Policymaking in the shadow of the pandemic
In the first part of this essay, I placed policymaking in the context of Buddhist ethics, emphasising the need for a wise head as well as a loving heart. I also suggested that wise policymaking was tantamount to a spiritual practice for leaders of Buddhist communities, and a beneficial activity for the world. I then stated my intention to offer some principles of policymaking — a set of five in total. I proposed to discuss these principles in the context of faith communities, and illustrate them by reference to the Covid-19 pandemic.
The first part of the essay included my first and second principles. The first was ‘view the problem in the round’. Under that heading, I suggested there were five ‘lenses’ through which policymakers should view a crisis such as Covid-19. The first four are the perspectives of public health, economics, civil liberties, and social cohesion. For faith communities, there is also a fifth lens, namely the values and principles that are specific to that community.
The second principle was ‘anticipate trade-offs’. A trade-off is an exchange that entails both gains and losses, but in the context of principle 2, I used the term to refer primarily to the losses — the disadvantages that result from seeking or obtaining an advantage through the adoption of a policy. I cited the view of the economic and political thinker Thomas Sowell that ‘there are no solutions; there are only trade-offs’. I suggested that Buddhism was better aligned with Sowell’s view than with utopian philosophies that promise unmixed blessings from large-scale social interventions. With reference to the Covid pandemic, I considered the trade-offs (including ethical compromises) that would arise if a Buddhist community were to choose a policy of excluding unvaccinated members from its activities.
In this, the second part of the essay, I am going to discuss my third and fourth policymaking principles, which relate closely to each other, and form a distinct sub-set within the five. These are ‘identify and examine your assumptions’, and ‘don’t blindly follow the herd’. (The fifth and final principle — ‘Hone your truth-seeking ability’ — will be considered in the third instalment of the essay.)
Principle 3: Identify and Examine Your Assumptions
Suppose we have chosen an appropriate policy lens, and are striving to foresee and evaluate trade-offs. So far, so good. Even then, we are likely to include in our thinking certain assumptions. An ‘assumption’ is an idea that is uncritically taken to be true, but may prove false.
Caution about assumptions should come naturally to Buddhists. The Dharma teaches us that we all live under the spell of delusion (Skt. moha) or ignorance (Skt. avidyā), and it warns us against our tendency to cling to false views. Logically then, Buddhists — of all people — should need no reminder of the human bias towards ignorance and delusion, and should proceed with due caution. But how well, typically, do we keep up our guard?
Of course, it is understandable that, in matters of small or merely private concern, we don’t have time to re-examine our assumptions constantly. But the task of policymaking is neither small nor private. It has significant consequences for many others. It should call forth from us our utmost in the effort to review all relevant data, carefully teasing out what we know from what is assumed. (I will examine the difficulties of this in principle 5.)
The forms taken by false assumptions are legion: defunct theories, half-truths, ‘factoids’, fashionable manias, and hearsay. Such assumptions may spring from the grassroots of public opinion in the form of rumour and folklore. Or they may descend upon the public from above in the form of ‘authoritative’ pronouncements from governments or officially approved experts. In the case of Covid, the need for caution about assumptions issuing from the latter source was at least as great as the former, but much less recognised. In what follows, I shall therefore concentrate on those assumptions that rained down on us from above.
Some Specific Assumptions
As our first example, let’s start with the assumption that vaccines were the only way out of the crisis. This assumption was dependent upon another, namely that there were no effective treatments for Covid in the early days of the pandemic. Without the latter assumption, pharmaceutical companies could never have secured emergency-use approval for their vaccines.
Yet in the first year of the pandemic (before the vaccines were announced towards the end of 2020) claims had been made for beneficial effects of various drugs, sometimes backed by what seemed to be strong evidence from a variety of sources. One such was ivermectin. The prospect was exciting for several reasons: ivermectin had a long track record of safe use for other conditions. What was more, it was widely and cheaply available because it was out of patent. Yet the public never got to hear much of ivermectin, and what was reported was mostly negative. The assumption of ‘no effective treatments’ therefore remained current.
It is worth examining this story in a little more detail. When Covid-19 first appeared, several doctors experimented, using repurposed ivermectin as an early-stage anti-viral treatment. To check whether the treatment was effective, there were many studies. A meta-analysis that aggregated the results demonstrated a statistically significant improvement in outcomes, leading to the adoption of ivermectin for early treatment in twenty-two countries and sixteen non-government medical organizations.1This meta-analysis could have enabled policymakers (or at least, those willing to make diligent effort) to audit the assumption that there were no effective treatments for Covid.
Instead, there was an effective lobby that advocated against ivermectin. The claims of the meta-analysis were undermined by cherry-picking studies.2Also, critics alleged signs of possible bias and other weaknesses in the studies included in the meta-analysis (such as poor design or reporting of data). On this basis, health authorities in the USA, the UK and the EU withheld approval of therapeutic use of ivermectin for Covid, while giving permission for further clinical trials. At present, studies on the use of ivermectin for the treatment of Covid continue, but with a strange lack of apparent urgency. In the UK, for example, the ‘Principle Study’ at Oxford has included ivermectin in its research on possible treatments for Covid since June 2021, but has yet to report.3
Meanwhile, mainstream media coverage of ivermectin has been limited and has tended to take the form of ‘hit pieces’. For example, ivermectin has been contemptuously dismissed as a ‘horse de-wormer’,4 or its name associated with ‘right wing groups’ and ‘conspiracy theorists’. Meanwhile, doctors who spoke up for ivermectin and other treatments they had found to be effective (and who had nothing to gain personally for such advocacy) were threatened with the removal of their practice licenses.
The upshot of all this — to reiterate the point — was the assumption there were apparently no therapeutic solutions available for Covid. Thus, the way was cleared for a singular and urgent focus on vaccine development.
Apart from the assumption of ‘no effective treatments’, there were many other assumptions that have been commonly held during the pandemic, but which are also questionable in varying degrees. There is, for example, the idea that PCR mass testing reliably identifies people who are infectious. This assumption was important because it was the key to whether or not a person with no Covid symptoms, but with a positive PCR test, was required to go into isolation. Yet the reliability of a PCR test as an indication of infectiousness is uncertain because of variations in the number of amplification cycles that are used in the test.5
Two of the most important questionable assumptions about Covid-19 provide the illustrative motifs of this essay as a whole. One is the idea that the novel vaccines have been definitively proved ‘safe and effective’. The other is the idea that draconian lockdowns can eliminate Covid without imposing economic and human costs that might ultimately outweigh the benefits. I do not claim that either of these assumptions has been disproved. Yet it is now abundantly clear that both assumptions are very questionable.
With regard to lockdowns, a recent major meta-study acknowledges that purely voluntary changes in behaviour, such as social distancing, did indeed play an important part in mitigating the pandemic. But what of lockdowns per se (legally enforced measures such as the restriction of movement and the closure of businesses and schools)? According to the study, lockdowns of that sort in the spring of 2020 ‘had little to no effect on COVID-19 mortality.’6
As for the safety and effectiveness of vaccines, there is much that could be said, and here we can only take a lightning tour of some important points. First, we must note there are some novel aspects of the Covid vaccines that warranted special caution. Most notably, some vaccines used an mRNA gene therapy that instructs the recipient’s body to produce a spike protein, similar to that produced by Covid. Despite this novelty, the clinical timeframe of the vaccine trials was compressed (being far shorter than what normally would be required even for a conventional vaccine). The trial for the most widely used mRNA vaccine did not test the sample group for prior immunity to Covid. Nor did it test for virus transmission, although this claim was initially made. The vaccine was tested for reduction of symptoms, and found a positive result. But this distracted attention from an increase in all-cause injury and death within the vaccinated group, compared with the non-vaccinated control group. The section of the population most at risk from Covid (the elderly) was not included in the trial in sufficient numbers to give statistically significant results. (The contrast with ivermectin, where trials were publicly discredited for lack of statistical significance, is ironic.) The vaccine publicity referred to a relative risk reduction of 95%, but that result, whilst relevant for trials, is irrelevant to individuals making a medical choice. They need to know the absolute risk reduction, which was less than one percent – 0.84%.7
In terms of safety, the randomised controlled trial for the same vaccine was unblinded early, and the control group was given the vaccine. This means that no long-term safety data will ever be obtainable from that trial. A post-trial follow-up in September 2021 did not prove safety, but suggested harm.8 We are now at a point where we have the benefit of hindsight, and can assess the health outcomes. Data from the USA Vaccine Adverse Event Reporting System (VAERS), the UK yellow card reporting scheme, and the Office of National Statistics data on deaths (not to mention escalating medical insurance claims) have prompted many health professionals to question the ‘safe and effective’ assumption.9
For anyone lacking relevant medical or statistical expertise, the task of evaluating the mass of information and conflicting arguments about Covid-19 vaccinations is truly daunting. Nevertheless, for a policymaker contemplating a mandate for vaccination within their community, the task should not be shirked. The considerations that flow from the assumption of ‘safe and effective’ provide a near-perfect example of the gravitas of policymaking and the consequences that can flow from a faulty policy assumption.
The Biggest Assumption
Underlying all these particular assumptions, there is a deeper and more pervasive assumption affecting the responses of policymakers to the Covid pandemic. This is hard to formulate precisely, but broadly speaking, it involves the narrow identification of ‘policy’ with the interventions of an increasingly authoritarian welfare state.
In principle 2, I argued that policymakers should not assume that for every problem there will be a solution that is cost-free, or worth the price to be paid. The essence of principle 2 was to anticipate trade-offs, and choose policy options that offered the optimum balance of benefits over costs. But to speak in such terms is to leave untouched the deeper underlying assumption that I am now addressing — namely that the state holds ultimate responsibility for our health, rather than each of us individually. For those who make that assumption, the state will seem entitled — indeed, duty-bound — to make drastic interventions, including interventions that curb the freedom of individuals to decide for themselves how best to protect their own health or that of their children.
I am not saying that interventionist views of public welfare are wrong. However, such views, if held too narrowly, can lead to a dangerous disregard of other considerations. As I argued in principle 1, instead of viewing a crisis like Covid exclusively through the ‘medical’ lens of public health, we also need to view it in the round — meaning through other lenses, such as those of economics, civil liberties, social cohesion and faith.
An assumption that we might call ‘authoritarian welfarism’ has been very evident in the response of governments all around the world to the Covid-19 pandemic. ‘Policy’ has been equated with encroachments upon civil liberties that were unprecedented outside of wartime. Such encroachments included lockdowns, enforced by policing; and policies of mass vaccination, pursued aggressively by the threat of exclusion from occupations, travel, and so on.
Here I am touching — very reluctantly — on politics and ideology. I cannot avoid doing so in any adequate consideration of the current principle, which is ‘identify and examine your assumptions’. There is of course a spectrum of political views about the proper relation between the individual and the state. To risk simplifying a complicated matter, we can say that the spectrum runs from paternalism at one end to libertarianism at the other. It is not my purpose here to advocate for any particular point on the spectrum. However, I do suggest that policymakers — including those in faith groups — need at least to be aware of three things concerning the spectrum.
Firstly, they need to be aware that the spectrum exists, and that honest and well-meaning people may inhabit very different points upon it. Secondly, they should be aware that public discourse at any moment may be dominated by views emanating from one part of the spectrum, while other views may be stigmatised unfairly, and effectively excluded. In other words, policymakers should not assume that the mindset that currently prevails in our culture is the only one that is possible or legitimate. Scepticism about lockdowns for example, does not necessarily reflect a callous preference for ‘profits over people’. In faith groups, policymakers need to be on guard against any facile equation of an ideology at a certain point of the spectrum with the values and principles of their faith. For Buddhists, the desire for policy to reflect the principle of compassion does not necessarily justify authoritarian interventions in people’s lives, especially if the actual outcomes of the intervention are uncertain. The Buddhist Dhamma itself is traditionally characterised as ‘an invitation’, not a commandment.10
Thirdly, policymakers need to strive to be independent in their thinking, and not helplessly subject to whatever ideology holds sway in the mainstream of public discourse. This means attempting to understand the various bands within the spectrum of political thought — to understand the genuine concerns that animate the various positions in the spectrum, as well as the strengths and weaknesses in the ideas and arguments associated with each. In formulating policy to deal with a problem, policymakers should try to formulate their policies upon logic and upon all the relevant evidence, viewed through a range of lenses such as those outlined in principle 1. They should not simply succumb to whichever orthodoxy is in fashion.
To all this, I would add a final warning: that the tendency to intervene too officiously can be aggravated by hubris. Policymakers are people who have achieved positions of high responsibility and authority. An acute sense of that position (and of their achievement in getting there) may make them susceptible to the assumption that lesser mortals cannot be trusted to make their own decisions; that they — the anointed policymakers — have the right and duty to take such decisions on their behalf. The irony of this point will not escape my readers: that an essay on policymaking includes a health warning about policymaking and policymakers.
For Buddhists, committed to truthful and helpful speech, all of the foregoing should give added impetus to an investigation into assumptions. We have to realise that misinformation comes not only from cranks and contrarians, but also from institutions that hitherto we may have trusted implicitly. The misinformation may lie less in what is said than in what is left unsaid, or even suppressed. This is called ‘the bias of selection’. For those making policy for independent institutions, such as faith groups, the bottom line is that it is not sufficient to rely on mainstream media or official government pronouncements.
But with regard to the pandemic, many readers will protest, ‘But how can the leaders of faith groups (who typically have no expertise in any of the relevant specialisms, such as vaccinology, epidemiology or health economics) second-guess the pronouncements of public health authorities?’ I will turn to this question in my fifth principle (in the third and final part of this essay).
A policy based on false assumptions will lead to unforeseen and unintended consequences. Therefore, as policymakers, and as Buddhists committed to truthful and helpful speech, we have a duty of care to recognise our assumptions, and audit them for veracity. To quote Thomas Sowell again, ‘It takes considerable knowledge just to realise the extent of your own ignorance.’
Principle 4: Don’t Blindly Follow the Herd
The Power of the Herd
This fourth principle flows from the third. It concerns the psychological difficulties of relinquishing our assumptions. We obtain emotional comfort from thinking we know. We therefore grasp after certainty, even when it is unavailable. The Buddha, who identified views as objects of clinging, understood this two and a half millennia ago.
Why do we cling to views? One of the biggest reasons is that we are affiliative beings. By nature, we tend to follow the herd. We live in fear that the herd will turn upon us, or abandon us. That fear holds us under a spell, paralysing our power of independent thought.11 Have you ever, whilst enjoying the company of friends, been struck by an insight at odds with the mood of your companions? And in that situation, did you stifle the thought because an instinct warned you not to risk losing their esteem and goodwill? Such a suppression of independent thinking easily becomes an unconscious habit.
This doesn’t mean that our views are fixed or stable. Precisely because we take them from the herd, our views can be swayed by impulses passing through the herd, like gusts of wind passing through a cornfield. One of the great ironies of the Covid crisis is the zeal with which habitual critics of capitalism and mighty corporations have embraced the cause of mass vaccination — despite the fact it has greatly enriched the ‘big pharma’ corporations whose bloated profits they would usually condemn.
It is true that those corporations have a mixed track record, to put it mildly. Long before Covid-19, Pfizer, for example, had been forced to pay compensation for transgressions during clinical trials, and to pay fines running into billions of US dollars.12 Moreover, the agencies mandated to regulate the pharmaceutical industry are funded by the same people they police.13 Yet the failures of policy making in the context of Covid cannot be blamed exclusively on greedy capitalists. That would be to oversimplify the problem. The truth is more complex, involving failings of both private and public sector institutions, together with a cultural mindset that encompasses both — the ‘authoritarian welfarism’ that I touched on under Principle 3.
There may have been a halcyon time when, in some matters at least, we could unthinkingly but safely defer to an expert authority — a time when we could safely follow the bellwethers of the herd. But if so, those days have passed. To grasp this, we must take note of two phenomena, referred to respectively as ‘regulatory capture’ and ‘the replication crisis’.
Public authorities are supposed to protect us from exploitation by commercial interests, but it has been clear for several decades that such authorities may fall under the control of the very industries they are meant to regulate. This phenomenon is now well known under the name of ‘regulatory capture’. The pharmaceutical business is merely one of many in which it goes on.
Governments establish regulatory bodies to ensure that an industry serves the public interest. However, the relationship between the regulators and the industry is often ambivalent — partly adversarial, but simultaneously a partnership. The public interest requires the existence of a profitable industry — for example, a pharmaceutical industry with the economic and technical firepower to generate rapid fixes for a crisis such as Covid. The regulators therefore cannot regulate too severely for fear of killing the goose, or at least stemming the flow of golden eggs. The industry, for its part, needs the public health bureaucracy (including the regulatory body) to commission and validate its products. The two sides can become further entwined through the exchange of personnel — the famous ‘revolving door’ phenomenon (the industry, for instance, may recruit insiders with a background in regulation to help them negotiate the regulatory labyrinth). In such ways, the partnership aspect of the relationship may come to predominate, and even develop into collusion. At its worst, this can amount to ‘crony capitalism’.
The phenomenon of regulatory capture was originally understood in material terms as a product of the greed of capitalists — a case of corporate moguls simply bribing their bureaucratic warders. But some analysts now argue that ‘non-material’ capture (or ‘cultural capture’), which may occur in parallel with material capture, is also important. Cultural capture is the process by which regulators may come to feel part of the same ‘in group’ as the industry’s elite. This has been observed, for example, in the relations between financial institutions and their regulators in the period leading up to the financial crisis of 2008. In the absence of bribery or improper incentives, why did financial regulators fail to stop, or even to foresee the catastrophe? It has been explained in terms of the self-esteem and prestige that regulators obtained from the industry. Overawed by the power and status of the industrial elite — so the argument goes — the regulators felt flattered to gain entry to the same social set. Consequently, they came to share the industry’s self-satisfied view of itself.14 Could something similar have happened in the case of the pharmaceutical industry and its regulators?
But the full truth of cultural capture seems to be even subtler than this. I’ve already suggested that the industry and the bodies that serve the public interest need each other. They are constantly interacting with each other, and even exchanging personnel. They all conceive of themselves as essential to the public good. The net result is not a one-way process whereby one entity (the industry) captures others (the regulatory body, the public health bureaucracy, and the government department) in its own selfish interest. Rather, all the entities have been captured by a common mindset. They have sincerely come to believe that they collectively, and only they, can ‘deliver’ health to the public (as if health were intrinsically a commodity or a service that the corporate state provides to us all). In this way, a herd mentality may be born among bodies that outwardly appear to be distinct from, and even at odds with, one another. That mentality may be hardened by the hubris that I mentioned under principle 3.
The combined power of material and cultural capture is awesome. It spreads to encompass the academic world and prestigious scientific journals, which rely for their funding on the industry or the bureaucracy or both. Anybody who tries to step outside the herd — anybody who has a different philosophy of public health, or a dissident view on whether a particular treatment is efficacious or safe — will soon find their reputations and their livelihoods under attack. That is authoritarian welfarism in action.
The Replication Crisis
Regulatory capture is not the sole reason for caution about the claims made by scientific or medical authorities. The last decade has seen the dawning recognition of a ‘replication crisis’ in the sciences, including pharmacology. An alarmingly high percentage of often-cited research findings have proved impossible to reproduce. Subsequent studies may contradict the earlier results, or find a significantly weaker effect than first claimed. A wonder drug may turn out to be far less wonderful than thought. For some findings, no attempt at replication is made at all. In short, it is becoming clear that what ‘scientists say’ may sometimes turn out to be less true than we were told. It might even be plain wrong.15
Again, this should not really surprise us if we contemplate the vested interests at stake. Pharmaceutical firms need to come up with a steady flow of new products that can be patented and taken to market. Academic researchers need to get results that help them scale the career ladder, or secure funding streams, or just allow them to keep their jobs. Health services are under pressure to meet patients’ demands for something — whether a jab, a pill or an operation — that will fix their suffering (or at least promises to do so).
To take a single specific example of the replication crisis, we might step aside from Covid for a moment and consider the case of antidepressants, which apparently are taken by as many as one in six adults in England during a typical year, and therefore represent a slice of the NHS prescription budget that isn’t negligible. The most common types of antidepressants — known as SSRIs — are supposed to work by boosting levels of a neurotransmitter called serotonin. This has been a standard theory, taught in medical training for decades. Yet as I write this, a new study from University College, London, based upon a ‘comprehensive review’ of the literature, finds that ‘there is no convincing evidence that depression is caused by serotonin abnormalities, particularly by low levels or reduced activity of serotonin.’ The UCL study only reinforced conclusions reached more than a decade earlier by Robert Whitaker in his book Anatomy of an Epidemic. Nevertheless, prescriptions for SSRIs still continue to grow.
Nor is the problem confined to the researchers. The typical family doctor who urges a treatment upon patients (such as a Covid-19 vaccination) often lacks the specialist knowledge required to make an independent judgement of the efficacy or safety of that treatment. With their noses to the grindstone of general practice, such doctors may be only faintly aware, if at all, of such problems as regulatory capture and the replication crisis. To complicate matters further, the curriculum that GPs follow at medical school generally does not include statistics, so they may even fail to grasp the difference (for instance) between relative and absolute risk reduction from a vaccine. As a result, your doctor might — with the best intentions in the world — seriously overstate the benefit of a procedure or treatment, and seriously understate its risks.16
What does all this mean for policymakers in faith groups? For them — as indeed for the public in general — the lesson to be learned is clear, though not reassuring or comforting. It is that there are rational grounds for a measure of healthy scepticism about the claims issuing from authorities. And by ‘authorities’, I mean not only pharmaceutical companies. The policy choices of public health authorities and the deliverances of science must also be viewed critically. This must be the greatest challenge that policymakers face at the present moment. Clearly, we can’t just disregard science in policymaking. Nevertheless, caution must be applied even to the findings of university professors, and the contents of learned scientific journals. How can we know when to apply a dose of scepticism to our assumptions, or how to optimise that dose? The task is huge, but bear with me: I will offer some guidelines in my fifth principle.
To encourage healthy scepticism is not the same as promoting a conspiracy theory. Scepticism need not entail paranoia or extreme cynicism about the motivations of powerful individuals or groups. I don’t doubt that dirty deals often happen, but the fundamental problem is more diffuse and less conscious than that. We are dealing with a herd, albeit one full of very clever beasts. Vaccine makers, for example, may have a just sense of the historical importance and achievements of their industry, so they are naturally inclined to see convergences between their profits and the public good. Elected governments are anxious to be re-elected, and consequently persuade themselves that their duty is to appease the electorate’s present panic rather than meticulously calculate its long-term welfare. Government medical advisers fear bearing responsibility for a public health disaster, so they may recommend policies based on worst-case scenarios, neglecting to weigh the true balance of probabilities.17 All three of them — the vaccine makers, the ministers and the officials — may quietly take solace in the thought that any harmful effects of their policies will be scattered far and wide across an indefinite future — hard to discern and harder to prove. In doing so, they do not have to conspire with one another or even admit to themselves what is guiding their thinking. The essence of the problem is groupthink — the triumph of a herd mentality.
All of this is in keeping with what psychologists tell us about the way human reason works. We don’t look dispassionately at the evidence and then make up our minds what to believe. Rather, we first prefer to believe something, often driven by emotions, and then look for evidence to support our belief. What is more, we do not automatically become exempt from this human weakness just through being highly intelligent, educated and qualified.
Buddhism versus Groupthink
Not only psychology, but also Buddhism can illuminate this territory with its insights into the mind and our tendency to grasp at views. Our views mediate our experience, even modifying our perceptions. This is why I often compare views to spells: they grip our mind, keeping us blind to reality. They can be difficult to recognise and even more difficult to renounce.
Buddhist practice can help us to break these spells: it shows us how to purify the mind so that reality can shine through, unobscured by the poisons of greed, hatred and delusion. It can help us to cease blindly following the herd — not in order to feel superior to it, or resentful of it. Rather, to help the herd towards safer grazing, or perhaps to save it from stampeding over the edge of a cliff.
But we must understand that Buddhist practice consists in something more than the cultivation of kindly intentions. If we want to play a role in policymaking, we must recognise that a good heart is not enough. In Part Three of this essay, I will outline my final principle, which will include some concrete suggestions as to how policymakers can free themselves of groupthink.
With the completion of this, the second part of the essay, we have so far explored four principles for wise policy making. To recapitulate, these are:
- View the problem in the round
- Anticipate trade-offs
- Identify and examine your assumptions
- Do not blindly follow the herd
In the third and final part of this essay, I will suggest a fifth principle: ‘hone your truth-seeking ability’.
- A summary of the meta-study can be found at https://c19ivermectin.com. The compiled results make for compelling reading. Studies are usefully separated into (a) prophylaxis, (b) early-stage treatment, (c) late-stage treatment. The efficacy for those treatment regimes, averaged over the studies, is 83%, 62% and 39% (average of means). We should be guided by the totality of study results available, thereby avoiding the accidental or deliberate cherry-picking of data or trials. For early-stage treatment, many of the studies are not statistically significant, but the ten that are all show efficacy. (Also, many studies which are not individually significant gain statistical significance when appropriately aggregated because almost all show efficacy.)
- One clinical trial that was used to undermine the results of the meta-study was the Lim et al. trial. This was a late-stage trial, with a mortality efficacy in line with other trial results. A comprehensive statistical analysis is contained here: https://c19ivermectin.com/lim.html. It showed a reduction of mortality of 69% for those treated with ivermectin but this was only mentioned in the footnotes, which described a control group mortality rate more than three times greater as ‘similar’. A Bayesian analysis (which is appropriate for these results) at Probability, Risk and Statistics | Norman Fenton refers to a 97% probability that ivermectin reduces mortality. Whilst the results were not statistically significant, it would only have taken 13% more participants or a two-week extension for the result to become significant. The 69% reduction in deaths is consistent with other trials. This is a non-trivial result which would equate to c. 4 million lives saved if this protocol had been adopted at the start of the pandemic
- The PRINCIPLE Trial – two years on — Nuffield Department of Primary Care Health Sciences, University of Oxford
- Ivermectin is an antiparasitic drug that has been in use since the 1970s. While used to treat a wide range of conditions in various animals, it has also long been used for humans. In 1987, the World Health Organisation promoted the use of ivermectin for onchocerciasis (‘river blindness’ – a disease that is estimated to affect 15.5 million people) and it remains the standard treatment. It is also used to treat a variety of other parasitic conditions in humans. It is absurd to suggest that William Campbell and Satoshi Omura (the discoverers of ivermectin) were awarded the 2015 Nobel Prize in Physiology or Medicine merely for the discovery of a ‘horse de-wormer’. The Nobel citation specifically referred to the drug’s uses in River Blindness and Lymphatic Filariasis. Of the two discoverers (together with another scientist, cited for her work on malaria) the citation concludes with these words: “The global impact of their discoveries and the resulting benefit to mankind are immeasurable.” (See citation at http://www.nobelprize.org/nobel_prizes/medicine/laureates/2015/press.pdf). What then of ivermectin’s potential as an antiviral drug? Over the few years preceding the appearance of Covid-19, there was evidence from in vitro studies of antiviral properties in ivermectin (see Discovery of berberine, abamectin and ivermectin as antivirals against chikungunya and other alphaviruses – ScienceDirect). Thus, the possibility of its relevance to Covid was not prima facie absurd. It is true that, with most doctors in the West either prohibited or discouraged from prescribing ivermectin, rumour has led some anxious Covid sufferers to self-medicate using ivermectin preparations designed for animals, and without a proper understanding of dosage. Unsurprisingly, this has led to incidents of harm, which have been reported as though such incidents altogether discredited ivermectin as a potential treatment.
- In order to detect the presence of Covid-19, the PCR test ‘amplifies’ the DNA or RNA of the virus by making it copy itself through repeated cycles. If the virus becomes detectable after only a small number of amplification cycles, that points to a high viral load in the sample, and hence a higher probability of current infectiousness. Conversely, if numerous cycles are required to make the virus detectable, that indicates a low viral load, and lower probability of infectiousness. The number of amplification cycles is known as the Cycle Threshold (Ct). A January 2021 study published in Nature compared how well RNA detected by PCR tests matched evidence of the presence of infectious virus obtained by other means. It found that ‘Detection of the subgenomic RNAs outlasted the detection of infectious virus, and predicted poorly if virus cultures were positive (positive predictive value of 37.5%).’ In other words, positive PCR tests, if they are obtained on the basis of a high Ct, might be detecting non-viable fragments of virus perhaps lingering from an earlier infection, meaning that the source of the sample was no longer infectious. (Duration and key determinants of infectious virus shedding in hospitalized patients with coronavirus disease-2019 (COVID-19) | Nature Communications). Dr Carl Heneghan, Director of the Centre for Evidence-Based Medicine at Oxford, has commented: “In the UK, by design, we carry out a large amount of asymptomatic testing, but we rarely, if ever, report on an individual’s Ct numbers of these tests. If we look at these findings in the context of reducing the amount of testing done in the UK, for example, it could be that by reporting people’s Ct numbers, we could better determine if someone should isolate or not. This would have multiple positive effects on both people, such as saving them the worry of being notified they may have been in contact with someone infected, and society, by stopping people needlessly having to isolate and all the problems this causes people and communities as they go about their daily lives.” (see: PCR cycle threshold may be key to predicting infectiousness of people with asymptomatic and pre-symptomatic COVID-19, suggests new review. — Nuffield Department of Primary Care Health Sciences, University of Oxford)
- Herby, Jonas and Jonung, Lars and Hanke, Steve, A Literature Review and Meta-Analysis of the Effects of Lockdowns on Covid-19 Mortality – II, Cepos, Copenhagen, Dept of Economics, Lund University, Johns Hopkins Institute for Applied Economics, May 2022. Available online at A Literature Review and Meta-Analysis of the Effects of Lockdowns on Covid-19 Mortality – II Munich Personal RePEc Archive (uni-muenchen.de). Advance reports (during the spring of 2022) of the findings before the publication of the study were met with a storm of criticism in the media, which the authors patiently deal with in the final, published version (dated May 2022).
- See https://rumble.com/vobcg5-relative-vs-absolute-risk-reduction.html and the next note for information on absolute risk reduction and relative risk reduction.
- A 2021 report by Canadian Covid Care Alliance gives the Pfizer clinical trial data, together with an explanation on how to read trial data: https://www.canadiancovidcarealliance.org/wp-content/uploads/2021/12/The-COVID-19-Inoculations-More-Harm-Than-Good-REV-Dec-16-2021.pdf
- The original vaccine trial data are now in the public domain, and the health protection and injury results of the vaccines are now auditable. Therefore, with the wisdom of hindsight, a reassessment is possible. A 15-minute overview interview between Mark Steyn and Dr Aseem Malhotra (broadcast by the UK media channel GB news) contains a number of references, including references to BMJ papers. Dr Malhotra also touches on how many of those who promote the vaccine, including regulatory authorities and many medics, do not critically appraise the data. Regulatory capture and excess death figures are discussed. https://youtu.be/DWaYdDKKTXc
- According to a canonical formula in Pali, the Tiratana Vandana, the Dhamma is ehipassiko. Literally, the Dhamma invites us to ‘come and see’ for ourselves, not to compel us or scare us.
- Dr Matthias Desmet offers a perspective on this, describing a phenomenon he calls ‘mass (crowd) formation’. Taking vaccine policy as a case study, he talks about it in an interview with Dan Astin-Gregory September 2021: https://youtu.be/uLDpZ8daIVM.
- In 2009, in the largest health care fraud settlement in history, pharmaceutical giant Pfizer paid $2.3 billion to resolve criminal and civil allegations that the company illegally promoted uses of four of its drugs, including the painkiller Bextra, the U.S. Department of Justice advised. https://abcnews.go.com/Business/pfizer-fined-23-billion-illegal-marketing-off-label/story?id=8477617
- For evidence of the conflicts of interest, read this peer-reviewed British Medical Journal paper – https://www.bmj.com/content/376/bmj.o702 or listen to this thorough commentary on the paper by John Campbell: The illusion of evidence based medicine – YouTube. For an overview of the conflicts of interest at work read https://www.ukcolumn.org/article/Covid–19-big-pharma-players-behind-uk-government-lockdown
- See, for example, the discussion at The Lobbyists and the Regulators Were Really, Socially and Culturally, the Same People | Oxford Law Faculty
- A seminal study in the medical field can be viewed at Contradicted and Initially Stronger Effects in Highly Cited Clinical Research | Research, Methods, Statistics | JAMA | JAMA Network
- For a succinct introduction to these problems, see the talk by Dr Aseem Malhotra at Aseem Malhotra: Evidence-Based Medicine Has Been Hijacked – YouTube – also 8.07minutes onwards for education of doctors and RRR versus ARR
- In December of 2021, the journalist Fraser Nelson of The Spectator reported an online conversation with Graham Medley, Professor at LSHTM and Chairman of the modelling committee of SAGE (the body responsible for giving the UK government scientific advice relating to public emergencies). The focus of the conversation was the number of deaths per day to be expected from the Omicron variant. Professor Medley appeared to confirm that he and his committee focused on worst-case scenarios. This was partly because that was what they were asked to do (‘We generally model what we are asked to model.’) But it was also partly because of an assumption that policymaking as an activity is all about responding to worst-case scenarios (‘Decision makers are generally only interested in situations where decisions have to be made.’) In other words, outcomes that are possible, but require little or no change in policy, need not be included in the range that scientific modellers present to policymakers. The folly of this should be obvious: a decision not to impose a lockdown, for example, is no less a decision than its opposite. Yet it is easy to see how such thinking could take hold and become routine in the machinery of government. It reflects the view that ‘policy’ equates with intervention and compulsion. See the report at My Twitter conversation with the chairman of the Sage Covid modelling committee | The Spectator