Please don’t misrepresent my posts. I never – never, ever – said that I believed one venue was ten times as infectious as the other. What I said was that one venue could be more infectious than another – meaning have a greater base level of infectiousness because of things like density and duration, or mask wearing or not, or lowered inhibitions – and yet still contribute less to overall spread in the community. When asked how that was possible, I used round numbers for the sake of argument to illustrate the point. If that method of reasoning is lost on someone, then I don’t know what to say. There is nothing illegitimate about it, and to say that it reflects a belief that the numbers are real measures is to misrepresent what I said.
So when I argued that “greater level of infectiousness” is probably closer to 1/100 than 1/10 and you said “nuh-uh” and
with no actual cite, you were doing exactly what, other than making things up?
Feel free to back up your feelings, or continue to make up numbers to feel better about your position. Neither matters to me, because it’s blatantly clear there’s no avenue for honest discussion here.
Let me get this straight. You think it’s clear, somehow, that if we could know the real measure, in some empirical way, it’s ‘probably closer to 1/100 than 1/10’ and you think it’s me that’s making things up? You think that’s honest discussion?
I don’t know what the real measure is. I’m certainly willing to concede that all other things being equal, time spent in a nightclub carries more risk of infection than the same amount of time spent in a grocery store. But I don’t know if it’s ten times more. And I don’t know if it’s 100 times more. If you asked my guess, I would guess closer to ten times than one hundred. But I’m not going to tell you that I have any empirical data to base that guess upon. I was wondering if you did for yours.
But if you want to look at some attempt at an actual multiple – though of course it’s based on a model and not empirical observations, with all the limitations that entails – you can look at item “c” in figure 5 here:
https://www.nature.com/articles/s41586-020-2923-3/figures/8
There you see their estimates for additional infections compared to not reopening per POI, not per category. So, in other words, what one restaurant would contribute, on average, compared to one grocery store. The differences in that chart aren’t anywhere near 100 times. They are much, much closer to 10, if not half that.
I don’t pretend that this study is the final word on it, or anything of the sort, because I can see the obvious limitations the study has. But I also can see that they are making a strenuous effort to do something besides guess (or I suppose as you put it, ‘make numbers up’), and they aren’t arriving at anything remotely approaching 100 times.
I am very happy to have an honest discussion about it, which is why I asked if you had seen something that would support a multiplier of 100. In fact, I’m still eager to consider it if you have. Have you? Or is that just a guess.
On that much I think we can agree.
I have previously asked for a source or sources of information for dates of interventions, levels of interventions, demographics of different geographic locations, and compliance within those geographic locations. That kind of information is the detail needed to piece out the kind of detailed analysis you are insisting on - a level of detail that probably needs a federal grant to dedicate time to do fully. I sure hope someone is doing that somewhere, but I’m not the guy.
I am well aware that a seasonal variation is a possibility. We are just now approaching one year of this disease. We simply do not have the data to assess any seasonality. Sure, we can compare across the globe to see if patterns emerge, but then we get into those complicated factors that you point out make pulling out trends difficult.
But the basic trends of data are clear. Composite numbers for the US match pretty damn well what the experts predicted.
We started a spike early, so we implemented heavy shutdowns, mostly in the large urban areas where the spikes were occurring. Cases and deaths dropped. We then began a supposedly slow, incremental, controlled reopening that in a lot of places was fast, somewhat incremental, and not particularly controlled. Numbers of cases and deaths rose - as predicted.
We then had a cycle of trying to tighten up a bit at the end of summer, with some drop in numbers, followed by the reopening of schools and reductions of limitations in other areas. Cases and deaths increased. Then came Halloween and people partied and numbers took a bump. Then came Thanksgiving, and people decided to visit their families and friends, and we got a increase. Next came Christmas, which is moving things upward, followed by New Year’s, which we haven’t really seen the impact from yet.
But the trend is clear. The numbers are soaring. Hospitals are facing bed and staff shortages, ambulances sit hours with patients in them to get admitted because there is no room. Morgues and funeral homes are filling up. I just saw one funeral home in S. Cal. that had the chapel stacked with full caskets and the proprietor said she has probably turned down a thousand families because they can’t fit them in. Even if that is an exaggeration, cut that by a factor of 10 and you still have 100 families turned down.
Meanwhile, yes we have a vaccine rolling out - slowly. We also have more and more people openly defiant about not wearing masks. We have more people resisting control measures. And the case counts and deaths match that behavior.
Frankly, that you can’t see that pattern is puzzling. You’re looking for a seasonality pattern when you can’t even see the direct correlation between behavior and cases/deaths.
Believe whichever fits our preferred agenda? Or maybe see what else shakes out of the science tree before drawing a conclusion? Maybe constraining behavior based on the more dangerous assumption until the science gets sorted out?
You have yet to propose an alternative approach. The default alternative is fully reopen. Is that your plan? If not, tell us what is it you have in mind.
You are correct that there is a massive tragedy beyond the deaths and the permanent impacts of the disease on the ones who catch it. The damage to our children’s education is significant. The loss of jobs and businesses is terrible. The economic hit is tough.
But the economic hit was going to be tough. The thing is, the solution we ended up with is a piecemeal inadequate approach. I fully agree we ended up with a partial solution that has had devastating impacts. But I feel the better solution would have involved a massive government financed shutdown for a controlled period to kill the transmission, followed by a reopening with heavy testing and strong contact tracing and quarantining. Sure, that would have been expensive, too, but look at the damage you so rightly lament and tell me that my solution would have been worse.
I’m saying we should have taken a controlled hit that kept paying people to shut down. Pay businesses to go on hold, pay their employees to stay home. Then be able to get things rolling again while simultaneously controlling the spread of the disease. Which would also have probably meant opening schools and restaurants and bars, maybe with crowd size limits.
We didn’t do that.
But that doesn’t mean reopening everything right now is the solution, either. That might start to improve the economic problems, but the cost in lives would surely escalate, and the system is already stressed to the limits.
As for whether the things we are doing are having any impact on the disease, I simply disagree. The epidemiologists are the ones suggesting those controls. They’ve recommended stronger versions in a lot of places, but those have not been followed - starting from the President of the United States setting the tone. The population as a whole has tired of restrictions and started defying them. See Thanksgiving, Christmas, and New Year’s for examples. See mask compliance dropping.
And once again, I implore you to tell us how you would fight the spread of infection right now until the vaccines can get spread enough to improve things.
Well, tell me what you make of Florida…South Dakota…Iowa. Are there chapels there that are turning away a thousand families? I mean, you seem to be painting with a broad brush, all across the United States. Do you think it’s fair to look at jurisdictions that have relatively few restrictions and compare their situations?
FWIW, your link above has little radio buttons you can toggle to see the effects of various venues on the infection rate. Restaurants are by far the highest risk on there.
Why do you keep asking about Florida? Their cases are climbing. They had a lockdown early in the pandemic like everyone else. There are restrictions by county like everyone else. The only difference is that the governor is making a fuss about some of the restrictions some of the counties placed. De Santis just lifted penalties for the bans and put some restrictions around some of the bans, but the bans are still in place. Besides De Santis being in the news all the time, what’s remarkable about Florida?
I’d start with the difference between Florida and California, if you’re looking for something remarkable.
Could spell out the differences between CA and FL and why you think they’re so remarkable, along with the numbers for those differences?
I guess we could, but we’ve just been given some hard data from another poster in the thread, about funeral homes in California turning away a thousand families, and we don’t have those same reports from Florida. The remarks are already being made.
Because no one but you is talking about Florida. Do you have some other data from Florida?
Florida has a death ratio around half that of the worst-hit parts of the country, states that have had and continue to have more in the way of restrictions than Florida has had for the past several months. Florida has a trajectory at present that is not as severe as that of California, a state with far more in the way of restrictions.
In relation to California, it is the absence of data that is remarkable. The ambulances aren’t queued up for hours in Florida, they aren’t stacking caskets in the gift shops and building makeshift morgues, and the waiting list for funeral services is not a thousand families long. Unless those stories have gone unreported, that is.
Any data for that? Having read your numbers before, I won’t be taking your word for that. Also, the population density figures would help too.
Just the deaths-per-million stat over at Worldometers. Today it’s showing 1074 for Florida, with New Jersey and New York over 2000. California has been running 550-600 deaths reported on recent days, Florida a fair amount under 200 most days. California has a little under double the population of Florida.
I don’t pretend that’s a rigorous analysis, but the rough numbers paint a clear enough picture.
Okay, so I dug in to that study a bit.
I don’t see anywhere where they discuss their Susceptibility Exposure Infectious Removed model and what those terms mean and how they established those numbers. Maybe it’s buried in the part of the report with all the math. I just don’t feel like digging in to all that. But that’s a quibble. I will accept for this discussion that that model makes sense.
For looking at all the comparisons, I will point out they provide no data whatsoever for clubs or bars as a class, so we can’t use this study to measure them.
You said to look at plot c, the effect of each Point of Interest (POI). (Yes, I had to look that up, as well as Census Block Groups - CBGs.) That puts full-service restaurants as the second biggest effect behind hotels & motels. Using the interquartile median (yes, I had to go look all that “interquartile stuff” up too), FS restaurants are about 0.65 per 100k. Grocery stores are about 0.03 per 100k. That’s about a factor of 22.
Great, not 100. But I disagree that is the correct comparison. Look at plot d, additional infections per class. FS restaurants are way higher than any other listed class. FS restaurants are about 7,000 per 100k. Grocery stores are about 210 per 100k. That’s a factor of 33.
Okay, again not 100. Glad we established that. Now go on to look at the second part of your assumptions, how time spent and crowd size affects the numbers based on POI class.
Look at Figure 2 plot d of the report. FS restaurants have a much more significant impact on additional infections than any other category listed (which doesn’t include bars, so we don’t know how they compare). FS restaurants is right around 7,000 additional infections per 100k people compared to not reopening. Number 2 is fitness centres (their spelling) at about 2,000. Grocery stores comes in at around 230. That’s around 30 times worse for FS restaurants. Limited service restaurants are still around 1,000.
And what does the description of the figure say?
From the discussion paragraph:
What about model limitations? From their Supplementary Information (.pdf)
Mask wearing and ventilation - two big differences between grocery stores and restaurants and bars.
So, after all their analysis, what is their recommended strategy?
More stringent caps on occupancy. Food distribution centers. Free and widely available testing. Improved workplace prevention such as PPE and ventilation and physical distancing. And improved sick leave or income support for sick workers.
Any of that sound familiar? Like maybe metering at grocery stores, mask mandates, work from home, paying people to not work, especially when sick. Limiting group sizes. Reducing non-essential gatherings. You know, all the things that the Coronavirus Task Force recommended and Dr. Fauci has been advocating. All the things Americans are failing to do.
That’s good analysis of the study. I like it! You’ve made some excellent points.
There is still more to it, though, as I’m sure you yourself gleaned too. One of the big motives of that study was to look at disparity in risk between socioeconomic groups, and in so doing they found that a ‘grocery store’ is not a grocery story is not a grocery store. I believe that their model found that grocery stores in one of the cities, I think Philadelphia, were about ten times as risky as those in other places. (Or maybe it was just grocery stores in less affluent areas versus more affluent areas, but the point still holds.) The reason being, of course, that grocery stores in those areas were smaller and denser and people spent more time there, and that’s really all this particular study is concerned with.
Me, I think a major drawback of the study design is that they break up ‘retail’ by sub-category after sub-category after sub-category, from womens’ clothing to kids’ to used to new and so on, but a restaurant is a restaurant is a restaurant. It’s just not apples to apples, because most people think ‘going out shopping’ or ‘going out to eat’, they don’t think ‘going shopping to a used shoe store’ or ‘going to eat at a Thai place’. It would have been funny if they had made a separate category for each type of cuisine! Then we could have found out if pizza is more dangerous than falafels.
They also simply got rid of all ‘parent’ categories, like ‘shopping malls’, because otherwise they couldn’t figure out how not to count each venue inside twice. But again, people think about ‘going to the mall’, not ‘going to that one pet store in the mall and nothing else around you counts’.
There are further limitations on the way they approached things, too. Did you read the part about the tests they did to see if density and duration were the right parameters for the model? It’s because when they tweaked the model they got results that didn’t make certain places, like restaurants, as dangerous as these certain two sources said they were, so they dismissed those out of hand. Well, for one thing, that’s tautological, as far as I can see, and it calls the entire study into question. But what’s more, you should see the two sources they chose… I mean, really! Look them up. It’s embarrassing. About as far from rigorously scientific as you get. It’s like ratings of 1 to 5 on danger level for broad categories, in infographic format, published on a website by a couple professors, with suggestions to print and hang around town. With no data or analysis included. None. I mean, really, you can’t make this stuff up. They based this entirely mathematically rigorous model on a premise that itself includes no scientific or mathematical rigor at all.
Your chart shows 1,074 deaths per million for Florida and 769 deaths per million for California. According to you, Florida has less restrictions and more deaths per million than California. That’s unsurprising. What is your point in comparing FL and CA?
My point is that the trajectory California is on is not good. Not good at all. In fact, it’s very bad. It’s much worse than that of Florida. And if it’s true that reopening is very dangerous, you would expect exactly the opposite.
I brought that up because you previously said Americans were smart enough to notice bodies piling up in the streets. I’m pointing out once again that we aren’t piling them in the streets, we are piling them in refrigerated trailers and funeral homes. Sure, not everywhere is as bad as S. Cal.
Check out this from IBISWorld about funeral homes in Florida.
Bolding added.
Or this - excerpts:
So, maybe the stats aren’t quite as clear.