In May of 2020, I tried to tell three people about the Pfizer numbers you mentioned (162 placebo, 8 vaccinated); numbers easily found on Pfizer’s corporate website. One said it was too confusing for her to do the required 30 seconds of math, another said “Well, that was last year—we have more information now,” and the third offered a word salad of canned talking points. I never mentioned it to anyone again after that. It was like trying to tell someone that their partner is cheating on on them when the person really, really does not want to know.
As I understand it, “efficacy” has a more precise meaning in the context of a clinical trial. It describes how well a drug performs IN A CLINICAL TRIAL. By this definition, the Pfizer jab was 100% efficacious in pregnant women, for example, and all other vulnerable populations that were vetted, culled, or otherwise prevented from participating in the trial. Not to mention those that were eliminated from the trial when they got sick.
What I really don’t get is the assertion that time is a factor in effectiveness. Let’s say a trial starts on Day 0. On D1, nobody gets sick. Can we say the drug is 100% effective for one day? On D10, 10% of the non-placebo group gets sick. So after ten days, the drug loses 10% of its effectiveness? Or did it just take more time for more people to get sick as the virus spread?
Vax effectiveness is a function of relative risk so we need to know what the infection rate is in the unvaccinated population on each of these days as well.
The issue with the CDC classification of outcomes is that they are excluding cases in the recently vaccinated but not excluding people who are recently vaccinated from the pool of vaccinated people. This will drive the infection rate in the vaccinated down and exaggerate vaccine effectiveness as long as people continue to get jabbed.
The more rapid the uptake the greater the illusion of effectiveness.
In May of 2020, I tried to tell three people about the Pfizer numbers you mentioned (162 placebo, 8 vaccinated); numbers easily found on Pfizer’s corporate website. One said it was too confusing for her to do the required 30 seconds of math, another said “Well, that was last year—we have more information now,” and the third offered a word salad of canned talking points. I never mentioned it to anyone again after that. It was like trying to tell someone that their partner is cheating on on them when the person really, really does not want to know.
As I understand it, “efficacy” has a more precise meaning in the context of a clinical trial. It describes how well a drug performs IN A CLINICAL TRIAL. By this definition, the Pfizer jab was 100% efficacious in pregnant women, for example, and all other vulnerable populations that were vetted, culled, or otherwise prevented from participating in the trial. Not to mention those that were eliminated from the trial when they got sick.
You are correct. I should have referred to it as Vaccine Effectiveness when it was measured in the population
What I really don’t get is the assertion that time is a factor in effectiveness. Let’s say a trial starts on Day 0. On D1, nobody gets sick. Can we say the drug is 100% effective for one day? On D10, 10% of the non-placebo group gets sick. So after ten days, the drug loses 10% of its effectiveness? Or did it just take more time for more people to get sick as the virus spread?
Vax effectiveness is a function of relative risk so we need to know what the infection rate is in the unvaccinated population on each of these days as well.
The issue with the CDC classification of outcomes is that they are excluding cases in the recently vaccinated but not excluding people who are recently vaccinated from the pool of vaccinated people. This will drive the infection rate in the vaccinated down and exaggerate vaccine effectiveness as long as people continue to get jabbed.
The more rapid the uptake the greater the illusion of effectiveness.
Placebo effect, like nocebo effect, are real phenomenon. They have real world impacts. Their impact in this plandemic should not be underestimated.
Thank you!
Well done analysis.