It seems some data are needed before reaching clear conclusions: the number of people in each vaccine status week after week. (We're having this debate in France over and over, but unfortunately, such data as those which were provided thanks to FOIA in Nova Scotia, or which used to be spontaneously provided in Island, Scotland or Ontario, do not exist in France. Not reliable ones, at least.)
b4 the jabs were rolled out Seneff & Nigh published a report on the jabs and all of the research, I took 3 days to read it and worked at understanding all of the research. My bottom line take away was the more of the jabs you received the higher the likelihood that you were going to have an adverse reaction leading to death.
everything they said was a negative possibility has come to pass, there were no positives that I could find in any of the research.
It IS interesting, however, that actually receiving ONE dose(only) appears to have the optimum outcome related to death over the entire timeline. Thoughts on that?
Is it possible to normalize this data to #/100,000 (or something similar)? It seems we'd expect higher raw count numbers in the vaxxed, since they are the much larger proportion of the population overall (but noting that the number with >2 doses is declining/additional dose, so the boosters look particularly ominous in these graphs).
The same criteria that you use to say some 0-dosers are actually (spike-transfection delayed)-1-dosers should also be used to count 1-, 2-, 3-dosers.
Or with a larger population base, the people in the two week injection incubation period could be tracked separately, to tease out the AEs, ADEs, and immune-suppressed.
I think there is another issue here (and it's been there from the start). Anyone who is vaccinated is likely to, perhaps quite frequently, present themselves for Covid tests. Further, those without any jabs (I hypothesize) are far, far less likely to present themselves for any tests.
To put it another way, those who are likely to get jabbed are also, in my opinion, likely to test frequently and therefore have a better chance to be associated with the negative results in these charts.
So "vaccination" consequences are probably being amplified (or to me less likely attenuated) by the circle of { sniffle | cough | ... | no reason whatsoever } -> test. If people weren't running to the doctor/tester constantly the results would be different.
I guess in general without totally random "testing" applied across a population by a known set of "testers" that are themselves unbiased in terms of process or the infection being tested for its hard to know for sure what is being shown with this data.
A FOIA request came in for Nova Scotia
It seems some data are needed before reaching clear conclusions: the number of people in each vaccine status week after week. (We're having this debate in France over and over, but unfortunately, such data as those which were provided thanks to FOIA in Nova Scotia, or which used to be spontaneously provided in Island, Scotland or Ontario, do not exist in France. Not reliable ones, at least.)
Relevant is this recent video interview between Mikki Willis and Mattias Desmet:
👀 Plandemic - Mass Formation: https://plandemicseries.com/massformation/ (7 min)
And, of course, I wonder what the “NUMBERS” would have been if all those dead-from-COVID had received SAFE and EFFECTIVE early treatment.
Dr. Peter McCullough said 85% could have been saved with early treatment (https://palaceintrigueblog.com/2021/12/15/dr-peter-mccullough-85-of-covid-deaths-couldve-been-prevented-with-early-treatment/).
b4 the jabs were rolled out Seneff & Nigh published a report on the jabs and all of the research, I took 3 days to read it and worked at understanding all of the research. My bottom line take away was the more of the jabs you received the higher the likelihood that you were going to have an adverse reaction leading to death.
everything they said was a negative possibility has come to pass, there were no positives that I could find in any of the research.
It IS interesting, however, that actually receiving ONE dose(only) appears to have the optimum outcome related to death over the entire timeline. Thoughts on that?
These clot shots are 95% effective of curing overpopulation, which was always their purpose.
Is it possible to tell if the "zero dose" group includes or excludes the 2 week period after the first dose?
It's not a coincidence that the CDC suspended its publication of US all-cause mortality data on June 3. It had been low up until then, but I suspect it was starting to spike so they stopped publishing it. https://data.cdc.gov/NCHS/Provisional-COVID-19-Death-Counts-by-Week-Ending-D/r8kw-7aab/data
The data should be presented with the per capita numbers for each cohort. Last October, the NS govt bragged that 85% were "fully vaccinated".
Keep charging, sister!
Is it possible to normalize this data to #/100,000 (or something similar)? It seems we'd expect higher raw count numbers in the vaxxed, since they are the much larger proportion of the population overall (but noting that the number with >2 doses is declining/additional dose, so the boosters look particularly ominous in these graphs).
Is it possible to tell if the "zero dose" group includes or excludes the 2 week period after the first dose?
But how do we get this information out with the media stonewalling?
The same criteria that you use to say some 0-dosers are actually (spike-transfection delayed)-1-dosers should also be used to count 1-, 2-, 3-dosers.
Or with a larger population base, the people in the two week injection incubation period could be tracked separately, to tease out the AEs, ADEs, and immune-suppressed.
Maybe Prof.Norman Fenton and colleagues (of which it would appear you are one), who did a mathy paper on this sort of systematic miscategorization could help figure out what the likely effects on the interpretation would be. https://www.researchgate.net/publication/358979921_Official_mortality_data_for_England_reveal_systematic_undercounting_of_deaths_occurring_within_first_two_weeks_of_Covid-19_vaccination
Excellent work. Thank you
I think there is another issue here (and it's been there from the start). Anyone who is vaccinated is likely to, perhaps quite frequently, present themselves for Covid tests. Further, those without any jabs (I hypothesize) are far, far less likely to present themselves for any tests.
To put it another way, those who are likely to get jabbed are also, in my opinion, likely to test frequently and therefore have a better chance to be associated with the negative results in these charts.
Or, perhaps, more tests equals more exposure to health care "professionals" who may (or may not) be more likely to have Covid (see: https://lwgat.blogspot.com/2020/05/coronavirus-georgias-early-reopening.html).
So "vaccination" consequences are probably being amplified (or to me less likely attenuated) by the circle of { sniffle | cough | ... | no reason whatsoever } -> test. If people weren't running to the doctor/tester constantly the results would be different.
I guess in general without totally random "testing" applied across a population by a known set of "testers" that are themselves unbiased in terms of process or the infection being tested for its hard to know for sure what is being shown with this data.
Makes my head spin!