A patent’s viability can be assessed by four objective criteria: its novelty, non-obviousness to a practitioner in the art, ability to be taught from prior art, and finally its isolate case of use. By these same four factors a purported expert may also be evaluated for their genuineness in delivering their craft.
In specific roles during my career I have had the good fortune to both conduct patent strategies and manage successful patenting processes on behalf of my smaller clients. In one instance my team’s patent strategy successfully defended a small company’s novel technology from both politically powerful investors, as well as a very familiar and notoriously predatory intellectual property tech-development company. If you have ever filed an electronic or mechanical device/apparatus patent, you probably already bear a suspicion as to what company this might be. You would probably also be correct.
Moreover, I have a handful of patents in development right now regarding a novel energy technology (which will remain confidential). During these opportunities it was my good fortune to be instructed/mentored by some of the top patent attorneys in the United States. My task was to teach them how each technology could be brought to bear and impact a market or vertical, as well as what features/applications must be protected to the greatest degree through what is called by the practitioner, ‘layering’. Their task was to teach my team how to craft patent structure and negotiate a successful prosecution process with the US Patent and Trademark Office. Despite all this, I am merely a journeyman with regard to patenting – what might be deemed a Type II Expert below. However, this does not prevent me from adeptly applying those lessons learned in developing patents as a Type III Expert in skepticism, nor from spotting the pretenders therein.
The Three Types of Expert
At a basic level, the strength of proficiency on the part of an expert can be discerned through how they deal with randomness and obviousness within their chosen topic of prowess.
Expert – one who can negotiate randomness and spot obviousness, more reliably than the average person.
Therefore, beware of the circumstance where subject professionals who understand this, bear only enough expertise to frame their works or analyses as successes, and essentially nothing more.
The four objective criteria used in crafting a viable patent, are also useful philosophically under ethical skepticism. They bear utility in discerning the pseudo-expert from the real thing; in particular regarding how the erstwhile expert handles randomness and obviousness within their subject. For example, a faking expert skeptic will appeal to a corrupt buzzword called ‘Occam’s Razor’, which conflates the cache of obviousness with simplicity – in hopes that if their target fails to detect this sleight-of-hand, they can then offload to them a number of religious conclusions they favor, as also being ‘simple’ (and therefore scientific).1
In general, with some overlap, there are three types of expert and expertise. The Type I or what I call, Bowel Movement Expertise, the Type II or Semantics Expertise, and finally Type III or Hard Expertise. Their framing along the lines of each of the four objective criteria for successful patents, is outlined in the graphic below.
Type I: Bowel Movement Expertise
The bowel movement expert (derived from an activity in which everyone is an expert, but some regard that their own expertise therein is superior – a perfect storm of ‘their shit don’t stink’ and ‘don’t know jack shit’) is an advisor inside a subject which is part of everyday life or is commonly experienced by many or most people. Many times this species of expert is someone who found a new way to skin the cat, or is spinning a new take on an old subject. Often this can involve a bit of huckster play as well.
An example of this species of expert might be the case of a skeptic, astrophysicist, astronomer, or even instrumental sky-survey specialist who thinks along the lines: ‘If Unidentified Aerial Phenomena were real, I would know about it’. When in actuality, they don’t know jack shit more than the average person about the topic, and a lot less than do subject specialists.
Politics or advertising are realms of endeavor which involve bowel movement expertise promoted through an appeal to authority. Ultimately the most effective means of persuasion brought to bear by this type of expert comes in the form of Aristotle’s pathos. In other words, this type of expert is there to sell you something by appealing to your emotions or desire for quick and simple finality, as opposed to actual knowledge.
Expertise is held to varying degrees by almost everyone – and is rarely novel.
Few actual experts exist, and those who pose as such are mostly specialists or hucksters exploiting false novelty, randomness, and obviousness.
There exist few or very narrowly applied standards or procedures – while method is usually not teachable.
Relies heavily upon abductive inference from an appeal to authority or at best, established prior art.
Examples: Politician, TV gadget-sales personality, weight-loss celebrity, nutritional supplement expert, football or basketball fan.
Type II: Semantic Expertise
The semantics expert is an advisor regarding the terminology or history surrounding a subject – features of academic knowledge which are not generally known on the part of the average individual. Often this involves intimidation of others by means of specialized language concealing a shallow grasp of true subject dynamics, overly-complex formulas and heuristics used to represent otherwise simple principles, while name-dropping a list of prior art practitioners. Though less common, huckster play can be introduced as well – usually in the form of agency, corrupt data-only science, or fake forms of skepticism.
As we cautioned earlier in this article, the Type II Expert bears only that knowledge sufficient to frame their analyses as successes. In abetment, neither do their Type II Expert peers bear a quality of knowledge sufficient to refute what was contended. As a result, sciences led by such experts spend decades adrift in fecklessness.
Such was the state of epidemiology and its impotent ‘SEIR/SEIRS+ model‘ prior to Covid-19. Despite decades of publication-celebration inside self-congratulation circles, those models and their experts failed mankind miserably.2 These experts were firemen who sat around the fire station for decades, wearing the boots and red helmets, boasting academic credential and supposed prowess – but when the fire actually came, they could not so much as don an oxygen breathing apparatus nor start a fire pump.Their exculpatory cover story? Blaming and intimidating outsiders, implying that such incompetence was everyone else’s fault.
Of course this did not stop these same Type II Experts from drowning out the voices of true modeling, simulation, and economic value chain professionals who were sounding the alarm over their actions. As a result of such semantic play-acting, hundreds of thousands of people died – all because the discipline did not possess a competent understanding of coronavirus dynamics nor true expertise on the societal impact of lockdowns and mRNA vaccines.
Psychology or philosophy are realms of endeavor which feature quite a few semantics experts. This is one reason why I refuse to habitually appeal to ancient Greek philosophers – as novel philosophy is developed in the heart, through life-trial first. Only thereafter is it apperceived, crafted, and posed, and not vice versa (I do however make an exception in the case of Aristotle’s three means of persuasion). Ultimately the most effective means of persuasion brought to bear by this type of expert comes in the form of Aristotle’s ethos. In other words, this type of expert is there to promote an agency or line of reasoning through exploiting semantic ignorance, rhetorical argument, and appeal to credential.
Expertise is established primarily by means of exclusive terminology or subject antiquity and its long list of noteworthy semantics experts – its expertise is rarely novel.
Persuasion hinges upon skill in managing perceptions of success by adeptly surfing randomness and exploiting obviousness.
Standards and procedures are situational (take or leave them depending upon the goal at hand) – and are sometimes teachable from prior art.
Relies heavily upon relative privation and linear induction from prior art.
Examples: Economist, professional skeptic, epidemiologist, dermatologist, academic philosopher, art critic, sports commentator.
Type III: Hard Expertise
The hard expert is an advisor regarding the functional disciplines regarding a specific subject – features of experience-based and field knowledge which are not generally known on the part of the average individual, nor even sometimes academicians specializing in the subject. This expertise involves well-established standards of performance or development. Not only do they grasp true subject dynamics, but odds are that they have incrementally developed some of the industry standard practices therein. I’ve had prospective new clients in the past namedrop my own practice methodologies and industry success case studies to me in a first meeting, as a means of exemplifying subject prowess. Fully unaware that their case examples were the result of my teams’ work.
For example, microeconomics addresses issues around static scarcity, demand, revenue, and the price-leveraging attainable therein. Such knowledge constitutes Type II Expertise (and does bear some utility).
Value chains in contrast, address incremental flows of value, stakeholder impacts, the loading/efficiency of nodes inside the value chain, and resulting margin-leveraging attainable therein (not just price). The latter equates to Type III Expertise. With this type of expertise, it helps to actually have ‘been there and done that’.
How many instances today have we borne witness to industry failure-consolidation and human suffering induced through price and elite stockholder driven decision-making? This is our real pandemic. The net uptake from this: Never allow an economist to develop your business or national strategy. Never allow an epidemiologist to forecast nor estimate social or economic impacts. They don’t actually know how.
Mathematics, genetics, engineering, or medical interventions technology are realms of endeavor which feature quite a few hard experts. Ultimately the most effective means of persuasion brought to bear by this type of expert comes in the form of Aristotle’s logos. In other words, logic can be applied once all the Wittgenstein features of sound foundational knowledge are well established, and firmly affixed inside recognized standards of deliberation.
Expertise is towards the engineering end of the discovery spectrum – and is almost always novel when in development.
Filters out randomness and distinguishes the obvious from the non-obvious.
Involves established procedures, measures, and technical standards – almost always teachable.
Inference is deductive at best, but also often consists of small-increment induction from subject prior art.
Examples: Applied physicist, genetic engineer, cardiologist, mathematician, medical technologist, football defensive line coach.
The adept ethical skeptic should be aware of the type of expert who is approaching them, and regard their strength of advisement accordingly.
A world inquiring about the origins of SARS-CoV-2 has been met with repeated antipathy and lack of cooperation on the part of the Chinese Communist Party. Consequently, any speculation that the CCP concealed the presence of SARS-CoV-2 prior to December 2019 must be researched through an examination of corroborating yet circumstantial evidence. Inference which may be ascertained only through prosecution along a series of must-answer critical questions.
The Chinese Communist Party owes the entire world restitution for its negligent handling and release of a virus which they fully understood could be deployed as a weapon of war. A virus which has destroyed human rights, worldwide economies, and furthermore resulted in over 5 million deaths globally to date.
When the United States Navy mistakenly shot down a civilian airliner over the Persian Gulf, Iran Flight 655 on July 3rd 1988, despite some reasonable evidence as to its helicopters having coming under fire during that incident, the United States could not have reasonably made the claim ‘Does it really make a difference who is at fault? Let’s focus on making sure there is no repeat of this type of incident’.
Despite most folks understanding that it would not (usually) intentionally shoot down a civilian passenger airliner, the United States in this instance still owed restitution to Iran and its harmed citizens for malicious negligence in the handling and safekeeping of a potential weapon of war – an Aegis/SM-2MR anti-air warfare missile system. The United States had been entrusted by the international community with keeping peace in the Persian Gulf and furthermore maintaining the safety of key shipping lanes therein. The U.S. was negligent and cavalier in that duty however, mistakenly releasing a missile and causing the death of multiple innocents. In February 1996, the U.S. agreed to pay Iran US$131.8 million in settlement to discontinue a case brought by Iran in 1989 against the U.S. in the International Court of Justice (The Hague).1
Ethically, a gain-of-function man-made virus is no different than a missile system or weapon of war. Those who are entrusted by the international community with safekeeping of such weapons of mass destruction must be held accountable for incompetence in their handling and employment, as well as the harm derived thereof.
The mistaken disposition of an IFF (Identify friend or foe) aircraft transponder signal as ‘foe (hostile)’ – is not materially different from the inept execution of bio safety level (BSL) lab procedures – both involve a hazardous ‘lab’ environment entrusted to professionals supposedly trained in their craft and its safekeeping protocols. Negligence here, imparts liability.
This responsibility mandate is the impetus behind obfuscation efforts on the part of Chinese officials regarding the origins of Covid-19 – efforts to block a reasonable process of discovery, which are profiled in this article. The People’s Republic of China and its Chinese Communist Party (hereinafter ‘the CCP’, ‘China’s CCP’, or ‘The Party’) owe the world restitution along the same legal lines as those which presided in the Iran Flight 655 case. Theirs was a case of malicious negligence in the handling of a Chinese-made virus which could be mistakenly released as a defacto weapon of war, no different than a missile inadvertently deployed from an anti-air warfare, or even strategic nuclear system. A duty which was entrusted to them by the international community for handling and safekeeping of such a potential weapon. A duty they were negligent and cavalier in executing, causing the ‘shoot-down’ death of myriad innocents outside their nation.2
How do we infer that the Chinese Communist Party both reacted to and concealed the existence of SARS-CoV-2 as far back as March 2018? There is a critical path of query and dependency necessary and sufficient in prosecuting this problem from a deductive perspective. The questions which compose this pathway are exhibited in detail within this article. To summarize in advance, the critical arguments within this article involve nine key avenues of consilient inference:
The mismatch in timing of Chinese SARS-CoV-2 B.1 and B.1.617.2 variant global rates of spread
The conclusive evidence of both risk and culpability that SARS-CoV-2 was released (not zoonotic) from a Chinese BSL gain-of-function lab (during a U.S. ‘pause’ in such research)
The elevated rates of unidentified ‘flu’ in longitude E65-180 nations during 2018/19, matching geographic pathogenic history
The observed natural progression of a 35 to 1 Covid prior immunity signal, in longitude E65-180 and across 173 nations (which presided up until Delta variant natural-immunity breakthrough infections)
The genetics and mutation history of SARS-CoV-2 itself, which strongly suggest an inception case date in early 2018
The 2021 appearance of a pre-October-2019 genetic Jan-2018-LCA highly divergent variant of SARS-CoV-2 (Omicron) in highly immune African populations under low mutagenic pressure
The CCP’s social response to an unknown, which resulted in 45-year unprecedented CO2 ppm reductions during 2018/19
The CCP’s reactive social disruption patterns exhibited during 2019
The CCP’s Nelsonian knowledge of SARS-CoV-2 exhibited in December 2019, along with its concerted efforts to conceal critical information, databases, 8 index-genomes, 174 index and inception case patient samples/profiles, and pertinent lab production logs.
What follows within this article therefore, and through confirmation of some of its central tenets on the part of U.S. Intelligence services (see Question #17 near end of article), does not constitute a conspiracy theory. Its construct follows:
In the January to March timeframe of 2018, the People’s Republic of China experienced a biosafety level (BSL) lab leak of a furin cleavage edited and 4% modified, human-optimized SARS coronavirus. The Chinese Communist Party mandated that this release be kept confidential, hoping that it would die out, as did SARS-CoV-1. The virus ended up spreading more quickly than they had anticipated however, propagating through central Africa and the longitude East 65 through 180 contiguous set of nations – a common geographic corridor through which novel flu and cold viruses have initially propagated in the past.
This proto-SARS-CoV-2 virus accelerated in its human-adaptation and infected a much larger host base than the CCP had anticipated, conferring a high degree of natural immunity to the virus inside more than 66 mostly contiguous nations initially infected.This less virulent form of proto-Covid was dangerous primarily to those over age 85 and was mistaken by apportionment sentinel sampling as high rates of influenza in both 2018 and 2019.Given the younger population demographic comprised by most those nations initially infected, along with the virus’ high percentage of asymptomatic transmission, the proto-Covid illness proliferated undetected while its human host antibodies waned over the ensuing two years.
Unfortunately for the CCP, the virus consequently broke through to a more virulent and deadly form (first Wuhan or ‘wild’ variant) during a mid-2019 tail outbreak in Hubei province. By October of 2019, following significant unrest in a suffering Wuhan city, and under the impending realization that they could no longer conceal an outbreak of such virility, the CCP formulated an elaborate obfuscation campaign and coronavirus mitigation charade. A scheme crafted to both minimize China’s culpability before the international community and furthermore tender the appearance that the resulting catastrophic harm to the rest of the world had resulted from merely a freak occurrence of natural virus evolution. That plan launched on 31 December 2019, when the PRC informed the World Health Organization of a novel pneumonia of unknown etiology which had been detected at a wet-food market in Wuhan City, Hubei Province.
What the astute ethical skeptic may notice is that this hypothesis bears critical elegance. In other words, its construct both addresses every ‘must answer’ or critical path question we just outlined with regard to Covid-19, and achieves this without having to resort to assembling highly convoluted and risky stacks of conjecture in order to do so. The prosecution of this series of 17 critical path questions is outlaid with in this article. One should note however, that the following is not a ‘study’; rather it is an argument and petition for plurality under Ockham’s Razor.
Notes: Click on images to enlarge them inside a separate tab. Reference sources are indicated inside each graphic or in its preamble text/footnote. Also please note that ‘SARS-CoV-2’ or ‘Covid-19’, as used in a context prior to November 2019, can also comprise a precursor or less virulent/communicable early form of the virus (which is also now extinct and unmeasurable, save for 174 early-patient profiles which China’s CCP refuses to disclose). Where a reference Exhibit or Question is not specifically indicated, each paragraph principally discusses the image or chart immediately following it.
1. Did China’s CCP misrepresent Covid’s speed and means of spread/transmission in Jan 2020? Answer: Yes.
China deceptively communicated that Covid-19 had gone from a first infection on December 27th 2019, to the entire world, inside of three months. In fact, Covid actually spreads geographically slow, by season (see Exhibit 2.2 below), from an impetus which involves primarily fecal aerosols active in specific Hope-Simpson seasonal conditions. While it is reasonable that traditional oral fomites are also a principal form of Covid transmission, the big picture does not support the contention that this mode of transmission is its primary one.
Having done work in materials research, I note that often what is observed in the microscopic expresses in the macroscopic. When I observe Covid outbreak inceptions, routes of progression, speed, and patterns in other species – I see fecal aerosol transmission as explaining the big picture very elegantly. Influenza-styled fomites do not travel long distances in the air nor spread through locked-down compartmented offices and apartment buildings, however fecal aerosols can. For instance, one can observe the Midwest deer population Covid-19 infection arrival curve relative to Class B Biosolid spraying in the Midwest for 2020 in Exhibit 1.1 below, extracted and modified from the footnoted Kuchipudi, et al study.3
Deer hunters did not give Covid-19 to their already-dead prey, nor for that matter 33 – 40% of deer (only in the Midwest and not the Southeast or Southwest) by means of direct-contact fomites or ‘tossed apples’. In fact, why would deer bear an equivalent balance of all human Covid variants, if their population outbreak came from single point exposures? This is an ignorant and Pollyanna supposition. As well, this contention has been exploited by China to spread the notion that Covid-19 appeared in the U.S. before it did in China, and smacks of absolute desperation.4
One has to create highly complexity-stacked notions in order to explain Covid-19’s progression via solely fomites. In other words Covid looks nothing like the flu in its geographic/demographic progression. Many of my protein rendering company clients had 25 – 40% rates of Covid by June 2020 – and fecal/offal gravity drains are the most likely candidate in this anomaly. We could see Covid creep in though the rendering supply chain in early July 2020, in southern states last year by examining county by county data. Thereafter, when the top 500 counties for growth in Covid just also happened to overlap 90% with U.S. Midwest corn growing counties in early November last year, immediately after Class B Biosolid application season (see Exhibit 1.2 below) – while 40% of the deer in that region got Covid immediately thereafter – this stands as a deductive piece of evidence as to Covid-19’s method of reemergence-inception. One ounce of deduction is worth a dozen of suggestive study.
Principal spread was by means of household toilet aerosols and plumbing, as well as spraying of Class B Biosolids bearing human sewage sludge onto (primarily corn) fields in the Fall, and the fecal-protein particulate convective uplift potential of CAPE(S) or Convective Available Potential Energy (from Surface). CAPE(S) defines the energetic capability of the atmosphere to loft and carry aerosols (<5 μm)5 or drive aerosolization of open wastewater (as shown in the left hand panel of Exhibit 1.3 below).6 These three factors became the origin of most Covid outbreaks, with household transmission being the principal sustaining factor thereafter (and not public gatherings).7 These outbreaks then followed a Hope-Simpson seasonal-latitude progression and did not principally spread through breathing fomites as does the flu – as China had claimed early on to the international community.
2. How long does the most communicable Covid variant (B.1.617.2 Delta) take to progress globally? Answer: 10 months. And to herd resistance? Answer: 24 – 32 months.
The seasonal spread from the chart peak on the left in Exhibit 2.1 below, to the peak depicted in the chart on the right, will actually span a period of around 5 months – half of its global progression reach timeframe. Covid’s natural spread does not come in the form of rocketing across the globe in just over two months as it turns out, contrary to what we believed (were told by China’s CCP) in March 2020. Remember that the first priority of China’s CCP was to confuse the international community as to Covid’s characteristics and measures – so that their culpability in its release could not be directly observed nor inferred.
The reader should keep this principle in mind to the end of the article: The relatively advanced early knowledge regarding SARS-CoV-2 on the part of the CCP, their adept grasp of exactly what was needed in order to confuse origin issues, knowledge of fecal aerosol mitigation protocols, and awareness that they were in Covid’s third and final year for their nation – is collectively called Nelsonian Knowledge. It betrays a deep experiential knowledge of Covid-19 and its particulars on the part of China’s CCP – a knowledge they should not have possessed, if indeed this was a ‘novel pneumonia’.
The Party Rule #1: The Party must not be mocked.
One must remember two principles in this deliberation of how fast Covid, and in particular the Delta variant, spread globally. First, Covid vaccines do not stop the transmission of the virus, rather only serve to mitigate its severity in vaccinated individuals.8 In fact, the opening of society based upon higher levels of vaccination, only served to speed the transmission of the Delta variant, not slow it. Second, the Delta variant still infected those with natural prior immunity from previous Covid B.1 and B.1.1.7 infection. So the notion that, for these reasons, the Delta variant spread more slowly across the globe is incorrect. Therefore, the fastest actual global spread we witnessed for a Covid variant, was indeed 10 months in duration, as indicated in Exhibit 2.2 below.
Exhibit 2.2 below was developed from GSAID: CovidCG Global Lineages Variant Tracker – New Lineage Percentages by Week. Period of escalation for B.1.617.2 was 56 weeks. We assume 41 weeks for conservancy. Raw data snapshot can be viewed by clicking here.
Moreover, take note that each main wave of SARS-CoV-2 inside a previously naive nation, generates a serum IgG antibody prevalence of around 12 – 18%. Observe the net effect of six months (Apr – Sep 2020) of Covid-19 in the United States in Exhibit 2.3 below. This was repeated in European and South American nations as well. The fact that Covid spreads slowly, not fast, mandates that 5 to 7 waves of Hope-Simpson outbreak are necessary to bring a population into any semblance of herd immunity.
The period in which this takes place is around 24 – 32 months, with some straggling communities (such as Wuhan in China) filling in at the tail, before the virus has run its full course. China bore this understanding as Nelsonian knowledge and exploited that awareness to tender the appearance of cultural superiority. They ‘quashed Covid’, when in reality they had merely surfed the final (albeit more deadly Alpha variant) Wuhan wave (in green in Exhibit 2.4 below). They were still vulnerable to the Delta variant in late 2021, however more in the form of an endemic arrival profile and not a naive outbreak.
Accordingly, now that we have a solid and repeatably-observed benchmark as to how long it takes for a naive demographic compartment to reach Covid-19 herd immunity (before arrival of a significant variant such as Delta), if we subtract this observational period from the end of the Wuhan outbreak in March 2020, we arrive at an inception date for China, of January – March of 2018.
Therefore, theories which assume (and fail to inform of this assumption) that 66+ contiguous nations (led by China statistically, see ‘Zone I’ in Exhibit 4.5 below) used an unacknowledged implicit magic to avoid a full 28 month course of Covid-19, are not credible.
3. Were lockdowns ‘successful’ as a means to mitigate Covid spread, as China’s CCP claimed? Answer: No.
“We cannot rule out the possibility that the local population’s fear in the early days of COVID-19 determined both the strictness of state-imposed lockdowns and subsequent COVID-19 death rates, with no direct causal link between state actions and subsequent observed deaths.
By shutting down large portions of the economy, lockdowns were accompanied by the failure of many businesses and a massive increase in unemployment. While the entire country has been affected by the pandemic, low-income and middle-income workers have been disproportionately impacted. As a result of furloughs, layoffs, and general economic retraction, as many as 8 million Americans have fallen into poverty since the pandemic began.”9
~ Rice University’s Baker Institute for Public Policy; Report on State Restrictions versus Covid Death Rates
Sweden, one of the few nations which refused to heed the lockdown-fable boasts on the part of the long E65 – 180 nations, has fared better than or equal to, most of its peer nations in terms of Covid cases (Exhibit 3.1 left panel below) and fatality rate (Exhibit 3.1 right panel below). Lockdowns in those peer nations bore no appreciable impact benefit as compared to Sweden. (Note: Sweden’s ‘peer nations’ in terms of pandemic are not small compartmented communities, peninsulas, nor islands, such as exist in Norway, Denmark, Finland, Ireland, Iceland, etc.) (Charts below are from 91-DIVOC and Our World in Data).
Sweden Charts – Cases per Day and Case Fatality Rate (log)
Neither a 70% vaccination rate, nor extensive lockdowns have proven effective in quelling Australia’s severe SARS-CoV-2 Delta variant outbreak. The Gompertz progression proceeded unabated through a normal profile as shown on the left in Exhibit 3.2 below. States such as Australia and New Zealand paid an albeit later in the game, but still heavy price for misunderstanding what exactly worked and did not work against Covid-19 (Left panel in Exhibit 3.2 is from WorldoMeters, Right panel is from Our World in Data) Suddenly, with the onset of the Delta variant, the boasting about superior national lockdown policy and execution has ended.
In the right-side panel in Exhibit 3.2 below one may observe as clean a peer-cohort comparison as can be derived globally regarding lockdowns (there are at least 15 more comparatives just like this). Estonia’s case curve behaved (non-coincidentally) in arrival distribution exactly as did the case curve of its lockdown neighbor, Latvia. Lockdowns work on fomite-transmitted heavier-than-air direct contact pathogens. Lockdowns are not effective in the face of fecal-aerosol (<5 μm) transmitted viruses – and unless the pathogen involves a large outbreak of fomite-transmitted Ebola, they constitute a human rights crime of the highest order.
Finally, just as in the case of Australia, as soon as these nations in the long E65 – 180 geographic block were hit with the Delta variant of SARS-CoV-2, the variant with the most genetic divergence from B.1 – they suddenly found lockdowns to be useless as well. The case is clear. Prior immunity benefited these 66 nations, called ‘Zone I’ nations later on in Exhibit 4.5, but only lasted for a couple years up until the Delta variant (B.1.617.2) breakthrough against a waning IgG antibody base.
This should not have been a surprise, because all four existing endemic human coronaviruses (HCoV’s 229E, NL63, OC43, and HKU1) have been mutating and breakthrough-reinfecting the population with new mutations every 3 to 6 years, for literally most of the last century.10
In Exhibit 3.3 below, one can observe the net effect of the combination of waning IgG antibodies and the breakthrough of a new SARS-CoV-2 variant on the Asian population which had once had 92% lower rates of cases and deaths (see Exhibit 4.2). We observe the coincidence with rates of vaccination without remark.
4. Did Covid spread in Feb/Mar 2020 as if it was a pathogen novel to the entire globe? Answer: No.
By August 2020 it had become clear that the contiguous group of nations in the East Asia-Pacific region between longitudes E65 and E180 all bore a prior immunity to Covid-19. This was falsely passed off as the result of superior knowledge, governing, mitigation practices, and racial stereotypes on the part of those nations. In fact, as it turned out, those nations had been exposed to a precursor SARS-CoV-2 or SARS-CoV-2 itself, long before the theater of coercion which encompassed 2020.
Specifically, nations in this geographic cluster bore a null relationship between size of population and number of Covid cases or deaths (beige dots and Pearson line in Exhibit 4.1 below). Since Covid spreads in the household and inside venues which cannot be sanitized completely, only prior immunity can create a lack of association between these two variables to this comprehensive degree. It is clear that SARS-CoV-2 behaved as if already endemic inside this geographic block of nations.
As one can see in Exhibit 4.2 below (extracted from WorldoMeters), by mid October 2020 most of the group of longitude E65 – 180 nations had experienced only 8% the rate of the world’s average national total cases and deaths from Covid-19. This trend was later broken by Covid-19 Delta variant natural immunity breakthrough illnesses which skyrocketed in that same longitude region in mid 2021 (as we saw in Exhibit 3.3 above).
Having one lockdown nation exceed another lockdown nation’s NPI performance by 1250% (1.00 – .08 or 92 percentage points) is one thing – which itself pushes credibility. However, having 20+ contiguous nations (40+ if you count Equatorial African nations) collectively exceed the entire world by 1250% is a claim that a reasonable ethical mind cannot let stand unchallenged. No hypothesis which accepts this as part of its structure has been vetted properly in its duty to reduce, address, and inform.11
This differential shown in Exhibit 4.2 below was produced by nascent prior immunity (i.e. not extant Human CoVs), and any hypothesis to the contrary must assemble grand stacks of convoluted and improbable happenstance in order to explain this. Nascent (SARS-CoV-2 or precursor) immunity is elegant and is also the null hypothesis in this case.
This block of nations (shaded blue in Exhibit 4.3 below), between longitude E65 ad E180 bore the highest level of immunity to Covid, followed by central African nations with high concentrations of Chinese workers/projects, and exposure along equatorial trade winds along CAPES (see Question #1 above) concentrations.
Moreover, these exact same nations have a solid history of being the first nations which gain exposure/immunity to Asian novel pathogens in the past. Thus there exists a long precedent of history as to this pattern of pathogen progression globally. Below in Exhibit 4.4 we observe that the 1957 H2N2 flu took the same exact pathway of spread which SARS-CoV-2 has under this article’s line of conjecture.12
To sum up Exhibits 4.1 through 4.4 into two charts, below one can observe (Exhibit 4.5 – deaths per million in population) both the geographic migration of the SARS-CoV-2 virus from the longitude East 65 – 180 nations (on the right in green), across the years and globe through to the 35 holdout or virus-naive nations (on the left in blue). There are three zones of mathematics embedded into the curve in the chart plot itself (beige line). An inelastic (Zone I – immune) set of 66 nations, a linear (Zone II – transitional immunity group) set of 107 nations, finally followed by our exponential (Zone III – naive) set of 35 nations (Chart is developed from WorldoMeters Covid-19 case, death, and population data by nation).
This is important. The set of groupings and their associated mathematics outlined in Exhibit 4.5 below deductively falsify the notion that the below immunity (remember the context is immunity here, not infection) profile spread across the globe in 2 to 3 months in early 2020. There is absolutely no viable possibility that such a spread could have produced this, a. contiguous, b. mathematically segmented, c. 35 to 1 ratio signal, and d. conforming-to-typical-viral-history sequence of immunity arrival across 173 of 208 nations in that short amount of time. Zero.
The outbreak waves in Exhibit 2.4 reiterated below, are necessary to produce the immunity profile shown in Exhibit 4.5 further below. This is a ‘must address’ question and any hypothesis which does not have a straightforward answer for this is a false hypothesis.
5. Were the nations hardest and least hit by Covid concentrated into longitudinal groups by human travel and climate pathways? Answer: Yes.
Not only were the nations which exhibited prior immunity to SARS-CoV-2 all grouped together inside traditional pathways of historic virus spread, as well, these nations (outside of China) happened to reside along equatorial trade wind latitudes transferring virus material westward towards central Africa and the remainder of Pacific Oceania.
Just as did the 1957 H2N2 influenza, SARS-CoV-2 transferred along CAPE pathways of viral conveyance globally. Geographic proximity, regional worker migration corridors, and CAPES-energized air movements, in that order, appeared to be the primary factors which related to prior immunity against SARS-CoV-2. Below in Exhibits 5.2 and 5.3, one can observe that SARS-CoV-2 communicated not only along CAPES and worker-migration pathways, but along the exact same geographics as the 1957 H2N2 influenza did as well (see Exhibit 4.4 above). Exhibit 5.2 is provided courtesy of Twitter’s @StatSleuth.
6. Were there indicators that an unknown pathogen struck areas least hit by Covid, in the years prior to Covid-19 – and further then finally struck Western nations 10 to 18 months later? Answer: Yes.
It became clear in my investigation, that the Pacific Rim and Oceania nations (Exhibit 6.1 below) purportedly bore the sole ‘success’ in lockdowns globally. However, eventually lockdowns were disproved as an effective means of mitigating SARS-CoV-2. So how do we resolve this conundrum? The next candidate for such mitigation was prior immunity to SARS-CoV-2 in particular. But this required that Covid, or a precursor thereof, circulate in the 12 to 21 months immediately prior (based on IgG antibody dilution curves which left the same region vulnerable to the Delta variant in 2021) to the 2020 pandemic. Was there evidence that such a pathogen indeed circulated in these regions and in this timeframe? Yes, good evidence in fact. Exhibits 6.1 and 6.2 show clearly that a sudden rise in illness and death preceded Covid in these prior immunity nations during the 2018 and 2019 timeframe.
Remember that very few cases of influenza are actually derived from a genetically tested phenotype. Most cases are diagnosed abductively (are simply declared to be flu, because that is what is going around and that is what sentinel stations have apportion-sampled). In the years immediately prior to 2020, the Pacific Rim and Oceania nations which showed prior immunity, just happened to also experience much higher rates of influenza and death in their 85+ age cohorts (see Exhibit 6.2 below).
However, in the U.S. one can observe in Exhibit 6.3 immediately below, developed from National Center for Health Statistics data, a sudden uptrend in Alzheimer’s and Dementia deaths beginning in the early summer of 2018. Given the very close association (#1 rank, #2 is metabolic disorder – with many medical professionals regarding A&D to simply be late-stage diabetes/metabolic disorder) between this particular comorbidity and SARS-CoV-2, this change in a long-established growth rate of 1.35% is alarming. Something caused this, aside from the normal demographic trends which drive the former 1.35% annual increase. That something was introduced (on this chart) in May of 2018, and escalated strongly in 2019, causing an exception in terms of excess deaths in the 65+ and 85+ age cohorts in the U.S., as we observe in Exhibits 6.4 and 6.5 later below. The unknown malady then dovetailed nicely into Covid-related Alzheimer and Dementia deaths in 2020. This steady scale-up from 2019 and into 2020 was not a coincidence.
I do not hold therefore, that the July 2019 Virginia Department of Health elder care center respiratory illness outbreak deaths or other U.S. respiratory illness outbreaks in 2019 (cited in Exhibits 13.9 through 13.11 below) were a mere coincidence. Nor have they ‘been debunked’ as a form of Covid precursor – because we no longer have access to the measures necessary to debunk them. I bristle at drawing inference from such a position of politically-motivated ignorance.
Across the nations in the eight panel charts below (Exhibit 6.4), one may observe the progression of excess deaths in the 65-year old and older cohort for the years 2015 – 2021 YTD. In each nation, an off-season (this is important) departure from historic growth (or decline as demographics dictate) begins in early to mid 2018 – with an excess death rate for this Covid-vulnerable age cohort persisting right into the December 2019 inception case period for Covid-19. The data is obtained from the University of Berkeley, Max Planck Institute – Human Mortality Database.13
One may observe a very strong off-season excess death signal in mid-2019 for South Korea and Taiwan (as we see also in Exhibit 6.5 below), both nations which had ‘successful’ lockdowns until the Delta variant arrived in 2021. One may observe for Australia and New Zealand as well, that both nations did not suffer from Covid-19 in 2020 – instead they suffered excess deaths in 2018, 2019, and 2021 (Delta variant). What was the factor which caused these excess deaths worldwide during the very pre-Covid timeframe upon which this article focuses? We contend that the SARS-CoV-2 genetics dictate that this was a milder form of precursor virus.
In particular, one should note that the off-season excess death in the United States panel on the lowest left of Exhibit 6.4 is solely driven by the high Covid-comorbidity relationship cited in Exhibit 6.3 above. This is the most Covid-vulnerable population therein, and also happens to match the timeframe where something was killing the 65+ age group to excess in all these nations. We do not believe that this is a coincidence.
The excess death in the 85+ age cohort for 2018/19 shown in Exhibit 6.5 below, dovetailed nicely into Covid excess deaths in Italy, Spain, and later on in the U.S. beginning in early-mid 2019. Of key interest to note in Exhibit 6.5, is that both Italy and Spain’s 2019 average excess death for this age cohort constituted a double-digit increase over previous years. 2019 rates of excess death equaled around a third or more of the magnitude of each nation’s 2020 Covid-19-year for the same 85+ cohort statistic. Not a trivial observation by any means. Curiously, Italy and Spain were also the first European nations to be hit hard by Covid-19 in early 2020.
This is neither a coincidence nor the result of statistical drift. An exception caused this to occur, just as happened in Taiwan in 2019 and South Korea in 2018 and 2019. Our contention is that this East-to-West progression demonstrates the natural and well-documented actual spread rate of Covid identified in Exhibit’s 2.2 and 4.5 above. As we will see in Exhibit 8.1 later below, we have established that China’s variant of Covid-19 spread too fast to be credible. The challenge therefore that, ‘Why didn’t Covid spread to the entire world in 2019?’ becomes moot. It did spread. Just not at the Chinese-advertised rate, during a time when the virus was less virulent, and during a heavy flu period wherein we were simply not aware of its presence.
Meanwhile, Australia and other Pacific Rim and Oceania nations struggled with a severe ‘not subtyped’ flu during the 2018/19 season. This ‘flu’ then conferred the observed Covid prior immunity upon the long E65 – 180 group of nations. Below are three charts showing annual rates of influenza for the Philippines (Exhibit 6.6), Japan (Exhibit 6.7), and Australia (Exhibit 6.8).
Note that Australia’s flu peak, the superimposed red arrival curve in Exhibit 6.9 below, coincides nicely with both Japan’s rate of excess death as well as China’s sigma reductions in carbon dioxide emissions for that timeframe. SARS-CoV-2 might or might not have hit the region in 2017, however it is clear that China knew about its presence by Covid’s peak in early 2018. While the CCP responded too late in 2018 to have an impact on the pathogen, by 2019 they knew exactly what they were facing and how they wanted to go about mitigating it (although in the end what turned out to be feckless measures) – but of course the CCP failed to inform the world community because it was ‘none of their business’. As always, this was a Chinese internal-state matter.
The Party Rule #2: Matters of The Party are matters of The Party only.
Not only was there an exceptionally large ‘flu’ rate in China in 2018/19, prior to SARS-CoV-2, but as well there was a curious pause in the 2018 flu altogether (see Exhibit 6.10 below), right as carbon emissions in China plummeted to their lowest levels. Levels which were the result of an unknown-in-cause social clampdown. Curiously this constituted a flu-disappearing-act which was also observed later in western nations during their peak period of SARS-CoV-2.
7a. and 7b. Do Covid-19’s genetics/variants indicate that it existed as a lab-release pathogen well before Oct 2019? Answer: Yes.
7a. SARS-CoV-2 – genetic variance and regression estimates
The genetic divergence dates based upon mutation frequency, between SARS-CoV-2 and its originating bat sarbecovirus subgenus were estimated as 1948, 1969, and 1982, (55 average years of evolution) indicating that if SARS-CoV-2 was of indeed zoonotic as opposed to lab origin, then the SARS-CoV-2 lineage had to have been circulating unnoticed for decades prior to 2019.14 While it is not impossible that SARS-CoV-2 could have evaded detection all this time, by either bat colony survey or human illness sentinel work, this represents a non-trivial measure of genetic distance. One composed of around a 4% nucleotide jump from BANAL-52 (as shown in the Nucleotide Identity Comparative chart to the right), along with an impossible poly-basic furin cleavage segment insertion (center panel of the chart).15 Of particular note, is the fact that human-adaptation features of the virus bear a strikingly large genetic distance from this comparative group, which whole-genome comparatives tend to misleadingly obscure.
This requires any hypothesis that features zoonotic origin as its foundation, to craft complex explanations as to how the modifications in Exhibits 7.1 through 7.5 just suddenly occurred recently, absent of a human host. Conversely, under the assumption that the virus had been circulating/mutating for decades, then one need explain how decades of sampling bat viruses failed to ever find a wild SARS-CoV-2’s species and furthermore demonstrate that it absolutely never jumped to humans prior to October 2019. Both of these demands upon hypothesis are a pretty tall order, even a bit of a Catch-22. There are therefore, no parsimonious zoonotic origin hypotheses.
In particular, the virus bears a genetic exception in the form of a furin specific cleavage site which cannot realistically exist in a zoonotic virus of this phenotype, and had to be created in a lab and gain-of-function setting. The genetic jump from BAT-CoV-HKU5 to SARS-CoV-2, combined with the inception-only human specific mutations (Exhibit 7.2) and furin cleavage insert (Exhibit 7.1), render a zoonotic origin essentially only a desperate political notion masquerading as science. The sole reason it perpetuates as an idea is that experts fear being categorized in the ‘disinformation’ group by various social conformance patrols (see the DNI Report Conclusions 1 – 7 in Question #17 at the end of this article).
As well, despite circulating in myriad number of human hosts for almost two years now, most of SARS-CoV-2’s human-adaptation variations occurred in the ‘early phase’ of (read as ‘in a lab’ or the ‘two years prior to’) the pandemic.
Precursor genetics of the virus identified by China in December of 2019, indicate one or two years of mutation prior to the index case genomics of the B.1 variant.
If one estimates a slope-derivative of the changing pseudo-rate of mutation of the SARS-CoV-2 virus, around October 2020 in the timeline shown in Exhibit 7.4 below, avoiding both the early ‘pseudo-hyper-mutation’ period and the later accelerated mutation brought on by an extreme amount of circulation in the population, one can derive the actual 2018 through mid-2020 intrinsic rate of mutation for the virus. When this real rate of mutation is then extrapolated linearly, it suggests strongly an index case in mid-early 2018 or May 2019 at the latest.
One must bear in mind that the red line in the chart below is not a ‘mutation emergence curve’ but rather a discovery curve. Treating it as the former is an act of propaganda, not science. Neither can one fit a regression line to this entire genomic progression (see an example of such ineptness here), as such a line is not mathematically valid, spans differing nonlinear dynamics, and involves Gaussian blindness.
Please take note that as much as one third of all Covid variations to the end date on this chart occurred in that first month of the virus’ ‘existence’. The reality is that this portion of the mutation base probably occurred over the 20 months prior to December 2020, and not inside the two months shown in the chart below.
Before we move on make a mental note to carry forward as you read, that now we have been huckstered with the notion of global spread, as well as a principal portion of Covid’s history of mutation, as having both occurred in just two months.
Similarly, when linear extrapolations are compared between variants of Covid from outside China, Wuhan, and China areas outside of Wuhan, a progressive story can be witnessed in the mutation base. The areas in China outside of Wuhan featured the oldest variants of Covid, with a suggested index case in mid-late 2018. Thereafter, the strains of the virus in Wuhan coincide with exactly the dates in which Wuhan residents were protesting about a June 2019 unidentified deadly respiratory illness in the city’s population (see Exhibits 11.1 and 11.2 below). In turn, these timeline milestones also happen to coincide exactly with China’s anomalous (45-year exception) reductions in CO2 ppm output (Exhibit 11.4).
7b.Omicron Variant – genetics are older than and lineage does not connect back to Dec 2019 ‘wild’ type
Finally, emergence of the Omicron variant of SARS-CoV-2 in Botswana in November of 2021 presents another post October 2019 falsification-level event. The Omicron variant of SARS-CoV-2 has alarmed many scientists due to the sheer number of genetic mutations it carries — 93 in all, including 32 in the spike protein alone, 16 silent, 27 nucleotide deletions, 3 nucleotide/amino acid insertions, and at least 43 mutations that are unique to Omicron (see both left and right hand panels in Exhibit 7.6 below).161718 In all, Omicron’s mutation set bears 29% nucleotide deletions, which is highly divergent as compared to the known SARS-CoV-2 phylogeny shown on the left side of Exhibit 7.6 below. This percentage of deletions (27 of 93) and amino acid mutations (50 of 93) both far exceed the number of much more likely silent-synonymous mutations (16 of 93). This suggests that the ‘deletions’ are rather actually ‘insertions’ which occurred in the lineage to the 2 Feb 2020 Alpha Variant Clade 20B. The terminology inversion stemming from an effort to stuff a 10 pound virus divergence into a 2 pound bag of posterity. We will treat these generically (conservatively) as INDELs (insertion-deletions) therefore in the genetic clock analysis later in this segment of Question #7.
Under this paradigm, if Omicron turns out to be highly transmissible but mild in terms of symptomatic severity – then it has a great likelihood of being the direct descendant of the pre-Wuhan 2018/19, 173 nation (Zone I and II in Exhibit 4.5 above) immunity-conferring strain of Covid conjectured within this article.
As well, Omicron carries 3 amino acid insertion mutations (ins214EPE) which do not exist in any extant clade of SARS-CoV-2, but does exist in other human alpha and beta coronaviruses.20 If this insertion occurred as the result of ‘template switching’ in a human coronavirus co-infected individual, then the other alleles in Omicron should have matched the lineage of one of our known clades. It didn’t. Thus, we face a confounded problem in trying to stuff Omicron artificially into a recent (<2 year) timeline of origin. In the timeline developed from GISAID data in the left hand panel of Exhibit 7.6 for instance,21 the exceptional red clade-line, which suggests a narrative-comforming lineage for Omicron, is an assumption and not a derivation.
“We probably missed many generations of recombinations” that occurred over time and that led to the emergence of Omicron, Soundararajan added.
Venky Soundararajan of Cambridge, Chief Scientific Officer of EMR data analytics firm nference
This confounding, along with the evidence presented below, indicates that Omicron’s genetic particulars constitute not merely mutations, but more importantly alleles which pre-date, not post-date, our best index case of SARS-CoV-2 in Oct/Dec 2019 (according to Chinese and other narratives). In other words the genetic last common ancestor (LCA, aka ‘MRCA’) which birthed Omicron existed well prior to the Wuhan wild and B.1 variants of Oct – Dec 2019. Again, this is not inductive evidence (as has been used to assemble the Wuhan/China/WHO wet market chronology), but is rather much stronger deductive inference. The entailed calculations and logic are outlined below and in Exhibit 7.8.
Multiple studies have estimated that SARS-CoV-2 mutations occur at the rate of 1 x 10-4 (measured by survival in population)22 to 1.1 x 10-3 raw mutations per nucleotide per year.23 These extremes are shown in Exhibit 7.7 below. This equates to .0001 to .0011 mutations per nucleotide per year, with an average of .0006. Since the sustaining of a mutated clade-member or especially novel variant occurs at a slower rate than the raw rate of mutation,24 we err conservatively towards the survival rate, or .00036 (.0006 x .6 or 3.6 x 10-4) mutations per nucleotide per year, based upon the arrival rate of new sustainable mutations in the circulating population.
There are 29,811 single strand RNA nucleotides in SARS-CoV-2. Given its 93 differential mutations from a ~March 2020 Alpha Clade 20B variant, which can be seen in Exhibit 7.6, this would at first glance indicate around 8.7 years of genetic distance wound up inside Omicron’s divergence from other existing variants. However we must adjust the calculation in that only 66 of the 93 total mutations constitute the most typical RNA virus mutation, called a ‘substitution’.25 Therefore,
Substitution Clock – .00036 x 29811 = 10.7 mutations per year 66/10.7 = 6.1 years of mutation
However, genetic distance by typical RNA virus mutation is not the end-all of this derivation. Not all nucleotides mutate at the same rate.26 As we just mentioned, most mutations arrive in the form of synonymous high frequency events called substitutions – mutations that separate Covid in-clade variants in linear sequence from their initial index sequence (see horizontal lines in the left panel of Exhibit 7.8 below). The mutations in Omicron do not follow this pattern, and in fact constitute an exception within the entire diagram. Instead, Omicron mutations comprise about 32% of what are called ‘insertion/deletion’ mutations (INDELs).27 INDELs do not arrive at the same rate as higher frequency substitutions, but rather constitute less common absences or novel-presences of an entire nucleotide. Insertions and deletions constitute a change in the logical structure of the RNA sentence and not a mere synonymous replacement of a word, if you will. Thus they produce failures (extinction) more often than successes, and as such constitute a much bigger challenge in terms of genetic language. They can also often result in different mutational clock measures as compared to those based upon substitutions alone. In fact, RNA virus INDELs are 4x less frequent in their occurrence than are substitutions (actually deletions are 8x less frequent, and the majority of INDELs for Omicron are deletions – however, we still use 4x here for conservancy).28 If we approach our genetic clock with this second method of measuring genetic distance, we get the following result – which importantly, substantiates and exceeds fairly well our substitution-nucleotide method of measuring genetic distance conducted above.
INDEL Clock – (.00036 / 4) x 29811 = 2.68 INDEL mutations per year 30/2.68 = 11.2 years of mutation
We therefore through triple-conservancy in this method,29 can reasonably cite that 6.1 years (the smaller of the two above substitution and INDEL based estimates) would be the minimum time duration required to enact all 66 Omicron substitution mutations as observed in sample sequence QLD-2568 of 2 Dec 2021. We must leave the alarming INDEL mutation rate in Wittgenstein silence because sadly we cannot connect it back to any kind of usable reference. Finally, before we move on from this set of calculations, we should employ this same method to take quick note of the evolutionary time which would be required for SARS-CoV-2 to have evolved naturally from its nearest relative among beta coronaviruses, BANAL52. This will act as a double-check of the validity of our estimates above as well (consilience). We divide by two here because two virus evolutionary pathways are involved in this analytical context. Reader please note that this is a benchmark comparison for establishing credibility of our assumed 3.6 x 10-4 survival mutation rate only. It does not mandate that SARS-CoV-2 necessarily evolved naturally from BANAL52. The conjectured Jan 2018 lab accident could have released either a natural or edited SARS-CoV-2 under our hypothesis.
Total amount of time needed to naturally evolve from BANAL52 = (1/2 x 4% of 29,811 / 10.7) = ~55 years.
This matches exactly (consilience again) the 55 years divergence cited at the beginning of Question #7a above (1966 average through to 2021). It also means that 1 x 10-3 mutations per nucleotide per year estimates for rates of mutation are far too high and theoretical, to be used as basis for estimating the appearance of sustained Covid-19 variants like Omicron (the context we need for this deliberation). This 10-3 order of magnitude was also the mutation rate for SARS-CoV-1 after all, which mutated so fast that it exterminated all of its genetic lineages before it could spread past one season (see Exhibit 15.1).30 The Furin Cleavage Site mutates at a rate ten times faster (3.6 x 10-3) than does the overall Covid genome.31 So a too-fast Covid mutation rate, will only result in destruction of the virus’ very ability to infect human hosts to begin with.
Our assumed rate of mutation provides for the appearance of a new sustained SARS-CoV-2 variant every year, per clade. We have 23 clades as of December 2021 (see Exhibit 7.8), and only 13 named variants to date – so even this conservative rate indexes high against the Covid-19 mutational reality (left hand side of mutation rate spectrum in Exhibit 7.7 above). Therefore, as a mutation rate, 3.6 x 10-4 not only matches historical indexing against FCS mutations, but moreover provides a falsification-based sound match from every angle of outside-comparative or deliberation within this analysis. Nonetheless, I fully anticipate that the raw (theoretical) 1.1 x 10-3 or higher mutation rate will be exploited by those desperate to enforce the Dec 2019 narrative. Hold them accountable by showing that not only does Omicron not have an existing precedent from which it could recently have mutated (see Exhibits 7.6 and 7.9), but their preferred mutation rate would serve to extinguish SARS-CoV-2 within a season as well – both by SARS-CoV-1 precedent, and by mathematical modeling. Such a raw theoretical and excessive assumption is an orphan assumption and artifice, which in no way matches our observed Covid clade-to-variant reality.
Now lets carry this three-way validated, 6.1 years of genetic distance forward as we consider it in relation to the nearest relative to the Omicron variant. Omicron carries a mutation called N501Y, which affords the virus a greater ability to bind to human cells. This mutation was also present in the Alpha variant and was linked to its higher contagiousness as compared to the wild variant. But N501Y did not exist in Delta, nor the wild variant, so those constitute a separate evolutionary pathway – this is very important. Therefore Omicron must share an LCA not with the wild/Wuhan variant, but rather the very first Covid Alpha 20B Clade of 3 February 2020.32 Remember, that the 66-mutation line drawn in the GISAID chart on the left in Exhibit 7.8 is an assumption, not a derivation (and a wholly different assumption from the one in the Exhibit 7.6 left hand chart we showed earlier in this Omicron subject segment). These connectors therefore, are basically viral fiction.
Now, if we add this 6.1 years of mutation clock time to evolve an Omicron variant directly from Alpha 20B (Sep 2021, or even 3 Feb 2020) as the Nextstrain/GSAID chart on the left in Exhibit 7.8 suggests, we get Oct 2027 (or Mar 2026) as a timeframe for Omicron’s arrival. This obviously did not happen – so Omicron did not originate from Alpha 20B itself, nor the wild variant, nor Delta, but rather a prior LCA with Alpha 20B. Therefore, conversely we must parse these same 6.1 years from the arrival date of Omicron (Nov 2021) through to the detection date of Alpha 20B (3 Feb 2020) in order to find the actual date of the LCA with Omicron and Alpha.
By the 2 variable/2 sentence reduction shown on the right hand side of Exhibit 7.8 we are able to solve for an estimated emergence date for this last common ancestor of January 2018. Exactly the date we have estimated for the lab leak in China.
To frame this in a simpler perspective – the average maximum clade divergence from Clade 19A (26 Dec 2019), wild variant, on the GSAID chart is 46 nucleotides (1 sigma = 6.2).33 The below mathematical approach is not entirely valid because successive mutations are merely synonymous substitutions, and do not usually include anywhere near Omicron’s 29% portion of INDELs. Nonetheless, let’s benchmark Omicron against the other clades on Exhibit 7.9 below.
Benchmarking off this relative measure serves to place the latest Omicron variant (93 mutations on 2 Dec 2021) as originating from an LCA at 93/46 x 23 months = 47 months – or Jan 2018 in origin. A clean match.
If evolutionary pressure during the last year had served to accelerate this variant into being (or even cause its 12-mutation spread observed over a mere 8 days), then it should have borne the nucleotide base of any variant on the above chart (Exhibit 7.9) which has existed since Clade 19A. As one can observe in Exhibits 7.6 and 7.9 above, Omicron did not bear such a genetic legacy from any existing clade – merely the ‘N501Y association’ with Alpha. However, this mere single nucleotide linkage with Alpha is not enough solid evidence, so we undertook a more sophisticated approach to viral adjacency next.
We developed a 144 nucleotide by nucleotide alike-proximity analysis of four important variant benchmarks in SARS-CoV-2 history:
B.1 (Wuhan, 12/24/2019),
B.1.1.7 (Alpha, 2/3/2020),
B.1.617.2 (Delta, 10/08/2020, and
B.1.1.529 (Omicron, 11/24/2021).
The worksheet which outlines this analysis can be accessed by clicking here. The source for the nucleotide data was Covid CG – Covid Genetics: Lineage Reports by Nucleotide.34 If we take the frequency of common mutations shared between these four variant benchmarks, and assign a value of 1 to each, then we end up with a value for each of the variety of relative strengths in relationship between the four variants (see ‘Omicron Allele Continuity’ chart in Exhibit 7.10 below). If those strengths are then shown as vectors on a spanning tree diagram (see upper right of Exhibit 7.10), they can be optimized into a single configuration of nodes (optimized spanning tree). If we then remove redundant but weaker relationship vectors we end up with a relationship spine, as shown on the lower right of Exhibit 7.10.
This effort produces a diagram which allows us to observe that Omicron not only is nowhere near related to Alpha and Delta, but bears a remarkable similarity strength to the original Wuhan strain.
The important thing to understand here is that the only way one can assemble this optimized spanning tree is by assuming the ancestor of Omicron to have existed prior to the B.1 Wuhan strain – separated by an amount of time near double that between Wuhan and either Alpha or Delta.
The dynamics of virus outbreaks are not well understood. Viruses have been observed to flourish, go dormant, and then re-emerge with relatively little genetic clock progression between the two outbreaks despite being separated in time by 5 years or more.35 Thus, objection to this theory based upon the idea that Omicron was ‘too human adapted and similar to the human adaptations of Alpha/Delta variants to be this old’, does not hold scientific water. Again, a highly ‘if’-dependent effort to stuff 10 pounds of evolution into a 2 pound bag of recency.
Thus, by means of this highly divergent novel-base Omicron genome, we find agreement with our early 2018 lab leak estimate and as well provide a fourth means of falsifying China’s Dec 2019 narrative.
8. Do the progression timelines of the wild (B.1) and Delta (B.1.617.2) variants of SARS-Cov-2 agree in their implications? Answer: No.
China’s CCP lied about the speed at which SARS-CoV-2 B.1 spread globally. This variant of the virus not only did not spread globally in a mere two to three months, but moreover when indexed against the well-measured rate of spread for the Delta variant, indicates a probable index case and inception in China of around mid-to-late 2018, or into 2019 at the latest (if we pretend that the Delta variant is not really more transmissible). The relative transmission rate for Delta is sourced from 26 Aug 2021 CDC advisory on Delta variant. Some sources contend that Delta’s transmission rate, relative to the wild virus, is even higher than 2.5 : 1.36 However for conservancy, we use the CDC comparative in Exhibit 8.1 below, which is damning enough as it is.
9. Did the CCP bear the capacity and opportunity to release, and imminent risk of releasing Covid in 2018/19? Answer: Yes.
Before they were aware that their emails would become critical evidence, members of Anthony Fauci’s team expressed the opinion that SARS-CoV-2 genetics were inconsistent with a virus of zoonotic origin. They believed that it was the product of a gain-of-function lab – but both a lab and a genomic signature about which they had no specific knowledge.
Note the dates of these alerts issued by U.S. Embassy officials (Exhibits 9.2 and 9.3), January 19th 2018. Our estimated release date of SARS-CoV-2 was around March 2018, two months after this warning was issued: “but [the Wuhan BSL-4 lab’s] current productivity is limited by a shortage of the highly trained technicians and investigators required to safely operate a BSL-4 laboratory and a lack of clarity in related Chinese government policies and guidelines.”
Finally, based upon the commissioning and operating schedule of China’s 5 top BSL-level operations, there existed ample opportunity for this novel pathogen, featuring a genetically manipulated furin cleavage site, to have escaped from poorly security-administered labs in both 2018 and 2019 (or even 2017 during the U.S. ‘pause’ in gain-of-function research).
10. Did other nations besides China bear this capacity, opportunity, and imminent risk of Covid release? Answer: No.
The Obama Administration had placed a pause on the very gain-of-function research which would have been required to produce SARS-CoV-2, from 17 October 2014 until 19 December 2017 (timeframe is referenced from Exhibit 10.2 below). Given that the United States and China were the only principal nations involved in this research, this leaves China as the only researching body which could have conducted the gain-of-function development necessary for am early 2018 release of the SARS-CoV2 virus.
In fact, in 2016/17 and during the ‘pause’ in gain-of-function research in the U.S., the National Institutes of Health funded and conducted this very gain-of-function research on bat coronaviruses – in and only in – China (see Exhibits 10.2 and 10.3).
11. Were there indicators of potential virus social impact and disruption in China during the ‘unknown pathogen years’ experienced by its contiguous nations? Answer: Yes.
As one may observe in the four-panel chart shown in Exhibit 11.1 below, the critical China keyword searches (per Google Trends) associated with the pandemic, other than ‘coronavirus’, ‘SARS’, Covid-19, etc. do not concentrate in January and February of 2020. Keyword popularity for ‘cold (illness)’, ‘medicine’, ‘lung-cough’, and ‘hospital’ all concentrate during the March 2018 – August 2019 period – right in the same timeframe when influenza took a ‘zero-case pause’ in China and mysteriously did a Covid-style disappearing act (see Exhibit 6.10 above). The search hit arrival chart for the term ‘hospital’ on the bottom right is particularly intriguing in that the March 2018 period dwarfs the January 2020 Covid-19 panic period in Wuhan. Very curious. In fact, this keyword group’s search intensity rivals the volume for the same word searches for the Jan-Feb 2020 period, when one would expect such keywords to register with high hits.
Now focusing back upon Wuhan in particular: “…in late June and early July of 2019 the residents of Wuhan began to fill the streets, angry that officials responsible for the health and prosperity of the city’s 11 million people had betrayed them. They were sick, and feared getting sicker. The elderly gasped for breath. There was fear that the ill had suffered permanent damage to their immune and nervous systems.“
China proper experienced an alarmingly robust 2019 flu season as well. Remember that the vast (99%+) majority of these flu cases were guesses as to the actual virus involved.
Of key significance is the extraordinary set of 45-year exceptions in CO2 emissions produced out of China during the June 2018 through March 2020 timeframes. The dotted red line in Exhibit 11.4 below depicts 2018 CO2 ppms measured at Mauna Loa observatory, while the solid red line shows 2019. Parts per million measures during those two years were anywhere from 2 to 6 standard deviations (sigmas) lower than their 45-year well-established precedent. This was an extraordinary set of occurrences which dovetailed nicely into being explained by Chinese lockdown, once December 2019 arrived. The key inference here is that the prior suppressed periods, could only be explained by Chinese lockdown (regional) as well. A brushfire-approach lockdown practice which began in earnest in May of 2018.
In addition, notice that as soon as China ceased its lockdown of just Hubei province on 8 April 2020, the world immediately experienced a 45-year record in CO2 ppm spring increase (grey ‘2020’ line on the left hand side of Exhibit 11.4 below). Because 47% of the West was locked-down at this time, this demonstrated clearly that it is China, and not Western nations, which impart the most significant impact in terms of CO2 production globally. Sorry Greta.
Finally, the reader should note that I am not talking about China enacting a comprehensive lockdown of its entire nation and economy in this context – rather just small regions where a Covid outbreak was known to exist (potentially or even likely known on the part of very few persons). The actions could be excused through a cover-story regarding influenza quarantines (2018/19 flu season was 6x heavier as we observed in Exhibit 11.3), African Swine Fever and H5N1 bird flu mitigation efforts, 2019 flood alerts, or a variety of other exculpatory rationale.
When China locked-down only Hubei province on 23 January 2020 for example (4% of population) – this drove the largest CO2 reduction on the entire chart depicted below. Thus China did not have to undertake drastic nationwide measures in order to effect these smaller-variance 2018 (tomato) and 2019 (red) charted CO2 ppm trend lines. Regardless, China’s CCP contention that they did not know about Covid-19 until late December 2019 is belied by the chart below. So we know they were lying – now we are only negotiating how much.
The red trend line ppm suppression impetus in July 2019 (or 2018 for that matter) did not just coincidentally give way to a convenient, exactly-timed, and same-magnitude Covid lockdown suppression tend line in December 2019. Such a suggestion broaches incredulity. No, this entire ppm suppression all stemmed from one single factor. This is also the parsimonious explanation for what we observe in Exhibit 11.4 below.
Meanwhile Japan, as we noted earlier in Exhibit 6.9, struggled with the same set of ‘severe flu season’ issues in terms of excess deaths, curiously evolving at the same time as Australia’s record illness peak, and commensurate with China’s CO2 production shutdowns (‘sigmas’ extracted from Exhibit 11.4).
Many observers as well noted increased traffic patterns at Chinese hospitals in mid 2019, accompanied by decreased mobility measures on the part of Chinese cell phone users. Of course, we now know that the pandemic did not begin in China ‘in August’ as the article below cites – however, that was the peak of actual virus circulation and lockdown activity on the part of the CCP (see Exhibit 11.2). So this makes sense relative to our argument.
12. Was this social response/carbon reduction reaction due to African Swine Fever or Trump Trade Tariffs? Answer: No.
The 2018 African Swine Fever resulted in a single-year hit to China’s GDP of 0.78%.37 Despite this large of a hit to GDP, when we contrast the CO2 reduction sigmas seen in Exhibit 11.4 and 11.5 above with the progression of African Swine Fever,38 we are able to falsify the notion that ASF served to produce the 45-year exception reductions in carbon emissions on the part of China.
As well, Trump Administration tariffs approached nowhere near a 0.78% impact upon Chinese GDP. In fact 2019 was a record year for China in terms of global containerized shipping, with the greatest fluctuation in export volume being attributable to China’s annual celebration of the Lunar New Year.39 A normal condition which has existed for all 45 years analyzed in Exhibit 11.4 above. In fact, the Brookings Institute, in their Election Policy 2020 Report, identified that China-US supply chain entities simply paid the additional tariffs and went on about conducting business order cycles as usual – resulting in a rise in costs to American consumers and not an appreciable drop in traded unit volumes nor harm to China’s economy.40
As a note before we move on, if anything, it is more likely that the African Swine Fever, various chicken pathogens, and human ‘influenza’ to which the CCP responded during this timeframe, also served as a diversion away from their activity in attempting to mitigate and understand a nascent viral (later named SARS-CoV-2) challenge.
13. Did the world exhibit blood antibody serum, CLI outbreak, or Covid-19 mRNA profiles which matched an exposure to Covid-19 prior to Oct 2019? Answer: Yes.
Sewage sampling and blood testing for serum antibodies even in Western nations such as Italy, France, and Barcelona, Spain, consistently showed mRNA or antibodies to Covid-19 which were generated as far back as January 2019. Given that it takes 10 months (Exhibit 2.2) for Covid to spread across the globe, this places a likely inception (true index case) in China, around March – June 2018.
To corroborate the Barcelona March 2019 mRNA detection (Exhibit 13.3) we note high excess death observations in Spain (Exhibits 6.4 and 6.5) – which place Covid in China around the Feb – May 2019 inception period. Both Barcelona, Spain as well as Lombardy, Italy are heavy Chinese citizen travel destinations. Accordingly, the Spain 4%, 11%, and 18% excess death data matches the 8%, 12%, and 26% excess death rates we observed in the over 85 cohort in Italy for 2018, 2019, and 2020 respectively (Exhibit 6.5). Something less virulent, but nonetheless still deadly swept through these first European regions to be hit with Covid up to a year before their supposed March 2020 outbreaks. These benchmarks corroborate the genetic analyses in Exhibits 7.4 and 7.5 well.
The U.S. blood donation antibody tests in particular demonstrated IgG antibodies in the population which were generated as far back as March 2019 in the United States alone (see Exhibit 13.2 below). In the chart immediately below (Exhibit 13.1), one can find all the studies cited inside this Question summarized onto one graphic. Each cited study then follows inside a set of actual study first page or critical images shown as Exhibits 13.2 through 13.12.
The chart below (Exhibit 13.1) falsifies the notion that SARS-CoV-2 appeared in China in December, or even October, 2019. It was present (in likely a less virulent or even precursor form) much earlier than those dates allow. Desperate attempts at debunking these detection points are underway, as they serve to falsify China’s CCP fairy tale – be cautious of such plausible deniability debunking efforts, and furthermore watch for the exercise of ‘outference’ (a method of pseudo-skepticism) as defined in Question #17 at the end of this article.
U.S. Blood Donation IgG Antibody study – March 2019
Barcelona Wastewater study Covid-19 mRNA – March 2019.
Please note that this study did not find just one detect, but two and from the same sample on the RdRp gene, primers IP2 and IP4 at 39 C(t). This was very unlikely to be a false positive given that there were two hits not just one, and furthermore RdRp primers are selected specifically to avoid cross-reactivity with the six other human-circulation coronavirus members (229E, OC43, SARS-CoV, NL63, HKU1, and MERS-CoV).41 While it is possible the detection was the result of contamination or sample mix-up, given the array of samples conducted with no contamination/mix-up false positives, this was also very unlikely. These plausible deniability spins constitute nothing more than simply a version of nulla infantis or ‘nuh-uh’ argument.
Therefore, one cannot just declare either of these as the conclusion nor even likely or implied conclusion. However, in a subsequent release the authors chose to leave the observation mute, because it was being exploited by China’s CCP as evidence that SARS-CoV-2 did not originate in China.42 The detection was not refuted, recanted, nor retracted – rather just left as an isolated observation. Fact-checkers agree with this neutral assessment.43 No effort has been made to confirm these results – so we have a case again, of Nelsonian inference being exploited to increase ignorance and imply ‘finished science’. Theories which get stronger as ignorance increases, are not theories at all. Do not trust people who make debunking claims based upon this common circumstance in scientific study.
Brazil Wastewater Study – November 2019
Oropharyngeal Swab Study from Milan, Italy – December 2019
Lung Cancer Blood Serum Antibodies in Pre-pandemic IgG Antibody Italy study – February 2019
India demonstrated a serum antibody rate of 60% in June 2021, despite only documenting Covid in a mere 2.1% of the population up to that time. Comparatively, it took the United States a full 18 months of exposure, just to get to a 38% seroprevalence. By deduction, India would have to have been exposed to a precursor of Covid, or Covid itself, a full 18 months prior to January 2020 – July 2018.
IgG Constances Cohort Antibody study from France – March 2019
VA Respiratory Illness Virginia Dept of Health – July 2019
Illinois Lung Injury Syndrome – April 2019
Wisconsin Pediatric Hospital Respiratory & Gastrointestinal Distress Syndrome Pneumonia with Glass Opacities – July 2019
SARS Antibodies in 50% of Population – National University of Singapore study – April 2020
14. Did China’s CCP attempt to conceal its gain-of-function activities, early case data, and genome libraries from the 2014 – 2019 period? Answer: Yes.
China’s CCP requested that 200 coronavirus samples submitted to the U.S. National Institutes of Health (NIH) be deleted in June of 2019. As it turned out, these sequences suggested that the virus was circulating in Wuhan earlier than previously thought, and could perhaps point toward answers on the origins of Sars-CoV-2 – answers that could not only help end this pandemic but prevent the next one. China’s CCP regarded its Party interests as being more important than global health however.
The Party Rule #3: There are no interests more important than the interests of The Party.
As well, China refused to submit samples from the first 174 cases of SARS-CoV-2 which it detected. These inception cases are critical in determining how diverse Covid mutation had been by the index case detection date. This would allow investigators to both affix an estimated actual inception date to the virus in China, and as well establish a likelihood of its inception being confined only to Wuhan. Thus, we must presume that by withholding these samples, China’s CCP is concealing data which could serve to falsify their narrative. This forces the earlier (before Oct 2019) outbreak hypothesis (the one favored by the House Minority Intelligence Committee, see Question #17) into becoming the null hypothesis. One must prove that Covid-19 miracle-mutated and appeared in Oct/Dec 2019, not simply assume it and then look for the evidence later.
15. Did China’s CCP appear to fudge its case and fatality measures regarding Covid, thereby obfuscating data indicating a much longer period of Covid exposure nationally? Answer: Yes.
Given that we know that lockdowns were not effective in quelling SARS-CoV-2 (Questions #1 through #6), we can infer that China’s report of cases (cited in green in Exhibit 15.1 below), were both mitigated by prior immunity, and as well were fabricated even given this reality. The sole purpose of this under-reporting was to ensure that the Chinese Communist Party did not appear weak before the international community. Targeted lockdowns had failed in China for 2 years, however now that the nation was seeing herd resistance at play, the CCP decided to exploit this natural phenomenon to make itself appear superior to the world. We observe here that the CCP’s intransigence with regard to its transparency is not merely motivated by a desire to not be mocked; but moreover, a desire to appear racially superior to their lesser-human planetary co-inhabitants. A formula we observed plied in the years immediately prior to World War II. A sentinel warning about what may also lie ahead for the world.
The Party Rule #4: Every decision on the part of The Party is both brilliant and correct.
Furthermore, in a display of how fudged the Chinese numbers were, the reduced case reporting shown in Exhibit 15.1 above served to artificially decrease the denominator in China’s advertised case fatality ratios (CFR’s) shown in Exhibit 15.2 below. As a result, China’s CCP gave the world a false depiction of Covid’s fatality rate at 4.15% (see the green trend y-axis intercept in Exhibit 15.2), sending most nations into overreaction. Not only was Covid ‘not like the flu’, apparently it was like Ebola. Accordingly, instead of preparing medical resources and treatment capabilities, panicked nations elected to pursue harmful lockdowns, feckless ‘zero-Covid’ impossibilities, and a slew of rushed vaccines. Flawed national policies were hastily enacted under this erroneous level of coerced panic and malicious actors exploited this in order to alter election laws towards The Party’s favor.
Patients were wrongly instructed by their doctors that ‘there is no treatment, go home and sleep it off’, and as a result large numbers of people died of easily treatable pneumonia, sepsis, and blood clots in their homes.4445
Many people died from the ensuing shortfall in understanding, that Covid-19 did require treatment which was critical in avoiding death from secondary effects (warfarin, budesonide, doxycyline, apixaban, prednisone, etc.), as well as successful therapies for Covid-19 itself (ivermectin, monoclonal antibodies, hydroxycytidine, zinc, quercitin, vitamin D, etc.).
The Party Rule #5: Every action on the part of The Party is virtuous.
16. Did China’s CCP sabotage efforts to investigate SARS-CoV-2 and impose an obfuscating veil of intimidation around its origins and timing? Answer: Yes.
China falsely portrayed willingness to continue further investigation into the origins of SARS-CoV-2. But the reality was that this was under the condition that ‘lab leak’ was not one of the options under consideration to investigate. China delayed and terminated critical investigations, secured veto rights over critical participants, and clumsily tried to affix blame for SARS-CoV-2 upon other nations – especially the United States.
“It is beyond doubt that the CCP actively engaged in a cover-up designed to obfuscate data, hide relevant public health information, and suppress doctors and journalists who attempted to warn the world. They deliberately, and repeatedly, disregarded their obligations under the 2005 IHR. …As more countries have begun to question the CCP’s official accounting of the early stages of the pandemic and call for an international investigation, the PRC has used economic manipulation and trade coercion to demand silence.”
China’s shutdown of travel within Wuhan, but abject allowance for travel from there to other nations, implies culpability on its part. It was only after US President Donald Trump petitioned directly to him on March 27th 2020, that Chinese President Xi Jinping finally agreed to curb international flights from Wuhan and China. Three months too late, and after a massive propaganda campaign on China’s part to dissuade nations from adopting travel clampdowns, only then did China finally call an end to this method of polluting the Covid-origins pool.47
Finally, how did China know to procure/equip/deploy trucks to spray atomized alcohol or bleach solutions into the atmosphere of the Wuhan streets in order to combat the virus, a mere four weeks after its very detection?48 Studies on the virus’ bacteriophage phases, fecal/wet protein aerosol transmission, and CAPE(S) associations were not conducted until months after pictures such as the one on the right were taken of Chinese mitigation efforts. Most track-and-trace minded global nations were puzzled by the apparent overkill in approach. But as we in the West gathered 15 intense months worth of knowledge about SARS-CoV-19, it became clear that the People’s Republic of China government held an intelligence base concerning SARS-CoV-2 in December 2019 that they did not offer up to the international community. Nor could they, as it would only serve to betray the charade. Their pandemic was in its third year and final phase – immunity was widespread. The rest of the world was fucked, and it was not the CCP’s problem.
As we noted in Question #2 above, this relatively advanced early knowledge regarding SARS-CoV-2 on the part of the CCP, and their adept grasp of exactly what was needed in order to obfuscate origin issues, is called Nelsonian Knowledge. It betrays a deep a priori experiential knowledge of Covid-19 and its particulars on the part of China’s CCP – a knowledge they should not have possessed, if indeed this was a 27 Dec 2019 ‘novel pneumonia’.
The notion that SARS-CoV-2 originated from a gigantic genetic/furin cleavage zoonotic jump event in a seafood wet market in December 2019, and then underwent 18 months of variant mutations and spread to 95% of global nations in the next 70 days, and that the Chinese just withhold critical information because that is just what Chinese do, it’s their thing – is not only racist, but scientifically gullible.
The Party Rule #6: The narrative is the truth.
17. Did various nation’s/intelligence agencies agree with the above assessment on the part of The Ethical Skeptic? Answer: Yes (mostly), and No.
Of course we reviewed the assessment by the House Foreign Affairs Committee Minority Staff Report of 21 Sep 2021 in Question #16 above. They cite an obvious campaign of coverup and intimidation on the part of the CCP. However, let’s continue on with reports from the intelligence community itself. Two reports in particular came out in August and October of 2021. Their conclusions are outlined below.
“It is the opinion of Committee Minority Staff, based on the preponderance of available information; the documented efforts to obfuscate, hide, and destroy evidence; and the lack of physical evidence to the contrary; that SARS-CoV-2 was accidentally released from a Wuhan Institute of Virology laboratory sometime prior to September 12, 2019. [Note that the HICMS does not agree with the Easter Egg (a planted discovery waiting to be found) ‘October Surprise’ theory.]
The virus …was likely collected in the identified cave in Yunnan Province, PRC, sometime between 2012 and 2015. Its release was due to poor lab safety standards and practices, exacerbated by dangerous gain-of-function research being conducted at inadequate biosafety levels…”
~ House Intelligence Committee Minority Staff Report, August 2021
However the Office of the Director of National Intelligence shied away from taking the recommendation of the House Committee in its unclassified Update Assessment of October 2021. Its constituents officially ‘remained divided’ (politics?) on the issue of lab versus zoonotic origin, and did not hold enough real information to conjecture further.49
Outference – a critical (not rhetorical) argument which bases its inference or conclusions upon cultivated ignorance and the resulting lack of information, rather than the presence of sound information. More than simply an appeal to ignorance, this ‘lack’ of information is specifically engineered to produce specious conclusion in the first place. This type of argument gets stronger and stronger the less and less critical information one holds. This is a warning flag of agenda or political shenanigans at play.
Keep that critical definition in mind when reviewing the following ODNI Update Assessment summary:
“The IC assesses that SARS-CoV-2, the virus that causes COVID-19, probably emerged and infected humans through an initial small-scale exposure that occurred no later than November 2019 with the first known cluster of COVID-19 cases arising in Wuhan, China in December 2019.”
Agrees with our assessment but really means nothing. Is a ‘the sky is some color between red and violet’ statement.
“Most agencies also assess with low confidence that SARS-CoV-2 probably was not genetically engineered; however, two agencies believe there was not sufficient evidence to make an assessment either way.”
Neutral. Disagrees with our assessment at face value, but is a rhetorical argument and implies nothing of a critical path nature. Merely symbolic.
“Finally, the IC assesses China’s officials did not have foreknowledge of the virus before the initial outbreak of COVID-19 emerged.”
Disagrees with our conclusion, but bases this inference on a lack of, rather than a presence of information. A lack of information specifically engineered by China’s CCP.
“After examining all available intelligence reporting and other information, though, the IC remains divided on the most likely origin of COVID-19. All agencies assess that two hypotheses are plausible: natural exposure to an infected animal and a laboratory-associated incident.”
Neutral and implies nothing.
“One IC element assesses with ‘moderate confidence’ that the first human infection with SARS-CoV-2 most likely was the result of a laboratory-associated incident, probably involving experimentation, animal handling, or sampling by the Wuhan Institute of Virology.”
Agrees with our assessment but offers no evidence nor critical argument.
“The IC—and the global scientific community—lacks clinical samples or a complete understanding of epidemiological data from the earliest COVID-19 cases. If we obtain information on the earliest cases that identified a location of interest or occupational exposure, it may alter our evaluation of hypotheses.”
Neutral – essentially saying that they do not really know much.
China’s cooperation most likely would be needed to reach a conclusive assessment of the origins of COVID-19. Beijing, however, continues to hinder the global investigation, resist sharing information, and blame other countries, including the United States.
Agrees. The strongest critical argument of the report.
One cannot contend a conclusion nor a confidence level on that conclusion, and thereafter cite that they are not getting the data they need in order to make a conclusion in the first place. Such cultivated ignorance and the theories which result from its outference, merely serve as political-fear narratives protecting their issuers from The Party’s compliance patrols.
The mistakes outlined above, along with the conjecture as to who bears responsibility for them, therefore do not constitute a conspiracy theory. They were enacted on the part of a Chinese Communist Party which wholly underestimated the level of program rigor and operational discipline required to manage and control a potential bio-weapon. They further then mistakenly launched this weapon upon a planet-load of innocent civilians. Finally, like any mafia they followed up their crime with an utter disregard for ethics, humanity, and any semblance of accountability.
The Party Rule #7: In the end, only The Party is of any importance.
If China’s CCP is willing to conduct this level of surreptitious harm to the rest of the world over a matter of a virus escape, then what will The Party be willing to do to the rest of the world when they are really upset? The Chinese Communist Party owes the international community recompense for the massive levels of death, economic disruption, and suffering of our loved ones.
The Ethical Skeptic, “China’s CCP Concealed SARS-CoV-2 Presence in China as Far Back as March 2018”; The Ethical Skeptic, WordPress, 15 Nov 2021 (Rev 1.2, 2 Dec 2021); Web, https://theethicalskeptic.com/?p=54800
Exhibiting a disciplined and sound set of ethics during argument is a key indicator of high intelligence. Argument is a spiritual endeavor after all. There are twelve steps to sobering one’s self from the addiction of always appearing to be right. Key attributes of discussion that serve to earmark a quest for actual knowledge, as opposed to the loosh of utterly destroying an opponent.
Given that we outlined the Art of Pseudo-Argument in our last article, I thought it would be appropriate to outlay those elements of discourse which I believe provide for the most effective form of arguing. Several of my loyal Twitter followers even broached this very question. Therefore, bear in mind that this article outlines the traits of effective or dialectic arguing and not necessarily the structure of a sound argument.1 Those are two different things. These features of sound arguing serve to underpin the goal of ascertaining knowledge, or communicating the past and future critical path of research, if not knowledge itself.
You may notice that these twelve elements do not pertain to the intoxicating rush of a Schopenhauer-esque need to always be found right. Nor do they pertain to the Hegelian notion of arriving at the truth by stating a thesis, developing a contradictory antithesis, and combining and resolving them into a coherent synthesis. These notions developed by Schopenhauer and Hegel constitute Pollyanna views of the readiness of most domains of inquiry to support and vet a claim to resolution in the first place. The context for our argument herein regards subjects which are murky in comparison, and for various reasons (most often obfuscation or our not knowing what we do not know) have, other than from a simpleton’s perspective, eluded true consensus.
Thus, without further ado, ladies and gentlemen, The Ethical Skeptic’s Fabric of Sound Argument.
I. Articulate your opponent’s actual position, even if they are not skilled at doing so
The first priority during an argument’s inception is to understand your opponent’s position. The reason why this is necessary as a first step, is that this allows you to detect the situation where the arguer’s sole point is ‘You are an idiot’ (coercive religious argument camouflaged in extensive rhetoric). Such is not really an argument at all, and finding out that this shallow depth of thought, constitutes the sole objective or cache the arguer has to offer, saves one from a complete waste of time.
Avoid inflammatory buzzwords (pseudoscience, anti-______, woo, believer, etc.) to describe your opponent’s position. This is a large warning flag that there is not much going on inside you intellectually. As with all warning flags of this nature, you are typically the last one to realize it.
One may employ a steel man tactic here, provided it is not conducted in an insulting manner. A steel man argument is simply one in which you help you opponent articulate their position in a clearer manner, or at the very least, a manner which will bear utility in the putative upcoming discussion. Exploiting your opponent’s inability to articulate a point, in order to embarrass them, is not a valid method of improving knowledge nor alleviating suffering.
Nothing in life is to be feared. It is only to be understood.
~ Marie Curie
II. Resist the temptation to imbibe in the loosh of embarrassing or insulting an honest opponent
If your opponent is sincerely in the business of probing truth, don’t seek a goal of destroying them by means of your accrued wisdom and skill in argument, simply because they may disagree. In contrast, loosh is an addictive spiritual intoxicant derived from the instance wherein one enjoys causing the suffering of a higher order being, especially one of an unblemished, young, virginal, or innocent nature. Although an example in the extreme, a serial killer is a being who has fully succumbed to the addictive nature of loosh. They draw power from imparting terror in and the specter of death upon their victims. For most other people however, observing mere discomfort through social embarrassment (epicaricacy) or harm to an opponent’s career will suffice. You can detect them by the focus of their argument. Is it truth, or is it you? Despite constituting a mild form thereof, one who seeks knowledge earnestly, falls into a category of innocence.
‘Turning the other cheek’ is not simply a beattitude mandating niceness to others. Rather it is the signature spiritual rejection of loosh, both as a currency expended in lieu of faith, and as a passport indicating citizenship inside a vast dark Kingdom fueled by its addiction.
If you catch the scent of loosh on your opponent’s breath, block them and move on.Where one is corrupt in their skepticism, there also they will be corrupt in their heart.
~ The Ethical Skeptic
This does not mean you need to be nice to everyone, but it does mandate discernment. If a person researches dishonestly, argues dishonestly, or seeks harm, these are all really manifestations of the same thing. No matter what act they may put on. Let them know this and depart the argument. One is either seeking knowledge or hungering for loosh as a self-priority, and there is not much in the way of overlap between the two. Detecting a person motivated by the latter (and even deceiving themselves in this regard) is a fairly easy task for an ethical skeptic. Degrees, credentials, authority, humor – these things do not confer immunity from this mandate. Everyone gets frustrated at times, but we all will eventually revert back to that which constitutes our essential nature. Don’t hide your allegiance to Antifa or hate for your fellow citizen, your character will still be betrayed (along with its dishonest veneer) through your habits of argument.
Make a habit of two things, to help; or at least to do no harm.
III. Clarify the semantics – neutralize ambiguity, amphibology, and equivocation
One should try and set forth a Wittgenstein level grounding of what specific terms and phrases mean. Always leave little room for undefined concepts, dual interpretations (amphibology), or equivocation. For instance, terms/phrases such as ‘proof’, ‘rationality’, ‘credulity’, ‘the evidence’, ‘hypothesis’, or ‘bias’ connote different things at differing points or situations inside scientific deliberation. A charlatan will exploit the large footprint of such terms to self-aggrandize and place unreasonable epistemic demands upon their opponent. Moreover, the use of terms as weapons essentially guarantees that the conversant has no desire to learn anything. If you encounter this, end the discussion immediately and let the other party retreat back into their hole.
Above all, don’t employ ‘Occam’s Razor‘. If you don’t know why, you probably should not be undertaking an argument to begin with.
Philosophy is a battle against the bewitchment of our intelligence by means of language.
~ Ludwig Wittgenstein
IV. Understand that evidence is a domain and not merely a set
Evidence is rarely constrained only to the set of things which the conversants personally know, nor really even to the set of all things observed by science or humanity. Evidence is a domain which man rarely penetrates very far, if at all. It is not a set, outside of which a convenient appeal to ignorance can be leveraged. Ask your opponent how much of the observable domain as been indeed detected and measured by science to date. Odds are that this is both a paltry amount, and as well consists mostly of linear inductive guessing. If the critical path question at hand is ‘Why does the ocean horizon appear to be curved?’, well then we are 99.9999% through that evidence domain. Unfortunately, most areas of human deliberation are not this well researched and vetted. If a topic’s evidence domain has been about 1% researched, and all inference is merely suggestive – then no claim based upon ‘the evidence’ can be made by either party. Make this clear in your deliberation. Do not allow premature inference and fanaticism to rule the day.
A person’s vehemence in opinion is inversely proportional to that which is actually known about the domain in question.
~ The Ethical Skeptic
V. Avoid ‘is likely’ and ‘could plausibly be’ positions in favor of epoché (silent neutrality)
Always favor the dispassionate and quiet neutrality of epoché over hasty linear inductive inference. The second Gulf War in Iraq was driven by linear inductive arguments as to weapons of mass destruction being secretly developed by Saddam Hussein. Rumor, individual speculation, circumstantial evidence, machined parts dug up in yards, oddly designed factories, along with a pinch of confirmation bias – all combined into a recipe for inferring an invalid conclusion that specific weapons were being made.
Induction is that form of inference panned by philosopher Karl Popper in his work, The Problem of Induction; and while being somewhat in backtrack today, induction remains a problematic means of inferring a final conclusion. In contrast with deduction, induction is a method of explaining as much as it is one of describing. The difficulty resides in that most of our contentious issues of science, have been researched by inductive and not deductive means. One can pretty much ‘prove’ anything within reason by means of linear induction. Be cautious as to how far induction (‘likely is’ conjecture used in lieu of actual science) can be used to drive home a preferred conclusion.
Whereof one cannot speak, thereof one must be silent. Only describe, don’t explain.
~ Ludwig Wittgenstein, Tractatus Logico-Philosophicus
Even worse than linear inductive inference, is inference from a standpoint of plausible deniability. One can fabricate an entire cosmology and religion from the inverse negation of plausible deniability. If your opponent decides that he or she can armchair debunk an entire panorama of ideas by merely dreaming up a plausible means as to why each is invalid (panduction), you are not really dealing with the sharpest tool in the drawer. Plausible deniability is just one step removed from divine revelation. Depart the discussion immediately, as persons who conduct this type of fanciful conjecture are merely wasting your time with an exercise in self-aggrandizement.
The important thing is that we maintain plausible deniability.
~ Richard M. Nixon
VI. Favor deductive, consilient and falsifying evidence over linear inductive suggestion
This is the only time during a discussion where logical consequence, proof theory, and model theory (e.g. ‘ if p => then q‘, quod erat demonstrandum, logical versus semantic truth, p-values, etc.) can come into play. Beware of those who use this structured approach to argument outside the context of deduction and falsification. They are conducting sophistry. Such fake deliberation is depicted in the graphic to the right, in the forms of panduction, abduction, and cleverly leveraged linear induction. It goes without saying, that a sound arguer should avoid panduction (and even abduction for the most part), for this is the habituated practice of the debunker.
Deduction is the process of inference which reduces (or deducts from) the set of reasonable possibilities/hypothesis features. Consilience is the property wherein several disparate avenues of investigation all triangulate upon common answer. Finally falsification is the white crow moment, when an entire idea can be released from consideration because it has been conclusively shown to be invalid or no longer salient to the argument at hand (see ‘critical path’, below).
Six friends do I trust, six friends I know true, their names are what, where, and when, how, why, and who.
~ Kipling, Bacon, Jefferson, et. al.
So goes the famous quip attributed loosely to Kipling, Bacon, and/or Jefferson. For me however, of even more importance is the additional rhyme I crafted:
Four inferences of sound ranking will good evidence produce, to falsify, deduct, triangulate, and induce.
~ The Ethical Skeptic
Always examine the strength of inference first, as a priority over ‘drilling-down on the data’. A treasure trove of less-examined wealth often resides therein. One can possess absolutely pristine and reliable data, and be able to infer absolutely nothing from it save for mild suggestion. Such is the more common circumstance in professional deception plaguing today’s social discourse around science.
But the quick inference, the subtle trap, the clever forecast of coming events, the triumphant vindication of bold theories – are these not the pride and the justification of our life’s work?
~ Sherlock Holmes, The Valley of Fear – Arthur Conan Doyle
VII. Constrain the discussion to the critical path of inquiry
A critical path is a concept employed inside systems theory and complex program management. The critical path is the sequence of events or questions upon which the entire outcome of events, or their final conclusions depend. It is the ‘thin red line’ of an avenue of investigation or prosecution of an inquiry. It is the ‘prosecution’ which a legal counsel employs in a court of law. Everything aside from the critical path becomes moot under an objection which is sustained by the presiding court.
The critical path is the sequence of questions which must be answered (as opposed to ‘would be nice if we could answer’), and answered in the correct order, as the means to arrive at a sound conclusion. Watch quietly for persons, organizations, or scientists who meticulously avoid ‘must be answered’ questions or observations (methodical deescalation). They are not honest, no matter how much ‘science’ they may appear to do. In theory, every other question or issue which does not reside upon the critical path is either rhetorical, ignoratio elenchi, red herring, out of correct sequence, or irrelevant.
Keep your focus on this ‘shining pathway of success’ as I like to call it with my strategy clients, and eventually you will be able to spot the time-wasters and pretenders at play – regardless of their credentials and purported authority. You will also become a better presenter and casual conversant.
The best way to succeed is to have a specific Intent, a clear Vision, a plan of Action, and the ability to maintain Clarity. Those are the Four Pillars of Success.
~ Steve Maraboli, Life, the Truth, and Being Free
VIII. Avoid appealing to the popularity of an idea or employing social pressure in order to persuade
An appeal to popularity, or ‘what scientists think’, or an attempt to imply that your opponent is socially unsophisticated because they do not appear to know what everyone else knows, is a weak method of argument. The very ethic and purpose of argument is to shatter widely accepted myth in the first place. Don’t fall back on such a crutch, because not only is the form of argument weak – but it demonstrates your weakness as well. Neither should you allow your opponent to leverage such appeals. Many people never get out of high school emotionally. You harm both your ability to communicate an idea, as well as persuade, through such rhetorical artifice.
An idea that is not dangerous is unworthy of being called an idea at all.
~ Oscar Wilde
IX. Avoid rhetoric, but acknowledge when you do broach it
Rhetoric is ‘an answer looking for its next question’, the special pleading of using any and all available means of pathos persuasion, aside from that which is actually important. For example, citing that a hypothesis will ‘offend a research host nation’ or ‘is racist against an ancient culture’ constitute bogus and desperate attempts to persuade. However, sometimes a rhetorical device is useful in illuminating a side issue in a debate. If you undertake such a process, make it clear that you are citing a special case, per hoc aditum, or presenting a rhetorical argument. This will place a check upon your opponent’s ability to surreptitiously employ rhetoric against you at a later time, as you both will be able to detect its abuse.
You can sway a thousand men by appealing to their prejudices quicker than you can convince one man by logic.
~ Robert A. Heinlein, Revolt in 2100/Methuselah’s Children
X. Acknowledge speculation or when you personally don’t hold the qualifications or answer to something
Acknowledge when you do not bear the qualifications or knowledge level to answer a specific question. As well, make it clear when you are speculating on an outcome, scenario, or answer. This will engender trust in your opponent and encourage them to do the same. If you speculate, acknowledge that your speculation might bear fewer constraints than would reality. Everyone claims to know how the Great Pyramid of Khufu was built, but few have actually built a structure of such scale in their life. Pull out only that inference which is potentially useful, or even set the conjecture aside as lacking utility if needed.
Here we begin frank speculation. And since we are speculating, we’ll use those powerful pseudo-laws, the Principles of Mediocrity and Minimal Assumption.
~ Yanis Varoufakis, Another Now: Dispatches from an Alternative Present
XI. Rarely force argument to a conclusion – rather make it clear when you are resisting a forced conclusion
Unless you possess a strong cache of deductive evidence sufficient to drive home a conclusion, odds are that the reason you are embroiled in an argument to begin with is because someone else is pushing a fatalistic and agenda-based conclusion of their own. Make it clear that you are not enforcing one single answer, but rather opposing the enforcement of an unsound answer upon people who might not know any better. Oppressive voices always contend that there is one equivocal answer which must be adhered to. Need an example for this? – simply watch any official syndicate news outlet or one of their sycophant trolls on Twitter. There is only one answer, and they possess it – guaranteed (see Element #2 above as well).
Don’t employ apothegms such as ‘Occam’s Razor’, ‘Poe’s Law’, or ‘Hanlon’s Razor’ to force a conclusion – as this is the methodology of a pathos-only arguer. You quietly gain no respect through such short-cuts, and often are the last person to perceive this.
If your opponent has the courage to contend that you are attempting to force a contrary position, ask them to steel man your position for you. In such an instance, the odds are very high that they will not be able to do so. Give them points for even trying.
There are no whole truths; all truths are half-truths. It is trying to treat them as whole truths that plays the devil.
~ Alfred North Whitehead
XII. The argument should end with both parties hungering for more research on the matter
Finally, both you and your opponent should bear a renewed hunger to research the issue under deliberation to a further extent. An ethical arguer might even suggest a reconvening of the discussion at another time – in order to deliberate over what you each found in your work.
There is a principle which is a bar against all information, which is proof against all arguments and which cannot fail to keep a man in everlasting ignorance – that principle is contempt prior to investigation.
~ English Philosopher, Herbert Spencer
Do I succeed at employing these elements every time I have a discussion or argument? No, I fall very short most of the time. These are the things to which an ethical skeptic aspires. Faith is the portrait of our life we paint inside the frame of objective reason. One of the purposes of life is to bring unity between what we aspire to have that portrait be, and what life crafts that portrait into becoming (aka integrity). This is a process of learning, hard knocks, along with some successes.
Through using these elements, not only will you find that you have some successes, but you will also find trusted companionship along your journey as well.