I suggest you visit @EthicalSkeptic twitter feed. He has done the best work on modeling and forecasting on Covid by far. According to him, the vaccinated is 2.6x more likely to be infected than the unvaccinated. My personal experience also bears it out.
Firstly the incidence rates look really really low for the time period. Lauterbach would have committed murder for such low incidence rates.
Most importantly, I think they have also pulled the Bavaria/Hamburg trick. From the DSHS graphic towards the bottom:
Fully vaccinated population is defined as the number of cases who are determined to be fully vaccinated...
Boosted population is defined as the number of cases who are determined to be boosted in Texas...
Unvaccinated = everyone else.
There will be a lot of vaccinated and boosted people in that "unvaccinated" cohort numerator simply because their vaccination status was not recorded at the time of testing.
This is an old-fashioned missing information trick that has been pulled so many times that only those with a predetermined fish to fry could still fall for it.
when looking to solve for variable x(unvaccinated incidence rate) - shouldn't y(vaccinated) and z(boosted) be fully included in the scheme? I have seen this trick many times - split the vaccinated into separate buckets so if you compare one bucket to variable x - x will almost always look incredibly larger, but if you put ALL evidences of vaccinated (1 jab, 2 jab, 3 jab, 4 etc) into one cohort, then all the numbers for vaccinated fall apart completely. I personally love how these snake oil salesmen will pull out of the vaccinated equations any incidences that occur in the 14 days or 30 days after vaccination. sad comedy.
Okay. I don't mean to offend you, but to challenge you... My question is, how could ANY of this be "credible" when there is no proof, ever, anywhere, produced by anyone, that viruses actually exist? Never been isolated! Oh yes, there are people whose livelihoods depend on the existence of viruses, but... Where's the PROOF? There isn't any. Never shown to be anything, anywhere, at all. And these TESTS! What the hell good is a test for something that doesn't exist? Just wondering, after all your work sniffing out the bs, how you can ignore this glaring issue. No offense, I know it's been 200 years of BS, but... The truth is pretty well uncovered now... All anyone has offered is in silico "simulations" and a SOUP of horse serum, monkey kidney, milk, antibiotics, etc etc... How is this SOUP considered "isolation"? Okay, thanks.
Thank you for having the talent and the patience to go through claims like this. Your post would be excellent educational material in itself.
I suggest you visit @EthicalSkeptic twitter feed. He has done the best work on modeling and forecasting on Covid by far. According to him, the vaccinated is 2.6x more likely to be infected than the unvaccinated. My personal experience also bears it out.
Firstly the incidence rates look really really low for the time period. Lauterbach would have committed murder for such low incidence rates.
Most importantly, I think they have also pulled the Bavaria/Hamburg trick. From the DSHS graphic towards the bottom:
Fully vaccinated population is defined as the number of cases who are determined to be fully vaccinated...
Boosted population is defined as the number of cases who are determined to be boosted in Texas...
Unvaccinated = everyone else.
There will be a lot of vaccinated and boosted people in that "unvaccinated" cohort numerator simply because their vaccination status was not recorded at the time of testing.
This is an old-fashioned missing information trick that has been pulled so many times that only those with a predetermined fish to fry could still fall for it.
To me, the litmus tests of doctors or PH "experts are their public and private actions, posts, etc re all covid-related matters.
This quack is one of "them". What useful info he provides id also being provided by many others.
In fact, we need only about 40 SM accounts covering all the angles of covid scams to be sufficiently informed.
when looking to solve for variable x(unvaccinated incidence rate) - shouldn't y(vaccinated) and z(boosted) be fully included in the scheme? I have seen this trick many times - split the vaccinated into separate buckets so if you compare one bucket to variable x - x will almost always look incredibly larger, but if you put ALL evidences of vaccinated (1 jab, 2 jab, 3 jab, 4 etc) into one cohort, then all the numbers for vaccinated fall apart completely. I personally love how these snake oil salesmen will pull out of the vaccinated equations any incidences that occur in the 14 days or 30 days after vaccination. sad comedy.
Okay. I don't mean to offend you, but to challenge you... My question is, how could ANY of this be "credible" when there is no proof, ever, anywhere, produced by anyone, that viruses actually exist? Never been isolated! Oh yes, there are people whose livelihoods depend on the existence of viruses, but... Where's the PROOF? There isn't any. Never shown to be anything, anywhere, at all. And these TESTS! What the hell good is a test for something that doesn't exist? Just wondering, after all your work sniffing out the bs, how you can ignore this glaring issue. No offense, I know it's been 200 years of BS, but... The truth is pretty well uncovered now... All anyone has offered is in silico "simulations" and a SOUP of horse serum, monkey kidney, milk, antibiotics, etc etc... How is this SOUP considered "isolation"? Okay, thanks.