A Pandemic? What Pandemic?

Written by Dr Urmie Ray on December 1, 2020. Posted in Current News

1 “Whats in a Name?” The unprecedented measures imposed on world populations were justified by the supposed spread of a pandemic. Hence, to begin with, it is necessary to have a precise idea of the meaning of this term to be able to assess whether there has been a pandemic or not. To paraphrase Shakespeare, “Whats in a name?

That which we call a pandemic. By any other name would be as devastating.” Well its not that simple, names are important because they are charged with connotations, and hence potent with consequences. In the case of a pandemic, a fundamental point is that it is variously defined.

According to the 2001, fourth edition of the Dictionary of Epidemiology it is an “epidemic occurring worldwide, or over a very wide area, crossing international boundaries, and usually affecting a large number of people”, and an epidemic as the “occurrence in a community or region of cases of an

illness, specific health-related behavior, or other health-related events clearly in excess of normal expectancy”.[1]

In 2003, the notion of immunity was added by the World Health Organization: “An influenza pandemic occurs when a new influenza virus appears against which the human population has no immunity, resulting in several simultaneous epidemics worldwide with enormous numbers of deaths and illness.”[2]

On 6 May 2009[3] the WHO altered its definition to: “A disease epidemic occurs when there are more cases of that disease than normal. A pandemic is a worldwide epidemic of a disease. An influenza pandemic may occur when a new influenza virus appears against which the human population has no immunity.”[4]

This description no longer conjures up nightmarish visions of soaring numbers of victims. In contrast, popular conceptions continue to invoke “danger to the public and a very large number of victims”.[5]

Besides discrepancies between definitions, each of them involves serious issues. Science is a question of comparison with respect to some external reference. Absolute concepts like hot or cold are utterly subjective and unscientific. What is scientific are the relative concepts of hotter and colder. Now, there cannot be an objective reference with respect to which a disease can be said to amount to an epidemic or a pandemic. These terms are absolute concepts, involving in the 2003 WHO definition the absolute unscientific concept of “enormous numbers”.  Disconnected strings of numbers may feed number mysticism, but are worthless scientifically.  Thus there can only be a legal subjective definition.  That is precisely the case in many countries.  In 1996, it was argued in the House of Lords that “Administrative definitions can be set for different diseases in which an arbitrary threshold is selected above which the term ‘epidemic’ is applied.”[6] Since then many national health authorities, including the American and French ones, have chosen an “arbitrary threshold” in the case of influenza. Although until 2020 it only applied to influenza, it opened the door to its extension to other diseases.

Issues do not stop there. Definitions of a pandemic and of an epidemic are too imprecise, making even their legal definition problematic. First, both the epidemiological and 2009 WHO definitions involve the term “normal”. What is “normal”? What happens every year? Given, there can be noticeable differences between years, does this refer to an average? If so, over how many years? Or does this refer to some median number of cases?  Once again how many years should be considered? Besides what does it mean regarding a new disease? When exactly can we talk of “clear excess”?

Moreover, there is no obvious criteria on which to found the definitions. The behaviour of a disease has at least two different components. The speed of its spread if it is contagious and its severity. Speed is related to the number of cases of the disease as well as to their distribution. Entire populations

and all geographical areas may be equally affected or mainly some specific subgroups and areas. As for severity, it depends not only on the number of cases, but also on the number of deaths.

But how severe should a disease be and how fast should it spread to be considered an epidemic or a pandemic?  There can be and there is no consensus on this question,  adding to the subjectivity of any definition.  The epidemiological and the 2009 WHO definitions totally discount severity.  So does the British administrative definition of an influenza epidemic.[7]     In contrast, the former 2003 WHO definition does involve severity, and so does implicitly the popular vision of a pandemic,  but imprecisely.    In contrast, it is better accounted for in the American government definition of an epidemic of influenza, where the death rate is paid attention to, and there is an attempt to define the threshold reasonably.  Still arbitrariness cannot be eliminated.[8]  As for speed it is not explicitly included in any definition.   At the very least, given that many cases may remain too mild to be noticeable, only a study over several years may begin to give some minimally reliable indication. Time is also required to gauge immunity and its extent.

Now, before anything else, a specific disease has to be identified.  More precisely a set of similarities must be found between suspected cases, as well as differences from other known health issues. Only once the occurrence of a specific disease has been confirmed can the question of its evolution begin

to be discussed. Then its causes have to be assessed, notably whether it is contagious or the consequence of environmental and living conditions. Apart from adding to the time required to reach reasonable conclusions, this means its behaviour may vary from year to year, and from place to place, further jeopardizing any definition of a pandemic.

All this certainly makes any “expectancy” more a matter of prescience than of science, especially in case of a pandemic. In fact, the latter concept, contrary to that of an epidemic, is recent. Although it can be traced back to the cholera outbreak of 1831-1832 that spread from Asia to Europe, and especially the 1889 influenza outbreak, it was very loosely used through the twentieth century and even as late as the 1990s was not included in epidemiological reference works.[9] It may suit the philosophy of standardization of a globalized world symbolized by the WHO, but is more a question of policies than of anything else.

2 A Logically Flawed Approach

This leaves us in a state of confusion. When should the emergence of a disease raise alarm? Why was alarmed raised in 2020?

According to the WHO, on 31 December 2019, “the WHO China Country Office was informed of cases of pneumonia of unknown etiology (unknown cause) detected in Wuhan”.[10] In other words, we were not faced with a new disease, but its cause was purported to be new.

Indeed, based on the observation of 44 patients in Wuhan, of which 11 were in a severe condition, and 33 stable, the “clinical signs and symptoms”[11] – the only possible indications of a new disease – can all be attributed to pneumonia or to a number of lung conditions, or even to influenza. Indeed these are mainly “fever, with a few patients having difficulty in breathing”,[12] even the later added symptom of loss of smell can be due to sinus infections, common colds, smoking, flu, allergies and other chronic conditions.[13] Many seem convinced they have experienced a loss of smell this winter and thus

were infected by Covid. Did they in the past ever focus on this particular symptom, or did the current insistence on it make them suddenly focus on it?

So from the beginning, as the WHO statement implies, the identification of the disease has been equivalent to the identification of its causes, which is logically questionable on more than one count. To begin with, if there are no distinguishable symptoms from other known diseases, then why search for novel causes? This question is all the more relevant because:

1) Community-acquired pneumonia, i.e. developed outside the hospital,

is one of the most common infections and a leading cause of death worldwide, the mortality rate of those hospitalized being on the whole above 20%, whereas the death rate among the 41 of the 44 patients hospitalized was only 15%.[14]

2) Pneumonia has long been the commonest infective reason for ICU (intensive care unit) admission, as well as the commonest secondary infection acquired in ICU. In particular this implies that the state of a patient with pneumonia symptoms admitted to ICU may worsen.

3) At the time and throughout the winter, Chronic Obstructive Pulmonary Disease (COPD), remained the third mortality rate in China.[15]

4) Pneumonia can be caused by a variety of factors: inhalation or ingestion of poisons and toxins, in the form of liquids, gases, small particles, such as dust or fumes,[16] and like COPD by air pollution, especially prolonged exposure, and hence predisposing the elderly. The level of “PM2.5 (particles less than 2.5 micrometers in diameter) that can penetrate deeply into the lung, irritate and corrode the alveolar wall, and consequently impair lung function”[17] was excessively high in Wuhan in December 2019, varying between 140 and 250 μg/m3, beyond 162 for most of the month, and beyond 150 for most of January 2020.[18] At these high levels, it is considered to result in: “Significant aggravation of heart or lung disease and premature mortality in persons with cardiopulmonary disease and the elderly; significant increase in respiratory effects in general population”, a safe level being estimated to be less than 12.[19] Besides, in January 2020 it was “observed by randomly taking one day as a sample … that the area with the highest level of air pollution in Wuhan was Huanan Wholesale Seafood Market”,[20] where three of the seven patients admitted to the Hubei Provincial Hospital in December were from.[21] In comparison, PM2.5 levels in Beijing for the period remained on the whole far below 100.[22]

Note that two other later locations thought to be clusters, Northern Italy and Iran, also suffer from high levels of air pollution. In 2018, “in 55 provincial capitals” in Italy, especially in the north, “the daily limits set for fine particles or ozone were exceeded.”[23] In January 2020, the level of fine particles in Milano was more than 125 for 20 days, of which for 14 days it was more than 150 and even reached 202 for one day.[24] As for Iran, its population density is like in China one of the highest, and air quality in Tehran as bad as in Wuhan, but while it is improving in China, it is declining in Iran, due in particular to diesel vehicles, resulting in soaring pollution levels in winter time.

5) In 2019,Wuhan was covered by 5G electromagnetic frequencies (EMFs): 1580 bases were activated by mid-October. Manmade EMFs differ from natural ones,[25] the reason for their adverse biological effects on living organisms, in particular humans, as is known since 2015.[26] Regarding 5G in particular, the European EMF guideline 2016 recognizes that it can cause fatigue and flu-like symptoms.[27] Indeed, it uses higher frequency radio waves than has been the case so far for cellular networks. Mid-band 5G uses microwaves of 2.5-3.7 GHz and high-band 5G uses frequencies of 25–39 GHz.

Once again of note: The 5G network was activated in Milano and 28 surrounding localities in June 2019.

So what led Dr Zhang Jixian, the first doctor to consider the emergence of a new disease,[28] to think that the causes of cases displaying the usualsymptoms of pneumonia were unknown? What led her to order CT Scans of an elderly couple who came to the hospital with fever and cough?  According to the Mayo Clinic, blood tests and xrays are among the usual tools used to diagnose pneumonia, a CT scan may be recommended only if it persists longer than “expected”.[29] Several articles imply that she was worried both husband and wife showed the same symptoms. Is it so unusual for two people, especially elderly people, who have shared the same roof for decades in such a polluted city? Did she overreact because of her “experience during the 2003 SARS outbreak”[30]and of her conviction this had amounted to a highly contagious disease due to viruses jumping species barriers, a thesis highly popularized for a number of years? We will return to the validity of her convictions later.

The chest scans appear to have confirmed her suspicions and to have convinced her superiors. They show “invasive lesions of both lungs”,[31] but the ground glass opacities seen are not markers of any specific disease or pathogenic agent. They are non-specific findings “with a wide aetiology [cause] including infection, chronic interstitial disease and acute alveolar disease.”[32] Yet, not all known “bacterial and viral pathogens that cause pneumonia” were ruled out, only “common” ones.[33] As for interstitial diseases, which cover some 100 lung disorders, or acute alveolar diseases, which include pulmonary edema, they were not ruled out. In fact, later autopsies conducted in other parts of the world imply that death is largely due to “Disseminated Intravascular Coagulation or Pulmonary Thrombosis”.[34] [35]

2.1 Is the existence of Sars-Cov-2 scientifically corroborated?

Hence the question that arises is: why was the viral thesis retained and why were lower respiratory tract samples collected for virus sequencing?  The scans did not point towards anything unprecedented, and the environmental conditions were especially congenial for pneumonia among patients with comorbidities – 13 of the 41 patients admitted to hospital in Wuhan by 2 January 2020 had other “underlying diseases”[36] – as well as among the healthy population.

It is claimed that these samples revealed the presence of a new virus, since then known as Sars-Cov-2. For such a claim, the virus needs to be observed under the electron microscope given its tiny dimensions. For this it first needs to be isolated from tissue samples or body fluid, in the case at hand lung fluid, and this in every patient suspected of suffering of the disease, identified through its clinical symptoms. However there was no such identification, and hence the cases selected would have to be random pneumonia ones.

In fact, the claim is based on samples from only four patients.[37] However no generalization can be made on such scarce data. Any investigation of our sense-perceptible world to be at all credible must be based on reproducible and multiply reproduced observation. To use a simple example: from the observation of four black swans, it cannot be concluded that all swans are black. The larger and more varied the data, the lesser the likelihood of mistaken conclusions. If nothing else, no amount of precaution can eliminate errors. They creep in at every step of the process used of “next-generation sequencing [NGS]”,[38] notably handling and storage.[39] The sequencing was done in one of the more than forty-six Life Sciences start ups in Wuhan, the Guangzhou Weiyuan Gene Technology Co., Ltd., founded in 2018, which is heavily invested in by Volcanics Venture, a venture capital firm founded in 2016. Indeed, gene sequencing is now big business, whose aim is profit. Whether this is compatible with a proper scientific approach may well be asked.

The isolation has to be done without the addition of anything that could adulterate the process. However not only in early Chinese ones, but in all studies so far, enzymes have been added, and then DNA oligonucleotides (PCR probes) to amplify various segments. The resulting fluid, whether purified or not, has been mixed with commercially prepared mammelian non-host cells, notably Vero cell, i.e. monkey kidney cells.[40] [41]  Mamellian cells produce exosomes, i.e. particles secreted by our own cells, which help us heal from diseases. The particles were then observed under the electron microscope. Even by purifying the fluid, it would then be impossible to tell if they originated from the lung fluid or to differentiate them from exosomes, which resemble viral particles.

Moreover, PCR is not appropriate to determine a virus for it aims “to concentrate a single DNA locus in the presence of millions of similar but different DNA loci”. It does so by “selectively multiplying and mass-producing specific DNA [the molecule that carries genetic information, which is composed of long sequences made of short bases, small sections of which are genes] segments”. However these segments may not be complete, nor are they usually genes (of which humans are said to have 20,000 to 25,000).  In spite of this, it is suggested that ‘pasted together’ they would depict the whole genetic material of a given virus.” But, what is true for past research, remains true in the present case: there is no “paper that shows an electron micrograph of this so-called reproduced virus.” In effect, the virus needs to be beforehand precisely determined through “direct observation” to be able to estimate whether or not the segment is from the virus.[42]

Hence so far, no virus has been isolated, only bits of genetic material have been obtained, neither in the early studies conducted in China,[43] [44]   nor in a later one[45] whose press release[46] claims to have isolated the full genome of the virus. In fact, in the actual published paper, it acknowledges that it could not eliminate some known pathogens: it “remains unclear whether these pathogens have a role as causative factors or cofactors in SARS.” It even warns that “One should bear in mind, however, that in the past, viruses have been initially isolated from patients with a specific disease but subsequent investigations revealed no actual association at all. Thus, larger studies with appropriate control groups are needed to verify or eliminate our hypothesis about the cause of SARS.”[47]

Without isolating the virus, namely without determining that which is thought to be the cause of a disease, it cannot be shown to be in any way associated with the disease, let alone cause the disease. To prove causality, according to the Koch postulates or to their revised version given by Rivers in 1937 in the case of a virus,[48] the virus needs to be further grown either in a pure culture or at least in host cells. However, as stated above, all mixtures were adulterated and non-host cells were used. It has to then be shown to produce the same disease in a healthy organism. This process too has its own issues as it is conducted through inoculation. Regarding respiratory diseases, assuming they are contagious, the natural way of transmission is through close contact, not inoculation. In fact no systematic inoculation of healthy individuals has been conducted, and the rest of the Koch or Rivers postulates have not been verified to hold.  For similar reasons, even in the case of Sars-Cov-1, to this date, the viral thesis remains unconfirmed, despite what is claimed in some articles,[49] and thus any fears among Wuhan doctors was misplaced.

Note that according to a WHO statement of 5 January 2020, there was “no evidence of significant human to human transmission and no health care worker infections report”.[50] In other words, this contradicts the thesis of an alarmingly contagious virus.

2.2 PCR tests

Yet, by 1 January 2020, Professor Christian Drosten from the Charité hospital in Germany had begun to work towards a “diagnostic flow”[51] and the first version of his paper on the subject was released on 13 January.[52]   It is only on January 11-12 that “the Chinese authorities shared” what they claimed is “the full sequence of the coronavirus genome, as detected in [the four] samples taken from the first patients”.[53] This was the first scientific claim of any similarity with any former Sars virus. Thus his work entirely “relied on social media reports announcing detection of a SARS-like virus,”[54] not on any scientific data regarding any eventual virus.

Now, a paper written by Chinese scientists first published on January 23, clearly states that the “genome sequences obtained from five patients” are not identical, but merely “almost identical to each other and share 79.5% sequence identify to SARS-CoV.”[55] Given that we are in effect only talking of segments and have no idea of what they are segments of, neither the former Sars virus nor the new one having been observed, the estimation of 79.5% should be taken with prudence. Moreover it is only based on very few samples. It should be noted that using partly the same PCR methods, humans are claimed to share 90% of their DNA with cats and 96% with chimpanzees. Hence, even assuming all estimations of similarities are satisfactory, transferring information from the former Sars virus to the present one is a highly faulty method. It is not even possible to gauge the errors involved given none of the viruses have been identified.

PCR methods and tests are anyhow inconclusive since they consist in identifying only small fragments, but the Drosten test is particularly problematic as we have even less idea what it reveals.

Yet on January 21, the WHO recommended what he claimed to be a “genetic detection procedure with which he can reliably detect the presence of the new corona virus in humans … as a reliable test method”[56] and all tests are since based on it.

Even were a virus identified through an independent reliable method, RT-PCR tests do not detect any onslaught of diseases. According to Kary Mullis, the inventor of the PCR test, it can lead “you to find almost anything in anybody … for if you are going to amplify one single molecule up to something you can really measure, which PCR can do then, there is just very few molecules that you don’t have one single one of them in your body.  So that can be thought as a misuse to claim that it is meaningful.”[57]

Indeed, the very large majority of positive cases show no symptoms. Were a disease caused by a virus, the viral load needs to be high. Estimating the viral load is complicated. This is done using the reverse transcription real-time quantitative PCR (RT-qPCR), of which RT-PCR is only a first step. RT-qPCR requires dyeing, a process during which “particles bec[o]me totally deformed, so that they appear[] as particles with long tails. They [a]re full-blown artificial products of the laboratory, and they still look[] exactly like so many other non-viral cellular components. This, logically, ma[kes] it impossible to determine if a virus or a non-viral particle ha[s] been found.”[58] Therefore this can contribute to false positives, a problem which already pervades the simpler RT-PCR.[59] Moreover, “elementary protocol errors, inappropriate data analysis and inadequate reporting continue to be rife … [So] a majority of published RT-qPCR data are likely to represent technical noise. Confidence in quantitative measurements depends on a number of parameters, one of which is reproducibility.” However, “experimental test results can vary widely, even when performed by the same individual at the same time”.[60]

As for antibody tests, they meet with a similar issue: without identifying the virus, what the tests are reacting to cannot be ascertained.

Thus the diagnosis of the supposed disease named Covid is now based on an inappropriate test. This was for instance the case regarding the cruise ship Diamond Princess in February with 3711 people on board: 696, i.e. 18.75%, were said to have tested positive, and thus have the virus.[61] However, apart from the issue of false positive, illnesses on ships are common. In 2017, on the Sea Bird Lindblad, according to the CDC, 16.09% were afflicted by a virus.[62] As for the 18 deaths of Diamond Princess passengers they occurred after hospitalization and hence could well be due to wrong treatment due to an erroneous assessment of an identified disease from an unadapted test, as well as other issues connected to hospitalization: pneumonia as was stated has a high rate of fatality in ICUs.

As an aside, claims that the unidentified Sars-Cov-2 originates in bats are based on the inference that “96% identical [is] at the whole genome level to a bat coronavirus”.[63] For reasons stated above, it would be imprudent from this near but not total similarity to conclude that it has jumped any species barriers.

3 Numerical data

In effect alarm was raised based on a negligible number of cases in Wuhan, which led to a unscientifically uncorroborated viral thesis.

Even within the framework of this thesis, Covid was at best ranked the 49th cause of death there,[64] its contribution to mortality remaining negligible. In France[65] and England+Wales,[66] from January to end of March, the number of overall deaths remained lower than in 2019, a mild year for winter diseases.  In Italy, it was assumed that there were some 150 cases in some small towns in Lombardy by 23 February, of which on February 20 only 3 were estimated to be severe.[67] In comparison:

1) In 2004-2005, the incidence of influenza alone reached 12 per 1000, namely some 109,884 cases.[68]

2) In 2018, there was an unexplained increase in the number of pneumonia cases in September in a large area of the region, with some 500 patients with lower respiratory tract infection having accessed the Emergency Departments of local hospitals (by September 24). Five deaths were reported.[69]

Yet a lockdown was imposed on 8 December 2019 in Wuhan with only some 540 cases and 17 deaths alleged to be from Covid, on the 3 March in Lombardy, on the 17 March in France, and on the 23rd in the UK. A similar pattern can be seen in numerous countries.

In effect, there was no quantitative reason to impose any measures. This raises the issue of the critical discrepancy between the accepted official definition and mundane ones regarding the number of victims. Instead of explaining to populations that the concept of a pandemic no longer involves large numbers, fear has been instilled through the corporate media, governments and health authorities by preposterous daily announcements of ‘large’ numbers of supposed cases and fatalities.Why this duplicity? Is it because populations would not have accepted such draconian measures otherwise?

3.1 The Spread of the disease: the reproduction number

Attention was taken away from these negligible numbers and lockdowns and other measures were justified by estimations of the reproduction number, which is supposed to indicate the potential of a disease to spread.  This major tool in epidemiology cannot be evaluated through direct counting. It is a probabilistic and statistical abstract concept, whose estimation must perforce be based on mathematical models, “few of which agree with each other”.[70]  This is because mathematised theories are especially approximative. They discount most facets of a phenomena as these are not quantifiable. Besides, they can only address identical objects, eliminating individual features, for they set aside all that differentiates and only retains some common properties. Thus, the more complexity is involved, the less a mathematical description is appropriate.

This process of standardisation is epitomised in the field of statistics which studies large aggregates whose elements cannot be individually scrutinised.  Statistical methods consist in averaging out. Averages do not exist in reality.  As decried by the father of physiology, Claude Bernard: “all the biological characteristics of the phenomenon disappear in the average”.[71] Statistics magnifies the issues inherent to mathematical applications.  Not only does a statistical approach assume that dissimilarities between the component parts of the phenomena under study can be ignored, but the models used follow from essentially subjective criteria.  The population studied statistically has to be divided into non-overlapping groups according to selected traits, in other words, into strata, but there may be more than one reasonable way of determining strata boundaries and the number of relevant traits may be intractable.  Moreover, to properly choose the sample size for each stratum, its percentage within the population needs to be known. Then, the sample needs to be chosen randomly within each strata – a random choice is in practice not at all obvious.[72]

Even where mathematical methods are more appropriate, approximations cannot be avoided. A hypothesis has to be initially expressed in mundane language. The translation process into mathematical symbolism carries with it much loss of information. The equations we get describe idealised interactions, not real ones. Among quantifiable features, a choice has to be made. Mathematics can only deal with a very limited number of parameters, and only a very simplified version of their relations. Besides, there is a whole set of scientific questions that are in principle computable, but in practice cannot be computed because the time taken, the resources needed, and so on, are too extensive. In short, mathematical assumptions, namely the selection of parameters and relations they satisfy, tend to be made for the sake of mathematical convenience, not for any justified scientific reason. Although equations do in theory have exact solutions, except in the simplest cases, contrived methods only give us approximate ones. This is usually the case for differential equations, namely equations indicating the evolution of a system over time or space and thus on which predictions are based. A whole series of approximations again occurs when retranslating our mathematical representation into mundane language, notably as they are likely to involve non-exact numbers such as π. In this retranslation, as in the context of quantum mechanics, another problem might arise, that of interpretation since the same set of mathematics can generate diverging scientific explanations; or to put it more mathematically, there many not be a one-to-one correspondence between the mathematical part of a theory and its scientific interpretation.

In short, the perfect accuracy inherent in mathematical formalism allows us greater control on some quantifiable features, but, precisely because of this accuracy, it is a far cry from reality. “As far as the propositions of mathematics refer to reality they are”, to quote Albert Einstein, “uncertain; and as far as they are certain, they do not refer to reality,”[73] all the more so as they are inferred from knowledge which, as remarked by his colleague Max Born, is necessarily both “limited and approximate”.[74]

Probability introduces a whole new set of issues. It can be interpreted in three ways. The most common one assumes that all single outcomes are equally likely. In some situations, a frequency interpretation is more adequate or the only possible, as in Mendelian genetics. However, this too is problematic and rests on assumptions. Trials cannot be infinitely repeated. Hence it is assumed that were they repeated over and over again, the relative frequency would be reaching a definite value. More precisely, for each sample size q, our measures give a frequency ratio x/q, where x is the number of times the desired property occurs. The probability will be the limiting value these ratios reach as q keeps increasing. Now, there are two ways of proceeding. We can proceed scientifically and infer the limiting value based on a large number of such ratios obtained experimentally. But then, we end up with the same problem as in all science, induction. The other way is to find the limit mathematically. Associated to each sample sizes q1 < q2 < …. < qn, there is a ratio. Let us call these x1/q1, …, xn/qn.  It is then a matter of finding the best suited real function f representing this correspondence, namely associating a real value f(q) to all real numbers q, such that for each i, f(qi) = xi/qi – a perforce approximative process.  However, nothing guarantees that the limit of the function f as q approaches infinity estimated mathematically will be the same as the limit reached by the former scientific method.  Since both methods involve uncertainties, we have a priori no way of knowing which result is more appropriate. This incompatibility, Maynard Keynes showed, can generate even greater issues.[75]

The probabilities in the context of events repeatable as many times as desired raise so many questions, assigning probabilities to events that occur only a few times can be expected to be even more problematic. The frequency interpretation is unsuited for this. So is the equal likelihood assumption since we cannot know that such phenomena display any regularity. In this case a probability value is subjectively assigned by the investigator depending on his personal assessment of an event in the future. Until the event actually happens, there is no way of checking the quality of the assessment. After the event has happened, it has become fully certain, and this is no indication of the correctness of the probability assigned to it prior to its occurrence.  Hence these assessments do not belong to the realm of science, but provide them with the veneer of scientific ‘respectability’ and apparent objectivity.

The basic reproduction number R0 involves all these issues. Based on multiple complex interdependent factors – “biological, sociobehavioral, and environmental”[76] –, it raises the spectre of unpredictability, likely a far greater issue in biology and sociology than in the physics of the inanimate world, as well as the inevitability of innumerable unverified and unwarranted assumptions and thus of subjectivity. Regarding viral diseases, it not only assumes that the disease is contagious, but that microbes can affect us all equally since it is “the number of secondary cases which one case would produce in a completely susceptible population”.[77] It leaves aside the role of individual susceptibility and in the case of Covid, local environmental and cultural factors on immunity. Besides, any empirical data it is founded on is necessarily limited.  Since a study based on data that is not reproducible at will runs the risk of not being scientific, to be convincing, the data would have to be accumulated over a period of several years, to notably be compared with data obtained over a sufficiently long period for other diseases.

Consequently, estimations can vary according to the methods applied as in the case of malaria, where, keeping all parameters constant, a slight change in one of them may alter the value of R0[78] – unsurprising since linearizing equations amounts to increasing unrealism, while non-linear expressions are greatly sensitive to input values.[79]

Regarding Covid, the concept of R0 is particularly flawed since the existence of such a contagious pathogen has not yet been scientifically corroborated. Apart from being founded on biological studies themselves ridden with assumptions and making claims that are far from evidenced, the mathematical models rely on scarce data. Even when internally coherent, these models can in no way be affirmed to correspond to any form of reality, all the more so as they are highly reliant on computer simulations since the latter are critically dependent on input conditions. Hence, no wonder its estimation has varied widely.  Yet unprecedented “[p]olicy decisions are being based upon the concept, with limited understanding of the complexity and errors that exist in the very structure of the concept”.[80]

3.2 Measures causing excess mortality

The use of an inappropriate mathematical tool contributed to raise fears of exponential growth of infections among populations. Preliminary estimations of R0 based on the Wuhan scenario was thought to range between 2.24 and 3.58 by some and between 1.4 and 2.5 by the WHO[81] and the infection fatality ratio was estimated to be 4.06.[82]

However, some 5 million people escaped Wuhan just before the lockdown.[83] More than 30%,[84] i.e. more than 1.5 million are considered to have left the province. Yet no other province imposed lockdowns, and supposed Covid deaths were negligible even at the height of the crisis. This belies the thesis of an epidemic with “enormous numbers” of deaths.  The case fatality rate in Wuhan was re-estimated in February to be only 0.04%.[85]

In fact, not only in China, but nowhere has any spectacular growth of overall mortality occurred, but contrary to what is affirmed, this is not thanks to the measures, but any excess mortality and rise in cases of a variety of diseases are a direct consequence of the measures. The numbers rose following the imposition of measures, especially lockdowns, and of the panic created.

All this is reflected in the following tables (overall mortality for the various years is given per 100 000 inhabitants). In particular, the figures for 2020 show that the more severe the measures, the greater the excess of deaths. Still the increase in both Sweden and France between 2018 and 2020 is negligible both for the first 6 months (Table 1), and the first 4 months (Table 2 and 2’).  Consequently, an increase for 2020 is notably the consequence of an inability of the care and medical infrastructure to cope – especially the former in Sweden – which does not date from 2020, as well as possible other social factors such as an aging population, within which deaths that would naturally have occurred during the winter, were spread over time due to its mildness.  Such a conclusion is supported by the figures for France which reveal a much more significant increase of deaths between 2018 and 2017.

Table 1: Mortality Jan-June

Table 2: Mortality Jan-April

Table 2’: Mortality Jan-April

Let us look at the UK data more closely. Between January and August, 52,327 death certificates mentioned Covid. Of these, 19,459 also mentioned pneumonia and influenza. Yet only 14013 deaths have been officially attributed to the latter two,[98] compared to the 26,398 of a mild year such as 2019 or 29519 of 2018.

Given that the symptoms attributed to Covid are similar, and that such a drop would be surprising, deaths alleged to be due to Covid appear to be over-estimated. Indeed, like in many other countries, a mention of Covid in a death certificate in no way means the person had been tested positive, or if they had, the tests do not indicate that Covid was the actual cause of death.  It only means that Covid may be involved.  Moreover, “U.S. Centers for Disease Control and Prevention Director Robert Redfield agreed that some hospitals have a monetary incentive to overcount coronavirus deaths as they do deaths for other diseases.”[99] In fact, in November, the CDC admitted that “COVID-19 was the only cause mentioned” for only “6% of the deaths”.[100] Already in March, the National Institute of Health of Italy had re-evaluated that “only 12 per cent of death certificates have shown a direct causality from coronavirus.”[101]

Hence it is reasonable to apply the conservative Italian estimate. We then get that between week 1 and 24 there were 316812 overall deaths, of which only 5787 are officially attributable to Covid,[102] while in 2018 there were 275643 deaths in the same period. This not only accounts for the missing deaths from flu and pneumonia, but it shows that the main part of the excess of deaths from 2018, namely 35301, are not due to Covid. As for the 5787 excess deaths, they are largely accounted for by the excess deaths in care homes. Indeed 33.9% of deaths for that period, i.e. 93475, occurred in care homes, while in 2016, only 21.8% did.[103]

Besides, even without taking account of any re-evaluation of mortality figures, global deaths between 1 January and 31 August amount to 40 million.  Of these deaths officially attributed to Covid represent less than 1%,[104] while an estimated 31% die of cardiovascular diseases each year according to the WHO.[105]

Given that no new viral disease has been identified and that therefore the tests do not indicate its presence, the mortality figures suggest the likelihood of a lethal contagious disease is low even though in principle at some future date a virus may be identified. Pathologists in Europe found from autopsies that “there is no one who has died from the coronavirus”,[106] or rather whatever is alleged to be the coronavirus.

What about non-lethal cases? In China, hospitals were only overwhelmed in Wuhan. Any spread is posterior to 5 January for until this date there was no noticeable contagion.[107] This altogether points to dire hygienic conditions in its makeshift hospitals as a major contributing factor – no washroom, no

toilets, innumerable patients all piled in the same enclosure, some sleeping on the floor, no medication or doctors available.[108] Bacterial infections are more than likely to worsen patients already in a poor state.

Like in most of China beyond Hubei, on the whole, UK hospitals have according to a consultant remained “pretty much empty” from March to June, 95% down from other years.[109] This was also the case of a major hospital in a main city of France, according to one of its senior doctors.[110] In New York, a Hospital, “which is said to be the epicenter of the coronavirus pandemic in NYC, look[ed] quiet” in March.[111] This is not to say that in some regions of the world, hospitals were not overwhelmed. However in view of the fact this was not a generalized phenomena, this is not the consequence of a pandemic, but of human decisions:

1) The diagnosis of Covid being based on an inappropriate test is, as already stated, very likely to have led to wrong diagnosis, and thus medical errors in the treatment of patients with other issues, creating a vicious circle: people who would usually recover from pneumonia or other respiratory diseases in their own homes were hospitalized.  This together with the mounting panic are likely to have further contributed to wrong treatments, and hence deaths. Alongside, crowding already weakened patients in a confined space known to be congenial for many bacterial infections cannot be said to be innocuous. Notably, toilets in Wuhan hospitals may have been dire, but those in European ones as experienced by the author can also be worrisome.

2) Cuts both in personnel and beds have already led to far worse crisis situation. Hospital bed occupancy data shows that in “2018/19, overnight general and acute bed occupancy averaged 90.2 per cent, and regularly exceeded 95 per cent in winter” in the UK.[112] “This exceeded the 85% bed occupancy level which is recommended to maintain patient safety standards”.[113] Similarly, in the winter of 2018, hospitals in many parts of the US were stretched, “thin”,[114] so were many emergency services across France in March of that year,[115] and in Milan, intensive care collapsed, and many operations were postponed.[116]

3) Care homes and hospitals have become even more understaffed as many have resigned out of fear, while foreign staff, which make up a large part of the contingent, have often returned to their respective countries.  The inhumanity with which prospective patients have been treated is unbelievable: no visits, no human touch even from personnel too afraid to approach them without masks or even without hazmat suits, making impossible unspoken communication – which most of our human communication consists of –,  the total failure of any religious organization to provide solace when people most need it, or simply the fear generated.   The system of care having fully collapsed because of the panic artificially created, even within the community, too many needing medical attention, in particular those with pre-existing conditions, have been left unattended by carers[117] and doctors.[118] In Sweden, where no panic was generated, “hospitals have not been overwhelmed.”[119]

Hence there was no exponential growth of severe cases. This too is not due to the measures, for otherwise there would have been far more deaths.

4 In Conclusion

1) To isolate a virus, namely to associate a virus to a disease, it has to be found in every case of the disease. This is clearly stated in Koch’s and Rivers’ first postulate. This logically requires a means of identifying the cases independent from that of searching for a virus.

2) No such independent means could identify any cases of a new disease, given that the symptoms observed were those of pneumonia or flu, and the CT scans were non-specific.

3) Yet from the study of a very insignificant number of patients, a new disease was defined by its assumed viral cause using RT-PCR, a method that cannot identify new viruses.

4) The same method relying on RT-PCR was used to then test for the presence of the virus in individuals, or possibly its more complex quantitative version, of which it is a first step, and which has its own added sets of issues.  Antibody tests also suffer from the same flaw: what they are reacting to is

not known.  It could merely be exosomes or some other particles our body creates to protect itself, not viruses attacking our body.

5) No virus has therefore been identified, let alone shown to be the cause of any new disease. This would be logically impossible given the the identification of a new disease has been assimilated to the search for its viral cause using inappropriate methods. In particular, no contagiousness has yet been evidenced.

6) Given the multitude of viruses in any given individual, the term “case” and “infection” are being assimilated, which is all the more questionable as the virus in question has not yet been identified.

7) So has there been a pandemic or not?  According to the numerical data, there has been no significant excess overall deaths, except possibly as a consequence of the measures and local environmental conditions.  This implies there has in particular been no excess deaths due to pneumonia from unknown causes, nor of any new disease.  The data also shows there has been no excess severe cases either.  Hence there certainly has not been any pandemic in the popular sense of the term.

Given severity is not included in the epidemiological and 2009 WHO definitions, there could have been a pandemic according to these, but then it has remained totally mild and undetectable.  As to whether eventual diseases with only mild cases should give rise to much ado may well be asked.  But in the case that concerns us, this question is premature since occurrence, the extent of its spread, its cause, none of these are yet known.  Indeed, because of the disease’s logically flawed definition from a viral cause, it is not possible to assess its existence, all the more so as no virus has yet been identified.  The latter issue also makes it impossible to yet address immunity to, at the cost of repetition, an unidentified disease.   In short, even a totally mild pandemic conforming to these two definitions has not been evidenced so far.

[1]https://pestcontrol.ru/assets/files/biblioteka/file/19-john_m_last-a_dictionary_of_epidemiology_4th_edition-oxford_university_press_usa_2000.pdf

[2]https://web.archive.org/web/20030202145905/http://www.who.int/csr/disease/influenza/pandemic/en/

[3]https://web.archive.org/web/20090504005605/http://www.who.int/csr/disease/influenza/pandemic/en/

[4]https://web.archive.org/web/20090507005246/http://www.who.int/csr/disease/influenza/pandemic/en/

[5]https://www.ima.org.il/FilesUploadPublic/IMAJ/0/55/27606.pdf

[6]Ibid.

[7]Ibid.

[8]Ibid.

[9]https://academic.oup.com/jid/article/200/7/1018/903237

[10]https://www.who.int/csr/don/05-january-2020-pneumonia-of-unkown-cause-china/en/

[11]Ibid.

[12]https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30183-5/fulltext

[13]https://www.healthline.com/health/anosmia#causes

[14]Ibid.

[15]https://www.brookings.edu/blog/future-development/2020/03/23/a-mortality-perspective-on-covid-19-time-location-and-age/

[16]https://www.webmd.com/lung/chemical-pneumonia

[17]  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4740125/

[18]https://aqicn.org/city/wuhan/

[19]https://blissair.com/what-is-pm-2-5.htm

[20]https://www.khmertimeskh.com/688880/polluted-air-could-be-an-important-cause-of-wuhan-pneumonia/

[21]https://www.mdpi.com/1660-4601/17/9/3279/htm

[22]https://aqicn.org/city/beijing/

[23]https://www.legambiente.it/malaria-2019-il-rapporto-annuale-annuale-sullinquinamento-atmosferico-nelle-citta-italiane/

[24]https://aqicn.org/city/italy/lombardia/milano-senato/

[25]https://ecfsapi.fcc.gov/file/107282190822431/Panagopoulos-Man-Made%20EMR%20is%20Not%20Quantized-Nova%202018-chapter.pdf

[26]https://www.nature.com/articles/srep14914

[27]https://ecfsapi.fcc.gov/file/10910251701394/EUROPAEM%20EMF%20Guideline%202016%20for%20the%20prevention%20and%20treatment%20of%20EMF-related%20health%20problems.pdf

[28]http://jnm.snmjournals.org/content/61/6/782.full.pdf+html

[29]https://www.mayoclinic.org/diseases-conditions/pneumonia/diagnosis-treatment/drc-20354210

[30]http://jnm.snmjournals.org/content/61/6/782.full.pdf+html

[31]https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30183-5/fulltext

[32]https://radiopaedia.org/articles/ground-glass-opacification-3?lang=gb

[33]https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30183-5/fulltext

[34]https://www.drrobertyoung.com/post/autopsies-prove-death-by-disseminated-intravascular-coagulation-or-pulmonary-thrombosis

[35]Confirmed independently by private email by a Dutch epidemiologist and specialist of lung diseases

[36]https://www.who.int/csr/don/05-january-2020-pneumonia-of-unkown-cause-china/en/

[37]https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30183-5/fulltext

[38]Ibid.

[39]https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1659-6

[40]https://www.nejm.org/doi/full/10.1056/nejmoa030747

[41]https://www.who.int/docs/default-source/coronaviruse/real-time-rt-pcr-assays-for-the-detection-of-sars-cov-2-institut-pasteur-paris.pdf?sfvrsn=3662fcb6_2

[42]Engelbrecht, T. and K\”ohnlein, C. 2007. {\it Virus Mania}. Translated by Megan Chapelas, Danielle Egan.   Victoria, Ca.: Trafford

[43]https://www.nejm.org/doi/full/10.1056/nejmoa2001017

[44]https://www.biorxiv.org/content/10.1101/2020.01.22.914952v1

[45]https://www.nejm.org/doi/full/10.1056/nejmoa030747

[46]https://www.pasteur.fr/en/press-area/press-documents/institut-pasteur-sequences-whole-genome-coronavirus-2019-ncov

[47]https://www.nejm.org/doi/full/10.1056/nejmoa030747

[48]https://www.ncbi.nlm.nih.gov/pmc/articles/PMC545348/

[49]https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7095368/

[50]https://www.who.int/csr/don/05-january-2020-pneumonia-of-unkown-cause-china/en/

[51]https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6988269/

[52]https://www.who.int/docs/default-source/coronaviruse/protocol-v2-1.pdf

[53]https://www.pasteur.fr/en/press-area/press-documents/institut-pasteur-sequences-whole-genome-coronavirus-2019-ncov

[54]https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6988269/

[55]https://www.biorxiv.org/content/10.1101/2020.01.22.914952v2

[56]https://winteroakpress.files.wordpress.com/2020/07/the-scientific-fraud-by-prof.-christian-drosten-10.7.20.pages_.pdf

[57]https://www.youtube.com/watch?v=Xc0Kysti6Kc

[58]Engelbrecht, T. and K\”ohnlein, C. 2007. {\it Virus Mania}. Translated by Megan Chapelas, Danielle Egan.   Victoria, Ca.: Trafford

[59]https://principia-scientific.com/covid-tests-scientifically-fraudulent-epidemic-of-false-positives/

[60]https://pubmed.ncbi.nlm.nih.gov/28796277/

[61]https://en.wikipedia.org/wiki/COVID-19_pandemic_on_Diamond_Princess#Number_of_confirmed_cases

[62]http://www.cruisejunkie.com/outbreaks2017.html

[63]https://www.biorxiv.org/content/10.1101/2020.01.22.914952v2

[64]  https://www.brookings.edu/blog/future-development/2020/03/23/a-mortality-perspective-on-covid-19-time-location-and-age/

[65]http://www.francesoir.fr/societe-sante/le-nombre-cumule-des-deces-fin-mars-2020-est-toujours-inferieur-aux-annees-anterieures

[66]https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/monthlyfiguresondeathsregisteredbyareaofusualresidence

[67]https://www.axios.com/italy-coronavirus-timeline-lockdown-deaths-cases-2adb0fc7-6ab5-4b7c-9a55-bc6897494dc6.html

[68]https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4514189/

[69]https://hygimia69.blogspot.com/2018/09/pneumonia-cluster-in-lombardy-italy.html

[70]https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3157160/

[71]Bernard, C. (1865). An Introduction to the Study of Experimental Medicine.

Translated by Henry Copley Greene. United States: Henry Schuman. 1949. p. 134.

[72]Ray, U. De la Democratie et de la survie de l’Homme.  Paris: Archives Contemporaines. 2014. p. 121

[73]Einstein, A. [1921] 1960. “Geometry and experience: Lecture before the Prussian Academy of Sciences on 27 January 1921”. Translated and revised by Sonja Bargmann. In Ideas and Opinions, 232–245. New York: Crown Publishers. p. 233

[74] Born, M. 1965. “In memory of Einstein”. In Born, M. 1970. Physics in my generation.

London: The English Universities Press; Springer Verlag. p. 163.

[75] Keynes, J. M. 1921. A treatise on probability. London: Macmillan. chapter 8, p. 102–122

[76]https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3157160/

[77]https://journals.sagepub.com/doi/abs/10.1177/096228029300200103

[78]https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3157160/

[79]Ray, T. and Ray, U. 2020. On Science: Concepts, Cultures, and Limits.  London: Routledge.  2020.

[80]https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3157160/

[81]https://reader.elsevier.com/reader/sd/pii/S1201971220300539?token=16EE8C6CCEDF3789CD5739A5BB7926C26228D767FD8B58BBE254D7C560EA9125026DE25F44460C75B88312DCA9E0E923

[82]https://www.medrxiv.org/content/10.1101/2020.02.12.20022434v3

[83]https://www.express.co.uk/news/world/1233967/Coronavirus-warning-China-Wuhan-lockdown-lunar-year-Zhou-Xianwang-virus-symptoms-latest

[84]https://apnews.com/article/c42eabe1b1e1ba9fcb2ce201cd3abb72

[85]https://www.medrxiv.org/content/10.1101/2020.02.12.20022434v3

[86]http://www.francesoir.fr/societe-sante/le-nombre-cumule-des-deces-fin-mars-2020-est-toujours-inferieur-aux-annees-anterieures

[87]https://www.insee.fr/fr/statistiques/4487861?sommaire=4487854#consulter-sommaire

[88]https://www.insee.fr/fr/statistiques/3692693

[89]https://www.insee.fr/fr/statistiques/4281618

[90]https://www.insee.fr/fr/statistiques/2554860

[91]T78MDEC, https://www.insee.fr/fr/statistiques/3596204?sommaire=3596218

[92]https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/monthlyfiguresondeathsregisteredbyareaofusualresidence

[93]https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates

[94]https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/bulletins/annualmidyearpopulationestimates/mid2016

[95]https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/bulletins/annualmidyearpopulationestimates/mid2017

[96]https://www.scb.se/en/finding-statistics/statistics-by-subject-area/population/population-composition/population-statistics/

[97]https://www.statista.com/statistics/1115707/sweden-number-of-deaths-per-week/

[98]https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/deathsduetocoronaviruscovid19comparedwithdeathsfrominfluenzaandpneumoniaenglandandwales/deathsoccurringbetween1januaryand31august2020

[99] https://www.washingtonexaminer.com/news/cdc-director-acknowledges-hospitals-have-a-monetary-incentive-to-overcount-coronavirus-deaths

[100]https://www.cdc.gov/nchs/nvss/vsrr/covid_weekly/index.htm

[101]https://www.telegraph.co.uk/global-health/science-and-disease/have-many-coronavirus-patients-died-italy/

[102] https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales

[103] https://www.gov.uk/government/publications/end-of-life-care-profiles-february-2018-update/statistical-commentary-end-of-life-care-profiles-february-2018-update

[104] https://swprs.org/studies-on-covid-19-lethality/#foobox-1/0/covid-deaths-cases-global.jpg

[105] https://www.who.int/health-topics/cardiovascular-diseases/#tab=tab_1

[106] https://off-guardian.org/alexov-webinar-transcript/

[107] https://www.who.int/csr/don/05-january-2020-pneumonia-of-unkown-cause-china/en/

[108] https://www.bitchute.com/video/OrXKHYkdgkba/

[109] https://www.thebernician.net/nhs-consultant-says-staff-are-being-silenced-over-covid-19/

[110] Private conversation

[111] https://farnesius.wordpress.com/2020/04/01/hospitals-are-not-overwhelmed-there-are-no-lines-for-testing-and-ambulances-arent-bringing-patients-in/

[112] https://www.kingsfund.org.uk/publications/nhs-hospital-bed-numbers

[113] https://www.rcseng.ac.uk/news-and-events/media-centre/press-releases/nhs-bed-occupancy-rates/

[114] https://www.statnews.com/2018/01/15/flu-hospital-pandemics/

[115] https://www.20minutes.fr/sante/2239611-20180319-hopitaux-pourquoi-services-urgences-satures-plusieurs-villes-france

[116] https://milano.corriere.it/notizie/cronaca/18_gennaio_10/milano-terapie-intensive-collasso-l-influenza-gia-48-malati-gravi-molte-operazioni-rinviate-c9dc43a6-f5d1-11e7-9b06-fe054c3be5b2.shtml

[117] https://swprs.org/covid-19-a-report-from-italy/

[118] https://britishasianews.com/death-at-home-the-unseen-toll-of-italys-coronavirus-crisis-2/

[119] https://www.nytimes.com/interactive/2020/05/15/world/europe/sweden-coronavirus-deaths.html?searchResultPosition=2/

About the author: Dr Urmie Ray read mathematics at the University of Cambridge, where she obtained her B.A. (M.A.), Mmath, and PhD. After 23 years as an academic, several articles and a book in the field of algebra, she resigned her professorship in France – the country of her childhood – to dedicate herself to her lifelong interests in current issues, notably those related to science. Her second non-mathematical book “On Science: Concepts, Cultures, and Limits” (Routledge, Dec. 2020) in particular examines why and how science has been increasingly transformed into its exact opposite, a dogma which claims to speak in its name. Dr Ray is a Senior Scientist at Principia Scientific International (PSI).

Please Donate Below To Support Our Ongoing Work To Expose The Lies About COVID19

PRINCIPIA SCIENTIFIC INTERNATIONAL, legally registered in the UK as a company incorporated for charitable purposes. Head Office: 27 Old Gloucester Street, London WC1N 3AX. 

Please DONATE TODAY To Help Our Non-Profit Mission To Defend The Scientific Method

Trackback from your site.