after age 67.
Not necessarily. In my persona value system I would much rather live 20 more years when I'm 20 over living those same years once I'm 60.
It makes sense if we consider the possibility of novel life experiences to be an important value of how we live life. If you've made it to 60 (a not uncommon life expectancy), you've had a chance to travel, have children, live through many different life occasions, etc. If you're 20, you've barely had two years as a legal adult where you could make something of your life. It has little to do with economic productivity.
Someone who is 20 should be valued more than someone who is 60. Case in point, the deaths of the ~100,000 centenarians are going to be way less impactful than a disaster that wipes out the entire town of San Antonio.
> YLL is a horrifying metric because it values someone who is 20 over someone who is 60.
Not to my father, who is in his late 60s and the most at-risk member of the family, and who has been more opposed to the lockdowns than any of us.
His calculation is that at some point - for the good of the family, long-term - the economic damage and delayed social development of his grandchildren outweigh his personal safety.
I have encountered very few older people who don't also think this way.
The only argument I can see for its "usefulness" as a statistic is if you want to imply that the old are less useful than the young.
It's not about "usefulness", it's that saving the life of a young person produces a larger benefit in terms of expected future years of life. Take the extreme case: if a building is on fire and you can only rescue one person, would you be indifferent between saving the life of a 10 year old child versus a 90 year old with terminal cancer?
If you're going to get super utilitarian about it, strict years of life lost is not the best measure. As nearly all of human history proved out, very young children, especially infants, are particularly easy to replace. It's losing people in the prime years that really hurts a society, why for instance the US Civil War and the two World Wars were so terrible, where huge regions lost a majority of 20-40 year old men. Although again, if we're being very utilitarian, men are a lot less valuable than women, which is at least one reason we've usually sent men to war. Childbearing doesn't scale nearly as easily as child seeding.
interestingly i take it more from an intergenerational contract that at some point it's the duty of the old to senesce and optimize for the good of subsequent generations.
As I understand it this intergenerational contract used to be quite strong as people would see that previous generations invested in them and as a pay it forward sort of mechanism, they would in turn pay it forward to generations that proceed them .
I suppose there was some "take care of me when I'm old" in the intergenerational contract too, but I understood that as secondary to the propagation aspect...
I agree that we should be tracking years of lost life expectancy. I also believe in attempting a quality adjustment; we get better public policy from counting Quality Adjusted Life Years (QALY) lost.
I think that the main obstacle to this approach is that people instinctively think cross-sectionally rather than longitudinally. When you say "kills young people" and "kills old people", listeners focus on 2021. A young person is somebody born in 2000 and an old person is somebody-else, born in 1940. That is cross-sectional thinking, with 2021 as the date of the cross section.
But the real issue is that we nearly all live to grow old and get to experience both sides of the issue. Someone born in 2000 is likely to live until 2080. They will probably see a different respiratory virus going round then; it may even be what kills them.
So what would you personally prefer? The pro-lockdown approach trades losing a year out of your twenties to lock downs, in return for some action (perhaps ineffective, perhaps unnecessary) to ensure that you survive the plague of 2080 and get to live a few years longer.
The anti-lockdown approach makes the opposite trade-off. It is not really young versus old; it is now versus later.
I'm getting old and rather dreading later. I would prefer that society prioritize letting the young get on with their lives, education, dating, etc. and if I lose some poor quality care-home years, well, I've seen my grandparents and parents get old and frail, and I'd rather not dwell on the details of what I'm dreading.
If young people want to argue for the anti-lockdown trade-off, if they claim that in general young people shouldn't be locked down in the hope of protecting the elderly and they will accept their fate gracefully when they get old, well, I would think them wise beyond their years.
It's also greater than all of US military combat deaths for every war combined i.e. Civil War, WW1/2, Korea, Vietnam etc.. And think of how much concern (legitimately so) we have for them.
US Civil War death toll is estimated between 620,000 and 750,000, which is higher than the official Covid toll so far. It was also much more highly concentrated in a small number of states in a country that was far less populated.
This is anecdotal at best, but when my grandfather passed last May from COVID, his death certificate did not record the cause of death as COVID.
He tested negative twice after his month long bought with it, but only lived for another few weeks until dying of respiratory failure. We were told that because he was not testing positive at the time of death, his cause of death could not be recorded as COVID. I thought cause of death was whatever disease or injury started the chain of events that lead to one's death, but it felt like serious statistic manipulation.
Gets manipulated in the other direction too: financial incentives nudge hospitals to assign coronavirus as a cause of death if you had it when you died, even if it wasn't what actually killed you. I don't know if it's as blatant as "died in a car crash of coronavirus," but enough of my medical friends have mentioned it that I believe there's truth to it.
Many tallies in the US were adjusted after this specific criticism over 8 months ago. But I guess the talking point won't be updated, oh well.
My main issue with this criticism is that tallies of other illnesses have the same issues. So if an actual flu season said 20,000 people died, it had the same reporting issues and distribution of reporting issues.
This means a direct comparison to two ailments with the same distribution of reporting issues gives you an accurate view of the affect.
So even without going back and fixing the records - which I'm not sure you or other people even know happened - this means Covid deaths are more accurate and actually proves how it is much much worse.
Anybody see the irony there? Given that the point of bringing attention to this would be to downplay the severity or response (or that there is a 100% correlation between the people that subscribe to these talking points and want a dramatically different response or no mitigation response at all), so, thanks for keeping healthcare authorities accountable, I guess.
Source? Hospitals bill based on services performed, not based on what the ailment is. Nowhere in my bills did it say I went in for a kidney stone last year.
> Our ruling
> A post shared on Facebook claims hospitals have a financial incentive to claim patients had COVID-19, saying payment is three times higher if a patient goes on a ventilator. An article the post links to includes comments from a doctor who suggests the number of coronavirus cases is being padded.
> It is standard for Medicare to pay roughly three times more for a patient with a respiratory condition who goes on a ventilator than for one who does not. That has nothing to do with the coronavirus.
> As part of a federal stimulus bill, Medicare is paying hospitals 20% more than standard rates for COVID-19 patients.
> Indications are that due to a lack of testing and other factors, the number of coronavirus cases has been undercounted, not padded.
> For a statement that is partially accurate, our rating is Half True.
Not necessarily the hospital itself, but with that kind of incentive it's going to find its way in. One possibility is family members applying pressure to compassionate doctors.
“Show me the incentive and I'll show you the outcome” - Charlie Munger
Lady calls in, her 450lb 57 year old son with uncontrolled type 2 diabetes and COPD is found dead at his home. Post-mortem test shows he's positive for COVID. You're the doctor, your hospital has had to furlough a quarter of their staff because nobody is coming in for any outpatient care, there's an ICU full of people on vents and you've been there for 18 hours already.
The guys mom is there and you're working up her son's case. You have to fill in the blank for cause of death. What are you going to do? Order an autopsy and possibly cut this family out of government aid for COVID-related expenses and deaths?
It's pretty difficult to prove covid was not a contributing factor to a person's death. So unless there's clear evidence it wasn't, it should be listed as a contributing factor.
This isn't really any different than when a person dies some immediate event while also suffering from an underlying illness. If a leukemia patent suffers a an aneurysm, one would expect leukemia to be present on their death certificate.
"It is pretty difficult to prove god does not exist, so unless there's clear evidence he doesn't, it should be assumed he does."
The answer is the opposite, actually: if it is difficult to disprove any single contributor one way or another it should not be listed as a contributing factor.
Isn't it plausible your medical friends mentioned it a lot because...others around them also mentioned it a lot? Doctors and nurses are just as capable as spreading rumors as anyone else.
> financial incentives nudge hospitals to assign coronavirus as a cause of death if you had it when you died, even if it wasn't what actually killed you.
This accusation of fraud and malpractice has been a common talking point amongst those seeking to downplay COVID.
But I've yet to see any evidence that its common or widespread.
Medicare pays out 20% more to the hospital if a patient is Covid-19 positive. So there's actually a strong financial incentive to report every possible Covid-19 case in the US.
Death certificates can record both a primary cause and contributing factors. It's often a judgment call on what to consider as the cause and how far back in the chain of causality to go. There's no statistical manipulation there, just a lack of consistent standards.
More generally, there is no universally agreed way to record all the factors that contributed to a death at the time of death or certification.
This is why excess deaths is the real metric by which the toll of this pandemic will be measured, at least in countries with reliable records about whether deaths happened at all.
Excess deaths doesn't work either. Gun violence has increased everywhere. So have suicides in my region of the world. I don't know who or why this comment got flagged, it doesn't change reality
Excess deaths in a decent model account for other explanatory factors (war, sociopolitical things, etc.) that are not linked to the factor in question (covid-19 here). I'm not suggesting the crude arithmetical number of excess deaths is the key, but that a nuanced estimate of excess deaths in a model that accounts for other significant factors is a far better measure than anything else we have available.
I'm pretty sure there have been non-detectable covid variants in the wild in the US for months now. I went through this with my mother, she was admitted to the hospital for a surgery and contracted some kind of "flu." She tested negative several times for covid. She stayed with me to convalesce and I came down with a "flu" in the middle of summer that had most of the symptoms of covid, except the loss of taste/smell. But my PCR test came back negative.
I also had zero side-effects from my vaccine, which I understand is supposed to make people feel sick the day after the second dose.
Multiple medical professions felt it was covid and recommended testing.
Some of our symptoms weren't associated with flu, but were with covid.
There are some 20 tracked covid variants spreading in the USA right now.
Tracking of variants didn't begin until Dec. But even in the few months since they began tracking variant proportions, the dominant strains have shifted quite dramatically.
T his is not some wacky conspiracy. Given this evidence, my money is on it was a variant of covid not tested for. You might see things differently, and that's fine.
I'm sorry for your loss. I had a similar experience in the US. In my case, a doctor flatly contributed the (impending) death a byproduct of COVID. All tests prior to COVID were positive and pointed to many more years ahead.
I'm not certain, but I suspect something was lost in the handoff to the hospice care company where they just didn't have the history and I assume they were the ones that reported the COD. Not certain about this. I plan on looking to see if there's anyway to have this retroactively updated, but I'm not optimistic.
Similar story here - a family member contracted COVID in a nursing home, was sent to the hospital due to low blood oxygen levels, and was discharged. They passed away 2 weeks later, but the cause of death was not listed as COVID. I live in a red state, and for some reason, people are very hesitant to admit COVID can kill.
So much for all the conspiracy theories we saw last year claiming deaths attributed to COVID were being wildly inflated. Many people felt the opposite was likely true - and I think history will prove them right.
Wonder how they accounted for the gun shot victims and motorcycle crashes who are accounted as covid deaths?
Looking at Italian data going back to March/April of 2020, we knew that over 50% of deaths, the patient had 3+ serious diseases and had a median age of 79+.
The true death rate is the delta of standard deaths in a “normal” year and the ones recorded now. That and somehow account for some pull-forward that’s clearly happened.
If a person was somehow due to die (assume a God exists and it’s already planned) on January 2021 of terminal cancer, but then covid found him and he died Dec 2020, what’s the real cause of death?
It looks like Florida is two shades "better" than California in the diagram, which would put the total Florida death rate as better than California. That would be interesting because Florida did almost no lockdown.
Florida aggressively locked down visitor access to nursing homes pretty early on, which is where the vast majority of deaths happen.
Wearing masks on beaches and in restaurants etc may slightly impact the case count but really doesn't impact mortality in the same way that an outbreak in a care home does.
Is there any reliable evidence that wearing masks on beaches even impacts the case count? Data from actual contact tracing seems to indicate that outdoor transmission is close to zero.
Explain China, Vietnam, New Zealand, Australia, and Korea.
Not all of those countries are islands (The UK is one, and you may note that it's not on the list.)
But all of those countries instituted short, hard lockdowns, and relaxed them after bringing local cases to zero.
Around here, we institute half-assed lockdowns, that are lifted when enough people complain about them (only to come back, as cases surge). Maybe that's why they don't work for us - because we are politically and socially incapable of dealing with even a few weeks of hardship.
China literally welded people in their homes. They probably lied about their numbers.
New Zeland, and Australia had few cases when they did lock down, and are islands.
Korea has a very disciplined population compared to the West.
Really you should be comparing the US to Europe. The EU didnt do much better, but was far more draconian. Or within the states.
But anyway, i never know if people are serious when they propose the China or Australian model. Those were brutal and Im glad to be voting for a constitutional amendment next week to limit the governor's lockdown authority.
> But anyway, i never know if people are serious when they propose the China or Australian model. Those were brutal and Im glad to be voting for a constitutional amendment next week to limit the governor's lockdown authority.
I never know if people are serious when they suggest that a few hundred thousand dead is a worthwhile footgun-sacrifice to escape the draconian rule to which Australians and New Zealanders were subjected to over the past year. I'm generally a bit leery of ideological arguments that necessitate sacrificing those numbers of people for some intangible, abstract good.
But if we are going to go down that road, can I get a say in which people we will get to sacrifice to meet that ideological objective?
Death is not the worst things in life, an unreasonably large fear of death is much worse. A death cowering in fear, or full of regret is pathetic.
Who do you think you are picking who dies like a tyrant doling favors? Do you not think I have elderly loved ones I worry about? Do you think I would enjoy getting COVID myself, or potentially orphaning my daughters? No! I just refuse to blow my kids mind with endless lock downs.
My obligation is to take COVID seriously, and do my utmost not to get sick myself. If I do, ill lock myself up in the basement for as long as it takes.
But with my obligations I also have rights, and Ill be damned if someone too scared to have ever pondered their own mortality will ruin life for me without protest.
Korea didn't have national lockdowns and I don't think China did either. Vietnam's lock-downs were all harsh, but extremely short (2 weeks).
The common denominator in all covid success cases seems to be an effective and strong contract tracing and quarantine protocol. That is the tried and true method used to defeat outbreaks.
If you have a good contract tracing program, a short-hard lockdown can be used to delay the outbreak while your tracers find and isolate the infected.
But without an effective contract tracing program (and I'm not talking about some bullshit smartphone app, but public health contract tracers with the power to actually do something), the lockdown is just a delay tactic.
Even if we got down to 0 cases in April 2020 in the USA, the virus would work its way back in within weeks, if not days. Without a tracing program that works, we'd be back to ten thousand cases in a few months.
All those countries have tight border controls. We get hundreds of thousands of illegal border crosses ever year. We'd have to deploy the military along the Mexican border and probably Canada too.
I don't think a single state has really tried to ramp up contract tracing efforts to the required levels.
And Australia had a several month long lockdown to get defeat a relatively small, isolated breakout. The bigger the outbreak the longer the lockdown is needed. And the longer the lockdown, the less severe it can realistically be. I accepted "don't have any social visits" for 6 weeks, but I wouldn't comply if they asked for 6 months. You can close factories for a couple weeks, but not for 6 months.
They didn't have national lockdowns, and neither did the US.
They had regional lockdowns early in the pandemic. The US... Had a patchwork of half-assed regional lockdowns, that came weeks late.
> All those countries have tight border controls. We get hundreds of thousands of illegal border crosses ever year. We'd have to deploy the military along the Mexican border and probably Canada too.
The overwhelming majority of border cases in the US did not come from illegal crossings in Mexico. They came from legal crossings through controlled borders, because the US did not implement any quarantine control on inbound travelers. It asked for travelers to self-quarantine as a courtesy, with no verification or enforcement, with predictable results.
It's true that lockdowns without contact tracing just delay the problem. The US has failed at that too. If you caught COVID in April, chances are, you'd have no idea who you caught it from. It would have been difficult to engineer a more spectacular disaster, if we tried.
You need two parts to this equation. Lockdown, and contact tracing. Both are required, and it's disingenuous to say that lockdowns don't work. It's fair to say that they don't work as we implemented them. Our implementation of them is not the only implementation of them.
I’m not trying to blame illegal immigrants for our pandemic. They didn’t cause it and I really doubt they made it appreciably worse. Like you said, we didn’t even have restrictions on anyone.
But in my hypothetical where we got to where NZ and AZ are right now (no covid in the community), and quarantine controlled entries, uncontrolled border crossings would 1000% bring in new cases. My point is you need to seal your borders nearly 100% to pull off what NZ and Az do.
And some of it’s a law of large numbers issue. If there is a 1/10,000 chance covid makes it through border quarantine, then if we have 50X as many crossings, we’ll need 50X as many mini-lockdowns. At some point it becomes impractical.
I don’t think it’s fair to say “lockdowns work” when you really mean “lockdowns work at the very start of an outbreak when paired with a strong contract tracing, quarantine, and border sealing.”
I think there is a point of no return at which you cannot lockdown/trace your way back to zero because the virus is everywhere is large numbers.
Total speculation, but I think the US would have had to implement the NZ plan + military on the borders + internal restrictions on travel to different metro areas in Feb. 2020 to have really successfully avoided Covid.
> I don’t think it’s fair to say “lockdowns work” when you really mean “lockdowns work at the very start of an outbreak when paired with a strong contract tracing, quarantine, and border sealing.”
Well, I was initially responding to a context-free claim about them not working. I agree, my response was also a bit light on context, and it made a stronger claim than was warranted.
> Total speculation, but I think the US would have had to implement the NZ plan + military on the borders + internal restrictions on travel to different metro areas in Feb. 2020 to have really successfully avoided Covid.
That may be true. It might not be. I think we will never know, because official policy at the time was 'don't test sick people [1], sweep everything under the rug to make the numbers look good, don't let private providers test people, institute a delayed travel ban that does not include Europe.'
[1] Unless they recently traveled from a foreign outbreak area. I remember reading about the hoops people had to jump through to get tested - and how many of them just gave up on the whole thing. Official policy was not to test non-travelers, because there was no evidence of community spread. Of course, if you never test anyone, you won't find any...
I agree with the last point and I don't think it's a bad thing. I'm against lockdowns period. I'm not against vaccines, not against masks, but I don't want this administration, the last administration, or any other to have the power to put us on indefinite house arrest. This IS a hill I wont budge from.
With China, we don't have enough information to make the claim that they under-reported deaths. If you CTRL-F China in the OP data on them is absent. I'm a bit surprised that the author could extrapolate a gap between reporting and actual deaths for every other country except that one.
As for comparing EU and the UK to Australia and New Zealand, that's more easily explained by the much higher air traffic volume between these countries and covid hotspots early on. In short, the combination of being "islands" with limited ports of entry and smaller passenger volume meant that early border closures could be much more feasible and effective.
Korea for all intents and purposes is an "island" in this comparison as well, in that on 3 sides it's surrounded by water and its northern border has no ports of entry.
A short, early response with entry closures and contact tracing does seem to be key, but I don't agree with the notion that we need to emulate their lockdowns. I'd rather wear a mask forever than be like them. The UK got the worst of both worlds since they got stricter lockdowns than the US without getting it under control. The decision to go for zero and stop all social life in order to get down to zero deaths from all covid is commendable but not our obligation. Our duty was to stop from overwhelming our medical system only, not to go for zero by giving up all social life and the economy.
That's what's confusing. It's really not clear what works and what doesn't. Germany and India did well until they didn't. Maybe all hell will break loose in Florida soon.
What I don't get that people who don't want lockdowns also oppose masking and other measures. Why not try to keep things open but also strongly support masking just to be sure?
One of the people I know who died, did so after traveling to Florida where they did catch covid, return home and died 40 some days later on a ventilator.
Maybe travel in and out of Florida is fluid enough to explain it to some degree.
> did so after traveling to Florida to catch covid
uh, what? I don't understand why anyone would willingly try to catch a disease...
(get your kids the chickenpox vaccine, don't do those chickenpox parties if those still exist. The vaccine drastically reduces the occurrence shingles later in life. I'm a bit envious that my younger sisters got it, but I got chickenpox as a child. Seeing it flare up in my dad every 18 months doesn't give me hope).
> Studies show that more than 99% of Americans 40 years and older have had chickenpox, even if they don’t remember having the disease.
I'm a little surprised that the quoted age of most Americans having it is not less than that. The chickenpox vaccine was only authorized for use in the US in 1995 (I was born a bit before that, my siblings after that). That would make everyone 28 or older at least 2 years old before the vaccine came out in the US, which is the most likely age people got it.
(Assuming that immigrants in the window of 1988 to 1995 from nations who authorized in that period do not make up a substantial fraction of the present US population).
2. No there weren't. That was a rumor that no one has been able to find a single shred of evidence for. Just because the local news repeated a rumor they heard from a student doesn't make it factual. It's beyond pathetic that so many in the national news media repeated this and is yet another example why they cannot be trusted. Sensationalism, be it in modeling or journalism, is absolutely destroying trust in institutions and the medical community. Want to know why so many distrust the vaccine? Look at your own post to understand why.
Figure 5: The (estimated) ratio of reported versus total deaths. It appears from it that FL was more accurate in their reported numbers than CA. That has absolutely nothing to do with lockdowns.
Figure 7: The cumulative deaths, where FL and CA are the same color (that is, in the same range of cumulative deaths).
Either way, neither indicates that FL's death rate was better than CA's.
I was in Florida for a good part last year, and it was pretty similar to how things were in Illinois, as a lot of response was left to the local authorities and a lot of people distanced themselves without needing laws to tell them to do so. The biggest difference was that there was more indoor dining and some public schools were in person.
I think you’re talking about Figure 5 which is the ratio of total to reported COVID related deaths. This would mean that CA underreported COVID related deaths compared to Florida.
Figure 7, the cumulative total death rate, is probably more relevant to the point you’re trying to make, in which case FL and CA are in the same bin.
One conclusion you might draw is that the effectiveness of lockdowns cannot be inferred from this single map.
If California did underreport Covid-related deaths compared to Florida, that in itself would be interesting because endless column inches were spent on claims that Florida was underreporting its Covid deaths as part of a cover-up by its evil right-wing leaders and we definitely didn't see nearly so many claims that California was doing this.
What do you stand to gain by spreading political narratives even more? It doesn’t matter what side they say they’re on. Take, for instance, the democratic governor of NY, among the biggest culprits of hiding reporting on deaths. What’s the point?
Maybe your problem is more with the media than any side which they defined.
Maybe lockdown is not as effective as people think - not for deaths anyway (I'm sure it keeps case numbers down).
For deaths it seems by far the most important is not lockdown, but rather protecting elderly. So maybe Florida prioritized that, and didn't spend effort on lockdown, while California prioritized lockdown thinking it would also help elderly.
Or, maybe California was hit earlier, having a greater share of its total cases relatively early in the pandemic and geographically concentrated, meaning more overwhelmed hospitals and more use of early-pandemic treatment protocols that both overused ventilation based on generic protocols not tuned to COVID’ behavior and lacked more effective treatments developed during the pandemic.
(I mean, that definitely happened, but I haven’t seen analysis quantifying the significance of the total contribution.)
There’s a whole lot of omitted confounding variables in the “compare aggregate totals and jump to policy conclusions” games people are playing.
Florida was hit way earlier. You can see that from the excess mortality graphs here [1].
Here's a cumulative death per capita graph for 5 states that illustrate 5 different patterns [2]. Most states followed one of these patterns.
There is the "New York" pattern: densely populated states with a large elderly population. Hit very hard very early with a very high death rate, but after a couple of months got a handle on it and from then on was about average.
There is the "Washington" pattern: a fairly steady rise in deaths per capita, never quite under control but never really out of hand either.
The "Florida": like Washington for the first 3 or 4 months, then shifts to a more rapid growth, and pretty much stays there.
The "California": 3 or 4 months like Washington, the starts to Florida but gets the rate back down, then spends another 3 or 4 months like Washington (but shifted up because of the burp at 3 or 4 months), but then loses it in the third wave almost catching up to Florida.
The "South Dakota": low population low density state that with reasonable precautions should do better than Washington, but by working really hard to ignore it manage to end up with high numbers.
Use the drop down to flip that graph from total deaths to total cases, and South Dakota is even more striking.
Flip to new cases or new deaths 1 week averages to compare how they all are doing currently. Florida's currently running about 3-4 times the new cases as California, and about 50% more new deaths. (Change the highlight dropdown from "All Highlight & All Current" to "All Current" to make it easier to see the latest values).
It will be interesting to see how vaccination will affect this. With the more easily transmittable variants becoming more common, which also seem to hit younger people more, I've seen the estimates from what we need for herd immunity go up to 80-90% from the early 70% estimates for the original variant.
Overall, there are enough people who say that they will not get vaccinated to make it unlikely that the US can reach that, especially if it turns out to be 90% needed. However, those people are not uniformly distributed among the states. I would not be surprised if in a half a year we end up with two kinds of states: those where it is fully under control due to herd immunity and life has largely returned to normal, and those where it is still sickening and killing a lot of people.
Most of California's deaths occurred in a wave from January to March of 2021, while Florida had their first wave in the summer of 2020. (https://linqbymarsh.com/blueicustominsights/covid-insights is good for historical data like this).
There’s a whole lot of omitted confounding variables in the “compare aggregate totals and jump to policy conclusions” games people are playing.
Very true, but the lack of clear correlation between level of restrictions and Covid outcomes is at least some evidence against lockdowns.
We should be concluding that lockdown and masks leads to more deaths, not less (or at the very least that they are an unjustifiably expensive public health intervention), and begin rolling back all restrictions immediately.
You can't compare countries like that. People live very differently in Sweden and India; the healthcare system is different, and so is climate, population density and distribution, customs ( e.g. in France people used to kiss on the cheek when meeting, including for the first time), etc.
It would make more sense to compare similar countries, and Sweden is drastically worse than any its neighbours. Not only that, they changed course and added tougher restrictions than originally, so they themselves realised it doesn't work to fo nothing.
Sweden had a couple of days living lost per capita more than its neighbours last year, hardly a catastrophe. Maybe it was worth it for them, maybe not, but it is really hard to argue that the difference is so large that Sweden was objectively worse.
If you argue about healthcare reforms overall then sweden does much better than Finland and Denmark, as expected lifespan was still much longer even when covid was at its worst. So a Sweden with covid every single year is still better off than Finland and Denmark without covid. Likely they could do better if they implemented some of Swedens others healthcare reforms rather than fight covid.
Japan also never had any legally mandated lockdowns or business closures. (Their constitution wouldn't allow it, among other issues.) But Japan is very different. A strong recommendation from health authorities with broad social compliance there may as well carry the full weight of a law. It's a country where your lost wallet will almost certainly be returned to you by a random stranger who finds it. Can you guess which country is often in the top five with Japan in studies which test civic virtue like that? Yep. Sweden.
It's worth noting that the governments in both Japan and Sweden have very strongly recommended distancing, and probably just as importantly they've provided some funding to allow individuals and businesses to comply. Just paying people to stay home without a compulsory element might have been quite effective in many societies with relatively high civic virtue and social trust, but only Japan and Sweden seem to have actually tried it.
Besides, if we're just cherry-picking examples -- well, Canada is doing much better than Sweden. Or America. And Canada is more comparable to America than Sweden. And Canada has had more drastic shutdowns and restrictions compared to America. So how does that fit into the picture?
A lot of people in Florida ignored the Governors advice and self-locked down. So there's no real way to know what the impact of lockdowns were in Florida.
The organization that published these numbers apparently a. Doesn't know how to use certbot and b. Is primarily funded by organizations who are anything but impartial on the subject
From Wikipedia:
IHME receives core grant funding from the Bill & Melinda Gates Foundation[60] and the state of Washington. The US Centers for Disease Control and Prevention (CDC); Inter-American Development Bank; Gavi, the Vaccine Alliance; the National Heart, Lung and Blood Institute; Kingdom of Saudi Arabia Ministry of Health; Medtronic Philanthropy; and the National Institute on Aging have also contributed funding through project grants and contracts.
Billions of dollars from organizations that have billions invested in selling vaccines
Look into the criticism of organizations such as Gavi.
What about what I said was "conspiracy bs"? These are the organizations that fund the group. They are invested in vaccine sales, and some of them have very questionable ethics. Again from Wikipedia:
"Public-sector workers and academics public health have criticized GAVI, and other global health initiatives (GHIs) with private-sector actors, saying that they have neither the democratic legitimacy nor the capacity to decide on public health agendas. Private donors often find it easier to exert influence through public-private partnerships like GAVI than through the traditional public sector. There is also criticism that staff at GHIs are often recruited directly from elite educational institutions, and have no experience in health care systems, especially those in poorer countries. Some WHO officials have privately criticized GAVI for infringing and weakening the WHO's mandates"
And that is just a small portion of the issues with that organization. GAVI is an organization that promotes sales of the industry's newest vaccines, not promoting vaccination as a whole.
"In 2012, the first MSF "The right shot" report criticized GAVI for focussing on funding expensive new vaccines and neglecting to give children cheap old ones. "Twenty percent of the world’s children aren’t even getting the basic vaccines", MSF's vaccine policy adviser said.[11] MSF criticized the Global Vaccine Action Plan (GVAP), a WHO global collaboration of which GAVI is listed as a leader, as flawed for failing to help those 20%, which is some 19 million children.[28]"
And this is just complaints against one of the organizations.
Conspiracy BS because it cherry picks ideas to support a conclusion.
The implied conclusion is that Covid has been exaggerated to sell vaccines
Cherry picking exapmple: "criticized GAVI for focussing on funding expensive new vaccines and neglecting to give children cheap old ones" Two minutes reading the article on Wiki tells me that the purpose of the organisation is to facilitate access to new vaccines, expensive patented ones. Access to non patented cheap vaccines does not need a group like this.
Hardly worth bothering about, but the question was asked. That is why "conspiracy BS"
This isn't a "study", it's a statistical model. It reflects the assumptions put into it. To wit:
> Our analysis follows four key steps. First, for all locations where weekly or monthly all-cause mortality has been reported since the start of the pandemic, we estimate how much mortality increased compared to the expected death rate....Second, based on a range of studies and consideration of other evidence, we estimate the fraction of excess mortality that is from total COVID-19 deaths as opposed to the five other drivers that influence excess mortality. Third, we build a statistical model that predicts the weekly ratio of total COVID-19 deaths to reported COVID-19 deaths based on covariates and spatial effects. Fourth, we use this statistical relationship to predict the ratio of total to reported COVID-19 deaths in places without data on total COVID-19 deaths and then multiply the reported COVID-19 deaths by this ratio to generate estimates of total COVID-19 deaths for all locations.
And, what, you may ask, are the biases of the models' authors with regards to the percentage of excess mortality due to Covid itself? Excellent question:
> Deaths that are directly due to COVID-19 are likely underreported in many locations, particularly in settings where COVID-19 testing is in short supply. Most excess mortality is likely misclassified COVID-19 deaths.
> Given that there is insufficient evidence to estimate these contributions to excess mortality, for now we assume that total COVID-19 deaths equal excess mortality. For the reasons presented in this section, we believe that this is likely an underestimate.
As someone who has now spent the better part of his life creating statistical models, when you assume something is true, your model is likely to confirm your assumptions.
This is why statistical models are worthless without prospective validation. If you haven't shown that your assumptions are correct for the future, you're just making castles in the sky.
Yep, and it's a suspect one at best. Personally I wouldn't trust a stastical model from someone who advertises that they own the book "how to lie with statistics" and obviously used it
A comment from a high school math teacher concerning that book (which yes, was commonplace to read even decades ago, even among high school AP students) has stuck with me: "It's definitely possible to lie with statistics, but wait until you see how much you can get away with without them!"
The book "how to lie with statistics" (1954) was written before tags like /s were invented. Referencing "how to lie with statistics" is an indicator that the author is trying to avoid common pitfalls in statistical reasoning.
I own an inherited blue Pelican paperbook copy from my pharmacist grandfather.
Surely you'd agree that "2020 excess deaths are going to be predominantly covid" is a very reasonable hypothesis though, right? And you agree that "2020 has an extraordinarily high excess death rate", because that part is easily measured data, right?
Basically: your response seems a bit nitpicky to me, which tells me that perhaps you're starting from a perspective where you're assuming the article is wrong and looking for holes to poke.
Look, nothing about this paper's conclusions is surprising at all. At all. We all know true covid deaths are higher than reported, because all such metrics underreport, for all diseases (and frankly almost all causes of death). The only question is "By how much?". So you don't like 400k. What's your counter?
> Surely you'd agree that "2020 excess deaths are going to be predominantly covid" is a very reasonable hypothesis though, right? And you agree that "2020 has an extraordinarily high excess death rate", because that part is easily measured data, right?
I don't know the answer, and neither do you. But given that the top-line is asserting that there are 900k excess deaths due to Covid, the choice of assumption here is not some minor detail. There are lots of other plausible alternative hypotheses.
Aassuming X, then building a model that shows X is true, is not validating a hypothesis.
> There are lots of other plausible alternative hypotheses.
Please list them.
We have data about deaths going back many decades. It's very safe to say that if in 2010 you made a prediction about the number of expected deaths in 2011, you would have been very close to the real number. Same if you had predicted the deaths for 2019 in 2018.
Suddenly, after decades and decades of being almost perfect in your predictions, you would have been wildly wrong for the predicted number of deaths in 2020.
After decades of predictability, there was a whopping 20% increase in 2020 [1]. How can you possibly say it wasn't caused by Covid?
We also have plenty of time series data from effectively instituted lockdowns worldwide. Excess deaths rise prior to the lockdown, in line with but greater than reported COVID deaths. They continue rising until median COVID- time-to-death days after the start of lockdown. Then they fall, sharply, dipping below regular excess deaths (and tracking the fall in COVID deaths). That isn't a pattern that fits the "maybe some other factor like the lockdown itself caused the spike" hypothesis, and it is also the pattern that was predicted by the scientists advocating the lockdowns.
Sure, some deaths are caused by lockdown, but the evidence suggests a pattern of the deaths which have been[1] caused by lockdown being [more than] netted out by normal deaths prevented by lockdown.
Some days it's cold, and anthropogenic climate change models are just fancy math, but this doesn't make all climate hypotheses equally plausible
[1]there's a plausible argument lack of medical attention during lockdowns and/or long term economic consequences may have a significant death toll in future, but that doesn't affect the "excess deaths reported during COVID have matched COVID spikes evidence
Your claims of "vast time series data" would be more believable if you actually linked to some of it.
It's interesting how you can't suspend your credulity to encompass the idea that there are alternative hypotheses for excess deaths, but you are more than happy to assert the existence of "vast datasets" to defend your own opinions.
Here are a few plausible alternative hypotheses that actually have substantial backing evidence, which can be obtained with trivial googling:
* Excess deaths due to missed treatments (we know this is happening, e.g. for cancer)
* Excess deaths due to untreated acute medical emergencies (e.g. physicians in NYC noticed the curious phenomenon of heart attacks disappearing from ERs during the height of lockdown
* Excess deaths due to drug and alcohol abuse (again, we know it's happening)
I'm sure there are many others worth consideration. My point is not to assert that any of these are automatically true, but that they merit consideration, and anyone who doesn't fairly consider them is probably not engaged in good-faith debate.
Again, not sure why I can’t reply directly to timr, but the data in the graphs on EuroMOMO is not spelled out, it’s just data. That’s no reason to dismiss it?
You can start by asking questions like- why do some neighbouring countries have different profiles? Why do some not have any excess mortality? Why do some have multiple spikes?
Which is an excellent article. I just fail to see how you think it's inconsistent with the numbers in the IHME story above or their methodology. Lots of these confounding factors are expressly enumerated. I mean, do experts like the authors of that OWiD article find the same fault with IHME that you do? Can you cite some making similar criticisms?
Again, I get the distinct feeling that you're arguing with methodology here not because there's anything particularly suspicious with IHME at all, but because the conclusion (that the US is approaching 1M covid deaths, something that should surprise no one) is politically inconvenient.
> I mean, do experts like the authors of that OWiD article find the same fault with IHME that you do? Can you cite some making similar criticisms?
I don't know. I don't cross-check my thoughts with every "expert" in the world before I express them. I have expertise in this field; I can think for myself.
> Again, I get the distinct feeling that you're arguing with methodology here not because there's anything particularly suspicious with IHME at all, but because the conclusion (that the US is approaching 1M covid deaths, something that should surprise no one) is politically inconvenient.
You have no idea what my politics are. I am saying that this model reflects the assumptions used to create it. Nothing more, nothing less. It is not a validation of the assumptions -- it is a regurgitation of the assumptions.
I think the critique is more that the 'study' is really just a complicated statistical restatement of the assumption, so it doesn't prove or even highlight anything new or interesting.
That's some kind of relativist argument I don't understand. Modelling and theory is an important part of science. We have something that is difficult to measure independently, so we build models to derive an explanation from things we can measure. And they did that. And the results line up with the hypothesis.
I mean, duh. Usually hypotheses are right! You're right that it would be more interesting if it showed some kind of confounding effect or whatever.
But it didn't. It turns out that the boring explanation seems like the right one: the anomalously high number of people who died of unexplained reasons in 2020 was just the giant global pandemic. Oh well.
You have deaths due to Covid directly, additonal deaths that come as a result of good policies, and additional deaths that come as a result of bad policies.
It's disengenuous to say Covid is the cause if politicians used hamfisted responses that led to more deaths than necessary.
Sorry, what exactly is the mechanism for those policy deaths you're invoking? Can you cite the relevant study you're thinking of and explain why it's more convincing than people simply dying of a serious disease?
> for now we assume that total COVID-19 deaths equal excess mortality.
This part is especially doubtful for me, as there are factors moving it in either direction. For one, the pandemic measures also helped a lot for things like the flu, which had less cases and therefore caused less deaths. On the other hand, problems caused by lack of exercise and social interaction have definitely increased. Lastly, I'm quite sure we have a lot of missclassified deaths in either direction.
These are all quite different and I see no reason to assume these factors even out.
I wouldn't call it at all doubtful. The fact there's less cars on the road can only push excess mortality down, regardless of lack of exercise, so it seems sensible to attribute it all to the pandemic.
Also, suicides aren't significantly up,the physical and psychological effects of lockdown don't happen immediately, while a reduction of car deaths do.
e.g. UK suicides have not significantly changed in 2020:
People avoiding medical treatment is awkward in the figures, because - medical treatment sometimes kills people. First link I found suggests that medical treatments cause 800,000 deaths per year in the USA.
If medical treatments are really down, I'd guess we might actually expect mortality figures to be temporarily down (but, higher later).
If medical treatment causes more deaths than it prevents on average, we’re probably doing it wrong, though maybe it looks different in the short term as you imply.
Agreed. All medical treatments are about balancing risks.
Whenever you take any surgery (for example), the meaningful risk of immediate death is balanced against the benefit of better quality of life later.
If you measure the impact of medical treatments only on the day they are taken, you'll only find evidence that a bunch of people have died who wouldn't have otherwise died on that day.
You can't then observe the benefit until some time has passed.
> irst link I found suggests that medical treatments cause 800,000 deaths per year in the USA.
That number pops up all the time in clickbait headlines, but the study behind it doesn't really support the claim.
There is a pretty substantial difference between "Deaths caused by medical mistakes" and "Deaths that occur in a certain timeframe after a medical mistake occurs" (which is what the study actually looked at) are two very different things.
The sicker someone is, the more likely they are to receive healthcare (so there are more opportunities for mistakes). Also, the sicker someone is, the more likely they are to die. Those two combine to result in a lot of folks that die shortly after a medical mistake, even if the mistake was very minor, and didn't contribute in any way to their death.
I would generally expect non-covid deaths to be down as is indicated by correlations between mortality and economic decline, the fact that suicides haven't trended substantially upwards, and the fact that cars are off the road.
I saw an article to the effect that car-related deaths are up because, since there are fewer cars on the road, the drivers who are left drive faster and/or more recklessly and get in more accidents. So, as with everything in this pandemic, it's complicated...
Doesn't honestly surprise me that much , I was driving up i95 in late March and people were pulling some really crazy shit in the early pandemic. I also saw a few (looked deadly to me) wrecks on the highway.
Yeah I was struck by how fucking insane people got on the roads shortly after the pandemic struck.
You'd think people would chill out because the roads were practically empty, but I guess pandemic stress combined with the immediate rage of "the roads are empty and this asshole camper is only doing 75 mph in left lane" leading to absolute lunacy at very high speeds.
Normal levels of rush hour traffic around here mean nobody can do more than 50 mph at best with an average speed closer to 35, which probably keeps the deaths down.
There are around 30,000 to 35,000 car deaths per year in the US over the last ten years, and around 35,000 to 45,000 deaths from suicide. Those are terrible number sin absolute terms, of course, but even if those went to 0 for a year during the pandemic, that’s still less than 15% of the deaths currently attributed to COVID-19 in the US.
For my country and some others I monitored, the first wave happened outside of flu season, and excess mortality was higher than COVID deaths at that point and continued to track.
Second wave was more difficult since it overlapped the normal flu season.
> for now we assume that total COVID-19 deaths equal excess mortality.
This seems reasonable, although I'd suggest it's an underestimate of COVID-19 deaths.
Excess deaths counts have been consistently showing negative in countries during periods of time where they have coronavirus under control.
Other significant causes of death (including suicide, influenza, road traffic accidents) appear to be down.
As such, I'd assume that COVID-19 deaths are likely somewhat higher than excess mortality figures. I'm prepared to accept the assumption that they're approximately the same.
[Edited to note: the linked article discusses this with further detail and evidence]
I just don't understand where they got such high excess death numbers in the first place. Fitting a sinusoid with a 52 week perios and adding a slope for population growth you can get a very good (R=99.xx) fit up until the pandemic. Using that ramped sinusoid the excess death number comes out about 50k over the reported covid totals.
Edit: data source is cdc total mortality page. Going back to 2014
> [Edited to note: the linked article discusses this with further detail and evidence]
Here's the sum total of evidence provided:
> An analysis by the Netherlands statistical agency suggested that all excess deaths in the Netherlands were directly due to COVID-19
So they use a single study out of Europe to extrapolate here.
> The second driver of excess mortality is reduced health care utilization for many causes;3 however, the impact of reduced health care use on health outcomes is harder to prove. Many mechanisms have been proposed, including reduced vaccination rates and reduced births in hospital.4 Demonstrated increases in cause-specific mortality related to these causes, however, have not yet been verified. The impact of changes in health care utilization on excess mortality may be observed in later years, rather than in 2020 or the first quarter of 2021.
So they dismiss this.
> Third, convincing evidence has been found that rates of anxiety and depression have increased, which might in turn lead to increases in deaths from suicide.5 To date, the evidence on increased suicide is very limited.6 Opioid deaths, on the other hand, have clearly increased7 in the United States. Compared to past trends, opioid deaths increased by around 15,000 since March 2020. Evidence on whether this has also occurred in other countries awaits further study.
So again, they dismiss this.
> Fourth, we reviewed the evidence on decreases in injuries as a result of reductions in mobility. We analyzed data from 12 countries that provide cause of death data by week or month, which allows us to test whether some causes decreased significantly during 2020 and whether that decrease was related to the decreases in mobility that have been reported. This analysis suggests that globally, injury mortality decreased by 5% in 2020 due to reductions in mobility. At the global level, this translates into a reduction of approximately 215,000 deaths.
Conveniently, when then assumption works out in their favor, they include it in the model.
> Fifth, some infectious causes of death may have declined during the pandemic due to the behavioral changes associated with control of the pandemic, including mask use and reduced contact with others. Causes that have clearly declined are influenza,8,9 respiratory syncytial virus,10 measles,11 and possibly other respiratory viruses and viral diarrheas. For example, influenza cases in the United States declined 99.3% from the winter season of 2019–2020 to the winter season of 2020–2021. Combining the reductions reported in different countries in influenza, respiratory syncytial virus, and measles, the global reduction in mortality from these causes may be larger than 400,000 deaths.
Again, when the assumption works in their favor, they include it.
> Sixth, deaths from some chronic conditions such as ischemic heart disease or chronic respiratory disease declined in some months of 2020, most notably in May and June in Europe. These declines were most likely due to the fact that frail individuals who died from COVID-19 earlier in the year would otherwise likely have died from these chronic conditions. The strongest evidence for this effect is that excess mortality was negative in some countries in Europe in June when the reported COVID-19 death rate was very low. In aggregate, this effect likely reduced mortality by only 2% based on our analysis.
This is so egregious as to be laughable...they find evidence for something, and then "based on their analysis", limit the effects.
> The main potential increases in excess mortality due to deferred care and increases in drug overdose and depression are hard to quantify at this point or are of a much smaller magnitude. Given that there is insufficient evidence to estimate these contributions to excess mortality, for now we assume that total COVID-19 deaths equal excess mortality.
So they didn't even try.
Again...I don't know what the right answer is here, but this is, at best, a biased reading of the available data. All you can do is throw up your hands and go back to first principles: without prospective validation, statistical models are fiction.
On the other hand:
"in many European countries there was a spike of excess deaths in weeks 31–35 during a period when COVID-19 reported deaths were extremely low. This period coincided with a heat wave and national reports of deaths due to the heat wave. We excluded these weeks of data from subsequent analyses."
I personally wouldn't have excluded these weeks - unless you're going to exclude historical (near-annual) heatwaves from the figures, this should balance out.
> All you can do is throw up your hands and go back to first principles: without prospective validation, statistical models are fiction.
No estimation is perfect, nor expected to be, and so your criticism is unreasonable. You're doing exactly the things that you are criticising the study for, and more so. You provide zero evidence to counter their sourced evidence, and ignore and dismiss points that don't match what you are trying to say.
> No estimation is perfect, nor expected to be, and so your criticism is unreasonable. You're doing exactly the things that you are criticising the study for, and more so. You provide zero evidence to counter their sourced evidence, and ignore and dismiss points that don't match what you are trying to say.
They have provided no "evidence" -- they made a model. They have provided no validation of that model, so it could be completely incorrect. Nobody knows.
Furthermore, I just showed you that of the sourced evidence they did consider, they dismissed nearly everything that reduced the death rate attributable to Covid, and said it was "too dificult" to quantify.
Mathematical models without prospective validation are not evidence. They are not science. They are bedtime stories.
> without prospective validation, statistical models are fiction.
I wouldn't be completely dismissive. The first attempts at using statistical data to drive medical practice were during the Napoleonic wars, and dramatically improved medicine. I would expect the statistical methods used were pretty crude, as it was a very young discipline.
Maybe I'm just ignorant of the relevant statistical methods, but how do you suggest models be validated prospectively? All the model validation techniques I'm aware of come after the model is fit on the data (or a subset of it), like testing against a holdout set, or k-fold cross-validation, or checking R^2.
Not just a holdout set -- a holdout set of prospective data, where you actually predict the future, blindly, and see how you do.
Obviously, you have to wait a little while to gather such data before you make big claims with your model. Doesn't mean you get to skip it.
It's not even clear to me that the authors did a cross-validation here, or even bothered to fit the free parameters of their model based on any kind of empirical data at all. At least with regard to percentage of excess deaths due to Covid, I'm not sure how they could...the parameters seem to be unrelated to any empirical data.
What is the mathematical difference between testing against a holdout set of data collected at the same time as the data used to fit the model, and a holdout set collected in the future? I'm in total agreement that avoiding, e.g., overfitting is a good thing – but what work is prospectivity doing here?
Also, if I understand correctly, none of the modeling done in standard texts such as Gelman et al.'s Bayesian Data Analysis involves prospective validation under your definition. Should we then classify the examples in that book as "mathematical fairy tales"? This seems like a fairly strict standard!
A prospective test is blind. You don't know what the data looks like, so you can't cheat.
> Also, if I understand correctly, none of the modeling done in standard texts such as Gelman et al.'s Bayesian Data Analysis involves prospective validation under your definition. Should we then classify the examples in that book as "mathematical fairy tales"? This seems like a fairly strict standard!
It's surprisingly common for models to pass all of the cross-validation you want to throw at them, and fail in the real world. I don't care what statistical techniques you've applied, if you don't conduct blind tests, you don't know how your model performs.
Setting this aside: TFA did nothing you're talking about. Let's be clear about that.
> A prospective test is blind. You don't know what the data looks like, so you can't cheat.
Suppose I blind myself to the holdout set. What's the difference?
> It's surprisingly common for models to pass all of the cross-validation you want to throw at them, and fail in the real world. I don't care what statistical techniques you've applied, if you don't conduct blind tests, you don't know how your model performs.
What exact failure mode is such that a) prospective testing guards against it, and b) traditional validation methods do not?
Take for example distribution shift. Suppose I'm worried the underlying data generating process is going to change between training and deployment. You propose, I guess, that this is fixed by collecting more data prospectively. OK, suppose and I do that and everything checks out. Now what guarantees there is no distribution shift between the time I do the prospective testing and subsequently deploy the model?
To be more direct: one eventually has to make assumptions of statistical regularity and distributional constancy somewhere, at some point, in order to do any statistical inference at all. If you have good reasons to make such an assumption, I don't see why prospective data collection is any different from a regular holdout set. And if you don't, then you're screwed no matter what you do.
> Setting this aside: TFA did nothing you're talking about. Let's be clear about that.
Sure, but strongly held, unorthodox opinions about statistical practice are more interesting to me than tearing down some mediocre article.
Not the poster, but happy to answer since I have a decent amount of experience in similar areas.
Their point is that while in theory you could blind yourself to the holdout set - that rarely REALLY happens. At least in a truly good way. Almost everyone is going to either peek at the data, massage the data, or try the validation and when it fails tweak the model and try again, or any number of shenanigans that no one admits happen - but happen all the time.
The failure mode that a prospective test would guard against in this case is - you can't peek or massage the future (and if you can, you can retire a billionaire pretty easy and stop worrying about this) - so you can't accidentally fool yourself or others by peeking, massaging, etc. And if you tweak your model, then do another prospective test - then you still can't peek at the future, and you'll have a different set of data, so you can't be overfitting to the old data/p-hacking.
You can do it over and over again, and as long as you don't just say 'all good' on a failed test without doing another different prospective test, you either have a predictive model or you clearly do not.
That is something the traditional validation models cannot do, since they aren't looking for truly never before seen data.
It still doesn't tell you if once in production you will stop fitting and fail over, but it does at least tell you that it fit a never been seen, new set of data at least once. Which is better than the other tests can do by their very nature.
> Almost everyone is going to either peek at the data, massage the data, or try the validation and when it fails tweak the model and try again, or any number of shenanigans that no one admits happen - but happen all the time.
While "peeking" at the data is certainly something that happens all the time, usually what happens for even the most rigorous of model-makers is that your model fails "out of domain" -- the past doesn't accurately reflect the future.
Even if you get everything else right, it's incredibly common to fool yourself into believing you're capturing "reality", when in fact you're just making a good fit to past random fluctuations.
The point about peeking at the holdout set is fine, I guess. But then the slogan should be "models without a truly blinded holdout set are statistical fiction." Prospectivity doesn't do any work above and beyond blinding there.
I already addressed the point about distribution shift above. You need to assume that the past reflects the future at some point, otherwise you can't justify deploying the model even after the prospective test.
> a holdout set of prospective data, where you actually predict the future, blindly, and see how you do.
According to your theory, publishing would act as a 'nothing up my sleeve' validation of their model.
Since, you can check this model in the future - you can do it for yourself.
And yet, you seem to be complaining about this publication?
(I still don't agree with this as a principle - since I wouldn't now expect the future to reflect the past, and the authors make no claim to predictive powers when they are identifying that the present is unlike the past)
> The second driver of excess mortality is reduced health care utilization for many causes;
Wouldn't that still be technically tangentially an after effect of covid? I mean no covid, no reason not to get to the doctor, so if covid didn't exist you might survive those, no?
I noticed (late summer last year) that especially age group 25-44 is/was affected in the US with a +25% (excess) mortality YoY. It is not entirely unusual that diseases affect different countries differently; However I found it peculiar.
USA has 30 times the deaths among 30-39 year olds but only 5.5 times the population. It isn't just Italy, almost every other country has a distribution similar to Italy.
Italy has a huge older population and a lot more lax on cigarettes... older smokers = raised chances of death...
USA on the other hand has excess obesity across all metrics (I'm one), so if it hit younger ages harder here it's probably due to obesity epidemic raising death chances.
> Excess deaths counts have been consistently showing negative in countries during periods of time where they have coronavirus under control.
> Other significant causes of death (including suicide, influenza, road traffic accidents) appear to be down.
That's most probably a direct factor of the containment measures. Influenza has been on sometimes historic lows (https://www.who.int/influenza/surveillance_monitoring/update...), and as many people have stayed home streets have been free and people don't drive home from bars totally drunk, both drastically reducing road accidents.
These are mostly unchecked secondary sources, of course. But, your secondary source, the "National Safety Council", appears to over-report deaths compared to the Department of Transportation's later figures. In 2019, they over-reported by... 8%.
Alzeimer's currently doesn't have any effective treatments, so I'd repeat the question: how would the fatality rate from Alzheimer's double year over year?
At the very least this has no way to distinguish directly between direct and indirect effects of the epidemic. The average person has put on weight, gets less exercise and is less likely to go visit a doctor. I think the distinction is important if this type of statistics are used to consider e.g. the easing of outdoor restrictions.
But this wasn’t written to confirm that COVID was underreported, nor predict future results, it was written to estimate the mortality rate of the past year and a half. Your criticism doesn’t seem to hold here.
Also: The author cited the sources for their assumptions, specifically on COVID mortality classification.
The IHME has been wildly wrong yet highly cited for over a year now. I've still got screencaps of their models that predict around 90,000 total deaths in the USA by the end of 2020. They were lifting a sigmoid curve off of China's numbers and applying it to the United States entirely blindly. It didn't even predict the shape of the decline off the first peak correctly since it was implicitly assuming the US would take similar steps to China (martial law) and drive the R0 down to 0.4 or so.
There has been a ton of terrible modeling this year, and the IHME is just one example. This week the CDC published an ensemble of models trained on Covid case data up to March 27.
The models completely mispredict the actual number of cases since that time:
This is a total failure of validation that would make any other practitioner question the whole exercise, but it didn't stop the CDC from publishing them. Nor did it stop the news media from trumpeting the results. The Washington Post and CNBC and others wrote headline articles fawning over them.
Third, we build a statistical model that predicts the weekly ratio of total COVID-19 deaths to reported COVID-19 deaths based on covariates and spatial effects.
Given how disastrously wrong most modeling/forecasting(1) has been during this pandemic color me a little bit skeptical that their model is somehow better. Models give wide latitude to fiddle with parameters.
Color me completely distrusting. Between the IHME and Neil Ferguson (aka The Master of Disaster because of how horrifically wrong his models have been) models in the UK, they haven't even been close to reality. The IHME was even called out last year by other data modelers at one point for how poorly done their models were.
This is a slight re-write of history, by my recollection.
Neil Ferguson's earliest models were used to justify no action/herd immunity as the UK's initial strategy.
I recall (but can't find) the Imperial College scientists saying they didn't fully consider any other option at first, because they understood that it would be politically unpalatable.
Just goes to show how faulty our recollection is that it changes what we think was history.
Best to actually look it up.
(hint: you won't find the 'do nothing for herd immunity' as a stategy, but you will find many newspaper articles speculating about it based on out of context quotes)
History gives a better record than our impressions from the news of the sensational at the time and our faulty memories.
which discusses 'mitigation' and 'suppression' as two possible strategies, in March 2020.
The UK government took this report as an endorsement for 'mitigation', which it discusses in more detail, even though the report says "For countries able to achieve it, this leaves suppression as the preferred policy option."
Mitigation is quoted as meaning "reducing peak healthcare demand while protecting those most at risk of severe disease from infection" - I'll admit I extrapolated this into "do nothing".
>the discrepancy between reported deaths and analyses of death rates compared to expected death rates, sometimes referred to as “excess mortality,” suggests that the total COVID-19 death rate is many multiples larger than official reports.
So...not as many people died as we thought were going to so we're now just going to arbitrarily say any excess death was a covid death just to make sure the numbers look like what we think they should?
These are the kinds of statistical shenanigans that have been going on all year and people wonder why people question 'the science.'
Comparison of expected versus actual outcomes is a reliable method to estimate the overall effect of a new input. Can you specifically point out how such analysis constitutes "shenanigans"?
It includes deaths caused by the response to covid, such as people avoiding hospital for other diseases and whatever the deathy consequences of lockdowns might be.
Just a few sentences later, they break down changes in death rates into 6 categories -- 3 that are increases but also 3 that are decreases.
But in any case, it's a pretty reasonable first-order assumption that excess deaths are from COVID, that can then be analyzed in more detail per-population to see if it continues to be plausible, e.g. whether excess deaths were also correlated in time and place with COVID, etc.
And isn't this precisely the kind of double-checking of official numbers that is valuable? Official statistics don't always tell the truth -- witness Cuomo specifically undercounting nursing home deaths. The shenanigans we should be concerned with aren't this -- it's shenanigans in official reporting. Thank goodness we live in a democracy with free speech where these kinds of things can be questioned.
Challenging findings to produce stronger, more trustworthy final results ultimately increases faith in science, don't you think? It sounds like you're arguing findings should never be challenged, which isn't science at all.
They then say that they considered all the 3 factors that lead to increases to be COVID deaths:
> The main potential increases in excess mortality due to deferred care and increases in drug overdose and depression are hard to quantify at this point or are of a much smaller magnitude. Given that there is insufficient evidence to estimate these contributions to excess mortality, for now we assume that total COVID-19 deaths equal excess mortality
Basically the 6 factor breakdown is a way to decrease the volume of expected deaths to make the excess mortality number larger. 100% of which was attributed to COVID.
For me its shocking that we as a population have become so numb to so much death around us. Wonder what it says about society in general. Would be fascinating to read any research reports on that aspect.
That's because our media has a gentleman's agreement to not show it to us.
If the news were running 24/7 with reels of disaster porn - images of people dying in ICUs, or struggling to breathe and unable to get treatment, we'd have been taking this problem seriously last year. Instead, it's this abstract, sanitized problem that only happens to other people.
Sure. And the evening news should show every fatal car crash, in multiple angles, slo-mo, so the population would learn about these deathtraps called "automobiles" and we could take that problem seriously too.
As others have pointed out the death toll from COVID is truly astounding. Get your vaccines if you can.
That being said, excess mortality is not purely from COVID. There are widely reported drops in treatment for various cancers [1,2,3]. The link between COVID and diabetes is also very complicated and will take years to figure out what happened. The grim bright side is that we've seemed to hit peak excess deaths and may be dipping below and so the 900k number might decrease a little moving forward [4].
Isn't "total mortality due to COVID-19" different than "total mortality from COVID-19"? As I understand the cancer treatments were aborted due COVID-19, therefore, more person died due to COVID-19 but not necessarily from COVID-19... does it make sense?
I think that's exactly the criticism of this paper. They are precisely saying "total mortality due to COVID-19" = "total mortality from COVID-19". From the paper:
> for now we assume that total COVID-19 deaths equal excess mortality
Well that's a question of if you think the lockdowns were necessary or not. If you think they were, then of course excess mortality is due to covid. If you think they weren't then that excess mortality was due to unneeded human intervention. Of course the answer is somewhere in between, that is, some degree of lockdowns and therefore the deaths attendant to that were overzealous, and that throws this entire model in the trash.
“If there were 315,507 excess deaths due to Covid-19, why is the difference in all-cause deaths between the end of 2020 and the end of 2019 only 61,654? That’s 61,654 more all-cause deaths in 2020 than in 2019, where the increase in all-cause deaths over each of the past ten years has averaged 44,806. That’s a difference of 16,848 from the median in a year with an alleged 315,507 extra Covid-related deaths.”
I'm curious to find out the long-term effect from all the organ damage caused by non-lethal COVID-19. Heart damage, lung damage, brain damage, blood clots, chronic fatigue. Wonder if our healthcare costs will reach a new high over the next 30 years.
An interesting read, but the title here is pretty terrible. It represents one line in a table halfway down the page. The original article title is "Estimation of Total Mortality Due to COVID-19" which is accurate, if dull. I'd perhaps add "worldwide".
They claim COVID led to behavioral changes that lowered the expected volume of death, so the naive excess mortality is an undercount:
> Overall, the evidence suggests reductions of 615,000 deaths, or potentially more, stemming from behavioral changes at the global level. The main potential increases in excess mortality due to deferred care and increases in drug overdose and depression are hard to quantify at this point or are of a much smaller magnitude. Given that there is insufficient evidence to estimate these contributions to excess mortality, for now we assume that total COVID-19 deaths equal excess mortality
So basically they lowered the expected number of deaths, then claimed all deaths above expectation are COVID.
How many more people have died during the pandemic than we would expect to have died based on past trends? The NYT had a tracker (which they stopped updating) that showed the number of excess deaths was not much higher than than confirmed COVID-19 deaths. https://www.nytimes.com/interactive/2021/01/14/us/covid-19-d...
It is totally a coincidence not worth investigating that the covid outbreak started in a city with the lab that holds the world’s largest collection of bat coronaviruses.
for starters let’s have WHO investigate it by a team not led by the guy who was a close collaborator with Wuhan lab.
yet to see an independent team of experts (as in no previous collaborators, not vetted by ccp, etc) allowed to investigate the lab which holds the world’s largest collection of bat coronaviruses and just happened to be located in Wuhan.
This headline is wildly click-baity and does not reflect the linked "study", however flawed, at all. The headline should be changed.
The "study" (really it's just a model) primarily investigated excess mortalities related to our response to COVID-19, NOT COVID-19 itself. The second paragraph states six drivers of all-cause mortality that were taken into consideration:
a) the total COVID-19 death rate, that is, all deaths directly related to COVID-19 infection
b) the increase in mortality due to needed health care being delayed or deferred during the pandemic
c) the increase in mortality due to increases in mental health disorders including depression, increased alcohol use, and increased opioid use
d) the reduction in mortality due to decreases in injuries because of general reductions in mobility associated with social distancing mandates
e) the reductions in mortality due to reduced transmission of other viruses, most notably influenza, respiratory syncytial virus, and measles
f) the reductions in mortality due to some chronic conditions, such as cardiovascular disease and chronic respiratory disease, that occur when frail individuals who would have died from these conditions died earlier from COVID-19 instead.
Only 2 of these 6 factors are related to the virus itself; the rest are related to our response.
If anything, this model highlights how destructive our response was.
Anecdotes obviously don't validate data models, but I do wonder if my personal experience was common.
My mother-in-law passed last summer, alone in her apartment. She was sick beforehand, quarantined, and living in a senior living community. When she was discovered the coroner did not come and investigate because it appears of natural causes, based on the observations of the local police officer. Her body was transported directly to the funeral home.
I insisted they do a COVID-19 test, which the coroner did at the funeral home. The results came back as positive. Had I not pushed them to actually test, it would have been misreported and her death mis-attributed.
It left me wondering if this was common and how many people may have passed in similar circumstances, without family pushing for testing.
I won't make the unfair comparison to, say, New Zealand, which has no land borders, but let's take Vietnam:
* 100M people
* Long land borders with Laos, Cambodia, and China
* Virus located in state territory in Jan 2020
* Total number of verified cases: 3,137.
* Total number of deaths: 35
* Current number of daily new cases: ~50.
Multiply the figures by 3.3 or so to normalize with US population.
Forget the quibbling over the statistical model. Maybe it's only 600K. Regardless, it's over _20000 times higher_. And even allowing for, I don't know, different susceptibility to the symptoms, or whatever - the US numbers are just insane.
What everyone is neglecting to talk about is the age effect of mortality with Covid.
For people under 55 the chance of fatility is miniscule.. in the range of choking or car accidents. This age group makes up 80% or so of the population.
For people over 80 this may be the worst disease since the black plague. Millions upon millions of deaths. This age group makes up approximately 10% of the population.
This is an important consideration because the lockdowns effectively trapped mostly working age people who weren't at risk of dying from Covid in the first place.
I think that's where a lot of criticism of Covid policies stems from.
Should we make national health policy based on a disease that effects a minority of the population?
US population: 328.2 million. So that's 0.24%. Assuming the average victim would have died another 10 years, that means everyone lost, on average, 0.024 years = 8.8 days.
Heh, the thread is amusing. A few days back there was another thread discussing true mortality rate of COVID in India and a lot of support for how deviation from base rates are a fairly good indicator. When it comes to the US...
Basically, it's nothing to worry about. On an average year, about 2.5 million people die in the US, with at least 600k from cancer. Another data point is that something like 2.3 millions sit in the US prisons right now, so if the 900k number makes you terrified, you should be 3x more terrified about ending up in a prison one day and Nx more terrified by cancer, as for each cancer death, there are tens living in misery fighting that cancer.
The study is counting all excess mortality during the pandemic. This is a bad methodology, and I might add possibly a politically motivated one, but that's neither here nor there.
There are metrics all over the place showing some regions with no lockdowns having less excess mortality and mortality due to covid. Some of the lockdown measures in some places were counterproductive. Some people say all of them were, some people say none of them were anywhere (which makes no sense really), but the truth is probably somewhere in the middle: at least some measures taken in some places were the wrong call. This is to be expected, we didn't know what the disease was going to do and lots of us panicked. But conflating deaths from covid with deaths from the response and attributing all of them to the same cause is going to necessarily include deaths that would not have happened even in the pandemic if it weren't for the response. And we can quantify that, as an example, look at the disparity in excess mortality and covid death between California and Florida. California had a higher excess mortality and a higher covid death rate. Was that excess death in California due to covid, or due to a botched response? Again, probably a bit of both, but there's no way to pick the two categories apart, and so this entire methodology is not useful to quantify anything.
Compare 900k dead from COVID-19 (so far) to U.S. deaths in:
- Vietnam[1]: 58 k
- World War Two[2]: 407 k
- World War One[3]: 117 k
and due to the huge numbers of people in the U.S. who are refusing to get vaccinated, wear masks, or participate in social distancing, the U.S. deaths from COVID-19 are probably far from over.
900k people did not die from COVID-19. This "model" is predicting deaths related to the response to COVID-19 (deaths to to increase drug usage, missed cancer screenings, etc.).
The second paragraph of the linked article clearly states this.
Not to be grim but seems to me that a country that suffered lots of casualties of their oldest, weakest and most infirm and the least economic disaster is probably well suited to be successful in the future.
So many commenters arguing about the accuracy of the statistical models used to reach the 900,000 dead figure.
Missing the terrible, tragic, point. Too many people have died (and too many been disabled - for each death about 10 get "Long Covid") It did not have to be like this.
This is/was a tragedy. There have been way too many deaths. Some places did much worse than others - perhaps it is time to start thinking about, and discussing that?
In order to even start calculation the "true" cost, they should also subtract the deaths from school shootings, road accidents, etc. that did not happen this past year.
We changed the title from "True U.S. death toll from Covid is more than 900k, study finds". That was editorialized, which breaks the site guidelines. It was also arguably both misleading and baity, which means that it broke the site guidelines on all three points:
"Please use the original title, unless it is misleading or linkbait; don't editorialize."
Note this also means COVID has been the number 1 cause of fatalities in total. The other top killers are heart disease and cancer. Heart disease kills ~660k a year and cancer 600k a year. We're not that much over 1 year now since the first cases in the USA. This means that COVID is absolute top cause of fatalities at the moment. For anyone that may feel the need to mention car crashes, guns or drugs those don't even rank in the top 10 of fatalities in the USA.
Something to consider if you see anyone trying to downplay this.
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