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The Obamacare Bedrock of the Fraudulent COVID Pandemic

Two recent articles were comprehensive capstone pieces on a body of existing work and one vectored in on private equity and energy as a conduit to move money within a global fraud network. The other drew down on U.S. biosecurity and the long run-up to the offshoring of gain of function work to China. A third and fourth article followed to further confirm broad and specific aspects of the full body of work through the forensic examination of 4,000 U.S. patents by MCAM and Dr. David E. Martin.

Here are those articles:

Follow the Money
Dangerously Changing Inconvenient Rules
COVID-19: Public Crisis or Opportunistic Marketing Campaign – The Most Important Article To-date
COVID-19: Public Crisis or Opportunistic Marketing Campaign Part II, Martin on Stew Peters with Confirmations and Relevant Data Points

This item is long and complex and this is our objective: coming to understand how discretionary funding at the sole discretion of appointed secretaries and directors; and as appropriated by congress, presents as a federal funding mechanism to build the pandemic construct over a long timeline while overlapping in the same redundant locations found in our full body of work here at Moonshine; and then tying it all together with money through the wide lens of fraud.

If you get lost, re-frame your view through that lens. That said, this wanders because we have a lot of ground to cover and I’m going to be thorough in evidencing the position. There’s a lot here but we’ll bring it all together for meaning.

As we get rolling, remember that these people play inside of a box and that lends towards predictability and precisely so.

Framing It Up

As we’re being leveraged and ushered into a third straight COVID season [peak flu 2021-2022] by the newest boogeyman, which is the Delta variant and precisely as I predicted it on 30 Nov 21 and then proved on 20 Jan 21 and then again in March 2021, let’s stack up more evidence to destruct this fraudulent construct and fight back in our favor.

The Delta variant is being used as a seasonal drag-through to circumvent the seasonal die-off of the co-morbidities being harvested as the primary data driver for the fraudulent COVID construct. In this way, it serves in the same precise capacity as the mid-April shift I identified April 2020.

Once again we’ll look back to see and plan ahead by further enmeshing the fraudulent and criminal aspects of the COVID pandemic by examining it against something I’ve yet to give due diligence and parse out but which is a logical component to it all since it lays a bedrock of healthcare law to serve a construct rooted in healthcare and epidemiology. It’s the Affordable Care Act [ACA] or Obamacare.

After all, if one desires to up end the U.S. by means of a fraudulent construct leveraging a fake pandemic, there is no better place to begin than with a complete overhaul of U.S. healthcare to one’s liking and so as to deign it to serve said construct. That’s elementary.

Most recently, the work has been focused on a presentation intended for third parties and designed as a tool to eviscerate the predicate for the 11 Mar 20 National Emergency Declaration and in so doing, eviscerate all federal and state authority found in the emergency executive powers that were usurped by a criminal enterprise [under RICO.] I have compiled them all into this video. THESE GRAPHICS WERE NEVER INTENDED FOR USE IN A VIDEO and the video is really for the informed reader who already has a firm understanding of the work at Moonshine.

If you’re newer to the work here, you may find the video frustrating and without question, having an already established and informed base of understanding is ideal if not requisite; especially if it’s wet with Moonshine.


We’ll be examining funding very closely so here is the CDC’s operational funding for FY 2019 and FY 2020. It’s a lot of money. Note the respective allocations for aspects of importance: epidemiology, development of vaccines, pandemic preparedness, etc.

Funding will come to bear down with greater might once we outline the finer points on discretionary supplemental funding that is substantial and occurs inside of closed loops with unilateral decree by means of the sole discretion of appointed directors and secretaries. We’ll run down the veiled grains of it to develop a list from which we should be able to identify the 37 hospitals providing the bulk data sets for the CDC’s COVID metrics.

From there, we track to Obamacare/The Affordable Care Act to show how our bedrock foundation is laid and we draw down on it with the discretionary funding.

Questions to Start

Lets’ begin with a tip of the hat to Tore at Tore Says for first bringing sunlight to the Obamacare angles. I haven’t seen/heard any of her work [or others] beyond it as a topic.

Questions to start.

What are the chances that we can find language within the ACA that can be considered foundational pieces of the bedrock to the fraudulent pandemic as I’ve outlined it to-date in hundreds of articles, videos and graphics?

What are the chances that footnotes, citations and sources provide further evidence?

What are the chances that funding is central to it?

What are the chances that we can tie it all back and together for fulsome meaning?

What are the chances that this work – as it always does – generates more pertinent questions to which the CDC/NIH/NIAID cartel has apparently made the answers difficult to find?

Let’s start with this question. Why can’t I find the list of 37 hospitals that contribute to the CDC’s bulk COVID data sets and which drive its metrics and decision-making processes respective to the issuance of guidelines and mitigations; and why can’t I find it relative to the federal dollars they receive in SUPPLEMENTAL DISCRETIONARY FUNDING that occurs at the sole discretion of unelected and appointed directors and secretaries?

Why is that so layered and difficult to find? It’s simply a 37-point list of hospitals. To the contrary, what I have discovered is an 81-page document detailing the “scheme” – their words, not mine – and additionally, I have 40 or so open tabs right now – browser not bar – where the information either escapes us or is hidden in a minutia of footnoted code I’ve yet to unskew to deliver the 37.

That said, I think I found the list from which the 37 originate and I think I can prove that and another position – that a minority of urban hubs respective to the balance of the country and as leveraged by federalism overlap in all the right places as discussed momentarily. We can prove it to a degree by running down general and discretionary funding.

Back to questions.

Do they appear in states like NY, CA, PA, GA, NC, AZ, MI, MN and similar others – you know the list? Just see the map overlays in the Soros graphic way down below.

Do those locations have redundant overlaps with COVID mitigation/guidelines enforcement as coinciding with voter fraud and election issues and higher funding/grant amounts? They’re making it difficult to find out but we may have it.

Will we find more compelling evidence that federalism is being leveraged back against the American people?

If you’re drunk on the ‘Shine you already know these answers and if not, the title gave it away.

Here we go.

[Embedded documents and images follow – for embedded documents tap and scroll down within the document to access all pages.]


Our first order of business before digging into the Affordable Care Act [ACA] is drawing attention to how the curation of COVID data occurs because it’s fundamental component to the construct and it falls directly back on Obamacare so we’ll go there next. Doing this will help us understand how, where and why the ACA applies when we talk about it.

Beginning on firm ground and with hard numbers, existing work narrows COVID infection and mortality data providers to 63 entities and here, it’s further narrowed to 37. The takeaway is that conceivably and within a closed loop, the CDC could cherry pick a non-representative data set from within an incomplete operational system; and do so from entities that receive standard and discretionary supplemental federal funding occurring at the sole discretion of appointed [not elected] directors and secretaries embedded in the broader bureaucracy; and then fraudulently propagate it as COVID data. The work here functions to identify that system.

Here’s how COVID data is curated with some graphic illustrations to start.

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?

Here we go beginning with the ambiguous and vague 37 data point.

What’s bothersome and as noted, why isn’t there a public and easy-to-find list of these 37 entities that provide data and receive federal dollars? What are we hiding?

Note that you will see redundant wording in a similar CDC extract below but it’s different in important ways that we’ll latch onto.

Below we’ll note the granular aspects of how the data is collected while paying particular attention to the language that serves fraud; and especially as it relates to the established bulk data set revisions occurring on 26 Aug 20 and 12 May 21. This language permits back-end revisions of data that is subject to change and especially so for anyone looking to change it.

That equates to constructively [fraudulently] formulating the data parameters [footnotes are telling] to serve the intended net effect and then, once the data sets become contradictory to the narrative and conflicting altogether, they simply get revised away on the back end and out of sight.

We’ll start with the bulk revisions the net effect of which is obvious and clearly provides empirical evidence of co-mobridity harvesting as a primary construct driver.

Below we begin to get into those granular aspects of how the data is curated with that similar language I mentioned above. As we do, note that the broader NHCS source data is derived from “Uniform Bill [UB-04] administrative claims” or “electronic health records” from a nationally representative sample of 608 hospitals.

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 NCHS 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.

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?

I also took specific note of how the data are not nationally representative and in light of the evidence following below this strengthens our positions. Some locations deciding things for other locations.

Here we get into the “scheme” responsible for determining the 37 hospitals that were selected to be the COVID data drivers in the “NCHS urban-rural classification system for counties.”

Here is a graphic representation of it.

This following document entitled 2013 NCHS Urban-Rural Classification Scheme for Counties details the formulation of the data provider scheme [interesting word choice in the world of fraud, no?] in 81 pages and it presents with the following description for that formulation; and noting the draw-back to established work on the 2001 timeline as discussed in Dangerously Changing Inconvenient Rules,

The first NCHS urban–rural scheme, developed in 2001 and referred to as the 1990 census-based NCHS urban–rural scheme, was a six-level classification scheme for counties. This scheme was based on the 1990 Office of Management and Budget (OMB) standards for defining metropolitan statistical areas (MSAs) and on data from the 1990 census. It was updated in 2006 (referred to as the 2006 NCHS Urban–Rural Classification Scheme for Counties), following release of MSAs and micropolitan statistical area delineations based on application of the 2000 OMB standards for defining MSAs and micropolitan statistical areas to 2000 census data. A detailed description of the construction of these two schemes is provided in an earlier report (1).

Again, remember that what were doing is coming through 81 pages to dig-out the 37-hospital list. Absurd.

Inside of that document, our previous 63 figure bears down with “Large central metro” considerations relative to federal dollars in 2006 but it doesn’t hold up for 2013, which represents the current model and whereby footnotes make the county classifications malleable and permit skewing the numbers at the skewer’s discretion.

Moreover, there is a bunch of included dialogue, tables and footnotes identifying county classification outliers, the reasons for them and classification changes that contradict their own data parameters. Attempting to unskew it all has been so far fruitless with a less than fulsome understanding of the full data set to permit decoding the skews. Time limitations apply.

Keep in mind that if data from [63?] large metro counties is driving the decisions for the entire country, it fails to take into account that most of America is geographically rural [and remembering that Alaska is not to scale in the images.] This is compounded when we understand that it’s actually 37.

Viral outbreaks present differently in densely populated urban environments as compared to sparsely populated rural ones. So then, we have a real issue if a narrow scope of 37 hospitals were used to drive the metrics to formulate pandemic guidelines and mitigations writ large for the entire country and especially since they so clearly align on exact and precise political lines. This is critically so when coming to understand that in those sparsely populated rural areas the only real threat was fake flu/pneumo data [co-morbidity harvesting.]

That smells like fraud. That looks like more deliberate steering to desired data endpoints.

As we mine stacks of complex documents in an attempt to locate our data targets and then discern and identify them accordingly, there’s a real possibility I’m wrong here. But I don’t think I am because after all, they make stuff like this hard to find on purpose to keep regular folks from finding it. More importantly, I’m following the trail of crumbs they were required to leave as per the box and its rules.

If this is the case and I think it may be, the fraud presents in obvious ways as depicted here urban-rural.

Importantly, we note that despite Leftist and Progressive outrage against statistically [FBI’s own crime data] and demonstrably fraudulent “systemic racism” [the BLM construct] a major portion of America is poorer, white and living in a rural setting; and without urban conveniences. Still though, it appears as if it’s urban areas [the ones under Democratic control forever] that appear to drive the decision making process for the entire nation thus entangling federalism once again. Certain locations deciding things for other locations; especially the ones that don’t have the financial resources to fight back.

From the 81 page document outlining the formulation of the urban-rural scheme, which sets the data providers/data drivers for the construct, we note the occurrence of our ambiguous and vague 63 data point in the following 2 tables but we also recognize the flaws associated with it [2016 v. 2013.]

Here are the footnoted permissions to 1) create rules establishing how the data driving county classifications are assigned with 2) room left to break those rules to steer the data outcomes as desired within the classifications. Or, in other words, make sure you get the ones you want.

This graphic also from the report presents the general concept.

In the extracted pages that follow [Table IV below] we have the list from which I believe we can extract the 37 if we can unskew it, which I think will take more primers than what we currently have but I think we have parts of it. I’ll spend more time with this and searching for 37 in other ways after publishing.

You may care to scroll on through because I gave you all of the pages containing the locations by 53 subgroups and I list the itemized subgroups below the pages. This is Table IV from our document.

Here’s the the itemized list of the sub-groups derived from the previous pages. The itemized list presents as urban hub areas consisting of a county or a conglomeration of counties. The 37 COVID data providing hospitals should come from this list and if controlled for redundant/overlapping locations, we can likely narrow it further to some accurate degree. We’re going to use funding as one control to examine this list and unskew it for the 37.

  • Atlanta-Sandy Springs-Roswell, GA
  • Austin-Round Rock, TX
  • Baltimore-Columbia-Towson, MD
  • Birmingham-Hoover, AL
  • Boston-Cambridge-Newton, MA-NH
  • Buffalo-Cheektowaga-Niagara Falls, NY
  • Charlotte-Concord-Gastonia, NC-SC
  • Chicago-Naperville-Elgin, IL-IN-WI
  • Cincinnati, OH-KY-IN
  • Cleveland-Elyria, OH
  • Columbus, OH
  • Dallas-Fort Worth-Arlington, TX
  • Denver-Aurora-Lakewood, CO
  • Detroit-Warren-Dearborn, MI
  • Grand Rapids-Wyoming, MI
  • Hartford-West Hartford-East Hartford, CT
  • Houston-The Woodlands-Sugar Land, TX
  • Indianapolis-Carmel-Anderson, IN
  • Jacksonville, FL
  • Kansas City, MO-KS
  • Las Vegas-Henderson-Paradise, NV
  • Los Angeles-Long Beach-Anaheim, CA
  • Louisville/Jefferson County, KY-IN
  • Memphis, TN-MS-AR
  • Miami-Fort Lauderdale-West Palm Beach, FL
  • Milwaukee-Waukesha-West Allis, WI
  • Minneapolis-St. Paul-Bloomington, MN-WI
  • Nashville-Davidson–Murfreesboro–Franklin, TN
  • New Orleans-Metairie, LA
  • New York-Newark-Jersey City, NY-NJ-PA
  • Oklahoma City, OK
  • Orlando-Kissimmee-Sanford, FL
  • Philadelphia-Camden-Wilmington, PA-NJ-DE-MD
  • Phoenix-Mesa-Scottsdale, AZ
  • Portland-Vancouver-Hillsboro, OR-WA
  • Providence-Warwick, RI-MA
  • Raleigh, NC
  • Richmond, VA
  • Riverside-San Bernardino-Ontario, CA
  • Rochester, NY
  • Sacramento–Roseville–Arden-Arcade, CA
  • San Antonio-New Braunfels, TX
  • San Diego-Carlsbad, CA
  • San Francisco-Oakland-Hayward, CA
  • San Jose-Sunnyvale-Santa Clara, CA
  • Seattle-Tacoma-Bellevue, WA
  • St. Louis, MO-IL
  • Tampa-St. Petersburg-Clearwater, FL
  • Virginia Beach-Norfolk-Newport News, VA-NC
  • Washington-Arlington-Alexandria, DC-VA-MD-WV

We really need the exact list of 37 to better understand how the COVID is curated and how it fits into the construct I’ve demonstrated.

When we get it, I want to vet it against the discretionary funding mechanisms I’m outlining next relative to the ACA, the stolen election, Soros’ prosecutorial grabs, anomalies in federalism and more.

Really, I want to see the funding because funding and grants create documentation. If this list of 37 is the same list or is included in the list of top recipients of discretionary funds, then we’re likely standing of firm ground.

What happens when we vet all of that against those who are entangled in private equity and we identify ties back to those 37 hospitals?

I think we’re standing on firm ground.

I’m also going to be embarrassed if someone sends me the link for the exact list because I’ve looked every way I know to look and I can’t find it. It would be disappointing if I overlooked something obvious or easily accessible. Really I’d be happy to get it though.

For now, hold on to 37 and our list above because we’re going to come back to it post-ACA. Let’s diverge into Obamacare to understand the roots for 37 and to see the ACA’s broader impact on it all relative to epidemiology, pandemic, infectious outbreaks and all of the regular and customary things you find in a global fraud scheme built around a fake pandemic.


Let’s begin with the ACA itself and we’ll get right to brass tacks.

Building on established positions and evidence by years and spades, the Affordable Care Act appears to evidence the laying of the foundation for an overthrow constructed around a pandemic constructed around fraudulently propagated infection and mortality data.

Our ACA lenses are federal funding, federal grant money, recipients thereof, “surveillance,” the 37 entities that provide the bulk COVID data that factor into the CDC/NIH/NIAID pandemic guidelines and the ACA; and all collectively viewed through our primary fraud lens.

The methods here do not include reading the entire bill; time limitations apply. The results here are delivered by searching the bill for key terms.

As we get into this remember that in fraud and because of the box and its rules, the players essentially have to put their intentions down on paper or in this case, within the language of a piece of legislation. Just like we unskew numbers to find real and accurate values here we unskew language to understand how it veils the truth and serves the construct.

In the ACA, we find this with the understanding that Obama sought to “fundamentally change” America when he entered office in January 2009. In order to do that within a fraudulent construct, sole discretion to award funding, grants and financial incentives are framed under fraudulent pretenses. Here we have both and noting how “TRANSFORMATION GRANTS” applies to another foundational position stating that federalism serves as the enforcement mechanism for the construct. It plays out as awarding competitive grants with sole discretion and whereby “State and local government agencies and community-based organizations” [federalism] receive the funds for the “implementation” of the transformation.

As the entry describes “transforming communities” under the guise of healthcare being delivered by the equivalent of your local DMV branch, recall the backdrop already in place: Biden is a Chinese proxy who is facilitating the application of Chinese doctrine [primarily One Belt, One Road] to the U.S. by means of the forthcoming infrastructure bill and his Executive authority writ large.

What follows is so critical to everything and like many other angles, no one else talks about it but we Moonshiners. Perhaps that’s because the evidenced position discussed in multiple articles is dead-on in an era of unprecedented censorship.

The critical point is this.

Chinese doctrine leverages energy as its financial arm [One Belt, One Road and where the CCP serves as the political arm] and in the same vein, infrastructure is the primary mechanism to accomplish political objectives and change. Infrastructure then becomes a primary mechanism that permits the CCP to apply political doctrine to the real world, in real tangible ways and whereby infrastructure is the interface to desired change.

Rinse/repeat here and now with Biden.

Now you know why Pelosi/Schumer/Democrats refused to do infrastructure with President Trump and insist upon it now.

Now you know why Biden’s infrastructure bill’s elements are far, far beyond the sphere of what infrastructure really is and more closely align with “fundamentally” changing America under fraudulent pretenses as is found in EVERYTHING THEY DO.

Now you know why Obamacare had to pass and become law and now you know why a supposedly Republican, Conservative and compromised Chief Justice John Roberts made sure Obamacare stuck.

Pelosi/Schumer/Democrats refused to do infrastructure with Trump because they were preserving the CCP’s primary mechanism to affect change in real and tangible ways.

Rinse/repeat here and now with Biden.

I took the time to outline that because it’s critical and no one else talks about it but us. Mot importantly, it enmeshes or marries the ACA to infrastructure. The ACA therefore serves the construct as the interface that permits infrastructure to be reciprocally infused into healthcare and healthcare into infrastructure.

It’s like infrastructure and healthcare “become friends with benefits” and China is infrastructure’s pimp.

Here we show you where and how we think that is happening.

In summary and to move forward, if infrastructure serves as the the direct application of a mechanism for change, then by entangling infrastructure, healthcare and epidemiology together in reciprocating legislation where each includes the others, it lays a bedrock foundation in U.S. law that works against the American people and for the Chinese as explained and in ways that are entirely serviceable to a pandemic fraudulent construct. Probably just a coincidence.

Another bedrock position for us is that our nation’s biggest scab – slavery, the Civil Rights Movement, etc. – is being picked and leveraged back against the people as an enforcement and offensive mechanism. See the entanglement of Antifa and BLM and all of their subsequent incendiary, riotous and murderous mayhem circa the summer of 2020 to the present.

Even further, see the dearth of prosecution in locales that also feature George Soros’ installed prosecutors and consider them all relative to the disproportionate and political prosecution of the 06 Jan 21 Capitol “insurrectionists.”

In that light, here is our map overlay as also noted above relative to federalism. We’re currently enduring modern era World War II Nazi era propaganda being enforced by Nazi tactics. Period. For anyone who disagrees, open a history book already and utilize that lens, please. The map evidences it. Some locations deciding things for other locations.

Through the broader lens I have put together for us, which centers on transforming communities, let’s read this bedrock language from the ACA and then you can decide for yourself if it would be beneficial in a situation that entailed overthrowing the nation under the guise of a fraudulent pandemic and applying infrastructure as the politically dogmatic change mechanism.

As you do and although not highlighted, see how this becomes unilateral at the CDC director’s sole discretion. It is again emblematic of the layered and redundant control systems deliberately enmeshed in this other worldly fraud construct.

In the following we note the annual tie back to the director on important matters that we’ve already discussed in previous work including using mental health to cleave away Second Amendment rights from Americans relative to the explosion of mental health ads contemporaneously found in legacy media and entertainment writ large. Remember, the root word of surveillance is SURVEY.

Then we arrive at this. Meat and potatoes. Brass tacks. Incriminating evidence? Likely.

Below, we’ll note the following.

First, the focus is ‘Public Health Surveillance Systems” relative to “Epidemiology Capacity Grants.” Epidemiology obviously gets our attention and let us not forget that “surveillance” equates to monitoring and providing – or exchanging – information.

From there, the grant recipients are being financially incentivized to “transform” their communities using “innovation” that applies to surveillance and monitoring.

We also note that federalism again bears down as the construct enforcement mechanism since the grants go to “State” and “local” health departments, which are the agencies that issue the mitigations and guidelines as per the CDC/NIH/NIAID; and in the form of gubernatorial edicts that do not constitute law a passed by any state legislature.

Importantly, Fauci, Birx, Pence or even Trump were never directly responsible for the closing or shuttering of anything – they only issued guidelines that were adopted and then enforced at state and local levels – federalism. It cuts both ways. They use it as the construct enforcement mechanism and we can leverage it back against them.

Continuing, this below gives the CDC director sole discretion and complete control inside of a closed loop to allocate the grants/funds. That equates to paying the entities you want for the reasons you want when you want.

Note the continued language of “improving information systems” relative to “information exchange” against the backdrop of “innovation,” grants and the vaccine passport unfolding now.

Also note that the funding is based upon congressional appropriations so Congress can control the entire thing via funding via the appropriation committees in the House and Senate; and as directly and respectively controlled by Pelosi and Schumer.

Take all of that and view it through the lens of the vaccine passport system that’s currently being innovated.

Will you see bedrock pieces? Probably.

In the above extract, the concept of Trump’s vaccine program rises to the surface and in the extract below, we note how the President reserves the right to make the pandemic determination and this draw back on our position that the 11 Mar 20 National Emergency Declaration removed that right from him and compelled Trump to legally defer to his experts, who happen to be the usurping criminal enterprise in the construct. Full circle for them.

We’ll be latching on to the Epidemiology and Laboratory Capacity Grant Program [ELC.]

The Epidemiology and Laboratory Capacity Grant Program

We note that the director of the NIH again reserves the right to decide grant allocation unilaterally based upon the innovation of technologies; and that surveillance mechanisms are attached to experimental products and their alignment with regulatory requirements. Does this sound like experimental mRNA vaccines and vaccine passports?

The type and quality of the listed institutions also comports with the ones that Fauci was engaged with relative to gain of function research [labs and universities like Ralph Baric’s at University of North Carolina or the University of Texas Medical Branch in Galveston and many more.]

This is the Epidemiology and Laboratory Capacity for Prevention and Control of Emerging Infectious Diseases [ELC] cited in the ACA.

Apparently and coinciding with Clinton’s anticipated 2016 victory that was undone by a legitimate Trump win, the ELC serves to pickle the pandemic engine with gas as comporting with the expectation that the COVID pandemic would unfold on the same 2016-2017 timeline we’ve outlined and not the 2019-2020-2021 timeline as per the Trump interruption, which we’ve also outlined.

The images above evidence this as does the ordering of “COVID test kits” circa 2017. COVID wasn’t even created as a pandemic namesake until 11 Feb 20 ergo you can’t have a thing before you actually have the thing, as Dr. Martin likes to put it.

Based upon the evidence, our position is a reasonable one.

This is the ELC cooperative agreement that also indicates funding allocations. We note the 63 figure [Cross-cutting Epidemiology & Laboratory Capacity Program] at the top of page 2 since previous work establishes that the CDC’s bulk COVID data comes from 63 entities that receive federal dollars as I mentioned at the beginning. Are these the 63 and now 37 that provide bulk data? [Tap the document and scroll within it to see the table containing 63.]

The following images represent the ELC’s receipt history and noting the locations [federalism] draws back on our established [via patents and Dr. David E. Martin’s work at MCAM] timeline and further extends it from 1999 to 1995 relative to biosecurity, epidemiology and patent filings. 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.

This is the ELC’s officers structure noting the 63 recipients within 64 jurisdictions.

Here are the officers.

This is the ELC’s 5-year focus with COVID in the cross-hairs.

Okay, here is where 37 begins to bear down again as thrust forward by Obamacare.

What follows are PDFs from the list above [Awards Prior to FY 2020] as embedded into the article to depict ELC funding awards over time and per recipient. It will be important to also apply a political pork spending lens and for example, how red states like Indiana and Kentucky and others factor towards the top via IN/Pence, Ky/McConnell, etc. Here they are.

Here we take note of the umbrella entity that encompasses the ELC as we’ve outlined it. It’s the “Division of Preparedness and Emerging Infections” [DEPI] and it serves as a tip of the spear for pandemic response. Therein, we again note the director’s sole discretion for funding relative to locations [federalism.] The important aspects are highlighted and as you evaluate them, ask yourself if leveraging these components with money would be useful in our fraudulent pandemic. We also note the overlap with bioterrorism thus providing a robust agency to leverage in a pandemic construct.

Here we evidence how funding works per the appropriations committees and we note an example of funding and preparations for an influenza pandemic like the one we’re in [fraudulently] right now.

From this bill, again note the sole discretion of the Secretary to expend allotted funding.

Here we evidence more appropriations considerations for pandemic preparedness as another example.

In this bill and under “Title VII: General Provisions – Sets forth certain limits and prohibitions on the use of appropriations for specified activities,” we note the following and specifically as it relates to a host of other relevant data points typically associated with narrative talking points [levers]: whistleblowers, political opportunities, human trafficking and women, children and equity.

ACA and ELC for 37

Now that we understand what the ELC does, how it applies to Obamacare, how Obamacare provides a bedrock of enmeshed and reciprocating legislation that perfectly services a fraudulent pandemic construct, let’s take the ELC’s base and COVID funding as of June 2021 [from the PDF above] and rank all of the states in order of federal dollars received.

From there, we’ll then take our earlier itemized sub-group list of large metro areas thought to contain our 37 data providing hospitals and cross-reference the two lists to vet them against each other. This should render-out evidence supporting that the federal dollars flowed to a small contingency of 37 select urban hubs that are dominating the nation and driving all of the fraudulent pandemic’s data.

It doesn’t take long to see that our jug holds Moonshine. Via funding and through the first 22 rankings alone, we can account for most of the list. Here’s the spreadsheet work detailing the findings.


If there’s an easy button to find the 37 contributing hospitals to the bulk COVID data set, I’m oblivious to it. I looked everywhere and for a long time.

Even if there is and I just couldn’t find it for one dumb reason or another, all of this work serves our case very well because we can prove aspects of the positions in thoroughly hashed out and logically deduced ways that leave little room for other explanations.

There’s little doubt now as to whether we’ve uncovered a mechanism to allocate federal funding with complete and total discretion from Congress right down to appointed secretaries and directors; and it even provides the flexibility to erase inconvenient data points while permitting the unilateral allocation of money to preferred and desired entities.

Can we say with absolute certainty that this is the system or that it was and is being used this way? No. Can we follow the money to the same redundant locations and make logical deductions evidencing it? Yes.

A lot of elbow grease and Moonshine in this one. I think our jug is water-tight on concept and we have a good idea, but we still need that list of 37.

Why have they made it so hard to find? Rhetorical question.



  1. Glenda Kay Sousa August 11, 2021

    Can you please set up a print mechanism for your articles? They are very long and it’s easier to read and compare all items.

  2. Paul August 11, 2021

    Every time I read one of your posts I’m blown away by the amount of corruption in this country and world. Americans have been asleep far too long and I hope it isn’t too late to recover. The only remedy I can see for this is by the military stepping in because these people are lunatics. Anyway, keep up the good work and know that I link/tell people about this website everyday. Cheers!

  3. Michael Buhagiar August 11, 2021

    Another great article. Many thanks for your tireless work. You’ll be pleased to know that I’ve submitted a paper to Quadrant journal in Australia, based on the Martin interview and your interpretation of it. I have a 100 % record there so am very hopeful that it will be accepted. Also trying to raise awareness of PM on Telegram.There are many ways of waging a war, and mine is by the pen. I think one of the central issues in all of this is the abysmal level of critical thinking capability amongst the general populace in both Australia and the US, possibly slightly worse in the latter, especially in Democrat controlled states. If there has been a cultural Marxist agenda behind this, then it would appear to have achieved its aims. Btw, I entered my url into the correct field and it was rejected. Many thanks again.

  4. Mary February 1, 2023

    A lot of complicated assertions, and not every intelligible.

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