First blog post in a while, as most content now goes via Patreon (link on the homepage). In Reading this article, please be aware that it is not denying Covid-19, although I prefer to focus upon SARS-CoV-2 as a specific viral strain rather than a collection of symptoms classed a disease.
This article focuses upon the vaccine trials which have not set out to prove efficacy in preventing mortality or viral transmission, and on the reactionary "science" that broke out as the pandemic unfolded and has not been updated as things became clearer.
Product Type: Vaccine
Item Code (Source): NDC: 59267-1000
Administration: Intramuscular
Ingredients: RNA ingredient BNT-162B2 (UNII: 5085ZFP6S) (RNA ingredient BNT-162B2 - UNII:5085ZFP6S)
Basis of Strength: RNA ingredient BNT-162B2
Strength: 0.23 grams in 1.8 millilitres
lipid ALC-0159 (UNII: PJH39UMU6H)
lipid ALC-0315 (UNII: AVX8DX713V)
POTASSIUM CHLORIDE (UNII: 660YQ98I10)
MONOBASIC POTASSIUM PHOSPHATE (UNII: 4J9FJ0HL51)
SODIUM CHLORIDE (UNII: 451W47IQ8X)
SODIUM PHOSPHATE, DIBASIC, UNSPECIFIED FORM (UNII: GR686LBA74)
SUCROSE (UNII: C151H8M554)
The Covid-19 pandemic brought about an almost immediate discussion around the prospects for vaccination against the virus responsible for the cluster of symptoms classified as Covid-19, the now infamous SARS-CoV-2. Researchers around the globe working for various research institutions and pharmaceutical companies began work, a lot of early research was based upon prior work regarding SARS-CoV-1, the one most of us have either forgotten or were not too aware of with the lack of internet based media outlets. Throughout the Spring, Summer and beyond “experts” and government ministers have promised that if all goes well, an “effective” vaccine may be achieved by *insert various dates here.*
SARS-CoV-1 or severe acute respiratory syndrome, referred to as SARS (it never managed to gain the title Covid-02) had approximately 100 cases out of 8096-8422 total cases and no deaths in the United Kingdom, and MERS-CoV had 31 cases out of a total of 2449 and two U.K. deaths. Globally at least 774-916 deaths occurred (1), giving a case fatality rate of 11 percent (2), which in theory suggest it to be highly lethal, despite this it ultimately seemingly mysteriously vanished. Coronaviruses as previously discussed are a large family of viruses, ranging from the common cold to more severe diseases, including the novel coronavirus, including SARS and SARS-CoV-2.
SARS, the 21st Centuries first pandemic, was initially identified in China’s Guangdong province, in late 2002, by medical practitioners who became aware of an “unusual” pneumonia, but did not report it to the World Health Organization (WHO). In early 2003 an outbreak in Hanoi, Vietnam, involving a WHO officer that later died, reported on a large outbreak on the 10th March.
A physician that travelled from the Guangdong province to Hong Kong, while infected with SARS and stayed at the Metropol Hotel, reportedly transmitting the virus around a dozen guests, three returned to Singapore, two of whom then returned home to Canada, one to Vietnam, one to Ireland, one to the United States and thus SARS began its spread around much of the globe but with the majority of cases occurring in Asia.
SARS was described as both aggressive and with a high lethality, symptoms were typically reported within two to three days and with limited reports infections in absence of symptoms. One must recall variances in test capacity in regards to total cases, when comparing SARS and SARS-CoV-2. The recent pandemic has seen Covid-19 testing reach biblical scales, with the United States alone, as of December 2, 2020 performing >196 million tests for Covid-19. (3)
In April 2003 the WHO suggested laboratory diagnostics tests, stating that;
“researchers in several countries are working towards developing fast and accurate laboratory diagnostic tests for the SARS coronavirus (SARS-CoV). However, until standardised reagents for virus and antibodies detection are available and methods have been adequately field tested, SARS diagnosis remains based on the clinical and epidemiological findings: acute febrile illness with respiratory symptoms not attributed to another cause and a history of exposure to a suspect or probable case of SARS or their respiratory secretions and other bodily fluids.” (4)
This indicates that clinical symptoms such as respiratory distress were indicated as a need for further differential diagnosis, thus samples from “suspected and probable SARS cases” were tested for SARS-CoV using the following methodology.
“Laboratory test result criteria for confirming or rejecting the diagnosis of SARS remain to be defined.
Principally, existing PCR tests are very specific but lack sensitivity. This means that negative tests cannot rule out the presence of the SARS virus in patients. Furthermore, contamination of samples in laboratories in the absence of laboratory quality control can lead to false positive results.
Positive PCR results, with the necessary quality control procedures in place. Recommendations for laboratories testing for SARS-coronavirus, are very specific and mean that there is genetic material (RNA) of the SARS-CoV in the sample. This does not mean that there is live virus present, or that it is present in a quantity large enough to infect another person.
Negative PCR results do not exclude SARS. SARS-CoV PCR can be negative for the following reasons:
- The patient is not infected with the SARS coronavirus; the illness is due to another infectious agent (virus, bacterium, fungus) or a non-infectious cause.
- The test results are incorrect (“false-negative”). Current tests need to be further developed to improve sensitivity.
- Specimens were not collected at a time when the virus or its genetic material was present. The virus and its genetic material may be present for a brief period only, depending on the type of specimen tested.
2. Antibody tests
These tests detect antibodies produced in response to the SARS coronavirus infection. Different types of antibodies (IgM and IgG) appear and change in level during the course of infection. They can be undetectable at the early stage of infection. IgG usually remains detectable after resolution of the illness.
The following test formats are being developed, but are not commercially available yet:
- ELISA (Enzyme Linked ImmunoSorbant Assay): a test detecting a mixture of IgM and IgG antibodies in the serum of SARS patients yields positive results reliably at around day 21 after the onset of illness.
– IFA (Immunofluorescence Assay): a test detecting IgM antibodies in serum of SARS patients yields positive results after about day 10 of illness. This test format is also used to test for IgG. This is a reliable test requiring the use of fixed SARS virus on an immunofluorescence microscope.
Positive antibody test results indicate a previous infection with SARS-CoV. Seroconversion from negative to positive or a four-fold rise in antibody titre from acute to convalescent serum indicates recent infection.
Negative antibody test results: No detection of antibody after 21 days from onset of illness seems to indicate that no infection with SARS-CoV took place.
3. Cell culture
Virus in specimens (such as respiratory secretions, blood or stool) from SARS patients can also be detected by inoculating cell cultures and growing the virus. Once isolated, the virus must be identified as the SARS virus with further tests. Cell culture is a very demanding test, but currently (with the exception of animal trials) only means to show the existence of a live virus.
Positive cell culture results indicate the presence of live SARS-CoV in the sample tested.
Negative cell culture results do not exclude SARS (see negative PCR test result).” (4)
Case detection in 2003 SARS pandemic took a different approach to SARS-CoV-2 in 2020, and the closest similarities may be seen potentially at the early onset of what became Covid-19 before mass roll out of tests occurred outside of laboratory settings.
In 2003 severe respiratory illness needed be within the context of “documented exposure risk” when diagnosing SARS-CoV disease. SARS-CoV disease was thus to be investigated in patients hospitalised for:
Data on the number of tests carried out during the 2003 epidemic seems scant, no doubt diagnostic attempts were drastically ramped up for the 2019-2020 emergence of a “novel” coronavirus, and in part that context needs including within the suggesting that 2003 SARS had higher risk for mortality, but did not infect so many or last as long. One must consider that in 2020 after much failure to implement testing, alongside track and trace (considering that the United Kingdom Government abandoned this strategy initially), testing was eventually conducted beyond the 2003 SARS criteria, including those that had little to no symptoms and or had been identified for testing by studies and contact tracers. As such, one may consider the sudden disappearance of SARS occurred to searches being limited to those with more serious manifestations of SARS pathology. Hence the mortality rate was also substantially more severe in 2003-2004.
With regard to a SARS vaccine, the studies for SARS-CoV-1 were initiated and tested in animal models, with an inactivated whole virus being tested in mice, ferrets, and nonhuman primates, which was suggested to provide protective immunity, but sadly in the animal studies it seemed to cause immune disease, specifically an immunopathologic-type lung disease, which given the nature of SARS was not a good outcome. (6)
Human studies were not conducted, and the vaccine studies petered out due to the apparent disappearance of the virus, which was attributed to a number of factors, including the weather in the summer, the “strict quarantine initiate of not only those infected, but those who had been in contact with individuals identified as infected. In reality nobody knows why the pandemic ended, viruses tend to be unpredictable, but as written by the author in Pandemic Panic (7), viruses tend to mutate to less severe strains in order to survive. A virus that is either lethal to all hosts, or renders hosts unable to circulate in the community leads to less spread and the virus being unable to survive. Potentially in SARS the increased mortality rate may have caused such a phenomena, but it seems more plausible, given that while mortality was suggested to be higher than SARS-CoV-2, it did not kill all those infected, that limitation of testing to those informally diagnosed as being infected led to the less severe strains running unchecked in asymptomatic individuals. In SARS-CoV-2, mild and asymptomatic cases are being highlighted giving the impression that this latest pandemic is less lethal but more virulent. Vaccine development for SARS-CoV-2 varies, with some using minute viral portions, or virus ribonucleic acid (RNA). (8)
This is suggested to circumvent the issues that occurred with the SARS-CoV-1 vaccine that relied upon greater amounts of the actual virus.
BioNTech and Pfizer recently announced preliminary “evidence,” and in the United Kingdom following hasty checks which some suggest to be a political move by a government reeling from the looming disasters of Brexit, and the poor handling of the pandemic that has been mired in controversy with cronyism amongst other issues, he United Kingdom became the first to approve the Pfizer/BioNTech vaccine, paving the way for so-called “mass” vaccination, after Britain's medicines regulator, the MHRA, suggested the product which allegedly offers “up to" 95 percent “protection against Covid-19 illness,” was safe enough to be rolled out. (9)
The news was greeted with much excitement, but one must consider that “up to” 95 percent and “protection against Covid-19 illness” are not well defined.
The approval of an mRNA vaccine for use is a world first (10), and while the technology appeared in 1990 within literature it has been fraught with numerous issues that needed solving.
Vaccines in theory works via the introduction to the body of material that is sufficient and specific enough to provoke and immune response. These are in theory achieved by an attenuated (weakened) virus, a virus that has killed, or a viral protein, such as occurs in an mRNA vaccine in which a messenger RNA is introduced, this RNA is the genetic material utilised to translate the proteins used within our bodies.
The typical self/non-self model of immune function whilst still the predominant held view both in immunology within general practise has encountered problems since the 1980s, and Dr Matzinger’s Danger Theory (11), argues that tissues are a large factor in driving an immune response, and that an immune response occurs in response to a danger which may vary not only between, but between individuals. What may present danger to one, may not represent the same degree of danger to another. Certainly this needs to be accounted for in vaccines that do not contain a live virus, and also in those with attenuated virus samples. Viruses that have been inactivated are less dangerous and produce a weaker response immune response, necessitating immunologic adjuvants, and often and multiple "booster" injections. (12)
Adjuvants in immunology refer to substances included to potentiate and improve the immune response (13) Vaccine manufacture was assumed to cause significant variability in batch efficacy due to contamination within reaction vessels used within processing, however, when cleaning protocols were scrupulously increased a reduction in vaccine “effectiveness,” and contaminants were noted to enhance immune response. (14)
As can be seen at the beginning of the article, the vaccine includes the RNA ingredient BNT-162B2, and a number of other ingredients or adjuvants, namely;
lipid ALC-0159 (UNII: PJH39UMU6H)
lipid ALC-0315 (UNII: AVX8DX713V)
POTASSIUM CHLORIDE (UNII: 660YQ98I10)
MONOBASIC POTASSIUM PHOSPHATE (UNII: 4J9FJ0HL51)
SODIUM CHLORIDE (UNII: 451W47IQ8X)
SODIUM PHOSPHATE, DIBASIC, UNSPECIFIED FORM (UNII: GR686LBA74)
SUCROSE (UNII: C151H8M554)
Adaptive immune response theoretically occurs following an innate immune response (danger) which see cells such as the dendritic cells being engulf ed by the pathogens, which migrate to lymph nodes and the T cells that act as the adaptive immune cells are then activated. (15)
This activation causes mast cells to release both heparin and histamine that isolates the infection site to enable immune cells ability to clear out pathogens, but also causing the release chemokines. Adjuvants are suggested to increase the local reactions and induce a larger release of danger signals, plus induce release of inflammatory cytokines. The immune system to suggested to recognise these pathogenic molecules due in part to Toll-Like Receptors (TLRs).
Various medical complications are suggested to occur both in humans and animals due to adjuvants, with aluminium salts, utilised in numerous vaccines but regarded safe by the Food and Drugs Administration (16), yet numerous studies indicate a role in the development of Alzheimer's disease (17), an adjuvants may be too reactogenic, creating susceptibility to fever. Indeed fever post vaccination is an expected outcome. The vaccination for “swine flu” H1N1 pandemic was associated with incidence of the chronic sleep disorder, narcolepsy in both children and adolescents (18), which associated with an influenza vaccine called pandemrix that has the AS03-adjuvant.
In animals, specifically mice, aluminium adjuvants which have been previously linked to Gulf War syndrome (GWS), following its use in anthrax vaccination, been indicated to cause motor neuron death (19), increases in incidences of amyotrophic lateral sclerosis as well as other related neurological disorders correlated with GWS. No doubt multiple environmental variables are noted, anthrax vaccination and the relevant adjuvants such as aluminum hydroxide and squalene have repeatedly and increasing faced scrutiny. The use of squalene, a suspension of oil-water is also indicated as increasing the risk for auto-immune disease incidence in rodents. (20) Squalene itself is indicated in arthritis prone rodents as inducing rheumatoid arthritis (21), a 2006 report by Richards et al (22), found a relationship between vaccine-associated sarcoma (VAS), but conflicts exist on whether risk is increased by specific vaccines, manufacturing processes specifically, adjuvants, or other associated variables. (23).
On the 8th December 2020, United Kingdom began rolling out the Pfizer vaccine candidate, a mRNA (messenger RNA) type of vaccine as previously discussed, that enables synthetic genetic material that is enveloped in lipids to transfect (infect) the cell, which occurs due polyethylene glycol (PEG). In what is often referred to as conspiracy theory circles, public awareness usually focuses upon PEGs use in anti-freeze type products that may be utilised in motor vehicle radiator amongst other use. With the Pfizer vaccine candidate, PEG aids in the Nucleoside modified mRNA encoding for SARS-CoV-2 full-length spike protein antigen is combined with a lipid nanoparticle (LNP) formulation. (24)
Polyethylene glycol forms part of the formulation of lipid nanoparticle that envelops the specific mRNA genetic material, which was previously noted as ALC-0159, which is the name for 2[(polyethylene glycol)-2000]-N,N-ditetradecylacetamide. (25)
Knop et al (26), reviewed the use of polyethylene glycol in delivery of pharmaceutical drugs, indicating that as early as the 1950s they were linked to a propensity to cause cellular clumping and blood clotting, which increases risk for embolisms, including pulmonary embolisms, as well as inducing an inflammatory cytokine storm. Polyethylene glycol are suggested to be linked to high incidences of drug related adverse reactions, including but not limited to anaphylaxis. (27; 28; 29; 30; 31; 32; 33; 34; 35)
Indeed, as indicated by Pottel et al (36), medications tend to constitute relatively minute amounts of the active pharmaceutical ingredient, with the majority of tablets, capsules, liquids, and injectables such as vaccines including numerous ingredients such as dyes to help distinguish drugs, preservatives to ensure stability and shelf life, antimicrobials and excipients compounds which may be either fillers, or as is suggested in vaccines suggested to be essential to ensure the active ingredient is delivered both safely and effectively.
It is generally accepted that ingredients listed as excipients are biologically due to an absence of acute toxicity in studies using animals. Pottel et al (36), searched for long-term subtle effects, and interaction with other medicines, stating that many excipient have effects that may have been previously unappreciated and may play an important role in health outcomes and disease.
The use of lipid nanoparticles in the Pfizer vaccine, like one from Moderna, are suggested to be approximately 100 nanometers in diameter, similar to the actual coronavirus. Pfizer suggests it uses four different lipids in a “defined ratio”, with lipid ALC-0315 being a primary ingredient within the formulation that are ionizable, and can be positively charged, while the RNA has a negative charge causing the two to attract each, but that it is a component known to able to cause side-effects. (37)
Errors made by the Scientific Advisory Group for Emergencies (SAGE), ones that have continued throughout the pandemic, were discussed in other works by the author (7), and the errors occurring in assessment of the unfolding SAR-CoV-2 pandemic rendered the predictions grossly inaccurate, which was seen to have both disastrous effects upon the nations response to Covid-19, and also necessitated frequent and drastic re-evaluated estimates. SAGE’s initial estimates followed a narrative that SARS-CoV-2 was a novel coronavirus, and that the cases found in late 2019 were the initiation of its spread, and thus that the pandemic was in early stages, and that the majority of the United Kingdom population (as high as >93 percent) had not been exposed to the virus and were at risk of infection, and a failure to act would lead to 500,000 deaths if not action were taken. (38)
This modelling assumed the total population to susceptible to SARS-CoV-2, with no pre-existing degree of immunity present within communities. Yet as described by Doshi (39), who highlights six specific studies that report SARS-CoV-2 T cell reactivity in between 20 to 50 percent of individuals with no documented viral exposure.
Ng et al (40), studying samples of blood collected in the United States between 2015 and 2018, found 50 percent had some form of SARS-CoV-2 T cell reactivity. Weiskopf et al, utilising specimens collected in the Netherlands found T cell reactivity in two out of 10 individuals that had not been virally exposed. (41)
Further reactivity was identified in individuals in the United Kingdom, Germany, Sweden, and Singapore. (42; 43; 44; 45)
Whilst small in scale and unable to provide accurate estimates of whom might have prior immunological SARS-CoV-2 responses, that findings indicated across continents, and various laboratories suggest that further research is warranted.
Chavarria-Miró et al (46),indicate the detection of SARS-CoV-2 in sewage retrospectively tested in Barcelona, Spain long before their first case of Covid-19 presented, this they suggest indicates that SARS-CoV-2 present within the population prior to reports of a global pandemic.
Indeed, Basavaraju et al (47), indicated SARS-CoV-2 infections within the United States in mid December 2019, further evidence that supports the notion that this strain of coronavirus was actually spreading throughout many nations prior to the reports of initial cases in Wuhan, China. Sadly, entering further into such narrative potentially labels one as a “conspiracy theorist”, a term some suggest is linked to the United States Central Intelligence Agency (C.I.A). (48) That said, failure to consider all theories and possibilities risks one being labelled a “complicity theorist.”
Anyone reading The Devil’s Chessboard by Talbot (49), will have little doubt of the levels the United States have previously, and presumably will still go in order to maintain and further their cause. The book details the morally corrupt and rather cynical rise of the United States intelligence apparatus that not only documents from official records, their capability of intervening clandestinely in internal affairs of competing nations but on a domestic front.
From the fanaticism brought on by the Cold War against Soviet Russia and the “necessity” for unaccountable secret institutions to distort home politics and undermine the “democratic” elsewhere, one must draw parallels with the ideology to secretly fight communism, even to the degree Dulles engaged in secret activities following World War Two to establish “ratlines” that aided Nazis considered useful to the United States in the new Cold War against the Soviet Union could both travel to the U.S, and avoid prosecution, and the secret testing on many U.S citizen via the MKULTRA project. (50) Dulles led the CIA-engineered coups in Iran in 1953 that toppled the democratically elected government of Mohammad Mossedegh and installed Shah Reza Pahlavi (who ruled until 1979) an apparent bold and daring triumph for the United States in the cold war against the Soviets.
In an era in which Wall Street is untouchable, one in which China may be the United States current fear, whilst stories should be considered and rationalised, its is not farfetched to suspect that we will read about these aspects at some point via declassified intelligence documents long in the future. The 6th August, 2019 saw the United States main laboratory facility for biological warfare being issued a "cease and desist" order due to safety standards and protocol, and leaks violations. (51) Whether this was a convenient back story to cover for any clandestine activity remains unknown, but it all adds to the plausible deniability, a central tenet of CIA activity.
What do we know about the facility? Numerous experiments were engaged in by the United Sstates, from the case in 1954 when seven inmates, notably all were black males were isolated and fed mass doses of Lysergic acid diethylamide (LSD) for 77 days by Isbell (52), “work/research” that formed part of a highly secretive C.I.A program attempting to develop methods for mind control that was based at an inauspicious Army base, Fort Detrick.
Fort Detrick in Frederick, Maryland, just 50 miles from Washington and was initially selected as a site for the development of secret plans for germ warfare, and until recently thrived as the Army’s principal biological research base with approximately 600 buildings spread across 13,000 acres. Through declassified documents, the ones that were not destroyed, we can establish that secret programs occurred to develop biological weapons, such as the Whitecoats. (53; 54; 55)
Little has been said regarding Covid-19 by Fort Detrick, and that little mention is made of Covid-19 seems curious given the study available freely on available (56), by Hensley et al.
Lisa E. Hensley is described as the Associate Director of Science at the Office of the Chief Scientist, National Institute of Allergy and Infectious Disease Integrated Research Facility in Frederick, Maryland. Prior to that acting as a civilian microbiologist in the virology division of the United States Army Medical Research Institute of Infectious Diseases (USAMRIID) also located on Fort Detrick, Maryland, acting as a subordinate lab to the U.S. Army Medical Research and Development Command (USAMRDC), which is also headquartered on the same installation. (57) Hensley is one of the premier researchers of some of the world’s most dangerous infections, including Ebola hemorrhagic fever, and Severe acute respiratory syndrome (SARS). Holder of various patents for vaccines and treatments, Hensley seems to be erroneously forgotten in the current climate. (58; 59; 60)
Is it likely that the intelligence services wished to impact China, or indeed its own citizens with a viral infection? Hopefully not, but given past actions, and the serious breaches in safety one would expect a better account to explain such instances. The United States seems to be positioned as ever to maintain plausible deniability. Is it possible that SAR-CoV-2 was already present in the United States and other nations, and Wuhan, China was simply the site at which it was formally identified?
In the United Kingdom, and indeed many other nations, one must first consider that the scientific advisory group for emergencies (SAGE), consisted of no clinical immunologists, nobody with a degree in biology degree, or post-doctoral specialisations specifically in immunology. Some were medics, but there were sociologists, psychologists, economists, political theorists and a profuse amount of mathematicians, which formed the modelling group responsible for much of the pandemic response. (61)
Modelling does require specific expertise in order to achieve their desired outcomes, yet such outcomes may not specifically be based on the full available evidence, but in an ideological stance that misses context and skews the outcome predictions. When modelling is structured by those with little expertise in the specific subject-matter it risks foundational errors that are both missed by the modellers, and often by those tasked with implementing policy and operational changes due to a false belief in the disproportionate power of models. However credulous the modelling group within SAGE may appear, the claims made, that the processes and pathways of pathological diseases such as Covid-19 fails to account for specific biological variables and makes assumptions of key factors such as the starting for SARS-CoV-2 spread.
The models utilised on the suggestion of Imperial College were inherently flawed for a number of reasons, but primarily as discussed above, that SARS-CoV-2 was a novel virus and thus no prior immunity was conferred within the community. As has been discussed earlier, evidence currently suggests SAR-CoV-2 emerged before the date suggested in contemporary literature and the media, and that T-cell reactivity is evident in some degree of the population, which would be expected given that SARS-CoV-2 is a mutation of the Coronavirus and not a totally new emerging virus. (62)
This assumption that 100 percent of the population were susceptible to SARS-CoV-2 infection led to a further false assumption, that studies of antibodies within the blood allowed a model to be constructed that determined the percentage within the population that had been infected.
SAGE suggested as of September 2020, that >90 percent of the United Kingdom population remained at risk (63), which when combined with the “data” from the REal Time Assessment of Community Transmission (REACT) study which suggests “that slightly under 6 percent of the population may have antibodies for the virus by the end of June…” indicating that such individuals were “likely” to exposed to SARS-CoV-2, or suffered with Covid-19 “disease”. (64)
One could therefore assume that the United Kingdom government backed stance on SARS-CoV-2/Covid-19 risk suggest that circa 94 percent of the population have not been infected, a figure which seems disconcertingly high when one considers the narrative that while SARS-CoV-2 carries less mortality risk than SARS, it is suggested to be be more prevalent and spread more easily, even within individuals classified as asymptomatic i.e. people who are not displaying symptoms of disease.
The official data suggests a fatality rate circe 3.5 percent (65), with 1,766,819 positive tests, and 62,566 deaths recorded “with” Covid-19 identified. With a U.K. Population of 68,045,779, a six percent infection rate should mean that over four million eighty-two thousand seven hundred forty-six people have been, or are infected, which gives a fatality rate of approximately 1.5 percent.
However, as discussed, it seems curious that SARS-CoV-2 would infect such a low percentage of the population, even if one considers that it only began its global spread in December 2019. Indeed, Ioannidis (66), in study using globally collated data suggest an infection fatality rate circa 0.2 percent as a best estimate.
This error or flaw in the policies and models comes because of the initial assumptions that SARS-CoV-2 was novel virus, and while the event that led to finding SARS-CoV-2 made it seem novel, we neither know how long it existed undetected, nor know the immunity granted from prior coronaviruses infections. In short, viruses have genetic ancestors, and the previous “novel” coronaviruses already discussed, 2003 SARS and 2012’s MERS in 2012 (67) have similar DNA sequences and structures to the current virus, with SARS being indicated to be as much as >85 percent similar.
In prior work (7), I spoke about endemic coronavirus that are linked to the common-cold which ted to circulate both within the United Kingdom and globally freely. Modernity, specifically a tendency to remove sick pay in less affluent social communities seems to cause a tendency for faster and easier transmission of such viruses. Human coronaviruses (hCov) such as hCoV-HKU1, hCoV-OC43, hCoV-NL63 and hCoV-229E are discussed in detail by Zhu et al (67), and while discovered in the 1920s in animals (68; 69), it wasn’t until the 1960s that human coronaviruses were identified. (70; 71; 72; 73; 74) As before, discovery does not mean they were none existent and newly emerged, just that research has “isolated” and identified something which was considered new. That hCoV-HKU1, hCoV-OC43, hCoV-NL63 and hCoV-229E tend to either led to asymptomatic or mild type respiratory and/or gastrointestinal infections, does not discount from their circulation within humans since their first identification, and no doubt prior to their documented existence. While accounting for between five to 30 percent of all common colds, hCoVs are rarely considered serious until the occurrence of global pandemics such as in SARS-CoV, MERS-CoV and SARS-CoV-2.
Initial opinions of coronavirus appears to have considered them to be pathogens that were relatively harmless, yet in recent months they have become globally associated with potential severe clinical complications. Coronavirus, an enveloped type virus identified by a positive-strand ribonucleic acid (RNA) genome, primarily targets mucosal surfaces within both respiratory and the intestinal tracts in a variety of mammals and birds. (75; 76)
Human coronavirus isolates known as hCoV-229E and hCoV-OC43 were correlated with the “common cold”, and symptoms in the upper respiratory tract that were both mild and self-limiting. (77; 78) When the so-called new variant SARS-CoV was discovered, which initiated an outbreak globally of acute instances of often severe cases of atypical pneumonia circa 2003, it led to an interest in human coronaviruses and the identification of two further novel variants, HCoV-NL63 and HCoV-HKU1 (79; 80), which showed an ability to cause serious complications in the respiratory tract, particularly in patients with existing comorbidities.
The initial discovery of human coronaviruses in the 1960s (70; 81), involved two differing isolation methods. One, by Kendall, Byone and Tyrell (82), at the British Medical Research Councils Common Cold Unit, in which B814 a common cold novel virus that was unable to be cultivated using standard techniques previously used to successfully cultivate adenoviruses, rhinoviruses, and others associated with the common cold. (83) Tyrell and Byone instead used a technique in 1965, that involved serial passage through a human embryonic trachea organ culture. A 1966 paper by Hamre and Procknow (84), from the University of Chicago describes the isolation of another novel cold virus, hCoV-229E, which was sourced from medical students, and grown in a culture of kidney tissue.
Human coronaviruses are indicated to act with the renin–angiotensin proteases (enzymes that breakdown proteins and peptides), and in order to both establish and maintain a cycle of infection, coronaviruses require that they deliver genetic material inside the intracellular space, which is mediated by glycosylated spike proteins, which are discussed in other works. (7)
Angiotensin Converting Enzyme 2 (ACE2) is suggested to act as a functional receptor for human coronaviruses (9), with antibodies that direct against ACE2 theorised to prevent SARS-CoV infection. (85)
The renin–angiotensin system (RAS), is a well described endocrine system, vital in maintenance of cardiac function, arterial pressure, homeostasis of fluid, and salt balance, along with regulation of tissue remodelling, particularly in proliferation of cells, angiogenesis and apoptosis. (86)
Aside to the physiologically normal processes, RAS is correlated with a variety pathophysiological actions. (87) Abnormal RAS activation is established as a variable in the development of numerous cardiovascular diseases, including hypertension, diabetes and renal disease. (88; 89)
Within RAS, synthesis of a variety of angiotensin peptides occurs, which are degraded by the precursor angiotensinogen via a series of complex enzymatic reactions. Specific components of RAS generate within specific body regions, for example, renin is generated within the kidneys, whilst ACE is derived from the lungs, with the liver being responsible for angiotensinogen. In fact angiotensin synthesis is is suggested to be evident to some degree in all organs, RAS activity initiates via the kidney, following juxtaglomerular cells releasing renin (90; 91), which acting as an aspartic protease works to cleaves its substrate angiotensinogen, that is then produced in the liver and forms the inactive angiotensin peptide, Ang I or Ang 1–10. Ang I converts to either And II, a RAS effector peptide, or Ang 1–8 via the protease ACE which is dependent on zinc. (92)
Higher ACE expression occurs on vascular endothelial cell surfaces, in particular within lung tissue. (93) Ang II generation from Ang I is able to occur via enzymes that are not ACE related, such as chymase, a serine protease. Whilst ACE is considered to be the primary enzyme responsible for Ang II-conversion, research indicates that Ang II conversion occurs via chymase enzyme in certain pathological vascular conditions. Indeed, it must be noted that chymase activity is evident in pulmonary membranes, aiding Ang I conversion into Ang II within lung tissues. (94)
RAS is typically considered predominantly a system of endocrine and circulation, yet it is now well established that alongside RAS peripherals, RAS is both tissue-specific, and abundant in independent localised systems. Indeed, within various organ systems, such as the lungs, kidneys, liver, heart, brain, vasculature, pancreas, and within the reproductive, nervous, and the digestive system. (92)
In-spite speculation regarding the existence of RAG local airway capacity intrapulmonary generation of Ang II was a recent confirmation. (95) Alveolar mast cells within both the lower and upper respiratory tract, are evidenced to express levels of renin which triggers formation of pulmonary Ang II. (96;97)
RAS components are also abundant in airway tissue in humans, including ACE and angiotensinogen, with pulmonary epithelium evidenced as the primary circulatory source for ACE. (98) Receptors for Ang II are evidenced to be expressed within lungs, in the form of the subtype AT1 which is found in the smooth muscle bronchial cells, and bronchial receptors AT2 receptors within the epithelial brush borders. (99)
The expression of ACE2 in both alveolar, bronchiolar epithelial cells, and pulmonary endothelial cells is well documented. (100)
Lung masts cells are evidenced to have chymase, potentially being a the major enzyme responsible for Ang II-generation within the lung. Local RAS activity within pulmonary tissue has been indicated as contributory in processed of tissue remodelling, such as alveolar epithelial cell apoptosis regulation, fibroblast proliferation and production of collagen within the lung. (101; 102)
Thus it is suggested that activation that is inappropriate with regard to specific local components of the airway RAS, specifically ACE2, may initiate factors that exacerbate the development pathophysiological conditions that are associated with SAR-CoV-2, and the severity of disease outcome in covid-19.
ACE2 and SARS-CoV-2
Angiotensin-converting enzyme 2 (ACE2), plays a major role in RAS homeostasis, converting Ang II to Ang (1–7), and the activation the RAS putative pathway. ACE2 is thought to be responsible for the regulation net Ang II tissue levels, as an antagoniser of fibrotic and hypertrophic effects due to the AT1 receptor being the binding site of Ang II. (103; 104)
ACE2 may the exhibit a role of counter regulation that seems critical for RAS homeostasis within the lung (104; 105), thus, improper regulation leading to increases in both levels of ACE and Ang II levels are associated with the pathogenesis of numerous varied es of lung disease, such as sarcoidosis, pulmonary hypertension, pulmonary fibrosis and more inportantly in the context of COVID-19, acute respiratory stress syndrome (ARDS). (106; 107; 108)
Studies conducted in-vivo confirm an association between the severity of ARDS, and the outcome, with pulmonary RAS. (109) ARDS, a severe acute lung injury, which is characterised with an accumulation of inflammatory cells, pulmonary oedema, and severe hypoxia (110), as prevalent in documented cases of covid-19. ARDS may be triggered by a variety of pathogenic states, such as sepsis, pancreatitis and severe trauma/shock. (111)
A number of previous studies indicated pulmonary RAS in ARDS pathogenesis, and that ACE antagonists such as AT1 receptor blockers delay the onset of ARDS in rodents exhibiting acute lung injury. (112)
Negative contributions of ACE to pathogenesis of ARDS occurs via a variety of mechanisms, such as increases in vascular permeability. (113)
Imai et al (109), identified a protective role of ACE2 during acute lung injury such as ARDS, in counterbalancing the induced pathophysiological effects of angiotensin II. Mice bred with an abrogated expression of ACE2 expression exhibited more severe patterns of disease when compared to control mice, with an enhanced degree of vascular permeability, lung oedema, and decreased lung function.
SARS-CoV & HCoV-NL63 in relation to RAS activity
The 2003 epidemic of SARS-CoV, whilst a disease that remained relatively rare, with an incidence 8,422 cases, and a total fatality rate of circa 11 percent (114), which is primarily suggested to be attributable to ARDS induced respiratory failure. Indeed, the fatality rate is variable, largely dependent on factors such as age, treatment methodology, to be between 0 and 50 percent (115), with SARS patients < 24 years evidenced to be less likely (< one percent) to die from SARS, that those > 65 who had a 55 percent mortality rate. (116)
SARS-COV infectS host cells via ACE2, the component of RAS which is evidenced to protect against ARDS induced acute lung failure. (117; 118)
As the aforementioned spike protein engages with ACE2 a reduction occurs in the cell surface, thus ACE2 functional capacity is down regulated (117; 119), a phenomenon that is evidenced to provoke increased severity and risk of lung failure in rodents infected it SARS-CoV. (120)
It is also worthy of note, that the within the SARS-CoV-2 spike protein, a pocket of the free fatty acid, linoleic acid has been indicated to increase SARS-CoV-2 binding (121),
Interestingly, despite this research, the team consider linoleic acid to be a viable potential therapy due to the fatty acids so called “essential” nature.
Ling et al (122), studied rodent fatty acid profiles alongside inflammatory markers utilising animals fed a diet considered essential fatty acid-deficient (EFAD) constituting 2 percent hydrogenated coconut oil (HCO) for a 2 weeks period. Alongside groups supplemented with 1.3mg of arachidonic acid and 3.3 mg of docosahexaenoic acid (AA + DHA) which created a 2 percent fat diet. Upon exposure to lipopolysaccharide, the rodents on the EFAD diet had significantly lower levels of various markers of inflammations, such as tumor necrosis factor (TNF) and interleukin-6.
Increases in serum levels of C18 unsaturated free fatty acids are discussed by Bursten et al (123), as being a significant predictor in acute respiratory distress syndrome (ARDS) development, which was discussed within both Controlling Intuitive Appetite (124), and Pandemic Panic (7), which suggests that increases in ratios of unsaturated serum acyl chain occur between those codified as healthy and those patients which suffered severe outcomes, were both sufficient to identify those likely to suffer ARDS, and provide insights regarding the essentiality of unsaturated fatty acids.
Hanna and Hafez (125), discuss arachidonic acid being an unsaturated fatty acid that is sourced either via direct dietary means, or indirectly via metabolism of linoleic acid, in which its release occurs via the breakdown of phospholipids under the action phospholipase A2. Various factors, including mechanical through to chemical stimuli may induce a cascade of arachidonic acid.
Malcom et al (126), compared the composition of fatty acid in adipose tissue samples taken from 143 adults autopsied humans aged 24 to 61 years, one from a site that was deep-seated site (perirenal) and two from sites that are subcutaneous, the buttock and abdominal areas. Proportional levels of saturated fatty acid were found to be highest in samples of adipose tissue found in the perirenal, whilst the adipose tissue buttock was lowest in saturated fatty acids. Proportionally level of both linoleic and linolenic acids were similar across all sample sites, leading them to conclude adipose tissue found in the buttock has a greater degree of unsaturation than abdominal adipose tissue.
Mamalakis et al (127), in a study of 475 adolescents aged 11 to 18 years (138 aged 11 to 16 years completed all variables), assessed levels of physical activity, serum lipids, and both buttock and abdominal composition of adipose fatty acids finding that like adults, the composition of fatty acid in the abdominal adipose tissue of children is supposedly less favourable when the buttock, with abdominal adiposity once again exhibiting the much maligned saturated fatty acids elevated proportions, with decreased proportions of both monounsaturated and polyunsaturated fatty acids when compared to buttock adiposity. Such findings are corroborated in adults by Pittet et al (128), and Phinney et al. (129)
That unsaturated fatty acids are suggested as being important in the binding of the SARS-CoV-2 spike protein, and are indicated to be higher with age seems to correlate well with the susceptibility of aged subjects to SARS-CoV-2 infection and poorer mortality.
The team (123), state that activity in the linoleic acid metabolic pathway is able to trigger both systemic inflammation, acute respiratory distress syndrome and cause pneumonia, all pathologies observed in severe Covid-19, ARDS, Sepsis patients. (7)
El-Kurdi, et al (130), concurs that mortality increases in relation to unsaturated fatty acid both as exogenous consumption and administration, and also due to adipose lipolysis. Indeed it must be noted that as Covid-19 pathology worsens, dietary intake may reduce due to loss of appetite which increases fatty acid oxidation, potentially of unsaturated fatty acid. Unsaturated fatty acids seem key in ability of the SARS-CoV-2 spike proteins to attach and enter the human body, specifically via the ACE2 receptor.
Validation by research from Bristol University (121), which seeks a possible basis for a pharmaceutical intervention that may prevent the Sars-CoV-2 virus from entering the human body, consists of a research team, led by both Christiane Schaffitzel and Imre Berger that found unexpectedly that linoleic acid was exhibited within a pocket of the protein. Linoleic acid, a constituent of widely available linseed oil, is also a component of many industrial processes such as the manufacture of linoleum, a floor covering consisting of canvas with a preparation of linseed oil as a backing. Linoleic acid (18:2ω6; cis, cis-9,12-octadecadienoic acid) is the most highly consumed n-6 polyunsaturated fatty acid (PUFA) in the human diet (131), and can obtained from vegetable oils such as sunflower, safflower, soybean, corn, and canola oils as well as nuts and seeds.
The maintenance of n-6 polyunsaturated fatty acids as a so-called “essential fatty acid” as they cannot be manufactured endogenously (132), which is suggested to be required, among other things, to maintain cell membranes in the lungs, which continues to be the consensus belief (133), despite issues with membrane theory as described by Ling (134), in which he discusses a;
“concept that the basic unit of all life, the cell, is a membrane-enclosed soup of (free) water, (free) K+ (and native) proteins is called the membrane theory. A careful examination of past records shows that this theory has no author in the true sense of the word. Rather, it grew mostly out of some mistaken ideas made by Theodor Schwann in his Cell Theory. (This is not to deny that there is a membrane theory with an authentic author but this authored membrane theory came later and is much more narrowly focussed and accordingly can at best be regarded as an offshoot of the broader and older membrane theory without an author.) However, there is no ambiguity on the demise of the membrane theory, which occurred more than 60 years ago, when a flood of converging evidence showed that the asymmetrical distribution of potassium (K+) and sodium (Na+) observed in virtually all living cells is not the result of the presence of a membrane barrier that permits some solutes like water and K+ to move in and out of the cell, while barring - absolutely and permanently--the passage of other solutes like Na+. To keep the membrane theory afloat, submicroscopic pumps were installed across the cell membrane to maintain, for example, the level of Na+ in the cell low and the level of K+ high by the ceaseless pumping activities at the expense of metabolic energy. Forty-five year ago this version of the membrane theory was also experimentally disproved. In spite of all these overwhelming evidence against the membrane-pump theory, it still is being taught as verified truth in all high-school and biology textbooks known to us today. Meanwhile, almost unnoticed, a new unifying theory of the living cell, called the association-induction hypothesis came into being some 40 years ago. Also little noticed was the fact that it has received extensive confirmation worldwide and has shown an ability to provide self-consistent interpretations of most if not all known experimental observations that are contradicting the membrane-pump theory as well as other observations that seem to support the membrane pump theory.”
and that it appears to be the molecule to which Sars-CoV-2 attaches itself in order to enter the human body, the persistent narrative of it as essential leads the researchers to conclude not that n-6 polyunsaturated fatty acids should be limited, both via consumption and lipolysis, but that their challenge is the development of a pharmaceutical drug which is able to distorts the spike protein of Sars-CoV-2, thus preventing it attaching to the linoleic acid, pointing to similar drugs have already been developed to prevent rhinovirus attaching themselves to the lungs. (135)
The study authors note, that despite huge investment searching for elusive human immunodeficiency viruses (HIV) vaccines, the medical community relied upon therapeutic anti-viral medications of varying efficacy to decrease disease mortality risk.
Dr. Ray Peat (136), in an article titled “fats, functions & malfunctions”, discusses both linoleic acid and arachidonic acid as not only increasing lipid membrane permeability, but that the whole cell increases in permeability, causing structural proteins to bind throughout the cell which is exhibited in fibrosis seen in both Covid-19/ARDS and septic shock, along with an increased affinity to retain water which leads to generalised cellular swelling and localised swelling in the mitochondria that reduces oxidative function, and allows increased cellular calcium that activates cellular excitation and initiates a redox shift toward inflammatory states that ultimately leads to inappropriate growth and mass, as seen in fibrosis and cancer, or cell death.
Dr. Peat continues to highlight the impact of such cellular environments, and the effects of glycogen restriction, which may occur via increased energy demand, or energy restriction, either intentionally or due to metabolic dysfunction. Stating that decreased glycogen stores leads to increases in secretion adrenaline that may act to liberate fatty acids from adipose stores. Following chronic dietary consumption of n-6 polyunsaturated fatty acids, the ability to be oxidised or detoxified by the liver which is impacted by glycogen availability, thyroid function. (137)
Peat (136), draws awareness to research by Cook et al (138), Li et al (139), and Autore, et al (140), and the quite remarkable resistance displayed by animals deficient in so-called “essential fatty acids to shock, which indicates the central role of polyunsaturated fatty acids in the maladaptive, and often chronic adaptions caused by acute shock, such as retention of calcium, cellular leakiness, inhibition of energy production, which bare striking similarities to the markers of many disease pathologies, and so-called “normal” ageing. The abundance of serum free fatty acids and stress hormones that tend in aged subjects to be both chronically higher, and result in poorer outcomes in diseases such as Covid-19 and other respiratory illnesses, alongside reduced tolerance of incidences of stress.
Much research indicates that animals with lower levels of unsaturated fatty acids exhibit higher metabolic rates, and a preference of glucose use, which leads to increased carbon dioxide production (141), and enhanced resistance to toxins such as cobra venom (142), and lipopolysaccharides, commonly known as endotoxins.(139) This correlates with the discussion in Consistent Eating (143), that metabolism decreases in line with energy intake through lifespan, and that susceptibility to stress decreases as metabolism declines, which suggests a lower respiratory quotient due to limited glucose intake and/or increased consumption of fatty acids and protein.
Despite the associations with ACE2, identified polymorphisms in human ACE2 genes are however not correlated with SAR-CoV disease progression. (144; 145)
Functional performance of RAS is evidenced to decrease as part of “normal” physiological processes of ageing, as is exemplified by a progressive inhibition of circulating levels of renin and the plasma activity. (146; 147)
Indeed, ageing is a frequently noted variable in infections related to both SARS-CoV, and SARS-CoV-2 as a significant predictor of poor outcome. (148)
Thus, RAS function in elderly, and groups with co-morbid conditions may lead to worse outcomes regarding ARDS and acute injury due to an overall impairment in RAS activity.
That corona virus activates inflammatory systems, particularly RAS, and with available medications to act as both angiotensin receptor blockers and for inhibition of ACE. Angiotensin converting enzyme enables production of inflammatory proteins which increase blood pressure, and the correlation between angiotensin and serotonin is well established in regards to age related inflammation. As lifespan increases, exposure to and production of angiotensin occurs with then, increases blood vessel contraction, which creates greater clotting risk, and increases fatigue, alongside inhibiting energy production. (149; 150)
The class one viral fusion spike protein, which while unique to coronaviruses, a feature that mediates attachment to the host receptor in all species of CoV. (151) The N-glycosylated spike protein varies abundantly between the species of CoV with lengths between 1100 to 1600 residues, and estimation of molecular mass ranging to <220 kDa. The spike protein features trimers that form the spikes evident on the surface of the CoV particle may be between 18–23-nm, a factor which may cause issues in the reliance on reverse transcriptase-polymerase chain reaction (RT-PCR) testing. (152; 153; 154)
Reverse transcription polymerase chain reaction (RT-PCR) is an established laboratory technique used for the identification of specific genetic materials presence in a sample via the biochemical amplification process. The test has been lauded as a scientific advance of great importance to the field of molecular biology, with the foundation of PCR revolutionising DNA study and gaining its creator, Kary B. Mullis, the 1993 Nobel Prize for Chemistry, and it use primers to sequences the encoding may involve a cross reaction with the spike protein that not only detects SARS-CoV-2 but other hCoV during the sample collection (155), as well as other respiratory viruses, as discussed, some degree of immunity is conferred by previous exposure to similar viruses. (156)
Reported variances in illnesses range from mild symptoms to severe, and well documented occurrences of death since SARS-CoV-2 was first confirmed and reported in humans.
The Centre for Disease Control (CDC) initially suggested the following symptoms “may” appear 2-14 days after exposure.
Variances and confusion seem evident in testing protocol, with many citing initial failures in test validity (158; 159; 160; 161), with nucleic acid tests (NATs) that are widely utilised for diagnosis of new cases being suggested to have a likelihood that many such infections may remain undocumented, and presumably where false negatives are a possibility, so to must be false positives. Whilst relatively cheap, and potentially abundant, the use of NATs as one of the two primary methods for confirming Covid-19 presence in humans subjects involves the collection of patient samples that are then tested for specific molecules relevant to the Covid-19 genetic material.
Under previous criteria, a diagnosis of Covid-19 needed to be confirmed by lab tests, specifically a nucleic acid test performed on swabs from a patient’s respiratory tract or blood. Yet issues exist in nucleic acid testing, with “false negatives” created by tests that are not sensitive enough requiring greater amplification (cycle threshold), issues in transporting and handling samples, and questions over the quality of sample collection. (162)
A nucleic acid test (NAT) is a procedure for the detection a specific nucleic acid sequence to detect virus or bacteria via the genetic materials RNA (ribonucleic acid)/DNA (deoxyribonucleic acid), as opposed to antigens/antibodies. As the amounts of genetic material are typically small, techniques are used to amplify genetic materials, namely nucleic acid amplification tests (NAATs), such as a strand displacement assay (SDA), or transcription mediated assay (TMA), as seems to be utilised in the specific Covid-19 polymerase chain reaction (PCR) test.
PCR typically involves a process of 20–40 repeated cycles of thermal temperature variation. (163)
That the medical community has rallied in order to develop reliable molecular diagnostic tests has been aided by numerous research groups working to identify and sequence the viral genomes via open databases. As infections are suggested to increase, authorities sought methods to accurately diagnose and reliable document cases. Clinically, access to robust, and accurate data was dependent upon the isolation and cultivation of coronavirus from the broncho-alveolar lavage fluid via three patients that are classified as a probable outbreak source.
Electron microscopy, a technique fraught with issues as previously discussed by Hillman (164), allowed observations of “typical” coronavirus morphology, whilst more classic use of light microscopy demonstrated a cytopathic effect upon epithelial cells in the human airway. From this, various international groups worked utilising this sequence data in order to produce primers for PCR tests that would support public health laboratories in absence of an available commercial Covid-19 test.
The lab of Christian Drosten, of the Institute of Virology, Charité University Hospital, Berlin, along with academic collaborators in Europe and Hong Kong (165), verified and assessed the test validity in absence of both isolates of SARS-CoV-2 or indeed patient samples, instead confirming validity against 297 samples obtained from patients diagnosed with other respiratory infections. Upon this basis 250,000 kits, were dispatched by the World Health Organization (WHO), to 159 laboratories globally.
A Hong Kong University group developed two quantitative RT reverse transcription PCR tests (166), that target the sequences of viral genome deposited with GenBank, then validated against two clinical specimens via SARS-CoV-2/Covid-19 infected patients.
The PCR test is suggested to be highly sensitive, if used correctly, but notably when the cycle threshold (amplification) is increased, but this produces significant problems in high-pressure settings, and it also still remains unclear on the optimal type of clinical specimen, with suggestion that swabs of the nasopharyngeal give greater consistency compared to sputum samples. (167) Questions are also raised with regard to both consistency in cycle threshold between test (with variances in assays), and a cut off point art which cycle threshold becomes too sensitive and detects dead viral fragments from previous infection.
These early lab tests were suggested to “buy-time,’ and give public health authorities some diagnostic tools before commercial products and kits became available at scale. In China, genome sequencing firm BGI Group, of Shenzhen had by the end of January distributed over 50,000 test kits across China. On the 5th February it opened an emergency test laboratory in Wuhan that was able to process 10,000 samples per day. Other companies are developing their tests more slowly, but initial rollouts were suggested to be imminent.
Not all were relying on primer designs and protocols specified by academic laboratories or public health authorities. Rather than develop bespoke PCR tests, IDbyDNA was one of a handful of companies employing metagenomic nucleic acid analysis as a routine diagnostic and surveillance tool. Its existing Explify Respiratory test, which is a laboratory-developed test, able to identify over 900 respiratory pathogens, including viruses, bacteria, fungi and parasites, by comparing unbiased metagenomic data obtained from patient samples with a large repository of sequence data.
It was suggested that it could already detect the SARS-CoV-2 strain.
“We have now updated our data with the new coronavirus and are in the process of revalidating,”
said cofounder and chief medical officer Robert Schlaberg.
“The modifications are all on the data analysis side.”
That was, he stated, an easier process than updating the physical assay, with the actual data analysis taking less than an hour, giving a total turnaround time from receipt of sample to test result of 36 hours. Although more expensive than PCR testing, the falling costs of sequencing could help to democratise this approach. The company is selling the technology as well as its testing services.
The suggestion that NAT tests falsely produce negative results in patients with the infection is complicated by the suggestion that Computerised Tomography scans, are able clearly identify signs of viral infection, even though radiation creates tissue disturbances. (168)
The enactment of emergency measures created a situation in which large biotech and medical testing laboratories are allowed to develop and validate their own tests, yet various sources are compiled to create the data which becomes publicly available. Interestingly, despite the seeming fragility to the stock market, the value of certain bio-tech companies seems to be increasing. (169)
As described above regarding testing, the use of these probabilistic inferences relies upon clusters of so-called empirical evidences, which can be seen to lack validity. As discussed in Mandel (170), a problem discussed by Eddy (171), explains that the following problem is encountered with regard to a medical tests accuracy in aiding probability assessment;
“The probability of breast cancer is one percent for a woman at age 40 who participates in routine screening. If a woman has breast cancer, the probability is 80 percent that she will get a positive mammography. If a woman does not have breast cancer, the probability is 9.6 percent that she will also get a positive mammography. A woman in this age group had a positive mammography in a routine screening. What is the probability that she actually has breast cancer? __ percent.”
It is shown by Casscells, Schoenberger, and Graboys (172), amongst others, that physicians frequently incorrectly interpret the actual probability. Using bayesian reasoning, as discussed by Mandel (170), physicians fare better when all the information is considered rationally. The proportion of patients in the scenario originally suggested to have breast cancer would be referred to as the prior probability. The possibility that those with breast cancer receive a positive mammogram, and that a positive mammogram will be received by an individual who has not got breast cancer are both known as conditional probabilities. This information would collectively be referred to as priors, and through its use we could estimate probability of breast cancer, and that we know a positive mammogram has been received as a revised probability.
If a sample of 10,000 female participants is utilised, and 100 of those actually have breast cancer, of which just 80 have received a positive mammogram. 9,900 do not have breast cancer, yet 950 of them will also receive a positive mammogram. From this data we can assess that 1,030 females out of the original 10,000 participants received a positive mammogram, yet only 80 will actually have cancer, just 7.8 percent of the total group.
This gives us four groups:
Priors may be true, and they may indeed reflect the reality, but without effective judgement against all available data, or if priors are held as defined and established facts that are unchallengeable, beliefs may be given unsubstantiated credibility.
This serves to highlight that Covid-19 testing accuracy is not known, that multiple variants of tests may be been utilised both globally, nationally and indeed across state-lines. Indeed, all diagnoses may not be via tests, with less severe cases that are self-isolated and reported as Covid-19. That said, so-called asymptomatic carriers of the infection may remain undiagnosed, thus suggestions regarding mortality/fatality rates remain questionable.
We can draw out some data that helps from the cases in Wuhan, China. In Zhang et al (173), we see that from a total of 140 cases, other comorbidity’s were present, indeed from all cases the most prevalent underlying health issue, was hypertension.
64.3 percent of those in the Zhang et al research had underlying health conditions, that represents 90 people.
Of those 90;
In non-severe cases 82 cases were split by;
The endemic spread of hCoV’s that produce the so-called common-cold enables some degree of immunity, to not only to those specific viruses, but also to those that are closely related, with SARS-CoV-2 being one such virus. The evidence that SARS and SARS-CoV-2 are approximately 80 to 85 percent identical at the genome sequence (67), should indicated that some degree of immunity cross-over can be expected to be demonstrated in contamination of results indicating SARS-CoV-2 infection being due to other hCoV types.
A systematic review by Jefferson et al (174), suggests that the RT-PCR test is so sensitive that not only is it susceptible to picking up other hCoV contaminants, but also that it potentially detects post infection fragments of SARS-CoV-2 (or other hCoV) that are no longer live, which according to the team may be leading to over-diagnosis of Covid-19 that has occurred, specifically in the so-called second wave of the pandemic.
One of the authors of the study, Professor Heneghan suggests that their findings should be used to classify whether test outcomes that are currently “positive or negative” depending on detection of “the virus”, that the tests could be refined with either a viral cut-off point in which viral amounts are considered in regards to how much triggers what would classically be called a case, indicated by symptoms and illness, not the current definition of a case which is simply a positive result.
The team including Heneghan reviewed evidence collected from 25 studies in which viral specimens collected from samples of positive tests were virally cultured to test whether they were able to grow, indicating whether a positive test contains an active viral sample that is able to reproduce and transmit, or just viral fragments that are dead and unable to grow either in the laboratory setting, or presumably in an individual.
The diagnosis of Covid-19 involves an RT-PCR swab test as the standard diagnostic method in both clinical and community wide settings, uses numerous processes and chemicals that amplify the genetic material of the virus to aid its so studied. As discussed previously, "cycles" that occur in order to recover sufficient viral material to identify it could be utilised to indicate how much virus evident. The more replication cycle needed, the more infectious an individual may be, which presents an unquantified risk for false positives. Jefferson et al (174), suggest that while every sample cannot be cultured in a laboratory, an indication of a samples viral content could be deduced from knowledge of the number of replication cycles required to identify the virus which could provide evidence of whether it is indeed an active infection. (175)
Gniazdowski et al (176), suggest that even when SARS-CoV-2 was detected molecularly, acknowledgement of the number of cycle thresholds provided increased accuracy in infection diagnosis, particularly in combination with RT-PCR test results and in presenting with clinical symptoms. 161 cases indicated positive by RT-PCR exhibited a wide range of values for cycle threshold, which is suggested to reflect variance in viral load despite all sharing a positive test that confirms their status as a Covid-19 case by orthodox means.
In viral samples found to be infectious by culture study, the mean cycle threshold value was indicated to be 18.8 ± 3.4, with a median value of 18.7. In samples that could not be cultured, indication samples to be non-infectious, a mean cycle threshold value of 27.1 ± 5.7, with a median of 27.5 was indicated.
The research found a general trend that observed an increase in cycle threshold as indicating a reduced viral load. Interestingly, the study found that some patients initially testing negative for SARS-CoV-2, received a positive result on a subsequent test, but that the follow up positive result indicated on previous negative patient was elicited with a cycle threshold >29.5, and that attempts to recover the infectious virus via culturing these specimens indicated the samples to be negative.
Indeed, Public Health England, acting on behalf of the United Kingdom government (177), state that the cycle threshold provides a value that is semi-quantitative and able to broadly categorise viral concentration within a sample collected by RT PCR, yet they add the context with regards to samples collected from the upper respiratory tract may be inadequately collected or represent a degraded sample, as such irrespective of the same sample being used to diagnose a case of Covid-19 disease, single same samples cycle threshold value is suggested to be unreliable, nothing that values for cycle threshold are not directly comparable due to variances in assays types, not only between laboratories but also within the same laboratory which may have used multiple assays.
The United Kingdom government/SAGE stance is that around six to seven percent of the population have been infected with SARS-CoV-2 due in part to seroprevalence studies of viral antibodies with in the blood (64), a position that is supported by Sekine et al (178), in an investigation of the close members of family members of patients with “confirmed” Covid-19 infection, finding T cell reactivity in individuals that were asymptomatic or seronegative. Approximately 60 percent of close family members were evidenced to produce antibodies, yet 90 percent evidenced T cell response, suggesting that despite infection, many did not produce, or maintain antibodies. Gallais et al (179), also concluded that SARS-CoV-2 may induce virus-specific T cell responses without seroconversion, and that reliance upon epidemiological data based uponSARS-CoV-2 detection may be substantial underestimating prior viral exposure within the population. Media attention has maintained a focus on antibody research, and in contrast to the above findings, studies such as Long et al (180), and Seow et al (181), that report the waning of SARS-CoV-2 antibodies to at around two to three months fuelled a narrative in both the media and in governmental policy (64; 182), that repeat infection was a plausible risk that necessitated extreme measures to protect not only the 94 percent that had escaped infection, but the minority six percent that had been theoretically infected already. (183)
Le Bert et al (184), state that “T cell reactivity was found for SARS 17 years after the patients were infected with SARS, which led them to suggest the possibility that T cells generation may protect or reduce the pathology of SARS-CoV-2 infection, this would suggest that the basic premise that antibody data would allow an understanding of whom remained at risk and who was protected is inherently flawed, a fact discussed by Altmann and Boyton. (185)
In reviews (186; 187), of the primary and secondary outcome measures of the phase III placebo controlled trials, T cell reactivity is not considered, thus pre-existing levels of immunity are not considered either in the need to vaccinate previously exposed individuals, or in regards to suggested outcomes that Covid-19 vaccination is currently suggested to confer only short term “immunity”. With studies concluding at 56 days it is currently impossible to suggest long term immunity is possible, and given that “immunity” is measured by antibodies, one must conclude that it does not look plausible given the above noted evidence.
“Immunity” via vaccination
The known candidates for Covid-19 vaccine are Pfizer (188), Moderna (189), Johnson & Johnson (190), and AstraZeneca (191), with Pfizer’s already being issued emergency authorisation in the United Kingdom at time of writing. Some degree of transparency occurred in publishing vaccine trial protocols, which while worthy of praise, the protocols do raise concerns that are seemingly being ignored, both by a nation seeking a silver bullet, and government looking for some semblance of success in what has to date been an unmitigated disaster.
The protocols utilised in the trials seem to have been specifically designed in order to prove the efficacy of the vaccines, despite minimal measured effects. A trial for a vaccine would typically be expected to have as a critical outcome measure, the prevention of infection. As discussed this would need to occur alongside both PCR testing that is controlled for in terms of cycle threshold, serological tests, antibody tests and more importantly T cell reactivity measures.
Yet all the trial conduced did not have the prevention of infection as a criterion for effectiveness, or success. for any of these vaccines. In all studies the primary suggestion of successful outcome was that in those with confirmed infections, the differences in symptoms severity between vaccinated and unvaccinated participant was indicated as vaccine effectiveness. Thus, a measured differences in symptoms amongst those identified as being infected with SARS-CoV-2 (the accuracy of which may be affected by cycle threshold) identifies that the so-called “vaccines” are not effective in preventing infection, or transmission, but theoretically may be effective in modifying symptom in those classed as infected.
In much of society an expectation, and indeed a belief may be that an effective vaccine is one that not only prevents serious disease, but transmission of the disease/virus to achieve the desired herd immunity. The trials by Pfizer and Moderna that have been indicted for emergency use authorisation in the United Kingdom, and the protocol used by AstraZeneca do not set out to establish that the product prevents serious disease, just that prevention of mild-moderate symptoms are prevented or reduced.
To test vaccine efficacy in disease prevention, large clinical studies may take many years and involve 30-60 thousand participants, rather than the less rigorous protocols that saw manufacturers achieve authorisation for emergency use by the Medicines and Healthcare products Regulatory Authority (MHRA), and seek emergency use authorization (EUA) from the United States Food and Drug Administration (FDA), via their limited preliminary results.
The protocols also set out rather mild symptoms as the stated requirements for diagnosis that an individual has contracted Covid-19. Minimum criteria to be included as a Covid-19 case is a positive PCR test, which has already been discussed in regards to issues with accuracy, and either one or two symptoms including fever, headache, mild nausea, or a cough, all symptoms that are notable not only as common cold symptoms, side effects following vaccination and more astonishingly are amongst some of the symptoms indicated for injection of sodium chloride which is used in the the placebo drug. (192; 193) Criteria for approval is indicated to be the variance in symptoms displayed in control and vaccine groups that are “infected”, with no use of measures of infection between groups.
For many holding out hope that a vaccine will have an ability to both prevent infection, severe illness and death, particularly in those with known preexisting conditions, or older members of society, the vaccine is hoped to allow social interaction to occur once again, yet severe illness and death outcomes are listed as secondary objectives. The prevention of death and even hospitalisation from SARS-CoV-2 infection are not critical to the phase III trials satisfactory conclusion.
In being deemed effective in the United Kingdom, and as is expected, in other nations, the trials conducted today have simply been set out in order that products can be established as effective by measure that presumably the lowest barriers to success. Whether this is yet again for political aplomb by a government in crisis, or simply part of an industry race to both meet demand and beat the competition remains to be seen. As things stand, work remains incomplete in establishing vaccine efficacy, and questions arise as to whether such detailed research will be completed, or if this “emergency response” will become the new normal in bringing pharmaceutical to market in global pandemics.
Pandemic Parlour Tricks
As has been discussed in this text as well as both Consistent Eating (143), and Controlling Intuitive Appetite (124), science and particularly research remains at risk of data hacking and other scientific attempts to skew evidence to maintain a hypothesis.
As has been discussed, increased amplification, or cycle thresholds have been identified as having the potential to increase false positive, to diagnose cases of Covid-19 in individuals who may not have active infections. The much fated second wave of Covid-19 in the United Kingdom saw a paradox in which “cases” grew exponentially in relation to “deaths with Covid-19”, which may have occurred due to a number of factors;
This effect, whilst being plausibly deniable as either “conspiracy theory”, is in fact possible given that numbers of cases could be dialled up and down at will via a sleight of hand parlour trick that manipulates the data to suit the desired outcome. Whilst such underhand tactics may seem far fetched, one need only consider previous activities both within the industrial-medical complex, and government, particularly in the United States and the United Kingdom in relation to historical and recent manipulations. (7; 124)
Globally the establishment of RT-PCR testing as the Covid-19 gold standard has been flawed, indeed, without availability of viral material, a reliance was put upon the specific genetic sequence initially published by Chinese scientists (194)
Test protocols both globally and even within nations have utilised RT-PCR testing requiring two primer matches, instead of the preferred three, a potential “oversight” that may render such test protocols inaccurate in their ability to both delivery results, and in their use in comparing data against other variations of test protocols with Borger (195), suggesting that the use of such a poor PCR test protocol combined with a high cycle threshold (>35), as is common both in the United States and throughout Europe, that infection probability in a positively diagnosed person is <three percent, suggesting the probability of a false positive result is therefore 97 percent.
Even the United States Dr. Fauci is evidenced on video stating that; “If you get a cycle threshold of 35 or more…the chances of it being replication-competent are minuscule…you almost never can culture virus from a 37 threshold cycle…even 36…it’s just dead nucleotides, period.” (196)
As the virus apparently spreads rapidly with drastically increasing number of cases appearing despite the introduction of many measures (masks, social distancing et cetera), many have noted that a great majority of free from what may be classified as serious symptoms. This led to the warning initially that specific groups such as infants through to adolescents may be asymptomatic super spreaders (197), that while not evidently sick, did help transmit the virus amongst the community.
This narrative changed, specifically it seemed to alter when government required schooling facilities to reopen in order that the economy may also be opened by allowing parents and caregivers to outsources childcare once again allowing those who could to restart work. Around this period spread amongst younger people was partially dismissed as irrelevant, and asymptomatic spread was thus position as a community wide problem with potential for anyone without symptoms to spread SARS-CoV-2.
Remembering, as discussed in Controlling Intuitive Appetite (124), diseases are similar to language, and definitions alter as culture, or indeed industry manipulates its usage. Polios apparent eradication through vaccination is largely due to a manipulation of the classes of symptoms that now classify as polio. Jonas Salk’s miracle polio vaccine is a story perpetuated in current orthodox media, particularly in light of the announcement of Covid-19 vaccine availability. Polio, a disease often linked with dichlorodiphenyltrichloroethane (DDT) poisoning (198), prior to the introduction of the vaccine in 1955 >50,000 people within in the United States contracted polio per year, yet by 1955, a 45 percent decline was evident, and 1955 the figure was 28,985. (199)
Dr. Bernard Greenberg, the head of the University of Carolina School of Public Healths Department of Biostatistics stated that; qualification for diagnosis of paralytic poliomyelitis required a patient to be exhibit symptoms of paralytic state for at least 60 days following the diseases onset from 1955 onwards. Prior to the availability of vaccination (<1954), symptoms needed to be exhibited for just 24 hours with no need for conformation from either laboratory testing, or the residual presence of paralysis. Such changes in defined terms alter reporting and often lead to symptoms being attributed to other diseases classifications such as meant that in 1955 we started reporting a new disease, namely, “polio-like” illnesses such as transverse myelitis, acute flaccid paralyses, and aseptic meningitis which seem to be increasing in prevalence. (200; 201)
While some “polio” cases result in temporary paralysis, some present with no paralysis, and symptoms range from: fever, headache, sore throat, vomiting, fatigue, muscle aches/weakness, pain and stiffness in the back, neck or limbs, to meningitis. (202)
By redefining diagnostic criteria, this contributes to a downward shift in documented cases and a rise in other disease pathologies. Similar effects may be apparent in Covid-19 with similarity in pathology to other diseases, alterations in defined symptoms as time advances, with initial reports of symptoms for mild disease as;
Presenting with uncomplicated upper respiratory tract viral infection and may exhibit non-specific common symptoms;
Indeed, as documented in Controlling Intuitive Appetite (124), science seems to be for sale to the highest bidder, with industry seemingly able to pay for desirable results to be both published and receive peer review. Yet a replication crisis seems apparent when others attempt to reproduce the same results. (206)
This replication/reproducibility crisis is a methodological effect evident in numerous scientific studies and fields in which the findings are either difficult or impossible to reproduce. Within the field of medicine Ioannidis (207), found that from a total of 49 studies conducted between the years 1990 to 2003, accounting for >1000 citations, 45 of the studies claimed effective therapeutic effect, yet 16 percent of the studies were subsequently contradicted by further studies.
Baker (208), conducted a survey of >1,500 researchers, with >70 percent stating they had attempted to reproduced the experiments of other scientists and failed to replicate the findings.
Again Ioannidis (209), highlights this problem, suggesting a need for research to become patient centred, rather than focusing upon the “needs of physicians, investigators, or sponsors.” Despite this crisis in academia, and the industrial pace at which Covid-19 research occurred, both under time pressures but free from normal peer review, we are told government are following “the science” and that we should trust the experts.
Scientific credibility is not only achieved by research, but by establishing further with evidence via their replicability with newly acquired data. This stands alone from retesting scientific “evidence” using the same data and analyses (reproducibility) and retesting existing data with various types of analyses (robustness), in such a situation outcomes that were consistent with the prior finding increase confidence in the “evidence”, and inconsistent outcomes decrease the confidence.
In Covid-19 it seems there is no exact replication occurring in testing and diagnosis, with every test potentially utilising different cycle thresholds amongst other factors such as assay variability. As such generalisability in data decreases the confidence in the findings as the potentially unique conditions applied to RT-PCR tests means that it can not be consider a replication study.
The inability to validate the test data to support either the number of presenting cases, or the much queried number of deaths “with Covid-19” (remember that while preventable deaths should indeed be considered tragic losses, even if not due to SARS-CoV-2), skewed data does not present a true picture of either the scale of the problem, or whether measures are appropriate or effective.
This coupled with the suggestion that antibody production remains low following infection, a process entirely expected in younger and or “healthy” populations that rather than diverting energy generation to a complex, slow and energy-intensive process of antibodies production, utilises what is termed the innate immune system, which works via a far more efficient process involving T-cells that defend against future infections. A such, one would expect to see little or no evidence of antibodies as timespan since infection progresses, and its use by SAGE to guide the proportion of infection amongst the population is either an error due to inadequate qualifications amongst a SAGE team primary constituting mathematicians, modellers and behaviourists, with a government also lacking in biological knowledge, or more lately due to some degree of malice by seeking to maintain a narrative that is unproven and undoubtably flailing.
Estimating SARS-CoV-2 infection rates within the United Kingdom population may be achieved using the known infection fatality ratio (IFR), which is in itself imperfect given that deaths with Covid-19 may still be false positive, but theoretically this is less problematic than the opposing stance of utilising antibody data in all cases including those codified asymptomatic.
Despite confidence in government, current policy leaves us with this “known unknown” that both seriously hampers understanding of the crisis and damages that response, an effect that has been seen by many as the pandemic rages in. The modelling by the Imperial College team (38), led by Professor Ferguson suggests that <7 percent of the population of the United Kingdom have been infected, which powerfully justifies prolonging and or reassuring lockdowns, social restrictions and early vaccination roll out. Relaxation of measures such as social distancing risks millions individuals becoming infected, the already depleted national health service becomes overwhelmed, as it does each winter. (210)
The model suggested excess deaths of circa 510,000 without precautions, and approximate 250,000 using a strategy of mitigation, dropping to 20,000 if the strategy was to suppress the virus. This suggests that a policy of lockdown would prevent 230,000 excess and unnecessary deaths occurring.
As this paper has sought to establish, the model propagated by Professor Ferguson seems to have drastically underestimated infection rates amongst the population. Indeed, a paper by Lourenço et al (211), led by Professor Gupta from Oxford University various estimates are suggested for percentage of infected (both current and prior) population within the United Kingdom, with figures as high as 68 percent. Critics claimed the work led by Professor Gupta was too “speculative” with little “empirical justification”, yet the Imperial model also falls foul of the same accusation. The previously discussed estimates are based upon assumptions built into the Imperial model created an implausible view of a novel virus, and as such one would assume that models could be updated and coded to work with newly available data, such as cycle thresholds for RT-PCR tests (for example >30 cycle threshold positive tests could be weighed more towards being indicative of prior infection), T-Cell reactivity et cetera.
Being able to increase the accuracy in gauging rate of infection helps not only guide and justify policy interventions, but helps to establish the infection fatality rate (IFR) which is vastly different from the case fatality rate (CFR), that uses the number individuals that tested positive (ignoring false positive and negative results) and is divided by the total deaths (ignoring questions about whether SARS-CoV-2 was the specific cause of death, or a co-factor). Variability in CFR occurs between country due to multiple variables including testing availability et cetera.
Ioannidis (212), led a team to assess the actual infection rates in Santa Clara County, California, using serology testing for antibodies, which as noted performs poorly in documenting longterm exposure rates, specifically in younger/“healthier”. The team looked at the data of 3,300 Santa Clara County residents in the United States and found rates of infection to 50 to 85 times that the amount of cases officially documented (956 at the time of the study).
Loss of antibodies, while biologically expected due previously explained reasons (antibodies production is energetically expensive, while T-Cell reactivity which is part of innate immune function is less so), is suggested as a reason for caution within communities (lockdown et cetera) do to the “known unknown” regarding whether re-infection is plausible. (213)
A Japanese woman (214), was suggested to have been re-infected but was classified as being “immunocompromised.” In considering this we must rationalise many aspects, firstly considering the terms, being classified as suffering from Covid-19 may not necessarily be due to being evidenced SARS-CoV-2 as was clear early in the pandemic within many nations, diagnostic testing was not available to many, as such symptoms were utilised and quarantine necessary. It must be noted that such symptoms are shared by many other pathologies including the common-cold which of course can be due to specific coronaviruses. We must also differentiate between two actual positive results, one may be indicative of a live virus evident by a RT-PCR utilising a low cycle threshold, the second may be a test procured due to the onset of similar symptoms and a positive result produced using a much higher cycle threshold. Without availability of data on test protocols we can not accurately consider whether reinfection is plausible. Indeed, in a case report by Prado-Vivar et al (215), they put forward evidence including epidemiological data, clinical findings, the positive RT-PCR re-test, two different virus clades and the antibody response as being compatible with reinfection, but admit a critical limitation of the study was the failure to culture the virus, as such we are unable to conclusively state whether it was reinfection to fragments of prior infectious viral material that is no longer live or presenting risk to others.
Viruses do mutate, and as noted tend to become more easily transmissible, but less dangerous. As discussed, it is implausible that as suggested by the Ferguson Imperial College model, that it presented a novel pathogen, by the nature of evolution it has ancestors and will continue to do so, but our exposure to one strain should confer some degree of immunity to further, specifically weaker strains. Access to cycle threshold data and T-Cell reactivity studies could re-code the current epidemiological models and provide better guided governance and strategic planning in both tackling the virus, restoring public confidence and creating a plan that allows the economy to reopen and stay open. Without such data, and in the hands of leadership relying upon so-called super-forcasters (216), the country seems destined for regular occurrence of lockdowns and cyclical vaccination programs to “protect” against reinfections of new strains. No doubt the country (and many other nations) are in the grips or a pandemic that is straining health care provisions beyond their capabilities, but it is important to gain context. In the United Kingdom austerity and poor management have not only limited the resources of the National Health Service, which is annually at breaking point each flu season, but staffing levels have suffered due to poor funding for students aiming to enter the health care industry, and poor retention of staff due to wage freezes and poor working conditions.
I wrote in Controlling Intuitive Eating (124), that intelligence may be better measured by the ability to observe, analyse and update beliefs. At this we are failing, while an emerging pathogen causes fear and reactionary strategies, as timespan increases “the science” could and should be updated rather than moulded to fit the policy. That this continues alongside issues of cronyism in government contracts from personal protective equipment (PPE), testing, and vaccination causes a further degree of distrust in the political strategies utilised to date.
Science needs to be utilised to its full capacity, not coopted to enable and justify policies that meets industrial and political desires.
References:
1. Leong, H, N., Earnest, A., Lim, H, H., Chin, C, F., Tan, C., Puhaindran, M. E., Tan, A., et al. (2006). SARS in Singapore--predictors of disease severity. Annals of the Academy of Medicine, Singapore. 35(5): 326-331.
2. Chan‐Yeung, M., & Xu, R, H. (2003). SARS: epidemiology. Respirology. 8: S9-S14.
3. Number of coronavirus (COVID-19) tests performed in the most impacted countries worldwide as of December 2, 2020* Retrieved 1st December 2020, from https://www.statista.com/statistics/1028731/covid19-tests-select-countries-worldwide/
4. WHO. (2003). Severe Acute Respiratory Syndrome (SARS): Laboratory diagnostic tests. Retrieved 29th November 2020, from https://www.who.int/csr/sars/diagnostictests/en/
5. In the Absence of SARS-CoV Transmission Worldwide: Guidance for Surveillance, Clinical and Laboratory Evaluation, and Reporting. Retrieved 29th November 2020, from https://www.cdc.gov/sars/surveillance/absence.html
6. Tseng, C, T., Sbrana, E., Iwata-Yoshikawa, N., Newman, P, C., Garron, T., Atmar, R, L., Peters, C, J., et al. (2012). Correction: Immunization with SARS Coronavirus Vaccines Leads to Pulmonary Immunopathology on Challenge with the SARS Virus. PLOS ONE. 7(8): 10.1371/annotation/2965cfae-b77d-4014-8b7b-236e01a35492. Retrieved 29th November 2020, from https://doi.org/10.1371/annotation/2965cfae-b77d-4014-8b7b-236e01a35492
7. Craig, B. (Unpublished). Pandemic Panic. WWBS Publishing. London.
8. Amanat, F., & Krammer, F. (2020). SARS-CoV-2 Vaccines: Status Report. Immunity. 52(4): 583-589. https://doi.org/https://doi.org/10.1016/j.immuni.2020.03.007
9. Roberts, M. (2020). Covid-19: Pfizer/BioNTech vaccine judged safe for use in UK. BBC News Online. Retrieved 5th December 2020, from https://www.bbc.co.uk/news/health-55145696
10. Pardi, N., Hogan, M., Porter, F., & Weissman, D. (2018). mRNA vaccines — a new era in vaccinology. Nat Rev Drug Discov. 17: 261-279.
11. Matzinger, P. (2013). Friendly and dangerous signals: is the tissue in control? Nat. Immunol. 8(1): 11-3.
12. Petrovsky, N., & Aguilar, J, C. (2004). Vaccine adjuvants: Current state and future trends. Immunology and Cell Biology. 82(5): 488-496.
13. Sasaki, S., & Okuda, K. (2000). The Use of Conventional Immunologic Adjuvants in DNA Vaccine Preparations. In Lowrie DB, Whalen RG (eds.). DNA Vaccines: Methods and Protocols. Methods in Molecular Medicine. 29. Humana Press. pp. 241-250.
14. Travis, K. (2007). Deciphering Immunology's Dirty Secret. The Scientist. Retrieved 10th November 2020, from https://www.the-scientist.com/uncategorized/deciphering-immunologys-dirty-secret-46896
15. Bousso, P., & Robey, E. (2003). Dynamics of CD8+ T cell priming by dendritic cells in intact lymph nodes. Nature Immunology. 4(6): 579-85.
16. Baylor, N, W., Egan, W., & Richman, P. (2002). Aluminum salts in vaccines--US perspective. Vaccine. 20(3): S18-23.
17. Tomljenovic, L. (2011). Aluminum and Alzheimer's disease: after a century of controversy, is there a plausible link? Journal of Alzheimer's disease. JAD. 23(4): 567-598.
18. Sanita, M., Ploen, D., & Kunz, K. (2014). The adjuvant component α-tocopherol triggers via modulation of Nrf2 the expression and turnover of hypocretin in vitro and its implication to the development of narcolepsy. Vaccine. 32(5): 2980-2988.
19. Petrik, M, S., Wong, M, C., Tabata, R, C., Garry, R, F., & Shaw, C, A. (2007). Aluminum adjuvant linked to Gulf War illness induces motor neuron death in mice. Neuromolecular Medicine. 9(1): 83-100.
20. Satoh, M., Kuroda, Y., Yoshida, H., Behney, K, M., Mizutani, A., Akaogi, J., Nacionales, D, C., et al. (2003). Induction of lupus autoantibodies by adjuvants. Journal of Autoimmunity. 21(1): 1-9.
21. Carlson BC, Jansson AM, Larsson A, Bucht A, Lorentzen JC (June 2000). The endogenous adjuvant squalene can induce a chronic T-cell-mediated arthritis in rats. The American Journal of Pathology. 156(6): 2057-65.
22. Richards, J, R., Elston, T, H., Ford, R, B., Gaskell, R, M., Hartmann, K., Hurley KF, Lappin MR, et al. (2006). The 2006 American Association of Feline Practitioners Feline Vaccine Advisory Panel report. Journal of the American Veterinary Medical Association. 229(9): 1405-41.
23. Kirpensteijn, J. (2006). Feline injection site-associated sarcoma: Is it a reason to critically evaluate our vaccination policies? Veterinary Microbiology. 117(1): 59-65.
24. BioNTech, Pfizer, and Fosun Pharma - BNT162b2. genengnews.com. Retrieved 10th December 2020, https://www.genengnews.com/covid-19-candidates/biontech-pfizer-and-fosun-pharma-bnt162/
25. REG 174 INFORMATION FOR UK RECIPIENTS. GOV.UK. Retrieved 10th December 2020, from https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/940566/Information_for_UK_recipients_on_Pfizer_BioNTech_COVID-19_vaccine.pdf
27. Pizzimenti, S., Heffler, E., Gentilcore, E., Raie, A., Bussolino, C., Nebiolo, F., & Rolla, G. (2014). Macrogol hypersensitivity reactions during cleansing preparation for colon endoscopy. The journal of allergy and clinical immunology. In practice. 2(3): 353-354.
28. Jakasa, I., Verberk, M. M., Esposito, M., Bos, J. D., & Kezic, S. (2007). Altered penetration of polyethylene glycols into uninvolved skin of atopic dermatitis patients. The Journal of investigative dermatology. 127(1): 129-134.
29. Borderé, A., Stockman, A., Boone, B., Franki, A.‐S., Coppens, M, J., Lapeere, H., & Lambert, J. (2012). A case of anaphylaxis caused by macrogol 3350 after injection of a corticosteroid. Contact Dermatitis. 67: 376-378.
30. Wenande, E., & Garvey, L, H. (2016). Immediate-type hypersensitivity to polyethylene glycols: a review. Clin Exp Allergy. 46(7): 907-22.
31. Hyry, H., Vuorio, A., Varjonen, E., Skytta, J., & Makinen-Kiljunen, S. (2006). Two cases of anaphylaxis to macrogol 6000 after ingestion of drug tablets. Allergy. 61(8): 1021.
32. Schuman, E., & Balsam, P, E. (1991). Probable anaphylactic reaction to polyethylene glycol electrolyte lavage solution. Gastrointest Endosc. 37(3): 411.
33. Fisher, A, A. (1978). Immediate and delayed allergic contact reactions to polyethylene glycol. Contact Dermat. 4(3): 135-8.
34. Yamasuji, Y., Higashi, Y., Sakanoue, M., Katsue, H., Kawai, K., Arai, N., & Kanekura, T. (2013). A case of anaphylaxis caused by polyethylene glycol analogues. Contact Dermatitis. 69: 183-185.
35. Wenande, E, C., Skov, P, S., Mosbech, H., Poulsen, L, K., & Garvey, L, H. (2013). Inhibition of polyethylene glycol-induced histamine release by monomeric ethylene and diethylene glycol: a case of probable polyethylene glycol allergy. The Journal of allergy and clinical immunology. 131(5): 1425-1427.
36. Pottel, J., Armstrong, D., Zou, L., Fekete, A., Huang, X.-P., Torosyan, H., Bednarczyk, D., et al. (2020). The activities of drug inactive ingredients on biological targets. Science. 369(6502): 403 LP-413.
37. Regalado, A. (2020). What are the Ingredients of Pfizer’s Covid-19 Vaccine? MIT Technology Review. Retrieved 15th December 2020, from https://www.technologyreview.com/2020/12/09/1013538/what-are-the-ingredients-of-pfizers-covid-19-vaccine/
38. Ferguson, N, M., Laydon, D., Nedjati-Gilani, G., Imai, N., Ainslie, K., Baguelin, M., Bhatia, S., et al. (2020). Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. Imperial College COVID-19 Response Team. Retrieved 10th Dec 2020, from https://www.imperial.ac.uk/media/imperial-college/medicine/mrc-gida/2020-03-16-COVID19-Report-9.pdf
39. Doshi, P. (2020). Covid-19: Do many people have pre-existing immunity? BMJ. 370 :m3563. Retrieved 10th November 2020, from https://www.bmj.com/content/370/bmj.m3563
40. Ng, K, W., Faulkner, N., Cornish, G, H., Rosa, A., Harvey, R., Hussain, S., Ulferts, R., et al. (2020). (2020). Pre-existing and de novo humoral immunity to SARS-CoV-2 in humans. BioRxiv, 2020.05.14.095414. https://doi.org/10.1101/2020.05.14.095414
41. Weiskopf, D., Schmitz, K, S., Raadsen, M, P., Grifoni, A., Okba, N, M, A., Endeman, H., Johannes P.C. van den Akker, J, P-C., et al. (2020). Phenotype of SARS-CoV-2-specific T-cells in COVID-19 patients with acute respiratory distress syndrome. MedRxiv, 2020.04.11.20062349. https://doi.org/10.1101/2020.04.11.20062349
42. Le Bert, N., Tan, A. T., Kunasegaran, K., Tham, C., Hafezi, M., Chia, A., Chng, M., et al. (2020). SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls. Nature. 584(7821): 457-462.
43. Meckiff, B, J., Ramírez-Suástegui, C., Fajardo, V., Chee, S, J., Kusnadi, A., Simon, H., Grifoni, A., et al. (2020). Single-cell transcriptomic analysis of SARS-CoV-2 reactive CD4 + T cells. bioRxiv :the preprint server for biology. 2020.06.12.148916. Retrieved 11th November 2020, https://doi.org/10.1101/2020.06.12.148916
44. Sekine, T., Perez-Potti, A., Rivera-Ballesteros, O., Strålin, K., Gorin, J-B., Olsson, A., Llewellyn-Lacey, S., et al. (2020). Robust T cell immunity in convalescent individuals with asymptomatic or mild COVID-19 [preprint]. Retrieved 12th November 2020, from https://www.biorxiv.org/content/10.1101/2020.06.29.174888v1.abstract.
45. Sette, A., & Crotty, S. (2020). Pre-existing immunity to SARS-CoV-2: the knowns and unknowns. Nat Rev Immunol. 20: 457-8. Retrieved 22nd November 2020, from doi:10.1038/s41577-020-0389-z pmid:32636479
46. Chavarria-Miró, G., Anfruns-Estrada, E., Guix, S., Paraira, M., Galofré, B., Sáanchez, G., Pintó, R., et al. (2020). Sentinel surveillance of SARS-CoV-2 in wastewater anticipates the occurrence of COVID-19 cases. MedRxiv, 2020.06.13.20129627. https://doi.org/10.1101/2020.06.13.20129627
47. Basavaraju, S. V, Patton, M. E., Grimm, K., Rasheed, M. A. U., Lester, S., Mills, L., Stumpf, M., et al. (2020). Serologic testing of U.S. blood donations to identify SARS-CoV-2-reactive antibodies: December 2019-January 2020. Clinical Infectious Diseases. https://doi.org/10.1093/cid/ciaa1785
48. Butter, M. (2020). There’s a conspiracy theory that the CIA invented the term ‘conspiracy theory’ – here’s why. The Conversation. Retrieved 20th September 2020, from https://theconversation.com/theres-a-conspiracy-theory-that-the-cia-invented-the-term-conspiracy-theory-heres-why-132117
49. Talbot, D. (2015). The devil's chessboard: Allen Dulles, the CIA, and the rise of America's secret government. Harper Collins.
50. Baquiran, M., & Al Khalili, Y. (2020). Lysergic Acid Diethylamide Toxicity. In StatPearls. StatPearls Publishing.
51. Wyatt, T. (2019). Research into deadly viruses and biological weapons at US army lab shut down over fears they could escape. The Independent. Retrieved 5th April 2020, from https://www.independent.co.uk/news/world/americas/virus-biological-us-army-weapons-fort-detrick-leak-ebola-anthrax-smallpox-ricin-a9042641.html
52. Isbell, H., Belleville, R, E., Fraser, H, F., Wikler, A., Logan, C, R. (1956). Studies on Lysergic Acid Diethylamide (LSD-25) I: Effects in Former Morphine Addicts and Development of Tolerance During Chronic Intoxication. AMA Archives of Neurology and Psychiatry. 76(5): 468-478.
53. Zubay, G, L. (2005). Agents of Bioterrorism: Pathogens and Their Weaponization. Columbia University Press. pp. 132.
54. Pittman, P, R., Norris, S, L., Coonan, K, M., & McKee, K, T., Jr. (2005). An assessment of health status among medical research volunteers who served in the Project Whitecoat program at Fort Detrick, Maryland. Military medicine. 170(3): 183-187.
55. Kinzer, S. (2019). The Secret History of Fort Detrick, the CIA’s Base for Mind Control Experiments. Politico Magazine. Retrieved 20th April 2020, from https://www.politico.com/magazine/story/2019/09/15/cia-fort-detrick-stephen-kinzer-228109
56. Hensley, L, E., Fritz, L, E., Jahrling, P, B., Karp, C, L., Huggins, J, W., & Geisbert, T, W. (2004). Interferon-beta 1a and SARS coronavirus replication. Emerging Infectious Diseases, 10(2): 317–319.
57. Lisa Hensley (microbiologist). Wikipedia. Retrieved 20th July 2020, from https://en.wikipedia.org/wiki/Lisa_Hensley_(microbiologist)
58. Patents by Inventor Lisa E. Hensley. Retrieved 20th August 2020, from https://patents.justia.com/inventor/lisa-e-hensley
59. Branswell, H. (2018). ’You’re holding your breath’: Scientists who toiled for years on an Ebola vaccine see the first one put to the test. Stat. Retrieved 20th May 2020, from https://www.statnews.com/2018/05/22/ebola-scientists-outbreak/
60. Yount, B., Curtis, K. M., Fritz, E. A., Hensley, L. E., Jahrling, P. B., Prentice, E., Denison, M, R., et al. (2003). Reverse genetics with a full-length infectious cDNA of severe acute respiratory syndrome coronavirus. Proceedings of the National Academy of Sciences. 100(22): 12995 LP-13000.
61. Transparency data. List of participants of SAGE and related sub-groups. GOV.UK. Retrieved 20th August 2020, from https://www.gov.uk/government/publications/scientific-advisory-group-for-emergencies-sage-coronavirus-covid-19-response-membership/list-of-participants-of-sage-and-related-sub-groups
62. Yan, Y., Chang, L., & Wang, L. (2020). Laboratory testing of SARS-CoV, MERS-CoV, and SARS-CoV-2 (2019-nCoV): Current status, challenges, and countermeasures. Reviews in medical virology. 30(3): e2106.
63. Summary of the effectiveness and harms of different non-pharmaceutical interventions. GOV.UK. Retrieved 10th December 2020, from https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/925854/S0769_Summary_of_effectiveness_and_harms_of_NPIs.pdf
64. Largest study on home coronavirus antibody testing publishes first findings. (2020). Imperial College Healthcare. News. Retrieved 10th December 2020, from https://www.imperial.nhs.uk/about-us/news/largest-home-antibody-testing-publishes-results
65. The official UK Government website for data and insights on Coronavirus (COVID-19). UK Summary. Retrieved 10th December 2020, from https://coronavirus.data.gov.uk
66. Ioannidis, J, P, A. (2020). Global perspective of COVID-19 epidemiology for a full-cycle pandemic. European Journal of Clinical Investigation. 50(12): e13423.
67. Zhu, Z., Lian, X., Su, X., Wu, W., Marraro, G, A., & Zeng, Y. (2020). From SARS and MERS to COVID-19: a brief summary and comparison of severe acute respiratory infections caused by three highly pathogenic human coronaviruses. Respir Res. 21: 224.
68. Estola, T. (1970). Coronaviruses, a New Group of Animal RNA Viruses. Avian Diseases. 14(2): 330-336.
69. Fabricant, J. (1998). The Early History of Infectious Bronchitis. Avian Diseases. 42(4): 648-650.
70. Weiss, S, R. (2020). Forty years with coronaviruses. J Exp Med. 2020;217:e20200537.
71. Monto, A, S. (1984). Coronaviruses. In Evans AS (ed.). Viral Infections of Humans. Viral Infections of Humans: Epidemiology and Control. Springer US. pp. 151-165.
72. Kendall, E, J., Bynoe, M, L., & Tyrrell, D, A. (1962). Virus isolations from common colds occurring in a residential school. British Medical Journal. 2(5297): 82-6.
73. Tyrrell, D, A., & Bynoe, M, L. (1965). Cultivation of a Novel Type of Common-Cold Virus in Organ Cultures. British Medical Journal. 1(5448): 1467-70.
74. Tyrrell, D, A., & Fielder, M. (2002). Cold Wars: The Fight Against the Common Cold. Oxford University Press. pp. 93-95.
75. Gonzalez, J, M., Gomez-Puertas, P., Cavanagh, D., Gorbalenya, A, E., & Enjuanes, L. (2003). A comparative sequence analysis to revise the current taxonomy of the family Coronaviridae. Arch. Virol. 148(11): 2207-2235.
76. Weiss, S, R., & Navas-Martin, S. (2005). Coronavirus pathogenesis and the emerging pathogen severe acute respiratory syndrome coronavirus. Microbiol. Mol. Biol. Rev. 69(4): 635-664.
77. Bradburne, A, F., Bynoe, M, L., & Tyrrell, D, A. (1967). Effects of a ‘new’ human respiratory virus in volunteers. Br. Med. J. 3(5568): 767-769.
78. vander Hoek, L. (2007). Human coronaviruses: what do they cause? Antivir.Ther.12(4): 651-658.
79. van der Hoek, L., Pyrc, K., Jebbink, M, F., Vermeulen-Oost, W., Berkhout, R, J., Wolthers, K, C., Wertheim-van, P, M., et al. (2004). Identification of a new human coronavirus. Nat. Med. 10(4): 368-373.
80. Woo, P, C., Lau, S, K. K., Chu, C, M., Chan, K, H., Tsoi, H, W., Huang, Y., Wong, B, H., et al. 2005. Characterization and complete genome sequence of a novel coronavirus, coronavirus HKU1, from patients with pneumonia. J. Virol. 79(2): 884-895.
81. Kahn, J, S., & McIntosh, K. (2005). History and recent advances in coronavirus discovery. The Pediatric Infectious Disease Journal. 24(11): S223-7, discussion S226.
82. Kendall, E, J., Bynoe, M, L., & Tyrrell, D, A. (1962). Virus isolations from common colds occurring in a residential school. British Medical Journal. 2 (5297): 82-6.
83. Tyrrell, D, A., & Bynoe, M, L. (1965). Cultivation of a Novel Type of Common-Cold Virus in Organ Cultures. British Medical Journal. 1(5448): 1467-70.
84. Hamre, D., & Procknow, J, J. (1966). A new virus isolated from the human respiratory tract. Proceedings of the Society for Experimental Biology and Medicine. Society for Experimental Biology and Medicine. 121(1): 190-3.
85. Jiang, S., Hillyer, C., & Du, L. (2020). Neutralizing Antibodies against SARS-CoV-2 and Other Human Coronaviruses. Trends in Immunology. 41(5): 355-359.
86. Sparks, M. A., Crowley, S, D., Gurley, S, B., Mirotsou, M., & Coffman, T, M. (2014). Classical Renin-Angiotensin system in kidney physiology. Comprehensive Physiology. 4(3): 1201-1228.
87. Zimmerman, B, G., & Dunham, E, W. (1997). Tissue renin–angiotensin system: a site of drug action? Annu. Rev. Pharmacol. Toxicol. 37: 53-69.
88. Fleming, I., Kohlstedt, K., & Busse, R. (2006). The tissue renin–angiotensin system and intracellular signalling. Curr. Opin. Nephrol. Hypertens. 15(1): 8-13.
89. Nicholls, M, G., Richards, A, M., & Agarwal, M. (1998). The importance of the renin–angiotensin system in cardiovascular disease. J. Hum. Hypertens. 12(5): 295-299.
90. Batenburg, W, W., & Jan-Danser, A, H. (2008). The (pro)renin receptor: a new addition to the renin–angiotensin system? Eur. J. Pharmacol. 585(2–3): 320-324.
91. Hackenthal, E., Paul, M., Ganten, D., & Taugner, R. (1990). Morphology, physiology, and molecular biology of renin secretion. Physiol. Rev. 70(4): 1067-1116.
92. Paul, M., &Poyan-Mehr, A., & Kreutz, R. (2006). Physiology of local renin–angiotensin systems. Physiol. Rev. 86(3): 747-803.
93. Kurdi, M., De Mello, W, C., & Booz, G, W. (2005). Working outside the system: an update on the unconventional behavior of the renin–angiotensin system components. Int. J. Biochem. Cell Biol. 37(7): 1357-1367.
94. Lindberg, B, F., Gyllstedt, E., Andersson, K, E. (1997). Conversion of angiotensin I to angiotensin II by chymase activity in human pulmonary membranes. Peptides. 18(6): 847-853.
95. Veerappan, A., Reid, A. C., Estephan, R., Connor, N., Thadani-Mulero, M., Salazar-Rodriguez, M., Levi, R., et al. (2008). Mast cell renin and a local renin–angiotensin system in the airway: Role in bronchoconstriction. Proceedings of the National Academy of Sciences, 105(4): 1315LP-1320.
96. Andersson, C, K., Mori, M., Bjermer, L., Lofdahl, C, G., Erjefalt, J, S. (2009). Novel site-specific mast cell subpopulations in the human lung. Thorax. 64(4): 297-305.
97. Boyce, J, A. (2003). The role of mast cells in asthma. Prostaglandins Leukot. Essent. Fatty Acids. 69(2–3): 195-205.
98. Studdy, P, R., Lapworth, R., & Bird, R. (1983). Angiotensin-converting enzyme and its clinical significance - a review. J. Clin. Pathol. 36(8): 938-947.
99. Bullock, G. R., Steyaert, I., Bilbe, G., Carey, R. M., Kips, J., De Paepe, B., Pauwels, R., et al. (2001). Distribution of type-1 and type-2 angiotensin receptors in the normal human lung and in lungs from patients with chronic obstructive pulmonary disease. Histochemistry and Cell Biology. 115(2): 117-124.
100. Hamming, I., Timens, W., Bulthuis, M, L., Lely, A, T., Navis, G, J., & van Goor, H. (2004). Tissue distribution of ACE2 protein, the functional receptor for SARS coronavirus. A first step in understanding SARS pathogenesis. J. Pathol. 203(2): 631-637.
101. Wang, W., O’Connell, B., Dykeman, R., Sakai, T., Delporte, C., Swaim, W., et al. (1999). Angiotensin II induces apoptosis in human and rat alveolar epithelial cells. Am. J. Physiol. 276(5 Pt 1): L885-L889.
102. Papp, M., Li, X., Zhuang, J., Wang, R., & Uhal, B, D. (2002). Angiotensin receptor subtype AT(1) mediates alveolar epithelial cell apoptosis in response to ANG II. Am. J. Physiol. Lung Cell Mol. Physiol. 282(4): L713-L718.
103. Ferrario, C, M., Trask, A, J., Jessup, J, A. (2005). Advances in biochemical and functional roles of angiotensin-converting enzyme 2 and angiotensin-(1–7) in regulation of cardiovascular function. Am. J. Physiol. Heart Circ. Physiol. 289(6): H2281-H2290.
104. Hamming, I., Cooper, M, E., Haagmans, B, L., Hooper, N, M., Korstanje, R., Osterhaus, A., Timens, W., et al. (2007). The emerging role of ACE2 in physiology and disease. J. Pathol. 212(1): 1–11.
105. Kuba, K., Imai, Y., & Penninger, J, M. (2006). Angiotensin-converting enzyme 2 in lung diseases. Curr. Opin. Pharmacol. 6(3): 271-276.
106. Csaszar, A., Halmos, B., Palicz, T., Szalai, C., & Romics, L. (1997). Interpopulation effect of ACE I/D polymorphism on serum concentration of ACE in diagnosis of sarcoidosis. Lancet. 350(9076): 518.
107. Idell, S., Kueppers, F., Lippmann, M., Rosen, H., Niederman, M., & Fein, A. (1987). Angiotensin converting enzyme in bronchoalveolar lavage in ARDS. Chest. 91(1): 52-56.
108. Orte, C., Polak, J, M., Haworth, S, G., Yacoub, M, H., & Morrell, N, W. (2000). Expression of pulmonary vascular angiotensin-converting enzyme in primary and secondary plexiform pulmonary hypertension. J. Pathol. 192(3): 379-384.
109. Imai, Y., Kuba, K., Rao, S., Huan, Y., Guo, F., Guan, B., Yang, P., et al. (2005). Angiotensin-converting enzyme 2 protects from severe acute lung failure. Nature. 436(7047): 112-116.
110. Ware, L, B., & Matthay, M, A. (2000). The acute respiratory distress syndrome. N. Engl. J. Med. 342(18): 1334-1349.
111. Rubenfeld, G, D., Caldwell, E., Peabody, E., Weaver, J., Martin, D, P., Neff, M., Stern, E, J., et al. (2005). Incidence and outcomes of acute lung injury. N. Engl. J. Med. 353(16): 1685-1693.
112. Raiden, S., Nahmod, K., Nahmod, V., Semeniuk, G., Pereira, Y., Alvarez, C., Giordano, M., et al. (2002). Nonpeptide antagonists of AT1 receptor for angiotensin II delay the onset of acute respiratory distress syndrome. J. Pharmacol. Exp. Ther. 303(1): 45-51.
113. Nicholls, J., & Peiris, M. (2005). Good ACE, bad ACE do battle in lung injury, SARS. Nat. Med. 11(8): 821-822.
114. Chan-Yeung, M., & Xu, R, H. (2003). SARS: epidemiology. Respirology. 8(1): S9-14.
115. Chan, P, K, S., Wing-Kin, T., King-Cheung, N., Lam, R, K, Y., Tak-Keung, N., Chan, R, C, W., Wu, A., et al. (2004). Laboratory Diagnosis of SARS. Emerging Infectious Diseases. 10(5): 825-31.
116. Monaghan, K, J. (2004). SARS: Down But Still a Threat. National Academies Press (US).
117. Li, W., Moore, M, J., Vasilieva, N., Sui, J., Wong, S, K., Berne, M, A., Somasundaran, M., et al. (2003). Angiotensin-converting enzyme 2 is a functional receptor for the SARS coronavirus. Nature. 426(6965): 450-454.
118. Kuba, K., Imai, Y., Rao, S., Gao, H., Guo, F., Guan, B., Huan, Y., et al. (2005). A crucial role of angiotensin converting enzyme 2 (ACE2) in SARS coronavirus-induced lung injury. Nature medicine. 11(8): 875-879.
119. Frieman, M., & Baric, R. (2008). Mechanisms of severe acute respiratory syndrome pathogenesis and innate immunomodulation. Microbiol. Mol. Biol. Rev. 72(4): 672-685.
120. Nicholls, J., & Peiris, M. (2005). Good ACE, bad ACE do battle in lung injury, SARS. Nat. Med.11(8): 821-822.
121. Toelzer, C., Gupta, K., Yadav, S, K, N., Borucu, U., Davidson, A, D., Kavanagh Williamson, M., Shoemark, D. K., et al. (2020). Free fatty acid binding pocket in the locked structure of SARS-CoV-2 spike protein. Science. 370(6517): eabd3255.
122. Ling, P, R., Malkan, A., Le, H, D., Puder, M., & Bistrian, B, R. (2012). Arachidonic acid and docosahexaenoic acid supplemented to an essential fatty acid-deficient diet alters the response to endotoxin in rats. Metabolism: clinical and experimental. 61(3): 395-406.
123. Bursten, S, L., Federighi, D, A., Parsons, P., Harris, W. E., Abraham, E., Moore, E, E., Jr, Moore, F, A., et al. (1996). An increase in serum C18 unsaturated free fatty acids as a predictor of the development of acute respiratory distress syndrome. Critical care medicine. 24(7): 1129-1136.
124. Craig, B. (Unpublished). Controlling Intuitive Appetite. WWBS Publishing. London.
125. Hanna, V, S., & Hafez, E, A, A. (2018). Synopsis of arachidonic acid metabolism: A review. Journal of Advanced Research. 11: 23-32.
126. Malcom, G, T., Bhattacharyya, A, K., Velez-Duran, M., Guzman, M, A., Oalmann, M, C., & Strong, J, P. (1989). Fatty acid composition of adipose tissue in humans: differences between subcutaneous sites. The American journal of clinical nutrition. 50(2): 288-291.
127. Mamalakis, G., Kafatos, A., Manios, Y., Kalogeropoulos, N., & Andrikopoulos, N. (2002). Abdominal vs buttock adipose fat: relationships with children's serum lipid levels. European journal of clinical nutrition. 56(11): 1081-1086.
128. Pittet, P, G., Halliday, D., & Bateman, P, E. (1979). Site differences in the fatty acid composition of subcutaneous adipose tissue of obese women. The British journal of nutrition. 42(1): 57-61.
129. Phinney, S, D., Stern, J, S., Burke, K, E., Tang, A, B., Miller, G., & Holman, R, T. (1994). Human subcutaneous adipose tissue shows site-specific differences in fatty acid composition. The American journal of clinical nutrition. 60(5): 725-729.
130. El-Kurdi, B., Khatua, B., Rood, C., Snozek, C., Cartin-Ceba, R., Singh, V, P., & Group, L. in C.-19 S. (2020). Mortality From Coronavirus Disease 2019 Increases With Unsaturated Fat and May Be Reduced by Early Calcium and Albumin Supplementation. Gastroenterology. 159(3): 1015-1018.
131. Whelan, J., & Fritsche, K. (2013). Linoleic acid. Advances in Nutrition (Bethesda, Md.). 4(3): 311-312.
132. Food and Nutrition Board, Institute of Medicine. Dietary Fats: Total Fat and Fatty Acids. Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids. Washington, D.C.: National Academies Press. (2002): pp. 422-541.
133. Varsano, S., Rashkovsky, L., Shapiro, H., Ophir, D., & Mark-Bentankur, T. (1998). Human lung cancer cell lines express cell membrane complement inhibitory proteins and are extremely resistant to complement-mediated lysis; a comparison with normal human respiratory epithelium in vitro, and an insight into mechanism(s) of resistance. Clinical and Experimental Immunology. 113(2): 173-182.
134. Ling, G. (2007). History of the membrane (pump) theory of the living cell from its beginning in mid-19th century to its disproof 45 years ago--though still taught worldwide today as established truth. Physiological chemistry and physics and medical NMR. 39(1): 1-67.
135. Snell, N, J, C. (2001). New treatments for viral respiratory tract infections-opportunities and problems. Journal of Antimicrobial Chemotherapy. 47: 251-259.
136. Peat, R. (2013). Fats, functions & malfunctions. Retrieved 22nd August 2020, from http://raypeat.com/articles/articles/fats-functions-malfunctions.shtml
137. Canbay, A., Bechmann, L., & Gerken, G. (2007). Lipid metabolism in the liver. Zschr. Gastroenterol. 45: 35-41.
138. Cook, J, A., Wise, W, C., Knapp, D, R., & Halushka, P, V. (1981). Essential fatty acid deficient rats: a new model for evaluating arachidonate metabolism in shock. Advances in shock research. 6: 93-105.
139. Li, E, J., Cook, J, A., Spicer, K, M., Wise, W, C., Rokach, J., & Halushka, P, V. (1990). Resistance of essential fatty acid-deficient rats to endotoxin-induced increases in vascular permeability. Circulatory shock. 31(2): 159-170.
140. Autore, G., Cicala, C., Cirino, G., Maiello, F, M., Mascolo, N., & Capasso, F. (1994). Essential fatty acid-deficient diet modifies PAF levels in stomach and duodenum of endotoxin-treated rats. Journal of lipid mediators and cell signalling. 9(2): 145-153.
141. Craig, B. (Unpublished). Therapeutic Carbon Dioxide. WWBS Publishing. London.
142. Morganroth, M. L., Schoeneich, S. O., Till, G. O., Pickett, W., & Ward, P. A. (1989). Lung injury caused by cobra venom factor is reduced in rats raised on an essential fatty acid-deficient diet. The American journal of physiology. 257(4 Pt 2): H1192-H1199.
143. Craig, B. (2020). Consistent Eating. WWBS Publishing. London.
144. Chiu, R, W., Tang, N, L., Hui, D, S., Chung, G, T, Y., Chim, S, S, C., Chan, K, C, A., Ying-man Sung, Y-M., et al. (2004). ACE2 gene polymorphisms do not affect outcome of severe acute respiratory syndrome. Clin. Chem.50(9): 1683–1686.
145. Itoyama, S., Keicho, N., Hijikata, M., Quy, T., Phi, N, C., Long, H, T., Le Dang, H., et al. (2005). Identification of an alternative 5´-untranslated exon and new polymorphisms of angiotensin-converting enzyme 2 gene: lack of association with SARS in the Vietnamese population. Am. J. Med. Genet. A. 136(1): 52-57.
146. Weidmann, P., De Myttenaere-Bursztein, S., Maxwell, M, H., & de Lima, J. (1975). Effect on aging on plasma renin and aldosterone in normal man. Kidney Int. 8(5): 325-333.
147. Corman, B., Barrault, M, B., Klingler, C., Houot, A, M., Michel, J, B., Della Bruna, R., Pinet, F., et al. (1995). Renin gene expression in the aging kidney: effect of sodium restriction. Mech. Ageing Dev. 84(1): 1-13.
148. Cameron, M, J., Bermejo-Martin, J, F., Danesh, A., Muller, M, P., & Kelvin, D, J. (2008). Human immunopathogenesis of severe acute respiratory syndrome (SARS). Virus Res. 133(1): 13-19.
149. Brown, N, J., & Vaughan, D, E. (2000). Prothrombotic effects of angiotensin. Advances in internal medicine. 45: 419-429.
150. Kubo, M., Quayle, J, M., & Standen, N, B. (1997). Angiotensin II inhibition of ATP-sensitive K+ currents in rat arterial smooth muscle cells through protein kinase C. The Journal of Physiology. 503(3): 489-496.
151. Lalchhandama, K. (2020). The chronicles of coronaviruses: the electron microscope, the doughnut, and the spike. Science Vision. 20(2): 78-92.
152. Neuman, B, W., Kiss, G., Kunding, A, H., Bhella, D., Baksh, M, F., Connelly S., Droese, B., et al. (April 2011). A structural analysis of M protein in coronavirus assembly and morphology. Journal of Structural Biology. 174 (1): 11-22.
153. Zitek, T. (2020). The Appropriate Use of Testing for COVID-19. The western journal of emergency medicine. 21(3): 470-472.
154. Lai, M, M., & Cavanagh, D. (1997). The molecular biology of coronaviruses. Advances in Virus Research. 48: 1-100.
155. Cepheid Innovation Technical Datasheet. Retrieved 12th December 2020, from https://www.cepheid.com/coronavirus
156. Gupta, S. (2020). Matt Hancock is wrong about herd immunity. Unherd. Retrieved 20th November 2020, from https://unherd.com/2020/10/matt-hancock-is-wrong-about-herd-immunity/
156. Centers for Disease Control. Coronavirus Symptoms. Retrieved 20th September 2020, from https://www.cdc.gov/coronavirus/2019-ncov/about/symptoms.html
157. Human Disease Case Fatality Rate. Wikipedia. Retrieved 12th July 2020, from https://en.wikipedia.org/wiki/List_of_human_disease_case_fatality_rates
158. Chest CT for Typical 2019-nCoV Pneumonia: Relationship to Negative RT-PCR Testing: Radiology. https://doi.org/10.1148/radiol.2020200343. Accessed 12th March, 2020.
159. Time Course of Lung Changes On Chest CT During Recovery From 2019 Novel Coronavirus (Covid-19) Pneumonia: Radiology. https://doi.org/10.1148/radiol.2020200370. Accessed 12th March, 2020.
160. U.S. Food and Drug Administration: https://www.fda.gov/news-events/press-announcements/fda-takes-significant-step-coronavirus-response-efforts-issues-emergency-use-authorization-first?utm_campaign=020420_PR_FDA%20Issues%20EUA%20for%20First%202019%20Novel%20Coronavirus%20Diagnostic&utm_medium=email&utm_source=Eloqua. Accessed 12th March, 2020.
161. Public Health News Alert: CMS Develops New Code for Coronavirus Lab Test. https://www.cms.gov/. Accessed 12th March, 2020.
162. Borst, A., Box, A,T., Fluit, A,C. (2004). False-positive results and contamination in nucleic acid amplification assays: suggestions for a prevent and destroy strategy. Eur J Clin Microbiol Infect Dis. 23(4): 289-99.
163. Cheng, S., Fockler, C., Barnes, W, M., & Higuchi, R. (1994). Effective Amplification of Long Targets from Cloned Inserts and Human Genomic DNA. Proceedings of the National Academy of Sciences. 91(12): 5695-5699.
164. Hillman, H. (1989). Uncertainties, artifacts, uncontrolled experiments and incomplete evidence in modern biology. Physiol Chem Phys Med NMR. 21(2): 145-60; discussion 160-3.
165. Corman, V, M., Landt, O., Kaiser, M., Molenkamp, R., Meijer, A., Chu, D, K, W., Bleicker, T., et al. (2020). Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Eurosurveillance. 25(3): 23/Jan/2020. Accessed 12th March, 2020 https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2020.25.3.2000045
166. Chu, D, K, W., Pan, Y., Cheng, S, M, S., Hui, K, P, Y., Krishnan, P., Liu, Y., … Poon, L, L, M. (2020). Molecular Diagnosis of a Novel Coronavirus (2019-nCoV) Causing an Outbreak of Pneumonia. Clinical Chemistry. https://doi.org/10.1093/clinchem/hvaa029
167. Wang, M., Wu, Q., Xu, W., Qiao, B., Wang, J., Zheng, H., Jiang, S., et al. (2020). Clinical diagnosis of 8274 samples with 2019-novel coronavirus in Wuhan. MedRxiv, 2020.02.12.20022327. https://doi.org/10.1101/2020.02.12.20022327
168. Semendeferi, I. (2008). Legitimating a Nuclear Critic: John Gofman, Radiation Safety, and Cancer Risks", Historical Studies in the Natural Sciences. 38(2): 300.
169. Linnane, C. (2020). Inovio shares rally after biotech says human trials of coronavirus vaccine will start in April. Market Watch. Retrieved 20th June 2020, from https://www.marketwatch.com/story/inovio-shares-rally-after-biotech-says-human-trials-of-coronavirus-vaccine-will-start-in-april-2020-03-03
170. Mandel, D, R. (2014). The psychology of Bayesian reasoning. Frontiers in Psychology. 5: 1144.
171. Eddy, D, M. (1982). Probabilistic reasoning in clinical medicine: problems and opportunities, in Judgment under Uncertainty: Heuristics and Biases, eds Kahneman D., Slovic P., Tversky A., editors. New York, NY: Cambridge University Press. pp. 249-267.
172. Casscells, W., Schoenberger, A., & Graboys, T, B. (1978). Interpretation by physicians of clinical laboratory results. N Engl J Med. 299(18): 999-1001.
173. Zhang, J, J., Dong, X., Cao, Y, Y., Yuan, Y, D., Yang, Y, B., Yan, Y, Q., Akdis, C, A., & Gao, Y, D. (2020). Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China. Allergy. 75(7): 1730-1741.
174. Jefferson, T., Spencer, E, A., Brassey, J., & Heneghan, C. (2020). Viral cultures for COVID-19 infectivity assessment – a systematic review. In: Analysis of the Transmission Dynamics of COVID-19: An Open Evidence Review. Retrieved 10th November 2020, from https://www.medrxiv.org/content/10.1101/2020.08.04.20167932v3.full.pdf
175. Schraer, R. (2020). Coronavirus: Tests 'could be picking up dead virus’. BBC News. Retrieved 10th December 2020, https://www.bbc.co.uk/news/health-54000629
176. Gniazdowski, V., Morris, C, P., Wohl, S., Mehoke, T., Ramakrishnan, S., Thielen, P., Powell, H., et al. (2020). Repeat COVID-19 Molecular Testing: Correlation with Recovery of Infectious Virus, Molecular Assay Cycle Thresholds, and Analytical Sensitivity. MedRxiv, 2020.08.05.20168963. Retrieved 9th December 2020, from https://doi.org/10.1101/2020.08.05.20168963
177. Public Health England. Understanding cycle threshold (Ct) in SARS-CoV-2 RT-PCR A guide for health protection teams. GOV.UK. Retrieved 10th November 2020, from https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/926410/Understanding_Cycle_Threshold__Ct__in_SARS-CoV-2_RT-PCR_.pdf
178. Sekine, T., Perez-Potti, A., Rivera-Ballesteros, O., Strålin, K., Gorin, J.-B., Olsson, A., Llewellyn-Lacey, S., et al. (2020). Robust T cell immunity in convalescent individuals with asymptomatic or mild COVID-19. BioRxiv, 2020.06.29.174888. https://doi.org/10.1101/2020.06.29.174888
179. Gallais, F., Velay, A., Wendling, M.-J., Nazon, C., Partisani, M., Sibilia, J., Candon, S., et al. (2020). Intrafamilial Exposure to SARS-CoV-2 Induces Cellular Immune Response without Seroconversion. MedRxiv. 2020.06.21.20132449. https://doi.org/10.1101/2020.06.21.20132449
180. Long, Q, X., Tang, X, J., Shi, Q, L., Li, Q., Deng, H, J., Yuan, J., Hu, J, L., et al. (2020). Clinical and immunological assessment of asymptomatic SARS-CoV-2 infections. Nature medicine. 26(8): 1200-1204.
181. Seow, J., Graham, C., Merrick, B., Acors, S., Steel, K, J, A., Hemmings, O., O’Bryne, A., et al. (2020). Longitudinal evaluation and decline of antibody responses in SARS-CoV-2 infection preprint. MedRxiv. 2020. Retrieved 10th December 2020, from https://www.medrxiv.org/content/10.1101/2020.07.09.20148429v1.
182. Research and analysis. COG-UK: Summary report of COVID-19 reinfection, 3 September 2020. GOV.UK Retrieved 20th November 2020, from https://www.gov.uk/government/publications/cog-uk-summary-report-of-covid-19-reinfection-3-september-2020
183. Mandavilli, A. (2020). You may have antibodies after coronavirus infection. But not for long. New York Times. Retrieved 20th August 2020, from https://www.nytimes.com/2020/06/18/health/coronavirus-antibodies.html
184. Le Bert, N., Tan, A. T., Kunasegaran, K., Tham, C., Hafezi, M., Chia, A., Chng, M., et al. (2020). SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls. Nature. 584(7821): 457-462.
185. Altmann, D, M., & Boyton, R, J. (2020). SARS-CoV-2 T cell immunity: Specificity, function, durability, and role in protection. Science Immunology. 5(49): eabd6160. Retrieved 20th November 2020, from https://doi.org/10.1126/sciimmunol.abd6160
186. A study to evaluate efficacy, safety, and immunogenicity of mRNA-1273 vaccine in adults aged 18 years and older to prevent COVID-19. Retrieved 15th December 2020, from https://clinicaltrials.gov/ct2/show/NCT04470427.
187. Study to describe the safety, tolerability, immunogenicity, and efficacy of RNA vaccine candidates against COVID-19 in healthy adults. Retrieved 15th December 2020, from https://www.clinicaltrials.gov/ct2/show/NCT04368728
188. A Phase 1/2/3, placebo-controlled, randomised, observer-blind, dose-finding study to evaluate the safety, tolerability, immunogenicity, and efficacy or SARS-CoV-2 RNA Vaccine candidates against Covid-19 in healthy individuals. PF-07302048 (BNT162 RNA-Based COVID-19 Vaccines) Protocol C4591001. pp. 28. Retrieved 9th December 2020, from https://pfe-pfizercom-d8-prod.s3.amazonaws.com/2020-11/C4591001_Clinical_Protocol_Nov2020.pdf
189. ModernaTX, Inc. 20 Aug 2020 Protocol mRNA-1273-P301, Amendment 3. Retrieved 9th November 2020, from https://www.modernatx.com/sites/default/files/mRNA-1273-P301-Protocol.pdf
190. A Randomized, Double-blind, Placebo-controlled Phase 3 Study to Assess the Efficacy and Safety of Ad26.COV2.S for the Prevention of SARS-CoV-2-mediated COVID-19 in Adults Aged 18 Years and Older. Retrieved 9th December 2020, from https://www.jnj.com/coronavirus/covid-19-phase-3-study-clinical-protocol
191. A Phase III Randomized, Double-blind, Placebo-controlled Multicenter Study in Adults to Determine the Safety, Efficacy, and Immunogenicity of AZD1222, a Non-replicating ChAdOx1 Vector Vaccine, for the Prevention of COVID-19. Retrieved 9th December 2020, from https://s3.amazonaws.com/ctr-med-7111/D8110C00001/52bec400-80f6-4c1b-8791-0483923d0867/c8070a4e-6a9d-46f9-8c32-cece903592b9/D8110C00001_CSP-v2.pdf
192. Normal Saline. Generic Name: sodium chloride injection. RXList.com. Retrieved 10th December 2020, from https://www.rxlist.com/normal-saline-side-effects-drug-center.htm
193. Bar-Or, D., Rael, L, T., & Brody, E, N. (2017). Use of Saline as a Placebo in Intra-articular Injections in Osteoarthritis: Potential Contributions to Nociceptive Pain Relief. The Open Rheumatology Journal. 11: 16-22.
194. Wu, F., Zhao, S., Yu, B., Chen, Y, M., Wang, W., Song, Z, G., Hu, Y., et al. (2020). A new coronavirus associated with human respiratory disease in China. Nature. 579(7798): 265-269.
195. Borger, P., Malhotra, B, R., Yeadon, M., Craig, C., McKernan, K., Steger, K., McSheehy, P., et al. (2020).External peer review of the RTPCR test to detect SARS-CoV-2 reveals 10 major scientific flaws at the molecular and methodological level: consequences for false positive results. Eurosurveillance. Retrieved 30th November 2020, from https://cormandrostenreview.com/report
196. TWiV 641: COVID-19 with Dr. Anthony Fauci. YouTube. Retrieved https://youtu.b/a_Vy6fgaBPE
197. Stewart, P., & Ali, I. (2020). Coronavirus clue? Most cases aboard U.S. aircraft carrier are symptom-free. Reuters. Retrieved 10th January 2020, from https://www.reuters.com/article/us-health-coronavirus-usa-military-sympt/coronavirus-clue-most-cases-aboard-us-aircraft-carrier-are-symptom-free-idUSKCN21Y2GB
198. Conis, E. (2017). Polio, DDT, and Disease Risk in the United States after World War II. Environmental History. 22(4): 696-721.
199. Polio: A 20th Century Epidemic. Science Museum. Retrieved 20th November 2020, from https://www.sciencemuseum.org.uk/objects-and-stories/medicine/polio-20th-century-epidemic
200. Alcalá H. (1993). Diagnóstico diferencial de la poliomielitis y otras parálisis flácidas agudas [The differential diagnosis of poliomyelitis and other acute flaccid paralyses]. Boletin medico del Hospital Infantil de Mexico. 50(2): 136-144.
201. James, W. (1995). Immunization The Reality Behind the Myth. Greenwood Publishing Group. pp. 36.
202. Halstead, L, S., & Silver, J, K. (2000). Nonparalytic polio and postpolio syndrome. American journal of physical medicine & rehabilitation. 79(1): 13-18.
203. Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497-506. Epub 2020/01/28. doi: 10.1016/S0140- 6736(20)30183-5.
204. Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., et al. (2020). Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 395(10223): 507-13.
205. Guan, W, J., Ni, Z, Y., Hu, Y., Liang, W,H., Ou, C, Q., He, J, X., et al. (2020. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. Epub 2020/02/29. doi: 10.1056/NEJMoa2002032. PubMed PMID: 32109013.
206. Nosek, B, A., & Errington, T, M. (2020). What is replication?. PLOS Biology 18(3): e3000691.
207. Ioannidis, J, A. (2005). Contradicted and initially stronger effects in highly cited clinical research. JAMA. 294(2): 218-228.
208. Baker, M. (2016). 1,500 scientists lift the lid on reproducibility. Nature. 533(7604): 452-454.
209. Ioannidis, J, P, A. (2016). Why Most Clinical Research Is Not Useful. PLOS Med. 13(6): e1002049.
210. Matthews, S. (2018). Killer flu outbreak is to blame for a 42% spike in deaths in January after 64,000 people died - the highest number since records began. Daily Mail. Retrieved 20th December 2020, from https://www.dailymail.co.uk/health/article-5440785/Killer-flu-outbreak-blame-42-spike-deaths.html
211. Lourenço, J., Paton, R., Ghafari, M., Kraemer, M., Thompson, C., Simmonds, P., Klenerman, P., et al. (2020). Fundamental principles of epidemic spread highlight the immediate need for large-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic. Department of Zoology, 2 Nuffield Department of Medicine, University of Oxford, Peter Medawar Building for Pathogen Research, Oxford, United Kingdom. Retrieved 20th June 2020, from https://www.medrxiv.org/content/10.1101/2020.03.24.20042291v1.full.pdf
212. Bendavid, E., Mulaney, B., Sood, N., Shah, S., Ling, E., Bromley-Dulfano, R., Lai, C., et al. (2020). COVID-19 Antibody Seroprevalence in Santa Clara County, California. MedRxiv, 2020.04.14.20062463. Retrieved 27th August 2020, from https://doi.org/10.1101/2020.04.14.20062463
213. Falahi, S., & Kenarkoohi, A. (2020). COVID-19 reinfection: prolonged shedding or true reinfection? New Microbes and New Infections. 38: 100812. Retrieved 29th December 2020, from https://doi.org/https://doi.org/10.1016/j.nmni.2020.100812
214. Reuters. Coronavirus: Japanese woman tests positive for second time. The Guardian. Retrieved 23rd May 2020, from https://www.theguardian.com/world/2020/feb/27/japanese-woman-tests-positive-for-coronavirus-for-second-time
215. Prado-Vivar, B., Becerra-Wong, M., Guadalupe, J, J., Marquez, S., Gutierrez, B., Rojas-Silva, P., Grunauer, M., et al. (2020). COVID-19 re-infection by a phylogenetically distinct SARS-CoV-2 variant, first confirmed event in South America. SSRN. Retrieved 8th September 2020, from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3686174
216. Whipple, T. (2020). Superforecasters have bright future, predicts Dominic Cummings’ favourite academic Philip Tetlock. The Times. Retrieved 20th March 2020, from https://www.thetimes.co.uk/article/superforecasters-still-have-bright-future-predicts-academic-popular-with-cummings-ddzqsqwtc
This article focuses upon the vaccine trials which have not set out to prove efficacy in preventing mortality or viral transmission, and on the reactionary "science" that broke out as the pandemic unfolded and has not been updated as things became clearer.
Product Type: Vaccine
Item Code (Source): NDC: 59267-1000
Administration: Intramuscular
Ingredients: RNA ingredient BNT-162B2 (UNII: 5085ZFP6S) (RNA ingredient BNT-162B2 - UNII:5085ZFP6S)
Basis of Strength: RNA ingredient BNT-162B2
Strength: 0.23 grams in 1.8 millilitres
lipid ALC-0159 (UNII: PJH39UMU6H)
lipid ALC-0315 (UNII: AVX8DX713V)
POTASSIUM CHLORIDE (UNII: 660YQ98I10)
MONOBASIC POTASSIUM PHOSPHATE (UNII: 4J9FJ0HL51)
SODIUM CHLORIDE (UNII: 451W47IQ8X)
SODIUM PHOSPHATE, DIBASIC, UNSPECIFIED FORM (UNII: GR686LBA74)
SUCROSE (UNII: C151H8M554)
The Covid-19 pandemic brought about an almost immediate discussion around the prospects for vaccination against the virus responsible for the cluster of symptoms classified as Covid-19, the now infamous SARS-CoV-2. Researchers around the globe working for various research institutions and pharmaceutical companies began work, a lot of early research was based upon prior work regarding SARS-CoV-1, the one most of us have either forgotten or were not too aware of with the lack of internet based media outlets. Throughout the Spring, Summer and beyond “experts” and government ministers have promised that if all goes well, an “effective” vaccine may be achieved by *insert various dates here.*
SARS-CoV-1 or severe acute respiratory syndrome, referred to as SARS (it never managed to gain the title Covid-02) had approximately 100 cases out of 8096-8422 total cases and no deaths in the United Kingdom, and MERS-CoV had 31 cases out of a total of 2449 and two U.K. deaths. Globally at least 774-916 deaths occurred (1), giving a case fatality rate of 11 percent (2), which in theory suggest it to be highly lethal, despite this it ultimately seemingly mysteriously vanished. Coronaviruses as previously discussed are a large family of viruses, ranging from the common cold to more severe diseases, including the novel coronavirus, including SARS and SARS-CoV-2.
SARS, the 21st Centuries first pandemic, was initially identified in China’s Guangdong province, in late 2002, by medical practitioners who became aware of an “unusual” pneumonia, but did not report it to the World Health Organization (WHO). In early 2003 an outbreak in Hanoi, Vietnam, involving a WHO officer that later died, reported on a large outbreak on the 10th March.
A physician that travelled from the Guangdong province to Hong Kong, while infected with SARS and stayed at the Metropol Hotel, reportedly transmitting the virus around a dozen guests, three returned to Singapore, two of whom then returned home to Canada, one to Vietnam, one to Ireland, one to the United States and thus SARS began its spread around much of the globe but with the majority of cases occurring in Asia.
SARS was described as both aggressive and with a high lethality, symptoms were typically reported within two to three days and with limited reports infections in absence of symptoms. One must recall variances in test capacity in regards to total cases, when comparing SARS and SARS-CoV-2. The recent pandemic has seen Covid-19 testing reach biblical scales, with the United States alone, as of December 2, 2020 performing >196 million tests for Covid-19. (3)
In April 2003 the WHO suggested laboratory diagnostics tests, stating that;
“researchers in several countries are working towards developing fast and accurate laboratory diagnostic tests for the SARS coronavirus (SARS-CoV). However, until standardised reagents for virus and antibodies detection are available and methods have been adequately field tested, SARS diagnosis remains based on the clinical and epidemiological findings: acute febrile illness with respiratory symptoms not attributed to another cause and a history of exposure to a suspect or probable case of SARS or their respiratory secretions and other bodily fluids.” (4)
This indicates that clinical symptoms such as respiratory distress were indicated as a need for further differential diagnosis, thus samples from “suspected and probable SARS cases” were tested for SARS-CoV using the following methodology.
“Laboratory test result criteria for confirming or rejecting the diagnosis of SARS remain to be defined.
- Molecular tests (PCR)
Principally, existing PCR tests are very specific but lack sensitivity. This means that negative tests cannot rule out the presence of the SARS virus in patients. Furthermore, contamination of samples in laboratories in the absence of laboratory quality control can lead to false positive results.
Positive PCR results, with the necessary quality control procedures in place. Recommendations for laboratories testing for SARS-coronavirus, are very specific and mean that there is genetic material (RNA) of the SARS-CoV in the sample. This does not mean that there is live virus present, or that it is present in a quantity large enough to infect another person.
Negative PCR results do not exclude SARS. SARS-CoV PCR can be negative for the following reasons:
- The patient is not infected with the SARS coronavirus; the illness is due to another infectious agent (virus, bacterium, fungus) or a non-infectious cause.
- The test results are incorrect (“false-negative”). Current tests need to be further developed to improve sensitivity.
- Specimens were not collected at a time when the virus or its genetic material was present. The virus and its genetic material may be present for a brief period only, depending on the type of specimen tested.
2. Antibody tests
These tests detect antibodies produced in response to the SARS coronavirus infection. Different types of antibodies (IgM and IgG) appear and change in level during the course of infection. They can be undetectable at the early stage of infection. IgG usually remains detectable after resolution of the illness.
The following test formats are being developed, but are not commercially available yet:
- ELISA (Enzyme Linked ImmunoSorbant Assay): a test detecting a mixture of IgM and IgG antibodies in the serum of SARS patients yields positive results reliably at around day 21 after the onset of illness.
– IFA (Immunofluorescence Assay): a test detecting IgM antibodies in serum of SARS patients yields positive results after about day 10 of illness. This test format is also used to test for IgG. This is a reliable test requiring the use of fixed SARS virus on an immunofluorescence microscope.
Positive antibody test results indicate a previous infection with SARS-CoV. Seroconversion from negative to positive or a four-fold rise in antibody titre from acute to convalescent serum indicates recent infection.
Negative antibody test results: No detection of antibody after 21 days from onset of illness seems to indicate that no infection with SARS-CoV took place.
3. Cell culture
Virus in specimens (such as respiratory secretions, blood or stool) from SARS patients can also be detected by inoculating cell cultures and growing the virus. Once isolated, the virus must be identified as the SARS virus with further tests. Cell culture is a very demanding test, but currently (with the exception of animal trials) only means to show the existence of a live virus.
Positive cell culture results indicate the presence of live SARS-CoV in the sample tested.
Negative cell culture results do not exclude SARS (see negative PCR test result).” (4)
Case detection in 2003 SARS pandemic took a different approach to SARS-CoV-2 in 2020, and the closest similarities may be seen potentially at the early onset of what became Covid-19 before mass roll out of tests occurred outside of laboratory settings.
In 2003 severe respiratory illness needed be within the context of “documented exposure risk” when diagnosing SARS-CoV disease. SARS-CoV disease was thus to be investigated in patients hospitalised for:
- “Radiographically confirmed pneumonia or acute respiratory distress syndrome of unknown etiology, AND
- One of the following risk factors in the 10 days before illness onset:
- Travel to mainland China, Hong Kong, or Taiwan, or close contact with an ill person with a history of recent travel to one of these areas, OR
- Employment in an occupation associated with a risk for SARS-CoV exposure (e.g., healthcare worker with direct patient contact; worker in a laboratory that contains live SARS-CoV), OR
- Part of a cluster of cases of atypical pneumonia without an alternative diagnosis” (5)
Data on the number of tests carried out during the 2003 epidemic seems scant, no doubt diagnostic attempts were drastically ramped up for the 2019-2020 emergence of a “novel” coronavirus, and in part that context needs including within the suggesting that 2003 SARS had higher risk for mortality, but did not infect so many or last as long. One must consider that in 2020 after much failure to implement testing, alongside track and trace (considering that the United Kingdom Government abandoned this strategy initially), testing was eventually conducted beyond the 2003 SARS criteria, including those that had little to no symptoms and or had been identified for testing by studies and contact tracers. As such, one may consider the sudden disappearance of SARS occurred to searches being limited to those with more serious manifestations of SARS pathology. Hence the mortality rate was also substantially more severe in 2003-2004.
With regard to a SARS vaccine, the studies for SARS-CoV-1 were initiated and tested in animal models, with an inactivated whole virus being tested in mice, ferrets, and nonhuman primates, which was suggested to provide protective immunity, but sadly in the animal studies it seemed to cause immune disease, specifically an immunopathologic-type lung disease, which given the nature of SARS was not a good outcome. (6)
Human studies were not conducted, and the vaccine studies petered out due to the apparent disappearance of the virus, which was attributed to a number of factors, including the weather in the summer, the “strict quarantine initiate of not only those infected, but those who had been in contact with individuals identified as infected. In reality nobody knows why the pandemic ended, viruses tend to be unpredictable, but as written by the author in Pandemic Panic (7), viruses tend to mutate to less severe strains in order to survive. A virus that is either lethal to all hosts, or renders hosts unable to circulate in the community leads to less spread and the virus being unable to survive. Potentially in SARS the increased mortality rate may have caused such a phenomena, but it seems more plausible, given that while mortality was suggested to be higher than SARS-CoV-2, it did not kill all those infected, that limitation of testing to those informally diagnosed as being infected led to the less severe strains running unchecked in asymptomatic individuals. In SARS-CoV-2, mild and asymptomatic cases are being highlighted giving the impression that this latest pandemic is less lethal but more virulent. Vaccine development for SARS-CoV-2 varies, with some using minute viral portions, or virus ribonucleic acid (RNA). (8)
This is suggested to circumvent the issues that occurred with the SARS-CoV-1 vaccine that relied upon greater amounts of the actual virus.
BioNTech and Pfizer recently announced preliminary “evidence,” and in the United Kingdom following hasty checks which some suggest to be a political move by a government reeling from the looming disasters of Brexit, and the poor handling of the pandemic that has been mired in controversy with cronyism amongst other issues, he United Kingdom became the first to approve the Pfizer/BioNTech vaccine, paving the way for so-called “mass” vaccination, after Britain's medicines regulator, the MHRA, suggested the product which allegedly offers “up to" 95 percent “protection against Covid-19 illness,” was safe enough to be rolled out. (9)
The news was greeted with much excitement, but one must consider that “up to” 95 percent and “protection against Covid-19 illness” are not well defined.
The approval of an mRNA vaccine for use is a world first (10), and while the technology appeared in 1990 within literature it has been fraught with numerous issues that needed solving.
Vaccines in theory works via the introduction to the body of material that is sufficient and specific enough to provoke and immune response. These are in theory achieved by an attenuated (weakened) virus, a virus that has killed, or a viral protein, such as occurs in an mRNA vaccine in which a messenger RNA is introduced, this RNA is the genetic material utilised to translate the proteins used within our bodies.
The typical self/non-self model of immune function whilst still the predominant held view both in immunology within general practise has encountered problems since the 1980s, and Dr Matzinger’s Danger Theory (11), argues that tissues are a large factor in driving an immune response, and that an immune response occurs in response to a danger which may vary not only between, but between individuals. What may present danger to one, may not represent the same degree of danger to another. Certainly this needs to be accounted for in vaccines that do not contain a live virus, and also in those with attenuated virus samples. Viruses that have been inactivated are less dangerous and produce a weaker response immune response, necessitating immunologic adjuvants, and often and multiple "booster" injections. (12)
Adjuvants in immunology refer to substances included to potentiate and improve the immune response (13) Vaccine manufacture was assumed to cause significant variability in batch efficacy due to contamination within reaction vessels used within processing, however, when cleaning protocols were scrupulously increased a reduction in vaccine “effectiveness,” and contaminants were noted to enhance immune response. (14)
As can be seen at the beginning of the article, the vaccine includes the RNA ingredient BNT-162B2, and a number of other ingredients or adjuvants, namely;
lipid ALC-0159 (UNII: PJH39UMU6H)
lipid ALC-0315 (UNII: AVX8DX713V)
POTASSIUM CHLORIDE (UNII: 660YQ98I10)
MONOBASIC POTASSIUM PHOSPHATE (UNII: 4J9FJ0HL51)
SODIUM CHLORIDE (UNII: 451W47IQ8X)
SODIUM PHOSPHATE, DIBASIC, UNSPECIFIED FORM (UNII: GR686LBA74)
SUCROSE (UNII: C151H8M554)
Adaptive immune response theoretically occurs following an innate immune response (danger) which see cells such as the dendritic cells being engulf ed by the pathogens, which migrate to lymph nodes and the T cells that act as the adaptive immune cells are then activated. (15)
This activation causes mast cells to release both heparin and histamine that isolates the infection site to enable immune cells ability to clear out pathogens, but also causing the release chemokines. Adjuvants are suggested to increase the local reactions and induce a larger release of danger signals, plus induce release of inflammatory cytokines. The immune system to suggested to recognise these pathogenic molecules due in part to Toll-Like Receptors (TLRs).
Various medical complications are suggested to occur both in humans and animals due to adjuvants, with aluminium salts, utilised in numerous vaccines but regarded safe by the Food and Drugs Administration (16), yet numerous studies indicate a role in the development of Alzheimer's disease (17), an adjuvants may be too reactogenic, creating susceptibility to fever. Indeed fever post vaccination is an expected outcome. The vaccination for “swine flu” H1N1 pandemic was associated with incidence of the chronic sleep disorder, narcolepsy in both children and adolescents (18), which associated with an influenza vaccine called pandemrix that has the AS03-adjuvant.
In animals, specifically mice, aluminium adjuvants which have been previously linked to Gulf War syndrome (GWS), following its use in anthrax vaccination, been indicated to cause motor neuron death (19), increases in incidences of amyotrophic lateral sclerosis as well as other related neurological disorders correlated with GWS. No doubt multiple environmental variables are noted, anthrax vaccination and the relevant adjuvants such as aluminum hydroxide and squalene have repeatedly and increasing faced scrutiny. The use of squalene, a suspension of oil-water is also indicated as increasing the risk for auto-immune disease incidence in rodents. (20) Squalene itself is indicated in arthritis prone rodents as inducing rheumatoid arthritis (21), a 2006 report by Richards et al (22), found a relationship between vaccine-associated sarcoma (VAS), but conflicts exist on whether risk is increased by specific vaccines, manufacturing processes specifically, adjuvants, or other associated variables. (23).
On the 8th December 2020, United Kingdom began rolling out the Pfizer vaccine candidate, a mRNA (messenger RNA) type of vaccine as previously discussed, that enables synthetic genetic material that is enveloped in lipids to transfect (infect) the cell, which occurs due polyethylene glycol (PEG). In what is often referred to as conspiracy theory circles, public awareness usually focuses upon PEGs use in anti-freeze type products that may be utilised in motor vehicle radiator amongst other use. With the Pfizer vaccine candidate, PEG aids in the Nucleoside modified mRNA encoding for SARS-CoV-2 full-length spike protein antigen is combined with a lipid nanoparticle (LNP) formulation. (24)
Polyethylene glycol forms part of the formulation of lipid nanoparticle that envelops the specific mRNA genetic material, which was previously noted as ALC-0159, which is the name for 2[(polyethylene glycol)-2000]-N,N-ditetradecylacetamide. (25)
Knop et al (26), reviewed the use of polyethylene glycol in delivery of pharmaceutical drugs, indicating that as early as the 1950s they were linked to a propensity to cause cellular clumping and blood clotting, which increases risk for embolisms, including pulmonary embolisms, as well as inducing an inflammatory cytokine storm. Polyethylene glycol are suggested to be linked to high incidences of drug related adverse reactions, including but not limited to anaphylaxis. (27; 28; 29; 30; 31; 32; 33; 34; 35)
Indeed, as indicated by Pottel et al (36), medications tend to constitute relatively minute amounts of the active pharmaceutical ingredient, with the majority of tablets, capsules, liquids, and injectables such as vaccines including numerous ingredients such as dyes to help distinguish drugs, preservatives to ensure stability and shelf life, antimicrobials and excipients compounds which may be either fillers, or as is suggested in vaccines suggested to be essential to ensure the active ingredient is delivered both safely and effectively.
It is generally accepted that ingredients listed as excipients are biologically due to an absence of acute toxicity in studies using animals. Pottel et al (36), searched for long-term subtle effects, and interaction with other medicines, stating that many excipient have effects that may have been previously unappreciated and may play an important role in health outcomes and disease.
The use of lipid nanoparticles in the Pfizer vaccine, like one from Moderna, are suggested to be approximately 100 nanometers in diameter, similar to the actual coronavirus. Pfizer suggests it uses four different lipids in a “defined ratio”, with lipid ALC-0315 being a primary ingredient within the formulation that are ionizable, and can be positively charged, while the RNA has a negative charge causing the two to attract each, but that it is a component known to able to cause side-effects. (37)
Errors made by the Scientific Advisory Group for Emergencies (SAGE), ones that have continued throughout the pandemic, were discussed in other works by the author (7), and the errors occurring in assessment of the unfolding SAR-CoV-2 pandemic rendered the predictions grossly inaccurate, which was seen to have both disastrous effects upon the nations response to Covid-19, and also necessitated frequent and drastic re-evaluated estimates. SAGE’s initial estimates followed a narrative that SARS-CoV-2 was a novel coronavirus, and that the cases found in late 2019 were the initiation of its spread, and thus that the pandemic was in early stages, and that the majority of the United Kingdom population (as high as >93 percent) had not been exposed to the virus and were at risk of infection, and a failure to act would lead to 500,000 deaths if not action were taken. (38)
This modelling assumed the total population to susceptible to SARS-CoV-2, with no pre-existing degree of immunity present within communities. Yet as described by Doshi (39), who highlights six specific studies that report SARS-CoV-2 T cell reactivity in between 20 to 50 percent of individuals with no documented viral exposure.
Ng et al (40), studying samples of blood collected in the United States between 2015 and 2018, found 50 percent had some form of SARS-CoV-2 T cell reactivity. Weiskopf et al, utilising specimens collected in the Netherlands found T cell reactivity in two out of 10 individuals that had not been virally exposed. (41)
Further reactivity was identified in individuals in the United Kingdom, Germany, Sweden, and Singapore. (42; 43; 44; 45)
Whilst small in scale and unable to provide accurate estimates of whom might have prior immunological SARS-CoV-2 responses, that findings indicated across continents, and various laboratories suggest that further research is warranted.
Chavarria-Miró et al (46),indicate the detection of SARS-CoV-2 in sewage retrospectively tested in Barcelona, Spain long before their first case of Covid-19 presented, this they suggest indicates that SARS-CoV-2 present within the population prior to reports of a global pandemic.
Indeed, Basavaraju et al (47), indicated SARS-CoV-2 infections within the United States in mid December 2019, further evidence that supports the notion that this strain of coronavirus was actually spreading throughout many nations prior to the reports of initial cases in Wuhan, China. Sadly, entering further into such narrative potentially labels one as a “conspiracy theorist”, a term some suggest is linked to the United States Central Intelligence Agency (C.I.A). (48) That said, failure to consider all theories and possibilities risks one being labelled a “complicity theorist.”
Anyone reading The Devil’s Chessboard by Talbot (49), will have little doubt of the levels the United States have previously, and presumably will still go in order to maintain and further their cause. The book details the morally corrupt and rather cynical rise of the United States intelligence apparatus that not only documents from official records, their capability of intervening clandestinely in internal affairs of competing nations but on a domestic front.
From the fanaticism brought on by the Cold War against Soviet Russia and the “necessity” for unaccountable secret institutions to distort home politics and undermine the “democratic” elsewhere, one must draw parallels with the ideology to secretly fight communism, even to the degree Dulles engaged in secret activities following World War Two to establish “ratlines” that aided Nazis considered useful to the United States in the new Cold War against the Soviet Union could both travel to the U.S, and avoid prosecution, and the secret testing on many U.S citizen via the MKULTRA project. (50) Dulles led the CIA-engineered coups in Iran in 1953 that toppled the democratically elected government of Mohammad Mossedegh and installed Shah Reza Pahlavi (who ruled until 1979) an apparent bold and daring triumph for the United States in the cold war against the Soviets.
In an era in which Wall Street is untouchable, one in which China may be the United States current fear, whilst stories should be considered and rationalised, its is not farfetched to suspect that we will read about these aspects at some point via declassified intelligence documents long in the future. The 6th August, 2019 saw the United States main laboratory facility for biological warfare being issued a "cease and desist" order due to safety standards and protocol, and leaks violations. (51) Whether this was a convenient back story to cover for any clandestine activity remains unknown, but it all adds to the plausible deniability, a central tenet of CIA activity.
What do we know about the facility? Numerous experiments were engaged in by the United Sstates, from the case in 1954 when seven inmates, notably all were black males were isolated and fed mass doses of Lysergic acid diethylamide (LSD) for 77 days by Isbell (52), “work/research” that formed part of a highly secretive C.I.A program attempting to develop methods for mind control that was based at an inauspicious Army base, Fort Detrick.
Fort Detrick in Frederick, Maryland, just 50 miles from Washington and was initially selected as a site for the development of secret plans for germ warfare, and until recently thrived as the Army’s principal biological research base with approximately 600 buildings spread across 13,000 acres. Through declassified documents, the ones that were not destroyed, we can establish that secret programs occurred to develop biological weapons, such as the Whitecoats. (53; 54; 55)
Little has been said regarding Covid-19 by Fort Detrick, and that little mention is made of Covid-19 seems curious given the study available freely on available (56), by Hensley et al.
Lisa E. Hensley is described as the Associate Director of Science at the Office of the Chief Scientist, National Institute of Allergy and Infectious Disease Integrated Research Facility in Frederick, Maryland. Prior to that acting as a civilian microbiologist in the virology division of the United States Army Medical Research Institute of Infectious Diseases (USAMRIID) also located on Fort Detrick, Maryland, acting as a subordinate lab to the U.S. Army Medical Research and Development Command (USAMRDC), which is also headquartered on the same installation. (57) Hensley is one of the premier researchers of some of the world’s most dangerous infections, including Ebola hemorrhagic fever, and Severe acute respiratory syndrome (SARS). Holder of various patents for vaccines and treatments, Hensley seems to be erroneously forgotten in the current climate. (58; 59; 60)
Is it likely that the intelligence services wished to impact China, or indeed its own citizens with a viral infection? Hopefully not, but given past actions, and the serious breaches in safety one would expect a better account to explain such instances. The United States seems to be positioned as ever to maintain plausible deniability. Is it possible that SAR-CoV-2 was already present in the United States and other nations, and Wuhan, China was simply the site at which it was formally identified?
In the United Kingdom, and indeed many other nations, one must first consider that the scientific advisory group for emergencies (SAGE), consisted of no clinical immunologists, nobody with a degree in biology degree, or post-doctoral specialisations specifically in immunology. Some were medics, but there were sociologists, psychologists, economists, political theorists and a profuse amount of mathematicians, which formed the modelling group responsible for much of the pandemic response. (61)
Modelling does require specific expertise in order to achieve their desired outcomes, yet such outcomes may not specifically be based on the full available evidence, but in an ideological stance that misses context and skews the outcome predictions. When modelling is structured by those with little expertise in the specific subject-matter it risks foundational errors that are both missed by the modellers, and often by those tasked with implementing policy and operational changes due to a false belief in the disproportionate power of models. However credulous the modelling group within SAGE may appear, the claims made, that the processes and pathways of pathological diseases such as Covid-19 fails to account for specific biological variables and makes assumptions of key factors such as the starting for SARS-CoV-2 spread.
The models utilised on the suggestion of Imperial College were inherently flawed for a number of reasons, but primarily as discussed above, that SARS-CoV-2 was a novel virus and thus no prior immunity was conferred within the community. As has been discussed earlier, evidence currently suggests SAR-CoV-2 emerged before the date suggested in contemporary literature and the media, and that T-cell reactivity is evident in some degree of the population, which would be expected given that SARS-CoV-2 is a mutation of the Coronavirus and not a totally new emerging virus. (62)
This assumption that 100 percent of the population were susceptible to SARS-CoV-2 infection led to a further false assumption, that studies of antibodies within the blood allowed a model to be constructed that determined the percentage within the population that had been infected.
SAGE suggested as of September 2020, that >90 percent of the United Kingdom population remained at risk (63), which when combined with the “data” from the REal Time Assessment of Community Transmission (REACT) study which suggests “that slightly under 6 percent of the population may have antibodies for the virus by the end of June…” indicating that such individuals were “likely” to exposed to SARS-CoV-2, or suffered with Covid-19 “disease”. (64)
One could therefore assume that the United Kingdom government backed stance on SARS-CoV-2/Covid-19 risk suggest that circa 94 percent of the population have not been infected, a figure which seems disconcertingly high when one considers the narrative that while SARS-CoV-2 carries less mortality risk than SARS, it is suggested to be be more prevalent and spread more easily, even within individuals classified as asymptomatic i.e. people who are not displaying symptoms of disease.
The official data suggests a fatality rate circe 3.5 percent (65), with 1,766,819 positive tests, and 62,566 deaths recorded “with” Covid-19 identified. With a U.K. Population of 68,045,779, a six percent infection rate should mean that over four million eighty-two thousand seven hundred forty-six people have been, or are infected, which gives a fatality rate of approximately 1.5 percent.
However, as discussed, it seems curious that SARS-CoV-2 would infect such a low percentage of the population, even if one considers that it only began its global spread in December 2019. Indeed, Ioannidis (66), in study using globally collated data suggest an infection fatality rate circa 0.2 percent as a best estimate.
This error or flaw in the policies and models comes because of the initial assumptions that SARS-CoV-2 was novel virus, and while the event that led to finding SARS-CoV-2 made it seem novel, we neither know how long it existed undetected, nor know the immunity granted from prior coronaviruses infections. In short, viruses have genetic ancestors, and the previous “novel” coronaviruses already discussed, 2003 SARS and 2012’s MERS in 2012 (67) have similar DNA sequences and structures to the current virus, with SARS being indicated to be as much as >85 percent similar.
In prior work (7), I spoke about endemic coronavirus that are linked to the common-cold which ted to circulate both within the United Kingdom and globally freely. Modernity, specifically a tendency to remove sick pay in less affluent social communities seems to cause a tendency for faster and easier transmission of such viruses. Human coronaviruses (hCov) such as hCoV-HKU1, hCoV-OC43, hCoV-NL63 and hCoV-229E are discussed in detail by Zhu et al (67), and while discovered in the 1920s in animals (68; 69), it wasn’t until the 1960s that human coronaviruses were identified. (70; 71; 72; 73; 74) As before, discovery does not mean they were none existent and newly emerged, just that research has “isolated” and identified something which was considered new. That hCoV-HKU1, hCoV-OC43, hCoV-NL63 and hCoV-229E tend to either led to asymptomatic or mild type respiratory and/or gastrointestinal infections, does not discount from their circulation within humans since their first identification, and no doubt prior to their documented existence. While accounting for between five to 30 percent of all common colds, hCoVs are rarely considered serious until the occurrence of global pandemics such as in SARS-CoV, MERS-CoV and SARS-CoV-2.
Initial opinions of coronavirus appears to have considered them to be pathogens that were relatively harmless, yet in recent months they have become globally associated with potential severe clinical complications. Coronavirus, an enveloped type virus identified by a positive-strand ribonucleic acid (RNA) genome, primarily targets mucosal surfaces within both respiratory and the intestinal tracts in a variety of mammals and birds. (75; 76)
Human coronavirus isolates known as hCoV-229E and hCoV-OC43 were correlated with the “common cold”, and symptoms in the upper respiratory tract that were both mild and self-limiting. (77; 78) When the so-called new variant SARS-CoV was discovered, which initiated an outbreak globally of acute instances of often severe cases of atypical pneumonia circa 2003, it led to an interest in human coronaviruses and the identification of two further novel variants, HCoV-NL63 and HCoV-HKU1 (79; 80), which showed an ability to cause serious complications in the respiratory tract, particularly in patients with existing comorbidities.
The initial discovery of human coronaviruses in the 1960s (70; 81), involved two differing isolation methods. One, by Kendall, Byone and Tyrell (82), at the British Medical Research Councils Common Cold Unit, in which B814 a common cold novel virus that was unable to be cultivated using standard techniques previously used to successfully cultivate adenoviruses, rhinoviruses, and others associated with the common cold. (83) Tyrell and Byone instead used a technique in 1965, that involved serial passage through a human embryonic trachea organ culture. A 1966 paper by Hamre and Procknow (84), from the University of Chicago describes the isolation of another novel cold virus, hCoV-229E, which was sourced from medical students, and grown in a culture of kidney tissue.
Human coronaviruses are indicated to act with the renin–angiotensin proteases (enzymes that breakdown proteins and peptides), and in order to both establish and maintain a cycle of infection, coronaviruses require that they deliver genetic material inside the intracellular space, which is mediated by glycosylated spike proteins, which are discussed in other works. (7)
Angiotensin Converting Enzyme 2 (ACE2) is suggested to act as a functional receptor for human coronaviruses (9), with antibodies that direct against ACE2 theorised to prevent SARS-CoV infection. (85)
The renin–angiotensin system (RAS), is a well described endocrine system, vital in maintenance of cardiac function, arterial pressure, homeostasis of fluid, and salt balance, along with regulation of tissue remodelling, particularly in proliferation of cells, angiogenesis and apoptosis. (86)
Aside to the physiologically normal processes, RAS is correlated with a variety pathophysiological actions. (87) Abnormal RAS activation is established as a variable in the development of numerous cardiovascular diseases, including hypertension, diabetes and renal disease. (88; 89)
Within RAS, synthesis of a variety of angiotensin peptides occurs, which are degraded by the precursor angiotensinogen via a series of complex enzymatic reactions. Specific components of RAS generate within specific body regions, for example, renin is generated within the kidneys, whilst ACE is derived from the lungs, with the liver being responsible for angiotensinogen. In fact angiotensin synthesis is is suggested to be evident to some degree in all organs, RAS activity initiates via the kidney, following juxtaglomerular cells releasing renin (90; 91), which acting as an aspartic protease works to cleaves its substrate angiotensinogen, that is then produced in the liver and forms the inactive angiotensin peptide, Ang I or Ang 1–10. Ang I converts to either And II, a RAS effector peptide, or Ang 1–8 via the protease ACE which is dependent on zinc. (92)
Higher ACE expression occurs on vascular endothelial cell surfaces, in particular within lung tissue. (93) Ang II generation from Ang I is able to occur via enzymes that are not ACE related, such as chymase, a serine protease. Whilst ACE is considered to be the primary enzyme responsible for Ang II-conversion, research indicates that Ang II conversion occurs via chymase enzyme in certain pathological vascular conditions. Indeed, it must be noted that chymase activity is evident in pulmonary membranes, aiding Ang I conversion into Ang II within lung tissues. (94)
RAS is typically considered predominantly a system of endocrine and circulation, yet it is now well established that alongside RAS peripherals, RAS is both tissue-specific, and abundant in independent localised systems. Indeed, within various organ systems, such as the lungs, kidneys, liver, heart, brain, vasculature, pancreas, and within the reproductive, nervous, and the digestive system. (92)
In-spite speculation regarding the existence of RAG local airway capacity intrapulmonary generation of Ang II was a recent confirmation. (95) Alveolar mast cells within both the lower and upper respiratory tract, are evidenced to express levels of renin which triggers formation of pulmonary Ang II. (96;97)
RAS components are also abundant in airway tissue in humans, including ACE and angiotensinogen, with pulmonary epithelium evidenced as the primary circulatory source for ACE. (98) Receptors for Ang II are evidenced to be expressed within lungs, in the form of the subtype AT1 which is found in the smooth muscle bronchial cells, and bronchial receptors AT2 receptors within the epithelial brush borders. (99)
The expression of ACE2 in both alveolar, bronchiolar epithelial cells, and pulmonary endothelial cells is well documented. (100)
Lung masts cells are evidenced to have chymase, potentially being a the major enzyme responsible for Ang II-generation within the lung. Local RAS activity within pulmonary tissue has been indicated as contributory in processed of tissue remodelling, such as alveolar epithelial cell apoptosis regulation, fibroblast proliferation and production of collagen within the lung. (101; 102)
Thus it is suggested that activation that is inappropriate with regard to specific local components of the airway RAS, specifically ACE2, may initiate factors that exacerbate the development pathophysiological conditions that are associated with SAR-CoV-2, and the severity of disease outcome in covid-19.
ACE2 and SARS-CoV-2
Angiotensin-converting enzyme 2 (ACE2), plays a major role in RAS homeostasis, converting Ang II to Ang (1–7), and the activation the RAS putative pathway. ACE2 is thought to be responsible for the regulation net Ang II tissue levels, as an antagoniser of fibrotic and hypertrophic effects due to the AT1 receptor being the binding site of Ang II. (103; 104)
ACE2 may the exhibit a role of counter regulation that seems critical for RAS homeostasis within the lung (104; 105), thus, improper regulation leading to increases in both levels of ACE and Ang II levels are associated with the pathogenesis of numerous varied es of lung disease, such as sarcoidosis, pulmonary hypertension, pulmonary fibrosis and more inportantly in the context of COVID-19, acute respiratory stress syndrome (ARDS). (106; 107; 108)
Studies conducted in-vivo confirm an association between the severity of ARDS, and the outcome, with pulmonary RAS. (109) ARDS, a severe acute lung injury, which is characterised with an accumulation of inflammatory cells, pulmonary oedema, and severe hypoxia (110), as prevalent in documented cases of covid-19. ARDS may be triggered by a variety of pathogenic states, such as sepsis, pancreatitis and severe trauma/shock. (111)
A number of previous studies indicated pulmonary RAS in ARDS pathogenesis, and that ACE antagonists such as AT1 receptor blockers delay the onset of ARDS in rodents exhibiting acute lung injury. (112)
Negative contributions of ACE to pathogenesis of ARDS occurs via a variety of mechanisms, such as increases in vascular permeability. (113)
Imai et al (109), identified a protective role of ACE2 during acute lung injury such as ARDS, in counterbalancing the induced pathophysiological effects of angiotensin II. Mice bred with an abrogated expression of ACE2 expression exhibited more severe patterns of disease when compared to control mice, with an enhanced degree of vascular permeability, lung oedema, and decreased lung function.
SARS-CoV & HCoV-NL63 in relation to RAS activity
The 2003 epidemic of SARS-CoV, whilst a disease that remained relatively rare, with an incidence 8,422 cases, and a total fatality rate of circa 11 percent (114), which is primarily suggested to be attributable to ARDS induced respiratory failure. Indeed, the fatality rate is variable, largely dependent on factors such as age, treatment methodology, to be between 0 and 50 percent (115), with SARS patients < 24 years evidenced to be less likely (< one percent) to die from SARS, that those > 65 who had a 55 percent mortality rate. (116)
SARS-COV infectS host cells via ACE2, the component of RAS which is evidenced to protect against ARDS induced acute lung failure. (117; 118)
As the aforementioned spike protein engages with ACE2 a reduction occurs in the cell surface, thus ACE2 functional capacity is down regulated (117; 119), a phenomenon that is evidenced to provoke increased severity and risk of lung failure in rodents infected it SARS-CoV. (120)
It is also worthy of note, that the within the SARS-CoV-2 spike protein, a pocket of the free fatty acid, linoleic acid has been indicated to increase SARS-CoV-2 binding (121),
Interestingly, despite this research, the team consider linoleic acid to be a viable potential therapy due to the fatty acids so called “essential” nature.
Ling et al (122), studied rodent fatty acid profiles alongside inflammatory markers utilising animals fed a diet considered essential fatty acid-deficient (EFAD) constituting 2 percent hydrogenated coconut oil (HCO) for a 2 weeks period. Alongside groups supplemented with 1.3mg of arachidonic acid and 3.3 mg of docosahexaenoic acid (AA + DHA) which created a 2 percent fat diet. Upon exposure to lipopolysaccharide, the rodents on the EFAD diet had significantly lower levels of various markers of inflammations, such as tumor necrosis factor (TNF) and interleukin-6.
Increases in serum levels of C18 unsaturated free fatty acids are discussed by Bursten et al (123), as being a significant predictor in acute respiratory distress syndrome (ARDS) development, which was discussed within both Controlling Intuitive Appetite (124), and Pandemic Panic (7), which suggests that increases in ratios of unsaturated serum acyl chain occur between those codified as healthy and those patients which suffered severe outcomes, were both sufficient to identify those likely to suffer ARDS, and provide insights regarding the essentiality of unsaturated fatty acids.
Hanna and Hafez (125), discuss arachidonic acid being an unsaturated fatty acid that is sourced either via direct dietary means, or indirectly via metabolism of linoleic acid, in which its release occurs via the breakdown of phospholipids under the action phospholipase A2. Various factors, including mechanical through to chemical stimuli may induce a cascade of arachidonic acid.
Malcom et al (126), compared the composition of fatty acid in adipose tissue samples taken from 143 adults autopsied humans aged 24 to 61 years, one from a site that was deep-seated site (perirenal) and two from sites that are subcutaneous, the buttock and abdominal areas. Proportional levels of saturated fatty acid were found to be highest in samples of adipose tissue found in the perirenal, whilst the adipose tissue buttock was lowest in saturated fatty acids. Proportionally level of both linoleic and linolenic acids were similar across all sample sites, leading them to conclude adipose tissue found in the buttock has a greater degree of unsaturation than abdominal adipose tissue.
Mamalakis et al (127), in a study of 475 adolescents aged 11 to 18 years (138 aged 11 to 16 years completed all variables), assessed levels of physical activity, serum lipids, and both buttock and abdominal composition of adipose fatty acids finding that like adults, the composition of fatty acid in the abdominal adipose tissue of children is supposedly less favourable when the buttock, with abdominal adiposity once again exhibiting the much maligned saturated fatty acids elevated proportions, with decreased proportions of both monounsaturated and polyunsaturated fatty acids when compared to buttock adiposity. Such findings are corroborated in adults by Pittet et al (128), and Phinney et al. (129)
That unsaturated fatty acids are suggested as being important in the binding of the SARS-CoV-2 spike protein, and are indicated to be higher with age seems to correlate well with the susceptibility of aged subjects to SARS-CoV-2 infection and poorer mortality.
The team (123), state that activity in the linoleic acid metabolic pathway is able to trigger both systemic inflammation, acute respiratory distress syndrome and cause pneumonia, all pathologies observed in severe Covid-19, ARDS, Sepsis patients. (7)
El-Kurdi, et al (130), concurs that mortality increases in relation to unsaturated fatty acid both as exogenous consumption and administration, and also due to adipose lipolysis. Indeed it must be noted that as Covid-19 pathology worsens, dietary intake may reduce due to loss of appetite which increases fatty acid oxidation, potentially of unsaturated fatty acid. Unsaturated fatty acids seem key in ability of the SARS-CoV-2 spike proteins to attach and enter the human body, specifically via the ACE2 receptor.
Validation by research from Bristol University (121), which seeks a possible basis for a pharmaceutical intervention that may prevent the Sars-CoV-2 virus from entering the human body, consists of a research team, led by both Christiane Schaffitzel and Imre Berger that found unexpectedly that linoleic acid was exhibited within a pocket of the protein. Linoleic acid, a constituent of widely available linseed oil, is also a component of many industrial processes such as the manufacture of linoleum, a floor covering consisting of canvas with a preparation of linseed oil as a backing. Linoleic acid (18:2ω6; cis, cis-9,12-octadecadienoic acid) is the most highly consumed n-6 polyunsaturated fatty acid (PUFA) in the human diet (131), and can obtained from vegetable oils such as sunflower, safflower, soybean, corn, and canola oils as well as nuts and seeds.
The maintenance of n-6 polyunsaturated fatty acids as a so-called “essential fatty acid” as they cannot be manufactured endogenously (132), which is suggested to be required, among other things, to maintain cell membranes in the lungs, which continues to be the consensus belief (133), despite issues with membrane theory as described by Ling (134), in which he discusses a;
“concept that the basic unit of all life, the cell, is a membrane-enclosed soup of (free) water, (free) K+ (and native) proteins is called the membrane theory. A careful examination of past records shows that this theory has no author in the true sense of the word. Rather, it grew mostly out of some mistaken ideas made by Theodor Schwann in his Cell Theory. (This is not to deny that there is a membrane theory with an authentic author but this authored membrane theory came later and is much more narrowly focussed and accordingly can at best be regarded as an offshoot of the broader and older membrane theory without an author.) However, there is no ambiguity on the demise of the membrane theory, which occurred more than 60 years ago, when a flood of converging evidence showed that the asymmetrical distribution of potassium (K+) and sodium (Na+) observed in virtually all living cells is not the result of the presence of a membrane barrier that permits some solutes like water and K+ to move in and out of the cell, while barring - absolutely and permanently--the passage of other solutes like Na+. To keep the membrane theory afloat, submicroscopic pumps were installed across the cell membrane to maintain, for example, the level of Na+ in the cell low and the level of K+ high by the ceaseless pumping activities at the expense of metabolic energy. Forty-five year ago this version of the membrane theory was also experimentally disproved. In spite of all these overwhelming evidence against the membrane-pump theory, it still is being taught as verified truth in all high-school and biology textbooks known to us today. Meanwhile, almost unnoticed, a new unifying theory of the living cell, called the association-induction hypothesis came into being some 40 years ago. Also little noticed was the fact that it has received extensive confirmation worldwide and has shown an ability to provide self-consistent interpretations of most if not all known experimental observations that are contradicting the membrane-pump theory as well as other observations that seem to support the membrane pump theory.”
and that it appears to be the molecule to which Sars-CoV-2 attaches itself in order to enter the human body, the persistent narrative of it as essential leads the researchers to conclude not that n-6 polyunsaturated fatty acids should be limited, both via consumption and lipolysis, but that their challenge is the development of a pharmaceutical drug which is able to distorts the spike protein of Sars-CoV-2, thus preventing it attaching to the linoleic acid, pointing to similar drugs have already been developed to prevent rhinovirus attaching themselves to the lungs. (135)
The study authors note, that despite huge investment searching for elusive human immunodeficiency viruses (HIV) vaccines, the medical community relied upon therapeutic anti-viral medications of varying efficacy to decrease disease mortality risk.
Dr. Ray Peat (136), in an article titled “fats, functions & malfunctions”, discusses both linoleic acid and arachidonic acid as not only increasing lipid membrane permeability, but that the whole cell increases in permeability, causing structural proteins to bind throughout the cell which is exhibited in fibrosis seen in both Covid-19/ARDS and septic shock, along with an increased affinity to retain water which leads to generalised cellular swelling and localised swelling in the mitochondria that reduces oxidative function, and allows increased cellular calcium that activates cellular excitation and initiates a redox shift toward inflammatory states that ultimately leads to inappropriate growth and mass, as seen in fibrosis and cancer, or cell death.
Dr. Peat continues to highlight the impact of such cellular environments, and the effects of glycogen restriction, which may occur via increased energy demand, or energy restriction, either intentionally or due to metabolic dysfunction. Stating that decreased glycogen stores leads to increases in secretion adrenaline that may act to liberate fatty acids from adipose stores. Following chronic dietary consumption of n-6 polyunsaturated fatty acids, the ability to be oxidised or detoxified by the liver which is impacted by glycogen availability, thyroid function. (137)
Peat (136), draws awareness to research by Cook et al (138), Li et al (139), and Autore, et al (140), and the quite remarkable resistance displayed by animals deficient in so-called “essential fatty acids to shock, which indicates the central role of polyunsaturated fatty acids in the maladaptive, and often chronic adaptions caused by acute shock, such as retention of calcium, cellular leakiness, inhibition of energy production, which bare striking similarities to the markers of many disease pathologies, and so-called “normal” ageing. The abundance of serum free fatty acids and stress hormones that tend in aged subjects to be both chronically higher, and result in poorer outcomes in diseases such as Covid-19 and other respiratory illnesses, alongside reduced tolerance of incidences of stress.
Much research indicates that animals with lower levels of unsaturated fatty acids exhibit higher metabolic rates, and a preference of glucose use, which leads to increased carbon dioxide production (141), and enhanced resistance to toxins such as cobra venom (142), and lipopolysaccharides, commonly known as endotoxins.(139) This correlates with the discussion in Consistent Eating (143), that metabolism decreases in line with energy intake through lifespan, and that susceptibility to stress decreases as metabolism declines, which suggests a lower respiratory quotient due to limited glucose intake and/or increased consumption of fatty acids and protein.
Despite the associations with ACE2, identified polymorphisms in human ACE2 genes are however not correlated with SAR-CoV disease progression. (144; 145)
Functional performance of RAS is evidenced to decrease as part of “normal” physiological processes of ageing, as is exemplified by a progressive inhibition of circulating levels of renin and the plasma activity. (146; 147)
Indeed, ageing is a frequently noted variable in infections related to both SARS-CoV, and SARS-CoV-2 as a significant predictor of poor outcome. (148)
Thus, RAS function in elderly, and groups with co-morbid conditions may lead to worse outcomes regarding ARDS and acute injury due to an overall impairment in RAS activity.
That corona virus activates inflammatory systems, particularly RAS, and with available medications to act as both angiotensin receptor blockers and for inhibition of ACE. Angiotensin converting enzyme enables production of inflammatory proteins which increase blood pressure, and the correlation between angiotensin and serotonin is well established in regards to age related inflammation. As lifespan increases, exposure to and production of angiotensin occurs with then, increases blood vessel contraction, which creates greater clotting risk, and increases fatigue, alongside inhibiting energy production. (149; 150)
The class one viral fusion spike protein, which while unique to coronaviruses, a feature that mediates attachment to the host receptor in all species of CoV. (151) The N-glycosylated spike protein varies abundantly between the species of CoV with lengths between 1100 to 1600 residues, and estimation of molecular mass ranging to <220 kDa. The spike protein features trimers that form the spikes evident on the surface of the CoV particle may be between 18–23-nm, a factor which may cause issues in the reliance on reverse transcriptase-polymerase chain reaction (RT-PCR) testing. (152; 153; 154)
Reverse transcription polymerase chain reaction (RT-PCR) is an established laboratory technique used for the identification of specific genetic materials presence in a sample via the biochemical amplification process. The test has been lauded as a scientific advance of great importance to the field of molecular biology, with the foundation of PCR revolutionising DNA study and gaining its creator, Kary B. Mullis, the 1993 Nobel Prize for Chemistry, and it use primers to sequences the encoding may involve a cross reaction with the spike protein that not only detects SARS-CoV-2 but other hCoV during the sample collection (155), as well as other respiratory viruses, as discussed, some degree of immunity is conferred by previous exposure to similar viruses. (156)
Reported variances in illnesses range from mild symptoms to severe, and well documented occurrences of death since SARS-CoV-2 was first confirmed and reported in humans.
The Centre for Disease Control (CDC) initially suggested the following symptoms “may” appear 2-14 days after exposure.
- Fever
- Cough
- Shortness of breath (156)
Variances and confusion seem evident in testing protocol, with many citing initial failures in test validity (158; 159; 160; 161), with nucleic acid tests (NATs) that are widely utilised for diagnosis of new cases being suggested to have a likelihood that many such infections may remain undocumented, and presumably where false negatives are a possibility, so to must be false positives. Whilst relatively cheap, and potentially abundant, the use of NATs as one of the two primary methods for confirming Covid-19 presence in humans subjects involves the collection of patient samples that are then tested for specific molecules relevant to the Covid-19 genetic material.
Under previous criteria, a diagnosis of Covid-19 needed to be confirmed by lab tests, specifically a nucleic acid test performed on swabs from a patient’s respiratory tract or blood. Yet issues exist in nucleic acid testing, with “false negatives” created by tests that are not sensitive enough requiring greater amplification (cycle threshold), issues in transporting and handling samples, and questions over the quality of sample collection. (162)
A nucleic acid test (NAT) is a procedure for the detection a specific nucleic acid sequence to detect virus or bacteria via the genetic materials RNA (ribonucleic acid)/DNA (deoxyribonucleic acid), as opposed to antigens/antibodies. As the amounts of genetic material are typically small, techniques are used to amplify genetic materials, namely nucleic acid amplification tests (NAATs), such as a strand displacement assay (SDA), or transcription mediated assay (TMA), as seems to be utilised in the specific Covid-19 polymerase chain reaction (PCR) test.
PCR typically involves a process of 20–40 repeated cycles of thermal temperature variation. (163)
- Initialisation: Consisting of heating to between 94–96 °C (201–205 °F), or 98 °C (208 °F) for 1–10 minutes.
- Denaturation: Heating to 94–98 °C (201–208 °F) for 20–30 seconds.
- Annealing: Lowered temperature to 50–65 °C (122–149 °F) for 20–40 seconds.
- Extension/elongation: The temperature typically raised to approximately 75–80 °C (167–176 °F), but can be as low as 72 °C (162 °F)
- Final elongation: May be performed between 70–74 °C (158–165 °F) for 5–15 minutes.
- Final hold: Cools to 4–15 °C (39–59 °F) for indefinite periods, including short-term storage.
That the medical community has rallied in order to develop reliable molecular diagnostic tests has been aided by numerous research groups working to identify and sequence the viral genomes via open databases. As infections are suggested to increase, authorities sought methods to accurately diagnose and reliable document cases. Clinically, access to robust, and accurate data was dependent upon the isolation and cultivation of coronavirus from the broncho-alveolar lavage fluid via three patients that are classified as a probable outbreak source.
Electron microscopy, a technique fraught with issues as previously discussed by Hillman (164), allowed observations of “typical” coronavirus morphology, whilst more classic use of light microscopy demonstrated a cytopathic effect upon epithelial cells in the human airway. From this, various international groups worked utilising this sequence data in order to produce primers for PCR tests that would support public health laboratories in absence of an available commercial Covid-19 test.
The lab of Christian Drosten, of the Institute of Virology, Charité University Hospital, Berlin, along with academic collaborators in Europe and Hong Kong (165), verified and assessed the test validity in absence of both isolates of SARS-CoV-2 or indeed patient samples, instead confirming validity against 297 samples obtained from patients diagnosed with other respiratory infections. Upon this basis 250,000 kits, were dispatched by the World Health Organization (WHO), to 159 laboratories globally.
A Hong Kong University group developed two quantitative RT reverse transcription PCR tests (166), that target the sequences of viral genome deposited with GenBank, then validated against two clinical specimens via SARS-CoV-2/Covid-19 infected patients.
The PCR test is suggested to be highly sensitive, if used correctly, but notably when the cycle threshold (amplification) is increased, but this produces significant problems in high-pressure settings, and it also still remains unclear on the optimal type of clinical specimen, with suggestion that swabs of the nasopharyngeal give greater consistency compared to sputum samples. (167) Questions are also raised with regard to both consistency in cycle threshold between test (with variances in assays), and a cut off point art which cycle threshold becomes too sensitive and detects dead viral fragments from previous infection.
These early lab tests were suggested to “buy-time,’ and give public health authorities some diagnostic tools before commercial products and kits became available at scale. In China, genome sequencing firm BGI Group, of Shenzhen had by the end of January distributed over 50,000 test kits across China. On the 5th February it opened an emergency test laboratory in Wuhan that was able to process 10,000 samples per day. Other companies are developing their tests more slowly, but initial rollouts were suggested to be imminent.
Not all were relying on primer designs and protocols specified by academic laboratories or public health authorities. Rather than develop bespoke PCR tests, IDbyDNA was one of a handful of companies employing metagenomic nucleic acid analysis as a routine diagnostic and surveillance tool. Its existing Explify Respiratory test, which is a laboratory-developed test, able to identify over 900 respiratory pathogens, including viruses, bacteria, fungi and parasites, by comparing unbiased metagenomic data obtained from patient samples with a large repository of sequence data.
It was suggested that it could already detect the SARS-CoV-2 strain.
“We have now updated our data with the new coronavirus and are in the process of revalidating,”
said cofounder and chief medical officer Robert Schlaberg.
“The modifications are all on the data analysis side.”
That was, he stated, an easier process than updating the physical assay, with the actual data analysis taking less than an hour, giving a total turnaround time from receipt of sample to test result of 36 hours. Although more expensive than PCR testing, the falling costs of sequencing could help to democratise this approach. The company is selling the technology as well as its testing services.
The suggestion that NAT tests falsely produce negative results in patients with the infection is complicated by the suggestion that Computerised Tomography scans, are able clearly identify signs of viral infection, even though radiation creates tissue disturbances. (168)
The enactment of emergency measures created a situation in which large biotech and medical testing laboratories are allowed to develop and validate their own tests, yet various sources are compiled to create the data which becomes publicly available. Interestingly, despite the seeming fragility to the stock market, the value of certain bio-tech companies seems to be increasing. (169)
As described above regarding testing, the use of these probabilistic inferences relies upon clusters of so-called empirical evidences, which can be seen to lack validity. As discussed in Mandel (170), a problem discussed by Eddy (171), explains that the following problem is encountered with regard to a medical tests accuracy in aiding probability assessment;
“The probability of breast cancer is one percent for a woman at age 40 who participates in routine screening. If a woman has breast cancer, the probability is 80 percent that she will get a positive mammography. If a woman does not have breast cancer, the probability is 9.6 percent that she will also get a positive mammography. A woman in this age group had a positive mammography in a routine screening. What is the probability that she actually has breast cancer? __ percent.”
It is shown by Casscells, Schoenberger, and Graboys (172), amongst others, that physicians frequently incorrectly interpret the actual probability. Using bayesian reasoning, as discussed by Mandel (170), physicians fare better when all the information is considered rationally. The proportion of patients in the scenario originally suggested to have breast cancer would be referred to as the prior probability. The possibility that those with breast cancer receive a positive mammogram, and that a positive mammogram will be received by an individual who has not got breast cancer are both known as conditional probabilities. This information would collectively be referred to as priors, and through its use we could estimate probability of breast cancer, and that we know a positive mammogram has been received as a revised probability.
If a sample of 10,000 female participants is utilised, and 100 of those actually have breast cancer, of which just 80 have received a positive mammogram. 9,900 do not have breast cancer, yet 950 of them will also receive a positive mammogram. From this data we can assess that 1,030 females out of the original 10,000 participants received a positive mammogram, yet only 80 will actually have cancer, just 7.8 percent of the total group.
This gives us four groups:
- 80 females have both breast cancer and a mammogram that is positive.
- 20 females that have breast cancer mammogram that is negative.
- 950 females that do not have breast cancer but have a mammogram that is positive.
- 8,950 females that do not have breast cancer and also have a mammogram that is negative.
Priors may be true, and they may indeed reflect the reality, but without effective judgement against all available data, or if priors are held as defined and established facts that are unchallengeable, beliefs may be given unsubstantiated credibility.
This serves to highlight that Covid-19 testing accuracy is not known, that multiple variants of tests may be been utilised both globally, nationally and indeed across state-lines. Indeed, all diagnoses may not be via tests, with less severe cases that are self-isolated and reported as Covid-19. That said, so-called asymptomatic carriers of the infection may remain undiagnosed, thus suggestions regarding mortality/fatality rates remain questionable.
We can draw out some data that helps from the cases in Wuhan, China. In Zhang et al (173), we see that from a total of 140 cases, other comorbidity’s were present, indeed from all cases the most prevalent underlying health issue, was hypertension.
64.3 percent of those in the Zhang et al research had underlying health conditions, that represents 90 people.
Of those 90;
- 42 (30%) suffered hypertension
- 17 (12.1%) suffered diabetes
- 8 (5.7%) suffered fatty liver disease
- 7 (5%) chronic gastritis
- 7 (5%) coronary heart disease
- 5 (3.6%) thyroid disease
In non-severe cases 82 cases were split by;
- 20 (24.4% ) hypertension
- 9 (11%) diabetes
- 4 (5%) fatty liver diesese
- 5 (6.1%) chronic gastritis
- 3 (3.7%) coronary heart disease
- 1 (1.2%) thyroid disease
- 22 (37.9%) hypertension
- 8 (13.8%) diabetes
- 4 (6.9%) fatty liver disease
- 2 (3.4%) chronic gastritis
- 4 (6.9%) coronary heart disease
- 4 (6.9%) thyroid disease
- Hypertension - 0.85
- Diabetes - 0.615
- Fatty liver disease - 0.718
- Chronic gastritis - 0.700
- Coronary heart disease - 0.448
- Thyroid disease - 1.60
The endemic spread of hCoV’s that produce the so-called common-cold enables some degree of immunity, to not only to those specific viruses, but also to those that are closely related, with SARS-CoV-2 being one such virus. The evidence that SARS and SARS-CoV-2 are approximately 80 to 85 percent identical at the genome sequence (67), should indicated that some degree of immunity cross-over can be expected to be demonstrated in contamination of results indicating SARS-CoV-2 infection being due to other hCoV types.
A systematic review by Jefferson et al (174), suggests that the RT-PCR test is so sensitive that not only is it susceptible to picking up other hCoV contaminants, but also that it potentially detects post infection fragments of SARS-CoV-2 (or other hCoV) that are no longer live, which according to the team may be leading to over-diagnosis of Covid-19 that has occurred, specifically in the so-called second wave of the pandemic.
One of the authors of the study, Professor Heneghan suggests that their findings should be used to classify whether test outcomes that are currently “positive or negative” depending on detection of “the virus”, that the tests could be refined with either a viral cut-off point in which viral amounts are considered in regards to how much triggers what would classically be called a case, indicated by symptoms and illness, not the current definition of a case which is simply a positive result.
The team including Heneghan reviewed evidence collected from 25 studies in which viral specimens collected from samples of positive tests were virally cultured to test whether they were able to grow, indicating whether a positive test contains an active viral sample that is able to reproduce and transmit, or just viral fragments that are dead and unable to grow either in the laboratory setting, or presumably in an individual.
The diagnosis of Covid-19 involves an RT-PCR swab test as the standard diagnostic method in both clinical and community wide settings, uses numerous processes and chemicals that amplify the genetic material of the virus to aid its so studied. As discussed previously, "cycles" that occur in order to recover sufficient viral material to identify it could be utilised to indicate how much virus evident. The more replication cycle needed, the more infectious an individual may be, which presents an unquantified risk for false positives. Jefferson et al (174), suggest that while every sample cannot be cultured in a laboratory, an indication of a samples viral content could be deduced from knowledge of the number of replication cycles required to identify the virus which could provide evidence of whether it is indeed an active infection. (175)
Gniazdowski et al (176), suggest that even when SARS-CoV-2 was detected molecularly, acknowledgement of the number of cycle thresholds provided increased accuracy in infection diagnosis, particularly in combination with RT-PCR test results and in presenting with clinical symptoms. 161 cases indicated positive by RT-PCR exhibited a wide range of values for cycle threshold, which is suggested to reflect variance in viral load despite all sharing a positive test that confirms their status as a Covid-19 case by orthodox means.
In viral samples found to be infectious by culture study, the mean cycle threshold value was indicated to be 18.8 ± 3.4, with a median value of 18.7. In samples that could not be cultured, indication samples to be non-infectious, a mean cycle threshold value of 27.1 ± 5.7, with a median of 27.5 was indicated.
The research found a general trend that observed an increase in cycle threshold as indicating a reduced viral load. Interestingly, the study found that some patients initially testing negative for SARS-CoV-2, received a positive result on a subsequent test, but that the follow up positive result indicated on previous negative patient was elicited with a cycle threshold >29.5, and that attempts to recover the infectious virus via culturing these specimens indicated the samples to be negative.
Indeed, Public Health England, acting on behalf of the United Kingdom government (177), state that the cycle threshold provides a value that is semi-quantitative and able to broadly categorise viral concentration within a sample collected by RT PCR, yet they add the context with regards to samples collected from the upper respiratory tract may be inadequately collected or represent a degraded sample, as such irrespective of the same sample being used to diagnose a case of Covid-19 disease, single same samples cycle threshold value is suggested to be unreliable, nothing that values for cycle threshold are not directly comparable due to variances in assays types, not only between laboratories but also within the same laboratory which may have used multiple assays.
The United Kingdom government/SAGE stance is that around six to seven percent of the population have been infected with SARS-CoV-2 due in part to seroprevalence studies of viral antibodies with in the blood (64), a position that is supported by Sekine et al (178), in an investigation of the close members of family members of patients with “confirmed” Covid-19 infection, finding T cell reactivity in individuals that were asymptomatic or seronegative. Approximately 60 percent of close family members were evidenced to produce antibodies, yet 90 percent evidenced T cell response, suggesting that despite infection, many did not produce, or maintain antibodies. Gallais et al (179), also concluded that SARS-CoV-2 may induce virus-specific T cell responses without seroconversion, and that reliance upon epidemiological data based uponSARS-CoV-2 detection may be substantial underestimating prior viral exposure within the population. Media attention has maintained a focus on antibody research, and in contrast to the above findings, studies such as Long et al (180), and Seow et al (181), that report the waning of SARS-CoV-2 antibodies to at around two to three months fuelled a narrative in both the media and in governmental policy (64; 182), that repeat infection was a plausible risk that necessitated extreme measures to protect not only the 94 percent that had escaped infection, but the minority six percent that had been theoretically infected already. (183)
Le Bert et al (184), state that “T cell reactivity was found for SARS 17 years after the patients were infected with SARS, which led them to suggest the possibility that T cells generation may protect or reduce the pathology of SARS-CoV-2 infection, this would suggest that the basic premise that antibody data would allow an understanding of whom remained at risk and who was protected is inherently flawed, a fact discussed by Altmann and Boyton. (185)
In reviews (186; 187), of the primary and secondary outcome measures of the phase III placebo controlled trials, T cell reactivity is not considered, thus pre-existing levels of immunity are not considered either in the need to vaccinate previously exposed individuals, or in regards to suggested outcomes that Covid-19 vaccination is currently suggested to confer only short term “immunity”. With studies concluding at 56 days it is currently impossible to suggest long term immunity is possible, and given that “immunity” is measured by antibodies, one must conclude that it does not look plausible given the above noted evidence.
“Immunity” via vaccination
The known candidates for Covid-19 vaccine are Pfizer (188), Moderna (189), Johnson & Johnson (190), and AstraZeneca (191), with Pfizer’s already being issued emergency authorisation in the United Kingdom at time of writing. Some degree of transparency occurred in publishing vaccine trial protocols, which while worthy of praise, the protocols do raise concerns that are seemingly being ignored, both by a nation seeking a silver bullet, and government looking for some semblance of success in what has to date been an unmitigated disaster.
The protocols utilised in the trials seem to have been specifically designed in order to prove the efficacy of the vaccines, despite minimal measured effects. A trial for a vaccine would typically be expected to have as a critical outcome measure, the prevention of infection. As discussed this would need to occur alongside both PCR testing that is controlled for in terms of cycle threshold, serological tests, antibody tests and more importantly T cell reactivity measures.
Yet all the trial conduced did not have the prevention of infection as a criterion for effectiveness, or success. for any of these vaccines. In all studies the primary suggestion of successful outcome was that in those with confirmed infections, the differences in symptoms severity between vaccinated and unvaccinated participant was indicated as vaccine effectiveness. Thus, a measured differences in symptoms amongst those identified as being infected with SARS-CoV-2 (the accuracy of which may be affected by cycle threshold) identifies that the so-called “vaccines” are not effective in preventing infection, or transmission, but theoretically may be effective in modifying symptom in those classed as infected.
In much of society an expectation, and indeed a belief may be that an effective vaccine is one that not only prevents serious disease, but transmission of the disease/virus to achieve the desired herd immunity. The trials by Pfizer and Moderna that have been indicted for emergency use authorisation in the United Kingdom, and the protocol used by AstraZeneca do not set out to establish that the product prevents serious disease, just that prevention of mild-moderate symptoms are prevented or reduced.
To test vaccine efficacy in disease prevention, large clinical studies may take many years and involve 30-60 thousand participants, rather than the less rigorous protocols that saw manufacturers achieve authorisation for emergency use by the Medicines and Healthcare products Regulatory Authority (MHRA), and seek emergency use authorization (EUA) from the United States Food and Drug Administration (FDA), via their limited preliminary results.
The protocols also set out rather mild symptoms as the stated requirements for diagnosis that an individual has contracted Covid-19. Minimum criteria to be included as a Covid-19 case is a positive PCR test, which has already been discussed in regards to issues with accuracy, and either one or two symptoms including fever, headache, mild nausea, or a cough, all symptoms that are notable not only as common cold symptoms, side effects following vaccination and more astonishingly are amongst some of the symptoms indicated for injection of sodium chloride which is used in the the placebo drug. (192; 193) Criteria for approval is indicated to be the variance in symptoms displayed in control and vaccine groups that are “infected”, with no use of measures of infection between groups.
For many holding out hope that a vaccine will have an ability to both prevent infection, severe illness and death, particularly in those with known preexisting conditions, or older members of society, the vaccine is hoped to allow social interaction to occur once again, yet severe illness and death outcomes are listed as secondary objectives. The prevention of death and even hospitalisation from SARS-CoV-2 infection are not critical to the phase III trials satisfactory conclusion.
In being deemed effective in the United Kingdom, and as is expected, in other nations, the trials conducted today have simply been set out in order that products can be established as effective by measure that presumably the lowest barriers to success. Whether this is yet again for political aplomb by a government in crisis, or simply part of an industry race to both meet demand and beat the competition remains to be seen. As things stand, work remains incomplete in establishing vaccine efficacy, and questions arise as to whether such detailed research will be completed, or if this “emergency response” will become the new normal in bringing pharmaceutical to market in global pandemics.
Pandemic Parlour Tricks
As has been discussed in this text as well as both Consistent Eating (143), and Controlling Intuitive Appetite (124), science and particularly research remains at risk of data hacking and other scientific attempts to skew evidence to maintain a hypothesis.
As has been discussed, increased amplification, or cycle thresholds have been identified as having the potential to increase false positive, to diagnose cases of Covid-19 in individuals who may not have active infections. The much fated second wave of Covid-19 in the United Kingdom saw a paradox in which “cases” grew exponentially in relation to “deaths with Covid-19”, which may have occurred due to a number of factors;
- Increased test availability when compared to early 2020
- A less lethal strain but with increased virulence
- Increased cycle threshold
This effect, whilst being plausibly deniable as either “conspiracy theory”, is in fact possible given that numbers of cases could be dialled up and down at will via a sleight of hand parlour trick that manipulates the data to suit the desired outcome. Whilst such underhand tactics may seem far fetched, one need only consider previous activities both within the industrial-medical complex, and government, particularly in the United States and the United Kingdom in relation to historical and recent manipulations. (7; 124)
Globally the establishment of RT-PCR testing as the Covid-19 gold standard has been flawed, indeed, without availability of viral material, a reliance was put upon the specific genetic sequence initially published by Chinese scientists (194)
Test protocols both globally and even within nations have utilised RT-PCR testing requiring two primer matches, instead of the preferred three, a potential “oversight” that may render such test protocols inaccurate in their ability to both delivery results, and in their use in comparing data against other variations of test protocols with Borger (195), suggesting that the use of such a poor PCR test protocol combined with a high cycle threshold (>35), as is common both in the United States and throughout Europe, that infection probability in a positively diagnosed person is <three percent, suggesting the probability of a false positive result is therefore 97 percent.
Even the United States Dr. Fauci is evidenced on video stating that; “If you get a cycle threshold of 35 or more…the chances of it being replication-competent are minuscule…you almost never can culture virus from a 37 threshold cycle…even 36…it’s just dead nucleotides, period.” (196)
As the virus apparently spreads rapidly with drastically increasing number of cases appearing despite the introduction of many measures (masks, social distancing et cetera), many have noted that a great majority of free from what may be classified as serious symptoms. This led to the warning initially that specific groups such as infants through to adolescents may be asymptomatic super spreaders (197), that while not evidently sick, did help transmit the virus amongst the community.
This narrative changed, specifically it seemed to alter when government required schooling facilities to reopen in order that the economy may also be opened by allowing parents and caregivers to outsources childcare once again allowing those who could to restart work. Around this period spread amongst younger people was partially dismissed as irrelevant, and asymptomatic spread was thus position as a community wide problem with potential for anyone without symptoms to spread SARS-CoV-2.
Remembering, as discussed in Controlling Intuitive Appetite (124), diseases are similar to language, and definitions alter as culture, or indeed industry manipulates its usage. Polios apparent eradication through vaccination is largely due to a manipulation of the classes of symptoms that now classify as polio. Jonas Salk’s miracle polio vaccine is a story perpetuated in current orthodox media, particularly in light of the announcement of Covid-19 vaccine availability. Polio, a disease often linked with dichlorodiphenyltrichloroethane (DDT) poisoning (198), prior to the introduction of the vaccine in 1955 >50,000 people within in the United States contracted polio per year, yet by 1955, a 45 percent decline was evident, and 1955 the figure was 28,985. (199)
Dr. Bernard Greenberg, the head of the University of Carolina School of Public Healths Department of Biostatistics stated that; qualification for diagnosis of paralytic poliomyelitis required a patient to be exhibit symptoms of paralytic state for at least 60 days following the diseases onset from 1955 onwards. Prior to the availability of vaccination (<1954), symptoms needed to be exhibited for just 24 hours with no need for conformation from either laboratory testing, or the residual presence of paralysis. Such changes in defined terms alter reporting and often lead to symptoms being attributed to other diseases classifications such as meant that in 1955 we started reporting a new disease, namely, “polio-like” illnesses such as transverse myelitis, acute flaccid paralyses, and aseptic meningitis which seem to be increasing in prevalence. (200; 201)
While some “polio” cases result in temporary paralysis, some present with no paralysis, and symptoms range from: fever, headache, sore throat, vomiting, fatigue, muscle aches/weakness, pain and stiffness in the back, neck or limbs, to meningitis. (202)
By redefining diagnostic criteria, this contributes to a downward shift in documented cases and a rise in other disease pathologies. Similar effects may be apparent in Covid-19 with similarity in pathology to other diseases, alterations in defined symptoms as time advances, with initial reports of symptoms for mild disease as;
Presenting with uncomplicated upper respiratory tract viral infection and may exhibit non-specific common symptoms;
- fever
- fatigue
- cough (both with or without production of sputum production)
- anorexia (medically described as lack of appetite/disinterest in food.
- malaise
- muscle pain
- sore throat
- dyspnea (difficulty or laboured breathing)
- nasal congestion
- headache
Indeed, as documented in Controlling Intuitive Appetite (124), science seems to be for sale to the highest bidder, with industry seemingly able to pay for desirable results to be both published and receive peer review. Yet a replication crisis seems apparent when others attempt to reproduce the same results. (206)
This replication/reproducibility crisis is a methodological effect evident in numerous scientific studies and fields in which the findings are either difficult or impossible to reproduce. Within the field of medicine Ioannidis (207), found that from a total of 49 studies conducted between the years 1990 to 2003, accounting for >1000 citations, 45 of the studies claimed effective therapeutic effect, yet 16 percent of the studies were subsequently contradicted by further studies.
Baker (208), conducted a survey of >1,500 researchers, with >70 percent stating they had attempted to reproduced the experiments of other scientists and failed to replicate the findings.
Again Ioannidis (209), highlights this problem, suggesting a need for research to become patient centred, rather than focusing upon the “needs of physicians, investigators, or sponsors.” Despite this crisis in academia, and the industrial pace at which Covid-19 research occurred, both under time pressures but free from normal peer review, we are told government are following “the science” and that we should trust the experts.
Scientific credibility is not only achieved by research, but by establishing further with evidence via their replicability with newly acquired data. This stands alone from retesting scientific “evidence” using the same data and analyses (reproducibility) and retesting existing data with various types of analyses (robustness), in such a situation outcomes that were consistent with the prior finding increase confidence in the “evidence”, and inconsistent outcomes decrease the confidence.
In Covid-19 it seems there is no exact replication occurring in testing and diagnosis, with every test potentially utilising different cycle thresholds amongst other factors such as assay variability. As such generalisability in data decreases the confidence in the findings as the potentially unique conditions applied to RT-PCR tests means that it can not be consider a replication study.
The inability to validate the test data to support either the number of presenting cases, or the much queried number of deaths “with Covid-19” (remember that while preventable deaths should indeed be considered tragic losses, even if not due to SARS-CoV-2), skewed data does not present a true picture of either the scale of the problem, or whether measures are appropriate or effective.
This coupled with the suggestion that antibody production remains low following infection, a process entirely expected in younger and or “healthy” populations that rather than diverting energy generation to a complex, slow and energy-intensive process of antibodies production, utilises what is termed the innate immune system, which works via a far more efficient process involving T-cells that defend against future infections. A such, one would expect to see little or no evidence of antibodies as timespan since infection progresses, and its use by SAGE to guide the proportion of infection amongst the population is either an error due to inadequate qualifications amongst a SAGE team primary constituting mathematicians, modellers and behaviourists, with a government also lacking in biological knowledge, or more lately due to some degree of malice by seeking to maintain a narrative that is unproven and undoubtably flailing.
Estimating SARS-CoV-2 infection rates within the United Kingdom population may be achieved using the known infection fatality ratio (IFR), which is in itself imperfect given that deaths with Covid-19 may still be false positive, but theoretically this is less problematic than the opposing stance of utilising antibody data in all cases including those codified asymptomatic.
Despite confidence in government, current policy leaves us with this “known unknown” that both seriously hampers understanding of the crisis and damages that response, an effect that has been seen by many as the pandemic rages in. The modelling by the Imperial College team (38), led by Professor Ferguson suggests that <7 percent of the population of the United Kingdom have been infected, which powerfully justifies prolonging and or reassuring lockdowns, social restrictions and early vaccination roll out. Relaxation of measures such as social distancing risks millions individuals becoming infected, the already depleted national health service becomes overwhelmed, as it does each winter. (210)
The model suggested excess deaths of circa 510,000 without precautions, and approximate 250,000 using a strategy of mitigation, dropping to 20,000 if the strategy was to suppress the virus. This suggests that a policy of lockdown would prevent 230,000 excess and unnecessary deaths occurring.
As this paper has sought to establish, the model propagated by Professor Ferguson seems to have drastically underestimated infection rates amongst the population. Indeed, a paper by Lourenço et al (211), led by Professor Gupta from Oxford University various estimates are suggested for percentage of infected (both current and prior) population within the United Kingdom, with figures as high as 68 percent. Critics claimed the work led by Professor Gupta was too “speculative” with little “empirical justification”, yet the Imperial model also falls foul of the same accusation. The previously discussed estimates are based upon assumptions built into the Imperial model created an implausible view of a novel virus, and as such one would assume that models could be updated and coded to work with newly available data, such as cycle thresholds for RT-PCR tests (for example >30 cycle threshold positive tests could be weighed more towards being indicative of prior infection), T-Cell reactivity et cetera.
Being able to increase the accuracy in gauging rate of infection helps not only guide and justify policy interventions, but helps to establish the infection fatality rate (IFR) which is vastly different from the case fatality rate (CFR), that uses the number individuals that tested positive (ignoring false positive and negative results) and is divided by the total deaths (ignoring questions about whether SARS-CoV-2 was the specific cause of death, or a co-factor). Variability in CFR occurs between country due to multiple variables including testing availability et cetera.
Ioannidis (212), led a team to assess the actual infection rates in Santa Clara County, California, using serology testing for antibodies, which as noted performs poorly in documenting longterm exposure rates, specifically in younger/“healthier”. The team looked at the data of 3,300 Santa Clara County residents in the United States and found rates of infection to 50 to 85 times that the amount of cases officially documented (956 at the time of the study).
Loss of antibodies, while biologically expected due previously explained reasons (antibodies production is energetically expensive, while T-Cell reactivity which is part of innate immune function is less so), is suggested as a reason for caution within communities (lockdown et cetera) do to the “known unknown” regarding whether re-infection is plausible. (213)
A Japanese woman (214), was suggested to have been re-infected but was classified as being “immunocompromised.” In considering this we must rationalise many aspects, firstly considering the terms, being classified as suffering from Covid-19 may not necessarily be due to being evidenced SARS-CoV-2 as was clear early in the pandemic within many nations, diagnostic testing was not available to many, as such symptoms were utilised and quarantine necessary. It must be noted that such symptoms are shared by many other pathologies including the common-cold which of course can be due to specific coronaviruses. We must also differentiate between two actual positive results, one may be indicative of a live virus evident by a RT-PCR utilising a low cycle threshold, the second may be a test procured due to the onset of similar symptoms and a positive result produced using a much higher cycle threshold. Without availability of data on test protocols we can not accurately consider whether reinfection is plausible. Indeed, in a case report by Prado-Vivar et al (215), they put forward evidence including epidemiological data, clinical findings, the positive RT-PCR re-test, two different virus clades and the antibody response as being compatible with reinfection, but admit a critical limitation of the study was the failure to culture the virus, as such we are unable to conclusively state whether it was reinfection to fragments of prior infectious viral material that is no longer live or presenting risk to others.
Viruses do mutate, and as noted tend to become more easily transmissible, but less dangerous. As discussed, it is implausible that as suggested by the Ferguson Imperial College model, that it presented a novel pathogen, by the nature of evolution it has ancestors and will continue to do so, but our exposure to one strain should confer some degree of immunity to further, specifically weaker strains. Access to cycle threshold data and T-Cell reactivity studies could re-code the current epidemiological models and provide better guided governance and strategic planning in both tackling the virus, restoring public confidence and creating a plan that allows the economy to reopen and stay open. Without such data, and in the hands of leadership relying upon so-called super-forcasters (216), the country seems destined for regular occurrence of lockdowns and cyclical vaccination programs to “protect” against reinfections of new strains. No doubt the country (and many other nations) are in the grips or a pandemic that is straining health care provisions beyond their capabilities, but it is important to gain context. In the United Kingdom austerity and poor management have not only limited the resources of the National Health Service, which is annually at breaking point each flu season, but staffing levels have suffered due to poor funding for students aiming to enter the health care industry, and poor retention of staff due to wage freezes and poor working conditions.
I wrote in Controlling Intuitive Eating (124), that intelligence may be better measured by the ability to observe, analyse and update beliefs. At this we are failing, while an emerging pathogen causes fear and reactionary strategies, as timespan increases “the science” could and should be updated rather than moulded to fit the policy. That this continues alongside issues of cronyism in government contracts from personal protective equipment (PPE), testing, and vaccination causes a further degree of distrust in the political strategies utilised to date.
Science needs to be utilised to its full capacity, not coopted to enable and justify policies that meets industrial and political desires.
References:
1. Leong, H, N., Earnest, A., Lim, H, H., Chin, C, F., Tan, C., Puhaindran, M. E., Tan, A., et al. (2006). SARS in Singapore--predictors of disease severity. Annals of the Academy of Medicine, Singapore. 35(5): 326-331.
2. Chan‐Yeung, M., & Xu, R, H. (2003). SARS: epidemiology. Respirology. 8: S9-S14.
3. Number of coronavirus (COVID-19) tests performed in the most impacted countries worldwide as of December 2, 2020* Retrieved 1st December 2020, from https://www.statista.com/statistics/1028731/covid19-tests-select-countries-worldwide/
4. WHO. (2003). Severe Acute Respiratory Syndrome (SARS): Laboratory diagnostic tests. Retrieved 29th November 2020, from https://www.who.int/csr/sars/diagnostictests/en/
5. In the Absence of SARS-CoV Transmission Worldwide: Guidance for Surveillance, Clinical and Laboratory Evaluation, and Reporting. Retrieved 29th November 2020, from https://www.cdc.gov/sars/surveillance/absence.html
6. Tseng, C, T., Sbrana, E., Iwata-Yoshikawa, N., Newman, P, C., Garron, T., Atmar, R, L., Peters, C, J., et al. (2012). Correction: Immunization with SARS Coronavirus Vaccines Leads to Pulmonary Immunopathology on Challenge with the SARS Virus. PLOS ONE. 7(8): 10.1371/annotation/2965cfae-b77d-4014-8b7b-236e01a35492. Retrieved 29th November 2020, from https://doi.org/10.1371/annotation/2965cfae-b77d-4014-8b7b-236e01a35492
7. Craig, B. (Unpublished). Pandemic Panic. WWBS Publishing. London.
8. Amanat, F., & Krammer, F. (2020). SARS-CoV-2 Vaccines: Status Report. Immunity. 52(4): 583-589. https://doi.org/https://doi.org/10.1016/j.immuni.2020.03.007
9. Roberts, M. (2020). Covid-19: Pfizer/BioNTech vaccine judged safe for use in UK. BBC News Online. Retrieved 5th December 2020, from https://www.bbc.co.uk/news/health-55145696
10. Pardi, N., Hogan, M., Porter, F., & Weissman, D. (2018). mRNA vaccines — a new era in vaccinology. Nat Rev Drug Discov. 17: 261-279.
11. Matzinger, P. (2013). Friendly and dangerous signals: is the tissue in control? Nat. Immunol. 8(1): 11-3.
12. Petrovsky, N., & Aguilar, J, C. (2004). Vaccine adjuvants: Current state and future trends. Immunology and Cell Biology. 82(5): 488-496.
13. Sasaki, S., & Okuda, K. (2000). The Use of Conventional Immunologic Adjuvants in DNA Vaccine Preparations. In Lowrie DB, Whalen RG (eds.). DNA Vaccines: Methods and Protocols. Methods in Molecular Medicine. 29. Humana Press. pp. 241-250.
14. Travis, K. (2007). Deciphering Immunology's Dirty Secret. The Scientist. Retrieved 10th November 2020, from https://www.the-scientist.com/uncategorized/deciphering-immunologys-dirty-secret-46896
15. Bousso, P., & Robey, E. (2003). Dynamics of CD8+ T cell priming by dendritic cells in intact lymph nodes. Nature Immunology. 4(6): 579-85.
16. Baylor, N, W., Egan, W., & Richman, P. (2002). Aluminum salts in vaccines--US perspective. Vaccine. 20(3): S18-23.
17. Tomljenovic, L. (2011). Aluminum and Alzheimer's disease: after a century of controversy, is there a plausible link? Journal of Alzheimer's disease. JAD. 23(4): 567-598.
18. Sanita, M., Ploen, D., & Kunz, K. (2014). The adjuvant component α-tocopherol triggers via modulation of Nrf2 the expression and turnover of hypocretin in vitro and its implication to the development of narcolepsy. Vaccine. 32(5): 2980-2988.
19. Petrik, M, S., Wong, M, C., Tabata, R, C., Garry, R, F., & Shaw, C, A. (2007). Aluminum adjuvant linked to Gulf War illness induces motor neuron death in mice. Neuromolecular Medicine. 9(1): 83-100.
20. Satoh, M., Kuroda, Y., Yoshida, H., Behney, K, M., Mizutani, A., Akaogi, J., Nacionales, D, C., et al. (2003). Induction of lupus autoantibodies by adjuvants. Journal of Autoimmunity. 21(1): 1-9.
21. Carlson BC, Jansson AM, Larsson A, Bucht A, Lorentzen JC (June 2000). The endogenous adjuvant squalene can induce a chronic T-cell-mediated arthritis in rats. The American Journal of Pathology. 156(6): 2057-65.
22. Richards, J, R., Elston, T, H., Ford, R, B., Gaskell, R, M., Hartmann, K., Hurley KF, Lappin MR, et al. (2006). The 2006 American Association of Feline Practitioners Feline Vaccine Advisory Panel report. Journal of the American Veterinary Medical Association. 229(9): 1405-41.
23. Kirpensteijn, J. (2006). Feline injection site-associated sarcoma: Is it a reason to critically evaluate our vaccination policies? Veterinary Microbiology. 117(1): 59-65.
24. BioNTech, Pfizer, and Fosun Pharma - BNT162b2. genengnews.com. Retrieved 10th December 2020, https://www.genengnews.com/covid-19-candidates/biontech-pfizer-and-fosun-pharma-bnt162/
25. REG 174 INFORMATION FOR UK RECIPIENTS. GOV.UK. Retrieved 10th December 2020, from https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/940566/Information_for_UK_recipients_on_Pfizer_BioNTech_COVID-19_vaccine.pdf
27. Pizzimenti, S., Heffler, E., Gentilcore, E., Raie, A., Bussolino, C., Nebiolo, F., & Rolla, G. (2014). Macrogol hypersensitivity reactions during cleansing preparation for colon endoscopy. The journal of allergy and clinical immunology. In practice. 2(3): 353-354.
28. Jakasa, I., Verberk, M. M., Esposito, M., Bos, J. D., & Kezic, S. (2007). Altered penetration of polyethylene glycols into uninvolved skin of atopic dermatitis patients. The Journal of investigative dermatology. 127(1): 129-134.
29. Borderé, A., Stockman, A., Boone, B., Franki, A.‐S., Coppens, M, J., Lapeere, H., & Lambert, J. (2012). A case of anaphylaxis caused by macrogol 3350 after injection of a corticosteroid. Contact Dermatitis. 67: 376-378.
30. Wenande, E., & Garvey, L, H. (2016). Immediate-type hypersensitivity to polyethylene glycols: a review. Clin Exp Allergy. 46(7): 907-22.
31. Hyry, H., Vuorio, A., Varjonen, E., Skytta, J., & Makinen-Kiljunen, S. (2006). Two cases of anaphylaxis to macrogol 6000 after ingestion of drug tablets. Allergy. 61(8): 1021.
32. Schuman, E., & Balsam, P, E. (1991). Probable anaphylactic reaction to polyethylene glycol electrolyte lavage solution. Gastrointest Endosc. 37(3): 411.
33. Fisher, A, A. (1978). Immediate and delayed allergic contact reactions to polyethylene glycol. Contact Dermat. 4(3): 135-8.
34. Yamasuji, Y., Higashi, Y., Sakanoue, M., Katsue, H., Kawai, K., Arai, N., & Kanekura, T. (2013). A case of anaphylaxis caused by polyethylene glycol analogues. Contact Dermatitis. 69: 183-185.
35. Wenande, E, C., Skov, P, S., Mosbech, H., Poulsen, L, K., & Garvey, L, H. (2013). Inhibition of polyethylene glycol-induced histamine release by monomeric ethylene and diethylene glycol: a case of probable polyethylene glycol allergy. The Journal of allergy and clinical immunology. 131(5): 1425-1427.
36. Pottel, J., Armstrong, D., Zou, L., Fekete, A., Huang, X.-P., Torosyan, H., Bednarczyk, D., et al. (2020). The activities of drug inactive ingredients on biological targets. Science. 369(6502): 403 LP-413.
37. Regalado, A. (2020). What are the Ingredients of Pfizer’s Covid-19 Vaccine? MIT Technology Review. Retrieved 15th December 2020, from https://www.technologyreview.com/2020/12/09/1013538/what-are-the-ingredients-of-pfizers-covid-19-vaccine/
38. Ferguson, N, M., Laydon, D., Nedjati-Gilani, G., Imai, N., Ainslie, K., Baguelin, M., Bhatia, S., et al. (2020). Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. Imperial College COVID-19 Response Team. Retrieved 10th Dec 2020, from https://www.imperial.ac.uk/media/imperial-college/medicine/mrc-gida/2020-03-16-COVID19-Report-9.pdf
39. Doshi, P. (2020). Covid-19: Do many people have pre-existing immunity? BMJ. 370 :m3563. Retrieved 10th November 2020, from https://www.bmj.com/content/370/bmj.m3563
40. Ng, K, W., Faulkner, N., Cornish, G, H., Rosa, A., Harvey, R., Hussain, S., Ulferts, R., et al. (2020). (2020). Pre-existing and de novo humoral immunity to SARS-CoV-2 in humans. BioRxiv, 2020.05.14.095414. https://doi.org/10.1101/2020.05.14.095414
41. Weiskopf, D., Schmitz, K, S., Raadsen, M, P., Grifoni, A., Okba, N, M, A., Endeman, H., Johannes P.C. van den Akker, J, P-C., et al. (2020). Phenotype of SARS-CoV-2-specific T-cells in COVID-19 patients with acute respiratory distress syndrome. MedRxiv, 2020.04.11.20062349. https://doi.org/10.1101/2020.04.11.20062349
42. Le Bert, N., Tan, A. T., Kunasegaran, K., Tham, C., Hafezi, M., Chia, A., Chng, M., et al. (2020). SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls. Nature. 584(7821): 457-462.
43. Meckiff, B, J., Ramírez-Suástegui, C., Fajardo, V., Chee, S, J., Kusnadi, A., Simon, H., Grifoni, A., et al. (2020). Single-cell transcriptomic analysis of SARS-CoV-2 reactive CD4 + T cells. bioRxiv :the preprint server for biology. 2020.06.12.148916. Retrieved 11th November 2020, https://doi.org/10.1101/2020.06.12.148916
44. Sekine, T., Perez-Potti, A., Rivera-Ballesteros, O., Strålin, K., Gorin, J-B., Olsson, A., Llewellyn-Lacey, S., et al. (2020). Robust T cell immunity in convalescent individuals with asymptomatic or mild COVID-19 [preprint]. Retrieved 12th November 2020, from https://www.biorxiv.org/content/10.1101/2020.06.29.174888v1.abstract.
45. Sette, A., & Crotty, S. (2020). Pre-existing immunity to SARS-CoV-2: the knowns and unknowns. Nat Rev Immunol. 20: 457-8. Retrieved 22nd November 2020, from doi:10.1038/s41577-020-0389-z pmid:32636479
46. Chavarria-Miró, G., Anfruns-Estrada, E., Guix, S., Paraira, M., Galofré, B., Sáanchez, G., Pintó, R., et al. (2020). Sentinel surveillance of SARS-CoV-2 in wastewater anticipates the occurrence of COVID-19 cases. MedRxiv, 2020.06.13.20129627. https://doi.org/10.1101/2020.06.13.20129627
47. Basavaraju, S. V, Patton, M. E., Grimm, K., Rasheed, M. A. U., Lester, S., Mills, L., Stumpf, M., et al. (2020). Serologic testing of U.S. blood donations to identify SARS-CoV-2-reactive antibodies: December 2019-January 2020. Clinical Infectious Diseases. https://doi.org/10.1093/cid/ciaa1785
48. Butter, M. (2020). There’s a conspiracy theory that the CIA invented the term ‘conspiracy theory’ – here’s why. The Conversation. Retrieved 20th September 2020, from https://theconversation.com/theres-a-conspiracy-theory-that-the-cia-invented-the-term-conspiracy-theory-heres-why-132117
49. Talbot, D. (2015). The devil's chessboard: Allen Dulles, the CIA, and the rise of America's secret government. Harper Collins.
50. Baquiran, M., & Al Khalili, Y. (2020). Lysergic Acid Diethylamide Toxicity. In StatPearls. StatPearls Publishing.
51. Wyatt, T. (2019). Research into deadly viruses and biological weapons at US army lab shut down over fears they could escape. The Independent. Retrieved 5th April 2020, from https://www.independent.co.uk/news/world/americas/virus-biological-us-army-weapons-fort-detrick-leak-ebola-anthrax-smallpox-ricin-a9042641.html
52. Isbell, H., Belleville, R, E., Fraser, H, F., Wikler, A., Logan, C, R. (1956). Studies on Lysergic Acid Diethylamide (LSD-25) I: Effects in Former Morphine Addicts and Development of Tolerance During Chronic Intoxication. AMA Archives of Neurology and Psychiatry. 76(5): 468-478.
53. Zubay, G, L. (2005). Agents of Bioterrorism: Pathogens and Their Weaponization. Columbia University Press. pp. 132.
54. Pittman, P, R., Norris, S, L., Coonan, K, M., & McKee, K, T., Jr. (2005). An assessment of health status among medical research volunteers who served in the Project Whitecoat program at Fort Detrick, Maryland. Military medicine. 170(3): 183-187.
55. Kinzer, S. (2019). The Secret History of Fort Detrick, the CIA’s Base for Mind Control Experiments. Politico Magazine. Retrieved 20th April 2020, from https://www.politico.com/magazine/story/2019/09/15/cia-fort-detrick-stephen-kinzer-228109
56. Hensley, L, E., Fritz, L, E., Jahrling, P, B., Karp, C, L., Huggins, J, W., & Geisbert, T, W. (2004). Interferon-beta 1a and SARS coronavirus replication. Emerging Infectious Diseases, 10(2): 317–319.
57. Lisa Hensley (microbiologist). Wikipedia. Retrieved 20th July 2020, from https://en.wikipedia.org/wiki/Lisa_Hensley_(microbiologist)
58. Patents by Inventor Lisa E. Hensley. Retrieved 20th August 2020, from https://patents.justia.com/inventor/lisa-e-hensley
59. Branswell, H. (2018). ’You’re holding your breath’: Scientists who toiled for years on an Ebola vaccine see the first one put to the test. Stat. Retrieved 20th May 2020, from https://www.statnews.com/2018/05/22/ebola-scientists-outbreak/
60. Yount, B., Curtis, K. M., Fritz, E. A., Hensley, L. E., Jahrling, P. B., Prentice, E., Denison, M, R., et al. (2003). Reverse genetics with a full-length infectious cDNA of severe acute respiratory syndrome coronavirus. Proceedings of the National Academy of Sciences. 100(22): 12995 LP-13000.
61. Transparency data. List of participants of SAGE and related sub-groups. GOV.UK. Retrieved 20th August 2020, from https://www.gov.uk/government/publications/scientific-advisory-group-for-emergencies-sage-coronavirus-covid-19-response-membership/list-of-participants-of-sage-and-related-sub-groups
62. Yan, Y., Chang, L., & Wang, L. (2020). Laboratory testing of SARS-CoV, MERS-CoV, and SARS-CoV-2 (2019-nCoV): Current status, challenges, and countermeasures. Reviews in medical virology. 30(3): e2106.
63. Summary of the effectiveness and harms of different non-pharmaceutical interventions. GOV.UK. Retrieved 10th December 2020, from https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/925854/S0769_Summary_of_effectiveness_and_harms_of_NPIs.pdf
64. Largest study on home coronavirus antibody testing publishes first findings. (2020). Imperial College Healthcare. News. Retrieved 10th December 2020, from https://www.imperial.nhs.uk/about-us/news/largest-home-antibody-testing-publishes-results
65. The official UK Government website for data and insights on Coronavirus (COVID-19). UK Summary. Retrieved 10th December 2020, from https://coronavirus.data.gov.uk
66. Ioannidis, J, P, A. (2020). Global perspective of COVID-19 epidemiology for a full-cycle pandemic. European Journal of Clinical Investigation. 50(12): e13423.
67. Zhu, Z., Lian, X., Su, X., Wu, W., Marraro, G, A., & Zeng, Y. (2020). From SARS and MERS to COVID-19: a brief summary and comparison of severe acute respiratory infections caused by three highly pathogenic human coronaviruses. Respir Res. 21: 224.
68. Estola, T. (1970). Coronaviruses, a New Group of Animal RNA Viruses. Avian Diseases. 14(2): 330-336.
69. Fabricant, J. (1998). The Early History of Infectious Bronchitis. Avian Diseases. 42(4): 648-650.
70. Weiss, S, R. (2020). Forty years with coronaviruses. J Exp Med. 2020;217:e20200537.
71. Monto, A, S. (1984). Coronaviruses. In Evans AS (ed.). Viral Infections of Humans. Viral Infections of Humans: Epidemiology and Control. Springer US. pp. 151-165.
72. Kendall, E, J., Bynoe, M, L., & Tyrrell, D, A. (1962). Virus isolations from common colds occurring in a residential school. British Medical Journal. 2(5297): 82-6.
73. Tyrrell, D, A., & Bynoe, M, L. (1965). Cultivation of a Novel Type of Common-Cold Virus in Organ Cultures. British Medical Journal. 1(5448): 1467-70.
74. Tyrrell, D, A., & Fielder, M. (2002). Cold Wars: The Fight Against the Common Cold. Oxford University Press. pp. 93-95.
75. Gonzalez, J, M., Gomez-Puertas, P., Cavanagh, D., Gorbalenya, A, E., & Enjuanes, L. (2003). A comparative sequence analysis to revise the current taxonomy of the family Coronaviridae. Arch. Virol. 148(11): 2207-2235.
76. Weiss, S, R., & Navas-Martin, S. (2005). Coronavirus pathogenesis and the emerging pathogen severe acute respiratory syndrome coronavirus. Microbiol. Mol. Biol. Rev. 69(4): 635-664.
77. Bradburne, A, F., Bynoe, M, L., & Tyrrell, D, A. (1967). Effects of a ‘new’ human respiratory virus in volunteers. Br. Med. J. 3(5568): 767-769.
78. vander Hoek, L. (2007). Human coronaviruses: what do they cause? Antivir.Ther.12(4): 651-658.
79. van der Hoek, L., Pyrc, K., Jebbink, M, F., Vermeulen-Oost, W., Berkhout, R, J., Wolthers, K, C., Wertheim-van, P, M., et al. (2004). Identification of a new human coronavirus. Nat. Med. 10(4): 368-373.
80. Woo, P, C., Lau, S, K. K., Chu, C, M., Chan, K, H., Tsoi, H, W., Huang, Y., Wong, B, H., et al. 2005. Characterization and complete genome sequence of a novel coronavirus, coronavirus HKU1, from patients with pneumonia. J. Virol. 79(2): 884-895.
81. Kahn, J, S., & McIntosh, K. (2005). History and recent advances in coronavirus discovery. The Pediatric Infectious Disease Journal. 24(11): S223-7, discussion S226.
82. Kendall, E, J., Bynoe, M, L., & Tyrrell, D, A. (1962). Virus isolations from common colds occurring in a residential school. British Medical Journal. 2 (5297): 82-6.
83. Tyrrell, D, A., & Bynoe, M, L. (1965). Cultivation of a Novel Type of Common-Cold Virus in Organ Cultures. British Medical Journal. 1(5448): 1467-70.
84. Hamre, D., & Procknow, J, J. (1966). A new virus isolated from the human respiratory tract. Proceedings of the Society for Experimental Biology and Medicine. Society for Experimental Biology and Medicine. 121(1): 190-3.
85. Jiang, S., Hillyer, C., & Du, L. (2020). Neutralizing Antibodies against SARS-CoV-2 and Other Human Coronaviruses. Trends in Immunology. 41(5): 355-359.
86. Sparks, M. A., Crowley, S, D., Gurley, S, B., Mirotsou, M., & Coffman, T, M. (2014). Classical Renin-Angiotensin system in kidney physiology. Comprehensive Physiology. 4(3): 1201-1228.
87. Zimmerman, B, G., & Dunham, E, W. (1997). Tissue renin–angiotensin system: a site of drug action? Annu. Rev. Pharmacol. Toxicol. 37: 53-69.
88. Fleming, I., Kohlstedt, K., & Busse, R. (2006). The tissue renin–angiotensin system and intracellular signalling. Curr. Opin. Nephrol. Hypertens. 15(1): 8-13.
89. Nicholls, M, G., Richards, A, M., & Agarwal, M. (1998). The importance of the renin–angiotensin system in cardiovascular disease. J. Hum. Hypertens. 12(5): 295-299.
90. Batenburg, W, W., & Jan-Danser, A, H. (2008). The (pro)renin receptor: a new addition to the renin–angiotensin system? Eur. J. Pharmacol. 585(2–3): 320-324.
91. Hackenthal, E., Paul, M., Ganten, D., & Taugner, R. (1990). Morphology, physiology, and molecular biology of renin secretion. Physiol. Rev. 70(4): 1067-1116.
92. Paul, M., &Poyan-Mehr, A., & Kreutz, R. (2006). Physiology of local renin–angiotensin systems. Physiol. Rev. 86(3): 747-803.
93. Kurdi, M., De Mello, W, C., & Booz, G, W. (2005). Working outside the system: an update on the unconventional behavior of the renin–angiotensin system components. Int. J. Biochem. Cell Biol. 37(7): 1357-1367.
94. Lindberg, B, F., Gyllstedt, E., Andersson, K, E. (1997). Conversion of angiotensin I to angiotensin II by chymase activity in human pulmonary membranes. Peptides. 18(6): 847-853.
95. Veerappan, A., Reid, A. C., Estephan, R., Connor, N., Thadani-Mulero, M., Salazar-Rodriguez, M., Levi, R., et al. (2008). Mast cell renin and a local renin–angiotensin system in the airway: Role in bronchoconstriction. Proceedings of the National Academy of Sciences, 105(4): 1315LP-1320.
96. Andersson, C, K., Mori, M., Bjermer, L., Lofdahl, C, G., Erjefalt, J, S. (2009). Novel site-specific mast cell subpopulations in the human lung. Thorax. 64(4): 297-305.
97. Boyce, J, A. (2003). The role of mast cells in asthma. Prostaglandins Leukot. Essent. Fatty Acids. 69(2–3): 195-205.
98. Studdy, P, R., Lapworth, R., & Bird, R. (1983). Angiotensin-converting enzyme and its clinical significance - a review. J. Clin. Pathol. 36(8): 938-947.
99. Bullock, G. R., Steyaert, I., Bilbe, G., Carey, R. M., Kips, J., De Paepe, B., Pauwels, R., et al. (2001). Distribution of type-1 and type-2 angiotensin receptors in the normal human lung and in lungs from patients with chronic obstructive pulmonary disease. Histochemistry and Cell Biology. 115(2): 117-124.
100. Hamming, I., Timens, W., Bulthuis, M, L., Lely, A, T., Navis, G, J., & van Goor, H. (2004). Tissue distribution of ACE2 protein, the functional receptor for SARS coronavirus. A first step in understanding SARS pathogenesis. J. Pathol. 203(2): 631-637.
101. Wang, W., O’Connell, B., Dykeman, R., Sakai, T., Delporte, C., Swaim, W., et al. (1999). Angiotensin II induces apoptosis in human and rat alveolar epithelial cells. Am. J. Physiol. 276(5 Pt 1): L885-L889.
102. Papp, M., Li, X., Zhuang, J., Wang, R., & Uhal, B, D. (2002). Angiotensin receptor subtype AT(1) mediates alveolar epithelial cell apoptosis in response to ANG II. Am. J. Physiol. Lung Cell Mol. Physiol. 282(4): L713-L718.
103. Ferrario, C, M., Trask, A, J., Jessup, J, A. (2005). Advances in biochemical and functional roles of angiotensin-converting enzyme 2 and angiotensin-(1–7) in regulation of cardiovascular function. Am. J. Physiol. Heart Circ. Physiol. 289(6): H2281-H2290.
104. Hamming, I., Cooper, M, E., Haagmans, B, L., Hooper, N, M., Korstanje, R., Osterhaus, A., Timens, W., et al. (2007). The emerging role of ACE2 in physiology and disease. J. Pathol. 212(1): 1–11.
105. Kuba, K., Imai, Y., & Penninger, J, M. (2006). Angiotensin-converting enzyme 2 in lung diseases. Curr. Opin. Pharmacol. 6(3): 271-276.
106. Csaszar, A., Halmos, B., Palicz, T., Szalai, C., & Romics, L. (1997). Interpopulation effect of ACE I/D polymorphism on serum concentration of ACE in diagnosis of sarcoidosis. Lancet. 350(9076): 518.
107. Idell, S., Kueppers, F., Lippmann, M., Rosen, H., Niederman, M., & Fein, A. (1987). Angiotensin converting enzyme in bronchoalveolar lavage in ARDS. Chest. 91(1): 52-56.
108. Orte, C., Polak, J, M., Haworth, S, G., Yacoub, M, H., & Morrell, N, W. (2000). Expression of pulmonary vascular angiotensin-converting enzyme in primary and secondary plexiform pulmonary hypertension. J. Pathol. 192(3): 379-384.
109. Imai, Y., Kuba, K., Rao, S., Huan, Y., Guo, F., Guan, B., Yang, P., et al. (2005). Angiotensin-converting enzyme 2 protects from severe acute lung failure. Nature. 436(7047): 112-116.
110. Ware, L, B., & Matthay, M, A. (2000). The acute respiratory distress syndrome. N. Engl. J. Med. 342(18): 1334-1349.
111. Rubenfeld, G, D., Caldwell, E., Peabody, E., Weaver, J., Martin, D, P., Neff, M., Stern, E, J., et al. (2005). Incidence and outcomes of acute lung injury. N. Engl. J. Med. 353(16): 1685-1693.
112. Raiden, S., Nahmod, K., Nahmod, V., Semeniuk, G., Pereira, Y., Alvarez, C., Giordano, M., et al. (2002). Nonpeptide antagonists of AT1 receptor for angiotensin II delay the onset of acute respiratory distress syndrome. J. Pharmacol. Exp. Ther. 303(1): 45-51.
113. Nicholls, J., & Peiris, M. (2005). Good ACE, bad ACE do battle in lung injury, SARS. Nat. Med. 11(8): 821-822.
114. Chan-Yeung, M., & Xu, R, H. (2003). SARS: epidemiology. Respirology. 8(1): S9-14.
115. Chan, P, K, S., Wing-Kin, T., King-Cheung, N., Lam, R, K, Y., Tak-Keung, N., Chan, R, C, W., Wu, A., et al. (2004). Laboratory Diagnosis of SARS. Emerging Infectious Diseases. 10(5): 825-31.
116. Monaghan, K, J. (2004). SARS: Down But Still a Threat. National Academies Press (US).
117. Li, W., Moore, M, J., Vasilieva, N., Sui, J., Wong, S, K., Berne, M, A., Somasundaran, M., et al. (2003). Angiotensin-converting enzyme 2 is a functional receptor for the SARS coronavirus. Nature. 426(6965): 450-454.
118. Kuba, K., Imai, Y., Rao, S., Gao, H., Guo, F., Guan, B., Huan, Y., et al. (2005). A crucial role of angiotensin converting enzyme 2 (ACE2) in SARS coronavirus-induced lung injury. Nature medicine. 11(8): 875-879.
119. Frieman, M., & Baric, R. (2008). Mechanisms of severe acute respiratory syndrome pathogenesis and innate immunomodulation. Microbiol. Mol. Biol. Rev. 72(4): 672-685.
120. Nicholls, J., & Peiris, M. (2005). Good ACE, bad ACE do battle in lung injury, SARS. Nat. Med.11(8): 821-822.
121. Toelzer, C., Gupta, K., Yadav, S, K, N., Borucu, U., Davidson, A, D., Kavanagh Williamson, M., Shoemark, D. K., et al. (2020). Free fatty acid binding pocket in the locked structure of SARS-CoV-2 spike protein. Science. 370(6517): eabd3255.
122. Ling, P, R., Malkan, A., Le, H, D., Puder, M., & Bistrian, B, R. (2012). Arachidonic acid and docosahexaenoic acid supplemented to an essential fatty acid-deficient diet alters the response to endotoxin in rats. Metabolism: clinical and experimental. 61(3): 395-406.
123. Bursten, S, L., Federighi, D, A., Parsons, P., Harris, W. E., Abraham, E., Moore, E, E., Jr, Moore, F, A., et al. (1996). An increase in serum C18 unsaturated free fatty acids as a predictor of the development of acute respiratory distress syndrome. Critical care medicine. 24(7): 1129-1136.
124. Craig, B. (Unpublished). Controlling Intuitive Appetite. WWBS Publishing. London.
125. Hanna, V, S., & Hafez, E, A, A. (2018). Synopsis of arachidonic acid metabolism: A review. Journal of Advanced Research. 11: 23-32.
126. Malcom, G, T., Bhattacharyya, A, K., Velez-Duran, M., Guzman, M, A., Oalmann, M, C., & Strong, J, P. (1989). Fatty acid composition of adipose tissue in humans: differences between subcutaneous sites. The American journal of clinical nutrition. 50(2): 288-291.
127. Mamalakis, G., Kafatos, A., Manios, Y., Kalogeropoulos, N., & Andrikopoulos, N. (2002). Abdominal vs buttock adipose fat: relationships with children's serum lipid levels. European journal of clinical nutrition. 56(11): 1081-1086.
128. Pittet, P, G., Halliday, D., & Bateman, P, E. (1979). Site differences in the fatty acid composition of subcutaneous adipose tissue of obese women. The British journal of nutrition. 42(1): 57-61.
129. Phinney, S, D., Stern, J, S., Burke, K, E., Tang, A, B., Miller, G., & Holman, R, T. (1994). Human subcutaneous adipose tissue shows site-specific differences in fatty acid composition. The American journal of clinical nutrition. 60(5): 725-729.
130. El-Kurdi, B., Khatua, B., Rood, C., Snozek, C., Cartin-Ceba, R., Singh, V, P., & Group, L. in C.-19 S. (2020). Mortality From Coronavirus Disease 2019 Increases With Unsaturated Fat and May Be Reduced by Early Calcium and Albumin Supplementation. Gastroenterology. 159(3): 1015-1018.
131. Whelan, J., & Fritsche, K. (2013). Linoleic acid. Advances in Nutrition (Bethesda, Md.). 4(3): 311-312.
132. Food and Nutrition Board, Institute of Medicine. Dietary Fats: Total Fat and Fatty Acids. Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids. Washington, D.C.: National Academies Press. (2002): pp. 422-541.
133. Varsano, S., Rashkovsky, L., Shapiro, H., Ophir, D., & Mark-Bentankur, T. (1998). Human lung cancer cell lines express cell membrane complement inhibitory proteins and are extremely resistant to complement-mediated lysis; a comparison with normal human respiratory epithelium in vitro, and an insight into mechanism(s) of resistance. Clinical and Experimental Immunology. 113(2): 173-182.
134. Ling, G. (2007). History of the membrane (pump) theory of the living cell from its beginning in mid-19th century to its disproof 45 years ago--though still taught worldwide today as established truth. Physiological chemistry and physics and medical NMR. 39(1): 1-67.
135. Snell, N, J, C. (2001). New treatments for viral respiratory tract infections-opportunities and problems. Journal of Antimicrobial Chemotherapy. 47: 251-259.
136. Peat, R. (2013). Fats, functions & malfunctions. Retrieved 22nd August 2020, from http://raypeat.com/articles/articles/fats-functions-malfunctions.shtml
137. Canbay, A., Bechmann, L., & Gerken, G. (2007). Lipid metabolism in the liver. Zschr. Gastroenterol. 45: 35-41.
138. Cook, J, A., Wise, W, C., Knapp, D, R., & Halushka, P, V. (1981). Essential fatty acid deficient rats: a new model for evaluating arachidonate metabolism in shock. Advances in shock research. 6: 93-105.
139. Li, E, J., Cook, J, A., Spicer, K, M., Wise, W, C., Rokach, J., & Halushka, P, V. (1990). Resistance of essential fatty acid-deficient rats to endotoxin-induced increases in vascular permeability. Circulatory shock. 31(2): 159-170.
140. Autore, G., Cicala, C., Cirino, G., Maiello, F, M., Mascolo, N., & Capasso, F. (1994). Essential fatty acid-deficient diet modifies PAF levels in stomach and duodenum of endotoxin-treated rats. Journal of lipid mediators and cell signalling. 9(2): 145-153.
141. Craig, B. (Unpublished). Therapeutic Carbon Dioxide. WWBS Publishing. London.
142. Morganroth, M. L., Schoeneich, S. O., Till, G. O., Pickett, W., & Ward, P. A. (1989). Lung injury caused by cobra venom factor is reduced in rats raised on an essential fatty acid-deficient diet. The American journal of physiology. 257(4 Pt 2): H1192-H1199.
143. Craig, B. (2020). Consistent Eating. WWBS Publishing. London.
144. Chiu, R, W., Tang, N, L., Hui, D, S., Chung, G, T, Y., Chim, S, S, C., Chan, K, C, A., Ying-man Sung, Y-M., et al. (2004). ACE2 gene polymorphisms do not affect outcome of severe acute respiratory syndrome. Clin. Chem.50(9): 1683–1686.
145. Itoyama, S., Keicho, N., Hijikata, M., Quy, T., Phi, N, C., Long, H, T., Le Dang, H., et al. (2005). Identification of an alternative 5´-untranslated exon and new polymorphisms of angiotensin-converting enzyme 2 gene: lack of association with SARS in the Vietnamese population. Am. J. Med. Genet. A. 136(1): 52-57.
146. Weidmann, P., De Myttenaere-Bursztein, S., Maxwell, M, H., & de Lima, J. (1975). Effect on aging on plasma renin and aldosterone in normal man. Kidney Int. 8(5): 325-333.
147. Corman, B., Barrault, M, B., Klingler, C., Houot, A, M., Michel, J, B., Della Bruna, R., Pinet, F., et al. (1995). Renin gene expression in the aging kidney: effect of sodium restriction. Mech. Ageing Dev. 84(1): 1-13.
148. Cameron, M, J., Bermejo-Martin, J, F., Danesh, A., Muller, M, P., & Kelvin, D, J. (2008). Human immunopathogenesis of severe acute respiratory syndrome (SARS). Virus Res. 133(1): 13-19.
149. Brown, N, J., & Vaughan, D, E. (2000). Prothrombotic effects of angiotensin. Advances in internal medicine. 45: 419-429.
150. Kubo, M., Quayle, J, M., & Standen, N, B. (1997). Angiotensin II inhibition of ATP-sensitive K+ currents in rat arterial smooth muscle cells through protein kinase C. The Journal of Physiology. 503(3): 489-496.
151. Lalchhandama, K. (2020). The chronicles of coronaviruses: the electron microscope, the doughnut, and the spike. Science Vision. 20(2): 78-92.
152. Neuman, B, W., Kiss, G., Kunding, A, H., Bhella, D., Baksh, M, F., Connelly S., Droese, B., et al. (April 2011). A structural analysis of M protein in coronavirus assembly and morphology. Journal of Structural Biology. 174 (1): 11-22.
153. Zitek, T. (2020). The Appropriate Use of Testing for COVID-19. The western journal of emergency medicine. 21(3): 470-472.
154. Lai, M, M., & Cavanagh, D. (1997). The molecular biology of coronaviruses. Advances in Virus Research. 48: 1-100.
155. Cepheid Innovation Technical Datasheet. Retrieved 12th December 2020, from https://www.cepheid.com/coronavirus
156. Gupta, S. (2020). Matt Hancock is wrong about herd immunity. Unherd. Retrieved 20th November 2020, from https://unherd.com/2020/10/matt-hancock-is-wrong-about-herd-immunity/
156. Centers for Disease Control. Coronavirus Symptoms. Retrieved 20th September 2020, from https://www.cdc.gov/coronavirus/2019-ncov/about/symptoms.html
157. Human Disease Case Fatality Rate. Wikipedia. Retrieved 12th July 2020, from https://en.wikipedia.org/wiki/List_of_human_disease_case_fatality_rates
158. Chest CT for Typical 2019-nCoV Pneumonia: Relationship to Negative RT-PCR Testing: Radiology. https://doi.org/10.1148/radiol.2020200343. Accessed 12th March, 2020.
159. Time Course of Lung Changes On Chest CT During Recovery From 2019 Novel Coronavirus (Covid-19) Pneumonia: Radiology. https://doi.org/10.1148/radiol.2020200370. Accessed 12th March, 2020.
160. U.S. Food and Drug Administration: https://www.fda.gov/news-events/press-announcements/fda-takes-significant-step-coronavirus-response-efforts-issues-emergency-use-authorization-first?utm_campaign=020420_PR_FDA%20Issues%20EUA%20for%20First%202019%20Novel%20Coronavirus%20Diagnostic&utm_medium=email&utm_source=Eloqua. Accessed 12th March, 2020.
161. Public Health News Alert: CMS Develops New Code for Coronavirus Lab Test. https://www.cms.gov/. Accessed 12th March, 2020.
162. Borst, A., Box, A,T., Fluit, A,C. (2004). False-positive results and contamination in nucleic acid amplification assays: suggestions for a prevent and destroy strategy. Eur J Clin Microbiol Infect Dis. 23(4): 289-99.
163. Cheng, S., Fockler, C., Barnes, W, M., & Higuchi, R. (1994). Effective Amplification of Long Targets from Cloned Inserts and Human Genomic DNA. Proceedings of the National Academy of Sciences. 91(12): 5695-5699.
164. Hillman, H. (1989). Uncertainties, artifacts, uncontrolled experiments and incomplete evidence in modern biology. Physiol Chem Phys Med NMR. 21(2): 145-60; discussion 160-3.
165. Corman, V, M., Landt, O., Kaiser, M., Molenkamp, R., Meijer, A., Chu, D, K, W., Bleicker, T., et al. (2020). Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Eurosurveillance. 25(3): 23/Jan/2020. Accessed 12th March, 2020 https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2020.25.3.2000045
166. Chu, D, K, W., Pan, Y., Cheng, S, M, S., Hui, K, P, Y., Krishnan, P., Liu, Y., … Poon, L, L, M. (2020). Molecular Diagnosis of a Novel Coronavirus (2019-nCoV) Causing an Outbreak of Pneumonia. Clinical Chemistry. https://doi.org/10.1093/clinchem/hvaa029
167. Wang, M., Wu, Q., Xu, W., Qiao, B., Wang, J., Zheng, H., Jiang, S., et al. (2020). Clinical diagnosis of 8274 samples with 2019-novel coronavirus in Wuhan. MedRxiv, 2020.02.12.20022327. https://doi.org/10.1101/2020.02.12.20022327
168. Semendeferi, I. (2008). Legitimating a Nuclear Critic: John Gofman, Radiation Safety, and Cancer Risks", Historical Studies in the Natural Sciences. 38(2): 300.
169. Linnane, C. (2020). Inovio shares rally after biotech says human trials of coronavirus vaccine will start in April. Market Watch. Retrieved 20th June 2020, from https://www.marketwatch.com/story/inovio-shares-rally-after-biotech-says-human-trials-of-coronavirus-vaccine-will-start-in-april-2020-03-03
170. Mandel, D, R. (2014). The psychology of Bayesian reasoning. Frontiers in Psychology. 5: 1144.
171. Eddy, D, M. (1982). Probabilistic reasoning in clinical medicine: problems and opportunities, in Judgment under Uncertainty: Heuristics and Biases, eds Kahneman D., Slovic P., Tversky A., editors. New York, NY: Cambridge University Press. pp. 249-267.
172. Casscells, W., Schoenberger, A., & Graboys, T, B. (1978). Interpretation by physicians of clinical laboratory results. N Engl J Med. 299(18): 999-1001.
173. Zhang, J, J., Dong, X., Cao, Y, Y., Yuan, Y, D., Yang, Y, B., Yan, Y, Q., Akdis, C, A., & Gao, Y, D. (2020). Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China. Allergy. 75(7): 1730-1741.
174. Jefferson, T., Spencer, E, A., Brassey, J., & Heneghan, C. (2020). Viral cultures for COVID-19 infectivity assessment – a systematic review. In: Analysis of the Transmission Dynamics of COVID-19: An Open Evidence Review. Retrieved 10th November 2020, from https://www.medrxiv.org/content/10.1101/2020.08.04.20167932v3.full.pdf
175. Schraer, R. (2020). Coronavirus: Tests 'could be picking up dead virus’. BBC News. Retrieved 10th December 2020, https://www.bbc.co.uk/news/health-54000629
176. Gniazdowski, V., Morris, C, P., Wohl, S., Mehoke, T., Ramakrishnan, S., Thielen, P., Powell, H., et al. (2020). Repeat COVID-19 Molecular Testing: Correlation with Recovery of Infectious Virus, Molecular Assay Cycle Thresholds, and Analytical Sensitivity. MedRxiv, 2020.08.05.20168963. Retrieved 9th December 2020, from https://doi.org/10.1101/2020.08.05.20168963
177. Public Health England. Understanding cycle threshold (Ct) in SARS-CoV-2 RT-PCR A guide for health protection teams. GOV.UK. Retrieved 10th November 2020, from https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/926410/Understanding_Cycle_Threshold__Ct__in_SARS-CoV-2_RT-PCR_.pdf
178. Sekine, T., Perez-Potti, A., Rivera-Ballesteros, O., Strålin, K., Gorin, J.-B., Olsson, A., Llewellyn-Lacey, S., et al. (2020). Robust T cell immunity in convalescent individuals with asymptomatic or mild COVID-19. BioRxiv, 2020.06.29.174888. https://doi.org/10.1101/2020.06.29.174888
179. Gallais, F., Velay, A., Wendling, M.-J., Nazon, C., Partisani, M., Sibilia, J., Candon, S., et al. (2020). Intrafamilial Exposure to SARS-CoV-2 Induces Cellular Immune Response without Seroconversion. MedRxiv. 2020.06.21.20132449. https://doi.org/10.1101/2020.06.21.20132449
180. Long, Q, X., Tang, X, J., Shi, Q, L., Li, Q., Deng, H, J., Yuan, J., Hu, J, L., et al. (2020). Clinical and immunological assessment of asymptomatic SARS-CoV-2 infections. Nature medicine. 26(8): 1200-1204.
181. Seow, J., Graham, C., Merrick, B., Acors, S., Steel, K, J, A., Hemmings, O., O’Bryne, A., et al. (2020). Longitudinal evaluation and decline of antibody responses in SARS-CoV-2 infection preprint. MedRxiv. 2020. Retrieved 10th December 2020, from https://www.medrxiv.org/content/10.1101/2020.07.09.20148429v1.
182. Research and analysis. COG-UK: Summary report of COVID-19 reinfection, 3 September 2020. GOV.UK Retrieved 20th November 2020, from https://www.gov.uk/government/publications/cog-uk-summary-report-of-covid-19-reinfection-3-september-2020
183. Mandavilli, A. (2020). You may have antibodies after coronavirus infection. But not for long. New York Times. Retrieved 20th August 2020, from https://www.nytimes.com/2020/06/18/health/coronavirus-antibodies.html
184. Le Bert, N., Tan, A. T., Kunasegaran, K., Tham, C., Hafezi, M., Chia, A., Chng, M., et al. (2020). SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls. Nature. 584(7821): 457-462.
185. Altmann, D, M., & Boyton, R, J. (2020). SARS-CoV-2 T cell immunity: Specificity, function, durability, and role in protection. Science Immunology. 5(49): eabd6160. Retrieved 20th November 2020, from https://doi.org/10.1126/sciimmunol.abd6160
186. A study to evaluate efficacy, safety, and immunogenicity of mRNA-1273 vaccine in adults aged 18 years and older to prevent COVID-19. Retrieved 15th December 2020, from https://clinicaltrials.gov/ct2/show/NCT04470427.
187. Study to describe the safety, tolerability, immunogenicity, and efficacy of RNA vaccine candidates against COVID-19 in healthy adults. Retrieved 15th December 2020, from https://www.clinicaltrials.gov/ct2/show/NCT04368728
188. A Phase 1/2/3, placebo-controlled, randomised, observer-blind, dose-finding study to evaluate the safety, tolerability, immunogenicity, and efficacy or SARS-CoV-2 RNA Vaccine candidates against Covid-19 in healthy individuals. PF-07302048 (BNT162 RNA-Based COVID-19 Vaccines) Protocol C4591001. pp. 28. Retrieved 9th December 2020, from https://pfe-pfizercom-d8-prod.s3.amazonaws.com/2020-11/C4591001_Clinical_Protocol_Nov2020.pdf
189. ModernaTX, Inc. 20 Aug 2020 Protocol mRNA-1273-P301, Amendment 3. Retrieved 9th November 2020, from https://www.modernatx.com/sites/default/files/mRNA-1273-P301-Protocol.pdf
190. A Randomized, Double-blind, Placebo-controlled Phase 3 Study to Assess the Efficacy and Safety of Ad26.COV2.S for the Prevention of SARS-CoV-2-mediated COVID-19 in Adults Aged 18 Years and Older. Retrieved 9th December 2020, from https://www.jnj.com/coronavirus/covid-19-phase-3-study-clinical-protocol
191. A Phase III Randomized, Double-blind, Placebo-controlled Multicenter Study in Adults to Determine the Safety, Efficacy, and Immunogenicity of AZD1222, a Non-replicating ChAdOx1 Vector Vaccine, for the Prevention of COVID-19. Retrieved 9th December 2020, from https://s3.amazonaws.com/ctr-med-7111/D8110C00001/52bec400-80f6-4c1b-8791-0483923d0867/c8070a4e-6a9d-46f9-8c32-cece903592b9/D8110C00001_CSP-v2.pdf
192. Normal Saline. Generic Name: sodium chloride injection. RXList.com. Retrieved 10th December 2020, from https://www.rxlist.com/normal-saline-side-effects-drug-center.htm
193. Bar-Or, D., Rael, L, T., & Brody, E, N. (2017). Use of Saline as a Placebo in Intra-articular Injections in Osteoarthritis: Potential Contributions to Nociceptive Pain Relief. The Open Rheumatology Journal. 11: 16-22.
194. Wu, F., Zhao, S., Yu, B., Chen, Y, M., Wang, W., Song, Z, G., Hu, Y., et al. (2020). A new coronavirus associated with human respiratory disease in China. Nature. 579(7798): 265-269.
195. Borger, P., Malhotra, B, R., Yeadon, M., Craig, C., McKernan, K., Steger, K., McSheehy, P., et al. (2020).External peer review of the RTPCR test to detect SARS-CoV-2 reveals 10 major scientific flaws at the molecular and methodological level: consequences for false positive results. Eurosurveillance. Retrieved 30th November 2020, from https://cormandrostenreview.com/report
196. TWiV 641: COVID-19 with Dr. Anthony Fauci. YouTube. Retrieved https://youtu.b/a_Vy6fgaBPE
197. Stewart, P., & Ali, I. (2020). Coronavirus clue? Most cases aboard U.S. aircraft carrier are symptom-free. Reuters. Retrieved 10th January 2020, from https://www.reuters.com/article/us-health-coronavirus-usa-military-sympt/coronavirus-clue-most-cases-aboard-us-aircraft-carrier-are-symptom-free-idUSKCN21Y2GB
198. Conis, E. (2017). Polio, DDT, and Disease Risk in the United States after World War II. Environmental History. 22(4): 696-721.
199. Polio: A 20th Century Epidemic. Science Museum. Retrieved 20th November 2020, from https://www.sciencemuseum.org.uk/objects-and-stories/medicine/polio-20th-century-epidemic
200. Alcalá H. (1993). Diagnóstico diferencial de la poliomielitis y otras parálisis flácidas agudas [The differential diagnosis of poliomyelitis and other acute flaccid paralyses]. Boletin medico del Hospital Infantil de Mexico. 50(2): 136-144.
201. James, W. (1995). Immunization The Reality Behind the Myth. Greenwood Publishing Group. pp. 36.
202. Halstead, L, S., & Silver, J, K. (2000). Nonparalytic polio and postpolio syndrome. American journal of physical medicine & rehabilitation. 79(1): 13-18.
203. Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497-506. Epub 2020/01/28. doi: 10.1016/S0140- 6736(20)30183-5.
204. Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., et al. (2020). Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 395(10223): 507-13.
205. Guan, W, J., Ni, Z, Y., Hu, Y., Liang, W,H., Ou, C, Q., He, J, X., et al. (2020. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. Epub 2020/02/29. doi: 10.1056/NEJMoa2002032. PubMed PMID: 32109013.
206. Nosek, B, A., & Errington, T, M. (2020). What is replication?. PLOS Biology 18(3): e3000691.
207. Ioannidis, J, A. (2005). Contradicted and initially stronger effects in highly cited clinical research. JAMA. 294(2): 218-228.
208. Baker, M. (2016). 1,500 scientists lift the lid on reproducibility. Nature. 533(7604): 452-454.
209. Ioannidis, J, P, A. (2016). Why Most Clinical Research Is Not Useful. PLOS Med. 13(6): e1002049.
210. Matthews, S. (2018). Killer flu outbreak is to blame for a 42% spike in deaths in January after 64,000 people died - the highest number since records began. Daily Mail. Retrieved 20th December 2020, from https://www.dailymail.co.uk/health/article-5440785/Killer-flu-outbreak-blame-42-spike-deaths.html
211. Lourenço, J., Paton, R., Ghafari, M., Kraemer, M., Thompson, C., Simmonds, P., Klenerman, P., et al. (2020). Fundamental principles of epidemic spread highlight the immediate need for large-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic. Department of Zoology, 2 Nuffield Department of Medicine, University of Oxford, Peter Medawar Building for Pathogen Research, Oxford, United Kingdom. Retrieved 20th June 2020, from https://www.medrxiv.org/content/10.1101/2020.03.24.20042291v1.full.pdf
212. Bendavid, E., Mulaney, B., Sood, N., Shah, S., Ling, E., Bromley-Dulfano, R., Lai, C., et al. (2020). COVID-19 Antibody Seroprevalence in Santa Clara County, California. MedRxiv, 2020.04.14.20062463. Retrieved 27th August 2020, from https://doi.org/10.1101/2020.04.14.20062463
213. Falahi, S., & Kenarkoohi, A. (2020). COVID-19 reinfection: prolonged shedding or true reinfection? New Microbes and New Infections. 38: 100812. Retrieved 29th December 2020, from https://doi.org/https://doi.org/10.1016/j.nmni.2020.100812
214. Reuters. Coronavirus: Japanese woman tests positive for second time. The Guardian. Retrieved 23rd May 2020, from https://www.theguardian.com/world/2020/feb/27/japanese-woman-tests-positive-for-coronavirus-for-second-time
215. Prado-Vivar, B., Becerra-Wong, M., Guadalupe, J, J., Marquez, S., Gutierrez, B., Rojas-Silva, P., Grunauer, M., et al. (2020). COVID-19 re-infection by a phylogenetically distinct SARS-CoV-2 variant, first confirmed event in South America. SSRN. Retrieved 8th September 2020, from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3686174
216. Whipple, T. (2020). Superforecasters have bright future, predicts Dominic Cummings’ favourite academic Philip Tetlock. The Times. Retrieved 20th March 2020, from https://www.thetimes.co.uk/article/superforecasters-still-have-bright-future-predicts-academic-popular-with-cummings-ddzqsqwtc
RSS Feed