Vaccine

[Hüsker Dü]

Yeah my son and I were kicked off the beach for fishing when the beach was reopened but had to be participating in an active activity. Apparently fishing wasn't active enough. Sitting on the beach was prohibited. You could only walk one way on the boardwalk and then the other way on the sand. You can't make this shit up.

Yeah closing the oceans, bays, lakes and the parking lots (pretty much all outdoor activity) was pretty stupid. In Australia they kept the ocean open but closed the beach itself which was semi-reasonable. Again though, they erred on the side of safety. Either way it went there would be faults, it’s human nature.

 

[dad4]

Agree, but you had idiot "experts" that tried to be relevant and made claims like this:

UC San Diego virus expert pleads with surfers to stay out of the ocean to avoid coronavirus

Kim Prather — a UC San Diego atmospheric scientist who studies how viruses and bacteria are ejected from the ocean — pleaded with surfers on Monday to stay out of the water to minimize …

www.sandiegouniontribune.com

Landmark case study finds coronavirus easily transmitted in ideal outdoor conditions

www.utsa.edu

Your article was from March 31, 2020. That‘s still within the 15 days you were complaining about. Cases were doubling every 3 days back then. We didn’t really have time to find the minimal intervention. The question is why didn’t we get going on opening oudoor spaces soon after.

The research paper in the second article sounds fine. It’s a computer simulation trying to estimate what kinds of outdoor conditions are better or worse for spread of viral particles. That’s one step towards figuring out to what extent a stadium in Italy is different from a beach in Malibu. This is exactly what you want the academics to be doing. If you want to open the safe things first, you need this kind of research.

 

[watfly]

Your article was from March 31, 2020. That‘s still within the 15 days you were complaining about. Cases were doubling every 3 days back then. We didn’t really have time to find the minimal intervention. The question is why didn’t we get going on opening oudoor spaces soon after.

The research paper in the second article sounds fine. It’s a computer simulation trying to estimate what kinds of outdoor conditions are better or worse for spread of viral particles. That’s one step towards figuring out to what extent a stadium in Italy is different from a beach in Malibu. This is exactly what you want the academics to be doing. If you want to open the safe things first, you need this kind of research.

Doesn't change the fact that these notions were in the heads of the health policy makers. Further proof that expert opinion is just that (and not fact), and that we shouldn't rely on computer simulations for real world situations.

 

[dad4]

Doesn't change the fact that these notions were in the heads of the health policy makers. Further proof that expert opinion is just that (and not fact), and that we shouldn't rely on computer simulations for real world situations.

You realize that your food is grown by people who rely very heavily on computer simulations for real world situations.

When a farmer decides whether to spray for pests, he doesn’t just guess. He uses computer simulations to make that decision. Will the current infestation keep growing? Or will the hot weather knock it back anyway? That’s a computer simulation question. The only difference is that one pathogen hits corn and the other hits people.

 

[Grace T.]

You realize that your food is grown by people who rely very heavily on computer simulations for real world situations.

When a farmer decides whether to spray for pests, he doesn’t just guess. He uses computer simulations to make that decision. Will the current infestation keep growing? Or will the hot weather knock it back anyway? That’s a computer simulation question. The only difference is that one pathogen hits corn and the other hits people.

Kinda like weather predictions, no?

 

[watfly]

You realize that your food is grown by people who rely very heavily on computer simulations for real world situations.

When a farmer decides whether to spray for pests, he doesn’t just guess. He uses computer simulations to make that decision. Will the current infestation keep growing? Or will the hot weather knock it back anyway? That’s a computer simulation question. The only difference is that one pathogen hits corn and the other hits people.

Hate to burst your bubble but farmers rely on far more than computer simulations. Computer simulations are only a tool and shouldn't be solely relied on, because they often are incorrect. It also depends on the quality of the data and how much the simulation is filling in the blanks. Better input can lead to better output, but computer simulations are inherently speculative for many reasons.

 

[Grace T.]

Hate to burst your bubble but farmers rely on far more than computer simulations. Computer simulations are only a tool and shouldn't be solely relied on, because they often are incorrect. It also depends on the quality of the data and how much the simulation is filling in the blanks. Better input can lead to better output, but computer simulations are inherently speculative for many reasons.

Then there's also the personal biases, blind spots and politics which can distort everything. The one disappointing thing about Birx's book is that it doesn't give a really good explanation as to why they abandoned the years of planning and suddenly panic. They had planned for this situation for years but all that was tossed out the window. The biggest post morten really needs to settle on studying that.

The track record for the experts and big unexpected surprises isn't good, particularly in the modern era. Understanding how that happened probably requires a lot of introspection the ruling classes just aren't capable of, particularly in the current environment. Just in this century:

-Hurricane Katrina and the response
-The Iraq war/WMB
-The 2008 bubble
-COVID and the response
-the current "transitory" inflation

 

[dad4]

Hate to burst your bubble but farmers rely on far more than computer simulations. Computer simulations are only a tool and shouldn't be solely relied on, because they often are incorrect. It also depends on the quality of the data and how much the simulation is filling in the blanks. Better input can lead to better output, but computer simulations are inherently speculative for many reasons.

Yes, agribusiness uses computer simulations, together with real world information, to predict disease growth and prevent serious outbreaks.

That is the same as public health agencies. They also use a mix of computer simulations and real world data.

It's not as simple as your claim that simulations are inherently inapplicable to real world situations. People use computers to help predict the real world all the time.

 

[Grace T.]

Yes, agribusiness uses computer simulations, together with real world information, to predict disease growth and prevent serious outbreaks.

That is the same as public health agencies. They also use a mix of computer simulations and real world data.

It's not as simple as your claim that simulations are inherently inapplicable to real world situations. People use computers to help predict the real world all the time.

Taking the weather analogy further, the models are actually pretty good and most of the time we come pretty close to predicting the weather overall. However, we all know that sometimes the models just get it wrong. It's gotten a lot better than our parents in the 70s (when the weather men would famously always duff it), but we've also been at it for a really really long time, and in comparison to a virus or the economy, with multiple variables involved such as how skittish humans react, it's a lot more simple.

The critique of the models is that they should only be a tool, and you can't rely upon them to make decisions alone. They are the starting point, not the end, for critical thought. And there is no disputing that there have been many incidents now where they've gotten it spectacularly wrong.

 

[dad4]

Taking the weather analogy further, the models are actually pretty good and most of the time we come pretty close to predicting the weather overall. However, we all know that sometimes the models just get it wrong. It's gotten a lot better than our parents in the 70s (when the weather men would famously always duff it), but we've also been at it for a really really long time, and in comparison to a virus or the economy, with multiple variables involved such as how skittish humans react, it's a lot more simple.

The critique of the models is that they should only be a tool, and you can't rely upon them to make decisions alone. They are the starting point, not the end, for critical thought. And there is no disputing that there have been many incidents now where they've gotten it spectacularly wrong.

And, like the weather, the 2 week epidemiology models are a whole lot better than the 6 month ones.

Which makes it really odd to criticize the decision to do a shutdown based on March 2020 models. The predicted problem wasn’t 6 months out in the future. If we kept doubling every 3 days, we were going to run out of ventilators and PPE in a matter of weeks. We were well within the range where the models are quite accurate.

 

[Grace T.]

And, like the weather, the 2 week epidemiology models are a whole lot better than the 6 month ones.

Which makes it really odd to criticize the decision to do a shutdown based on March 2020 models. The predicted problem wasn’t 6 months out in the future. If we kept doubling every 3 days, we were going to run out of ventilators and PPE in a matter of weeks. We were well within the range where the models are quite accurate.

But again, you don't know what you don't know...the ventilators turned out to be counterproductive and within 6 months the medical community had radically shifted their use from them

Further, it was ridiculous to apply a country wide model to a nation like the US. New York should have probably been shut down way before they did it. There was no point in shutting down Iowa during that particular time period. The models were behind the time in New York, and inapplicable to Iowa. The only thing that happened as a result was that the administration burned its lockdown bullet in one blow (both social and economically) in places that didn't need to be locked down instead of targeting it for when surges inevitably happened (which if the short models were accurate, they should have been able to predict weeks ahead of time). Then BLM hit and that torched any further chance for using a targeted approach (which BTW is what China is doing now, way too late and with a virus which spreads rampantly through apartment buildings).

Again, taking the weather model: they work pretty good in a place like SoCal...they work pretty badly in a place with all the micro climates like Hawaii.

 

[crush]

Hate to burst your bubble but farmers rely on far more than computer simulations. Computer simulations are only a tool and shouldn't be solely relied on, because they often are incorrect. It also depends on the quality of the data and how much the simulation is filling in the blanks. Better input can lead to better output, but computer simulations are inherently speculative for many reasons.

Not this farmer. He makes fake meat and fake food for your brain that is being destroyed.

 

[watfly]

Predicative models are based on assumptions determined by the modeler. We all know what happens when you "ass u me". I use computer predicative models in my work (albeit fairly simple models compared to scientific models) using great data and at best my response to those predictions is "huh, that's interesting". At best your prediction is a possibility with an uncertain probability. Predicative models should never be used for conclusions and only as a tool along with other information.

The problem with Covid was that experts speculated and jumped to conclusions. Conclusions that in some cases were a contradiction to long held medical findings. Compounding the problem was the fact that few experts issued "mea culpas" for their inaccurate opinions. Even if they did, that bell had already been rung.

 

[dad4]

But again, you don't know what you don't know...the ventilators turned out to be counterproductive and within 6 months the medical community had radically shifted their use from them

Further, it was ridiculous to apply a country wide model to a nation like the US. New York should have probably been shut down way before they did it. There was no point in shutting down Iowa during that particular time period. The models were behind the time in New York, and inapplicable to Iowa. The only thing that happened as a result was that the administration burned its lockdown bullet in one blow (both social and economically) in places that didn't need to be locked down instead of targeting it for when surges inevitably happened (which if the short models were accurate, they should have been able to predict weeks ahead of time). Then BLM hit and that torched any further chance for using a targeted approach (which BTW is what China is doing now, way too late and with a virus which spreads rampantly through apartment buildings).

Again, taking the weather model: they work pretty good in a place like SoCal...they work pretty badly in a place with all the micro climates like Hawaii.

Not sure where you get the idea that models don’t predict waves. Pretty much every wave has come a few weeks after a subvariant begins to show exponential growth. Ever since they started sequencing sewage specimens, we’ve had a few weeks warning before anything hits. It doesn’t tell you peak height, but it does tell you timing.

We saw it with Beta. That “huge hurricane off the coast.”. Osterholm had the timing right, and the size wrong.

In the case of April 2020, the timing data was bad enough. We didn’t have enough PPE to manage current caseloads. Letting it double for 3 more weeks would have been a huge problem. You can argue whether the actual peak would have been 15% or 50% of population. Well before we hit peak, the upswing itself was going to cause trouble.

 

[dad4]

Predicative models are based on assumptions determined by the modeler. We all know what happens when you "ass u me". I use computer predicative models in my work (albeit fairly simple models compared to scientific models) using great data and at best my response to those predictions is "huh, that's interesting". At best your prediction is a possibility with an uncertain probability. Predicative models should never be used for conclusions and only as a tool along with other information.

The problem with Covid was that experts speculated and jumped to conclusions. Conclusions that in some cases were a contradiction to long held medical findings. Compounding the problem was the fact that few experts issued "mea culpas" for their inaccurate opinions. Even if they did, that bell had already been rung.

Which “jump to conclusions”?

The main argument was that, absent a change to behavior, cases were doubling every 3 days. That was empirical, not speculative. You can plot it on log paper and see the point where we would have exceeded hospital capacity. It wasn’t very far out.

 

[watfly]

But again, you don't know what you don't know...the ventilators turned out to be counterproductive and within 6 months the medical community had radically shifted their use from them

Further, it was ridiculous to apply a country wide model to a nation like the US. New York should have probably been shut down way before they did it. There was no point in shutting down Iowa during that particular time period. The models were behind the time in New York, and inapplicable to Iowa. The only thing that happened as a result was that the administration burned its lockdown bullet in one blow (both social and economically) in places that didn't need to be locked down instead of targeting it for when surges inevitably happened (which if the short models were accurate, they should have been able to predict weeks ahead of time). Then BLM hit and that torched any further chance for using a targeted approach (which BTW is what China is doing now, way too late and with a virus which spreads rampantly through apartment buildings).

Again, taking the weather model: they work pretty good in a place like SoCal...they work pretty badly in a place with all the micro climates like Hawaii.

Sometimes I wonder if weather predictions would be more accurate if meteorologists actually looked out the window instead of staring at their computer.

In Utah the quip is if you don't like the weather just wait an hour. (I'm sure other states say the same thing). How hard is it to predict weather in San Diego.? If you said Sunny and 75 you'd probably be accurate 50% if time. SD has to have more TV weather people per weather event than any other city.

 

[watfly]

Which “jump to conclusions”?

Well certainly the outdoors issue that we are talking about. But the worst is no doubt the claim that the vaccine will prevent you from getting Covid which led to vaccine mandate policies and resulted in people losing their jobs.

 

[Happened again]

Which “jump to conclusions”?

The main argument was that, absent a change to behavior, cases were doubling every 3 days. That was empirical, not speculative. You can plot it on log paper and see the point where we would have exceeded hospital capacity. It wasn’t very far out.

the modeling was innacurate (everyone trying to CYA), vents were not the correct treatement (known very early on). The virus was/is novel. Early intervention as the grassroots wasn't encouraged. Imagine treating someone early, increasing chances of not coming back to the hospital VS telling someone to go home and if/when they got really sic, come back. It's kinda like medicining and doctoring was discouraged - everyone crossing their fingers that pharma would bail us out (ahh, the twinkle in big pharma's eyes).

 

[dad4]

Sometimes I wonder if weather predictions would be more accurate if meteorologists actually looked out the window instead of staring at their computer.

In Utah the quip is if you don't like the weather just wait an hour. (I'm sure other states say the same thing). How hard is it to predict weather in San Diego.? If you said Sunny and 75 you'd probably be accurate 50% if time. SD has to have more TV weather people per weather event than any other city.

TV weather people don’t actually do any forecasting. They are only there to look pretty when you’re done looking at the map.

Which is why SD needs them. You guys don’t need to actually look at the forecast, so it’s more important to have some eye candy to pass the time.

 

[watfly]

TV weather people don’t actually do any forecasting. They are only there to look pretty when you’re done looking at the map.

Which is why SD needs them. You guys don’t need to actually look at the forecast, so it’s more important to have some eye candy to pass the time.

Good point.