Coronavirus in the United States - news and thoughts

LOL

 

It’s like you’re not allowed to die of anything other than Covid ...

Govt experts oppose downgrading Covid, citing excess cardio deaths

 

In the U.K. deaths from non-respiratory causes are projected to be a massive 10% higher than expected in 2022. Non-respiratory mortality typically varies little from year to year, changing by a maximum of just 1.3% in each of the six years from 2015 to 2020. However 2021 has registered a 3.72% increase and 2022 is projected to show a catastrophic 10.0% increase.

Hmm, what in the world could it be ?

 

Jay Downey on Instagram: "??????????????????jail"

 

One has to be utterly inhuman to laugh at the toll that COVID 19 has taken on pullout country and a truly callous mindset to laugh at the studies showing the number of lives saved by the vaccines. Then again, the posters here who made this thread unreadable with their anti-science based foolishness can take solace in the studies that show the significant mortality and serious illness differences between the vaccinated and unvaccinated and know that, in their own way, they contributed to scientific by spreading their garbage. Because they helped create the control group that died more and was sicker.

 

That was a model made by a liberal think tank to spit out a number they wanted.

It deserves a “come on man” more than a laugh. I laughed at it and gave a “winner” to the LOL to be nice…

Focused protection was the answer. The shots probably helped a few in the very early stages of when they were available. But they were a massive failure when you considering the one size fits all rollout. We knew who was at risk. We knew who was not. We had no long term data. We rolled this out as the silver bullet to end it. And it was the furthest thing from the truth. And if you ask me…they knew this. We
Destroyed trust in public health to line the pockets of a few. It is a travesty.

 

Okay, modeling and statistical expert that you are, tell me the methodological concerns here. Did they make faulty assumptions? I'm interested in hearing your underlying methodological concern.

 

You can model/simulate to create an answer you want. They have no clue if their model is accurate. Same crap happened at the beginning of this. And the idiots in public health fell for the fear and caused far more damage than was necessary. If only we listened to the Great Barrington Declaration. There was never going to be a perfect response to something like this. But good grief did we ever miss more than we hit…

A complete public health disaster. And nonsense models like the one a few posts ago were how we ended up with the disastrous response we got.

 

So that is a no, you can't actually say what is wrong with it? Because while they certainly could come up with a model to reach a result, you aren't presenting evidence that they did, other than not liking the final number, which isn't evidence.

It seems like you just don't like the results and would prefer other results that better fit your catchphrases and political ideology.

 

He’s just so bad at this.

 

Here is Dr. Bhattacarya in the early stages before we knew anything of substance on the virus. He touches implicitly on exactly what I am saying as the London Imperial College and facui peddled fear without knowing. Funny but not funny was Dr. Bhattacharya was an essential worker during the filming but the host was not…

 

Yes, statisticians can build models that are misleading. Is this model misleading? In what ways did they distort the data to create a misleading story about the underlying data?

 

Two points: (1) your anger is misdirected (2) you’re not half as angry as I am.

Not a soul has died of an imaginary rogue nanoparticle. Multitudes have died from the effects of gaslighting and hysteria.

 

It should be noted that Bhattacharya put his name on some absolutely ridiculous papers (most notably, the seroprevalence studies in Santa Clara and Los Angeles counties) that almost (and probably should have) lost the authors their tenure, as the mistakes in it were easily identifiable and so elementary as to be obviously intentional. They only survived because journals never published their studies.

Second, the difference between analyzing data and predicting future results should be obvious unless you are trying to be obtuse. The study you are criticizing directly was a backwards looking statistical model, while the Imperial College studies were based on a forward looking mathematical model. Just because both have the word "model" in their descriptions doesn't make them analogous.

Also, it should be noted that many of the critics of the Imperial College results did far worse in their projections in terms of accuracy. With mitigation, in fact, the IC models tended to underestimate total deaths a bit.

 

Bhattacharya is/was controlled opposition.

 

Since viruses don’t exist, the following categories are meaningless: immunity, herd immunity, seroprevalence, R0, etc.

 

DERP. lol This one got off his meds.

 

MOO. This one needs more hay.

 

Hmmm. Should I believe some idiots on a message board or studies based on vast amounts of data that show vaccinated people have much lower rates of death and hospitalization from covid than unvaccinated people do. Tough call.

 

Another term that is meaningless: vaccine efficacy.