Streetwise Professor

May 30, 2021

Intelligent Design vs. The Missing Link (or the Virus Gnomes)

Filed under: CoronaCrisis,Politics — cpirrong @ 5:50 pm

The raging debate over the covid lab leak theory reminds me of the Intelligent Design vs. Evolution debate, with the lab leak theory playing the role of ID and the natural origins theory playing that of Evolution.

There is a huge difference, however. Here we have a strong candidate for the Intelligent Designer: “Bat Woman” Shi Zhengli, and her team at the Wuhan Institute of Virology. Madam Shi has both capability and opportunity. She has a long history of engaging in the genetic engineering of viruses, with the specific goal of increasing and evaluating their virulence in humans (“gain of function research”). As her monicker demonstrates, this includes a specialization in modifying viruses found in bats, which even the evolutionists acknowledge is the original source of covid. There is recent evidence that she had (almost certainly uniquely) access to the raw material (bat viruses from a cave 1000+ miles from her lab) that a modern day Dr. Frankenstein could combine with other genetic material to produce covid.

There are reputable scientists who have recently released a paper claiming that covid-19 was created in a lab. I do not have the expertise to evaluate their claims, but I think it is beyond cavil that Shi had the ability to do what they claim.

Against this we have the evolutionists, who at this stage remind me of the South Park Underpants Gnomes:

  1. Bats.
  2. ????
  3. Covid-19!

Or to use an evolutionary metaphor, they have a huge missing link problem. Despite intense efforts, they have yet to identify the intermediate species between bats deep in a cave and humans in Wuhan. They have hypothesized such a link (or links) and asserted that their hypothesis is truth. This is unscientific. Absence of evidence is not evidence of absence, but unless and until the chain of transmission can be demonstrated, the hypothesis remains only that, and the longer we go without identifying the chain the less likely it is that it ever existed.

In stark contrast, the entire possible causal chain in the lab leak hypothesis is known, and extremely plausible, and there is circumstantial evidence that it indeed operated.

Right now, in my opinion the burden of proof is on the Evolutionists. They have far less evidence on their side than the Intelligent Designers.

I of course use the term “Intelligent Design” sarcastically, but not in the way that you might think (to cast aspersions on the lab leak hypothesis, given the low scientific standing of Intelligent Design Theory). No, the sarcasm relates to what Shi (and other scientists around the world) are designing: these are smart people, but how intelligent is it to create deadly pathogens that can escape into the human population–as even defenders of that research acknowledge is a possibility?

And of course, one of those defenders is none other than Dr. Anthony “The Dervish” Fauci. In 2012 he said thus:

In an unlikely but conceivable turn of events, what if that scientist becomes infected with the virus, which leads to an outbreak and ultimately triggers a pandemic? Many ask reasonable questions: given the possibility of such a scenario – however remote – should the initial experiments have been performed and/or published in the first place, and what were the processes involved in this decision?

Scientists working in this field might say – as indeed I have said – that the benefits of such experiments and the resulting knowledge outweigh the risks. It is more likely that a pandemic would occur in nature, and the need to stay ahead of such a threat is a primary reason for performing an experiment that might appear to be risky

What are these supposed benefits? Well, the Underpants Gnomes again come to mind: ???

Supposedly the idea is that we can get ahead of nature by creating deadly things that nature might produce through evolution and create cures in advance.

OK. I’ll bite. Name one cure produced by this type of research. Just one.

I have never seen a defender or advocate of this research point to a single example.

And indeed, it seems wildly implausible that this is very likely at all. What are the odds that nature would produce something so similar to what is produced in the lab by Dr. Shi or anybody else that a hypothetical vaccine for the Frankenstein creation would work on the evolved virus? Look at flu vaccines. They are frequently useless because the specific strains of virus they target happen NOT to be the one that crops up in a given year. Vaccines are not like hand grenades or horseshoes. Close is not good enough. A miss is as good as a mile.

Covid vaccines are very specifically targeted. The hysteria over covid variants is due in large part to concern that a vax that works on one variant won’t work well on other, very closely related ones.

But we are to believe that a vaccine (which again, has never been developed in reality) to treat a lab-created virus will be efficacious against another one that evolved independently?

So maybe GOF research creates the most deadly strain of pathogen, could–in theory–give us a defense against that specific or very closely related strains. But what good is that if other really deadly (if not quite so deadly) pathogens evolve, against which the unicorn vax is useless? And what are the odds that the most deadly pathogen would evolve naturally?

That is, how can (in Fauci’s words) you really “get ahead of the threat”? This is an especially valid question for evolutionists (whose ruling model is one of random variation plus natural selection): what are the odds that a threat that is created in the lab will help deal with a threat that evolves by a random process? Gain of Function seems to presume some sort of viral teleology. Which is to say, that nature acts by intelligent design that mirrors what is done in the lab. Human Intelligent Designers can “get ahead of” nature’s Intelligent Designer.

Ironic, eh?

So, GOF basically means create something really deadly that is unlikely to evolve naturally and which is also unlikely to permit developments of vaccines against what evolves naturally. This means that the odds of GOF research producing something that will protect against naturally occurring pathogens is vanishingly small.

But the risk of a lab leak is real, and non-trivial–as historical experience demonstrates and even Fauci acknowledges.

So how is this risk-reward trade-off intelligent?

This whole line of research seems to represent exactly the kind of scientific hubris that Mary Shelly wrote about two centuries ago. The “get ahead of the threat” rhetoric seems like propaganda intended to gull people into accepting Dr. Frankensteins pursuing their hubristic ambitions.

I am open to persuasion, which would have to take the following form. A rigorous calculation of the probability that a given GOF research effort will make it possible to accelerate meaningfully the development of a vaccine or therapy against a naturally evolved pathogen vs. a calculation of the probability that the pathogen created by this given effort will escape the lab.

Until I see such a demonstration, I will conclude that GOF should be banned, and its Dr. Frankenstein practitioners relegated to other, more benign tasks.

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53 Comments »

  1. @49 libte — here’s some data, some citations, and some stricter estimates for you.

    https://www.census.gov/data/tables/2019/demo/age-and-sex/2019-age-sex-composition.html

    US population by age: 80+: 11,943,000; 3.7%

    https://www-statista-com.stanford.idm.oclc.org/statistics/829732/global-population-by-age/

    World population by age: 64+: 9.3%
    US 64+: 16.4%

    Scaled World 80+ = (9.3/16.4)*3.7 = 2.1%
    Of 2.4 bn dosed globally, about 50.4 million are 80+

    Nursing home deaths after mRNA among 29,400 residents (87.7±7 yrs).
    Publication doi: 10.4045/tidsskr.21.0383

    100 deaths, 10 probably causal, 26 possibly causal. Total likely = 36%.

    Assign causality to 10+9 = 19 total.

    19/29400 = 0.00065. 29,400 participants is a statistically valid cohort.

    So scaled world deaths among the 80+ = 0.00065*50.4mn = 32,571 mRNA deaths among the 80+ aged alone. That’s 2.6 times more than the 1/3 estimate you didn’t like.

    H. Seligmann (2021) “Expert evaluation on adverse effects of the Pfizer-COVID-19 vaccination”

    PDF at ResearchGate. https://tinyurl.com/yjbpv2ap

    Seligman quantitatively assessed data from the extensive mRNA treatments in Israel.

    Using data from the Israeli Health Ministry, he shows that the death rate among the those treated with one mRNA dose was 3 times greater than the death rate of the untreated.

    During the first week after two doses, the death rate was 2.5 times greater and during the second two doses week was 4.5 times greater than the untreated..

    In Tabular form
    ________________Deaths per 10,000___Relative Rate
    Untreated_____________42_________________1
    dose 1_______________130_________________3.1
    dose 2 (1 week)_____207_________________4.9

    In Rose (2021) “A Report on the U.S. Vaccine Adverse Events Reporting System (VAERS) of the COVID-1 9 Messenger Ribonucleic Acid (mRNA) Biologicals” Science, Public Health Policy, and The Law 2, 59–80.

    The death rate among the mRNA-treated is 34 per million, with 25 dying after one dose. Among Covid-19 cases the death rate is 730 per million.

    In the US, with 285 million dosed, the mRNA deaths scale to 34*285 = 9690 for the US alone.

    For the world, with 2.4bn mRNA-treated, one gets 34*2,400 = 81,600 estimated deaths globally from the mRNA treatment.

    So, more detailed information makes the situation 6.5 times worse than the original estimate of 12.500.

    Comment by Pat Frank — June 10, 2021 @ 11:02 pm

  2. Thanks I appreciate you taking your time.

    a few things,
    1) of the global 2.4bn COVID administered doses, only a fraction is mRNA based. The Astrazeneca vaccine uses viral vector technology, not mRNA, and I think this is the most widely used. I think the same technology applies to the Russian and Chinese candidates.

    2) The study you are using from Norwegian nursing homes (10.4045/tidsskr.21.0383) makes it abundantly clear that we shouldn’t assign causality to the numbers, even to the probable causal:

    “Of the 100 reported deaths, the expert group classified 10 (10 %) as most likely related to the vaccine, and considered that there could be a possible link for 26 (26 %). It must be emphasised that these estimates are very uncertain, which is illustrated by the moderate kappa values for agreement between the initial assessments.”

    “Many of the reports did not contain sufficient clinical information to form an impression of the patient’s clinical course and a possible causal link between vaccination and death. Almost half of the reporting parties did not submit additional information. In particular, there was a lack of information about which phase of life the patients were in, and whether their health and general condition were already rapidly or slowly deteriorating before vaccination.”

    “It is therefore practically impossible to determine with any certainty how much of a role the vaccine played in the deaths.”

    “Our findings cannot…be used to estimate the incidence of vaccine-related deaths.”

    “Such an assessment requires nuanced and detailed clinical information, which in many cases was not available. The estimates are therefore uncertain.”

    3) Wrt the second paper (mRNA treatment in Israel).Do you truly believe that getting the Covid vaccine (two doses no less) results in a death rate 4.9x higher than not receiving the vaccine? Do you truly believe that?

    4) Again, you are making the same error. You assign causality between people receiving a mRNA vaccine and subsequently dying.

    Comment by l[email protected] — June 11, 2021 @ 6:59 am

  3. @52 libte

    1: every single immunological anti-covid treatment is an mRNA vehicle. Whether it’s delivered in nano-particle vesicles or in a viral vector, the active agent is mRNA or DNA that instructs the cell to make mRNA.

    Groceries delivered in a truck or in a trolley are still groceries.

    2: Regarding the Norwegian study, you’ve quoted out of context to make your point. The “Such an assessment requires nuanced …” statement referred to evaluation of very fragile patients, but did not refer to the 10 likely or 26 possible causal cases.

    The article goes on to make an incorrect assessment of the authors’ own data.

    In this case, the article mentions, “there will most likely have been far more than 100 deaths in nursing homes in a close temporal relationship to vaccination in the relevant time period. Our findings cannot therefore be used to estimate the incidence of vaccine-related deaths.

    This is a statistical argument. However, the experts examined the clinical histories of each of the 100 residents who died. They also had the event reports from the staff.

    These data allowed the subsequent causal analysis. Causal analysis disconfirms the purely statistical argument quoted above.

    Statistics use is inappropriate to judge event probability when causality can be appraised.

    The causally derived numbers therefore do instead positively allow their use to estimate the incidence of vaccine-related deaths.

    Here’s the critical point from the article: “In ten of the cases, a causal link between vaccine and death was considered probable, in 26 cases as possible and in 59 cases as unlikely.

    Nevertheless, we find it reasonable to assume that adverse effects from the vaccine in very frail patients can trigger a cascade of new complications which, in the worst case, end up expediting death.

    The categories ‘probable’ and ‘unlikely’ were used in cases where the expert group considered there to be a clear likelihood one way or the other, and the category ‘possible’ was used where a causal link between vaccination and death was just as likely as unlikely.

    As the 26 possible are equally likely as unlikely, we can safely surmise that about 13 of them are mRNA-caused deaths. We just don’t know which specific ones. The 10 are of clear likelihood.

    That makes the best estimate mRNA-caused deaths 23 rather than 19.

    23/29400 = 0.00078, which now scales to 39,429 mRNA deaths among the 80+ cohort globally.

    3: Your dismissal of Seligmann’s analysis is a mere argument from personal incredulity.

    Seligmann used official data from the Israeli Health Ministry. The numbers speak for themselves.

    Seligmann also compared death rates among statistically valid populations of mRNA treated and untreated. The mRNA treated displayed a significant excess death rate.

    If you don’t like the official data, you’re welcome to disbelieve them but that decision will be for no rational reason.

    4: You’re accusing me of the inverse of your own failing.

    The death and adverse reaction rates of the mRNA treatment are easily 10 times those of standard vaccines.

    Among the young and very young, it’s quite likely that the mRNA treatment is more dangerous than SARS-Cov-2 infection itself.

    Comment by Pat Frank — June 11, 2021 @ 11:38 am

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