If H:1 holds true upon good data input: of TOTAL US COVID DEATHS.
H1 is proposition of development of argument towards slope velocity and of model projection of such. _________________________________________________ Slope can A. stay on the current path at 75 degree slope. By the end of January almost 1 million will have died.
Slope can B. stay elevated at 65 degrees.
Slope C. stays on cycled compression at a modest 35 degrees.
Severity of slope is directly correlated with velocity of infection per X density of population. __________________________________________________________________________
Arguments against H:1 are as follows:
Z. Argument given. You can manipulate death totals at various levels of the collection process ie.state, county, etc.. Thus, your data is manipulated, leading to incorrect analysis. - Sure, but variance between cycles of infection per X density of population shows velocity (V) depicted by slope against a compressed plane. See that gray line stemming from the start of the data. That is an approximation of the mean in linear terms, showing a variety of compression/expansion cycles in the data provided. The variance velocity is naturally immune to manipulation of an input/output average consensus of a metric death.
When X density of infections follows rolling cycles, the problem becomes if the velocity of the variance increases quickly in any one segment of time (Y).
The initial peak of infection can be said to be 90 degrees from baseline 0 to the first junction of amplification.
If X density of population affected by Z virus has steep velocity variance in any one segment of time Y, then we see a social consequence from it. ie.overwhelmed hospitals, shortages of supplies *in a worldwide supply chain crisis cough*, staff shortages, medical burnout, etc. You get the idea. This leads to increased reporting of death totals due to covid-19. Regardless, we simply care about social consequence. Meaning people you love start getting sick, it usually doesn't mean as much until it hits home. Then it strikes a nerve of importance.
If we can come to a consensus of populations of America, its roughly 330 million.
If we roughly estimate that 200 million are vaccinated with first, second or third boosted levels of the vaccines out currently. Let's say hypothetically that 20% of that 200 million have breakthrough potential. + 40 million.
We now have 130 million of 330 total population that are unvaccinated. So, put them in a pool for risk of infection and dying. Plus, we have 20% (compounding variables of what ifs') of 200 million with a breakthrough potential for infection despite still being vaccinated. Furthermore, even if we said oh 10% of the covid-19 death is bullshit inflated manipulated politics. That actually strengthens the argument of immediate concern to increased variance velocity in total deaths because you have further increased the potential pool those who can be infected, but in a shorter time-span. The 20% who are vaccinated but still could be classified as vaccine covid-19 'breakthrough" includes everyone with a severe disease, elderly folk, and the young children whose immune systems are not strong enough yet to adapt to changing spike protein based viruses.
That's now 160 (+/- 10 m) million in the probability pool who have a potential of dying due to strain of a nasty virus. Out of that 160 million, a variance velocity increase at the levels stated above can easily take out another couple hundred thousand people in a short Y timeframe. EASILY.
I probably made some mistake in my calculations, but I think you get the picture.. maybe?
There is logic to this madness. Unless shit is shut down immediately. We once again risk increased variance velocity due to a wide range of ignorance that I can not even begin to address here. But who knows if we learned.
following 65 degree slope with excellent accuracy.
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incredible accuracy.
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doubt..
sure.
deny what your eyes experience.
Are you listening yet?
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it's like a point play by play of the future. But better.. NO COMMERCIALS.
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Like I am getting worried here. Please deviate for my own sanity.
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so yea... still following
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Yep.
845,437
The next data point is at 855,200.
10k+ more dead by Tuesday keeps us on track with surreal accuracy.
Notice how the fractal is playing out. Notice how the velocity of deaths is what really matters. Notice how the compressed fractal is "flattening the curve".
THAT IS WHAT IS MEANT BY "FLATTENING THE CURVE". It is a continuous dynamic. Not a static one.
The spread of the virus is rampant.
It is killing people at rate steady rate, a rate that outpaces all other reasons of death.
It's really about perspective..
330 million Americans. 845,437 (+/-2% error) that have died since Feb 2020 in America.
Even accounting for "fluff" in the data the velocity is on pace with the previous first wave. Each fractal you see was taken from different points in the overall data. This is crucial for understanding the structure. Clearly, in a structural sense, movements are not extreme or outlier. They are steady. This is important in determining truth from falsification.
If one was to manipulate the death pool data, we would see an erratic curve mismatch from any previous curve. Why?
Because the manipulators would have to add the SAME variance residual to velocity at every timeframe along the trend. Do you have ANY idea how incredibly hard that would be?
It is more likely that the count is suppressed, then added onto!
I know that blows ones mind to think about but my deduction comes straight from what you see above.
The fact that the trend is following with such accuracy should help imply natural growth based upon actual normalized functions of input:outputs.
But yea. Word salad as most say..
I say.. ITS SCIENCE.
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Very High probability of increased death output per vol population.
Highest velocity variance seen since data started.
omg cry me a river. 99.9% of the world will survive this virus. Lockdowns, masks, mandates - the hallmark of corrupt politicains, power grabs, centralization. Couple that with a brain dead population that is scared of the air...Too many clowns now of days.
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@ObamaBinLyin 0.1% of the population is 7.7 million deaths, which is not insignificant. I don’t think the author was arguing that humanity would be wiped out by COVID. And how is a mask a hallmark of centralization and corrupt politicians?
ObamaBinLyin
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@joppoe65630, because masks are useless and are a product of virtue signaling on an individual level. On a macro, political level, masks, lockdowns and mandates are control mechanisms. The expansion of authority over the individual. You'll notice, that since the start of covid restrictions, govts have only become bigger, more centralized and a lot more obvious in their power grabs. It's about breaking the individual into compliance. If it doesnt stop now, all this will morph into a centralized surveillance state in the near future and no one will remember it all started with covid. Hell, health canada is currently trying to obtain access to cell towers to make covid contact tracing easier. We've seen this before, we know where it leads to. Nothing new, history repeats itself, just a shame so many people don't know their history.
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@ObamaBinLyin, I am not a proponent of giving the government power at the expense of individual freedoms. But I think it helps to distinguish between real problems worth pushing against and distractions. I think it is debatable, for example, whether masks are useless on an individual level and, regardless of their utility from a health standpoint, whether they are effective control mechanisms when mandated in public spaces. Neither virtue signaling nor being requested (not sure where it is required) to cover my face in a public space diminishes any freedom of which I'm aware. The lockdowns and mandates probably could be abused given the right political environment.
stvmmmr
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You certainly deserve credit for all the work you put into this but there is one glaring problem and another factor to consider. You didn’t even mention or consider the population with natural immunity. Your data assumes they have the same risk of being infected and dying. Also there seems to be an assumption that those choosing not to vaccinated would have the same distribution of comorbidities of the general population, but it’s likely they chose not to be vaccinated because they have an extremely low risk of being seriously sick.
Glitch420
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@stvmmmr, Yes my proposition assumes the total sample pool minus those on the outlier extremes of a normal distribution would have equal chance of infection and death. This allows assumption of natural immune persons to only be on the outlier side. Serious pre-existing conditions are also paired to the outlier zones of the curve. This filtration technique allows one to simply look at a fully generalizable pool as equal, because most have adopted a complacent mindset to what @HarryBach referred to as 'man on the street'. The echochambers of social media, political news networks have absolutely done a great job confusing the majority. Some lost to mistrust for understandable reasons. Some hellbent on conspiracies. Others, a blend of all the information available. So they just remain indifferent, until of course it becomes personal and hits home. Then it matters. Then the science must be correct. Right? Perspective is killer in data analytics. Just so many angles. But see the problem is when everyone is an expert, you get streamlined mindsets that are simply unshakable to being adopted as truths. It's a slippery slope from there.
The human can understand the immense complexity of their immune system by "feeling" yet fields dedicated to the subject have convincing data showing the exact opposite. So who is right? The data deniers? or the Data studiers?
The mindset that YOU are at extremely low risk is the reason why risk exposure is so high among those with that mindset. The mindset of I am invincible is a slippery one. The mindset of I know exactly what my immune system is doing, so i am at extremely low risk; is even more so. We are all fleshy biological organisms with complexity that extrordinarily few people can say they understand they are at lowest risk.
stvmmmr
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@Glitch420, Does your data proposition assume that those with natural immunity have the same/similar risk of catching covid as those that are unvaccinated?
boojummert
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evolution never seemed so self-absorbed with it's own well-being
The_Real_AMF
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@boojummert, You don't understand evolution, or anything else you are talking about, then.