Pfizer & the Numbers- if you vaccinate 117,000 people to save one covid death, 9.04 people will have died from the vaccine ?

 

Posted Sep 23, 2021 by Martin Armstrong

COMMENT: Hi Marty,
I read your blog every morning.
Here’s some interesting math for you.
Number needed to vaccinate is 142 for Pfizer. (Moderna is 88 but I’ll use Pfizer for the demonstration).
So with Pfizer you need to vaccinate 117 people to prevent one CASE of covid. The current survival rate of covid is 99.86%, so approximately 1 death per thousand cases. So the NNV to prevent one covid DEATH is 117,000.
In the first 6 months of 2021, 134 million people were fully vaccinated in the US. VAERS listed 10,335 vaccine related deaths by that point, about 56 per day. Vaers has been proven to be underreported but let’s use it as a very rough conservative estimate.
So the 134 million / 10355 = 12,940 … one death per 12940 covid vaccinations.
So if you vaccinate 117,000 people to save one covid death, 117,000/12940 = 9.04 people will have died from the vaccine.
This is likely on the low end and also doesn’t include all the non-mortality vaccine side effects. It also doesn’t include the non mortality effects of covid either.
Interesting numbers though regardless.
Best regards
Rodger

REPLY: Very interesting analysis. There was a family friend who was in good health at 76. He was vaccinated, and suddenly within a month, he ended up in the hospital. One organ after the other was failing then came back. He finally recovered, but nobody could explain what the hell was going on. The doctors simply said they had never seen this before. It was like a mouse running around inside him, moving from one organ to the next. This is one giant experiment, and now Pfizer is claiming it is safe for 5-year-olds. But they are exempt from all liability and are making more money than ever. But we should trust them?

The FDA has been compromised. They are taking money from Bill Gates, who then, in turn, makes money from his ownership in Pfizer. If anyone did this in any other stock, the SEC would be dragging them in court. They took Elon Musk to court for simply saying he would take the company private. Bill Gates has so many conflicts of interest that we can NO LONGER trust the Biden Administration, the FDA, CDC, or Fauci.

Praying to Saints & Gods during a Pandemic

Posted Mar 31, 2020 by Martin Armstrong

A German cathedral has its collection of remains of St. Corona, the little-known Christian martyr who has been purported to be the patron saint of resisting epidemics. Her name in Latin merely means “crown,” which was an indication that the young saint had achieved the “crown of eternal life” because of the steadfastness of her faith. There is a connection with the coronaviruses, named because of their crown-like structure. So the virus is not named after her and there is not really any connection that can be verified that she is the patron saint of epidemics.

One of the excursions I have made in traveling around the world was to a tiny ancient city of Epidaurus in ancient Greece on the Argolid Peninsula at the Saronic Gulf. This is where people went to pray for their health. They prayed to Asclepius who was pictured with a staff with a serpent entwined which became our medical symbol still today. If you wanted to pray for the health of the community in times of a plague, you went to the temple next door for his daughter, Hygena, whose name is the origin of good hygiene.

Adapting Machine Learning for Medicine

Posted Feb 21, 2018 by Martin Armstrong

One project I want to move into after we finally get Socrates up for all levels of service is to turn toward medicine. Google’s AI algorithm predicts heart disease by scanning your eyes. They have used machine learning to accomplish what a doctor would do by traditional methods including blood work.

Medicine suffers from the same problem as financial analysis. It is dominated by opinion and that depends entirely upon (1) your experience and (2) the current situation. For example, a small child of about two was running a high fever. She was taken to the doctor who was flooded with flu patients. She was checked for the flu, found to be negative, and sent home. Day three, the fever was still there. Again, the little girl was taken back to another doctor. The same thing took place. After day four, the fever persisted and once more she was taken back to a doctor and the same thing took place.

Finally, the mother noticed she was not urinating and the child simply responded that it hurt. A fourth trip ended up admitting her to a hospital with a urinary infection that had by now started to impact her kidneys.

Medicine, like analysis, is dominated by opinion. If the doctor does not think of anything else to test, nothing takes place.

Machine learning can be used with a full body scanner and much more accurate results can be obtained. We need a machine that will also do a full body ultrasound scan, a simple pinprick for a drop of blood, and the machine could come up with a lot more information at a far lower cost than what we see today.