You’ve all seen the stats and the claims - didn’t Prof Joe Brandon recently say that if you’re Goo-free you’re something like 97 times more likely to die of covid than the Goo-Goo’ed and boosted? I probably need to be ‘fact-checked’ on this, but lots of people make similar claims for Goo efficacy.
I'm going to make myself a big strong coffee and read that again. Admitedly, I got a little lost halfway. I understand, and agree with the point you are making absolutely, but the math will need a second read. Thanks Riggery
Data, and especially data from the government-Pharma consortium, is the grease being applied to the tracks they've built on the slippery slope of corporate fascism.
Thankfully, some of us saw the sign along the way that read,
What if the limbo period isn't the "Devil's Two Weeks" but actually extends for years? What if you define survivorship bias as not merely surviving, but having the same health you would have had without vax? (Counterfactuals, therefore difficult to prove.) What if the vax makes everything worse than it otherwise would have been for all those that have taken it? It wouldn't be the first drug to do that.
OK, now I have to go and ask my (mathematician) husband to translate this whole post. Actually, I'm hoping we'll both learn something! Thanks for this.
Love it. Now consider what happens to the crude rates over time as recovered become less susceptible to both infection and severe outcome. They are all still in the denominator somewhere but without knowing the distribution you can get considerable distortion of crude rates; not a big deal with 1% of the population previously infected; huge deal with 25+% of the population previously infected. If the distribution of the previously infected is not equal to the distribution of the vaccine, you results will skew. Not a very reliable metric 2 years in to a pandemic.
AND! if they are distributed proportionately, incidence rates should go down over time, all else being equal because they are dividing the incident rates by the entire cohort(s) even though many of them are no longer vulnerable to severe outcomes (or infection at all prior to Omicron)
Thank you for explaining the math. I had to read it a couple times, but it explains why the official efficacy being proffered by "#Foulci aka, the science" has made no since.
I'm not Will Hunting, but I am a calibrated bullshit detector and the reported efficacy has never correlated with the facts on the ground.
I'm going to make myself a big strong coffee and read that again. Admitedly, I got a little lost halfway. I understand, and agree with the point you are making absolutely, but the math will need a second read. Thanks Riggery
Data, and especially data from the government-Pharma consortium, is the grease being applied to the tracks they've built on the slippery slope of corporate fascism.
Thankfully, some of us saw the sign along the way that read,
"Danger - Bridge Out Ahead",
and jumped off before the edge of the ravine.
Thank you for showing your work.
What if the limbo period isn't the "Devil's Two Weeks" but actually extends for years? What if you define survivorship bias as not merely surviving, but having the same health you would have had without vax? (Counterfactuals, therefore difficult to prove.) What if the vax makes everything worse than it otherwise would have been for all those that have taken it? It wouldn't be the first drug to do that.
I'll come back to this one as well. Have 80 emails from Substack this morning so need to go through them quickly to sort the chaff from the grain.
OK, now I have to go and ask my (mathematician) husband to translate this whole post. Actually, I'm hoping we'll both learn something! Thanks for this.
The RKI, in Germany, is using (separate dealing with boosters aside):
eps(g) = 1 - P(d,v,s) / P(d,u) = 1 - mu
eps(g) - eps(c) = lambda
eps(0) - eps(g) = mu * lambda / (1+lambda)
So this is always between the c and the o. Unfortunately, they never publish any limbo figures so it is not possible to evaluate those other measures.
Love it. Now consider what happens to the crude rates over time as recovered become less susceptible to both infection and severe outcome. They are all still in the denominator somewhere but without knowing the distribution you can get considerable distortion of crude rates; not a big deal with 1% of the population previously infected; huge deal with 25+% of the population previously infected. If the distribution of the previously infected is not equal to the distribution of the vaccine, you results will skew. Not a very reliable metric 2 years in to a pandemic.
AND! if they are distributed proportionately, incidence rates should go down over time, all else being equal because they are dividing the incident rates by the entire cohort(s) even though many of them are no longer vulnerable to severe outcomes (or infection at all prior to Omicron)
Thank you for explaining the math. I had to read it a couple times, but it explains why the official efficacy being proffered by "#Foulci aka, the science" has made no since.
I'm not Will Hunting, but I am a calibrated bullshit detector and the reported efficacy has never correlated with the facts on the ground.
A, "jiggery-pokery" :-) Are you a fan of Astrid Lindgren?
Have you seen Fenton/Niel's paper along similar lines? They conclude that the UK data is "anomalous". https://probabilityandlaw.blogspot.com/2022/02/update-bmj-rejects-without-review-paper.html
A hugely misleading result is what they want and have always wanted.