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Yale study on effectiveness of various covid restrictions.

Sandy Johnson

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I'll just leave this here for you guys to poke holes in:
https://insights.som.yale.edu/insights/study-shows-which-restrictions-prevent-covid-19-fatalities-and-which-appear-to-make-things?utm_source=YaleToday&utm_medium=Email&utm_campaign=YT_Yale%20Today%20-%20Best%20of%20the%20Week%20Faculty_12-5-2020&fbclid=IwAR1zgJy1btP-iCLpTo7NpTFoAawGJjbRKUcQSaOaubqO1e1s6EBwRn8KxpE

November 23, 2020

On November 16, Iowa governor Kim Reynolds issued a statewide mask mandate, a step she had been avoiding for months. “No one wants to do this,” she said. “I don’t want to do this.”

For many policymakers, 2020 has been a year of doing what no one wants to do. The choices brought about by the COVID-19 pandemic are agonizing: do you close schools and businesses, disrupting lives in hopes of preventing infection, or keep them open and hope for the best? What’s better: a mask mandate or a mask advisory? Varying responses to these questions have yielded a patchwork approach, with some states restricting many more activities than others.Part of the challenge stems from a lack of evidence: it’s hard to know which approaches are making a difference, and which may not be necessary. New research from Yale SOM’s Matthew Spiegel and Heather Tookes helps to shed light on the matter, offering new data on which policies prevented—and failed to prevent—COVID-19 fatalities in the United States from March to October.
Learn more
Spiegel and Tookes’s county-by-county analysis examined some of the most commonly used tactics to prevent the spread of COVID-19, including stay-at-home orders; mask mandates; limits on the size of gatherings; and closing schools, parks, and various kinds of businesses, including restaurants, gyms, and retailers.

One clear takeaway: while many of the available interventions work, mask mandates stand out for their effectiveness and relative lack of economic tradeoffs. “Mandatory mask policies seem to be as effective as policies that have higher costs,” says Tookes. (Simply recommending masks, Spiegel notes, “doesn’t do anything.”) In fact, instituting a mask mandate reduces a county’s future fatality growth rate by 12%—about the same, in isolation, as more disruptive measures including stay-at-home orders and closing restaurants.

Teasing apart the effectiveness of each policy required an army of research assistants, who created and continually updated a database of COVID-19 restrictions in every U.S. county. The team also tracked each county’s reported fatalities from the virus.
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Then, Spiegel and Tookes compared counties with and without a particular restriction in a given week —controlling for factors that might skew the analysis, such as demographics, density, population health, climate, and current pandemic severity—to see if there was any difference in their fatality growth rates four and six weeks ahead.

Among the policies that reduced fatality growth rates were general mask mandates, mask mandates for employees, stay-at-home orders, limiting gatherings to 10 people, and closing restaurants, gyms, and parks and beaches.

That last one came as a surprise to the researchers, given the studies showing a dramatically lower likelihood of outdoor transmission. Then again, Tookes notes, “people socialize at those venues, so it could be beach parties and park gatherings that are driving those results.” Spiegel hypothesizes that the closure of national parks, which typically attract tourists from around the country, might explain the pattern.
The researchers also identified several counterproductive policies. For instance, closing low-risk retail businesses such as bookstores and clothing stores actually came with higher fatality growth rates, likely because it pushed stir-crazy citizens toward higher-risk activities, like spending time indoors with friends. “You always have to be careful of what the tradeoffs are,” Spiegel says, “because if you shut down one thing, people then engage in another activity.”

Meanwhile, limiting gatherings to 100 guests—another harmful policy singled out by the researchers—may have the unintended consequence of making people feel too comfortable about inviting over 99 of their nearest and dearest.

The researchers checked their conclusions by conducting two additional analyses. First, they removed the five most populous counties in each state from their data, on the theory that what makes sense for a city may not be essential in a rural community. However, the results were largely unchanged: the same measures help (and hinder) denser and less dense areas alike.

Next, the researchers identified counties that were both geographically close and demographically similar—but had different restrictions in place. These “near-border” counties, they reasoned, might provide an especially accurate “apples-to-apples” comparison. Once again, many of the same policies proved effective.

In other words, across multiple analyses, Spiegel and Tookes identified a fairly consistent set of policies that seemed to help (mask mandates, closing restaurants, stay-at-home orders, limiting gatherings to 10 people) and a fairly consistent set that seemed to hurt (closing low-risk businesses, limiting gatherings to 100 people). Other policies, including closing schools, appeared not to affect fatality rates either way.

Spiegel and Tookes are continuing to collect data and hope to refine their results in the future. One big unanswered question is how different policies interact with one another. “It might be that as long as everyone’s wearing masks, a given policy is less effective,” Tookes says.

What might this mean for policymakers? The data suggests that closing certain businesses can reduce fatalities, but “we all know there are other costs,” Tookes says—and what’s worth it depends on context and priorities. “Our goal wasn’t to prescribe a particular policy, but to help inform the decisions.”

Written by Susie Allen.
Department:Research
Topics:
https://insights.som.yale.edu/insig...LpTo7NpTFoAawGJjbRKUcQSaOaubqO1e1s6EBwRn8KxpE
https://insights.som.yale.edu/insig...LpTo7NpTFoAawGJjbRKUcQSaOaubqO1e1s6EBwRn8KxpE
 
huh, weird. the most restrictive measures SEEM to make a SLIGHT difference? who would have guessed :rasta:

it certainly doesn't address the change in the slope vs total impact notions though. delaying growth for a few percent doesn't reduce ultimate growth significantly, for example.


this is why, since day 1, the goal was to keep the fed/national stuff to bare minimum and let the states decide, and the states should have pushed it down to the counties to decide, and the counties SHOULD have said "if we aren't beyond 100% hospital support, we aren't shutting down". and then highly local measures that are strict, for short duration (weeks, not months) could have had just as significant an impact in mitigation without the accompanying 20% unemployment.
 
In fact, instituting a mask mandate reduces a county’s future fatality growth rate by 12%—about the same, in isolation, as more disruptive measures including stay-at-home orders and closing restaurants.

i'm genuinely curious how they sussed this out. i'm not aware of any state or locality that has had a mask mandate and no other restrictions.
 
Fortunately, I only had to read the first five sentences of the abstract before realizing the study is a big nothing burger.

For example, baseline estimates imply that a county with a mandatory mask policy in place today will experience 4- week and 6- week ahead fatality growth rates that are each 1% lower (respectively) than a county without such an order in place.

One percent lower than something that is already a fraction of a percent. Hmmmm.
 
huh, weird. the most restrictive measures SEEM to make a SLIGHT difference? who would have guessed :rasta:

If ya squint just right, stick out your tongue and hop on one foot, MAAAAYBE there is a slight change.

Or maybe, just hear me out, maybe the death rate has been dropping across the board in every single state regardless of what ill conceived treason the govt decided to implement that week?
 
Fortunately, I only had to read the first five sentences of the abstract before realizing the study is a big nothing burger.



One percent lower than something that is already a fraction of a percent. Hmmmm.

Don’t you go bringing facts into this topic to fuck up that narrative :lmao:
 
In fact, instituting a mask mandate reduces a county’s future fatality growth rate by 12%

I need to know how they got this number when no model, math, or science has been able to accurately determine why some cases are fatalities to some seemingly healthy people and some people who hit all the high risk factors are fine
 
Fortunately, I only had to read the first five sentences of the abstract before realizing the study is a big nothing burger.



One percent lower than something that is already a fraction of a percent. Hmmmm.

ESTIMATES IMPLY that it will go down by 1%.
 
I need to know how they got this number when no model, math, or science has been able to accurately determine why some cases are fatalities to some seemingly healthy people and some people who hit all the high risk factors are fine

I'd like to see these 12% of immortals. I had always understood fatality rates of living were 100%...
 
what the article said

) In fact, instituting a mask mandate reduces a county’s future fatality growth rate by 12%


what the abstract said


For example, baseline estimates imply that a county with a mandatory mask policy in place today will experience 4- week and 6- week ahead fatality growth rates that are each 1% lower (respectively) than a county without such an order in place. This relationship is significant, both statistically and in magnitude. This relationship is significant, both statistically and in magnitude. It represents 12% of the sample mean of weekly fatality growth.

so yeah, i'd argue that isn't significant ESPECIALLY when people like the talking heads (biden/fauci?) say "with just mask mandates, we have prevented 200k deaths this year (or in the next few months)

if that were remotely true, we should not see 1% reduction in growth, we should see ~50% reduction in growth associated with mask mandates.



Policies that are put in place near the natural peak of the outbreak will be followed by mechanical declines in death rates and can lead to false positives. Policies that only partially mitigate death rates may yield false negatives. We try to deal with the false positive and negative issue through a variety of methods.

huh, copy/paste font size went wonky on the actual paper pdf. i'm glad they are acknowledging the many challenges laid out, this is also why it will be impossible to say with confidence anything strongly

Thus, our regressions predict differences in the future growth in fatalities in two counties that today have the same current level of deaths per capita, the same recent trajectory in deaths and similar demographics and climate . They differ in that their governments have introduced different policy interventions

Other policies, such as closing schools and some higher risk businesses closures (those businesses typically associated with Phase 3 reopenings) fail to yield consistently negative and statistically significant parameters

...

Gym closures, spa closures, school closures, as well as general low-risk business closures do not appear to curb fatality growth rates. Low risk business closures again seem counterproductive.

huzzah! confirmation of what we've all said :rasta:



and then later in the paper, gym closures are listed as effective, despite being earlier noted as ineffective

Policies that have negative and significant coefficient estimates (i.e., predict lower future fatality growth) at both 4 - and 6- weeks are: employee mask recommendations, mandatory mask use for the general population, restaurant closures, gym closures, and beach and park closures. Those with negative and significant coefficients at one of these horizons are: stay at home orders, no elective procedures, limiting gatherings to 10 and high-risk business closures (Risk Level 2).1


let's couple this note

Bar closures also show a negative and significant coefficient at the 6-week horizon, but that coefficient is positive and significant at 4 weeks. It may take time for policies that could impact transmission among the bar-going population to impact deaths in those more vulnerable to the virus.

with this finding

Nursing homes are a major source of coronavirus fatalities.11 The finding in Table 4 that banning family nursing home visits did not lead to a strong reduction in future fatalities seems inconsistent with what we know about the number of nursing home deaths relative to the rest of the population. ...

...It may be that most of the nursing home cases resulted from unregulated factors rather than family visits.

turns out, going out to the bar during the week is probably not killing nana at the nursing home


numbers

Because the policy variables are dummies, the estimated magnitudes of the coefficients in Columns (3) and (4) of Table 4 are directly comparable. For example, the estimated coefficients of −0.010 and −0.017 on mandatory masks and employee masks, respectively, are significant both statistically and in magnitude...

he sample mean fatality growth of 0.085). These are in line with the magnitudes of the estimated coefficients on stay-at-home orders (-0.010), restaurant closures (-0.011), gym closures (-0.013), and Risk Level 2 business closures (-0.014). This type of comparison useful because the costs of these policies are likely to differ substantiall

it's odd that in that list, they label masks as being among the lowest, on par with stay-at home orders.
 
I need to know how they got this number when no model, math, or science has been able to accurately determine why some cases are fatalities to some seemingly healthy people and some people who hit all the high risk factors are fine

assumptions, and working those assumptions based on observations. which is why the relatively weak (1-2%) correlations that they could find are, at the end of the day, just that. weak correlations, even if we were to extrapolate them out to be meaningful reductions in growth, which we have no way to do with any accuracy.


edit: i commend their efforts for sifting through the data, but there is no reason why any policy maker should take that report and do anything other than say "alright, we recommend you keep distance, wash hands and wear a mask when you are sick...get the fawk back to work and school"
 
what the article said




what the abstract said




so yeah, i'd argue that isn't significant ESPECIALLY when people like the talking heads (biden/fauci?) say "with just mask mandates, we have prevented 200k deaths this year (or in the next few months)

if that were remotely true, we should not see 1% reduction in growth, we should see ~50% reduction in growth associated with mask mandates.





huh, copy/paste font size went wonky on the actual paper pdf. i'm glad they are acknowledging the many challenges laid out, this is also why it will be impossible to say with confidence anything strongly





huzzah! confirmation of what we've all said :rasta:



and then later in the paper, gym closures are listed as effective, despite being earlier noted as ineffective




let's couple this note



with this finding



turns out, going out to the bar during the week is probably not killing nana at the nursing home


numbers



it's odd that in that list, they label masks as being among the lowest, on par with stay-at home orders.

You cant in good faith use Biden numbers. He has already stated that 120 million Americans have died from covid and 160 million americans died from gun violence this year. We done ran the fuck out of citizens already.
 
You cant in good faith use Biden numbers. He has already stated that 120 million Americans have died from covid and 160 million americans died from gun violence this year. We done ran the fuck out of citizens already.

it was biden quoting fauci saying "we can avoid 200k deaths"
 
Thanks for doing the leg work on that. I also appreciate that you approached deciphering the report with no(or at least very little) bias.

the pdf is 39 pages, there's 20 pages of article stuff and 19 pages of sources, which is good. so it is a reasonably quick read, but reading it was worthwhile.

my bias is showing in what i chose to quote :rasta:
 
But when the source data is not accurate the study is not accurate... that’s the issue.

The whole point of the study is to find a way to parse the data we have into something meaningful. I'm not saying to should be used as gospel, in fact, quite the opposite, it should be scrutinized. That's why I threw it up here for people to comment on: I wanted to see what those who have more time and energy than I to put into looking at the study had to say.
 
But when the source data is not accurate the study is not accurate... that’s the issue.

that's what's good about it.

EVEN knowing the numbers are rough and inconsistent, and EVEN knowing that they ran their numbers with cities and without cities and such, the best they could figure is that mandatory masks might make a 1% difference in delaying growth. equivalent to mandatory stay-at-home orders. Shutting down select business? 1.7%

shutting down nursing home visitation? Near 0%

shutting down schools? near 0%

limiting gatherings? unless very strict, might drive an increase

shutting down public areas? might drive an increase (because then people are more likely to meet indoors in private)

the ONLY reason the main article says and supports mask mandates, is because they ASSUME that there is no negative side effects of masks. this is patently false, but not easily reflected in numbers and stats.
 
They have clearly never had to sneeze inside their mask before. Fawking horrible.

and hell, if we just rejected the purely accidental and unrelated to covid deaths (ladders, car accidents, etc.) we would see a 5-20% (based on CDC and high ranking state health official estimates) drop in deaths overnight :laughing:
 
and hell, if we just rejected the purely accidental and unrelated to covid deaths (ladders, car accidents, etc.) we would see a 5-20% (based on CDC and high ranking state health official estimates) drop in deaths overnight :laughing:

My biggest uphill battle is going to be presenting these findings to my wife. She says she knows better, but still acts like she believes wearing a mask will somehow filter out the virus. As in, if no one else has one on, she acts like putting on a cloth mask with give protect her. I guess everyone needs a security blanket for something?
 
My biggest uphill battle is going to be presenting these findings to my wife. She says she knows better, but still acts like she believes wearing a mask will somehow filter out the virus. As in, if no one else has one on, she acts like putting on a cloth mask with give protect her. I guess everyone needs a security blanket for something?

i can't stand them, my wife can't stand them, i don't think my kids had one for 5 minutes all year. it's aggravating that we are stuck in a "mask or pull your business lic" state and just so happen to be in the capital city, not as deep blue as Seattle, but damn do they want to be :shaking:

and now museums are closed AGAIN. fucking idiotic.
 
Interesting data. As others pointed out the flaw in masks is assuming evreyone uses them as intended and designed. I'm still going to do my own informal study this week and next week at work and compare how many times I touch my face at home without a mask vs with a mask on at work. Assuming everytime I touch my face I could be contacting a contaminated surface and spreading it either off the mask or into one of my own muchas membraines.

​​​​ I am glad people are.doing research on this, kind of rare in 2020.

I also heard facui wrote a paper on how masks didn't do anything for the spanish flu pandemic, I need to find that.

EDIT: I was wrong about the fauci paper, looks like it was about bacterial pneumonia killing people in the second wave and not nessasarily the flu. Wonder where all that came from, who knows.... https://www.nih.gov/news-events/new...ia-caused-most-deaths-1918-influenza-pandemic
 
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