Watch now (26 min) | What is causing the deaths: Covid, long-covid, lockdowns, healthcare or the vaccines?
The Ethical Skeptic attributes Sweden's relatively low excess deaths to PFE.
I wish I had the skills to play devils advocate to that, but not likely to happen any time soon.
In any case, the main thing is I want to say thank you. We'd all be very lost without people like you two.
Well I made a little .gif of it here:
People in chat were like 'you didn't label your x-axis' and I said "that's because you didn't look close enough.
A few minutes later i was banned :)
Thank you for following up on Igor's already brilliant work with this excellent, thorough analysis, which sets the scene for what we can expect from your new substack. In the "days of yore" this would be picked up by the media, questions asked in parliament, and neutral scientists eagerly pawing over the data, instead it will probably be silence.. (ps on this theme, this morning I wrote you a "welcome to substack" note... https://garysharpe.substack.com/p/the-ebony-tower )
I read all these articles (especially Joel Smalley and John Dee but also Igor Chudov and others) and I have absolutely no idea what a scatter graph is or what it shows! But I read the text and I understand most of that. It is all unremittedly bad and if even a non-science non-maths person like me can understand that it's all bad then there really is no excuse for the media or the politicians to not know. All those people dying and everyone in authority pretending it's perfectly normal is just appalling.
There is no bias.
I did the analysis. There are a limited number of countries in the wired so random sampling isn't a thing in mortality analysis. Next we are restricted to what countries have published their statistics. This is out of our control. African states dont have the infrastructure and don't appear in the databases.
If you watch my presentation you will see I mention HMD and OWD databases. I need to ensure we can get a complete dataset across as many countries as possible. This reduces the working set of countries further.
And out pops the countries that appear in the analysis. I didn't aim to exactly reproduce Ignors analysis since that would have been trivial. Hence I include countries he did not. I also looked at competing hypotheses.
If you think we are cherry picking I suggest you try the exercise. You have everything you need to recreate what was done at your fingertips. It's pretty easy.
If every country and region in the world published up to date statistics I'd use them.
We are playing devil's advocate and trusting the official data. If you read our other articles it's clear we really don't though.
Even using the official data the results don't support long covid and safe vaxx conclusions.
We've covered a lot of this and were on top of it from early 2020. I suggest you read through our archive.
Thank you very much for this exploratory. I got here via Igor's reference. When the statistical analyses begin to indicate Something Very Bad happening, it is useful, it is paramount, to have additional voices who can author their own distinct viewpoints either in support or denial. Your help is much appreciated.
"For weeks 12-24 and 20-32 we do find high, and significant, correlation between excess deaths and covid, suggesting that covid is driving the excess deaths across all countries (even though both excess and covid rates are falling). However, for the final period, weeks 30-44 the effect of covid on the excess deaths has gone, yet excess mortality remains positive across the board"
a thought worth perhaps pursuing:
did you check this for seasonal/regional signal variance?
it's just a sort of intuition, but it seems to me that if you have, to be simple, 2 seasonal zones that get covid at different times of year, this in and out of correlation shift could be one peaking while another is low and vice versa with periods in the middle of each being sort of "middle severity" and thus seeming to correlate.
comparing even florida to NY, much less germany to austraila could possibly cause issues like this as they move in and out of phase with one another.
Thank you Professor for speaking out and for joining the fight against this terrible usurpation of all that was once science, ethics and humanity. However, I was surprised to read what I considered an odd and cautious assertion, ".... After all, blaming the vaccines is a pretty big claim to make..."
The incontrovertible truth is staring us all in the face and the burden of proof to show "safe and effective" in ALL these things absolutely lies with those that perpetrated and doubled down on the crimes, BigGOV, BigPharma and BigUN/WHO/WEF/CEPI/BC and the host of institutions and individuals that went along to get along.
Please let us remember that all scientific, medical, bureaucratic, political and ethical caution and rigour were hurled aside in 2020 and reinforced by, a priori, psy-ops (Yale study), while the formal controls were ditched on EUA, and any pretense of 'science' let alone ethics became pantomime farce.
Claiming the novel synthetic polynucleotide / LNP injections had any utility was fatuous to start with. It was shown very early on in a comparative study between Moderna and Pfizer mRNA injections (they are not "vaccinations" in any proper sense of the word) that individual response to injection was variable and quite unpredictable (and by extension, any resultant reactogenic or adverse events) they precipitated.
Meanwhile, controls gone, "effectiveness" became a black-box modeled circular function of efficacy and the absurd RT-PCR, RAT test data, hospitalisations with/of and death with/of...see UK ONS explanations around modeling. Since then Fraiman et al. show the likelihood of negative risk benefit, while others highlighted an ARR of 0.46% and NNV of 217 (Lancet).
The clear temporal relationship of hospitalisation and death to Pfizer injections and boosters was enough of a smoking canon for me (OECD.stat, excess mortality COVID 2020 - 2022).
Further, the absence of statistical power residing in the efficacy studies was as inadequate as it was appalling, while the corporate corruption around efficacy (see BMJ), and the delay in release and concealing of data unforgivable (see US courts and Pfizer). The six month follow-up by Pfizer and its 9 page appendix with >1000 events of "special interest" was utterly damning.
So, we are reduced to best fit regression analysis that adds to the empirical evidence of sudden death, that may eventually see the evil perpetrators answer for their crimes against humanity.
OECD.stat provide useful national data on excess deaths. I graphed the results for NZ and inserted the dates of the injection schedules. One hardly needs to look further and one wouldn't were this treated as 'usual clinical practice'. Instead, while emphatically denying the existence of a global experiment, the many corporate globalist protagonists clearly 'manage' it as such, post hoc injection. The resultant double benefit of this double standard is the massive under-reporting of adverse events and death and the perpetuation of the manufactured and nurtured illusion of "safe and effective."
And I haven't even started on 'consent' or the terrible mess that has been intentionally made of almost all the 'data', which is exactly why we find ourselves stuck with 'excess death' and some histology results from PMs.
Would I be correct in assuming that 'fully vaccinated' = two doses? It looks like a polynomial distribution would best fit that data rather than a simple linear relationship. Is it perhaps the case that the countries with the higher percentage of two doses are much more likely to have administered boosters? If the spike proteins accumulate in the body and if the harms are dose-dependent, then this might explain the apparent exponential rise in deaths occurring in very highly vaccinated countries.
Good stuff and a good springboard. You are better able to develop the analysis than I, but may I suggest that adjusting the data sets under different scenarios might prove useful?
For example, quantify the variability from GIGO!
misdiagnosis rates of C19 - 25% 50% 95% of "cases" and hence "deaths" are misdiagnosed as C19 using RT-PCR testing - not sure how you adjust for the "top secret" amplification cycles used in different countries, so maybe a range of possible misdiagnoses is the way to go (over 24 cycles = BS, most countries use 30-40.
Reverse the "no adverse event within 14 (or 21 or 28 days) is attributed to "vaccines" despite the fact that VAERS data shows around 80-90% of events occur within 14 days.
Factor in the likely under-reporting factor of adverse event reporting - starting with deaths. A hot topic, is it ZERO!!!! as claimed by the FDA, is it one in 100 events reported (as per Lazarus years ago (a big ACK if still accurate, is it likely to be one in 20, 40 or (as I believe) increasing from around 30-40 to over 60 as the distance from last injection recedes into the past and much less likely to be associated with the injection. see here for arguments
I appreciate that your exploratory study focuses on impacts from vaxx roll-out to "completed initial protocol" over 2021 and its impact on 2022, and your use of three years to the outbreak, to exclude dara over C19 only in 2020 and C19 plus partial vaxx in 2021, makes sense. I would find it useful to check out excess mortality against the "misdiagnosis using RT-PCR testing" hypothesis above.
I support the work here, that the majority of excess deaths in 2020 - and possibly 2021, though vac deaths also impacted.
I have been influenced a lot by this article that I would value your opinion of
By way of background, I have spent decades in the investment industry as an active participant but with more than half my career compiling and analyzing investment performance of portfolios using VaR (which could Lives at Risk, instead of Value) benchmark relative risk adjusted excess returns (could be excess deaths?0 using money and time weighted rates of return, plus "contribution to excess and attribution of excess returns (could be excess deaths?) - for portfolios woth billions/trillions in the aggregate. Seems to me, there must be some crossover to Information Ratios somewhere!
Keep up the good work. I look forward to seeing your quality on display!
Mortality data was available online in HMD and other data available in OWD. No cherry picking.
Your approach, analysis and conclusions make me feel like I made the right decision when I decided not to get vaccinated.
I keep wondering how many “anecdotes” make a “signal”?
Beautifully laid out, but can you clarify the difference, if any, between "COVID CASE RATE" on the X-axis of the first graph, and "COVID RATES" on the X-axis of the second graph?