How Politics Hijacked Science and Religion

probinson · Jun 17, 2021

200,000 EXTRA business closures in the Pandemic's fist year sounds like a significant amount of collateral damage to me. I mean, the business closing is just the start of a ripple effect that will result in higher unemployment, potential homelessness in extreme cases, higher stress levels, decreased mental health and increased suicides

Covid-19’s Toll on U.S. Business? 200,000 Extra Closures in Pandemic’s First Year

Kids committing suicides and self-harming at alarming rates seems significant as well;
child-psychiatrists-warn-that-the-pandemic-may-be-driving-up-kids-suicide-risk

Kids being socially isolated from their peers for over a year is definitely a factor here. Keeping kids of out school needlessly has harmed children. And we know that our CDC Director said it was safe in February for schools to return to in-person teaching without teachers being vaccinated. But that didn't happen not because of "science", but because of political and union pressures that did not have our children's best interests in mind. At all.

The Barbarian · Jun 17, 2021

probinson said:
Surely you're not implying that there were no collateral costs for mitigation measures, are you?

So far, all we have is your assurance that there are some. But you've been very reluctant to put any numbers to it, or even document that there is some. If we're going to have an objective measure, the claims can't be subjective. We can't simply say "collateral cost." How much are the collateral costs?

The Barbarian · Jun 17, 2021

As you learned, masks were important in reducing infection rates, and where they were used widely, the average infection rates were much lower.

probinson said:
No, they really weren't.

Yes, they really were. In April, averaging about 73,000/million for states with mask mandates and ablut 103,000/million for states with no mask mandates. Feel free to do another analysis for more recent data, but since the pandemic is now winding down, it won't be very much different, if at all.

The Barbarian · Jun 17, 2021

probinson said:
Henson says he doesn't feel the data represents the whole picture of Texas' population or the degrees of people's ideologies.

True. But the salient fact remains. Even though our politically-correct governor "opened up" the state before the pandemic ended, about 80% of Texans paid him no mind and went with the science, instead.

How they felt about it, or whether ideology or common sense made them do it, is really not the point.

Derek1234 · Jun 18, 2021

probinson said:
By how much? If we're going to have an objective measure, the numbers cannot be subjective. We can't simply say "reducing" something. How much reduction? In comparison to the collateral costs, what level of reduction should be considered beneficial?

Well, let's use this metric: How Government Agencies Determine The Dollar Value Of Human Life. So a human life is $10m, meaning the cost in the US has been USD 601,000*10,000,000. You may have a better answer. I sure hope it's not going to be that not all lives are worth the same, though.

probinson said:
I'm genuinely curious what evidence you believe "strongly suggests" that. If anything, the evidence might suggest that some strategies were effective at delaying the spread, and disproportionately making other people bear the burden. We called them "essential workers".

Articles in reputable journals like the Lancet. But even if your inference were justified, there is a reason why epidemiologists were pursuing a specific strategy of flattening the curve - because it reduces infection rates, morbidity and mortality.

probinson · Jun 18, 2021

Derek1234 said:
Well, let's use this metric: How Government Agencies Determine The Dollar Value Of Human Life. So a human life is $10m, meaning the cost in the US has been USD 601,000*10,000,000. You may have a better answer. I sure hope it's not going to be that not all lives are worth the same, though.

Earlier in the thread, I posted about "QALY" (Quality-Adjusted Life Years) to determine cost-effectiveness of medical interventions. Before we go any further, it's important to approach this topic delicately. I realize we are talking about human lives. I realize that life is precious, and any discussion of this topic can seem callous and uncaring. But in order to objectively determine cost-effectiveness, not all lives are worth the same in the equations, nor can they be if we want to objectively analyze cost-effectiveness of medical interventions.

Before anyone gets all indignant, let's look at this rationally; QALY accounts for not only how many additional years someone will live, but also the quality of life they can expect. The average life-expectancy in the US is currently roughly 79 years. So when calculating cost-effectiveness of medical interventions, one cannot equally weight the cost-effectiveness of saving the life of someone who is 80 years old with saving the life of someone who is 18. That disparity becomes even greater if quality of life is negatively impacted by the intervention.

As an example, let's say someone is diagnosed with a disease in their teens. A medical intervention means that they will likely live to a normal life-expectancy, but their quality of life, as a result from adverse side effects from the medical intervention, will be significantly impacted. We're talking about 61 actual years, but that number would be reduced due to the significant impact on their quality of life. What if the intervention results in complete paralysis?

A second example would be someone in their 60s receiving a medical intervention that results in a normal life expectancy with no appreciable impact on their quality of life. Now we're talking about 19 actual years, but perhaps the cost effectiveness is increased due to not negatively impacting that person's quality of life.

I am obviously no expert on QALY metrics, but the point (I hope) I'm making is that you cannot just arbitrarily say that every life is worth "X". There are too many factors.

We've heard well-meaning people say things like, "If it saves only 1 life, it's worth it." Of course that's not practical. It's the classic trolley problem. Do you pull the switch lever to save 5 people, killing the 1 on the other track, or do you leave the lever alone to save the 1 person, killing the other 5? What is the "right" thing to do? These are impossible questions, yet they are the kinds of things we need to consider when determining public health "efficacy".

probinson · Jun 18, 2021

The Barbarian said:
True. But the salient fact remains. Even though our politically-correct governor "opened up" the state before the pandemic ended, about 80% of Texans paid him no mind and went with the science, instead.

Except I just showed you that even the pollster said he didn't feel that this was representative of the entire population of Texas. But I can understand why you are so eager to use this. That's what confirmation bias does.

probinson · Jun 18, 2021

The Barbarian said:
So far, all we have is your assurance that there are some. But you've been very reluctant to put any numbers to it, or even document that there is some.

False. I've posted 19 pages of studies. These studies talk about the global impact of COVID mitigation measures on health, education, inequality, culture, economy and ethics.

probinson · Jun 18, 2021

The Barbarian said:
Yes, they really were. In April, averaging about 73,000/million for states with mask mandates and ablut 103,000/million for states with no mask mandates. Feel free to do another analysis for more recent data, but since the pandemic is now winding down, it won't be very much different, if at all.

Except you know as well as I do that there are countless confounders in the data.

As you know, some states did better without mask mandates than some states with mandates, and vise versa.

You've used studies that cherry-pick the data from a time that makes it appear masks are beneficial while ignoring data that shows they aren't. I guess you're in good company, as our own public health agencies do the same thing. It actually appears to be a requirement as a purveyor of The Science™.

probinson · Jun 18, 2021

Vaccination for children.

The CDC is seeing higher than usual myocarditis cases in young males getting the vaccine. So the CDC called an "emergency" meeting to discuss options. Of course, that "emergency" meeting was scheduled a full week ago for today. But now the "emergency" meeting has been pushed off again due to the newly minted federal Juneteenth holiday. Sounds like a real "emergency".

This while COVID poses extremely little risk to children. Data shows that children are at higher risk of drowning, vehicle accidents, homicide, cancer, cardiovascular disease, flu/pneumonia and suffocation than they are from COVID. From the NYT this morning;

Polls suggest that many Democratic voters have an inflated sense of Covid’s risks to children. If you’re liberal, you may want to ask yourself if you fall into this category.

Kids, Covid and Delta

All a direct result of The Science™.

probinson · Jun 18, 2021

More collateral damage;

Children’s Colorado Declares ‘State of Emergency’ for Youth Mental Health

probinson · Jun 18, 2021

Another example of how politics has infected science (emphasis added);

By creating a tracker that showed the situation in Florida to be somewhat less dire than enemies of Governor DeSantis preferred to believe, he had left the staid world of academia and entered the world of politics, where facts are subordinated to the question of whom those facts might help and whom they might hurt.

Rebekah Jones Tried to Ruin Florida Academic's Career | National Review

Derek1234 · Jun 18, 2021

probinson said:
Earlier in the thread, I posted about "QALY" (Quality-Adjusted Life Years) to determine cost-effectiveness of medical interventions. Before we go any further, it's important to approach this topic delicately. I realize we are talking about human lives. I realize that life is precious, and any discussion of this topic can seem callous and uncaring. But in order to objectively determine cost-effectiveness, not all lives are worth the same in the equations, nor can they be if we want to objectively analyze cost-effectiveness of medical interventions.

Before anyone gets all indignant, let's look at this rationally; QALY accounts for not only how many additional years someone will live, but also the quality of life they can expect. The average life-expectancy in the US is currently roughly 79 years. So when calculating cost-effectiveness of medical interventions, one cannot equally weight the cost-effectiveness of saving the life of someone who is 80 years old with saving the life of someone who is 18. That disparity becomes even greater if quality of life is negatively impacted by the intervention.

As an example, let's say someone is diagnosed with a disease in their teens. A medical intervention means that they will likely live to a normal life-expectancy, but their quality of life, as a result from adverse side effects from the medical intervention, will be significantly impacted. We're talking about 61 actual years, but that number would be reduced due to the significant impact on their quality of life. What if the intervention results in complete paralysis?

A second example would be someone in their 60s receiving a medical intervention that results in a normal life expectancy with no appreciable impact on their quality of life. Now we're talking about 19 actual years, but perhaps the cost effectiveness is increased due to not negatively impacting that person's quality of life.

I am obviously no expert on QALY metrics, but the point (I hope) I'm making is that you cannot just arbitrarily say that every life is worth "X". There are too many factors.

We've heard well-meaning people say things like, "If it saves only 1 life, it's worth it." Of course that's not practical. It's the classic trolley problem. Do you pull the switch lever to save 5 people, killing the 1 on the other track, or do you leave the lever alone to save the 1 person, killing the other 5? What is the "right" thing to do? These are impossible questions, yet they are the kinds of things we need to consider when determining public health "efficacy".

It is a delicate subject, and I agree that it needs to be approached with sensitivity, and we need to avoid slippery slope arguments. Nevertheless, we have to make some assumptions - the standard economists' approach - about acceptable trade-offs. The same policy that you have been (correctly, IMHO) indignant about - returning old people to care homes, an increasing their risk of death or isolation - has a cost to those people. Possibly the ultimate cost. But you're putting a qualitative value on their lives, not a quantititative one - arguing from a moral, not a financial, imperative. So where, and to whose lives, do we apply economic metrics? The currently-economically active? The de facto underclass you mention, whose role is to run around after us? The poor minority ethnic groups? Those in school, whose potential has yet to be realised? And so on. I've just given you an arbitrary starting point, because you asked for one, that estimates the cost in US lives alone at $6tn. The estimated global cost of the pandemic containment strategy, by contrast, was estimated at $1tn in 2020. So, your turn. What do you think is acceptable collateral, whether using qualitative or quantitative measures, and why?

Derek1234 · Jun 18, 2021

probinson said:
Except you know as well as I do that there are countless confounders in the data.

As you know, some states did better without mask mandates than some states with mandates, and vise versa.

You've used studies that cherry-pick the data from a time that makes it appear masks are beneficial while ignoring data that shows they aren't. I guess you're in good company, as our own public health agencies do the same thing. It actually appears to be a requirement as a purveyor of The Science™.

I don't understand why you are sometimes happy to accept confounders and sometimes not. Why do you persist in comparing Rhode Island with Texas, for example, when the environmental factors alone make it a bogus comparator?

The Barbarian · Jun 18, 2021

probinson said:
Except you know as well as I do that there are countless confounders in the data.

So, you'll cherry pick the outliers to save your case?

As you know, some states did better without mask mandates than some states with mandates, and vise versa.

"There you go again" - Ronald Reagan.

Turns out, you can find a few like that, but as you learned earlier, taking all the data for all the states, over the entire pandemic, states with mask mandates average significantly lower infection rates than states without them.

If you get to cherry-pick your states and time periods, you might show something different, but it fools no one.

The Barbarian · Jun 18, 2021

Derek1234 said:
I don't understand why you are sometimes happy to accept confounders and sometimes not. Why do you persist in comparing Rhode Island with Texas, for example, when the environmental factors alone make it a bogus comparator?

Because using all the data won't give him the results he wants.

The Barbarian · Jun 18, 2021

probinson said:
By creating a tracker that showed the situation in Florida to be somewhat less dire than enemies of Governor DeSantis preferred to believe, he had left the staid world of academia and entered the world of politics, where facts are subordinated to the question of whom those facts might help and whom they might hurt.

There aren't "good facts" and "bad facts." There are just facts (which are true) and falsehood. And when you start subordinating the truth to your idea of what's good or bad, you've lost your grip on reality.

This is why Trump botched the pandemic and DeSantis left Florida with a higher-than-average COVID infection rate; they subordinated the facts to their wishes.

The Barbarian · Jun 18, 2021

probinson said:
Except you know as well as I do that there are countless confounders in the data.

Which is why there are outliers in the data. But with fifty states, we have a pretty good data set. Your attempt to cherry-pick the states you want to talk about, fall apart when we compare all states, over the entire pandemic.

As you know, the average infection rate for states with mask mandates is significantly lower than the average for states without them, using all the data, not a small period within the pandemic.

The Barbarian · Jun 18, 2021

But the salient fact remains. Even though our politically-correct governor "opened up" the state before the pandemic ended, about 80% of Texans paid him no mind and went with the science, instead.

How they felt about it, or whether ideology or common sense made them do it, is really not the point. He did say that the survey did not necessarily represent ideologies.

probinson said:
Except I just showed you that even the pollster said he didn't feel that this was representative of the entire population of Texas.

It merely represented the state as a whole. The survey found about 80% of all Texans ignored the governor and continued to wear masks, while not focusing on ideological reasons for doing or not doing it.

But I can understand why you are so eager focus on ideology, instead of that which the survey actually measured. You ignored what the survey measured and focused on what it did not. That's what confirmation bias does.

It doesn't really change anything, but your confirmation bias requires you to use whatever you can to support it.

probinson · Jun 21, 2021

Derek1234 said:
I don't understand why you are sometimes happy to accept confounders and sometimes not. Why do you persist in comparing Rhode Island with Texas, for example, when the environmental factors alone make it a bogus comparator?

Not true. I'm happy to accept confounders all the time.

But I don't understand why it seems you don't apply the same scrutiny to all positions. The "studies" referenced to suggest an efficacy of masks look at declining case counts and conclude, without even considering confounders, that masks "work". But I don't understand why you just seem to accept this conclusion, when you know as well as I do that there are countless confounders.

These observational studies become even more useless when you realize that NOT ONE of them included the time period of October 2020 - January 2021, when cases were spiking all over the United States. If you apply the same methodology in these studies but change the time period that was studied, you get COMPLETELY different results. Yet NO ONE has deemed it necessary to study this time period. Why? I mean, just look at this graph again;

This is a CDC "study" on the efficacy of masking. It concludes masks were effective simply by looking at case numbers in the study period. It does not consider any confounders whatsoever. And it completely excludes data that would undermine the study's conclusions.

Why do you just accept the results of this study, given that it ignores confounders, and it cherry-picks data to arrive and a desired conclusion?

How Politics Hijacked Science and Religion

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