I didn't want to get into a game of who has been most wrong, because that will automatically trigger people to go back to their camps and hunker down. I agree that the "isolate the vulnerable, continue with life otherwise" is most likely the best outcome. The fact that this idea is attributed to the right is going to mean it is DOA, for the most part.

The main problem youi'll have with that is that many people assume that the value of a human life is infinite and we must expend all resources possible to save individuals. Neither of those makes for good economics, so folks who include economics and balanced risk into their equations often conflict with folks who want to take the "safest possible action with respect to human life".

The safest possible solution would be for the super wealthy pay to keep the population fed and housed while we wait for a vaccine or improved treatments. Otherwise, the virus will continue to propagate, the poor will have to risk their lives and the virus will inevitably reach the rich and their families in a later wave anyway as was the case with the 1918 flu.

Addendum: I posted this fully understanding how unpopular it would be with this crowd. If we ever get hit with a a more fatal and contagious virus this may be our only way of preserving life. And as things stand with our industrial meat processes I suspect we will have more viruses to contend with.

I can't tell if this is sarcastic or not, but I will assume it is not.

It is not this simple. You can't, in our current system, shift wealth that readily and quickly. Even if you could, how would you approach possibly selling this in a democracy? And assuming it was feasible, and we could get popular support for it, how would it be implemented? Rationing cards? Government ran food stores?

This is NOT the Spanish Flu. It is very different in its behavior. There is currently no evidence to expect a more deadly, virulent second wave. Please remember that the Spanish Flu was anomalous because it had a more deadly second wave. Almost all viruses, as a function of evolution, become less deadly over time.

And this ignores all of the vast improvements in our understanding of sickness and hygiene, our availability of clean, sanitary conditions etc. Hell, even the change in density between 1918 and 2021 is massively changed.

> You can't, in our current system, shift wealth that readily and quickly.

The Fed seems to be doing just that

One way would be to have a monthly payment similar to Trump's $1200 [stimulus check] every month. The government can later recoup that through more equitable tax policies on the ultra wealthy and massive corporations.

This has been proposed by legitimate legislators. https://twitter.com/SenSanders/status/1270000771132731397

As for your claim to a lack of a second wave, I'll have to defer to the experts on that. I'm looking at a historical case for a worse case scenario which I think is prudent to consider.

I don't know what Trump's $1200 monthly payment refers to, the welfare payments came from the us federal govt and state govts. A better reference is Andrew Yang's proposed $1000/month payment.

Understandable. Partisanship is the scourge of our generation.

i would like to know how to "isolate the vulnerable"...?! We send to an island? we weld inside home? We should talk only if we have a realizable plan and not a "dream/idealistinc" plan.

Well we were able to somewhat effectively isolate the entire country, so I would say have modified stay-home orders that target those who are most vulnerable. That, in addition to common sense acts like hand washing, isolating the sick etc. would go a long way to flatten the curve enough to not overwhelm the hospitals, which after-all was the original goal.

The problem is that you can't isolate the most vulnerable fully. The current lockdown works because it reduces the spread through the wider society, including all the people who are in contact with the most vulnerable. If you don't do that, then we have the Sweden scenario where inevitably there's someone young and fit and infected who brings the disease into the institutions that should be protected, because these young and fit and infected people work there or go there to deliver things.

Alternatively, you need a total quarantine isolation - e.g. anyone working in a care home should live there and can't touch their kids if they go to a school where will be spread because everyone else's parents are not on lockdown. Or the most vulnerable will die.

And has been widely discussed, Sweden has had a lot of excess deaths. Look at death rates compared to Finland, Norway, Denmark.

An interesting game theoretical interplay has been an almost irresistible force that draw almost all democracies towards the same behavior: if it was possible for 100% of confidence to separate the group of people at risk from the people whose risk factor is small (e.g. pick some threshold like smaller than the risk dying of any other cause), then sure, it would have worked.

But the moment a number of apparently healthy and young people start dying from it, people start thinking thateither a) it's hard to know in advance whether you're at risk (e.g. unknown pre-existing conditions) or b) the disease is stronger than previously thought.

And that's even if the actual cause has nothing to do with (a) or (b), i.e. if the data was just a statistical fluke or misattributed deaths (e.g. people dying from X who also had sars-cov-2 in their system). It doesn't matter; there is no time to get to the bottom of things. The authorities have to play it safe, least they will be proven to have acted recklessly. And even if they try to be "brave" and plow ahead, the public opinion will quickly sway towards playing ir safe.

This seems to be an especially strong force since people today have an unprecedented capability of communicating and broadcasting "gossip". Even China's strictly controlled public communications wasn't able to censor spontaneous outrage from the citizens. And the fact that China reacted they way they did, set a high bar; any country that wanted to act differently had to be play it pretty convincingly to their populace (e.g. "we can do it, because we're different, we are so disciplined we can pull it off")

For example, consider Sweden's approach. I have no idea whether their strategy is right or wrong, how should I know? experts disagree.

But it surely takes a lot of confidence to pull that off, knowing that opposition parties will feast on any opportunity to publicly decry your recklessness.

Covid-19 is real and it kills people, it's effects can be and will be measured.

We do make tradeoffs between economy and safety all the times, but we do that for things we're used to (traffic, pollution, diseases prevention, ...), so some people expect we can do the same kinds of tradeoffs with covid-19.

Again, I'm not an expert and have no idea on how to compute such a tradeoff.

But my point is that there is a inanimate force that is just pulling that card off the table.

It doesn't help that in some countries it also became such a heavily partisan topic.

I'm not from the US. I live in a country whose government has been very proactive and the population is generally supportive of the (re cently lifted) lockdown. And that's a country where rarely the populace has anything good to say about the government (a popular saying "it's raining, damned government!")

Playing it safe seems much more effective politically, that unless you want to play some "strong man" narrative like some governments did, there doesn't seem to be any advantage in taking excessive risks.

That raises the question of how to identify the sick. SARS-CoV-2 infections can be transmissible before the infected shows any symptoms, if they present at all.

Personally, I don't feel that there are many population centers in the US that are prepared to do the kind of testing that seems like would be needed to properly identify the sick.

Apparently this is not really the case any longer: https://www.cnbc.com/2020/06/08/asymptomatic-coronavirus-pat...

> i would like to know how to "isolate the vulnerable"...?!

We could start by NOT sending people with confirmed COVID-19 infections to live with them.

There are a lot of empty hotel and dorm rooms right now so that would be a good start. A lot of those who have died so far were infected in family homes with many people living in close quarters. We should focus our limited resources on providing safe living spaces where those at highest risk can isolate themselves if they voluntarily choose to do so.

No country has successfully done isolation of vulnerable, while there are many countries that have successfully eradicated or at least brought it to extremely low levels.

With cheaper testing, pooled testing protocols, etc. we could potentially test every household in the US every couple of weeks for less than we spend on auto insurance.

You can do both. Iceland isolated their older population quite well.

Sure, but if you do both, isolating the elderly becomes easier because there is less prevelance and slip-ups are less likely to cause issues. It is a totally different strategy than what he was saying. The US stopped nursing home visits as partial form of isolation.

To fully isolate you would need workers to go through quarantine periods before entering on shifts. Many vulnerable live at home so you'd have to provide support to isolate their cohabitants as well or something else. Physician specialists that serve vulnerable and non-vulnerable populations without enough overlap to split duties with similar doctors between both populations would need to operate inside a bubble boy setup or something.

The vulnerable also include people with pre-diabetes, heart conditions, etc. that may not be diagnosed, though maybe you just treat them as those not to be isolated.

This requires a citation. It's intuitively far easier to quarantine 1% of the population than 90+%.

To protect 1%, you need to isolate them absolutely from everyone else who will be infected.

To protect 90%, it's sufficient if you reduce the rate of spread below 1, which means that it's sufficient to have a (realistically achievable) "quarantine" that reduces the number of contacts 3-4 times. It's possible to have much less contact with people, it's very limiting to have no contact at all.

There's a huge world of difference between the contact limitations required for a true quarantine (essentially, zero contact) and what "lockdown" has meant in most places, with most people continuing to work with other people just with much less contact.

It's not at all clear to me how much more limiting the isolation required for the 1% is than the current quarantine measures. I certainly doubt that it means "no contact at all". It's also not clear to me that a very strict isolation for the 1% is overall better than a moderately strict "quarantine" for the remainder (trolley problem). It's also not sustainable to maintain quarantine indefinitely, and the economic ramifications alone will compound (exponential--not linear--decay). At some point, "quarantine" becomes a net negative for the vulnerable 1%, never mind the remainder. Further, as so many things do, these economic impacts are and will continue to be the most severe among the most economically vulnerable. It's certainly sustainable for 1% of people to isolate indefinitely; it's not sustainable at all for the rest of society to quarantine indefinitely and that sustainability falls off earlier for the most marginalized communities than it does for the rest of us.

I mean isolation of vulnerable while letting infections elsewhere raise to saturation. No (non-micro state) country has gotten close to saturation/herd immunity yet.

I'm not sure if you're trying to refute my post or support it, but your comment certainly supports my point. No country has gotten close to saturation/herd immunity yet, and it would be economically ruinous (and not uniformly so) to maintain current quarantine measures until we get there.

I’m saying there is no one to learn from, no one did that strategy yet. The UK almost did.

> the right has been pretty consistent about tailoring the response according to risk

Have we forgotten that "this is all a liberal hoax"? Remember HCQ is a cure-all? That's not being consistent--that's completely ignoring science.

The right in the US has been consistent about tailoring its message to AI driven talking points that drive social media engagement. Nothing more.

How about a "free market" solution? Give everybody who earns under $40K a year $2,000 per month unconditionally for the next 6 months. And let businesses reopen. Now, people who want to can go back to work and have a $2K bonus per month on top. Or they can forgo that and sit at home.

Let's see how people actually vote with their feet and wallets.

This, and so much more of this.

I was very careful to mention that the right was correct about this one point. I was hoping to dissuade this kind of overtly partisan reflex post. Clearly I failed.

A stopped clock is correct twice a day--we don't suddenly consider its accuracy improved.

Trying to thread needles like this is disingenuous, at best, and makes you look like an apologist, at worst.

You have a set of political leaders actively hunting for a hook that is sufficiently platable and plausible that they can get people to swallow in order to be exploited for their own power gain. Giving cover to that deserves neither praise nor quarter.

There are plausible solutions that have scientific backing. There are also plausible economic solutions. There are also degrees to those solutions--Switzerland shows this even though it is now matching the US in per capita Covid cases.

NONE of those solutions that would benefit the people have been proposed at the federal level here in the US.

Show me where I argued that their “accuracy improved”. Like I said in the previous post, I’m only noting that they were correct in this instance. I’m certainly not making arguments that Trump’s administration is doing a good job.

> In fairness, the right has been pretty consistent about tailoring the response according to risk—i.e., those who are at risk should isolate and everyone else should resume work.

I don't think that was being consistent about "tailoring the response according to risk [from the virus]," but rather being consistent about tailoring the response to pre-existing policy preferences. An ideal lock-down requires significant temporary bottom-up government economic intervention, which the right opposes on principle. The policy of "those...at risk should isolate and everyone else should resume work" fits nicely with existing right wing ideas: keep government intervention to a minimum by maximally individualizing health burdens. The difficulty is that might not actually attack the problem very well.

> tailoring the response to pre-existing policy preferences

Well, that's true of the left as well. A "bottom-up government economic intervention" fits nicely with existing left wing ideas.

> Well, that's true of the left as well. A "bottom-up government economic intervention" fits nicely with existing left wing ideas.

That's true, but the different political ideologies are better at handling different kinds of problems. Public health emergencies like this one are the kind of thing that benefits from a properly-resourced, centrally coordinated response; a solution that happens to lean left.

Each side would of course argue that its own methods for handling each kind of problem is superior.

The US never went into an actual lockdown in most places.

"Lockdown" is New York where R0 is 0.75. "Lockdown" is not California or Texas where R0 basically sits at 1.0.

R0 of 0.75 after the last 3 months would basically mean Covid cases in the single digits basically everywhere in the US. But, no, we can't actually get people's attention before we start piling body bags in the streets.

The people in the US who are "Open all the things!" are also the "I'll be damned if I'm wearing a mask." Ummm.

You can argue about the finer points all you want, but when you can't get people to do the basics, you're sunk.

Do you have a source for your R0 values? As far as I know there have been no per-state R0s released, though current estimates put ~20% at antibody positive [^1] in New York meanwhile Texas has a very low infection rate in comparison.

This likely has much more to do with relative densities than lockdown strategy. Texas is low density, and it was necessary to have looser restrictions in many areas due to distance to essentials like groceries. And indeed for Texas this seems to have been a fine call.

And Texas still has a declining rate of new cases despite continuing to reopen, and we have been in a decline for over 30 days despite bars and restaurants being open.

The complaints against mask wearing have primarily been against legal mandates. I wear a mask but I don't support fining or jailing Americans if they choose not to, especially since they are likely to be old, poor or a minority.

I don't believe anyone has been piling bodybags in the streets, though it's an excellent scaremongering claim. Remember lockdown was planned for a few weeks to flatten hospitalization rate - which it did.

[^1]:https://www.wsj.com/articles/the-numerical-language-of-covid...

You can get per state R0 values. rt.live is a website (that is not part of russia today), the RT url comes from "R0". It's from the people that sold instagram to facebook.

They do have per state R values. This does show that NY is at about 0.8. Texas is 1.02 currently. The one negative with their calcs is their R values seem too sensitive to daily conditions. It's a great visualization of infection rates too, please look at that.

To look at the daily infection numbers, find Texas, click on the "show new cases" tab. Texas has about 1500 new cases per day now. They've had a steady increase in new cases per day since mid April, when they were about 750 new pos cases/day. They are really growing. I'm not sure where your stats about Texas doing well are. It looks to me like the positive cases are unfortunately increasing there steadily, and it's a precursor to increasing hospitilization. I have family there, I'm increasingly concerned.

They get their data feed from https://covidtracking.com/api/v1/states/daily.csv which is downloadable. Look at TX (some days have multiple updates, you have to calculate the delta yourself). US date style, positives: 6/7 74978, 6/6 73553, 6/5 71613, the increases are very clear in daily positive cases; those counts are total pos counts to that date of course.

Another place to see per state (such as Texas) is https://www.worldometers.info/coronavirus/usa/texas/. Go down to 'daily new cases in texas' click on 7 day moving average. They've really been growing per day in new positive cases. One note, different websites show the current day's data differently (some show values that up dated in the middle of the day, others show one day late, so looking at the very latest rhs data point is sometimes confusing).

Texas absolutely shows the potential of opening up increasing infection rates. Alabama is another state that is hurting but reached a top, see Arkansas too. Florida was down but is now showing highest per day infection rates historically (7 day average, looks like new records beating 2 months ago). Some states are better, plenty are getting worse.

The number of diagnosed cases or positive test results is only loosely correlated with the number of actual infections. Thus any calculation of R values based on cases isn't mathematically valid.

> The number of diagnosed cases or positive test results is only loosely correlated with the number of actual infections.

Then that just means that we are likely underestimating R0--possibly by a huge amount. Okay, I agree with you.

Infections aren't LESS than the diagnosed cases and positive test results. So, all the calculations from data about the estimates of R0 are all a lower bound, not an upper one.

As such, our estimates of R0 are likely painting a much rosier picture than reality. Probably not the point you were trying to make.

You missed the point. There are a lot of cases which are never formally counted as "cases" because people recover without ever being diagnosed. We don't know whether that fraction of unreported cases has increased or decreased over time. Outside of a few limited areas there hasn't been enough random population sampling to draw any reliable conclusions one way or the other.

You have just said that we probably have quite a few cases of Covid which are not counted and are not part of the model because they were undiagnosed. I agree.

If we somehow magically started accounting for those cases the R0 would immediately go up (more cases per unit time means increased R0) unless the number of those cases is zero.

Thus, the R0 estimates we have are currently all underestimates. Covid is likely more contagious than we are calculating, not less.

Now, this doesn't matter to the people who recover, of course. And it effectively is correct in that people who simply recover aren't a big problem and so the R0 is roughly "correct" in the aggregate.

However, that incorrect R0 DOES matter when you start talking about vulnerable populations and how far you need to go to protect them.

R0 does not exist outside of context either. We like to think to R0 has being whole numbers. R2, R4 etc. Or small decimals.. R1.5.. But really, _everyone single person that gets infected_ actually lowers R0 a tiny bit, as they are now recovered. Combine this with the late breaking evidence that there is some cross reactive immunity in T cells with other coronaviruses, and we see that R0 is completely meaningless without more data. If R0 is a lot higher, lets say 7.5 or some absurd amount, and we do have such a cross-reactive immunity, herd immunity may come at 40%. See, it needs context.

Ok, so I spent some time digging into their source code. This is a model, and like many models it's output is fully dependent on the input. In this case we're dealing with significant inputs and assumptions tied to factors such as onset, delay, testing correctness and a lot of things we just don't have data for.

I'm going to share some quotes from the code.

> Our goal is to translate positive test counts to the dates where they likely occured. Since we have the distribution, we can distribute case counts back in time according to that distribution. To accomplish this, we reverse the case time series, and convolve it using the distribution of delay from onset to confirmation. Then we reverse the series again to obtain the onset curve.

> We assume a poisson likelihood function and feed it what we believe is the onset curve based on reported data. We model this onset curve based on the same math in the previous notebook

> We calculate this by figuring out how many cases we'd expect there to be yesterday total when adjusted for bias and plugging it into the first equation above. We then have to re-bias this number back down to get the expected amount of onset cases observed that day.

I don't want to invalidate efforts to build models because models are important, but it's also important to frame models as being statistical models and in this attempting to resolve R0 values from self-reported data, across districts with dramatically altered reporting methodology is extraordinarily fraught with peril. Even the model authors indicate this and have made several improvements, and models will naturally evolve over time.

Then let's touch on some of the stats we're looking at. Remember we are dealing with a sampled phenomenon - as our sampling rate changes (the amount of testing we're doing), our case rate will naturally rise. We want more testing because it helps us determine more accurate numbers, but it also means we need to understand we may see spikes in our daily reported cases. We therefore want to be careful with using small samples (3 or 4 days).

You'll also notice we have natural declines that align with the weekends - it's not because the disease takes the weekends off. One of the dangers of reading the worldometers graphs is that they're inclusive of all the data, including data from March/April which is probably underestimate.

Texas started lessening quarantine restrictions on May 16th, and indeed until about the 29th we see a pretty consistent decline (well past any incubation time). From the 30th to today's data (and always take the current day with a grain of salt because reporting isn't always instant) we do see a growth, primarily due to several abnormal spikes in the last week. When we compare that against deaths we don't see those same spikes represented - and in the last two days of the series (excluding today) we see a declining pattern again (but two days a pattern does not make).

So it's wrong to say "Texas has about 1500 new cases per day now. They've had a steady increase in new cases per day since mid April, when they were about 750 new pos cases/day. They are really growing.". The 7 day average keeps us at 1200 or less, with the exception of the last few days.

I pulled the hospitalization data from [^2] (xlsx format unfortunately) and while hospitalizations are technically increasing as a whole, that is almost entirely in the TSA of Houston (though Dallas/Ft Worth and Longview/Tyler show some increase as well) with 19 other TSAs declining or remaining steady. So, I wouldn't be overly concerned for your family, the data indicates things are generally going quite well.

I would be careful in how we read data.

[^2]: https://dshs.texas.gov/coronavirus/additionaldata/

> I don't believe anyone has been piling bodybags in the streets, though it's an excellent scaremongering claim.

New York was. Although the point wasn't intended to be about scaremongering, it was more about how people don't seem to have the ability to pay attention unless life kicks them personally in the balls.

Most people in the Northeast knew someone personally who died of Covid--when someone's Grandma you know dies of Covid, you'll put your mask on and stay locked down so yours doesn't, and you'll get mad about the people who won't.

That's why I chose California, which nominally has a lockdown, to contrast against Texas, which nominally doesn't, to contrast against New York, which really locked down, to show that the US really didn't lockdown very well.

I was in California after the orders--"Hey, we can't hang out inside the coffee shop. I got it! Let's hang out on the sidewalk outside!" <facepalm> Or, "Hey let's have a Mother's Day party"--two of which now account for more than 50% of the Covid cases in Santa Cruz county.

And all this is because we didn't have a unified response in the US to make people pay fucking attention.

And, even in "Open all the things!" Texas, it's not helping much. Most businesses run until they get a Covid case in the employees and then shut down for several weeks--lather, rinse, repeat. So, instead of everybody shutting down simultaneously and cutting down the number of cases, we have individual businesses shutting down hodgepodge which still hammers people's jobs and as a bonus doesn't help bring the Covid numbers down.

Yes, I'm glad we shut down to prevent overrunning the medical system. However, that was just "Step 1".

"Step 2" was not supposed to be "Do nothing else and then throw up your hands in 90 days."

The idea of isolation was most prominently attempted by Sweden, the UK, and the Netherlands.

To call it "right in this regard" is, in this regard, wrong. These countries are leading the per-capita corpse count. In the case of Sweden, deaths are about ten-fold that of neighbouring and rather similar Norway. And people are still dying at peak levels in Sweden, while Norway now goes a week without deaths.

Of course it's "right" to "keep vulnerable people away from danger". It just doesn't work. Elderly people in care homes need, well, care. Also food, and medical attention, and housecleaning, and maybe even social contact. All of those needs are provided by young people. How is this separation supposed to work?

In the Netherlands, I don't think this was even attempted, apart from forbidding visitors.