[Home] [Headlines] [Latest Articles] [Latest Comments] [Post] [Sign-in] [Mail] [Setup] [Help]
Status: Not Logged In; Sign In
|
World News See other World News Articles Title: Data From US Medicare and the New Zealand Ministry of Health It's finally here: record-level data showing vaccine timing and death date. There is no confusion any longer: the vaccines are unsafe and have killed, on average, around 1 person per 1,000 doses. Executive summary Today you will get to see the data that nobody wants you to see. FINALLY. No State or country has ever released record-level public health data on any vaccine. Privacy is not the reason for this; the data can be easily obfuscated (which we did on this data) so that no record entry would match that of any person, living or dead. The reason the data is kept secret is simple: it would expose the fact that the COVID vaccines are unsafe, as well as all the vaccines that I have been able to get record-level data on. Today, thanks to a courageous whistleblower who works at the New Zealand Ministry of Health, we have record-level information from a large population of all ages and are making it public for the first time in history. Vitamin K2 (MK7) with ... Buy New $24.99 ($0.10 / Count) (as of 10:00 UTC - Details) Here is the Rumble video announcing the leak. There was a YouTube link as well, but YouTube censored it within minutes of posting, just like we knew they would. Just as you suspected, the COVID vaccines have killed millions of people worldwide, an estimated 1 death per 1,000 doses on average in a standard population. And now we have the data to prove it. The MIT slide presentation You can read my “Is it safe?” MIT presentation slides here. I highly recommend reading the slides and/or watching the livestream. I tried to make the slides self-standing, but the livestream can be helpful in explaining some of the slides. I also periodically dump a PDF version of the presentation to my skirsch.com web server. The PDF version is searchable and you can copy/paste text from it (such as the access keys for the Wasabi server so you can download all the goodies). The MIT talk livestream links Here is the Twitter livestream. Here is the Rumble livestream. Downloading the data The presentation has everything you need including the credentials to download all the data (search for “Wasabi” in the PDF version of the slide deck). Here are the Wasabi credentials to make it easy: Public API keys: access-key= BDBT2BD1KKIXKPWY3030 secret-key= 5GQVqz9uDsmrYjLuNW24tRPzwPuPe0TTleUdpSF3 You can only access the data-transparency bucket for now. Trust me, there’s more that I’m not disclosing yet (including a new US source other than Medicare). Wasabi explorer downloads are here for PC and Mac. You can also use CyberDuck or any other S3-compatible browser. Make sure your destination folder is writable when you copy files from the server. You can also use rclone to make a local copy of the repository on your system: What you will find The data: All the data in the data-transparency bucket is sanitized. Any matches to actual records is completely accidental. The data was sanitized in a way that preserves the statistics. We ran the bucket analysis on the original and obfuscated data and got nearly identical results. There is no reason any health authority couldn’t do the same thing we did. The tools: We’ll give you our time-series cohort analysis software. This is the software that you’ll never get your State epidemiologist to use. Now, armed with record-level data, you can do your own analysis. We’ve made it super easy to use. When done, paste the output file into our v4 analysis .xlsx spreadsheet and you’ll see instantly whether the vaccine is safe or not. The analysis documents: You’ll find annotated spreadsheets as well as word documents. The description of the data: You’ll find documents describing the dataset (size, dates, average ages in each cohort, what the authorities claim, etc. I encourage you to explore. Everything is “legal” in that jurisdiction. So you’ll see the full times of people who died in the Maldives, for example. In other places, the names are omitted. Introduction I was provided the data on November 8, 2023 when it was uploaded to my Wasabi file server. I was asked by the whistleblower to keep the data confidential until November 30 in order to give the whistleblower time to work out the logistics of how the data would be made public. I honored my commitment and only shared it with a handful of colleagues including Norman Fenton and his associates in the UK with the whistleblower’s consent. The data from New Zealand is not perfect; it is not a complete sample. For example, for some people, the first record in the database is Dose #3. Also, only vaccinated people are in the database. But, by using a cohort time-series analysis, it doesn’t matter. There is no possible way that this data is consistent with a safe vaccine. I estimated that the vaccine killed, on average, about 1 person per 1,000 doses. That means an estimated 675,000 Americans were killed by the COVID vaccines. Zinc Quercetin 500mg w... Buy New $32.97 ($0.27 / Count) (as of 10:00 UTC - Details) We have confirmation of the analysis from the US Medicare data thanks to another whistleblower. The story of the data can be found in my presentation which has a link to the Wasabi server and access credentials, as well as how to download the free Wasabi File Explorers for PC and Mac. There is a large amount of data and analysis uploaded to the servers. The cohort time-series analysis takes about 2 hours to run on the data. We’ve included the output files so you can start from that. Analyzing the data takes about 5 minutes using the v4 spreadsheet in the analysis directory. Anyone can do it. You just plug in numbers to vary the parameters to look at anything you want to investigate. It has 8 visualizations: 4 main graphs (one for each independent variable) and 4 below each graph showing the number of deaths so you can use that to judge the reliability of the data points in the graph above. Be sure to read the entire presentation to understand how to interpret the data. Papers about the data Papers will be coming out from various authors over the coming weeks. See this article which I will update over time. Summary of what we found Record level vaccination-date/death data obtained from a whistleblower in the New Zealand Ministry of Health was analyzed using a standard time-series cohort analysis. The results remained consistent even after varying all four of the key independent variables (observation time window, days after shot, age, and dose number). The only way that can happen is if the COVID vaccines significantly increased mortality for those aged 60 and older, the very population that the vaccine was supposed to help. All five Bradford Hill causality criteria are satisfied. From this data, we can accurately estimate that overall, the mRNA vaccines led to the premature death of more than 1 person per 1,000 doses on average over all doses. This estimate is supported by COVID death data from Medicare obtained from another whistleblower. The data from Medicare was stunning: the number of people who died rose monotonically for those who got shot in 2021 or 2022. My whistleblower inside HHS had never seen anything like that before. It was a perfectly straight line sloping upwards for 365 days since the dose was given. A safe vaccine would see a decline in deaths by 4% to 5% after 1 year from the shot. The COVID vaccines had a 26% mortality increase, a net difference of 30%. This makes the COVID vaccine a competitor to heart disease as the leading cause of death among the elderly (which kills 20% of people per year). Read the Whole Article Poster Comment: Post Comment Private Reply Ignore Thread
|
||
|
[Home]
[Headlines]
[Latest Articles]
[Latest Comments]
[Post]
[Sign-in]
[Mail]
[Setup]
[Help]
|
||