I'm spoiled. I work in an industrial laboratory and can demand more information about the data and how it was collected. Your pretty colored lines for slope indicate a decrease in deaths since the vaccine. But they are at the end of the very noisy data. As a member of the jury I would like to see the data with no slopes and only two vertical lines. Start of Covid ~March 2020. Start of Vaccines ~March 2021. A table of slope and slope uncertainty would probably show the likely values of the blue and green slope overlap. Maybe a T-test?
Alabama is on the gulf coast, a near tropical climate. Historically flu's have a different profile in tropical climates than northern climates, a slower rise, a longer stable level, and a slow decline. (HT to Ivor Cummins, now on Odysee.) Northern climates like Scotland have a fast rise and somewhat slower fall.
A long stable level of virus infections in a tropical climate will make it hard to find the effect of the jabs. Too much overlap.
So yes, Prior knowledge did not allow me to answer your questions other than the prior knowledge question. I also don't know the percent jabbed, once, twice, jabbed to eventual death within 5 years for Alabama.
No they don't. But I recognise this as an issue which is why I went to great lengths to explain this in the guidance. A downward slope can result simply because of high deaths at the start of that period relative to the end, even though that period remains in excess overall.
All cause mortality numbers seem to be a great starting point indicating the need for further investigation.
That's when subsequent filters on other meta points like those with varying numbers of injections, underlying illness and so on can be analysed to narrow down the potential causes of the trend.
But clearly there is a significant trend of increased deaths within the vaccination window that would cause anyone seeing this analysis to want to dig deeper to discover the reality in the detail.
The graphs and textual numbers show that increase trend very clearly but the blue lines did not, for me, aid this visually intuitive presentation. Thank you for this work 🙏
Thanks, Nick. I am also interested to learn what makes sense in terms of quantitative reasoning and what doesn't. My intention is to provide information as clearly as possible but free of bias. Visual aids are essential, although not always as intuitive as I would hope for.
I'm spoiled. I work in an industrial laboratory and can demand more information about the data and how it was collected. Your pretty colored lines for slope indicate a decrease in deaths since the vaccine. But they are at the end of the very noisy data. As a member of the jury I would like to see the data with no slopes and only two vertical lines. Start of Covid ~March 2020. Start of Vaccines ~March 2021. A table of slope and slope uncertainty would probably show the likely values of the blue and green slope overlap. Maybe a T-test?
Alabama is on the gulf coast, a near tropical climate. Historically flu's have a different profile in tropical climates than northern climates, a slower rise, a longer stable level, and a slow decline. (HT to Ivor Cummins, now on Odysee.) Northern climates like Scotland have a fast rise and somewhat slower fall.
A long stable level of virus infections in a tropical climate will make it hard to find the effect of the jabs. Too much overlap.
So yes, Prior knowledge did not allow me to answer your questions other than the prior knowledge question. I also don't know the percent jabbed, once, twice, jabbed to eventual death within 5 years for Alabama.
No they don't. But I recognise this as an issue which is why I went to great lengths to explain this in the guidance. A downward slope can result simply because of high deaths at the start of that period relative to the end, even though that period remains in excess overall.
The blue and green lines do not help my interpretation of the data. In fact, I find them deceiving. I would prefer to see rate of change curves.
In Joel's presentation, the average weekly death data in the bottom right is most useful.
The vax somehow manages to reduce mortality from everything! It's amazing!
Or it's a pull-forward effect. More people die in 1 year (mostly old/frail who were close to death anyway) this reduces mortality the next year.
And when you include this mass-death event in the start of the next slope calculation, it can only go down.
Young people weren't really dying from the virus. Drug ODs and suicides were a far more significant cause of death.
All cause mortality numbers seem to be a great starting point indicating the need for further investigation.
That's when subsequent filters on other meta points like those with varying numbers of injections, underlying illness and so on can be analysed to narrow down the potential causes of the trend.
But clearly there is a significant trend of increased deaths within the vaccination window that would cause anyone seeing this analysis to want to dig deeper to discover the reality in the detail.
The graphs and textual numbers show that increase trend very clearly but the blue lines did not, for me, aid this visually intuitive presentation. Thank you for this work 🙏
Thanks, Nick. I am also interested to learn what makes sense in terms of quantitative reasoning and what doesn't. My intention is to provide information as clearly as possible but free of bias. Visual aids are essential, although not always as intuitive as I would hope for.