We now plot excess vs vaxx rate by country, age, sex.
Finally: the correct answer was
A ✅
B ❌
C ❌
I cannot see any correlation.
Closer look on the 20-24 year old boys. I can't see any correlation.
We should normalize by the population size to get a relative excess which is not distorted by the country bin size, but that shouldn't change a lot.
Find here the dashboard with the joint dataset (after joining 3 sets: vaxx rate, mort. 2020, mort. 2021). public.tableau.com/authoring/Mort…
Next time: same game for the elderly age bins. At some point, this magic, so important serum should give a pos. signal or not?😅
This may help to understand what I plotted. It’s basically the difference over a time window of @OS51388957 cumulative graphs. His graphs are a bit older, so they stop at week 30. But it nevertheless helps to understand I hope.
2/ Florida: the gulf area showing up red at the anomaly chart. The buoy shows nominal at average values. 25C versus +26-27C in the SST model. That's a +1C heat bias.
3/ Next - Hawaii. Buoys are below average. SST product is showing heat anomalies there.
14th May: buoy 24.5C vs. 25.5C SST.
+1C heat bias
Interesting. It's apparently too warm, as long as you don't stick a real thermometer into the water to measure and realize: it's cold.
1/ Let's revisit this result from AIRS satellite measurements over 17 years, showing a +0.36W increase in forcing alongside a 40 ppm rise in CO2 concentration.
Does this align with the "observed" (questionable) increase in global temperature anomaly (+0.6C)?
2/The IPCC reports a calculated CO2 forcing of +0.5W, as detailed on the NOAA AGGI page, which you can find here:
The SW calculation overestimates by 40% compared to the +0.36W derived by the AIRS satellite, marking the first significant discrepancy. gml.noaa.gov/aggi/aggi.html
3/ Now we return to Happer's paper, showing that doubling CO2 from 400 --> 800 ppm results in +3W of forcing.
This is consistent with +3.5W reported by the NOAA AGGI (+3.5W).
Imagine claiming the trial was correct, deploying it to 95% in NZ/AUT, and then—boom!—the incidence explodes instead of the virus being eliminated which should already happen at ~70% rate, and was calculated mathematically to happen based on that very promise. False. Study ➡️🚮
Moreover, mortality rises instead of falling. Who are these people still lying about its mortality effectiveness? It’s a failure, and rightfully, Pfizer's stock is plummeting. Keep grieving; won’t help. We want the money back. Those who wanted it can still buy it with own money.
They think that they will get out of this? Desperation. Or did he just admit that everybody (including the CEO Fauci CDC…) were involved in deceptive advertising claims? I doubt that it is going to have a better outcome. Keep digging the hole 👍
1/ Important. ERA5 is a weather model, not a measurement. This summer field tests revealed: rural areas suffer heat bias due to urban heat pollution, making models/interpolations heat biased.
Here a demo that ERA5 is wrong on the tested location.
2/ This implies that all temperature aggregations in climate aggregations incorporate the heat bias prevalent in rural areas. This outcome is hardly surprising given that the majority of weather stations are situated in urban or airport environments.
2/Context: When aiming to determine the Age-Standardized Mortality Rate (ASMR) rather than Life Expectancy (LE), we employ a straightforward relationship:
ASMR = 90 - LE
(valid for ESP2013 population)
However, for those who find it more relevant, we can maintain the LE-CO2
3/ It's important to mention that money is an abstraction of promised future work (energy future). This is why the US dollar is linked to oil; US have grasped this concept.
Rather than $ inflation adjustments, you can express your wealth / income as tons CO2 (or MWh) instead.