Deaths not attributed to Covid are quiet, they disappear into the background unnoticed by most people. No attention drawn to them by governments, scientists, public health or our mendacious media so the compliant masses pay no heed, young people die and it is just one of these things that happen. To be told that our younger people are dying is horrifying this is not a natural old age death but is an abnormal occurrence that should be shouted out by every institution as they did Covid but not a word just a deathly silence. Thank you Ethical Skeptic for making sure this real time tragedy does not disappear completely into the background.
In your plot for cardiac deaths in ages 0-54, did you fit the baseline based on only data from 2018 and 2019 or did you also include earlier years? Is the baseline a linear trend or polynomial trend or average or something else? Approximately the first two months of 2018 are missing from your plot, so did you also omit them from the baseline fitting period? And what method did you use to adjust for seasonal variation in mortality?
If you used only data from 2018-2019 to fit the baseline and you used a linear trend, the slope of the trend is going to point too much downwards because 2019 had an exceptionally low number of deaths: https://i.ibb.co/HHyH1MH/2018-to-2019-baseline-cdc-wonder.png. However it won't be as bad if you omitted the first two months of 2018 from the baseline fitting period, because there was a very high number of deaths in January 2018.
I'm not analyzing generational or population-diluted trends (potentially misleading statistics), I am detecting deviation from trend dynamics (detecting system inflection).
I cannot use Wonder 2017 and earlier because the numbers are boosted by the small county single-record effect. This is why Wonder 2018 and beyond is a new database (shows as a variance in your chart which does not actually exist), under that HIPAA constraint. Nor can I use 2002 - 2017 data because this contain a dissipating generational effect of those Boomers who suffered cardiac arrest from specific past health impacts which are no longer salient to this age bracket. That trend line must be moved to the 65+ bracket now. This has caused a slight downtrend into 2019, which I do accommodate, yes.
I compared that baseline to a linear regression of the old growth rate (2014-2017) before hand to ensure it was 'in context'. However, I did not use a pure linear regression of 2018 and 19 for this reason. I fit the baseline to the variances linearly, but not by least-squares regression (how I avoided the early 2018 surge). There is of course not enough data to then use a non-linear function beyond that as well. That would be whipsawing fiction.
But much of this is moot, because none of these manipulations serve to make this dramatic an inflection disappear. These are trend manipulations. Four years from now, trend models will have to be adjusted again, but the inflection will still be there. The argument will be over just how much excess death there indeed is... but I anticipate that it will be moot. If you have a strong inflection like this and your trend analysis makes it disappear quickly, odds are the trend analysis is biased.
As a result, I don't have either a Jan 2018 high or 2019 lowering bias in my baseline.
"These are VARIANCES, not datums - you are conflating the two as being the same thing in terms of linear regression" and hoping to doubt-cast based upon this little trick in context.
This is a sleight-of-hand. I don't tolerate such nefarious activity, and this is the reason why you were blocked on X --> for doing this in the past as well.
You are also 'plural arguing' - throwing out 20 'niggles' to see what sticks to the wall in support of your preconceived answer (the BS of 'proving an absence', rather than a presence). You ignore the ones which don't work, and immediately flag the ones which appear to work. This is akin to p-hacking and is pseudoscience/pseudoanalytics.
Again, we are looking for inflection, not trends. Trends are a statistics device, and can be crafted a number of ways in order to mislead.
PFE is an objectively determined model constraint, not an accidental of ASMR, population growth assumption, nor result-dependent output. (as a note, whenever you say 'ASMR' you should cite the census source, real-vs-projection basis/years, and calculation methodology used in deriving the standardization - as I do extensively with my PFE calculations - it is not a magic phrase that automatically makes an analyst more accurate or knowledgeable)
I'm going on a podcast soon to talk about a cancer risk no one has talked about.
I'm going to DM you some new analytics you need to watch for. Please watch for it.
If there's even a chance of what I realized is going to happen that no one has talked about, I think I'm going to lose my chite.
(I'm coming back to the digital sewer aka, X, just to post a couple things--I'll be sharing some significant studies with a podcast alongside a couple of new substacks. There's a different neoplasm that might rise up and if it does, it's going to be the stuff of nightmares.)
What is the medical and/or scientific threshold for considering the pandemic over? Nearly all of us are living as though it were, so as far as sociological concerns go, it is over, and has been for well over a year. I say this knowing I had a very mild case of Covid in February, lasting three days with some sniffles and a low fever.
We are officially in the post-pandemic, something which did not exist with any pandemic previously. We harmed 80% of our population in a mad panic over the pandemic, and now we must track that harm. But yes, we are in the post-Pandemic timeframe.
I had to go for an MRI or two (surgery for moi), and I had some chats.
I receive care from the top two hospitals in the Midwest, one of them is top of the nation. I live fairly close to their flagship hospital.
I got confirmation from MRI department at multiple sites: colon cancer is through the roof and they're seeing it in the young at stage 3 and stage 4.
The colon cancer MRIs have increased to the level these hospitals have now specific blocked off times exclusively for MRI of lower intestines (neoplasms).
I fear the worst is on deck.
Thanks for all of your work TES even in the face of so much personal loss.
So much for their "science" unassailable "safe and effective".
Topics for resolution:
What is the "safe" exposure, if any, to [RNA introduced] S protein?
How does exposure to S protein make the immune systems respond to an RNA virus? Any relation to DARPA not following through with Moderna from 2013 research?
Scratching my head.
Around 1 Mar I was exposed to relation who soon after had hard case of C19. I had a week or so of sniffles. Good thing I have had no boosters!
Our senate in Australia has finally voted (after 3 attempts) to have an inquiry into excess mortality in this country. If you are interested, out point man for this is Andrew Madry;
Every time you reveal how many of the deaths are being wrongly and criminally hidden under other “vague causes” I’m turning red in the face. I’m sick and tired of the hospitals and CDC purposefully “recategorizing” deaths to suit their own narrative and I think it’s like calling women “chest feeders”. Nothing is the truth anymore, it truly is 1984.
If you mean Sudden Cardiac Deaths in 0-54, yes - it is on a flat distribution now. That is not necessarily a good thing. 'Flat into what?' is the key question.
Deaths not attributed to Covid are quiet, they disappear into the background unnoticed by most people. No attention drawn to them by governments, scientists, public health or our mendacious media so the compliant masses pay no heed, young people die and it is just one of these things that happen. To be told that our younger people are dying is horrifying this is not a natural old age death but is an abnormal occurrence that should be shouted out by every institution as they did Covid but not a word just a deathly silence. Thank you Ethical Skeptic for making sure this real time tragedy does not disappear completely into the background.
In your plot for cardiac deaths in ages 0-54, did you fit the baseline based on only data from 2018 and 2019 or did you also include earlier years? Is the baseline a linear trend or polynomial trend or average or something else? Approximately the first two months of 2018 are missing from your plot, so did you also omit them from the baseline fitting period? And what method did you use to adjust for seasonal variation in mortality?
If you used only data from 2018-2019 to fit the baseline and you used a linear trend, the slope of the trend is going to point too much downwards because 2019 had an exceptionally low number of deaths: https://i.ibb.co/HHyH1MH/2018-to-2019-baseline-cdc-wonder.png. However it won't be as bad if you omitted the first two months of 2018 from the baseline fitting period, because there was a very high number of deaths in January 2018.
I'm not analyzing generational or population-diluted trends (potentially misleading statistics), I am detecting deviation from trend dynamics (detecting system inflection).
I cannot use Wonder 2017 and earlier because the numbers are boosted by the small county single-record effect. This is why Wonder 2018 and beyond is a new database (shows as a variance in your chart which does not actually exist), under that HIPAA constraint. Nor can I use 2002 - 2017 data because this contain a dissipating generational effect of those Boomers who suffered cardiac arrest from specific past health impacts which are no longer salient to this age bracket. That trend line must be moved to the 65+ bracket now. This has caused a slight downtrend into 2019, which I do accommodate, yes.
I compared that baseline to a linear regression of the old growth rate (2014-2017) before hand to ensure it was 'in context'. However, I did not use a pure linear regression of 2018 and 19 for this reason. I fit the baseline to the variances linearly, but not by least-squares regression (how I avoided the early 2018 surge). There is of course not enough data to then use a non-linear function beyond that as well. That would be whipsawing fiction.
But much of this is moot, because none of these manipulations serve to make this dramatic an inflection disappear. These are trend manipulations. Four years from now, trend models will have to be adjusted again, but the inflection will still be there. The argument will be over just how much excess death there indeed is... but I anticipate that it will be moot. If you have a strong inflection like this and your trend analysis makes it disappear quickly, odds are the trend analysis is biased.
As a result, I don't have either a Jan 2018 high or 2019 lowering bias in my baseline.
As I stated on X:
"These are VARIANCES, not datums - you are conflating the two as being the same thing in terms of linear regression" and hoping to doubt-cast based upon this little trick in context.
This is a sleight-of-hand. I don't tolerate such nefarious activity, and this is the reason why you were blocked on X --> for doing this in the past as well.
You are also 'plural arguing' - throwing out 20 'niggles' to see what sticks to the wall in support of your preconceived answer (the BS of 'proving an absence', rather than a presence). You ignore the ones which don't work, and immediately flag the ones which appear to work. This is akin to p-hacking and is pseudoscience/pseudoanalytics.
No, I use the same method throughout the horizon.
Again, we are looking for inflection, not trends. Trends are a statistics device, and can be crafted a number of ways in order to mislead.
PFE is an objectively determined model constraint, not an accidental of ASMR, population growth assumption, nor result-dependent output. (as a note, whenever you say 'ASMR' you should cite the census source, real-vs-projection basis/years, and calculation methodology used in deriving the standardization - as I do extensively with my PFE calculations - it is not a magic phrase that automatically makes an analyst more accurate or knowledgeable)
TES
Can't sleep.
I'm going on a podcast soon to talk about a cancer risk no one has talked about.
I'm going to DM you some new analytics you need to watch for. Please watch for it.
If there's even a chance of what I realized is going to happen that no one has talked about, I think I'm going to lose my chite.
(I'm coming back to the digital sewer aka, X, just to post a couple things--I'll be sharing some significant studies with a podcast alongside a couple of new substacks. There's a different neoplasm that might rise up and if it does, it's going to be the stuff of nightmares.)
What is the medical and/or scientific threshold for considering the pandemic over? Nearly all of us are living as though it were, so as far as sociological concerns go, it is over, and has been for well over a year. I say this knowing I had a very mild case of Covid in February, lasting three days with some sniffles and a low fever.
We are officially in the post-pandemic, something which did not exist with any pandemic previously. We harmed 80% of our population in a mad panic over the pandemic, and now we must track that harm. But yes, we are in the post-Pandemic timeframe.
Anecdotal:
I had to go for an MRI or two (surgery for moi), and I had some chats.
I receive care from the top two hospitals in the Midwest, one of them is top of the nation. I live fairly close to their flagship hospital.
I got confirmation from MRI department at multiple sites: colon cancer is through the roof and they're seeing it in the young at stage 3 and stage 4.
The colon cancer MRIs have increased to the level these hospitals have now specific blocked off times exclusively for MRI of lower intestines (neoplasms).
I fear the worst is on deck.
Thanks for all of your work TES even in the face of so much personal loss.
"Over-attribution" of covid deaths ... aka fairy tales.
Thank you!
So much for their "science" unassailable "safe and effective".
Topics for resolution:
What is the "safe" exposure, if any, to [RNA introduced] S protein?
How does exposure to S protein make the immune systems respond to an RNA virus? Any relation to DARPA not following through with Moderna from 2013 research?
Scratching my head.
Around 1 Mar I was exposed to relation who soon after had hard case of C19. I had a week or so of sniffles. Good thing I have had no boosters!
.
Taking The Vaccine
Was Such A Bad Idea
That It Will Follow Them
Into The Next Life.
It Also Helps Explain
How They Showed Up Here
So Fucking Stupid.
.
Our senate in Australia has finally voted (after 3 attempts) to have an inquiry into excess mortality in this country. If you are interested, out point man for this is Andrew Madry;
https://andrewmadry.substack.com/p/australia-2023-mortality-data
Will be complete theatre, another opportunity to whitewash and further firm up the narrative in the average apathetic bonehead’s mind
Of course they will... and the conclusion will be that the covid vaccines are not the cause.
Because they held an inquiry this will add gravitas to these conclusions
Every time you reveal how many of the deaths are being wrongly and criminally hidden under other “vague causes” I’m turning red in the face. I’m sick and tired of the hospitals and CDC purposefully “recategorizing” deaths to suit their own narrative and I think it’s like calling women “chest feeders”. Nothing is the truth anymore, it truly is 1984.
Treatment was delayed... appointments rescheduled... lockdowns... anything but you know what.
So still elevated but not on a rocketship higher like it was? Just looking for something to be hopeful about
If you mean Sudden Cardiac Deaths in 0-54, yes - it is on a flat distribution now. That is not necessarily a good thing. 'Flat into what?' is the key question.
Agreed, so glad I stopped at two shots (to save my job) still mad I caved
Me too!