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COVID Data: Cleaved, Compartmentalized, Controlled, Compromised, Criminal and Cunning

The CDC, which deservedly ought to be rebranded as the Cons for Disease Criminality, advises that the bulk data sets driving the metrics and decision making processes for the entire country respective to the COVID pandemic are derived from a cohort of only 37 hospitals that have been cleaved away from the 608 hospitals that comprise the standard NHCS survey pool, which typically informs the CDC on disease outbreaks. We spent quite a bit of time on this in the last article – The Obamacare Bedrock of the Fraudulent COVID Pandemic – and we’ll rely on some of that work here because this information is so significant that it deserves its own space.

Getting to brass tacks, here’s what the CDC advises relative to the curation of COVID data. In the first paragraph the broader cohort of 608 hospitals in the NHCS survey pool is cited but in the second, we note how 37 hospitals are cleaved away from the broader cohort of 608 and impacting data metrics substantially.

This leads to many important questions through the lens of fraud like which hospitals are they? Do they exist in particular geographic areas respective to Democratic control, major urban hub populations, federal funding and discretionary funding in the form of grants, etc.? Are they representative of the nation as a whole? Do they include rural hospitals outside of urban areas relative to virology and epidemiology?

More importantly, I’m going on several days of trying to identify the exact list of 37 hospitals ergo why is it so layered, obfuscated and difficult to find? Why isn’t there an embedded and convenient link to identify these 37 hospitals? What is being hidden?

Read this carefully for the discussion that follows.

In the first indicated paragraph above, we note these specific points respective to the data and the larger cohort of 608 hospitals that informs it. For one, the data captured is “electronic,” just like the voting data of the 2020 election and that makes it vulnerable to third party compromise. See the 2020 election. My broader concerns don’t necessarily lie there; however, that concern is a legitimate one.

For another, we note that the NHCS survey metrics include “all encounters in a calendar year from a nationally representative sample” of 608 hospitals. Through logical deduction and on its face, this is conventional and acceptable. Therein and importantly, the CDC is being informed by metrics that include ALL ENCOUNTERS that occur within a CALENDAR YEAR and this provides adequate baseline data against which to measure for any potential outbreaks or associated events. MOST IMPORTANTLY, the data sampling is “NATIONALLY REPRESENTATIVE.”

As we discussed in the last article and as evidenced above,

But then a clear, obvious and conflicting distinction is drawn whereby the distinct difference applies to NHCS data providers specifically for COVID data sets, which are only received from 37 hospitals spread throughout the country and just as we noted above. What makes this extract different is the inclusion of the NHCS Urban-Rural Classification System for Counties and we’re latching onto that to deliver the list of 37 that we intend to prove with the funding data points; especially discretionary funding.

The obvious and clear distinction relative to COVID v. other outbreaks is how the CDC diverges from the standard system of NHCS informative data practices [608 hospital survey pool] to cleave away a decidedly smaller survey data pool of 37 NHCS. This equates to a 94% change in the sample size and stands to affect the data output on COVID substantially.

Note how the data are positioned to be “preliminary, and the results may change with subsequent releases.” This bears down directly on previous work and right down to the exact same percentage – 94% – and not that we can make a direct correlation to it, but still. We find it in the two bulk data revisions on 26 Aug 20 and 12 May 21 that I’ve covered extensively.

For fulsome understanding here, we have to examine another CDC publication regarding the selected COVID hospitals and conveniently, this data point is omitted from the previous one meaning it won’t be found unless it’s sought out. It pertains to the concept of using a nationally representative data pool to drive the metrics.

First, we note how the “information is not available in other hospital reporting systems.” Why? Why is there a deliberate action to cleave away COVID data [its sources and systems] from the broader cohort?

We further draw down on the fact that, “The 2020 and 2021 NHCS are not yet fully operational.” Not fully operational? This means that the COVID data curation system equates to a car that doesn’t have all of it’s parts. Try driving that car anywhere safely, appropriately or effectively and then try driving it across the entire nation. This is evidenced fraud for my nickel.

Let me summarize all of this: Fauci and the CDC diverged away from the standard and nationally representative pool of 608 hospitals that normally informs their decision-making processes electing instead to use an incomplete system that is not nationally representative and only includes 37 hospitals the list for which we can not locate or identify.

Who has a problem with that? It’s a rhetorical question for us and not even an issue for the mask-wearing, vaccine-getting, Kool-Aid drinking sub-population of those incapable of independent and critical thinking and who insist on virtuously leading the rest of us to enslavement.

Here’s how I put it in the last article,

We talk about compartmentalizing culpability a lot and that’s what this is as I’ve been evidencing in the broader scope for a long time. Empirically and as it relates to the construct, identifying the 37-point list may allow us to draw-down with precision on identifiable components within this closed loop system by vetting it against the top federal funds recipients.

Why did they cleave the COVID data source away from the regular cohort of 608 hospitals? Easier to control. Easier to guarantee. Easier all the way around. Easier to compartmentalize culpability.

How many of those hospitals are located in areas where riots, COVID mitigation enforcement and election fraud were prominent issues and there is a heavy and powerful Democratic presence if not full control or a Republican presence known to be as compromised and corrupt as their Democratic counterparts?

Why can’t I find the list of those 37 hospitals?

It gets worse.

In my attempt to identify our NHCS list of 37 hospitals, we had to latch-on to the NCHS [different than the NHCS] urban-rural classification system for counties. This work equated to parsing-out an 81-page document to generate a list of urban hub populations comprised of sub-grouped counties to then cross-reference it against substantial discretionary funding [federal grant dollars] as per the CDC’s Epidemiology and Laboratory Capacity for Prevention and Control of Emerging Infectious Diseases (ELC).

In other words, we parsed-out 81 pages to formulate a list that should contain the 37 hospitals and then we drew down on that list to eliminate those outside of the 37 by running down the discretionary funding. That equates to paying the entities you want, where you want, for the reasons you want when you want. It’s fraud.

That work gave us a good idea, but not an exact one providing the precise list of 37 hospitals [see the article linked up top.]

Although the 37 NHCS hospitals are most important here because they tie directly to funding and discretionary funding, what’s more important about them are their geographic locations and for the critical reason I pointed out in the Obamacare piece,

Note these locations from the ELC relative to the map overlay graphic above: Colorado, Georgia, Florida, New York City, Los Angeles County, New York, Hawaii, Pennsylvania, Ohio, Tennessee, Wisconsin, Illinois, Arizona, North Carolina, Virginia, Texas, Houston, Philadelphia, Delaware, Maryland, Minnesota, Nevada, New Hampshire, Oregon, D.C., and Chicago. ALL OF THESE LOCATIONS are entangled in all of the work at Moonshine and in ways that all draw down on Orange Man Bad, fake pandemics and stolen elections. They all got discretionary federal money and it’s all of the usual suspects.

From the same,

The buried gold in this is understanding the source of the data for the data driver as fuel for the construct and then finding how the source is strung, funded and controlled. After issuing the NVSS diagnostic memos to steer COVID infection and mortality data to desired and fraudulent ends, the criminal enterprise appears positioned to cherry-pick data from the 37 hospitals they selected as COVID data providers. That data set drives the fraudulent construct and frames determinations of policy for the nation as a whole. Is the entire nation being dominated by 37 major urban areas and are Democratic leaders firmly in control of them?

Everything I’ve outlined here IS ENTIRELY DEMONSTRABLE OF FRAUD AS COMMITTED BY A CRIMINAL ENTERPRISE and as prosecutable under RICO statute. Period.

The COVID data sets have been cleaved away from the standard 608-hospital cohort and compartmentalized into one consisting of 37 hospitals. This occurs within the already established fraudulent construct of redundant control systems that permit the pulling of levers [manipulation of data and the subsequent decisions] whenever, wherever, however and why the CRIMINAL ENTERPRISE dictates.

This permits the CRIMINAL ENTERPRISE the capacity to control, insulate and establish a firewall for the data curation process relative to the medical provider community writ large [think about how internal whistleblowers could be disruptive to it.] Comprehensively, the constructive elements here manifest as a cunning strategy to destroy the nation with compromised data the metrics for which the CRIMINAL ENTERPRISE determined and then mandated for all medical providers and for the express purpose of executing a pandemic entirely of fraudulent data.

My bet is that we already know the 37 areas by a different context. My bet is that’s why they’re so damned difficult to find and identify. My bet is that these locations will overlap in myriad ways: COVID mitigations, rioting, burning, looting, election fraud, general funding, discretionary funding, etc. You know the list.

I’ve been saying SINCE EARLY FEBRUARY OF 2020 THAT THE ENTIRE PANDEMIC IS ONE OF FRAUDULENTLY PROPAGATED DATA. Someone – ANYONE – prove me wrong and provide the evidence. Good luck.



  1. […] and intricate COVID-19 data sets, it’s important to review some basic context about them noting existing positions that question the apparent compartmentalization of COVID-19 data in 37 “selected […]