I live in Contra Costa County (east bay, SF area), with a lot of retired people. 1.1 million residents. We’ve had 224 deaths with COVID so far. In the US, death rates are pretty flat (not fluctuating much with cases), and of the 198k deaths in the US, only 16K were younger than 54 years of age.
Does that sound like a pandemic?
Is it reasonable to shutter most of our economies for those numbers?
Can we not have different regulations for those with elevated risks?
Earnest questions.
People are suffering economically and emotionally because of stress and isolation.
1. That's the number of deaths given the restrictions. If there were no restrictions then the numbers would be much higher.
2. What is your source for death rates not fluctuating with cases? In general, deaths have reliably tracked cases, with a delay of a few weeks (because it takes time to progress from diagnosis to death).
3. Shuttering the economy is not binary. With an intelligent approach, and general compliance with measures such as mask wearing, we ought to be able to control the virus without a complete shutdown. Unfortunately we keep making unintelligent tradeoffs and executing inconsistently.
>If there were no restrictions then the numbers would be much higher.
There are a lot of claims like this which are very difficult to prove or disprove. Sweden was one of the few places that went very light on it's measures and never got overwhelmed and generally coped with the virus OK so far. (They admit they messed up with care homes, but that is the same as with many other countries who took far harsher measures).
It's worth noting that Sweden is actually more strict than a number of states in the US - 50 person limit on any gatherings, and that limit applies to restaurants as well. They were also better positioned than almost any country to potentially tackle the pandemic well - wealthy, very high percentage of single person households, high percentage of jobs amenable to working from home, and yet their deaths per million rate is close to that of the US. That rate is also 5-10x that of their Nordic neighbors.
What they did help show was that certain mixes of mitigation (vs suppression) measures could potentially keep R below 1 in certain places. But even there, because of a limited testing strategy, it was hard to confirm this for quite a while in Sweden. It would have been a lot more helpful if there'd been a lot more testing surveillance in Sweden, but alas.
3 - We are asking everyone to adhere to economic and social restrictions when the risks are not equal to everyone. People in certain age groups, and with health risks, are far more at risk than most people.
This site seems entirely untethered to reality? E.g. "2) Covid mortality vs. flu mortality" section appears to put IFR for covid of those at age 80 at 0.16%? Yet, we have entire countries that aren't far off from that number for population fatality rates, let alone infection fatality rate.
Wait.. I was just assuming this had to be an IFR comparison, because for something like this, anything else would be disingenuous. I should assume less. It looks like it is comparing annual mortality of flu with the current mortality of Covid-19.
1. We're still far from a year into notable spread of Covid-19.
2. Normal flu seasons don't have lockdowns, masks, bans on large events, etc.
3. In digging a bit more, this uses the 2017 flu season as a baseline, which was one of the worst.
This site is actually a great example of Covid-19 misinformation. It has a veneer of authority - Swiss Policy Research as a name sounds like it might be credible. And, it presents what, on first glance, appears to be claims grounded in science (and hey, nice graphs and all!).
But, one starts digging into the claims, and it starts to become clear the flaws.
jasonv: there are a lot of pseudoscientific resources out there with respect to Covid-19. This looks to be one of them. It's more essential than ever to vet what you're linking to these days.
Isn’t it as callous to dismiss the 50 million people who have filed for unemployment for the 200-210K who have died from the pandemic, esp when the majority of those are older?
From an argument perspective, I’d suggest that if we want to allay encryption restrictions because we don’t buy “think of the children”, the same logic could be applied to the economy and the 50m already at economic risk. People are dying and suffering from poverty, starvation.. around the globe. Children aren’t have their childhoods.
> I live in Contra Costa County (east bay, SF area), with a lot of retired people. 1.1 million residents. We’ve had 224 deaths with COVID so far.
> Does that sound like a pandemic?
It sounds like a region that has handled the pandemic well.
> In the US, death rates are pretty flat (not fluctuating much with cases)
Daily deaths are tracking case rates (given, one is best off looking at a combo of case rates, positivity and total testing). Of course, deaths lag a fair bit.
> of the 198k deaths in the US, only 16K were younger than 54 years of age.
And, we're only around 10% total incidence rate in the US, based on more recent widespread antibody studies. 16K for under 54 is still a fairly large number given that we're only at ~10%. Add in 55-64 and we're at 42K deaths. Let's ramp up to an incidence rate of 50% - super basic napkin math and we'd be at over 200K deaths for the under 65 crowd - as in, entirely people of below retirement age. That's huge.
> Is it reasonable to shutter most of our economies for those numbers?
We haven't though. Not to downplay the economic impact, but most of the economy is still running.
> People are suffering economically and emotionally because of stress and isolation.
Yeah, this aspect sucks. A few comments:
* Let's imagine we lifted all restrictions. How much do you think that would improve the economy? There's at least some evidence that economies that have failed in mitigation, such that the virus runs pretty close to free, have had the sharpest GDP declines - https://ourworldindata.org/covid-health-economy - granted, it is hard to separate out factors, as countries that have seen huge spread often also will, at least temporarily, lock down more. But, my general comment here is that the virus itself is a significant portion of the economic impact.
* The federal government should have done more to keep people afloat during this period. This sort of crisis is exactly when we should have committed to sustained support, e.g. UBI until the pandemic was over.
* Beyond that, re isolation, most places in the country allow for gatherings, for you to visit family and friends, for you to go out and about. Sure, big events and bars are still restricted in most places, but if one wants to socialize, they still can.
The United States leads the developed world in deaths due to this fucking virus. The gbdeclaration will help us continue to lead the world in deaths from the virus.
This seems incredibly hand-wavey in actually accomplishing "focused protection."
> Adopting measures to protect the vulnerable should be the central aim of public health responses to COVID-19. By way of example, nursing homes should use staff with acquired immunity and perform frequent PCR testing of other staff and all visitors. Staff rotation should be minimized. Retired people living at home should have groceries and other essentials delivered to their home. When possible, they should meet family members outside rather than inside. A comprehensive and detailed list of measures, including approaches to multi-generational households, can be implemented, and is well within the scope and capability of public health professionals.
The fundamental problem is that pretty much every country that has not been able to contain general community spread has had a hard time attempting to protect even just the super high risk populations (e.g. nursing homes).
But, in a country like the US, the high risk population is much, much larger than the nursing home population. Age or health conditions means that probably at least 100 million people in the country would be high risk. I've still not seen any comprehensive proposal for how you can protect the high risk populations while letting the virus run free in the low risk populations. In general, we're way too interconnected and aren't willing to invest the (likely massive) resources to even attempt this. Think of how many high risk people still have to work in non-WFH jobs. Think how many multi-family households there are. Think of how many low risk people live with high risk people. Think of how many parents of school kids and teens are high risk.
The more general community spread there is, the more it impacts high risk folks who don't have the luxury of fully isolating from community risk.
Finally, it doesn't help that Jay Bhattacharya is one of the authors - a Hoover Institution associated fellow who's pretty infamous in the epi community for the fundamentally flawed Santa Clara antibody study - significant statistical issues, a highly flawed recruitment strategy, a side story of his wife recruiting people through a non-approved side channel, questionable funding sources like the founder of JetBlue (with records that showed said founder might have influenced the research), and, and, and. Many of these flaws biased the study into showing a high infection incidence rate, and thus a much lower fatality rate, in the same ballpark as the flu. Given that he's continued to downplay the seriousness ever since then, his name being attached to any sort of declaration should give one at least pause.
"But, in a country like the US, the high risk population is much, much larger than the nursing home population. Age or health conditions means that probably at least 100 million people in the country would be high risk"
FWIW, 65% of the 9373 COVID19 deaths in Massachusetts occurred in Long Term Care homes [0]. This is a terrible thing that could have been prevented (or at least mitigated) and do I believe the Commonwealth has failed here. However it does seem to indicate that LTC home occupants are generally more at risk than people not in a LTC home (which seems to make some sense, if you're in a LTC home, it's probably for a reason -- e.g. significant health issues/frailty). We can do better.
For sure. Massachusetts seems especially high as a percentage re nursing homes. I believe the national average is ~40%. So, absolutely, a priority should be to focus on nursing homes.
And that's also part of my point - nursing homes were known to be extremely high risk from the very beginning - remember that outbreak in Washington. Despite that early warning, we still, by and large, failed to protect these smaller, super high risk communities. If we can't even do that well, what chance do we have in protecting the much larger "high risk but not super high risk" populations?
Back in March, when the lockdown was issued in Massachusetts, just a couple of days after CA and NY, it was chaotic. People were lining up for their toilet paper, hand sanitizer, lysol chicken etc. Old people standing next to young, shelves stripped bare in the stores, people driving around from store to store and even going up to NH looking for the basics.
It was a free for all, pandemonium. It had to have been a super-spreading event in it's own right.
In May, Gov. Baker activated the Mass National Guard to help the nursing homes, there were troopers/medics going from home to home, administering COVID tests, checking vitals and, unfortunately removing bodies.
What we _should_ have done is activate the National Guard back in late January to blockade all nursing homes, hospitals etc. to make sure only approved people entered and that they were provided with some of the limited PPE we had and were using it.
Additionally, towns could have organized volunteers to deliver food, groceries and medicines to the vulnerable who were quarantining at home.
So yes, some focus and we could probably have cut the death rate by 80% in MA.
I think this is misunderstanding the point. It's not that we can't protect the most vulnerable, it's that we can't protect them particularly well IF community spread is high.
We are partially effective in protecting the most vulnerable, e.g. through restrictions on nursing homes. But, infections in these communities still correlate with the level of community spread - e.g. if you halve the new case rate in nursing homes with restrictions, but you double the new case rate in the community, you may be back to where you started.
The point being, as you allow significantly more spread in lower risk populations, you'll have a really hard time keeping higher risk groups at their current level of transmission risk (which, in the US, is already a fairly high level of transmission risk).
Another interesting question is, what is the economic impact of those high risk people not being able to leave their homes? What happens to the schools and workplaces where they normally serve?
> A comprehensive and detailed list of measures, including approaches to multi-generational households, can be implemented, and is well within the scope and capability of public health professionals.
That is a rather coy statement. They don't even give us a clue how that could actually work.
> Another interesting question is, what is the economic impact of those high risk people not being able to leave their homes? What happens to the schools and workplaces where they normally serve?
Exactly. This is something I've pondered in thinking through some of these proposals - if one wanted to pursue these policies and actually protect high risk folks, that alone would likely have significant impacts.
E.g. KFF estimated that a quarter of workers are at high risk of severe illness with Covid - https://www.kff.org/coronavirus-covid-19/issue-brief/almost-... - of course, some of these folks will be in jobs amenable to work from home. But, for the rest of them? That's a lot of the workforce either a) temporarily leaving the workforce (oh hello, economic consequences) or b) staying in, and accepting the increased risk from community spread (oh hello, more death).
> That is a rather coy statement. They don't even give us a clue how that could actually work.
Yep, lots of hand waving in that one. It's hard to take this declaration with any seriousness given the lack of substance.
My parents are 80, currently in good health, but definitely at high risk if they caught COVID. They're well-off and like to go out and spend money. Any kind of "focused protection" strategy means they have to stop going out and their spending will plummet. They're not alone; I believe "healthy affluent Baby Boomers" is actually a pretty large group of people in Western countries.
Fortunately we live in New Zealand so they can (and do) continue to go out and spend money without fear.
”who's pretty infamous in the epi community for the fundamentally flawed Santa Clara antibody study - significant statistical issues, a highly flawed recruitment strategy, a side story of his wife recruiting people through a a non-approved side channel....Many of these flaws biased the study into showing a high infection incidence rate, and thus a much lower fatality rate, in the same ballpark as the flu.”
You skipped the part about how it was right. Current IFR estimates are on par with the flu:
> You skipped the part about how it was right. Current IFR estimates are on par with the flu:
For some reason, I assumed that once we got to hundreds of thousands of dead in the US, that people would move on from this.
Even the CDC puts the IFR around 0.65%. And, for example, you've got multiple boroughs in NYC with hundreds of deaths each that have exceeded a population fatality rate of 0.5%. You've got entire countries that have passed 0.1% population fatality rates. And, of course, none of these places have actually hit 100% of their population being infected.
> Moreover, Michael Ryan of the WHO estimates 750M infected globally, which would put the IFR at around 0.1%
This is only useful if you also estimate deaths, otherwise you are comparing confirmed deaths against estimated cases. Given the level of missed covid deaths, this only works to downplay the fatality rate.
This is an odd resource, at least with respect to IFR. I didn't look to see if the CFR section was more reasonable. They don't date the commentary in the IFR section, but it seems like it's mostly March/early April? If so, we obviously know a lot more since then.
> We could make a simple estimation of the IFR as 0.35%, based on halving the lowest boundary of the CFR prediction interval in Europe.
I mean, sure, maybe an ok guess way at the beginning.
> In Swine flu, the IFR ended up as 0.02%, fivefold less than the lowest estimate during the outbreak (the lowest estimate was 0.1% in the 1st ten weeks of the outbreak).
We simply weren't doing the surveillance needed for the 2009 H1N1 pandemic during the pandemic to have reasonable estimates for quite a while. We are doing much more of that for Covid - we have serology studies, and we have fairly accurate death numbers (at least in some countries), the key pieces to put together more robust IFR estimates. We didn't have those for H1N1. I also find it a little odd this page just generically references it as Swine flu, vs being specific about it being the 2009 iteration of it. I'd expect that from a news outlet, not an Oxford associated group.
> In Iceland, where the most testing per capita has occurred, the IFR lies somewhere between 0.03% and 0.28%.
Iceland contained their outbreak (yay!), and had very few cases overall, and just 10 deaths. Their CFR is 0.28%. Given their massive amounts of testing, it's hard to understand where the 0.03% comes from (and, obviously, is wildly low). But mostly, there were so few cases in Iceland that's it's hard to draw many fatality rate conclusions.
But mostly:
> Antibody testing will provide an accurate understanding of how many people have been infected so far, and permit a more accurate estimate of the IFR.
> *Estimating CFR and IFR in the early stage of outbreaks is subject to considerable uncertainties, the estimates are likely to change as more data emerges.
Seems to be consistent with this having been written up in March/early April. Since they haven't updated it, and the reasoning even at the time was fairly poor, this doesn't seem a useful resource (at least for IFR).
The COVID IFR is very strongly dependent on age. The U.S. median age is 38, the UK median age is 40, and the world median age is 30.
8-10 years difference in median age is an enormous difference in the proportion of 70+ in the population, and an even bigger difference in 80+. This is a huge part of the reason that you haven't seen the death toll be nearly as high in developing countries as in developed countries. In general, developing countries have a much younger population.
Sure that's a factor, but how do you account for Ecuador with a median age of 28 and a higher per capita death rate than the UK or USA? Ecuador has less healthcare capacity but that can't account for the whole difference. Conversely, Sweden has a median age of 41 and a lower death rate.
It's a statistical association, not a rule. I can't say specifically why those two countries have had the results that they have, but the age dependence holds both at the individual and country levels overall. That also doesn't mean that you can't find a 100 year old survivor and a 20 year old that dies from it.
”Even the CDC puts the IFR around 0.65%. And, for example, you've got multiple boroughs in NYC with hundreds of deaths each that have exceeded a population fatality rate of 0.5%.”
No, it doesn’t. You’re cherry-picking old data, and ignoring the links I gave you, which tell you the updated numbers:
The old reported numbers in New York are not a counterargument: we now know that number of cases was drastically under-counted, and the inferred IFR, if you use the right denominator, was a fraction of a percent.
You clearly know this, because you’re trying to talk about the rates in “boroughs” which are higher. But sample heterogeneity matters: I’m sure if you compute the IFR in Maimonedes ICU, it’s really high, too. The fact is, the fatality rate estimated by the Santa Clara study has been shown to be correct, and you’re simply spreading misinformation, because these new facts aren’t as scary.
These things are facts. Downvoting and brigading don’t change them.
Calculate the overall IFR from these numbers given the age breakdown of the population of the US, and you'll end up a bit above 0.6%, which is what I said (when referencing 0.65%). Your link explicitly confirms what I said.
> The old reported numbers in New York are not a counterargument: we now know that number of cases was drastically under-counted, and the inferred IFR, if you use the right denominator, was a fraction of a percent.
You misunderstood this. When I referred to NYC boroughs and countries, I was referring to population fatality rates. Those are independent of case rates - it's a measure of what percentage of the entire population of an area has died, independent of infection spread. They help set baselines.
> You clearly know this, because you’re trying to talk about the rates in “boroughs” which are higher. But sample heterogeneity matters: I’m sure if you compute the IFR in Maimonedes ICU, it’s really high, too. The fact is, the fatality rate estimated by the Santa Clara study has been shown to be correct, and you’re simply spreading misinformation, because these new facts aren’t as scary.
That's fine. We can look at entire states. 0.18% of the entire population of New Jersey has died from Covid. 0.17% of the entire population of New York has died from Covid. And does anyone think nearly the entire population of NJ or NY has been infected already? No. Even in NYC, we've only seen a couple of boroughs that have shown around 50% antibody positives, with most in the 20-30% range. And, of course, incidence rates in the rest of New York state are lower than NYC. What does this mean? With 0.17% of the entire population of NY state dead from Covid, with incidence rates generally at 1/5 to 1/3 of NYC, with incidence rates lower in NY outside of NYC, the implied IFR for NY state is north of 0.5%.
With all that said.. you sourced a CDC resource that puts the IFR of Covid-19 above 0.6%. You used it to support a claim of Covid having a similar IFR to flu. Given that your source actually confirmed the IFR I mentioned, does that change your stance?
”That's fine. We can look at entire states. 0.18% of the entire population of New Jersey has died from Covid. 0.17% of the entire population of New York has died from Covid. And does anyone think nearly the entire population of NJ or NY has been infected already? No....And, of course, incidence rates in the rest of New York state are lower than NYC. What does this mean?”
Any number of different things: it could mean that the deaths are overcounted (which seems likely in any case; we keep finding examples of “covid deaths” that are better described as “deaths with covid”). It could mean that there’s uncertainty on the IFR estimates, and it’s a bit higher than the point estimate. It could mean that New York City has a higher percentage of elderly and poor people who died at higher rates than average, which you can’t extrapolate to other populations. It could mean that the virus burned through the most vulnerable population already. It could mean that policy and medical decisions made early on in the pandemic were tragically misguided.
Or, it could be some combination of the above.
Point being, the Santa Clara study was a lot closer to right than wrong, and dismissing it, and the people involved, because of politics and methodological mistakes is a cheap shot.
When it came out, the media and “experts” were routinely claiming that this virus had a fatality rate as high as 3-5%. So I don’t particularly care if they were off by a factor of 3 (~0.5%); they were much closer to correct than anyone else at the time.
Yes, it can mean lots of different things, potentially, which is why it is useful to look at factors that may have impacted implied IFRs. E.g. is the population you are studying older than the national average (NY: about average for percent above age 65). Is the population unhealthier than average, e.g. looking at obesity rates (NY: significantly lower obesity than the national average). You want to look at how many deaths were in nursing homes vs not, to see if policy decisions meant disproportionate impact in high risk populations (NY: one of states with the lowest percentage of deaths linked to nursing homes). So many factors were either neutral for NY, or suggest that NY's IFR would be lower than the national average. But, one also considers that NY was stretched thin, which no doubt meant non-ideal care for many people, so that likely countered some of the advantages NY had had.
You also then want to compare with other serology studies, and the implied IFRs from those studies - are we looking at outlier numbers, or does it generally align? Outliers can help uncover factors that were missed, or flaws in the study itself. And that's the thing, all of the NY numbers have suggested an IFR above 0.5%, potentially upwards of 1%, which is broadly in line with other IFR calculations from other places.
> Point being, the Santa Clara study was a lot closer to right than wrong, and dismissing it, and the people involved, because of politics and methodological mistakes is a cheap shot.
> When it came out, the media and “experts” were routinely claiming that this virus had a fatality rate as high as 3-5%. So I don’t particularly care if they were off by a factor of 3 (~0.5%); they were much closer to correct than anyone else at the time.
This is just flatly wrong. You've conflated case fatality rates with infection fatality rates. The general consensus around the time of the Santa Clara study was that the IFR for the US was most likely in the 0.5% to 1% range. The 3-5% numbers were referring to case fatality rates.
"The NY study, if it holds up, suggests an IFR in the 0.8-1.0% range for NYC (depending on whether or not you include the additional excess deaths), which is in the range most experts have been assuming (0.5%-1.0% has been a common range that's been tossed around)."
You'll note April is also when the Santa Clara antibody study was released.
> they were much closer to correct than anyone else at the time
If the best science at the time of the Santa Clara study was estimating an IFR of 0.5-1%, and the Santa Clara study estimated 0.12-0.2%, and the current CDC estimate is 0.65%, who was closer to correct?
> Herd immunity describes the point at which a population is sufficiently immune to a disease to prevent its circulation.
These are very different definitions. If a disease spreads through the whole population (i.e. everyone eventually gets it), then herd immunity was never established, regardless of the infection rate.
Stop this please. Herd immunity is not a well-defined term [1]. Their definition is just as valid as yours.
"i.e. the point at which the rate of new infections is stable" is a perfectly fine assessment of herd immunity.
That paper certainly does not admit their definition. The abstract is very clear:
> A common implication of the term is that the risk of infection among susceptible individuals in a population is reduced by the presence and proximity of immune individuals
As I said, a steady infection rate does not imply there is any such reduction, therefore it does not imply herd immunity.
If you have a reference that uses their definition of herd immunity, please provide it.
I would like to avoid devolving into an argument about semantics.
My original point is that nothing about the original throwaway line is wrong per se or indicates that they do not know what they are talking about. I find these sorts of nit-picks odd.
I still believe that defining "herd immunity" as just barely reaching the HIT will confuse readers of the declaration, who will have mostly encountered the term in contexts where it means the disease is no longer endemic.
[0] The social-economic environment and the political consensus behind healthcare, were both contentious in the US pre covid-19 (and arguably globally as well). This has been the case for decades despite changes in the effectively two-party system at various levels of government, and contentiousness has only increased during this time.
[1] With the current variability in the approaches to covid-19 in the world, and without a vaccine that can make it so that those most at risk can not catch it (or the various strands) ever again (assuming that they choose to take one if available with possible trade-offs in mind), I find it very hard to believe that the measures to mitigate the downside risks to spread/death will some how improve anything in regards to [0], and only serve to accelerate/decelerate various socioeconomic trends that were already under way.
Good luck to my fellow citizens stateside, I long ago made my choice in regards to [0] (now in a jurisdiction where the government's ability to enforce anything has always been extremely limited compared to a lot of "first-world" countries) which was going always going to resolve itself one way or another and I didn't want to be around to face the extreme downsides of such.
So, the POTUS has caught it, along with many high-profile officers, who are both high-risk group and the group of people who should be protected from deadly virus in a functioning country. And yet the president is having a rally with hundreds of people at White House with no social distancing.
And we are somehow to believe that there's a plan to identify and protect vulnerable population while keeping the rest of the country running normal?
All the talk of "virus or economic doom" is false dichotomy - the truth is that America had a total leadership failure, which cost us both lives and economy, and now that it's everywhere and we aren't even pretending to trace the spread, we're stuck in the trench, and there's no way to get out. We can either stay at home, ruining economy, until vaccines arrive, or we can pretend the virus is gone, reopening, inviting the second wave, thereby killing more people and also ruining economy.
I live in Contra Costa County (east bay, SF area), with a lot of retired people. 1.1 million residents. We’ve had 224 deaths with COVID so far. In the US, death rates are pretty flat (not fluctuating much with cases), and of the 198k deaths in the US, only 16K were younger than 54 years of age.
Does that sound like a pandemic? Is it reasonable to shutter most of our economies for those numbers? Can we not have different regulations for those with elevated risks?
Earnest questions.
People are suffering economically and emotionally because of stress and isolation.