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Medical schools are run by big phara period end of story. My buddy had a major heart attack. there answer was 12 Scripts and open heart surgery. He reversed his heart disease with a no oil vegan diet. He found the diet from a doctor at the Cleveland clinic. His doctor told him it wouldn't work. this happened ten years ago and he's on ZERO meds. Doctors today don't want to cure you they want to write you a script.

Look at the 1/6 bs. The FBI and other government agency's flat out participated in these events to make them worse. Why isn't congress or better yet why isn't the republican caucus working in a united front to point this out????

And they've been brainwashed by social media, Big Tech, and the MSM. They have no grip on what's real and what's fake

Again why after two years isn't there a protocol for before your infected you can take on a daily basis and a protocol for after you're infected??? My answer is they A want to force vaccination and B want people to die

I'm not butt hurt at all I'm pointing you have the problem or butt hurt by what I post.

Is there a condition of being on the board that requires you to read or comment on my posts?

That came from Antarctica. Admiral Bird discovered it during operation high jump

Yep

Worldwide Bayesian Causal Impact Analysis of Vaccine Administration on Deaths and Cases Associated with COVID-19: A BigData Analysis of 145 Countries Policy makers and mainstream news anchors have promised the public that the COVID-19 vaccine rollout worldwide would reduce symptoms, and thereby cases and deaths associated with COVID-19. While this vaccine rollout is still in progress, there is a large amount of public data available that permits an analysis of the effect of the vaccine rollout on COVID-19 related cases and deaths. Has this public policy treatment produced the desired effect? One manner to respond to this question can begin by implementing a Bayesian causal analysis comparing both pre- and post-treatment periods. This study analyzed publicly available COVID-19 data from OWID utlizing the R package CausalImpact to determine the causal effect of the administration of vaccines on two dependent variables that have been measured cumulatively throughout the pandemic: total deaths per million (y1) and total cases per million (y2). After eliminating all results from countries with p > 0.05, there were 128 countries for y1 and 103 countries for y2 to analyze in this fashion, comprising 145 unique countries in total (avg. p < 0.004). Results indicate that the treatment (vaccine administration) has a strong and statistically significant propensity to causally increase the values in either y1 or y2 over and above what would have been expected with no treatment. y1 showed an increase/decrease ratio of (+115/-13), which means 89.84% of statistically significant countries showed an increase in total deaths per million associated with COVID-19 due directly to the causal impact of treatment initiation. y2 showed an increase/decrease ratio of (+105/-16) which means 86.78% of statistically significant countries showed an increase in total cases per million of COVID-19 due directly to the causal impact of treatment initiation. Causal impacts of the treatment on y1 ranges from -19% to +19015% with an average causal impact of +463.13%. Causal impacts of the treatment on y2 ranges from -46% to +12240% with an average causal impact of +260.88%. Hypothesis 1 Null can be rejected for a large majority of countries. This study subsequently performed correlational analyses on the causal impact results, whose effect variables can be represented as y1.E and y2.E respectively, with the independent numeric variables of: days elapsed since vaccine rollout began (n1), total vaccination doses per hundred (n2), total vaccine brands/types in use (n3) and the independent categorical variables continent (c1), country (c2), vaccine variety (c3). All categorical variables showed statistically significant (avg. p: < 0.001) postive Wilcoxon signed rank values (y1.E V:[c1 3.04; c2: 8.35; c3: 7.22] and y2.E V:[c1 3.04; c2: 8.33; c3: 7.19]). This demonstrates that the distribution of y1.E and y2.E was non-uniform among categories. The Spearman correlation between n2 and y2.E was the only numerical variable that showed statistically significant results (y2.E ~ n2: rho: 0.34 CI95%[0.14, 0.51], p: 4.91e-04). This low positive correlation signifies that countries with higher vaccination rates do not have lower values for y2.E, slightly the opposite in fact. Still, the specifics of the reasons behind these differences between countries, continents, and vaccine types is inconclusive and should be studied further as more data become available. Hypothesis 2 Null can be rejected for c1, c2, c3 and n2 and cannot be rejected for n1, and n3. The statistically significant and overwhelmingly positive causal impact after vaccine deployment on the dependent variables total deaths and total cases per million should be highly worrisome for policy makers. They indicate a marked increase in both COVID-19 related cases and death due directly to a vaccine deployment that was originally sold to the public as the “key to gain back our freedoms.” The effect of vaccines on total cases per million and its low positive association with total vaccinations per hundred signifies a limited impact of vaccines on lowering COVID-19 associated cases. These results should encourage local policy makers to make policy decisions based on data, not narrative, and based on local conditions, not global or national mandates. These results should also encourage policy makers to begin looking for other avenues out of the pandemic aside from mass vaccination campaigns. Some variables that could be included in future analyses might include vaccine lot by country, the degree of prevalence of previous antibodies against SARS-CoV or SARS-CoV-2 in the population before vaccine administration begins, and the Causal Impact of ivermectin on the same variables used in this study. Countries selected for Synthetic Control by rates of vaccination and average severity index since vaccine ad- ministration

Jimmy says your wrong and covid is the worst thing ever.

It's no big deal. I don't know one person that actually died of covid. I know one person that died of complications of being on a vent. I know multiple that died after taking vaccines. I love how you always follow me around the board like a little puppy. It makes me laugh.

I will find out in February

I didn’t get tested. My wife did as she wants the positive test as it excepts her from testing for 6 months at work if these biden mandates are upheld. I was sick first and then her about 12 hours later. Identical symptoms im Getting my annual physical at the end of February I will have my blood tested then for antibodies I’ll post the results of that test when I get them

And he’s a troll. It’s funny normally admins stop trolling. He’s one of the biggest on the board

https://youtube.com/shorts/QSNkde1hzss?feature=share

https://rumble.com/vs8tzw-maria-bartiromo-that-is-disgusting-i-know-for-a-fact-hcq-and-ivermectin-tre.html

Same response to you why do you care what I post. You’re not required to read or reply.

Not trying to rally anyone. You don’t have to read or respond to any of my posts but for sone reason you can’t seem to stop yourself from doing so

I’m pointing out to everyone here that the powers that be want to force vaccines and why that’s dangerous. Every person vaccinated and unvaccinated should fight mandates

AOC is a distraction. Stop giving her attention

You support forced vaccination and placement of people who aren’t vaccinated into camps?

Who said I’m speaking about individuals on the site?

Barns discussed this tonight on his podcast. It’s 100% true. @Woodtick Feel free to call me a tinfoil hat wearer

So about one month ago