Our Covid Response

Silvanus

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How are you going to get people to want to join up for a job that is obviously pretty limited in time? I'm going to take a job that I know won't last instead of a job that could last or at worst give me experience in the field I want to be in?
....you know seasonal jobs are typically oversubscribed, right?

Show me data that [...]
Yawn.

Knowing X amount of something vs knowing a good deal about something are 2 different things. Literally every model almost instantly was shown to be wrong. The UK one time voted to lockdown even when the model they were basing the decision on was already shown as very wrong.
So what information, exactly, were they lacking in your opinion?

They knew diagnosed cases were high. They knew the rate was climbing very quickly. They knew undiagnosed cases were many times higher than diagnosed. All of that was completely true, and was also sufficient to convince them to introduce restrictions in mid-March.

But you're claiming they were... lacking some other crucial bit of information that meant they couldn't possibly have introduced other restrictions? What piece of the puzzle were they missing? Are you going to go back to insinuating they should know the number of undiagnosed cases before making any decisions?
 

Trunkage

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....you know seasonal jobs are typically oversubscribed, right?



Yawn.



So what information, exactly, were they lacking in your opinion?

They knew diagnosed cases were high. They knew the rate was climbing very quickly. They knew undiagnosed cases were many times higher than diagnosed. All of that was completely true, and was also sufficient to convince them to introduce restrictions in mid-March.

But you're claiming they were... lacking some other crucial bit of information that meant they couldn't possibly have introduced other restrictions? What piece of the puzzle were they missing? Are you going to go back to insinuating they should know the number of undiagnosed cases before making any decisions?
I think you are asking the wrong question. Were they underguesssing cases or over? By how much?

Eg. The CDC, in March 2020 predicted that there was going to be 200k to 2M deaths in the US in 2 years. Around 2 years in, it was 1M. Is this them underestimating or overestimating? How much is this prediction an over or under estimate? (Sub in your UK variables here). Fox et al was predicting less than the Flu, i.e. under 100k in 2 years. Is this underestimating or over? By how much?

Phoenixmgs or anyone close to his side has not provided any prediction that could be close to accurate. Just because you think the UK models were wrong, that doesn't make yours right. I can, without reservation say that the UK models were far closer than anything Phoenixmgs provided. It's not even close. They might be wrong, but they arent as wrong as Phoenixmgs

Imagine if the world worked like this. A stock broker predicts that a certain stock goes up by 5% over the year. But the model was wrong and it went up by 6%. Since the model was wrong, then you cant possibly buy the stock.

The government make a budget at the start of the year. The models predicted 4 major hurriacanes this year. But there was only 3. Well, the models wrong so we need to get rid of all hurriance support and relief for all incidents

Restaurants use a model to predict how many patrons they will have in a night for staffing and produce reasons. They predict 40 patrons tonight but it ends up at 45. Well, the models are wrong and we just have to shut the restaurant down
 
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Asita

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Nope, you can find that argument online in many places. Where Leana Wen actually starts speaking with basic logic, people get all mad and random stuff like masks work and we need to mask because of long covid and tons of bullshit.
Oh, so it's not a strawman of your own invention, it's a strawman you're borrowing based on someone's rhetorical hyperbole and twits on twitter! Well that makes it completely different, doesn't it?

"I saw someone say it on the internet" amounts to zilch. It's the internet. If you look hard enough, you can find someone saying just about anything. Quoting a random schmuck on the internet amounts to nothing more substantive than quoting a random drunk in a tavern.

Credible sources only, please.

Fucking stop with your bullshit. When did I ever say anything that is anti-vax misinformation?
Oh where to even start with that... Perhaps the months you've spent trying to argue that vaccination was pointless on the grounds that "natural immunity" was superior? Your endorsement of what amounted to "super spreading" over vaccination because you got it into your head that that was the best way to reach "herd immunity"? All the railing against vaccines as ineffective because some chucklehead convinced you that their primary purpose was to be what amounted to a magical shield that would prevent an infection rather than making your body more effective at fighting it off if you caught it, and therefore the fact that Covid was still around meant that vaccines had failed in that goal? Shall I go on?

Don't try to accuse me of bullshitting when all I'm doing is calling you out on being the resident manure salesman.

YES, NOW THE FLU IS MORE DANGEROUS THAN COVID, THAT'S WHAT OFFICIAL ONS NUMBERS HAVE SAID.
Considering your consistent inability to understand scope, limitations, results, methodologies, and even simple definitions - never mind your propensity to simply presume that papers you did not remotely understand must support your extant conclusions - I severely doubt that's a reasonable reading of what it said. So I think the only proper response to that is to ask that you link to what you think you're citing.

What way do we have of confirming long covid or not for some guy walking into a doctor's office today (first time) that says he has long covid and it's been 3 months since he was originally sick?

You can run a study and determine long covid rate but not just some guy walking into a doctors office months after the original infection that was never even tested for to begin with.
I explained this to you several times over. It's a little something called labwork. Perhaps you've heard of it? It's kinda an important component of modern medicine and healthcare.

You might recall that I mentioned four different types of antibodies associated with Covid. Anti-S, Anti-N, IgM, and IgG, which tell different parts of the figurative story. By looking at the tale they collectively tell in concert, doctors can determine whether or not a person has, in fact, been infected with Covid and if so, how recently. And again, the very sources you yourself brought in showed the ability to make this very determination that you are insisting is impossible! Their methodology literally centered on them testing people who believed they had Long Covid and determining the accuracy of that assumption through lab results. And yet here you are, still acting like I'm speaking hypothetically rather than re-explaining basic concepts and established methods to you for the upteenth time.

I am not speaking hypothetically here. I am telling you in no uncertain terms that you are trying to argue against a well established method based on nothing but your personal ignorance of it.

Fatigue is always subjective!!! What does it matter if you do surveys or some other test (acting like there's no issue with confounders or the test itself).
Annnnd WOOOSH goes the point straight over your head.

The inherent subjectivity of these metrics is what I am trying to explain to you and exactly what makes the the survey incapable of the results you are trying to attribute to it (a claim that the paper itself does not make, mind you). You're trying to make a claim about the objective severity of two diseases relative to one another through the use of subjective data whose measurements both are vaguely defined and subject to varying interpretation by each respondent. And that simply does not work. You do not use subjective data to derive objective conclusions. Period. The closest you get is when you're using a survey to create exploratory data used to formulate a hypothesis, which you would then test with a more robust methodology with more accurate measurements and that can rule out response error. Surveys are a low cost starting point to help direct future research, not a conclusion.

That you evidently don't understand that and are insisting on treating different methodologies as necessarily equivalent for these purposes ("What does it matter if you do surveys or some other test")...well, in all honesty, it's so bizarre that it strains credulity. It's such a basic concept that you'd typically learn it in an the "introduction to surveys" section of a course or training dealing with research. It literally is one of the first things that anyone dealing with this kind of data would learn about it. The reading you're trying to insist upon is not only an egregious misreading of the paper, it's utterly reliant on a fundamental misunderstanding of what data a survey such as this can produce.
 
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Phoenixmgs

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....you know seasonal jobs are typically oversubscribed, right?



Yawn.



So what information, exactly, were they lacking in your opinion?

They knew diagnosed cases were high. They knew the rate was climbing very quickly. They knew undiagnosed cases were many times higher than diagnosed. All of that was completely true, and was also sufficient to convince them to introduce restrictions in mid-March.

But you're claiming they were... lacking some other crucial bit of information that meant they couldn't possibly have introduced other restrictions? What piece of the puzzle were they missing? Are you going to go back to insinuating they should know the number of undiagnosed cases before making any decisions?
You know everywhere was understaffed in the US in 2020, right?

Yes, me requesting proof and you not showing it is indeed par for the course.

They really had no idea of the undiagnosed cases. I don't know how Fauci on Feb 29th saying to New Yorkers go about your lives as normal doesn't prove that very fact, it wasn't close to safe to go about life normally at that time. That's not being off by a bit, that's being massively fucking off. They didn't know the extent anywhere near close to accurate until surveys were actually done. My point has little to do with how accurate their knowledge was at the time, it's that once we had the knowledge (20% of NYC infected by mid-April), contact tracing as a viable strategy was off the table, covid had spread for too much to try to contact trace it.

I think you are asking the wrong question. Were they underguesssing cases or over? By how much?

Eg. The CDC, in March 2020 predicted that there was going to be 200k to 2M deaths in the US in 2 years. Around 2 years in, it was 1M. Is this them underestimating or overestimating? How much is this prediction an over or under estimate? (Sub in your UK variables here). Fox et al was predicting less than the Flu, i.e. under 100k in 2 years. Is this underestimating or over? By how much?

Phoenixmgs or anyone close to his side has not provided any prediction that could be close to accurate. Just because you think the UK models were wrong, that doesn't make yours right. I can, without reservation say that the UK models were far closer than anything Phoenixmgs provided. It's not even close. They might be wrong, but they arent as wrong as Phoenixmgs

Imagine if the world worked like this. A stock broker predicts that a certain stock goes up by 5% over the year. But the model was wrong and it went up by 6%. Since the model was wrong, then you cant possibly buy the stock.

The government make a budget at the start of the year. The models predicted 4 major hurriacanes this year. But there was only 3. Well, the models wrong so we need to get rid of all hurriance support and relief for all incidents

Restaurants use a model to predict how many patrons they will have in a night for staffing and produce reasons. They predict 40 patrons tonight but it ends up at 45. Well, the models are wrong and we just have to shut the restaurant down
Huh? I wasn't claiming to know something that was unknown anymore than any model. I didn't claim to be right about my own prediction (in fact, I didn't even have one). All I said was at least in the US, nobody knew anywhere near to how close covid at spread in those 1st couple months until the surveys were done. Once we had the survey data (not some model, actual legit real world info) and found covid had spread far more than anyone thought, contact tracing the virus was off the table as a viable strategy. The one thing I recall about the UK (since I didn't follow the UK as I don't live there) was the following I think if I'm remembering correctly.


Oh, so it's not a strawman of your own invention, it's a strawman you're borrowing based on someone's rhetorical hyperbole and twits on twitter! Well that makes it completely different, doesn't it?

"I saw someone say it on the internet" amounts to zilch. It's the internet. If you look hard enough, you can find someone saying just about anything. Quoting a random schmuck on the internet amounts to nothing more substantive than quoting a random drunk in a tavern.

Credible sources only, please.



Oh where to even start with that... Perhaps the months you've spent trying to argue that vaccination was pointless on the grounds that "natural immunity" was superior? Your endorsement of what amounted to "super spreading" over vaccination because you got it into your head that that was the best way to reach "herd immunity"? All the railing against vaccines as ineffective because some chucklehead convinced you that their primary purpose was to be what amounted to a magical shield that would prevent an infection rather than making your body more effective at fighting it off if you caught it, and therefore the fact that Covid was still around meant that vaccines had failed in that goal? Shall I go on?

Don't try to accuse me of bullshitting when all I'm doing is calling you out on being the resident manure salesman.



Considering your consistent inability to understand scope, limitations, results, methodologies, and even simple definitions - never mind your propensity to simply presume that papers you did not remotely understand must support your extant conclusions - I severely doubt that's a reasonable reading of what it said. So I think the only proper response to that is to ask that you link to what you think you're citing.



I explained this to you several times over. It's a little something called labwork. Perhaps you've heard of it? It's kinda an important component of modern medicine and healthcare.

You might recall that I mentioned four different types of antibodies associated with Covid. Anti-S, Anti-N, IgM, and IgG, which tell different parts of the figurative story. By looking at the tale they collectively tell in concert, doctors can determine whether or not a person has, in fact, been infected with Covid and if so, how recently. And again, the very sources you yourself brought in showed the ability to make this very determination that you are insisting is impossible! Their methodology literally centered on them testing people who believed they had Long Covid and determining the accuracy of that assumption through lab results. And yet here you are, still acting like I'm speaking hypothetically rather than re-explaining basic concepts and established methods to you for the upteenth time.

I am not speaking hypothetically here. I am telling you in no uncertain terms that you are trying to argue against a well established method based on nothing but your personal ignorance of it.



Annnnd WOOOSH goes the point straight over your head.

The inherent subjectivity of these metrics is what I am trying to explain to you and exactly what makes the the survey incapable of the results you are trying to attribute to it (a claim that the paper itself does not make, mind you). You're trying to make a claim about the objective severity of two diseases relative to one another through the use of subjective data whose measurements both are vaguely defined and subject to varying interpretation by each respondent. And that simply does not work. You do not use subjective data to derive objective conclusions. Period. The closest you get is when you're using a survey to create exploratory data used to formulate a hypothesis, which you would then test with a more robust methodology with more accurate measurements and that can rule out response error. Surveys are a low cost starting point to help direct future research, not a conclusion.

That you evidently don't understand that and are insisting on treating different methodologies as necessarily equivalent for these purposes ("What does it matter if you do surveys or some other test")...well, in all honesty, it's so bizarre that it strains credulity. It's such a basic concept that you'd typically learn it in an the "introduction to surveys" section of a course or training dealing with research. It literally is one of the first things that anyone dealing with this kind of data would learn about it. The reading you're trying to insist upon is not only an egregious misreading of the paper, it's utterly reliant on a fundamental misunderstanding of what data a survey such as this can produce.
I never said half that shit you claim about vaccines. Every bit of data on natural immunity shows it's as good or better protection than vaccine induced immunity. What the fuck are you talking about "super spreading" over vaccination, I never said anything along those lines. All I ever said was that if you had gotten covid before the vaccines were available, you didn't need the vaccine (exceptions for the vulnerable and people with immune system issues obviously), which every bit of data on the subject to this day says that. I never said or implied the vaccines were ineffective (outside of ineffective to stopping transmission), they greatly reduce severe disease.

Right here, the CDC director says vaccines are not preventing transmission anymore, that's misinformation because the vaccines never did that, Pfizer literally said they never claimed the vaccine prevents transmission because they never tested for that in the first place. Plus, we had Israel data showing the vaccines didn't do that because Israel vaccinated before the US and we literally witnessed immunity wane very quickly.

Official ONS data and article
1678606193706.png

IgG antibodies last too long to be any definitive answer to whether someone has long-term symptoms triggered by covid.

Patient reported symptoms are not some horribly inaccurate way to do a study. The studies claiming long covid is something happening at some "high" rate use even worse methods. I've asked this many times from people here, show me legit data to proves long covid occurs more often than long flu, long RSV, long rhinovirus, long etc.

:unsure:

Pick any of your posts at random in this thread, there's a good chance you said it there.
Then it must be pretty fucking easy for you to dig up just a single bit of anti-vax misinformation but yet your post includes nothing I said...
 

Silvanus

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You know everywhere was understaffed in the US in 2020, right?
At no point was a contact tracing system in place and unable to find staff. This is pure spitballing.

Yes, me requesting proof and you not showing it is indeed par for the course.
You endlessly request "proof" or "data" that have already been provided, often multiple times, and which you have comprehensively ignored or dismissed. Everybody here is aware of this.

They really had no idea of the undiagnosed cases. I don't know how Fauci on Feb 29th saying to New Yorkers go about your lives as normal doesn't prove that very fact, it wasn't close to safe to go about life normally at that time. That's not being off by a bit, that's being massively fucking off. They didn't know the extent anywhere near close to accurate until surveys were actually done. My point has little to do with how accurate their knowledge was at the time, it's that once we had the knowledge (20% of NYC infected by mid-April), contact tracing as a viable strategy was off the table, covid had spread for too much to try to contact trace it.
They knew it was drastically higher than confirmed cases in early March. They were already certain enough of that to implement restrictions several weeks before you said it would be possible.
 

Asita

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Official ONS data and article
View attachment 8249
*facepalm*

So you're talking about that bit that Agema already explained to you was a misrepresentative soundbite that you are incorrectly taking to imply a generalized point by exaggerating the scope of a specific data point and focusing exclusively on raw lethality without consideration for contemporary circumstance or other factors.

Analogy: Have you ever seen a creationist try to argue against evolutionary theory by pretending that either mutation or natural selection was not a component of the process? Similar idea here. What makes a virus dangerous is a synthesis of a variety of traits. You can't simply laser focus on one aspect to the exclusion of all others, but that is exactly what you are insisting on doing.

In this case, the claim you're making is rooted in a limited-scope statement that the Omicron variant has, at this moment, statistically lower lethality on an individual level. However, the claim that the Flu is more dangerous than Covid [in England] is a declaration that makes a false implication by going well beyond that scope. That's a scope applied to a population, not an individual, meaning that we also must consider additional factors beyond simple lethality for a given case, such as infectiousness. And Covid is significantly more infectious.

By the article's own account, despite the fact that people are still being cautious about spreading respiratory infections, Omicron still elevated the death toll by 50% over the typical flu season, and 30% higher than historically bad years. And don't get me wrong, that's much better than where we were when the Alpha strain first hit, but to take from that the conclusion that Covid has now been reduced to something - all else being equal - less dangerous than the flu [in England] is amateur folly, which the writers obviously understand as they're quick to hedge their claims to something more reasonable within the article itself.

Here: quick thought exercise. Which is more dangerous for a population? A virus that can infect 2000 people in a week but will only kill 2% of them, or a virus that can only infect 100 people in a week, but will kill 10% of them? If we judge by individual lethality, then we must conclude that it is the latter virus because the former kills 2 out of 100, whereas the latter kills 10 out of 100. But that's a snapshot of an abstraction that ignores infectiousness in favor of assuming that they both infect an equal number of people, which you cannot do when making a generalized statement about the danger of a virus to the population. Let's run the numbers real quick to see how this snowballs. For simplicity, we'll assume the spread exhibits linear growth.

Week 1: Virus A infects 2000 and kills 40. Virus B infects 100 and kills 10.
Week 2: Virus A's death toll is up to 80. Virus B's toll is 20.
Week 3: Virus A is up to 120. Virus B is up to 30.
Week 4: Virus A is up to 160. Virus B is up to 40.

Now that we've seen that, I ask again: Which virus is more dangerous to the population? The numbers have not changed. Virus A still only kills 2% of the time, while Virus B kills 10% of the time. We just stopped employing tunnel vision for the on-paper mortality rate of the virus and started looking at what that means in practice considering how the virus spreads. Virus B is more dangerous to the individual, but its slower spread means that it's significantly less dangerous to the population than Virus A is. Virus A may kill more per infection, but Virus B kills more overall over a given time period and is much more difficult to contain because of how fast it spreads.

So yeah, about what I was expecting. You're not deferring to ONS data, you're skim-reading a Financial Times editorial's own quick-and-dirty calculations (which were partially derived from manipulating ONS data), and you aren't even representing that accurately because you are more interested in proving a point than understanding the subject. For goodness sake, the damn article notes that the experts are cautioning that a recent uptick in hospitalizations is a reason to be wary of exactly what you're pushing, implying that the cause is likely due to people being less cautious and their resistance waning.

You are trying to imply a ceteris paribus conclusion when ceteris paribus assumptions do not apply. The article understood the distinction. You did not.


IgG antibodies last too long to be any definitive answer to whether someone has long-term symptoms triggered by covid.
And yet again you're trying to argue as if I'm proposing some comprehensive hypothetical method that you can argue against rather than supplying you a cliff notes summation of what doctors do and the methods your own sources employed. That you - a layman with little-to-no understanding of the topic - don't understand how they do it is immaterial to the fact that they do it.

Patient reported symptoms are not some horribly inaccurate way to do a study. The studies claiming long covid is something happening at some "high" rate use even worse methods. I've asked this many times from people here, show me legit data to proves long covid occurs more often than long flu, long RSV, long rhinovirus, long etc.
"A study"? No. I believe I've been saying from the get-go that this stuff has its place. The conclusion that you're projecting onto the paper? It's absolutely terrible for that. Because again: Vague subjective measurements do not prove specific objective conclusions. This is not a negotiable point, Phoenix. You're wrong, and you are misrepresenting the paper. End of story.

And really? We're back to the "prove it happens more often" bullshit? I believe I already got into that:

it's further worth noting that even if you had been right about comparative incidence rate, it would still be - once again - irrelevant, because concerns about Long Covid are not predicated on comparative incidence rate as contrasted with the long term aftereffects for other diseases. This isn't a footrace wherein all the prize money goes to the first person past the post.

Generously, that'd be what we'd call the Fallacy of Relative Privation (aka the "Appeal to Worse Problems" Fallacy), a positively puerile fallacy that insists that if something isn't the foremost example of its kind, it's not worth concerning yourself with. Eg, "Breast Cancer isn't as bad as Brain Cancer, so why do we make a big deal about being vigilant about it?" When you understand why trying to object to Breast Cancer screenings by comparing Breast Cancer's fatality rate to that of Brain Cancer is idiotic, you will understand why the argument you just attempted by misrepresenting that study is equally stupid.
 
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Ag3ma

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Patient reported symptoms are not some horribly inaccurate way to do a study. The studies claiming long covid is something happening at some "high" rate use even worse methods. I've asked this many times from people here, show me legit data to proves long covid occurs more often than long flu, long RSV, long rhinovirus, long etc.
1) Why? What do you think such a comparison is going to demonstrate that's of any particular use? Why does this somehow invalidate the relevance of chronic symptoms following covid infection?

2) It's not useful to demand answers that (presumably) you know don't exist.

There is plentiful evidence that people can have long-term ill-effects from infection, even after the acute period has ended. This is extraordinarily hard to measure, because we are subjected to a wide range of infections, some of which we may even be barely aware of. Pinning these on a specific virus would be at minimum very hard. We know it happens - chronic fatigue syndrome is likely a long-term disturbance of the body's immune system caused by infection. Long covid is interesting, because it gives us a relatively clear example of such long-term effects due to a novel and extremely pervasive virus, as it can be much more easily teased out from the background noise.

There are two good biological reasons to believe covid may be more problematic than things like influenza. Firstly, over time viruses adapt to their hosts and hosts to viruses. Infections that have been widespread in the population a long time may therefore be less likely to disrupt the immune system or cause unusual complications because this adaptation has already taken place. Then, of course, most people will already have been exposed to them (or one very similar) at some point anyway, but this will be spread over a much longer time period: for instance, in any given year, most people don't catch 'flu.
 

Absent

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Well, the covid is now about to be considered as equal to the ordinary seasonal flu, in terms of dangerosity, according to the WHO.

That's nice. I don't really care about those who will react with "see, see, it's the proof it was never dangerous". The pandemic evolves and dies out as they do. I don't even care that much about its source, to be honest. A mix of fatigue and the assumption that certainties will stay out of reach.

My hope is that we've learnt something that will help us deal better with the next one (which I imagine pending). Socially, I'm not sure. But medically, at least, the little jump in RNA-based technology and its various applications is probably an advantage that will stay.
 
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Phoenixmgs

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At no point was a contact tracing system in place and unable to find staff. This is pure spitballing.



You endlessly request "proof" or "data" that have already been provided, often multiple times, and which you have comprehensively ignored or dismissed. Everybody here is aware of this.



They knew it was drastically higher than confirmed cases in early March. They were already certain enough of that to implement restrictions several weeks before you said it would be possible.
I literally linked the article that said it was unable to get enough staff...

Where was this proof of a virus similar to covid that was already widespread and contact tracing worked?

Then why did Fauci say it was still OK to go about your normal daily lives on Feb 29th if they knew with any accuracy how many infections there were?

*facepalm*

So you're talking about that bit that Agema already explained to you was a misrepresentative soundbite that you are incorrectly taking to imply a generalized point by exaggerating the scope of a specific data point and focusing exclusively on raw lethality without consideration for contemporary circumstance or other factors.

Analogy: Have you ever seen a creationist try to argue against evolutionary theory by pretending that either mutation or natural selection was not a component of the process? Similar idea here. What makes a virus dangerous is a synthesis of a variety of traits. You can't simply laser focus on one aspect to the exclusion of all others, but that is exactly what you are insisting on doing.

In this case, the claim you're making is rooted in a limited-scope statement that the Omicron variant has, at this moment, statistically lower lethality on an individual level. However, the claim that the Flu is more dangerous than Covid [in England] is a declaration that makes a false implication by going well beyond that scope. That's a scope applied to a population, not an individual, meaning that we also must consider additional factors beyond simple lethality for a given case, such as infectiousness. And Covid is significantly more infectious.

By the article's own account, despite the fact that people are still being cautious about spreading respiratory infections, Omicron still elevated the death toll by 50% over the typical flu season, and 30% higher than historically bad years. And don't get me wrong, that's much better than where we were when the Alpha strain first hit, but to take from that the conclusion that Covid has now been reduced to something - all else being equal - less dangerous than the flu [in England] is amateur folly, which the writers obviously understand as they're quick to hedge their claims to something more reasonable within the article itself.

Here: quick thought exercise. Which is more dangerous for a population? A virus that can infect 2000 people in a week but will only kill 2% of them, or a virus that can only infect 100 people in a week, but will kill 10% of them? If we judge by individual lethality, then we must conclude that it is the latter virus because the former kills 2 out of 100, whereas the latter kills 10 out of 100. But that's a snapshot of an abstraction that ignores infectiousness in favor of assuming that they both infect an equal number of people, which you cannot do when making a generalized statement about the danger of a virus to the population. Let's run the numbers real quick to see how this snowballs. For simplicity, we'll assume the spread exhibits linear growth.

Week 1: Virus A infects 2000 and kills 40. Virus B infects 100 and kills 10.
Week 2: Virus A's death toll is up to 80. Virus B's toll is 20.
Week 3: Virus A is up to 120. Virus B is up to 30.
Week 4: Virus A is up to 160. Virus B is up to 40.

Now that we've seen that, I ask again: Which virus is more dangerous to the population? The numbers have not changed. Virus A still only kills 2% of the time, while Virus B kills 10% of the time. We just stopped employing tunnel vision for the on-paper mortality rate of the virus and started looking at what that means in practice considering how the virus spreads. Virus B is more dangerous to the individual, but its slower spread means that it's significantly less dangerous to the population than Virus A is. Virus A may kill more per infection, but Virus B kills more overall over a given time period and is much more difficult to contain because of how fast it spreads.

So yeah, about what I was expecting. You're not deferring to ONS data, you're skim-reading a Financial Times editorial's own quick-and-dirty calculations (which were partially derived from manipulating ONS data), and you aren't even representing that accurately because you are more interested in proving a point than understanding the subject. For goodness sake, the damn article notes that the experts are cautioning that a recent uptick in hospitalizations is a reason to be wary of exactly what you're pushing, implying that the cause is likely due to people being less cautious and their resistance waning.

You are trying to imply a ceteris paribus conclusion when ceteris paribus assumptions do not apply. The article understood the distinction. You did not.




And yet again you're trying to argue as if I'm proposing some comprehensive hypothetical method that you can argue against rather than supplying you a cliff notes summation of what doctors do and the methods your own sources employed. That you - a layman with little-to-no understanding of the topic - don't understand how they do it is immaterial to the fact that they do it.



"A study"? No. I believe I've been saying from the get-go that this stuff has its place. The conclusion that you're projecting onto the paper? It's absolutely terrible for that. Because again: Vague subjective measurements do not prove specific objective conclusions. This is not a negotiable point, Phoenix. You're wrong, and you are misrepresenting the paper. End of story.

And really? We're back to the "prove it happens more often" bullshit? I believe I already got into that:
I will get covid and the flu again, what I care about is the IFF for them, was the IFF data interpreted wrong? If not, then that's exactly why I posted it and cared about it. Covid is less deadly than the flu in that regard. Hence, why I said if i was to get the flu or covid and I could actually choose which one I get somehow, I'd pick covid, it's less deadly and symptoms for me last quite a bit shorter than the flu. Also, from this last fall, winter, spring cold season, there wasn't a covid surge. It looks like covid won't be spreading at numbers nearly as high it did the 1st couple years.

All I said was you can't determine how someone with long symptoms comes into a doctor office months after an infection, you don't have a way to determine what triggered it. You have the short-term and long-term antibodies like you said, but the short-term are too short and the long lasts too long.

The paper I provided is literally better than any of the long covid papers. If my paper isn't good enough for you, then the long covid papers are like 10 times worse. Covid is comparable in that regard in rate because with covid being around the first couple years, it caused basically every other respiratory virus to disappear, thus if people are catching at worst the same amount of respiratory illnesses total, then it doesn't matter if covid is infecting more than the flu or RSV or other coronavirus, you're still getting the same amount of respiratory illness in the population.

1) Why? What do you think such a comparison is going to demonstrate that's of any particular use? Why does this somehow invalidate the relevance of chronic symptoms following covid infection?

2) It's not useful to demand answers that (presumably) you know don't exist.

There is plentiful evidence that people can have long-term ill-effects from infection, even after the acute period has ended. This is extraordinarily hard to measure, because we are subjected to a wide range of infections, some of which we may even be barely aware of. Pinning these on a specific virus would be at minimum very hard. We know it happens - chronic fatigue syndrome is likely a long-term disturbance of the body's immune system caused by infection. Long covid is interesting, because it gives us a relatively clear example of such long-term effects due to a novel and extremely pervasive virus, as it can be much more easily teased out from the background noise.

There are two good biological reasons to believe covid may be more problematic than things like influenza. Firstly, over time viruses adapt to their hosts and hosts to viruses. Infections that have been widespread in the population a long time may therefore be less likely to disrupt the immune system or cause unusual complications because this adaptation has already taken place. Then, of course, most people will already have been exposed to them (or one very similar) at some point anyway, but this will be spread over a much longer time period: for instance, in any given year, most people don't catch 'flu.
At what point was I trying to invalidate anyone's chronic symptoms? I want to know at what rate in comparison to other viruses to know if it's something to be concerned about. If it's the same as other common respiratory infections, then why would long covid be something to be concerned about anymore than any other long whatevers?

If someone is claiming long covid to be something to be concerned about (more than long anything else) like calling it a "mass disabling event", they need to prove their claim, not me. I'm asking for such proof.


Well, the covid is now about to be considered as equal to the ordinary seasonal flu, in terms of dangerosity, according to the WHO.

That's nice. I don't really care about those who will react with "see, see, it's the proof it was never dangerous". The pandemic evolves and dies out as they do. I don't even care that much about its source, to be honest. A mix of fatigue and the assumption that certainties will stay out of reach.

My hope is that we've learnt something that will help us deal better with the next one (which I imagine pending). Socially, I'm not sure. But medically, at least, the little jump in RNA-based technology and its various applications is probably an advantage that will stay.
The CDC doesn't change their recommendations based on new information like basically all of our other peer nations have done...
 

Asita

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I will get covid and the flu again, what I care about is the IFF for them, was the IFF data interpreted wrong? If not, then that's exactly why I posted it and cared about it. Covid is less deadly than the flu in that regard. Hence, why I said if i was to get the flu or covid and I could actually choose which one I get somehow, I'd pick covid, it's less deadly and symptoms for me last quite a bit shorter than the flu. Also, from this last fall, winter, spring cold season, there wasn't a covid surge. It looks like covid won't be spreading at numbers nearly as high it did the 1st couple years.
That is backpedaling, but moving on...

All I said was you can't determine how someone with long symptoms comes into a doctor office months after an infection, you don't have a way to determine what triggered it. You have the short-term and long-term antibodies like you said, but the short-term are too short and the long lasts too long.
That's why it's not an "either/or" situation, Phoenix. It's an "and" situation, and it's not a difficult concept. You don't look for one smoking gun trait. It's like building a case in court, there's rarely going to be a single piece of evidence that conclusively proves the case for the defense or prosecution, it's about evaluating the story that a lot of little - often circumstantial - pieces of evidence tell in concert.

You're not trying to understand how this works, you're trying to disprove it as a matter of principle.

The paper I provided is literally better than any of the long covid papers. If my paper isn't good enough for you, then the long covid papers are like 10 times worse. Covid is comparable in that regard in rate because with covid being around the first couple years, it caused basically every other respiratory virus to disappear, thus if people are catching at worst the same amount of respiratory illnesses total, then it doesn't matter if covid is infecting more than the flu or RSV or other coronavirus, you're still getting the same amount of respiratory illness in the population.
Bluntly, Phoenix, you have abundantly demonstrated that you lack the ability to make such a determination, as you have proven yourself either unable or unwilling to understand the contents of these studies, understand their methodologies and the limitations thereof, or interpret their results. You aren't making an informed determination on merit, you're just picking your favorite based on your mistaken presumption that it validates your opinion. Never mind that what I've been explaining to you is that the paper doesn't say what you claimed it did, and that the conclusion you attributed to it was well outside the scope of its data.
 
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Silvanus

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I literally linked the article that said it was unable to get enough staff...
No, you linked an article in which they left it far too late and then failed to hire.

Where was this proof of a virus similar to covid that was already widespread and contact tracing worked?
You've been provided with instances of contact tracing successfully reducing transmission for both influenza outbreaks and for covid itself.

If you always require an exact 100% analogous situation to have happened in the past before you make any decisions, you'd never make any public health decisions whatsoever. We have no choice but to look to similar situations, which have similarities but are not going to be 1-to-1.

Then why did Fauci say it was still OK to go about your normal daily lives on Feb 29th if they knew with any accuracy how many infections there were?
You'd have to ask Fauci. Not really sure why you expect me to provide justifications for what someone else said.
 

Ag3ma

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Then why did Fauci say it was still OK to go about your normal daily lives on Feb 29th if they knew with any accuracy how many infections there were?
I think one of the things that really fucks me off the most are the backseat drivers in the commentariat (this includes people like Vinay Prasad) who carp on and on about all sorts of things from the complacency of never having to make a difficult decision and usually with lashings of hindsight. The point is not that Fauci, the CDC and so on were always right. It's that they had to make tough calls often with limited data and a wide range of other factors to take into account. The only question we really need to ask is "Did they make a reasonable decision given the situation and information available at the time?"

The answer to this is, I think, in nearly all cases "Yes".

It's like that inevitable spectator at a football game who tells you who should be playing, where and how, and clearly thinks they could do a better job than the manager (/coach, if American). That guy is almost always wrong, and always a wanker.
 
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Silvanus

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I think one of the things that really fucks me off the most are the backseat drivers in the commentariat (this includes people like Vinay Prasad) who carp on and on about all sorts of things from the complacency of never having to make a difficult decision and usually with lashings of hindsight. The point is not that Fauci, the CDC and so on were always right. It's that they had to make tough calls often with limited data and a wide range of other factors to take into account. The only question we really need to ask is "Did they make a reasonable decision given the situation and information available at the time?"

The answer to this is, I think, in nearly all cases "Yes".

It's like that inevitable spectator at a football game who tells you who should be playing, where and how, and clearly thinks they could do a better job than the manager (/coach, if American). That guy is almost always wrong, and always a wanker.
Yep. Not to mention the fact that Phoenixmgs has himself excused a medical practitioner (that he likes) arguing early on that covid-19 would be over in a few months.

The practitioner himself admitted he was wrong. Phoenixmgs then endlessly argued that it was a perfectly reasonable mistake that lots of people made.

OK, yes, sure, whatever. Except... now he's willing to use a similar-- but much smaller-- error to besmirch someone he doesn't like.
 

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That is backpedaling, but moving on...



That's why it's not an "either/or" situation, Phoenix. It's an "and" situation, and it's not a difficult concept. You don't look for one smoking gun trait. It's like building a case in court, there's rarely going to be a single piece of evidence that conclusively proves the case for the defense or prosecution, it's about evaluating the story that a lot of little - often circumstantial - pieces of evidence tell in concert.

You're not trying to understand how this works, you're trying to disprove it as a matter of principle.



Bluntly, Phoenix, you have abundantly demonstrated that you lack the ability to make such a determination, as you have proven yourself either unable or unwilling to understand the contents of these studies, understand their methodologies and the limitations thereof, or interpret their results. You aren't making an informed determination on merit, you're just picking your favorite based on your mistaken presumption that it validates your opinion. Never mind that what I've been explaining to you is that the paper doesn't say what you claimed it did, and that the conclusion you attributed to it was well outside the scope of its data.
How is that backpedaling, this is the current state of covid... You don't use 2020 covid logic to make 2023 covid recommendations.

So you're solution to figure out the rate of long covid is to do a full investigation of every possible long covid case at every doctor's office across the country using the same methods that they all have to use? Doing an actual study would be a much better use of resources. Every such study hasn't said long covid is anything to be overly concerned about.

The papers I have linked at way better from an objective standpoint than any long covid paper saying it's some major problem. You nor anyone has linked to any paper worth a damn that says long covid is anything to be worried about. If the rate of covid triggering long-term symptoms is any more than other similar viruses, then prove it. Again, how science works is that people that claim something have to prove it, I'm merely calling bullshit and asking for the proof, which hasn't been provided.


No, you linked an article in which they left it far too late and then failed to hire.



You've been provided with instances of contact tracing successfully reducing transmission for both influenza outbreaks and for covid itself.

If you always require an exact 100% analogous situation to have happened in the past before you make any decisions, you'd never make any public health decisions whatsoever. We have no choice but to look to similar situations, which have similarities but are not going to be 1-to-1.



You'd have to ask Fauci. Not really sure why you expect me to provide justifications for what someone else said.
From reading the following article, you think contact tracing in the US would be a smart use of resources? If you think that, then your logic is way fucking off.

The effectiveness of the contact tracing to resources spent is not worth the resources when those can be applied to other things that improve people's health by a lot more.

My point is THEY (which includes Fauci obviously) had no idea how many covid infections there were.


I think one of the things that really fucks me off the most are the backseat drivers in the commentariat (this includes people like Vinay Prasad) who carp on and on about all sorts of things from the complacency of never having to make a difficult decision and usually with lashings of hindsight. The point is not that Fauci, the CDC and so on were always right. It's that they had to make tough calls often with limited data and a wide range of other factors to take into account. The only question we really need to ask is "Did they make a reasonable decision given the situation and information available at the time?"

The answer to this is, I think, in nearly all cases "Yes".

It's like that inevitable spectator at a football game who tells you who should be playing, where and how, and clearly thinks they could do a better job than the manager (/coach, if American). That guy is almost always wrong, and always a wanker.
Dude, I FUCKING KNEW it wasn't safe to go about normal life at that very time, it was fucking common sense. Marty Makary is on record saying January 2020 that actions needed to be taken. It wasn't hindsight. The CDC and Fauci have constantly been on record of not making the right decisions time after time. You can just look to the US peer countries that actually followed science like all of Europe knew schools should stay open yet schools remained closed for 18 FUCKING MONTHS in tons of cities like Chicago and California cities. Just about every European country has done something with regards to not recommending or banning mRNA vaccines for younger males that have the highest risk of myocarditis, the US has still done nothing because they want their precious one-size-fits-all recommendations to be true. Public health in the US has literally acted like Donald Trump and constantly doubling-down on every claim and never admitting they messed up. They lied about natural immunity, lied about masks, lied about the myocarditis issue, lied about boosters, the list goes on and on. It's not Monday morning quarterbacking as I can literally point to tons of other countries that made the exact opposite choices the US made at the exact same time in the pandemic. One top advisor for the UK literally answered the question of why they aren't masking kids because that's just plain stupid.
 

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Finally, the charade has ended!!!!! And literally everyone wasn't masking on Monday and it's been wonderful. And all the staff is telling any visitor right away that masks aren't required.

1680031750805.png
 

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How is that backpedaling, this is the current state of covid... You don't use 2020 covid logic to make 2023 covid recommendations.
Backpedaling meaning that you changed your position mid-argument to avoid having to own up to having been wrong. Your position has consistently been - for a long time now - that methods to contain Covid were excessive on the grounds that Covid was less dangerous than the flu. How was it that you put it? Oh yes, something to the tune of "lockdowns cost more lives than Covid"? That makes it pretty clear that your position was applied to the general population, and you've been scrambling to evidence that claim since 2021.

Hell, in this conversation, the very thing I was taking you to task over was your rhetorical question of "The question would be, did covid kill more kids than the flu USUALLY does during that time". In no uncertain terms: Did it kill more in that period. That is explicitly a population question. And yet now you're claiming that you were only ever talking about raw lethality purely on an individual level?

Pull the other one.

So you're solution to figure out the rate of long covid is to do a full investigation of every possible long covid case at every doctor's office across the country using the same methods that they all have to use? Doing an actual study would be a much better use of resources. Every such study hasn't said long covid is anything to be overly concerned about.
I'm not trying to figure out the rate of Long Covid. In fact I've repeatedly pointed out that comparative incidence rate is irrelevant. To repeat:

it's further worth noting that even if you had been right about comparative incidence rate, it would still be - once again - irrelevant, because concerns about Long Covid are not predicated on comparative incidence rate as contrasted with the long term aftereffects for other diseases. This isn't a footrace wherein all the prize money goes to the first person past the post.

Generously, that'd be what we'd call the Fallacy of Relative Privation (aka the "Appeal to Worse Problems" Fallacy), a positively puerile fallacy that insists that if something isn't the foremost example of its kind, it's not worth concerning yourself with. Eg, "Breast Cancer isn't as bad as Brain Cancer, so why do we make a big deal about being vigilant about it?" When you understand why trying to object to Breast Cancer screenings by comparing Breast Cancer's fatality rate to that of Brain Cancer is idiotic, you will understand why the argument you just attempted by misrepresenting that study is equally stupid.
What I've been explaining to you is how doctors make a positive diagnosis for long covid, which you have been insisting was impossible despite the very studies you cited - under the delusion that they supported your arguments - being predicated on those same methods.


The papers I have linked at way better from an objective standpoint than any long covid paper saying it's some major problem. You nor anyone has linked to any paper worth a damn that says long covid is anything to be worried about. If the rate of covid triggering long-term symptoms is any more than other similar viruses, then prove it. Again, how science works is that people that claim something have to prove it, I'm merely calling bullshit and asking for the proof, which hasn't been provided.
1) Once again: comparative incidence rate is irrelevant.
2) You're a random schmuck on the internet demanding that other random schmucks on the internet provide you with in-depth technical explanations that you have demonstrated yourself incapable of understanding, and then interpreting your failure to understand those explanations as meaning that the underlying position - not your understanding, not even the explanation, but the position - was deficient.
2a) In actuality, it's mostly just down to you being an obstinate contrarian.
3) Again: what I've been explaining to you is that the paper doesn't say what you claimed it did, and that the conclusion you attributed to it was well outside the scope of its data. That's not even an argument against the paper, that's saying you misunderstood and misrepresented it.
 
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Silvanus

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From reading the following article, you think contact tracing in the US would be a smart use of resources? If you think that, then your logic is way fucking off.
OK, let's put this in the context of resource allocation. Which of the following is a better expenditure for public health and wellbeing:

1) contact tracing;

2) ensuring Exxon-Mobbil makes 0.01% higher profit in a year?

The effectiveness of the contact tracing to resources spent is not worth the resources when those can be applied to other things that improve people's health by a lot more.
It's not either/or, as has been explained many times over. More than enough resources exist to do both.

My point is THEY (which includes Fauci obviously) had no idea how many covid infections there were.
...yet they knew enough to implement restrictions. They considered the high (and fast growing) rate of diagnosed infection, combined with the knowledge that undiagnosed cases will be much higher, to be enough information.
 

Ag3ma

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The CDC and Fauci have constantly been on record of not making the right decisions time after time. You can just look to the US peer countries that actually followed science like all of Europe knew schools should stay open yet schools remained closed for 18 FUCKING MONTHS in tons of cities like Chicago and California cities.
Fauci and the CDC didn't shut those schools, though, did they?

Fauci said plenty about schools - including advocating keeping them open as much as possible. But Fauci also had to point out, because the facts said so, that children are hospitalised by and die of covid, that open schools will increase spread of covid, and so on. The right-wing bullshit machine likes to pretend this was Fauci being "wrong", and to make out he ordered school closures, and they evidently suckered you hook, line and sinker. But he wasn't wrong and he didn't shut schools. Mostly, he just told people what the score was, and the decisions to shut schools were made by state or local authorities.

Just about every European country has done something with regards to not recommending or banning mRNA vaccines for younger males that have the highest risk of myocarditis, the US has still done nothing because they want their precious one-size-fits-all recommendations to be true.
So you might think... but that's the peril of watching so many YouTube videos by people who want you to freak out about vaccine-related myocarditis.

However, the USA for the most part did not have a traditional viral vector vaccine: regulators did not give approval to the AZ/Oxford vaccine because they had (not wholly unreasonable) concerns about the clinical trial data, and the J&J/Janssen vaccine has it's own adverse side effects even if it might be better for myocarditis. And it might not be better for myocarditis, because data suggests myocarditis is an increased risk of any vaccine anyway (although very rare). Plus, vaccine-related myocarditis even amongst this most vulnerable group was exceptionally rare and overwhelmingly low severity when it occurred. In fact, inevitably of course, Covid infection in the unvaccinated caused a higher risk of myocarditis (mild or severe). So... the better alternative to the mRNA vaccines for US men under 25 was, er, nothing obviously supportable by the data, or available.

In other words, the decision of the US regulators was at minimum reasonable by the data and situation. There's not really a problem here. There's a problem manufactured by the right wing, anti-vaxxers, and self-interested narcissists like ZDogg and Prasad who've found a bunch of suckers to sell subscriptions and YouTube advertising to.

They lied...
:rolleyes:

I hope, one day, you can realise that you don't have to stress yourself out unnecessarily by believing any quack with a YouTube channel who has realised conspiracy theory and bad science is a way to make money.